{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" }, "colab": { "name": "Ticket Data All Artists.ipynb", "provenance": [], "collapsed_sections": [], "include_colab_link": true } }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "view-in-github", "colab_type": "text" }, "source": [ "\"Open" ] }, { "cell_type": "markdown", "metadata": { "id": "6J38oLsfjNWg", "colab_type": "text" }, "source": [ "PART 1: READ IN AND FORMAT TICKET DATA" ] }, { "cell_type": "code", "metadata": { "id": "_tcE2RYtiaRp", "colab_type": "code", "colab": {} }, "source": [ "import pandas_profiling" ], "execution_count": 0, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "DGuvOX_piaRr", "colab_type": "code", "colab": {} }, "source": [ "import os\n", "import pandas as pd \n", "import numpy as np \n", "import matplotlib.pyplot as plt \n", "import seaborn as seabornInstance \n", "from sklearn.model_selection import train_test_split \n", "from sklearn.linear_model import LinearRegression\n", "from sklearn import metrics" ], "execution_count": 0, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "EC-qlN7FGvM0", "colab_type": "code", "outputId": "ec243c3a-7786-43ba-9bde-278e04f17ef3", "colab": { "resources": { "http://localhost:8080/nbextensions/google.colab/files.js": { "data": 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"ok": true, "headers": [ [ "content-type", "application/javascript" ] ], "status": 200, "status_text": "" } }, "base_uri": "https://localhost:8080/", "height": 37 } }, "source": [ "from google.colab import files\n", "uploaded = files.upload()" ], "execution_count": 0, "outputs": [ { "output_type": "display_data", "data": { "text/html": [ "\n", " \n", " \n", " Upload widget is only available when the cell has been executed in the\n", " current browser session. Please rerun this cell to enable.\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": { "tags": [] } } ] }, { "cell_type": "code", "metadata": { "id": "EE7dC6M2iaRs", "colab_type": "code", "colab": {} }, "source": [ "#bring in first file separately\n", "os.chdir('/Users/barr001/Downloads')\n", "first = pd.read_excel('john-mayer.xlsx')\n", "first['primary_artist_name']='John Mayer'" ], "execution_count": 0, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "vSFMwiUiiaRu", "colab_type": "code", "colab": {} }, "source": [ "#Loop for other files\n", "os.chdir('/Users/barr001/Downloads/Ticket Data')\n", "f = []\n", "for (dirpath, dirnames, filenames) in os.walk('/Users/barr001/Downloads/Ticket Data'):\n", " f.extend(filenames)\n", " break\n" ], "execution_count": 0, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "q6r_xvZgiaRw", "colab_type": "code", "outputId": "bc8abf0f-1a0d-4cdd-a6a0-3db11d81c268", "colab": {} }, "source": [ "f" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "['future.xlsx',\n", " 'justin-timberlake.xlsx',\n", " 'tony-bennett.xlsx',\n", " 'harry-styles.xlsx',\n", " 'kings-of-leon.xlsx',\n", " 'maxwell.xlsx',\n", " 'depeche-mode.xlsx',\n", " 'chris-brown.xlsx',\n", " 'bring-me-the-horizon.xlsx',\n", " 'pentatonix.xlsx',\n", " 'russ.xlsx',\n", " 'khalid.xlsx',\n", " 'modest-mouse.xlsx',\n", " 'judas-priest.xlsx',\n", " 'the-chainsmokers.xlsx',\n", " 'nicky-jam.xlsx',\n", " 'beyoncé.xlsx',\n", " 'dave-matthews-band.xlsx',\n", " 'enrique-iglesias.xlsx',\n", " 'gavin-degraw.xlsx',\n", " 'buddy-guy.xlsx',\n", " 'george-winston.xlsx',\n", " 'arcade-fire.xlsx',\n", " 'g-eazy.xlsx',\n", " 'ray-lamontagne.xlsx',\n", " 'foo-fighters.xlsx',\n", " 'billy-joel.xlsx',\n", " 'bob-dylan.xlsx',\n", " 'travis-scott.xlsx',\n", " 'quinn-xcii.xlsx',\n", " 'john-legend.xlsx',\n", " 'moon-taxi.xlsx',\n", " 'hozier.xlsx',\n", " 'leon-bridges.xlsx',\n", " 'lecrae.xlsx',\n", " 'the-script.xlsx',\n", " 'george-ezra.xlsx',\n", " 'kesha.xlsx']" ] }, "metadata": { "tags": [] }, "execution_count": 197 } ] }, { "cell_type": "code", "metadata": { "id": "FFeWzFLAiaRx", "colab_type": "code", "outputId": "17def0ef-9f35-40b9-bfa6-56828940f30c", "colab": {} }, "source": [ "ticket_data=pd.DataFrame()\n", "for i in range(0,len(f)):\n", " data = pd.read_excel(f[i])\n", " data['primary_artist_name']=str(f[i]).replace('-',' ').replace('.xlsx','').title()\n", " first = first.append(data)\n", "first.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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Start DateEnd DateNum ShowsHeadlinerSupportTickets SoldGross USDGross GateCurrencyVenue CapacityPercentage SoldTicket Price MinTicket Price MaxVenue NameVenue CityVenue StateVenue CountryPromoterprimary_artist_name
08/14/20198/15/20192John MayerNaN25235.02636712.02636712.0US DOLLAR13311.095%59.5175.0United CenterChicagoILUnited StatesNaNJohn Mayer
18/12/20198/12/20191John MayerNaN9196.0949348.0949348.0US DOLLAR9196.0100%59.5150.0Bankers Life FieldhouseIndianapolisINUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
28/11/20198/11/20191John MayerNaN13490.01490600.01490600.0US DOLLAR13490.0100%62.5153.0State Farm ArenaAtlantaGAUnited States(In-House Promotion), Live Nation, Live Nation...John Mayer
38/9/20198/9/20191John MayerNaN14570.01623735.01623735.0US DOLLAR14570.0100%59.5150.0Spectrum CenterCharlotteNCUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
48/8/20198/8/20191John MayerNaN14126.01733312.01733312.0US DOLLAR14126.0100%59.5150.0Bridgestone ArenaNashvilleTNUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
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" ], "text/plain": [ " Start Date End Date Num Shows Headliner Support Tickets Sold \\\n", "0 8/14/2019 8/15/2019 2 John Mayer NaN 25235.0 \n", "1 8/12/2019 8/12/2019 1 John Mayer NaN 9196.0 \n", "2 8/11/2019 8/11/2019 1 John Mayer NaN 13490.0 \n", "3 8/9/2019 8/9/2019 1 John Mayer NaN 14570.0 \n", "4 8/8/2019 8/8/2019 1 John Mayer NaN 14126.0 \n", "\n", " Gross USD Gross Gate Currency Venue Capacity Percentage Sold \\\n", "0 2636712.0 2636712.0 US DOLLAR 13311.0 95% \n", "1 949348.0 949348.0 US DOLLAR 9196.0 100% \n", "2 1490600.0 1490600.0 US DOLLAR 13490.0 100% \n", "3 1623735.0 1623735.0 US DOLLAR 14570.0 100% \n", "4 1733312.0 1733312.0 US DOLLAR 14126.0 100% \n", "\n", " Ticket Price Min Ticket Price Max Venue Name Venue City \\\n", "0 59.5 175.0 United Center Chicago \n", "1 59.5 150.0 Bankers Life Fieldhouse Indianapolis \n", "2 62.5 153.0 State Farm Arena Atlanta \n", "3 59.5 150.0 Spectrum Center Charlotte \n", "4 59.5 150.0 Bridgestone Arena Nashville \n", "\n", " Venue State Venue Country \\\n", "0 IL United States \n", "1 IN United States \n", "2 GA United States \n", "3 NC United States \n", "4 TN United States \n", "\n", " Promoter primary_artist_name \n", "0 NaN John Mayer \n", "1 Live Nation, Live Nation - Los Angeles John Mayer \n", "2 (In-House Promotion), Live Nation, Live Nation... John Mayer \n", "3 Live Nation, Live Nation - Los Angeles John Mayer \n", "4 Live Nation, Live Nation - Los Angeles John Mayer " ] }, "metadata": { "tags": [] }, "execution_count": 198 } ] }, { "cell_type": "code", "metadata": { "id": "WBfImtBXiaR2", "colab_type": "code", "outputId": "06cd8122-b4b2-4de3-d654-7bb658f75689", "colab": {} }, "source": [ "#Just to confirm data looks good\n", "first.head(5000)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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Start DateEnd DateNum ShowsHeadlinerSupportTickets SoldGross USDGross GateCurrencyVenue CapacityPercentage SoldTicket Price MinTicket Price MaxVenue NameVenue CityVenue StateVenue CountryPromoterprimary_artist_name
08/14/20198/15/20192John MayerNaN25235.02636712.02.636712e+06US DOLLAR13311.095%59.50175.00United CenterChicagoILUnited StatesNaNJohn Mayer
18/12/20198/12/20191John MayerNaN9196.0949348.09.493480e+05US DOLLAR9196.0100%59.50150.00Bankers Life FieldhouseIndianapolisINUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
28/11/20198/11/20191John MayerNaN13490.01490600.01.490600e+06US DOLLAR13490.0100%62.50153.00State Farm ArenaAtlantaGAUnited States(In-House Promotion), Live Nation, Live Nation...John Mayer
38/9/20198/9/20191John MayerNaN14570.01623735.01.623735e+06US DOLLAR14570.0100%59.50150.00Spectrum CenterCharlotteNCUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
48/8/20198/8/20191John MayerNaN14126.01733312.01.733312e+06US DOLLAR14126.0100%59.50150.00Bridgestone ArenaNashvilleTNUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
58/6/20198/6/20191John MayerNaN9559.0851823.08.518230e+05US DOLLAR10494.092%35.50166.00Fiserv ForumMilwaukeeWIUnited StatesFPC Live, Frank Productions Concerts, Frank Pr...John Mayer
68/5/20198/5/20191John MayerNaN12064.01207967.01.207967e+06US DOLLAR14115.086%49.50150.00Xcel Energy CenterSaint PaulMNUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
78/3/20198/3/20191John MayerNaN12557.01154123.01.154123e+06US DOLLAR12557.0100%39.50150.00Schottenstein CenterColumbusOHUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
88/2/20198/2/20191John MayerNaN11215.01214620.01.214620e+06US DOLLAR12518.090%59.50150.00Little Caesars ArenaDetroitMIUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
97/30/20197/31/20192John MayerNaN24242.02097804.02.747184e+06Canadian12121.0100%56.00171.50Scotiabank ArenaTorontoONCanadaLive Nation, Live Nation - Los AngelesJohn Mayer
107/28/20197/28/20191John MayerNaN11865.01080697.01.080697e+06US DOLLAR12571.095%39.50150.00PPG Paints ArenaPittsburghPAUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
117/25/20197/26/20192John MayerNaN35810.04601632.04.601632e+06US DOLLAR17905.0100%53.00193.00Madison Square GardenNew YorkNYUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
127/23/20197/23/20191John MayerNaN14287.01529302.01.529302e+06US DOLLAR14287.0100%49.50150.00Capital One ArenaWashingtonDCUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
137/22/20197/22/20191John MayerNaN12288.01271620.01.271620e+06US DOLLAR13767.090%49.50150.00Wells Fargo CenterPhiladelphiaPAUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
147/20/20197/20/20191John MayerNaN12139.01367805.01.367805e+06US DOLLAR12139.0100%49.50150.00Dunkin' Donuts CenterProvidenceRIUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
157/19/20197/19/20191John MayerNaN9182.0804632.08.046320e+05US DOLLAR10116.091%35.50146.00Times Union CenterAlbanyNYUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
164/10/20194/11/20192John MayerNaN16977.01768655.01.960815e+08Yen8488.0100%9500.0015000.00Nippon Budokan HallTokyoNaNJapan(In-House Promotion)John Mayer
174/8/20194/8/20191John MayerNaN7978.0941074.07.387925e+06Hong Kong7978.0100%588.001188.00Hong Kong Convention & Exhibition CentreHong KongNaNChinaLive Nation, Live Nation - Los AngelesJohn Mayer
184/5/20194/5/20191John MayerNaN10504.01750167.02.500238e+10Rupiah10504.0100%1825.004960.00Jakarta International Event & Convention CenterJakartaNaNIndonesia(In-House Promotion), Live Nation, Live Nation...John Mayer
194/3/20194/3/20191John MayerNaN10860.01537583.04.903007e+07Baht10860.0100%2000.007000.00IMPACT Exhibition And Convention CenterNonthaburiNaNThailandLive Nation, Live Nation - Los AngelesJohn Mayer
204/1/20194/1/20191John MayerNaN10240.01299916.01.762454e+06Singapore10302.0100%108.00248.00Singapore Indoor StadiumSingaporeNaNSingaporeLive Nation, Live Nation - Los AngelesJohn Mayer
213/29/20193/29/20191John MayerNaN15037.01672081.02.347374e+06Australian15037.0100%47.75487.65Qudos Bank ArenaSydneyNaNAustralia(In-House Promotion), Live Nation, Live Nation...John Mayer
223/27/20193/27/20191John MayerNaN13074.01467114.02.059627e+06Australian13074.0100%50.75488.20Rod Laver ArenaMelbourneNaNAustralia(In-House Promotion), Live Nation, Live Nation...John Mayer
233/25/20193/25/20191John MayerNaN8252.0908004.01.274713e+06Australian8252.0100%87.95487.65Brisbane Entertainment CentreBoondallNaNAustralia(In-House Promotion), Live Nation, Live Nation...John Mayer
243/23/20193/23/20191John MayerNaN8875.0997015.01.460207e+06New Zealand8875.0100%101.75502.75Spark ArenaAucklandNaNNew ZealandLive Nation, Live Nation - Los AngelesJohn Mayer
2512/30/201812/30/20181\"Controlled Danger\"Dave Chappelle, John Mayer9418.01027865.01.027865e+06US DOLLAR9671.098%45.00269.50MGM Grand Garden ArenaLas VegasNVUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
269/22/2018NaN1\"Bourbon & Beyond\"Brian Setzer's Rockabilly Riot!, David Byrne, ...NaNNaNNaNNaNNaN0%NaNNaNChampions ParkLouisvilleKYUnited StatesNaNJohn Mayer
274/30/20184/30/20181\"Controlled Danger\"John Mayer2639.0329875.03.298750e+05US DOLLAR2639.0100%49.50275.00The MasonicSan FranciscoCAUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
284/29/20184/29/20181\"Controlled Danger\"John Mayer1401.0140100.01.401000e+05US DOLLAR1401.0100%49.50275.00The FillmoreSan FranciscoCAUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
291/11/20181/11/20181John MayerNaN2813.0234160.02.341600e+05US DOLLAR3435.082%75.0085.00The MasonicSan FranciscoCAUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
............................................................
32311/23/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNNew AgeTrevisoNaNItalyNaNBring Me The Horizon
32411/22/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNKofmehl HalleSolothurnNaNSwitzerlandNaNBring Me The Horizon
32511/21/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNLes DocksLausanneNaNSwitzerlandNaNBring Me The Horizon
32611/19/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNSantana 27BilbaoNaNSpainNaNBring Me The Horizon
32711/18/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNSala ArenaMadridNaNSpainNaNBring Me The Horizon
32811/17/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNBikiniBarcelonaNaNSpainNaNBring Me The Horizon
32911/16/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNLe Rocher De PalmerCenonNaNFranceNaNBring Me The Horizon
33011/15/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNLe BataclanParisNaNFranceNaNBring Me The Horizon
33111/13/201311/13/20131Bring Me The HorizonPierce The Veil, Sights & Sounds1900.057143.04.180000e+04Euro1900.010022.0025.00Ancienne BelgiqueBrusselsNaNBelgium(In-House Promotion)Bring Me The Horizon
33211/12/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaN013TilburgNaNNetherlandsNaNBring Me The Horizon
33311/11/201311/11/20131Bring Me The HorizonPierce The Veil1500.051264.03.750000e+04Euro1500.010025.000.00LKA LonghornStuttgartNaNGermanyMarek Lieberberg KonzertagenturBring Me The Horizon
33411/10/201311/10/20131Bring Me The HorizonPierce The Veil1830.062946.04.604500e+04Euro2000.09225.000.00SchlachthofWiesbadenNaNGermanyMarek Lieberberg KonzertagenturBring Me The Horizon
33511/9/201311/9/20131Bring Me The HorizonPierce The Veil2000.068353.05.000000e+04Euro2000.010025.000.00E-WerkCologneNaNGermanyMarek Lieberberg KonzertagenturBring Me The Horizon
33611/7/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNO2 Academy BrixtonLondonNaNUnited KingdomNaNBring Me The Horizon
33711/6/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNO2 Academy BrixtonLondonNaNUnited KingdomNaNBring Me The Horizon
33811/5/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNManchester AcademyManchesterNaNUnited KingdomNaNBring Me The Horizon
33911/4/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNManchester AcademyManchesterNaNUnited KingdomNaNBring Me The Horizon
34011/2/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNO2 Academy BirminghamBirminghamNaNUnited KingdomNaNBring Me The Horizon
34111/1/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNO2 Academy BirminghamBirminghamNaNUnited KingdomNaNBring Me The Horizon
34210/31/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNO2 Academy NewcastleNewcastleNaNUnited KingdomNaNBring Me The Horizon
34310/30/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNO2 Academy GlasgowGlasgowNaNUnited KingdomNaNBring Me The Horizon
34410/19/2013NaN1\"Loud Park Festival\"Angra, Behemoth, Bring Me The Horizon, Carcass...NaNNaNNaNNaNNaN0NaNNaNSaitama Super ArenaSaitamaNaNJapanNaNBring Me The Horizon
34510/17/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNKL LiveKuala LumpurNaNMalaysiaNaNBring Me The Horizon
34610/16/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNThe Coliseum, Hard Rock HotelSingaporeNaNSingaporeNaNBring Me The Horizon
34710/14/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNHard Rock Cafe BaliBaliNaNIndonesiaNaNBring Me The Horizon
34810/12/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNHBF StadiumMt. ClaremontNaNAustraliaNaNBring Me The Horizon
34910/10/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNThebarton TheatreAdelaideNaNAustraliaNaNBring Me The Horizon
35010/9/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNFestival HallWest MelbourneNaNAustraliaNaNBring Me The Horizon
35110/6/201310/6/20131Bring Me The HorizonCrossfaith, Of Mice & Men5180.0345191.03.704640e+05Australian5493.09576.200.00Hordern PavilionMoore ParkNaNAustraliaSoundwaveBring Me The Horizon
35210/5/2013NaN1Bring Me The HorizonNaNNaNNaNNaNNaNNaN0NaNNaNThe MarqueeSydneyNaNAustraliaNaNBring Me The Horizon
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5000 rows × 19 columns

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" ], "text/plain": [ " Start Date End Date Num Shows Headliner \\\n", "0 8/14/2019 8/15/2019 2 John Mayer \n", "1 8/12/2019 8/12/2019 1 John Mayer \n", "2 8/11/2019 8/11/2019 1 John Mayer \n", "3 8/9/2019 8/9/2019 1 John Mayer \n", "4 8/8/2019 8/8/2019 1 John Mayer \n", "5 8/6/2019 8/6/2019 1 John Mayer \n", "6 8/5/2019 8/5/2019 1 John Mayer \n", "7 8/3/2019 8/3/2019 1 John Mayer \n", "8 8/2/2019 8/2/2019 1 John Mayer \n", "9 7/30/2019 7/31/2019 2 John Mayer \n", "10 7/28/2019 7/28/2019 1 John Mayer \n", "11 7/25/2019 7/26/2019 2 John Mayer \n", "12 7/23/2019 7/23/2019 1 John Mayer \n", "13 7/22/2019 7/22/2019 1 John Mayer \n", "14 7/20/2019 7/20/2019 1 John Mayer \n", "15 7/19/2019 7/19/2019 1 John Mayer \n", "16 4/10/2019 4/11/2019 2 John Mayer \n", "17 4/8/2019 4/8/2019 1 John Mayer \n", "18 4/5/2019 4/5/2019 1 John Mayer \n", "19 4/3/2019 4/3/2019 1 John Mayer \n", "20 4/1/2019 4/1/2019 1 John Mayer \n", "21 3/29/2019 3/29/2019 1 John Mayer \n", "22 3/27/2019 3/27/2019 1 John Mayer \n", "23 3/25/2019 3/25/2019 1 John Mayer \n", "24 3/23/2019 3/23/2019 1 John Mayer \n", "25 12/30/2018 12/30/2018 1 \"Controlled Danger\" \n", "26 9/22/2018 NaN 1 \"Bourbon & Beyond\" \n", "27 4/30/2018 4/30/2018 1 \"Controlled Danger\" \n", "28 4/29/2018 4/29/2018 1 \"Controlled Danger\" \n", "29 1/11/2018 1/11/2018 1 John Mayer \n", ".. ... ... ... ... \n", "323 11/23/2013 NaN 1 Bring Me The Horizon \n", "324 11/22/2013 NaN 1 Bring Me The Horizon \n", "325 11/21/2013 NaN 1 Bring Me The Horizon \n", "326 11/19/2013 NaN 1 Bring Me The Horizon \n", "327 11/18/2013 NaN 1 Bring Me The Horizon \n", "328 11/17/2013 NaN 1 Bring Me The Horizon \n", "329 11/16/2013 NaN 1 Bring Me The Horizon \n", "330 11/15/2013 NaN 1 Bring Me The Horizon \n", "331 11/13/2013 11/13/2013 1 Bring Me The Horizon \n", "332 11/12/2013 NaN 1 Bring Me The Horizon \n", "333 11/11/2013 11/11/2013 1 Bring Me The Horizon \n", "334 11/10/2013 11/10/2013 1 Bring Me The Horizon \n", "335 11/9/2013 11/9/2013 1 Bring Me The Horizon \n", "336 11/7/2013 NaN 1 Bring Me The Horizon \n", "337 11/6/2013 NaN 1 Bring Me The Horizon \n", "338 11/5/2013 NaN 1 Bring Me The Horizon \n", "339 11/4/2013 NaN 1 Bring Me The Horizon \n", "340 11/2/2013 NaN 1 Bring Me The Horizon \n", "341 11/1/2013 NaN 1 Bring Me The Horizon \n", "342 10/31/2013 NaN 1 Bring Me The Horizon \n", "343 10/30/2013 NaN 1 Bring Me The Horizon \n", "344 10/19/2013 NaN 1 \"Loud Park Festival\" \n", "345 10/17/2013 NaN 1 Bring Me The Horizon \n", "346 10/16/2013 NaN 1 Bring Me The Horizon \n", "347 10/14/2013 NaN 1 Bring Me The Horizon \n", "348 10/12/2013 NaN 1 Bring Me The Horizon \n", "349 10/10/2013 NaN 1 Bring Me The Horizon \n", "350 10/9/2013 NaN 1 Bring Me The Horizon \n", "351 10/6/2013 10/6/2013 1 Bring Me The Horizon \n", "352 10/5/2013 NaN 1 Bring Me The Horizon \n", "\n", " Support Tickets Sold \\\n", "0 NaN 25235.0 \n", "1 NaN 9196.0 \n", "2 NaN 13490.0 \n", "3 NaN 14570.0 \n", "4 NaN 14126.0 \n", "5 NaN 9559.0 \n", "6 NaN 12064.0 \n", "7 NaN 12557.0 \n", "8 NaN 11215.0 \n", "9 NaN 24242.0 \n", "10 NaN 11865.0 \n", "11 NaN 35810.0 \n", "12 NaN 14287.0 \n", "13 NaN 12288.0 \n", "14 NaN 12139.0 \n", "15 NaN 9182.0 \n", "16 NaN 16977.0 \n", "17 NaN 7978.0 \n", "18 NaN 10504.0 \n", "19 NaN 10860.0 \n", "20 NaN 10240.0 \n", "21 NaN 15037.0 \n", "22 NaN 13074.0 \n", "23 NaN 8252.0 \n", "24 NaN 8875.0 \n", "25 Dave Chappelle, John Mayer 9418.0 \n", "26 Brian Setzer's Rockabilly Riot!, David Byrne, ... NaN \n", "27 John Mayer 2639.0 \n", "28 John Mayer 1401.0 \n", "29 NaN 2813.0 \n", ".. ... ... \n", "323 NaN NaN \n", "324 NaN NaN \n", "325 NaN NaN \n", "326 NaN NaN \n", "327 NaN NaN \n", "328 NaN NaN \n", "329 NaN NaN \n", "330 NaN NaN \n", "331 Pierce The Veil, Sights & Sounds 1900.0 \n", "332 NaN NaN \n", "333 Pierce The Veil 1500.0 \n", "334 Pierce The Veil 1830.0 \n", "335 Pierce The Veil 2000.0 \n", "336 NaN NaN \n", "337 NaN NaN \n", "338 NaN NaN \n", "339 NaN NaN \n", "340 NaN NaN \n", "341 NaN NaN \n", "342 NaN NaN \n", "343 NaN NaN \n", "344 Angra, Behemoth, Bring Me The Horizon, Carcass... NaN \n", "345 NaN NaN \n", "346 NaN NaN \n", "347 NaN NaN \n", "348 NaN NaN \n", "349 NaN NaN \n", "350 NaN NaN \n", "351 Crossfaith, Of Mice & Men 5180.0 \n", "352 NaN NaN \n", "\n", " Gross USD Gross Gate Currency Venue Capacity Percentage Sold \\\n", "0 2636712.0 2.636712e+06 US DOLLAR 13311.0 95% \n", "1 949348.0 9.493480e+05 US DOLLAR 9196.0 100% \n", "2 1490600.0 1.490600e+06 US DOLLAR 13490.0 100% \n", "3 1623735.0 1.623735e+06 US DOLLAR 14570.0 100% \n", "4 1733312.0 1.733312e+06 US DOLLAR 14126.0 100% \n", "5 851823.0 8.518230e+05 US DOLLAR 10494.0 92% \n", "6 1207967.0 1.207967e+06 US DOLLAR 14115.0 86% \n", "7 1154123.0 1.154123e+06 US DOLLAR 12557.0 100% \n", "8 1214620.0 1.214620e+06 US DOLLAR 12518.0 90% \n", "9 2097804.0 2.747184e+06 Canadian 12121.0 100% \n", "10 1080697.0 1.080697e+06 US DOLLAR 12571.0 95% \n", "11 4601632.0 4.601632e+06 US DOLLAR 17905.0 100% \n", "12 1529302.0 1.529302e+06 US DOLLAR 14287.0 100% \n", "13 1271620.0 1.271620e+06 US DOLLAR 13767.0 90% \n", "14 1367805.0 1.367805e+06 US DOLLAR 12139.0 100% \n", "15 804632.0 8.046320e+05 US DOLLAR 10116.0 91% \n", "16 1768655.0 1.960815e+08 Yen 8488.0 100% \n", "17 941074.0 7.387925e+06 Hong Kong 7978.0 100% \n", "18 1750167.0 2.500238e+10 Rupiah 10504.0 100% \n", "19 1537583.0 4.903007e+07 Baht 10860.0 100% \n", "20 1299916.0 1.762454e+06 Singapore 10302.0 100% \n", "21 1672081.0 2.347374e+06 Australian 15037.0 100% \n", "22 1467114.0 2.059627e+06 Australian 13074.0 100% \n", "23 908004.0 1.274713e+06 Australian 8252.0 100% \n", "24 997015.0 1.460207e+06 New Zealand 8875.0 100% \n", "25 1027865.0 1.027865e+06 US DOLLAR 9671.0 98% \n", "26 NaN NaN NaN NaN 0% \n", "27 329875.0 3.298750e+05 US DOLLAR 2639.0 100% \n", "28 140100.0 1.401000e+05 US DOLLAR 1401.0 100% \n", "29 234160.0 2.341600e+05 US DOLLAR 3435.0 82% \n", ".. ... ... ... ... ... \n", "323 NaN NaN NaN NaN 0 \n", "324 NaN NaN NaN NaN 0 \n", "325 NaN NaN NaN NaN 0 \n", "326 NaN NaN NaN NaN 0 \n", "327 NaN NaN NaN NaN 0 \n", "328 NaN NaN NaN NaN 0 \n", "329 NaN NaN NaN NaN 0 \n", "330 NaN NaN NaN NaN 0 \n", "331 57143.0 4.180000e+04 Euro 1900.0 100 \n", "332 NaN NaN NaN NaN 0 \n", "333 51264.0 3.750000e+04 Euro 1500.0 100 \n", "334 62946.0 4.604500e+04 Euro 2000.0 92 \n", "335 68353.0 5.000000e+04 Euro 2000.0 100 \n", "336 NaN NaN NaN NaN 0 \n", "337 NaN NaN NaN NaN 0 \n", "338 NaN NaN NaN NaN 0 \n", "339 NaN NaN NaN NaN 0 \n", "340 NaN NaN NaN NaN 0 \n", "341 NaN NaN NaN NaN 0 \n", "342 NaN NaN NaN NaN 0 \n", "343 NaN NaN NaN NaN 0 \n", "344 NaN NaN NaN NaN 0 \n", "345 NaN NaN NaN NaN 0 \n", "346 NaN NaN NaN NaN 0 \n", "347 NaN NaN NaN NaN 0 \n", "348 NaN NaN NaN NaN 0 \n", "349 NaN NaN NaN NaN 0 \n", "350 NaN NaN NaN NaN 0 \n", "351 345191.0 3.704640e+05 Australian 5493.0 95 \n", "352 NaN NaN NaN NaN 0 \n", "\n", " Ticket Price Min Ticket Price Max \\\n", "0 59.50 175.00 \n", "1 59.50 150.00 \n", "2 62.50 153.00 \n", "3 59.50 150.00 \n", "4 59.50 150.00 \n", "5 35.50 166.00 \n", "6 49.50 150.00 \n", "7 39.50 150.00 \n", "8 59.50 150.00 \n", "9 56.00 171.50 \n", "10 39.50 150.00 \n", "11 53.00 193.00 \n", "12 49.50 150.00 \n", "13 49.50 150.00 \n", "14 49.50 150.00 \n", "15 35.50 146.00 \n", "16 9500.00 15000.00 \n", "17 588.00 1188.00 \n", "18 1825.00 4960.00 \n", "19 2000.00 7000.00 \n", "20 108.00 248.00 \n", "21 47.75 487.65 \n", "22 50.75 488.20 \n", "23 87.95 487.65 \n", "24 101.75 502.75 \n", "25 45.00 269.50 \n", "26 NaN NaN \n", "27 49.50 275.00 \n", "28 49.50 275.00 \n", "29 75.00 85.00 \n", ".. ... ... \n", "323 NaN NaN \n", "324 NaN NaN \n", "325 NaN NaN \n", "326 NaN NaN \n", "327 NaN NaN \n", "328 NaN NaN \n", "329 NaN NaN \n", "330 NaN NaN \n", "331 22.00 25.00 \n", "332 NaN NaN \n", "333 25.00 0.00 \n", "334 25.00 0.00 \n", "335 25.00 0.00 \n", "336 NaN NaN \n", "337 NaN NaN \n", "338 NaN NaN \n", "339 NaN NaN \n", "340 NaN NaN \n", "341 NaN NaN \n", "342 NaN NaN \n", "343 NaN NaN \n", "344 NaN NaN \n", "345 NaN NaN \n", "346 NaN NaN \n", "347 NaN NaN \n", "348 NaN NaN \n", "349 NaN NaN \n", "350 NaN NaN \n", "351 76.20 0.00 \n", "352 NaN NaN \n", "\n", " Venue Name Venue City \\\n", "0 United Center Chicago \n", "1 Bankers Life Fieldhouse Indianapolis \n", "2 State Farm Arena Atlanta \n", "3 Spectrum Center Charlotte \n", "4 Bridgestone Arena Nashville \n", "5 Fiserv Forum Milwaukee \n", "6 Xcel Energy Center Saint Paul \n", "7 Schottenstein Center Columbus \n", "8 Little Caesars Arena Detroit \n", "9 Scotiabank Arena Toronto \n", "10 PPG Paints Arena Pittsburgh \n", "11 Madison Square Garden New York \n", "12 Capital One Arena Washington \n", "13 Wells Fargo Center Philadelphia \n", "14 Dunkin' Donuts Center Providence \n", "15 Times Union Center Albany \n", "16 Nippon Budokan Hall Tokyo \n", "17 Hong Kong Convention & Exhibition Centre Hong Kong \n", "18 Jakarta International Event & Convention Center Jakarta \n", "19 IMPACT Exhibition And Convention Center Nonthaburi \n", "20 Singapore Indoor Stadium Singapore \n", "21 Qudos Bank Arena Sydney \n", "22 Rod Laver Arena Melbourne \n", "23 Brisbane Entertainment Centre Boondall \n", "24 Spark Arena Auckland \n", "25 MGM Grand Garden Arena Las Vegas \n", "26 Champions Park Louisville \n", "27 The Masonic San Francisco \n", "28 The Fillmore San Francisco \n", "29 The Masonic San Francisco \n", ".. ... ... \n", "323 New Age Treviso \n", "324 Kofmehl Halle Solothurn \n", "325 Les Docks Lausanne \n", "326 Santana 27 Bilbao \n", "327 Sala Arena Madrid \n", "328 Bikini Barcelona \n", "329 Le Rocher De Palmer Cenon \n", "330 Le Bataclan Paris \n", "331 Ancienne Belgique Brussels \n", "332 013 Tilburg \n", "333 LKA Longhorn Stuttgart \n", "334 Schlachthof Wiesbaden \n", "335 E-Werk Cologne \n", "336 O2 Academy Brixton London \n", "337 O2 Academy Brixton London \n", "338 Manchester Academy Manchester \n", "339 Manchester Academy Manchester \n", "340 O2 Academy Birmingham Birmingham \n", "341 O2 Academy Birmingham Birmingham \n", "342 O2 Academy Newcastle Newcastle \n", "343 O2 Academy Glasgow Glasgow \n", "344 Saitama Super Arena Saitama \n", "345 KL Live Kuala Lumpur \n", "346 The Coliseum, Hard Rock Hotel Singapore \n", "347 Hard Rock Cafe Bali Bali \n", "348 HBF Stadium Mt. Claremont \n", "349 Thebarton Theatre Adelaide \n", "350 Festival Hall West Melbourne \n", "351 Hordern Pavilion Moore Park \n", "352 The Marquee Sydney \n", "\n", " Venue State Venue Country \\\n", "0 IL United States \n", "1 IN United States \n", "2 GA United States \n", "3 NC United States \n", "4 TN United States \n", "5 WI United States \n", "6 MN United States \n", "7 OH United States \n", "8 MI United States \n", "9 ON Canada \n", "10 PA United States \n", "11 NY United States \n", "12 DC United States \n", "13 PA United States \n", "14 RI United States \n", "15 NY United States \n", "16 NaN Japan \n", "17 NaN China \n", "18 NaN Indonesia \n", "19 NaN Thailand \n", "20 NaN Singapore \n", "21 NaN Australia \n", "22 NaN Australia \n", "23 NaN Australia \n", "24 NaN New Zealand \n", "25 NV United States \n", "26 KY United States \n", "27 CA United States \n", "28 CA United States \n", "29 CA United States \n", ".. ... ... \n", "323 NaN Italy \n", "324 NaN Switzerland \n", "325 NaN Switzerland \n", "326 NaN Spain \n", "327 NaN Spain \n", "328 NaN Spain \n", "329 NaN France \n", "330 NaN France \n", "331 NaN Belgium \n", "332 NaN Netherlands \n", "333 NaN Germany \n", "334 NaN Germany \n", "335 NaN Germany \n", "336 NaN United Kingdom \n", "337 NaN United Kingdom \n", "338 NaN United Kingdom \n", "339 NaN United Kingdom \n", "340 NaN United Kingdom \n", "341 NaN United Kingdom \n", "342 NaN United Kingdom \n", "343 NaN United Kingdom \n", "344 NaN Japan \n", "345 NaN Malaysia \n", "346 NaN Singapore \n", "347 NaN Indonesia \n", "348 NaN Australia \n", "349 NaN Australia \n", "350 NaN Australia \n", "351 NaN Australia \n", "352 NaN Australia \n", "\n", " Promoter primary_artist_name \n", "0 NaN John Mayer \n", "1 Live Nation, Live Nation - Los Angeles John Mayer \n", "2 (In-House Promotion), Live Nation, Live Nation... John Mayer \n", "3 Live Nation, Live Nation - Los Angeles John Mayer \n", "4 Live Nation, Live Nation - Los Angeles John Mayer \n", "5 FPC Live, Frank Productions Concerts, Frank Pr... John Mayer \n", "6 Live Nation, Live Nation - Los Angeles John Mayer \n", "7 Live Nation, Live Nation - Los Angeles John Mayer \n", "8 Live Nation, Live Nation - Los Angeles John Mayer \n", "9 Live Nation, Live Nation - Los Angeles John Mayer \n", "10 Live Nation, Live Nation - Los Angeles John Mayer \n", "11 Live Nation, Live Nation - Los Angeles John Mayer \n", "12 Live Nation, Live Nation - Los Angeles John Mayer \n", "13 Live Nation, Live Nation - Los Angeles John Mayer \n", "14 Live Nation, Live Nation - Los Angeles John Mayer \n", "15 Live Nation, Live Nation - Los Angeles John Mayer \n", "16 (In-House Promotion) John Mayer \n", "17 Live Nation, Live Nation - Los Angeles John Mayer \n", "18 (In-House Promotion), Live Nation, Live Nation... John Mayer \n", "19 Live Nation, Live Nation - Los Angeles John Mayer \n", "20 Live Nation, Live Nation - Los Angeles John Mayer \n", "21 (In-House Promotion), Live Nation, Live Nation... John Mayer \n", "22 (In-House Promotion), Live Nation, Live Nation... John Mayer \n", "23 (In-House Promotion), Live Nation, Live Nation... John Mayer \n", "24 Live Nation, Live Nation - Los Angeles John Mayer \n", "25 Live Nation, Live Nation - Los Angeles John Mayer \n", "26 NaN John Mayer \n", "27 Live Nation, Live Nation - Los Angeles John Mayer \n", "28 Live Nation, Live Nation - Los Angeles John Mayer \n", "29 Live Nation, Live Nation - Los Angeles John Mayer \n", ".. ... ... \n", "323 NaN Bring Me The Horizon \n", "324 NaN Bring Me The Horizon \n", "325 NaN Bring Me The Horizon \n", "326 NaN Bring Me The Horizon \n", "327 NaN Bring Me The Horizon \n", "328 NaN Bring Me The Horizon \n", "329 NaN Bring Me The Horizon \n", "330 NaN Bring Me The Horizon \n", "331 (In-House Promotion) Bring Me The Horizon \n", "332 NaN Bring Me The Horizon \n", "333 Marek Lieberberg Konzertagentur Bring Me The Horizon \n", "334 Marek Lieberberg Konzertagentur Bring Me The Horizon \n", "335 Marek Lieberberg Konzertagentur Bring Me The Horizon \n", "336 NaN Bring Me The Horizon \n", "337 NaN Bring Me The Horizon \n", "338 NaN Bring Me The Horizon \n", "339 NaN Bring Me The Horizon \n", "340 NaN Bring Me The Horizon \n", "341 NaN Bring Me The Horizon \n", "342 NaN Bring Me The Horizon \n", "343 NaN Bring Me The Horizon \n", "344 NaN Bring Me The Horizon \n", "345 NaN Bring Me The Horizon \n", "346 NaN Bring Me The Horizon \n", "347 NaN Bring Me The Horizon \n", "348 NaN Bring Me The Horizon \n", "349 NaN Bring Me The Horizon \n", "350 NaN Bring Me The Horizon \n", "351 Soundwave Bring Me The Horizon \n", "352 NaN Bring Me The Horizon \n", "\n", "[5000 rows x 19 columns]" ] }, "metadata": { "tags": [] }, "execution_count": 199 } ] }, { "cell_type": "markdown", "metadata": { "id": "7C0gibF6iaR4", "colab_type": "text" }, "source": [ "Columns to get rid of: Support, Gross Gate, Currency, Venue Name, Venue City, Venue State, Venue Country, Promoter, End Date\n", "Columns for sure to keep: Percentage Sold, Venue Capacity, Gross USD, Start Date, Num Shows, Headliner(for join)\n", "Not sure about: Tickets Sold, Ticket Price Min, Ticket Price Max" ] }, { "cell_type": "code", "metadata": { "id": "qEqubI8UiaR5", "colab_type": "code", "colab": {} }, "source": [ "ticket_data = first" ], "execution_count": 0, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "gvcqEKdpiaR6", "colab_type": "code", "colab": {} }, "source": [ "#Add to this as needed to fix incorrectly formatted names, check below\n", "ticket_data = ticket_data.replace({'G Eazy': 'G-Eazy', 'Gavin Degraw': 'Gavin DeGraw', 'Quinn Xcii': 'Quinn XCII', 'Ray Lamontagne': 'Ray LaMontagne'})" ], "execution_count": 0, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "eWsIT2eeiaR8", "colab_type": "code", "outputId": "d9135ca2-67a3-4717-9b0c-81c200cf77cc", "colab": {} }, "source": [ "set(ticket_data['primary_artist_name'])" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "{'Arcade Fire',\n", " 'Beyoncé',\n", " 'Billy Joel',\n", " 'Bob Dylan',\n", " 'Bring Me The Horizon',\n", " 'Buddy Guy',\n", " 'Chris Brown',\n", " 'Dave Matthews Band',\n", " 'Depeche Mode',\n", " 'Enrique Iglesias',\n", " 'Foo Fighters',\n", " 'Future',\n", " 'G-Eazy',\n", " 'Gavin DeGraw',\n", " 'George Ezra',\n", " 'George Winston',\n", " 'Harry Styles',\n", " 'Hozier',\n", " 'John Legend',\n", " 'John Mayer',\n", " 'Judas Priest',\n", " 'Justin Timberlake',\n", " 'Kesha',\n", " 'Khalid',\n", " 'Kings Of Leon',\n", " 'Lecrae',\n", " 'Leon Bridges',\n", " 'Maxwell',\n", " 'Modest Mouse',\n", " 'Moon Taxi',\n", " 'Nicky Jam',\n", " 'Pentatonix',\n", " 'Quinn XCII',\n", " 'Ray LaMontagne',\n", " 'Russ',\n", " 'The Chainsmokers',\n", " 'The Script',\n", " 'Tony Bennett',\n", " 'Travis Scott'}" ] }, "metadata": { "tags": [] }, "execution_count": 202 } ] }, { "cell_type": "code", "metadata": { "id": "fAJEEA67iaR-", "colab_type": "code", "outputId": "f5c4f524-58b6-4e2c-c36b-d3285f26d642", "colab": {} }, "source": [ "ticket_data.shape" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "(22318, 19)" ] }, "metadata": { "tags": [] }, "execution_count": 203 } ] }, { "cell_type": "code", "metadata": { "id": "DxRIiXikiaR_", "colab_type": "code", "outputId": "548bbe0d-11db-4fd0-d643-472a4e668af5", "colab": {} }, "source": [ "ticket_data.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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Start DateEnd DateNum ShowsHeadlinerSupportTickets SoldGross USDGross GateCurrencyVenue CapacityPercentage SoldTicket Price MinTicket Price MaxVenue NameVenue CityVenue StateVenue CountryPromoterprimary_artist_name
08/14/20198/15/20192John MayerNaN25235.02636712.02636712.0US DOLLAR13311.095%59.5175.0United CenterChicagoILUnited StatesNaNJohn Mayer
18/12/20198/12/20191John MayerNaN9196.0949348.0949348.0US DOLLAR9196.0100%59.5150.0Bankers Life FieldhouseIndianapolisINUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
28/11/20198/11/20191John MayerNaN13490.01490600.01490600.0US DOLLAR13490.0100%62.5153.0State Farm ArenaAtlantaGAUnited States(In-House Promotion), Live Nation, Live Nation...John Mayer
38/9/20198/9/20191John MayerNaN14570.01623735.01623735.0US DOLLAR14570.0100%59.5150.0Spectrum CenterCharlotteNCUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
48/8/20198/8/20191John MayerNaN14126.01733312.01733312.0US DOLLAR14126.0100%59.5150.0Bridgestone ArenaNashvilleTNUnited StatesLive Nation, Live Nation - Los AngelesJohn Mayer
\n", "
" ], "text/plain": [ " Start Date End Date Num Shows Headliner Support Tickets Sold \\\n", "0 8/14/2019 8/15/2019 2 John Mayer NaN 25235.0 \n", "1 8/12/2019 8/12/2019 1 John Mayer NaN 9196.0 \n", "2 8/11/2019 8/11/2019 1 John Mayer NaN 13490.0 \n", "3 8/9/2019 8/9/2019 1 John Mayer NaN 14570.0 \n", "4 8/8/2019 8/8/2019 1 John Mayer NaN 14126.0 \n", "\n", " Gross USD Gross Gate Currency Venue Capacity Percentage Sold \\\n", "0 2636712.0 2636712.0 US DOLLAR 13311.0 95% \n", "1 949348.0 949348.0 US DOLLAR 9196.0 100% \n", "2 1490600.0 1490600.0 US DOLLAR 13490.0 100% \n", "3 1623735.0 1623735.0 US DOLLAR 14570.0 100% \n", "4 1733312.0 1733312.0 US DOLLAR 14126.0 100% \n", "\n", " Ticket Price Min Ticket Price Max Venue Name Venue City \\\n", "0 59.5 175.0 United Center Chicago \n", "1 59.5 150.0 Bankers Life Fieldhouse Indianapolis \n", "2 62.5 153.0 State Farm Arena Atlanta \n", "3 59.5 150.0 Spectrum Center Charlotte \n", "4 59.5 150.0 Bridgestone Arena Nashville \n", "\n", " Venue State Venue Country \\\n", "0 IL United States \n", "1 IN United States \n", "2 GA United States \n", "3 NC United States \n", "4 TN United States \n", "\n", " Promoter primary_artist_name \n", "0 NaN John Mayer \n", "1 Live Nation, Live Nation - Los Angeles John Mayer \n", "2 (In-House Promotion), Live Nation, Live Nation... John Mayer \n", "3 Live Nation, Live Nation - Los Angeles John Mayer \n", "4 Live Nation, Live Nation - Los Angeles John Mayer " ] }, "metadata": { "tags": [] }, "execution_count": 204 } ] }, { "cell_type": "code", "metadata": { "id": "bXKkd5_kiaSB", "colab_type": "code", "outputId": "1c523f6d-65bf-49d6-f5c8-392cb1cc7a6c", "colab": {} }, "source": [ "ticket_data = ticket_data[ticket_data['Venue Country']=='United States']\n", "ticket_data.shape" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "(15953, 19)" ] }, "metadata": { "tags": [] }, "execution_count": 205 } ] }, { "cell_type": "code", "metadata": { "id": "y5BTk_YliaSC", "colab_type": "code", "outputId": "9037735c-b87a-46ab-ee70-99be55613a87", "colab": {} }, "source": [ "del ticket_data['End Date']\n", "del ticket_data['Support']\n", "del ticket_data['Gross Gate']\n", "del ticket_data['Currency']\n", "del ticket_data['Venue Name']\n", "del ticket_data['Venue City']\n", "del ticket_data['Venue State']\n", "del ticket_data['Promoter']\n", "ticket_data.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Start DateNum ShowsHeadlinerTickets SoldGross USDVenue CapacityPercentage SoldTicket Price MinTicket Price MaxVenue Countryprimary_artist_name
08/14/20192John Mayer25235.02636712.013311.095%59.5175.0United StatesJohn Mayer
18/12/20191John Mayer9196.0949348.09196.0100%59.5150.0United StatesJohn Mayer
28/11/20191John Mayer13490.01490600.013490.0100%62.5153.0United StatesJohn Mayer
38/9/20191John Mayer14570.01623735.014570.0100%59.5150.0United StatesJohn Mayer
48/8/20191John Mayer14126.01733312.014126.0100%59.5150.0United StatesJohn Mayer
\n", "
" ], "text/plain": [ " Start Date Num Shows Headliner Tickets Sold Gross USD Venue Capacity \\\n", "0 8/14/2019 2 John Mayer 25235.0 2636712.0 13311.0 \n", "1 8/12/2019 1 John Mayer 9196.0 949348.0 9196.0 \n", "2 8/11/2019 1 John Mayer 13490.0 1490600.0 13490.0 \n", "3 8/9/2019 1 John Mayer 14570.0 1623735.0 14570.0 \n", "4 8/8/2019 1 John Mayer 14126.0 1733312.0 14126.0 \n", "\n", " Percentage Sold Ticket Price Min Ticket Price Max Venue Country \\\n", "0 95% 59.5 175.0 United States \n", "1 100% 59.5 150.0 United States \n", "2 100% 62.5 153.0 United States \n", "3 100% 59.5 150.0 United States \n", "4 100% 59.5 150.0 United States \n", "\n", " primary_artist_name \n", "0 John Mayer \n", "1 John Mayer \n", "2 John Mayer \n", "3 John Mayer \n", "4 John Mayer " ] }, "metadata": { "tags": [] }, "execution_count": 206 } ] }, { "cell_type": "code", "metadata": { "id": "8cOYhSjjiaSE", "colab_type": "code", "outputId": "e2a2e787-db9a-4fc9-cfb9-e61549ce1d42", "colab": {} }, "source": [ "ticket_data = ticket_data[ticket_data['Gross USD'].notnull()]\n", "ticket_data.shape" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "(9717, 11)" ] }, "metadata": { "tags": [] }, "execution_count": 207 } ] }, { "cell_type": "code", "metadata": { "id": "SFWzyaDGiaSF", "colab_type": "code", "outputId": "628b23b2-e183-45e1-e7d1-d1349fe0d611", "colab": {} }, "source": [ "ticket_data['Start Date'] = pd.to_datetime(ticket_data['Start Date'])\n", "ticket_data.dtypes" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Start Date datetime64[ns]\n", "Num Shows int64\n", "Headliner object\n", "Tickets Sold float64\n", "Gross USD float64\n", "Venue Capacity float64\n", "Percentage Sold object\n", "Ticket Price Min float64\n", "Ticket Price Max float64\n", "Venue Country object\n", "primary_artist_name object\n", "dtype: object" ] }, "metadata": { "tags": [] }, "execution_count": 208 } ] }, { "cell_type": "code", "metadata": { "id": "zBGBVmhmiaSH", "colab_type": "code", "outputId": "247f3b32-0604-41c7-c276-0cc4cf2d13a8", "colab": {} }, "source": [ "#Add lag_report_date - will need this for join\n", "ticket_data['year_month'] = pd.to_datetime(ticket_data['Start Date']).dt.to_period('M')\n", "ticket_data['year_month'] = ticket_data['year_month'].astype(str) \n", "ticket_data['lag_report_date'] = ticket_data['year_month']+'-01'\n", "ticket_data.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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Start DateNum ShowsHeadlinerTickets SoldGross USDVenue CapacityPercentage SoldTicket Price MinTicket Price MaxVenue Countryprimary_artist_nameyear_monthlag_report_date
02019-08-142John Mayer25235.02636712.013311.095%59.5175.0United StatesJohn Mayer2019-082019-08-01
12019-08-121John Mayer9196.0949348.09196.0100%59.5150.0United StatesJohn Mayer2019-082019-08-01
22019-08-111John Mayer13490.01490600.013490.0100%62.5153.0United StatesJohn Mayer2019-082019-08-01
32019-08-091John Mayer14570.01623735.014570.0100%59.5150.0United StatesJohn Mayer2019-082019-08-01
42019-08-081John Mayer14126.01733312.014126.0100%59.5150.0United StatesJohn Mayer2019-082019-08-01
\n", "
" ], "text/plain": [ " Start Date Num Shows Headliner Tickets Sold Gross USD Venue Capacity \\\n", "0 2019-08-14 2 John Mayer 25235.0 2636712.0 13311.0 \n", "1 2019-08-12 1 John Mayer 9196.0 949348.0 9196.0 \n", "2 2019-08-11 1 John Mayer 13490.0 1490600.0 13490.0 \n", "3 2019-08-09 1 John Mayer 14570.0 1623735.0 14570.0 \n", "4 2019-08-08 1 John Mayer 14126.0 1733312.0 14126.0 \n", "\n", " Percentage Sold Ticket Price Min Ticket Price Max Venue Country \\\n", "0 95% 59.5 175.0 United States \n", "1 100% 59.5 150.0 United States \n", "2 100% 62.5 153.0 United States \n", "3 100% 59.5 150.0 United States \n", "4 100% 59.5 150.0 United States \n", "\n", " primary_artist_name year_month lag_report_date \n", "0 John Mayer 2019-08 2019-08-01 \n", "1 John Mayer 2019-08 2019-08-01 \n", "2 John Mayer 2019-08 2019-08-01 \n", "3 John Mayer 2019-08 2019-08-01 \n", "4 John Mayer 2019-08 2019-08-01 " ] }, "metadata": { "tags": [] }, "execution_count": 209 } ] }, { "cell_type": "code", "metadata": { "id": "1Lo-PSrWiaSJ", "colab_type": "code", "outputId": "ad78249f-b582-4c03-cacc-aba6ca8aa0dd", "colab": {} }, "source": [ "ticket_data['lag_report_date'] = pd.to_datetime(ticket_data['lag_report_date'])\n", "ticket_data.dtypes" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Start Date datetime64[ns]\n", "Num Shows int64\n", "Headliner object\n", "Tickets Sold float64\n", "Gross USD float64\n", "Venue Capacity float64\n", "Percentage Sold object\n", "Ticket Price Min float64\n", "Ticket Price Max float64\n", "Venue Country object\n", "primary_artist_name object\n", "year_month object\n", "lag_report_date datetime64[ns]\n", "dtype: object" ] }, "metadata": { "tags": [] }, "execution_count": 210 } ] }, { "cell_type": "code", "metadata": { "id": "qK9sX0sfiaSK", "colab_type": "code", "outputId": "d401e3fc-76e0-465c-f554-7428481a1c7c", "colab": {} }, "source": [ "del ticket_data['year_month']\n", "del ticket_data['Venue Country']\n", "del ticket_data['Tickets Sold']\n", "ticket_data.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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Start DateNum ShowsHeadlinerGross USDVenue CapacityPercentage SoldTicket Price MinTicket Price Maxprimary_artist_namelag_report_date
02019-08-142John Mayer2636712.013311.095%59.5175.0John Mayer2019-08-01
12019-08-121John Mayer949348.09196.0100%59.5150.0John Mayer2019-08-01
22019-08-111John Mayer1490600.013490.0100%62.5153.0John Mayer2019-08-01
32019-08-091John Mayer1623735.014570.0100%59.5150.0John Mayer2019-08-01
42019-08-081John Mayer1733312.014126.0100%59.5150.0John Mayer2019-08-01
\n", "
" ], "text/plain": [ " Start Date Num Shows Headliner Gross USD Venue Capacity \\\n", "0 2019-08-14 2 John Mayer 2636712.0 13311.0 \n", "1 2019-08-12 1 John Mayer 949348.0 9196.0 \n", "2 2019-08-11 1 John Mayer 1490600.0 13490.0 \n", "3 2019-08-09 1 John Mayer 1623735.0 14570.0 \n", "4 2019-08-08 1 John Mayer 1733312.0 14126.0 \n", "\n", " Percentage Sold Ticket Price Min Ticket Price Max primary_artist_name \\\n", "0 95% 59.5 175.0 John Mayer \n", "1 100% 59.5 150.0 John Mayer \n", "2 100% 62.5 153.0 John Mayer \n", "3 100% 59.5 150.0 John Mayer \n", "4 100% 59.5 150.0 John Mayer \n", "\n", " lag_report_date \n", "0 2019-08-01 \n", "1 2019-08-01 \n", "2 2019-08-01 \n", "3 2019-08-01 \n", "4 2019-08-01 " ] }, "metadata": { "tags": [] }, "execution_count": 211 } ] }, { "cell_type": "code", "metadata": { "id": "WT91OiJQiaSN", "colab_type": "code", "outputId": "9672c72c-1114-41dc-a7b8-3f403b97d4f0", "colab": {} }, "source": [ "ticket_data = ticket_data[ticket_data['lag_report_date']>='2014-09-01']\n", "ticket_data.shape" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "(3283, 10)" ] }, "metadata": { "tags": [] }, "execution_count": 212 } ] }, { "cell_type": "code", "metadata": { "id": "umlZxERQiaSO", "colab_type": "code", "outputId": "f92c87fb-7ab8-4d4d-9197-77ad9e5ac5a1", "colab": {} }, "source": [ "ticket_data.dtypes" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Start Date datetime64[ns]\n", "Num Shows int64\n", "Headliner object\n", "Gross USD float64\n", "Venue Capacity float64\n", "Percentage Sold object\n", "Ticket Price Min float64\n", "Ticket Price Max float64\n", "primary_artist_name object\n", "lag_report_date datetime64[ns]\n", "dtype: object" ] }, "metadata": { "tags": [] }, "execution_count": 213 } ] }, { "cell_type": "code", "metadata": { "id": "XshsmDrPiaSQ", "colab_type": "code", "outputId": "c7bd9c46-822e-469f-c917-438b23e94c7a", "colab": {} }, "source": [ "#Loop to fix problem of 0s in Ticket Max Price Column\n", "i=0\n", "for i in range(3282): #get this from ticket_data.shape-1 2 cells up\n", " if ticket_data.iloc[i,7]==0.0:\n", " ticket_data.iloc[i,7] = ticket_data.iloc[i,6]\n", " i+=1\n", "ticket_data.head(129)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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Start DateNum ShowsHeadlinerGross USDVenue CapacityPercentage SoldTicket Price MinTicket Price Maxprimary_artist_namelag_report_date
02019-08-142John Mayer2636712.013311.095%59.50175.00John Mayer2019-08-01
12019-08-121John Mayer949348.09196.0100%59.50150.00John Mayer2019-08-01
22019-08-111John Mayer1490600.013490.0100%62.50153.00John Mayer2019-08-01
32019-08-091John Mayer1623735.014570.0100%59.50150.00John Mayer2019-08-01
42019-08-081John Mayer1733312.014126.0100%59.50150.00John Mayer2019-08-01
52019-08-061John Mayer851823.010494.092%35.50166.00John Mayer2019-08-01
62019-08-051John Mayer1207967.014115.086%49.50150.00John Mayer2019-08-01
72019-08-031John Mayer1154123.012557.0100%39.50150.00John Mayer2019-08-01
82019-08-021John Mayer1214620.012518.090%59.50150.00John Mayer2019-08-01
102019-07-281John Mayer1080697.012571.095%39.50150.00John Mayer2019-07-01
112019-07-252John Mayer4601632.017905.0100%53.00193.00John Mayer2019-07-01
122019-07-231John Mayer1529302.014287.0100%49.50150.00John Mayer2019-07-01
132019-07-221John Mayer1271620.013767.090%49.50150.00John Mayer2019-07-01
142019-07-201John Mayer1367805.012139.0100%49.50150.00John Mayer2019-07-01
152019-07-191John Mayer804632.010116.091%35.50146.00John Mayer2019-07-01
252018-12-301\"Controlled Danger\"1027865.09671.098%45.00269.50John Mayer2018-12-01
272018-04-301\"Controlled Danger\"329875.02639.0100%49.50275.00John Mayer2018-04-01
282018-04-291\"Controlled Danger\"140100.01401.0100%49.50275.00John Mayer2018-04-01
292018-01-111John Mayer234160.03435.082%75.0085.00John Mayer2018-01-01
302018-01-061\"Boak's Bash\"168265.01500.0100%85.00185.00John Mayer2018-01-01
312017-12-311\"Controlled Danger\"1938764.014461.0100%49.50275.00John Mayer2017-12-01
372017-09-031John Mayer831107.024483.086%15.00125.00John Mayer2017-09-01
382017-09-021John Mayer694037.028632.053%18.75125.00John Mayer2017-09-01
392017-09-011John Mayer767722.014827.099%27.00149.00John Mayer2017-09-01
402017-08-301John Mayer439519.020826.046%27.00125.00John Mayer2017-08-01
422017-08-271John Mayer389252.021629.036%15.00125.00John Mayer2017-08-01
432017-08-261John Mayer764662.020265.066%27.00125.00John Mayer2017-08-01
442017-08-251John Mayer581398.022583.055%15.00125.00John Mayer2017-08-01
452017-08-241Dave Chappelle / Ali Wong / John Mayer749257.05926.0100%83.50163.50John Mayer2017-08-01
462017-08-231John Mayer1003646.013891.098%27.00200.00John Mayer2017-08-01
.................................
992017-05-201Future619507.024095.09611.00125.00Future2017-05-01
1002017-05-191Future1240567.014695.09629.50135.50Future2017-05-01
1012017-05-181Future481370.016934.09735.00135.00Future2017-05-01
1032017-05-141Future589897.018746.09511.00121.00Future2017-05-01
1042017-05-131Future541522.019980.09825.00135.00Future2017-05-01
1052017-05-121Future665409.024877.09611.00121.00Future2017-05-01
1062017-05-111Future754228.022583.09711.00129.00Future2017-05-01
1072017-05-091Future433160.018970.08611.00121.00Future2017-05-01
1092017-05-061Future316286.07300.09211.00121.00Future2017-05-01
1102017-05-051Future519188.018920.09625.00135.00Future2017-05-01
1112017-05-041Future405569.010161.07811.00125.00Future2017-05-01
1122017-04-142\"Coachella Valley Music & Arts Festival\"114593000.0125000.0100399.00899.00Future2017-04-01
1162016-10-051Drake1741160.015094.09449.50149.00Future2016-10-01
1172016-10-041Drake1315998.012520.09749.50149.50Future2016-10-01
1182016-10-012Drake2525393.011949.094.549.00179.00Future2016-10-01
1192016-09-273Drake4445347.014105.092.333349.50179.50Future2016-09-01
1202016-09-242Drake3099175.013330.09749.50179.00Future2016-09-01
1232016-09-161Drake1678531.018544.09846.50126.50Future2016-09-01
1242016-09-132Drake3294595.012915.09757.50195.25Future2016-09-01
1252016-09-111Drake1767317.015142.09749.50179.50Future2016-09-01
1262016-09-073Drake4878848.013385.09249.50179.50Future2016-09-01
1272016-09-061Drake1310117.012542.09749.50179.50Future2016-09-01
1282016-09-032Drake2942070.012253.095.549.50179.50Future2016-09-01
1292016-09-021Drake1243870.014073.09549.50179.50Future2016-09-01
1302016-08-302Drake3282545.013903.09646.25146.25Future2016-08-01
1312016-08-271Drake1359752.013751.09746.25146.25Future2016-08-01
1322016-08-252Drake2853772.012714.09749.50179.50Future2016-08-01
1332016-08-231Drake1304350.014184.09789.00109.00Future2016-08-01
1342016-08-211Drake1665589.013402.09649.50179.50Future2016-08-01
1352016-08-192Drake3259446.014292.09789.00109.00Future2016-08-01
\n", "

129 rows × 10 columns

\n", "
" ], "text/plain": [ " Start Date Num Shows Headliner \\\n", "0 2019-08-14 2 John Mayer \n", "1 2019-08-12 1 John Mayer \n", "2 2019-08-11 1 John Mayer \n", "3 2019-08-09 1 John Mayer \n", "4 2019-08-08 1 John Mayer \n", "5 2019-08-06 1 John Mayer \n", "6 2019-08-05 1 John Mayer \n", "7 2019-08-03 1 John Mayer \n", "8 2019-08-02 1 John Mayer \n", "10 2019-07-28 1 John Mayer \n", "11 2019-07-25 2 John Mayer \n", "12 2019-07-23 1 John Mayer \n", "13 2019-07-22 1 John Mayer \n", "14 2019-07-20 1 John Mayer \n", "15 2019-07-19 1 John Mayer \n", "25 2018-12-30 1 \"Controlled Danger\" \n", "27 2018-04-30 1 \"Controlled Danger\" \n", "28 2018-04-29 1 \"Controlled Danger\" \n", "29 2018-01-11 1 John Mayer \n", "30 2018-01-06 1 \"Boak's Bash\" \n", "31 2017-12-31 1 \"Controlled Danger\" \n", "37 2017-09-03 1 John Mayer \n", "38 2017-09-02 1 John Mayer \n", "39 2017-09-01 1 John Mayer \n", "40 2017-08-30 1 John Mayer \n", "42 2017-08-27 1 John Mayer \n", "43 2017-08-26 1 John Mayer \n", "44 2017-08-25 1 John Mayer \n", "45 2017-08-24 1 Dave Chappelle / Ali Wong / John Mayer \n", "46 2017-08-23 1 John Mayer \n", ".. ... ... ... \n", "99 2017-05-20 1 Future \n", "100 2017-05-19 1 Future \n", "101 2017-05-18 1 Future \n", "103 2017-05-14 1 Future \n", "104 2017-05-13 1 Future \n", "105 2017-05-12 1 Future \n", "106 2017-05-11 1 Future \n", "107 2017-05-09 1 Future \n", "109 2017-05-06 1 Future \n", "110 2017-05-05 1 Future \n", "111 2017-05-04 1 Future \n", "112 2017-04-14 2 \"Coachella Valley Music & Arts Festival\" \n", "116 2016-10-05 1 Drake \n", "117 2016-10-04 1 Drake \n", "118 2016-10-01 2 Drake \n", "119 2016-09-27 3 Drake \n", "120 2016-09-24 2 Drake \n", "123 2016-09-16 1 Drake \n", "124 2016-09-13 2 Drake \n", "125 2016-09-11 1 Drake \n", "126 2016-09-07 3 Drake \n", "127 2016-09-06 1 Drake \n", "128 2016-09-03 2 Drake \n", "129 2016-09-02 1 Drake \n", "130 2016-08-30 2 Drake \n", "131 2016-08-27 1 Drake \n", "132 2016-08-25 2 Drake \n", "133 2016-08-23 1 Drake \n", "134 2016-08-21 1 Drake \n", "135 2016-08-19 2 Drake \n", "\n", " Gross USD Venue Capacity Percentage Sold Ticket Price Min \\\n", "0 2636712.0 13311.0 95% 59.50 \n", "1 949348.0 9196.0 100% 59.50 \n", "2 1490600.0 13490.0 100% 62.50 \n", "3 1623735.0 14570.0 100% 59.50 \n", "4 1733312.0 14126.0 100% 59.50 \n", "5 851823.0 10494.0 92% 35.50 \n", "6 1207967.0 14115.0 86% 49.50 \n", "7 1154123.0 12557.0 100% 39.50 \n", "8 1214620.0 12518.0 90% 59.50 \n", "10 1080697.0 12571.0 95% 39.50 \n", "11 4601632.0 17905.0 100% 53.00 \n", "12 1529302.0 14287.0 100% 49.50 \n", "13 1271620.0 13767.0 90% 49.50 \n", "14 1367805.0 12139.0 100% 49.50 \n", "15 804632.0 10116.0 91% 35.50 \n", "25 1027865.0 9671.0 98% 45.00 \n", "27 329875.0 2639.0 100% 49.50 \n", "28 140100.0 1401.0 100% 49.50 \n", "29 234160.0 3435.0 82% 75.00 \n", "30 168265.0 1500.0 100% 85.00 \n", "31 1938764.0 14461.0 100% 49.50 \n", "37 831107.0 24483.0 86% 15.00 \n", "38 694037.0 28632.0 53% 18.75 \n", "39 767722.0 14827.0 99% 27.00 \n", "40 439519.0 20826.0 46% 27.00 \n", "42 389252.0 21629.0 36% 15.00 \n", "43 764662.0 20265.0 66% 27.00 \n", "44 581398.0 22583.0 55% 15.00 \n", "45 749257.0 5926.0 100% 83.50 \n", "46 1003646.0 13891.0 98% 27.00 \n", ".. ... ... ... ... \n", "99 619507.0 24095.0 96 11.00 \n", "100 1240567.0 14695.0 96 29.50 \n", "101 481370.0 16934.0 97 35.00 \n", "103 589897.0 18746.0 95 11.00 \n", "104 541522.0 19980.0 98 25.00 \n", "105 665409.0 24877.0 96 11.00 \n", "106 754228.0 22583.0 97 11.00 \n", "107 433160.0 18970.0 86 11.00 \n", "109 316286.0 7300.0 92 11.00 \n", "110 519188.0 18920.0 96 25.00 \n", "111 405569.0 10161.0 78 11.00 \n", "112 114593000.0 125000.0 100 399.00 \n", "116 1741160.0 15094.0 94 49.50 \n", "117 1315998.0 12520.0 97 49.50 \n", "118 2525393.0 11949.0 94.5 49.00 \n", "119 4445347.0 14105.0 92.3333 49.50 \n", "120 3099175.0 13330.0 97 49.50 \n", "123 1678531.0 18544.0 98 46.50 \n", "124 3294595.0 12915.0 97 57.50 \n", "125 1767317.0 15142.0 97 49.50 \n", "126 4878848.0 13385.0 92 49.50 \n", "127 1310117.0 12542.0 97 49.50 \n", "128 2942070.0 12253.0 95.5 49.50 \n", "129 1243870.0 14073.0 95 49.50 \n", "130 3282545.0 13903.0 96 46.25 \n", "131 1359752.0 13751.0 97 46.25 \n", "132 2853772.0 12714.0 97 49.50 \n", "133 1304350.0 14184.0 97 89.00 \n", "134 1665589.0 13402.0 96 49.50 \n", "135 3259446.0 14292.0 97 89.00 \n", "\n", " Ticket Price Max primary_artist_name lag_report_date \n", "0 175.00 John Mayer 2019-08-01 \n", "1 150.00 John Mayer 2019-08-01 \n", "2 153.00 John Mayer 2019-08-01 \n", "3 150.00 John Mayer 2019-08-01 \n", "4 150.00 John Mayer 2019-08-01 \n", "5 166.00 John Mayer 2019-08-01 \n", "6 150.00 John Mayer 2019-08-01 \n", "7 150.00 John Mayer 2019-08-01 \n", "8 150.00 John Mayer 2019-08-01 \n", "10 150.00 John Mayer 2019-07-01 \n", "11 193.00 John Mayer 2019-07-01 \n", "12 150.00 John Mayer 2019-07-01 \n", "13 150.00 John Mayer 2019-07-01 \n", "14 150.00 John Mayer 2019-07-01 \n", "15 146.00 John Mayer 2019-07-01 \n", "25 269.50 John Mayer 2018-12-01 \n", "27 275.00 John Mayer 2018-04-01 \n", "28 275.00 John Mayer 2018-04-01 \n", "29 85.00 John Mayer 2018-01-01 \n", "30 185.00 John Mayer 2018-01-01 \n", "31 275.00 John Mayer 2017-12-01 \n", "37 125.00 John Mayer 2017-09-01 \n", "38 125.00 John Mayer 2017-09-01 \n", "39 149.00 John Mayer 2017-09-01 \n", "40 125.00 John Mayer 2017-08-01 \n", "42 125.00 John Mayer 2017-08-01 \n", "43 125.00 John Mayer 2017-08-01 \n", "44 125.00 John Mayer 2017-08-01 \n", "45 163.50 John Mayer 2017-08-01 \n", "46 200.00 John Mayer 2017-08-01 \n", ".. ... ... ... \n", "99 125.00 Future 2017-05-01 \n", "100 135.50 Future 2017-05-01 \n", "101 135.00 Future 2017-05-01 \n", "103 121.00 Future 2017-05-01 \n", "104 135.00 Future 2017-05-01 \n", "105 121.00 Future 2017-05-01 \n", "106 129.00 Future 2017-05-01 \n", "107 121.00 Future 2017-05-01 \n", "109 121.00 Future 2017-05-01 \n", "110 135.00 Future 2017-05-01 \n", "111 125.00 Future 2017-05-01 \n", "112 899.00 Future 2017-04-01 \n", "116 149.00 Future 2016-10-01 \n", "117 149.50 Future 2016-10-01 \n", "118 179.00 Future 2016-10-01 \n", "119 179.50 Future 2016-09-01 \n", "120 179.00 Future 2016-09-01 \n", "123 126.50 Future 2016-09-01 \n", "124 195.25 Future 2016-09-01 \n", "125 179.50 Future 2016-09-01 \n", "126 179.50 Future 2016-09-01 \n", "127 179.50 Future 2016-09-01 \n", "128 179.50 Future 2016-09-01 \n", "129 179.50 Future 2016-09-01 \n", "130 146.25 Future 2016-08-01 \n", "131 146.25 Future 2016-08-01 \n", "132 179.50 Future 2016-08-01 \n", "133 109.00 Future 2016-08-01 \n", "134 179.50 Future 2016-08-01 \n", "135 109.00 Future 2016-08-01 \n", "\n", "[129 rows x 10 columns]" ] }, "metadata": { "tags": [] }, "execution_count": 214 } ] }, { "cell_type": "code", "metadata": { "id": "7oL2CvYniaSS", "colab_type": "code", "outputId": "961aa459-2489-435a-8f15-331a58802f87", "colab": {} }, "source": [ "ticket_data[ticket_data['primary_artist_name']=='Khalid'] #confirm 0s are fixed" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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Start DateNum ShowsHeadlinerGross USDVenue CapacityPercentage SoldTicket Price MinTicket Price Maxprimary_artist_namelag_report_date
32019-08-141Khalid Free Spirit World Tour665076.010490.0100%42.95102.95Khalid2019-08-01
82019-08-031Khalid Free Spirit World Tour987941.014272.097%25.5085.50Khalid2019-08-01
92019-07-312Khalid Free Spirit World Tour2176940.013765.0100%53.9593.95Khalid2019-07-01
102019-07-291Khalid752422.013051.094%28.4585.70Khalid2019-07-01
152019-07-191Khalid Free Spirit World Tour656712.011387.090%29.9589.95Khalid2019-07-01
162019-07-181Khalid Free Spirit World Tour752200.011505.0100%49.9599.95Khalid2019-07-01
182019-07-141Khalid Free Spirit World Tour875832.013193.0100%34.4584.45Khalid2019-07-01
232019-07-011Khalid Free Spirit World Tour740020.011282.0100%36.9576.95Khalid2019-07-01
242019-06-291Khalid Free Spirit World Tour929035.013292.0100%56.3989.39Khalid2019-06-01
252019-06-281Khalid Free Spirit World Tour921605.014320.093%38.0594.95Khalid2019-06-01
282019-06-231Khalid756932.011743.088%55.4595.45Khalid2019-06-01
292019-06-221Khalid672494.012130.087%39.9579.95Khalid2019-06-01
382018-12-15193.3 FLZ's Jingle Ball Presented by Capital One791104.012382.081%41.00151.00Khalid2018-12-01
422018-12-011Wild 94.9's Jingle Ball Presented by Capital One663160.06080.0100%100.40180.50Khalid2018-12-01
432018-11-301KIIS FM's Jingle Ball Presented by Capital One1847429.016121.0100%42.00757.00Khalid2018-11-01
462018-09-151Khalid382957.07622.0100%45.0065.00Khalid2018-09-01
592018-06-071Khalid284025.05620.0100%35.5050.95Khalid2018-06-01
602018-06-042Khalid465849.04083.0100%40.9560.95Khalid2018-06-01
622018-06-011Khalid371966.07498.0100%30.5060.95Khalid2018-06-01
652018-05-261Khalid276551.04355.0100%49.9576.95Khalid2018-05-01
662018-05-251Khalid392639.08500.0100%50.9550.95Khalid2018-05-01
672018-05-231Khalid211175.05051.098%35.5050.95Khalid2018-05-01
682018-05-221Khalid427103.09385.093%30.9560.95Khalid2018-05-01
702018-05-181Khalid271432.06035.0100%40.9560.95Khalid2018-05-01
712018-05-171Khalid304840.06612.0100%49.2049.20Khalid2018-05-01
722018-05-161Khalid344067.06642.0100%40.9550.95Khalid2018-05-01
732018-05-141Khalid496706.09508.099%60.9560.95Khalid2018-05-01
742018-05-131Khalid209065.07735.067%40.0060.00Khalid2018-05-01
762018-05-092Khalid762820.05553.0100%40.9565.95Khalid2018-05-01
772018-05-071Khalid250011.05426.0100%48.9548.95Khalid2018-05-01
.................................
792018-05-031Khalid314069.07200.099%50.9550.95Khalid2018-05-01
812018-05-011Khalid369666.08202.098%50.9550.95Khalid2018-05-01
832018-04-111Khalid148685.06384.077%23.0043.00Khalid2018-04-01
1002018-01-271Khalid487441.05960.0100%35.00110.00Khalid2018-01-01
1022017-12-071\"B96 Jingle Bash\"1586200.016492.0100%45.00225.00Khalid2017-12-01
1052017-11-291\"Red Bull Sound Select Presents\"51656.04873.094%9.0015.00Khalid2017-11-01
1112017-10-211\"We Can Survive\"1610249.017441.090%95.00150.00Khalid2017-10-01
1302017-09-211Khalid89259.03207.090%25.0054.00Khalid2017-09-01
1332017-08-311Khalid138207.04006.0100%34.5034.50Khalid2017-08-01
1392017-08-221Khalid98974.03835.097%20.0035.00Khalid2017-08-01
1412017-08-191Khalid70400.03200.0100%22.0022.00Khalid2017-08-01
1502017-08-061Khalid66210.02425.0100%25.0047.50Khalid2017-08-01
1582017-07-271Khalid96055.04008.0100%20.0035.00Khalid2017-07-01
1612017-07-231Khalid51972.02425.0100%16.0047.00Khalid2017-07-01
1622017-07-221Khalid62750.02350.0100%25.0045.00Khalid2017-07-01
1652017-07-161Khalid25000.01000.0100%25.0025.00Khalid2017-07-01
1682017-07-121Khalid33750.01350.0100%25.0025.00Khalid2017-07-01
1702017-06-161\"Jam'n 94.5 Summer Jam\"828598.017146.090%45.0065.00Khalid2017-06-01
1712017-06-031\"The Roots Picnic\" (PA)819811.013747.0100%55.0075.00Khalid2017-06-01
1722017-06-021Travis Scott182508.05500.0100%33.5033.50Khalid2017-06-01
1732017-06-011Travis Scott153694.04300.089%35.0055.00Khalid2017-06-01
1742017-05-311Travis Scott149080.04007.099%25.0035.00Khalid2017-05-01
1782017-05-241Travis Scott218175.06500.095%35.0049.50Khalid2017-05-01
1792017-05-211Travis Scott156434.04386.095%11.0075.00Khalid2017-05-01
1822017-05-171Travis Scott79000.02000.0100%39.5039.50Khalid2017-05-01
1832017-05-061Travis Scott143515.03955.083%44.0064.00Khalid2017-05-01
1842017-05-021Travis Scott178003.04500.0100%39.5045.00Khalid2017-05-01
1852017-04-201Khalid13500.0750.0100%18.0023.00Khalid2017-04-01
1902017-02-141Khalid6375.0425.0100%15.0018.00Khalid2017-02-01
1912017-02-121Khalid11250.0750.0100%15.0015.00Khalid2017-02-01
\n", "

61 rows × 10 columns

\n", "
" ], "text/plain": [ " Start Date Num Shows Headliner \\\n", "3 2019-08-14 1 Khalid Free Spirit World Tour \n", "8 2019-08-03 1 Khalid Free Spirit World Tour \n", "9 2019-07-31 2 Khalid Free Spirit World Tour \n", "10 2019-07-29 1 Khalid \n", "15 2019-07-19 1 Khalid Free Spirit World Tour \n", "16 2019-07-18 1 Khalid Free Spirit World Tour \n", "18 2019-07-14 1 Khalid Free Spirit World Tour \n", "23 2019-07-01 1 Khalid Free Spirit World Tour \n", "24 2019-06-29 1 Khalid Free Spirit World Tour \n", "25 2019-06-28 1 Khalid Free Spirit World Tour \n", "28 2019-06-23 1 Khalid \n", "29 2019-06-22 1 Khalid \n", "38 2018-12-15 1 93.3 FLZ's Jingle Ball Presented by Capital One \n", "42 2018-12-01 1 Wild 94.9's Jingle Ball Presented by Capital One \n", "43 2018-11-30 1 KIIS FM's Jingle Ball Presented by Capital One \n", "46 2018-09-15 1 Khalid \n", "59 2018-06-07 1 Khalid \n", "60 2018-06-04 2 Khalid \n", "62 2018-06-01 1 Khalid \n", "65 2018-05-26 1 Khalid \n", "66 2018-05-25 1 Khalid \n", "67 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Scott \n", "174 2017-05-31 1 Travis Scott \n", "178 2017-05-24 1 Travis Scott \n", "179 2017-05-21 1 Travis Scott \n", "182 2017-05-17 1 Travis Scott \n", "183 2017-05-06 1 Travis Scott \n", "184 2017-05-02 1 Travis Scott \n", "185 2017-04-20 1 Khalid \n", "190 2017-02-14 1 Khalid \n", "191 2017-02-12 1 Khalid \n", "\n", " Gross USD Venue Capacity Percentage Sold Ticket Price Min \\\n", "3 665076.0 10490.0 100% 42.95 \n", "8 987941.0 14272.0 97% 25.50 \n", "9 2176940.0 13765.0 100% 53.95 \n", "10 752422.0 13051.0 94% 28.45 \n", "15 656712.0 11387.0 90% 29.95 \n", "16 752200.0 11505.0 100% 49.95 \n", "18 875832.0 13193.0 100% 34.45 \n", "23 740020.0 11282.0 100% 36.95 \n", "24 929035.0 13292.0 100% 56.39 \n", "25 921605.0 14320.0 93% 38.05 \n", "28 756932.0 11743.0 88% 55.45 \n", "29 672494.0 12130.0 87% 39.95 \n", "38 791104.0 12382.0 81% 41.00 \n", "42 663160.0 6080.0 100% 100.40 \n", "43 1847429.0 16121.0 100% 42.00 \n", "46 382957.0 7622.0 100% 45.00 \n", "59 284025.0 5620.0 100% 35.50 \n", "60 465849.0 4083.0 100% 40.95 \n", "62 371966.0 7498.0 100% 30.50 \n", "65 276551.0 4355.0 100% 49.95 \n", "66 392639.0 8500.0 100% 50.95 \n", "67 211175.0 5051.0 98% 35.50 \n", "68 427103.0 9385.0 93% 30.95 \n", "70 271432.0 6035.0 100% 40.95 \n", "71 304840.0 6612.0 100% 49.20 \n", "72 344067.0 6642.0 100% 40.95 \n", "73 496706.0 9508.0 99% 60.95 \n", "74 209065.0 7735.0 67% 40.00 \n", "76 762820.0 5553.0 100% 40.95 \n", "77 250011.0 5426.0 100% 48.95 \n", ".. ... ... ... ... \n", "79 314069.0 7200.0 99% 50.95 \n", "81 369666.0 8202.0 98% 50.95 \n", "83 148685.0 6384.0 77% 23.00 \n", "100 487441.0 5960.0 100% 35.00 \n", "102 1586200.0 16492.0 100% 45.00 \n", "105 51656.0 4873.0 94% 9.00 \n", "111 1610249.0 17441.0 90% 95.00 \n", "130 89259.0 3207.0 90% 25.00 \n", "133 138207.0 4006.0 100% 34.50 \n", "139 98974.0 3835.0 97% 20.00 \n", "141 70400.0 3200.0 100% 22.00 \n", "150 66210.0 2425.0 100% 25.00 \n", "158 96055.0 4008.0 100% 20.00 \n", "161 51972.0 2425.0 100% 16.00 \n", "162 62750.0 2350.0 100% 25.00 \n", "165 25000.0 1000.0 100% 25.00 \n", "168 33750.0 1350.0 100% 25.00 \n", "170 828598.0 17146.0 90% 45.00 \n", "171 819811.0 13747.0 100% 55.00 \n", "172 182508.0 5500.0 100% 33.50 \n", "173 153694.0 4300.0 89% 35.00 \n", "174 149080.0 4007.0 99% 25.00 \n", "178 218175.0 6500.0 95% 35.00 \n", "179 156434.0 4386.0 95% 11.00 \n", "182 79000.0 2000.0 100% 39.50 \n", "183 143515.0 3955.0 83% 44.00 \n", "184 178003.0 4500.0 100% 39.50 \n", "185 13500.0 750.0 100% 18.00 \n", "190 6375.0 425.0 100% 15.00 \n", "191 11250.0 750.0 100% 15.00 \n", "\n", " Ticket Price Max primary_artist_name lag_report_date \n", "3 102.95 Khalid 2019-08-01 \n", "8 85.50 Khalid 2019-08-01 \n", "9 93.95 Khalid 2019-07-01 \n", "10 85.70 Khalid 2019-07-01 \n", "15 89.95 Khalid 2019-07-01 \n", "16 99.95 Khalid 2019-07-01 \n", "18 84.45 Khalid 2019-07-01 \n", "23 76.95 Khalid 2019-07-01 \n", "24 89.39 Khalid 2019-06-01 \n", "25 94.95 Khalid 2019-06-01 \n", "28 95.45 Khalid 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2017-08-01 \n", "141 22.00 Khalid 2017-08-01 \n", "150 47.50 Khalid 2017-08-01 \n", "158 35.00 Khalid 2017-07-01 \n", "161 47.00 Khalid 2017-07-01 \n", "162 45.00 Khalid 2017-07-01 \n", "165 25.00 Khalid 2017-07-01 \n", "168 25.00 Khalid 2017-07-01 \n", "170 65.00 Khalid 2017-06-01 \n", "171 75.00 Khalid 2017-06-01 \n", "172 33.50 Khalid 2017-06-01 \n", "173 55.00 Khalid 2017-06-01 \n", "174 35.00 Khalid 2017-05-01 \n", "178 49.50 Khalid 2017-05-01 \n", "179 75.00 Khalid 2017-05-01 \n", "182 39.50 Khalid 2017-05-01 \n", "183 64.00 Khalid 2017-05-01 \n", "184 45.00 Khalid 2017-05-01 \n", "185 23.00 Khalid 2017-04-01 \n", "190 18.00 Khalid 2017-02-01 \n", "191 15.00 Khalid 2017-02-01 \n", "\n", "[61 rows x 10 columns]" ] }, "metadata": { "tags": [] }, "execution_count": 215 } ] }, { "cell_type": "markdown", "metadata": { "id": "rdV5FU1Uk5cX", "colab_type": "text" }, "source": [ "PART 2: BRING IN REST OF DATA TO JOIN TO GET EMPTY ROWS FOR CALCULATIONS" ] }, { "cell_type": "code", "metadata": { "id": "nO3K9DsKiaST", "colab_type": "code", "outputId": "8eb9687c-1cf9-46d5-af44-e864a4946c34", "colab": {} }, "source": [ "os.chdir('/Users/barr001/Downloads')\n", "full_data = pd.read_csv('train_test_with_release_flag_no_null.csv', index_col=0)\n", "full_data.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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" ], "text/plain": [ " report_year_month primary_artist_name all_revenues monthly_total_stream \\\n", "0 2018-07-01 21 Savage 201822.5515 74761529 \n", "1 2018-08-01 21 Savage 168988.9089 72316210 \n", "2 2018-09-01 21 Savage 161232.0460 60940016 \n", "3 2018-10-01 21 Savage 166704.2709 58102492 \n", "4 2018-11-01 21 Savage 148484.4162 46906635 \n", "\n", " consumer_count album_stream artist_stream chart_stream \\\n", "0 4984236 22673942 1568831 0 \n", "1 7172727 7752943 1968526 0 \n", "2 7572756 4265577 1739631 0 \n", "3 7237727 4059146 1483814 0 \n", "4 6868106 2787946 1044982 0 \n", "\n", " collection_stream other_stream ... playlist_other followers \\\n", "0 31679113 8114349 ... 948321 6088438 \n", "1 36820184 12082669 ... 1588048 6914528 \n", "2 32250405 11979070 ... 1797450 7257498 \n", "3 31514066 12918812 ... 2062691 7784313 \n", "4 25879830 11589279 ... 1784711 8491616 \n", "\n", " follower_growth post_count interaction interaction_growth \\\n", "0 0.163400 61 8335136 1.076333 \n", "1 0.257833 72 7055156 -0.547500 \n", "2 0.053500 23 3005737 1.224667 \n", "3 0.074767 47 6478947 5.741600 \n", "4 0.092133 18 4729944 -0.252600 \n", "\n", " lag_report_date lag_revenues type release_flag \n", "0 2017-07-01 1.647595e+06 train 1.0 \n", "1 2017-08-01 1.046511e+06 train 0.0 \n", "2 2017-09-01 9.847586e+05 train 0.0 \n", "3 2017-10-01 8.326544e+05 train 0.0 \n", "4 2017-11-01 6.427816e+05 train 0.0 \n", "\n", "[5 rows x 24 columns]" ] }, "metadata": { "tags": [] }, "execution_count": 216 } ] }, { "cell_type": "code", "metadata": { "id": "b6Q6xfjjiaSV", "colab_type": "code", "outputId": "7cbb5bf9-7328-4b5d-d067-b5cd9433f91a", "colab": {} }, "source": [ "full_data.shape" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "(10591, 24)" ] }, "metadata": { "tags": [] }, "execution_count": 217 } ] }, { "cell_type": "code", "metadata": { "id": "VagrlKgpiaSX", "colab_type": "code", "outputId": "845a6a3b-a4c4-4c26-a679-48657b43610d", "colab": {} }, "source": [ "full_data['lag_report_date'] = pd.to_datetime(full_data['lag_report_date'])\n", "full_data.dtypes" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "report_year_month object\n", "primary_artist_name object\n", "all_revenues float64\n", "monthly_total_stream int64\n", "consumer_count int64\n", "album_stream int64\n", "artist_stream int64\n", "chart_stream int64\n", "collection_stream int64\n", "other_stream int64\n", "playqueue_stream int64\n", "radio_stream int64\n", "search_stream int64\n", "playlist_spotify int64\n", "playlist_other int64\n", "followers int64\n", "follower_growth float64\n", "post_count int64\n", "interaction int64\n", "interaction_growth float64\n", "lag_report_date datetime64[ns]\n", "lag_revenues float64\n", "type object\n", "release_flag float64\n", "dtype: object" ] }, "metadata": { "tags": [] }, "execution_count": 218 } ] }, { "cell_type": "code", "metadata": { "id": "yY6ZguQniaSY", "colab_type": "code", "outputId": "4d5e4594-c638-4f98-afa4-dee5823c92b3", "colab": {} }, "source": [ "result = pd.merge(full_data, ticket_data, how='outer', on=['primary_artist_name','lag_report_date'])\n", "result.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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report_year_monthprimary_artist_nameall_revenuesmonthly_total_streamconsumer_countalbum_streamartist_streamchart_streamcollection_streamother_stream...typerelease_flagStart DateNum ShowsHeadlinerGross USDVenue CapacityPercentage SoldTicket Price MinTicket Price Max
02018-07-0121 Savage201822.551574761529.04984236.022673942.01568831.00.031679113.08114349.0...train1.0NaTNaNNaNNaNNaNNaNNaNNaN
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22018-09-0121 Savage161232.046060940016.07572756.04265577.01739631.00.032250405.011979070.0...train0.0NaTNaNNaNNaNNaNNaNNaNNaN
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5 rows × 32 columns

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" ], "text/plain": [ " report_year_month primary_artist_name all_revenues monthly_total_stream \\\n", "0 2018-07-01 21 Savage 201822.5515 74761529.0 \n", "1 2018-08-01 21 Savage 168988.9089 72316210.0 \n", "2 2018-09-01 21 Savage 161232.0460 60940016.0 \n", "3 2018-10-01 21 Savage 166704.2709 58102492.0 \n", "4 2018-11-01 21 Savage 148484.4162 46906635.0 \n", "\n", " consumer_count album_stream artist_stream chart_stream \\\n", "0 4984236.0 22673942.0 1568831.0 0.0 \n", "1 7172727.0 7752943.0 1968526.0 0.0 \n", "2 7572756.0 4265577.0 1739631.0 0.0 \n", "3 7237727.0 4059146.0 1483814.0 0.0 \n", "4 6868106.0 2787946.0 1044982.0 0.0 \n", "\n", " collection_stream other_stream ... type release_flag Start Date \\\n", "0 31679113.0 8114349.0 ... train 1.0 NaT \n", "1 36820184.0 12082669.0 ... train 0.0 NaT \n", "2 32250405.0 11979070.0 ... train 0.0 NaT \n", "3 31514066.0 12918812.0 ... train 0.0 NaT \n", "4 25879830.0 11589279.0 ... train 0.0 NaT \n", "\n", " Num Shows Headliner Gross USD Venue Capacity Percentage Sold \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN NaN \n", "4 NaN NaN NaN NaN NaN \n", "\n", " Ticket Price Min Ticket Price Max \n", "0 NaN NaN \n", "1 NaN NaN \n", "2 NaN NaN \n", "3 NaN NaN \n", "4 NaN NaN \n", "\n", "[5 rows x 32 columns]" ] }, "metadata": { "tags": [] }, "execution_count": 219 } ] }, { "cell_type": "code", "metadata": { "id": "QDtYL3sFiaSa", "colab_type": "code", "colab": {} }, "source": [ "result['Percentage Sold'] = result['Percentage Sold'].str.rstrip('%').astype('float') / 100.0\n", "#result.dtypes" ], "execution_count": 0, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "johxX9WGiaSc", "colab_type": "code", "outputId": "fba935d3-7855-485d-a3a3-342d307d5002", "colab": {} }, "source": [ "result.shape" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "(13226, 32)" ] }, "metadata": { "tags": [] }, "execution_count": 221 } ] }, { "cell_type": "code", "metadata": { "id": "XlH5pi_6iaSe", "colab_type": "code", "outputId": "6432a881-f411-48ae-cc1f-fee197719b0b", "colab": {} }, "source": [ "ticket_cols = result.loc[:, ['primary_artist_name', 'lag_report_date', 'Num Shows', 'Gross USD', 'Venue Capacity', 'Ticket Price Min', 'Ticket Price Max', 'Percentage Sold']]\n", "ticket_cols.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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021 Savage2017-07-01NaNNaNNaNNaNNaNNaN
121 Savage2017-08-01NaNNaNNaNNaNNaNNaN
221 Savage2017-09-01NaNNaNNaNNaNNaNNaN
321 Savage2017-10-01NaNNaNNaNNaNNaNNaN
421 Savage2017-11-01NaNNaNNaNNaNNaNNaN
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" ], "text/plain": [ " primary_artist_name lag_report_date Num Shows Gross USD Venue Capacity \\\n", "0 21 Savage 2017-07-01 NaN NaN NaN \n", "1 21 Savage 2017-08-01 NaN NaN NaN \n", "2 21 Savage 2017-09-01 NaN NaN NaN \n", "3 21 Savage 2017-10-01 NaN NaN NaN \n", "4 21 Savage 2017-11-01 NaN NaN NaN \n", "\n", " Ticket Price Min Ticket Price Max Percentage Sold \n", "0 NaN NaN NaN \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 NaN NaN NaN \n", "4 NaN NaN NaN " ] }, "metadata": { "tags": [] }, "execution_count": 226 } ] }, { "cell_type": "code", "metadata": { "id": "Tntw7iWniaSg", "colab_type": "code", "outputId": "aa3433db-f783-4d09-dade-b898a303d70f", "colab": {} }, "source": [ "#Calculate mean and fill blank values with averages\n", "ticket_mean = ticket_cols.groupby(['primary_artist_name','lag_report_date']).mean()\n", "ticket_mean = ticket_mean.interpolate()\n", "ticket_mean.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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Num ShowsGross USDVenue CapacityTicket Price MinTicket Price MaxPercentage Sold
primary_artist_namelag_report_date
21 Savage2017-07-01NaNNaNNaNNaNNaNNaN
2017-08-01NaNNaNNaNNaNNaNNaN
2017-09-01NaNNaNNaNNaNNaNNaN
2017-10-01NaNNaNNaNNaNNaNNaN
2017-11-01NaNNaNNaNNaNNaNNaN
\n", "
" ], "text/plain": [ " Num Shows Gross USD Venue Capacity \\\n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 NaN NaN NaN \n", " 2017-08-01 NaN NaN NaN \n", " 2017-09-01 NaN NaN NaN \n", " 2017-10-01 NaN NaN NaN \n", " 2017-11-01 NaN NaN NaN \n", "\n", " Ticket Price Min Ticket Price Max \\\n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 NaN NaN \n", " 2017-08-01 NaN NaN \n", " 2017-09-01 NaN NaN \n", " 2017-10-01 NaN NaN \n", " 2017-11-01 NaN NaN \n", "\n", " Percentage Sold \n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 NaN \n", " 2017-08-01 NaN \n", " 2017-09-01 NaN \n", " 2017-10-01 NaN \n", " 2017-11-01 NaN " ] }, "metadata": { "tags": [] }, "execution_count": 227 } ] }, { "cell_type": "code", "metadata": { "id": "pWDnLIBXiaSi", "colab_type": "code", "outputId": "663fd62a-f8f9-4b6b-a0c9-e8232a3d1595", "colab": {} }, "source": [ "#Calculate cumulative sum\n", "ticket_sum = ticket_cols.groupby(['primary_artist_name', 'lag_report_date']).sum().groupby(level=[0]).cumsum()\n", "ticket_sum.head() " ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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Num ShowsGross USDVenue CapacityTicket Price MinTicket Price MaxPercentage Sold
primary_artist_namelag_report_date
21 Savage2017-07-010.00.00.00.00.00.0
2017-08-010.00.00.00.00.00.0
2017-09-010.00.00.00.00.00.0
2017-10-010.00.00.00.00.00.0
2017-11-010.00.00.00.00.00.0
\n", "
" ], "text/plain": [ " Num Shows Gross USD Venue Capacity \\\n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 0.0 0.0 0.0 \n", " 2017-08-01 0.0 0.0 0.0 \n", " 2017-09-01 0.0 0.0 0.0 \n", " 2017-10-01 0.0 0.0 0.0 \n", " 2017-11-01 0.0 0.0 0.0 \n", "\n", " Ticket Price Min Ticket Price Max \\\n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 0.0 0.0 \n", " 2017-08-01 0.0 0.0 \n", " 2017-09-01 0.0 0.0 \n", " 2017-10-01 0.0 0.0 \n", " 2017-11-01 0.0 0.0 \n", "\n", " Percentage Sold \n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 0.0 \n", " 2017-08-01 0.0 \n", " 2017-09-01 0.0 \n", " 2017-10-01 0.0 \n", " 2017-11-01 0.0 " ] }, "metadata": { "tags": [] }, "execution_count": 228 } ] }, { "cell_type": "code", "metadata": { "id": "9MRx1orhiaSj", "colab_type": "code", "colab": {} }, "source": [ "#Rename for clarity in join\n", "ticket_sum = ticket_sum.rename(columns={'Num Shows':'Num_Shows1', 'Gross USD': 'Gross_USD1', 'Venue Capacity':'Venue_Cap1', 'Ticket Price Min': 'Tix_min1', 'Ticket Price Max': 'Tix_max1', 'Percentage Sold': 'pct1'})" ], "execution_count": 0, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "nLWs0ww6iaSk", "colab_type": "code", "outputId": "0fc5fa9a-1167-4355-859f-3ff2f5a40ef6", "colab": {} }, "source": [ "sum_mean = pd.merge(ticket_mean, ticket_sum, on=['primary_artist_name','lag_report_date'])\n", "sum_mean.head(5)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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Num ShowsGross USDVenue CapacityTicket Price MinTicket Price MaxPercentage SoldNum_Shows1Gross_USD1Venue_Cap1Tix_min1Tix_max1pct1
primary_artist_namelag_report_date
21 Savage2017-07-01NaNNaNNaNNaNNaNNaN0.00.00.00.00.00.0
2017-08-01NaNNaNNaNNaNNaNNaN0.00.00.00.00.00.0
2017-09-01NaNNaNNaNNaNNaNNaN0.00.00.00.00.00.0
2017-10-01NaNNaNNaNNaNNaNNaN0.00.00.00.00.00.0
2017-11-01NaNNaNNaNNaNNaNNaN0.00.00.00.00.00.0
\n", "
" ], "text/plain": [ " Num Shows Gross USD Venue Capacity \\\n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 NaN NaN NaN \n", " 2017-08-01 NaN NaN NaN \n", " 2017-09-01 NaN NaN NaN \n", " 2017-10-01 NaN NaN NaN \n", " 2017-11-01 NaN NaN NaN \n", "\n", " Ticket Price Min Ticket Price Max \\\n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 NaN NaN \n", " 2017-08-01 NaN NaN \n", " 2017-09-01 NaN NaN \n", " 2017-10-01 NaN NaN \n", " 2017-11-01 NaN NaN \n", "\n", " Percentage Sold Num_Shows1 Gross_USD1 \\\n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 NaN 0.0 0.0 \n", " 2017-08-01 NaN 0.0 0.0 \n", " 2017-09-01 NaN 0.0 0.0 \n", " 2017-10-01 NaN 0.0 0.0 \n", " 2017-11-01 NaN 0.0 0.0 \n", "\n", " Venue_Cap1 Tix_min1 Tix_max1 pct1 \n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 0.0 0.0 0.0 0.0 \n", " 2017-08-01 0.0 0.0 0.0 0.0 \n", " 2017-09-01 0.0 0.0 0.0 0.0 \n", " 2017-10-01 0.0 0.0 0.0 0.0 \n", " 2017-11-01 0.0 0.0 0.0 0.0 " ] }, "metadata": { "tags": [] }, "execution_count": 230 } ] }, { "cell_type": "code", "metadata": { "id": "uUTVTof_iaSn", "colab_type": "code", "outputId": "e31d2c8d-6bb5-48d0-d68e-0af8a861eede", "colab": {} }, "source": [ "del sum_mean['Venue_Cap1']\n", "del sum_mean['Tix_min1']\n", "del sum_mean['Tix_max1']\n", "del sum_mean['pct1']\n", "del sum_mean['Num Shows']\n", "del sum_mean['Gross USD']\n", "sum_mean.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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Venue CapacityTicket Price MinTicket Price MaxPercentage SoldNum_Shows1Gross_USD1
primary_artist_namelag_report_date
21 Savage2017-07-01NaNNaNNaNNaN0.00.0
2017-08-01NaNNaNNaNNaN0.00.0
2017-09-01NaNNaNNaNNaN0.00.0
2017-10-01NaNNaNNaNNaN0.00.0
2017-11-01NaNNaNNaNNaN0.00.0
\n", "
" ], "text/plain": [ " Venue Capacity Ticket Price Min \\\n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 NaN NaN \n", " 2017-08-01 NaN NaN \n", " 2017-09-01 NaN NaN \n", " 2017-10-01 NaN NaN \n", " 2017-11-01 NaN NaN \n", "\n", " Ticket Price Max Percentage Sold \\\n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 NaN NaN \n", " 2017-08-01 NaN NaN \n", " 2017-09-01 NaN NaN \n", " 2017-10-01 NaN NaN \n", " 2017-11-01 NaN NaN \n", "\n", " Num_Shows1 Gross_USD1 \n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 0.0 0.0 \n", " 2017-08-01 0.0 0.0 \n", " 2017-09-01 0.0 0.0 \n", " 2017-10-01 0.0 0.0 \n", " 2017-11-01 0.0 0.0 " ] }, "metadata": { "tags": [] }, "execution_count": 231 } ] }, { "cell_type": "code", "metadata": { "id": "6lldNTuTiaSp", "colab_type": "code", "outputId": "da687384-57ba-4d00-c2c2-204ed097a81c", "colab": {} }, "source": [ "sum_mean = sum_mean.rename(columns={'Num_Shows1':'num_shows', 'Gross_USD1': 'gross_usd', 'Venue Capacity':'venue_capacity', 'Ticket Price Min': 'tix_price_min', 'Ticket Price Max': 'tix_price_max', 'Percentage Sold': 'pct_sold'})\n", "sum_mean.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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venue_capacitytix_price_mintix_price_maxpct_soldnum_showsgross_usd
primary_artist_namelag_report_date
21 Savage2017-07-01NaNNaNNaNNaN0.00.0
2017-08-01NaNNaNNaNNaN0.00.0
2017-09-01NaNNaNNaNNaN0.00.0
2017-10-01NaNNaNNaNNaN0.00.0
2017-11-01NaNNaNNaNNaN0.00.0
\n", "
" ], "text/plain": [ " venue_capacity tix_price_min \\\n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 NaN NaN \n", " 2017-08-01 NaN NaN \n", " 2017-09-01 NaN NaN \n", " 2017-10-01 NaN NaN \n", " 2017-11-01 NaN NaN \n", "\n", " tix_price_max pct_sold num_shows \\\n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 NaN NaN 0.0 \n", " 2017-08-01 NaN NaN 0.0 \n", " 2017-09-01 NaN NaN 0.0 \n", " 2017-10-01 NaN NaN 0.0 \n", " 2017-11-01 NaN NaN 0.0 \n", "\n", " gross_usd \n", "primary_artist_name lag_report_date \n", "21 Savage 2017-07-01 0.0 \n", " 2017-08-01 0.0 \n", " 2017-09-01 0.0 \n", " 2017-10-01 0.0 \n", " 2017-11-01 0.0 " ] }, "metadata": { "tags": [] }, "execution_count": 232 } ] }, { "cell_type": "code", "metadata": { "id": "y517UjihiaSr", "colab_type": "code", "outputId": "a9c50240-b9f6-490b-c337-732c7da6b53a", "colab": {} }, "source": [ "sum_mean.shape" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "(10546, 6)" ] }, "metadata": { "tags": [] }, "execution_count": 233 } ] }, { "cell_type": "code", "metadata": { "id": "n5KErJWJiaSs", "colab_type": "code", "outputId": "a23ae91d-eb15-4ac2-9487-8b625cabff9e", "colab": {} }, "source": [ "sum_mean = sum_mean.reset_index()\n", "sum_mean.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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primary_artist_namelag_report_datevenue_capacitytix_price_mintix_price_maxpct_soldnum_showsgross_usd
021 Savage2017-07-01NaNNaNNaNNaN0.00.0
121 Savage2017-08-01NaNNaNNaNNaN0.00.0
221 Savage2017-09-01NaNNaNNaNNaN0.00.0
321 Savage2017-10-01NaNNaNNaNNaN0.00.0
421 Savage2017-11-01NaNNaNNaNNaN0.00.0
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" ], "text/plain": [ " primary_artist_name lag_report_date venue_capacity tix_price_min \\\n", "0 21 Savage 2017-07-01 NaN NaN \n", "1 21 Savage 2017-08-01 NaN NaN \n", "2 21 Savage 2017-09-01 NaN NaN \n", "3 21 Savage 2017-10-01 NaN NaN \n", "4 21 Savage 2017-11-01 NaN NaN \n", "\n", " tix_price_max pct_sold num_shows gross_usd \n", "0 NaN NaN 0.0 0.0 \n", "1 NaN NaN 0.0 0.0 \n", "2 NaN NaN 0.0 0.0 \n", "3 NaN NaN 0.0 0.0 \n", "4 NaN NaN 0.0 0.0 " ] }, "metadata": { "tags": [] }, "execution_count": 234 } ] }, { "cell_type": "markdown", "metadata": { "id": "tEu5eHZ8mpf4", "colab_type": "text" }, "source": [ "PART 3: REJOIN TO FULL DATA AND OUTPUT" ] }, { "cell_type": "code", "metadata": { "id": "l5-1lRXHiaSt", "colab_type": "code", "outputId": "93ff68c2-7aea-44ef-ed3d-0602321e339f", "colab": {} }, "source": [ "final = pd.merge(full_data, sum_mean, on=['primary_artist_name','lag_report_date'])\n", "final.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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report_year_monthprimary_artist_nameall_revenuesmonthly_total_streamconsumer_countalbum_streamartist_streamchart_streamcollection_streamother_stream...lag_report_datelag_revenuestyperelease_flagvenue_capacitytix_price_mintix_price_maxpct_soldnum_showsgross_usd
02018-07-0121 Savage201822.55157476152949842362267394215688310316791138114349...2017-07-011.647595e+06train1.0NaNNaNNaNNaN0.00.0
12018-08-0121 Savage168988.90897231621071727277752943196852603682018412082669...2017-08-011.046511e+06train0.0NaNNaNNaNNaN0.00.0
22018-09-0121 Savage161232.04606094001675727564265577173963103225040511979070...2017-09-019.847586e+05train0.0NaNNaNNaNNaN0.00.0
32018-10-0121 Savage166704.27095810249272377274059146148381403151406612918812...2017-10-018.326544e+05train0.0NaNNaNNaNNaN0.00.0
42018-11-0121 Savage148484.41624690663568681062787946104498202587983011589279...2017-11-016.427816e+05train0.0NaNNaNNaNNaN0.00.0
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5 rows × 30 columns

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" ], "text/plain": [ " report_year_month primary_artist_name all_revenues monthly_total_stream \\\n", "0 2018-07-01 21 Savage 201822.5515 74761529 \n", "1 2018-08-01 21 Savage 168988.9089 72316210 \n", "2 2018-09-01 21 Savage 161232.0460 60940016 \n", "3 2018-10-01 21 Savage 166704.2709 58102492 \n", "4 2018-11-01 21 Savage 148484.4162 46906635 \n", "\n", " consumer_count album_stream artist_stream chart_stream \\\n", "0 4984236 22673942 1568831 0 \n", "1 7172727 7752943 1968526 0 \n", "2 7572756 4265577 1739631 0 \n", "3 7237727 4059146 1483814 0 \n", "4 6868106 2787946 1044982 0 \n", "\n", " collection_stream other_stream ... lag_report_date lag_revenues type \\\n", "0 31679113 8114349 ... 2017-07-01 1.647595e+06 train \n", "1 36820184 12082669 ... 2017-08-01 1.046511e+06 train \n", "2 32250405 11979070 ... 2017-09-01 9.847586e+05 train \n", "3 31514066 12918812 ... 2017-10-01 8.326544e+05 train \n", "4 25879830 11589279 ... 2017-11-01 6.427816e+05 train \n", "\n", " release_flag venue_capacity tix_price_min tix_price_max pct_sold \\\n", "0 1.0 NaN NaN NaN NaN \n", "1 0.0 NaN NaN NaN NaN \n", "2 0.0 NaN NaN NaN NaN \n", "3 0.0 NaN NaN NaN NaN \n", "4 0.0 NaN NaN NaN NaN \n", "\n", " num_shows gross_usd \n", "0 0.0 0.0 \n", "1 0.0 0.0 \n", "2 0.0 0.0 \n", "3 0.0 0.0 \n", "4 0.0 0.0 \n", "\n", "[5 rows x 30 columns]" ] }, "metadata": { "tags": [] }, "execution_count": 235 } ] }, { "cell_type": "code", "metadata": { "id": "bhOl8x__iaSv", "colab_type": "code", "outputId": "1adda810-3a87-40bf-ae5a-815bda3ae2eb", "colab": {} }, "source": [ "final.shape" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "(10591, 30)" ] }, "metadata": { "tags": [] }, "execution_count": 236 } ] }, { "cell_type": "code", "metadata": { "id": "bShxoJpaiaSw", "colab_type": "code", "colab": {} }, "source": [ "final.to_csv('full_data_with_tickets.csv')" ], "execution_count": 0, "outputs": [] }, { "cell_type": "markdown", "metadata": { "id": "2gRW3rttiaSx", "colab_type": "text" }, "source": [ "JUST FOR TESTING FROM HERE ON" ] }, { "cell_type": "code", "metadata": { "id": "s53ogNq1iaSx", "colab_type": "code", "outputId": "c50a9496-f4b2-439c-b16c-fe2f67c99315", "colab": {} }, "source": [ "final[final['primary_artist_name']=='Khalid']" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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53212017-11-01Khalid1.230549e+06343281478441515277315486701798662160995...2016-11-014.578251e+04train0.0684.72771815.31149717.6100710.9996700.00.0
53222017-12-01Khalid1.341664e+064917916102337830705940577202582582228427...2016-12-011.027633e+05train0.0652.31847915.20766517.2400480.9997800.00.0
53232018-01-01Khalid1.212623e+06111271551606344781226125020706078718585931...2017-01-012.092430e+05train0.0619.90923915.10383216.8700240.9998900.00.0
53242018-02-01Khalid1.114972e+06198439622516180114282726410530103762951884251...2017-02-014.189703e+05train0.0587.50000015.00000016.5000001.0000002.017625.0
53252018-03-01Khalid1.256738e+066943181155862351390428462846190327293907272982...2017-03-011.080806e+06train0.0668.75000016.50000019.7500001.0000002.017625.0
53262018-04-01Khalid1.189670e+067535485663744571006595261058920388464949768465...2017-04-011.078879e+06train0.0750.00000018.00000023.0000001.0000003.031125.0
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53302018-08-01Khalid1.061632e+069055303682150129118988563860404805801412726029...2017-08-011.258190e+06train0.03366.50000025.37500034.7500000.99250022.03583261.0
53312018-09-01Khalid1.322789e+069460830686081438538812636101105285162313770809...2017-09-011.433923e+06train0.03207.00000025.00000054.0000000.90000023.03672520.0
53322018-10-01Khalid1.880492e+069012241985605797495377518912705216963714619543...2017-10-011.307773e+06train0.017441.00000095.000000150.0000000.90000024.05282769.0
53332018-11-01Khalid1.719935e+067748395784032126594688415632604495443612608698...2017-11-011.230549e+06train0.04873.0000009.00000015.0000000.94000025.05334425.0
53342018-12-01Khalid1.542600e+067333273381428596126021382126704164272511681921...2017-12-011.341664e+06train0.016492.00000045.000000225.0000001.00000026.06920625.0
53352019-01-01Khalid1.562916e+0672599899794411773649803785414277221419962449324167...2018-01-011.212623e+06train0.05960.00000035.000000110.0000001.00000027.07408066.0
53362019-02-01Khalid1.570194e+066285108770926446354972291185288122739747739559282...2018-02-011.114972e+06train0.06101.33333331.00000087.6666670.92333327.07408066.0
53372019-03-01Khalid2.145469e+066462063172430656369083274190328629840523564570160...2018-03-011.256738e+06train0.06242.66666727.00000065.3333330.84666727.07408066.0
53382019-04-01Khalid4.223924e+065534218067318194828775229511811138317688973795222...2018-04-011.189670e+06train0.06384.00000023.00000043.0000000.77000028.07556751.0
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53402019-06-01Khalid2.115626e+064964171268178173978409182357474984881835259622...2018-06-011.205009e+06train0.05733.66666735.65000057.6166671.00000048.014089309.0
53412019-07-01Khalid1.715814e+064687920268647164171578134882042180291594495164...2018-07-011.204912e+06train0.06363.11111138.76666760.0777781.00000048.014089309.0
53422019-08-01Khalid1.488443e+0645716465632604841167261219427323119961483889530...2018-08-011.061632e+06test0.06992.55555641.88333362.5388891.00000048.014089309.0
53432019-09-01Khalid5.334860e+0560015180866074454973731438855800520300180124714621...2018-09-011.322789e+06test0.07622.00000045.00000065.0000001.00000049.014472266.0
53442019-10-01Khalid0.000000e+00101075105104132841912390323633671931270431253866792650...2018-10-011.880492e+06predict0.011871.50000043.500000411.0000001.00000049.014472266.0
53452019-11-01Khalid0.000000e+00842806129582117931238618220221217648417846116397252...2018-11-011.719935e+06predict0.016121.00000042.000000757.0000001.00000050.016319695.0
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53472020-01-01Khalid0.000000e+009407522011105686641772726087712003408433953667090186...2019-01-011.562916e+06predict0.09837.70833366.826667153.1141670.90750052.017773959.0
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53502020-04-01Khalid0.000000e+00208873284128761505925151067759453542247783553281384984...2019-04-014.223924e+06predict1.011657.83333355.206667115.2066670.91500052.017773959.0
53512020-05-01Khalid0.000000e+00144006819125131991936122144538201778588703099441081591...2019-05-012.584391e+06predict0.012264.54166751.333333102.5708330.91750052.017773959.0
53522020-06-01Khalid0.000000e+0011453057811773890120479613628378131739560298878909347...2019-06-012.115626e+06predict0.012871.25000047.46000089.9350000.92000056.021054025.0
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53542020-08-01Khalid0.000000e+0096223297111566948575799259899757773952770365781502...2019-08-011.488443e+06predict0.012381.00000034.22500094.2250000.98500065.028661168.0
53552020-09-01Khalid0.000000e+0041148154758138932130349763227765123219682332318...2019-09-015.334860e+05predict0.012381.00000034.22500094.2250000.98500065.028661168.0
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38 rows × 30 columns

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" ], "text/plain": [ " report_year_month primary_artist_name all_revenues \\\n", "5318 2017-08-01 Khalid 1.258190e+06 \n", "5319 2017-09-01 Khalid 1.433923e+06 \n", "5320 2017-10-01 Khalid 1.307773e+06 \n", "5321 2017-11-01 Khalid 1.230549e+06 \n", "5322 2017-12-01 Khalid 1.341664e+06 \n", "5323 2018-01-01 Khalid 1.212623e+06 \n", "5324 2018-02-01 Khalid 1.114972e+06 \n", "5325 2018-03-01 Khalid 1.256738e+06 \n", "5326 2018-04-01 Khalid 1.189670e+06 \n", "5327 2018-05-01 Khalid 1.306788e+06 \n", "5328 2018-06-01 Khalid 1.205009e+06 \n", "5329 2018-07-01 Khalid 1.204912e+06 \n", "5330 2018-08-01 Khalid 1.061632e+06 \n", "5331 2018-09-01 Khalid 1.322789e+06 \n", "5332 2018-10-01 Khalid 1.880492e+06 \n", "5333 2018-11-01 Khalid 1.719935e+06 \n", "5334 2018-12-01 Khalid 1.542600e+06 \n", "5335 2019-01-01 Khalid 1.562916e+06 \n", "5336 2019-02-01 Khalid 1.570194e+06 \n", "5337 2019-03-01 Khalid 2.145469e+06 \n", "5338 2019-04-01 Khalid 4.223924e+06 \n", "5339 2019-05-01 Khalid 2.584391e+06 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"5350 3542247 78355328 1384984 ... 2019-04-01 \n", "5351 1778588 70309944 1081591 ... 2019-05-01 \n", "5352 1317395 60298878 909347 ... 2019-06-01 \n", "5353 849721 56478610 864918 ... 2019-07-01 \n", "5354 577739 52770365 781502 ... 2019-08-01 \n", "5355 77651 23219682 332318 ... 2019-09-01 \n", "\n", " lag_revenues type release_flag venue_capacity tix_price_min \\\n", "5318 2.202422e+02 train 0.0 781.955437 15.622995 \n", "5319 1.477781e+04 train 0.0 749.546197 15.519162 \n", "5320 2.949351e+04 train 0.0 717.136958 15.415330 \n", "5321 4.578251e+04 train 0.0 684.727718 15.311497 \n", "5322 1.027633e+05 train 0.0 652.318479 15.207665 \n", "5323 2.092430e+05 train 0.0 619.909239 15.103832 \n", "5324 4.189703e+05 train 0.0 587.500000 15.000000 \n", "5325 1.080806e+06 train 0.0 668.750000 16.500000 \n", "5326 1.078879e+06 train 0.0 750.000000 18.000000 \n", "5327 1.017206e+06 train 0.0 4224.666667 32.333333 \n", "5328 1.080759e+06 train 0.0 10173.250000 42.125000 \n", "5329 1.117101e+06 train 0.0 2226.600000 22.200000 \n", "5330 1.258190e+06 train 0.0 3366.500000 25.375000 \n", "5331 1.433923e+06 train 0.0 3207.000000 25.000000 \n", "5332 1.307773e+06 train 0.0 17441.000000 95.000000 \n", "5333 1.230549e+06 train 0.0 4873.000000 9.000000 \n", "5334 1.341664e+06 train 0.0 16492.000000 45.000000 \n", "5335 1.212623e+06 train 0.0 5960.000000 35.000000 \n", "5336 1.114972e+06 train 0.0 6101.333333 31.000000 \n", "5337 1.256738e+06 train 0.0 6242.666667 27.000000 \n", "5338 1.189670e+06 train 0.0 6384.000000 23.000000 \n", "5339 1.306788e+06 train 0.0 7067.500000 45.796429 \n", "5340 1.205009e+06 train 0.0 5733.666667 35.650000 \n", "5341 1.204912e+06 train 0.0 6363.111111 38.766667 \n", "5342 1.061632e+06 test 0.0 6992.555556 41.883333 \n", "5343 1.322789e+06 test 0.0 7622.000000 45.000000 \n", "5344 1.880492e+06 predict 0.0 11871.500000 43.500000 \n", "5345 1.719935e+06 predict 0.0 16121.000000 42.000000 \n", "5346 1.542600e+06 predict 0.0 9231.000000 70.700000 \n", "5347 1.562916e+06 predict 0.0 9837.708333 66.826667 \n", "5348 1.570194e+06 predict 0.0 10444.416667 62.953333 \n", "5349 2.145469e+06 predict 0.0 11051.125000 59.080000 \n", "5350 4.223924e+06 predict 1.0 11657.833333 55.206667 \n", "5351 2.584391e+06 predict 0.0 12264.541667 51.333333 \n", "5352 2.115626e+06 predict 0.0 12871.250000 47.460000 \n", "5353 1.715814e+06 predict 0.0 12363.833333 38.950000 \n", "5354 1.488443e+06 predict 0.0 12381.000000 34.225000 \n", "5355 5.334860e+05 predict 0.0 12381.000000 34.225000 \n", "\n", " tix_price_max pct_sold num_shows gross_usd \n", "5318 18.720143 0.999340 0.0 0.0 \n", "5319 18.350119 0.999450 0.0 0.0 \n", "5320 17.980095 0.999560 0.0 0.0 \n", "5321 17.610071 0.999670 0.0 0.0 \n", "5322 17.240048 0.999780 0.0 0.0 \n", "5323 16.870024 0.999890 0.0 0.0 \n", "5324 16.500000 1.000000 2.0 17625.0 \n", "5325 19.750000 1.000000 2.0 17625.0 \n", "5326 23.000000 1.000000 3.0 31125.0 \n", "5327 51.333333 0.953333 9.0 955332.0 \n", "5328 57.125000 0.947500 13.0 2939943.0 \n", "5329 35.400000 1.000000 18.0 3209470.0 \n", "5330 34.750000 0.992500 22.0 3583261.0 \n", "5331 54.000000 0.900000 23.0 3672520.0 \n", "5332 150.000000 0.900000 24.0 5282769.0 \n", "5333 15.000000 0.940000 25.0 5334425.0 \n", "5334 225.000000 1.000000 26.0 6920625.0 \n", "5335 110.000000 1.000000 27.0 7408066.0 \n", "5336 87.666667 0.923333 27.0 7408066.0 \n", "5337 65.333333 0.846667 27.0 7408066.0 \n", "5338 43.000000 0.770000 28.0 7556751.0 \n", "5339 56.328571 0.967143 44.0 12967469.0 \n", "5340 57.616667 1.000000 48.0 14089309.0 \n", "5341 60.077778 1.000000 48.0 14089309.0 \n", "5342 62.538889 1.000000 48.0 14089309.0 \n", "5343 65.000000 1.000000 49.0 14472266.0 \n", "5344 411.000000 1.000000 49.0 14472266.0 \n", "5345 757.000000 1.000000 50.0 16319695.0 \n", "5346 165.750000 0.905000 52.0 17773959.0 \n", "5347 153.114167 0.907500 52.0 17773959.0 \n", "5348 140.478333 0.910000 52.0 17773959.0 \n", "5349 127.842500 0.912500 52.0 17773959.0 \n", "5350 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primary_artist_namelag_report_datevenue_capacitytix_price_mintix_price_maxpct_soldnum_showsgross_usd
4824John Mayer2014-09-01NaNNaNNaNNaN0.00.0
4825John Mayer2014-10-01NaNNaNNaNNaN0.00.0
4826John Mayer2014-11-01NaNNaNNaNNaN0.00.0
4827John Mayer2014-12-01NaNNaNNaNNaN0.00.0
4828John Mayer2015-01-01NaNNaNNaNNaN0.00.0
4829John Mayer2015-02-01NaNNaNNaNNaN0.00.0
4830John Mayer2015-03-01NaNNaNNaNNaN0.00.0
4831John Mayer2015-04-01NaNNaNNaNNaN0.00.0
4832John Mayer2015-05-01NaNNaNNaNNaN0.00.0
4833John Mayer2015-06-01NaNNaNNaNNaN0.00.0
4834John Mayer2015-07-01NaNNaNNaNNaN0.00.0
4835John Mayer2015-08-01NaNNaNNaNNaN0.00.0
4836John Mayer2015-09-01NaNNaNNaNNaN0.00.0
4837John Mayer2015-10-01NaNNaNNaNNaN0.00.0
4838John Mayer2015-11-01NaNNaNNaNNaN0.00.0
4839John Mayer2015-12-01NaNNaNNaNNaN0.00.0
4840John Mayer2016-01-01NaNNaNNaNNaN0.00.0
4841John Mayer2016-02-01NaNNaNNaNNaN0.00.0
4842John Mayer2016-03-01NaNNaNNaNNaN0.00.0
4843John Mayer2016-04-01NaNNaNNaNNaN0.00.0
4844John Mayer2016-05-011120.000000135.000000135.0000000.9600001.0163870.0
4845John Mayer2016-06-012857.800000125.000000138.0000000.9250001.0163870.0
4846John Mayer2016-07-014595.600000115.000000141.0000000.8900001.0163870.0
4847John Mayer2016-08-016333.400000105.000000144.0000000.8550001.0163870.0
4848John Mayer2016-09-018071.20000095.000000147.0000000.8200001.0163870.0
4849John Mayer2016-10-019809.00000085.000000150.0000000.7850003.01650375.0
4850John Mayer2016-11-0110364.60000074.550000137.3500000.7900003.01650375.0
4851John Mayer2016-12-0110920.20000064.100000124.7000000.7950003.01650375.0
4852John Mayer2017-01-0111475.80000053.650000112.0500000.8000003.01650375.0
4853John Mayer2017-02-0112031.40000043.20000099.4000000.8050003.01650375.0
...........................
4855John Mayer2017-04-0112931.27272751.045455169.7500000.91590916.011974127.0
4856John Mayer2017-05-0113677.64015246.467803157.4583330.85352316.011974127.0
4857John Mayer2017-06-0114424.00757641.890152145.1666670.79113616.011974127.0
4858John Mayer2017-07-0115170.37500037.312500132.8750000.72875024.018325417.0
4859John Mayer2017-08-0116318.09090935.565909144.6590910.77863646.034867485.0
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121 Savage2017-08-01NaNNaNNaNNaN0.00.0
221 Savage2017-09-01NaNNaNNaNNaN0.00.0
321 Savage2017-10-01NaNNaNNaNNaN0.00.0
421 Savage2017-11-01NaNNaNNaNNaN0.00.0
521 Savage2017-12-01NaNNaNNaNNaN0.00.0
621 Savage2018-01-01NaNNaNNaNNaN0.00.0
721 Savage2018-02-01NaNNaNNaNNaN0.00.0
821 Savage2018-03-01NaNNaNNaNNaN0.00.0
921 Savage2018-04-01NaNNaNNaNNaN0.00.0
1021 Savage2018-05-01NaNNaNNaNNaN0.00.0
1121 Savage2018-06-01NaNNaNNaNNaN0.00.0
1221 Savage2018-07-01NaNNaNNaNNaN0.00.0
1321 Savage2018-08-01NaNNaNNaNNaN0.00.0
1421 Savage2018-09-01NaNNaNNaNNaN0.00.0
1521 Savage2018-10-01NaNNaNNaNNaN0.00.0
1621 Savage2018-11-01NaNNaNNaNNaN0.00.0
1721 Savage2018-12-01NaNNaNNaNNaN0.00.0
1821 Savage2019-01-01NaNNaNNaNNaN0.00.0
1921 Savage2019-02-01NaNNaNNaNNaN0.00.0
2021 Savage2019-03-01NaNNaNNaNNaN0.00.0
2121 Savage2019-04-01NaNNaNNaNNaN0.00.0
2221 Savage2019-05-01NaNNaNNaNNaN0.00.0
2321 Savage2019-06-01NaNNaNNaNNaN0.00.0
2421 Savage2019-07-01NaNNaNNaNNaN0.00.0
2521 Savage2019-08-01NaNNaNNaNNaN0.00.0
2621 Savage2019-09-01NaNNaNNaNNaN0.00.0
27A$AP Ferg2014-09-01NaNNaNNaNNaN0.00.0
28A$AP Ferg2014-10-01NaNNaNNaNNaN0.00.0
29A$AP Ferg2014-11-01NaNNaNNaNNaN0.00.0
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10485 rows × 8 columns

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" ], "text/plain": [ " primary_artist_name lag_report_date venue_capacity tix_price_min \\\n", "0 21 Savage 2017-07-01 NaN NaN \n", "1 21 Savage 2017-08-01 NaN NaN \n", "2 21 Savage 2017-09-01 NaN NaN \n", "3 21 Savage 2017-10-01 NaN NaN \n", "4 21 Savage 2017-11-01 NaN NaN \n", "5 21 Savage 2017-12-01 NaN NaN \n", "6 21 Savage 2018-01-01 NaN NaN \n", "7 21 Savage 2018-02-01 NaN NaN \n", "8 21 Savage 2018-03-01 NaN NaN \n", "9 21 Savage 2018-04-01 NaN NaN \n", "10 21 Savage 2018-05-01 NaN NaN \n", "11 21 Savage 2018-06-01 NaN NaN \n", "12 21 Savage 2018-07-01 NaN NaN \n", "13 21 Savage 2018-08-01 NaN NaN \n", "14 21 Savage 2018-09-01 NaN NaN \n", "15 21 Savage 2018-10-01 NaN NaN \n", "16 21 Savage 2018-11-01 NaN NaN \n", "17 21 Savage 2018-12-01 NaN NaN \n", "18 21 Savage 2019-01-01 NaN NaN \n", "19 21 Savage 2019-02-01 NaN NaN \n", "20 21 Savage 2019-03-01 NaN NaN \n", "21 21 Savage 2019-04-01 NaN NaN \n", "22 21 Savage 2019-05-01 NaN NaN \n", "23 21 Savage 2019-06-01 NaN NaN \n", "24 21 Savage 2019-07-01 NaN NaN \n", "25 21 Savage 2019-08-01 NaN NaN \n", "26 21 Savage 2019-09-01 NaN NaN \n", "27 A$AP Ferg 2014-09-01 NaN NaN \n", "28 A$AP Ferg 2014-10-01 NaN NaN \n", "29 A$AP Ferg 2014-11-01 NaN NaN \n", "... ... ... ... ... \n", "10455 ayokay 2019-09-01 12381.0 34.225 \n", "10456 kirstin 2017-05-01 12381.0 34.225 \n", "10457 kirstin 2017-06-01 12381.0 34.225 \n", "10458 kirstin 2017-07-01 12381.0 34.225 \n", "10459 kirstin 2017-08-01 12381.0 34.225 \n", "10460 kirstin 2017-09-01 12381.0 34.225 \n", "10461 kirstin 2017-10-01 12381.0 34.225 \n", "10462 kirstin 2017-11-01 12381.0 34.225 \n", "10463 kirstin 2017-12-01 12381.0 34.225 \n", "10464 kirstin 2018-01-01 12381.0 34.225 \n", "10465 kirstin 2018-02-01 12381.0 34.225 \n", "10466 kirstin 2018-03-01 12381.0 34.225 \n", "10467 kirstin 2018-04-01 12381.0 34.225 \n", "10468 kirstin 2018-05-01 12381.0 34.225 \n", "10469 kirstin 2018-06-01 12381.0 34.225 \n", "10470 kirstin 2018-07-01 12381.0 34.225 \n", "10471 kirstin 2018-08-01 12381.0 34.225 \n", "10472 kirstin 2018-09-01 12381.0 34.225 \n", "10473 kirstin 2018-10-01 12381.0 34.225 \n", "10474 kirstin 2018-11-01 12381.0 34.225 \n", "10475 kirstin 2018-12-01 12381.0 34.225 \n", "10476 kirstin 2019-01-01 12381.0 34.225 \n", "10477 kirstin 2019-02-01 12381.0 34.225 \n", "10478 kirstin 2019-03-01 12381.0 34.225 \n", "10479 kirstin 2019-04-01 12381.0 34.225 \n", "10480 kirstin 2019-05-01 12381.0 34.225 \n", "10481 kirstin 2019-06-01 12381.0 34.225 \n", "10482 kirstin 2019-07-01 12381.0 34.225 \n", "10483 kirstin 2019-08-01 12381.0 34.225 \n", "10484 kirstin 2019-09-01 12381.0 34.225 \n", "\n", " tix_price_max pct_sold num_shows gross_usd \n", "0 NaN NaN 0.0 0.0 \n", "1 NaN NaN 0.0 0.0 \n", "2 NaN NaN 0.0 0.0 \n", "3 NaN NaN 0.0 0.0 \n", "4 NaN NaN 0.0 0.0 \n", "5 NaN NaN 0.0 0.0 \n", "6 NaN NaN 0.0 0.0 \n", "7 NaN NaN 0.0 0.0 \n", "8 NaN NaN 0.0 0.0 \n", "9 NaN NaN 0.0 0.0 \n", "10 NaN NaN 0.0 0.0 \n", "11 NaN NaN 0.0 0.0 \n", "12 NaN NaN 0.0 0.0 \n", "13 NaN NaN 0.0 0.0 \n", "14 NaN NaN 0.0 0.0 \n", "15 NaN NaN 0.0 0.0 \n", "16 NaN NaN 0.0 0.0 \n", "17 NaN NaN 0.0 0.0 \n", "18 NaN NaN 0.0 0.0 \n", "19 NaN NaN 0.0 0.0 \n", "20 NaN NaN 0.0 0.0 \n", "21 NaN NaN 0.0 0.0 \n", "22 NaN NaN 0.0 0.0 \n", "23 NaN NaN 0.0 0.0 \n", "24 NaN NaN 0.0 0.0 \n", "25 NaN NaN 0.0 0.0 \n", "26 NaN NaN 0.0 0.0 \n", "27 NaN NaN 0.0 0.0 \n", "28 NaN NaN 0.0 0.0 \n", "29 NaN NaN 0.0 0.0 \n", "... ... ... ... ... \n", "10455 94.225 0.985 0.0 0.0 \n", "10456 94.225 0.985 0.0 0.0 \n", "10457 94.225 0.985 0.0 0.0 \n", "10458 94.225 0.985 0.0 0.0 \n", "10459 94.225 0.985 0.0 0.0 \n", "10460 94.225 0.985 0.0 0.0 \n", "10461 94.225 0.985 0.0 0.0 \n", "10462 94.225 0.985 0.0 0.0 \n", "10463 94.225 0.985 0.0 0.0 \n", "10464 94.225 0.985 0.0 0.0 \n", "10465 94.225 0.985 0.0 0.0 \n", "10466 94.225 0.985 0.0 0.0 \n", "10467 94.225 0.985 0.0 0.0 \n", "10468 94.225 0.985 0.0 0.0 \n", "10469 94.225 0.985 0.0 0.0 \n", "10470 94.225 0.985 0.0 0.0 \n", "10471 94.225 0.985 0.0 0.0 \n", "10472 94.225 0.985 0.0 0.0 \n", "10473 94.225 0.985 0.0 0.0 \n", "10474 94.225 0.985 0.0 0.0 \n", "10475 94.225 0.985 0.0 0.0 \n", "10476 94.225 0.985 0.0 0.0 \n", "10477 94.225 0.985 0.0 0.0 \n", "10478 94.225 0.985 0.0 0.0 \n", "10479 94.225 0.985 0.0 0.0 \n", "10480 94.225 0.985 0.0 0.0 \n", "10481 94.225 0.985 0.0 0.0 \n", "10482 94.225 0.985 0.0 0.0 \n", "10483 94.225 0.985 0.0 0.0 \n", "10484 94.225 0.985 0.0 0.0 \n", "\n", "[10485 rows x 8 columns]" ] }, "metadata": { "tags": [] }, "execution_count": 45 } ] }, { "cell_type": "markdown", "metadata": { "id": "Eoo4UrLUiaS4", "colab_type": "text" }, "source": [ "ARTIST NAME REFERENCE" ] }, { "cell_type": "code", "metadata": { "id": "XMIkrdV_iaS4", "colab_type": "code", "outputId": "4d134c33-9af6-4f57-8203-98eb570a3d19", "colab": {} }, "source": [ "set(full_data['primary_artist_name'])" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "{'21 Savage',\n", " 'A$AP Ferg',\n", " 'A$AP Mob',\n", " 'A$AP Rocky',\n", " 'A$AP Twelvyy',\n", " 'AC/DC',\n", " 'Adele',\n", " 'Alan Walker',\n", " 'Alicia Keys',\n", " 'Amy Shark',\n", " 'Arcade Fire',\n", " 'Au/Ra',\n", " 'Ayo & Teo',\n", " 'B. Smyth',\n", " 'BIA',\n", " 'Backstreet Boys',\n", " 'Barbra Streisand',\n", " 'Becky G',\n", " 'Beyoncé',\n", " 'Billie Marten',\n", " 'Billy Joel',\n", " 'Bleachers',\n", " 'Bob Dylan',\n", " 'Bring Me The Horizon',\n", " 'Britney Spears',\n", " 'Bruce Springsteen',\n", " 'Bryson Tiller',\n", " 'Buddy',\n", " 'Buddy Guy',\n", " 'Busta Rhymes',\n", " 'CNCO',\n", " 'Cage The Elephant',\n", " 'Calvin Harris',\n", " 'Cam',\n", " 'Camila Cabello',\n", " 'Chevelle',\n", " 'Chloe x Halle',\n", " 'Chris Brown',\n", " 'Christina Aguilera',\n", " \"Cosmo's Midnight\",\n", " 'Cousin Stizz',\n", " 'Craig David',\n", " 'Céline Dion',\n", " \"D'Angelo\",\n", " 'Daft Punk',\n", " 'Dave Gahan',\n", " 'Dave Matthews Band',\n", " 'David Gilmour',\n", " 'Davido',\n", " 'DeJ Loaf',\n", " 'Declan McKenna',\n", " 'Depeche Mode',\n", " \"Destiny's Child\",\n", " 'Dixie Chicks',\n", " 'Doja Cat',\n", " 'Earl Sweatshirt',\n", " 'Elle King',\n", " 'Elley Duhé',\n", " 'Enrique Iglesias',\n", " 'Era Istrefi',\n", " 'Faithless',\n", " 'Fifth Harmony',\n", " 'Fiona Apple',\n", " 'First Aid Kit',\n", " 'Foo Fighters',\n", " 'Foster The People',\n", " 'French Montana',\n", " 'Future',\n", " 'G-Eazy',\n", " 'GASHI',\n", " 'Gavin DeGraw',\n", " 'George Ezra',\n", " 'George Winston',\n", " 'GoldLink',\n", " 'Grace',\n", " 'Grace VanderWaal',\n", " 'Grizzly Bear',\n", " 'H.E.R.',\n", " 'HAIM',\n", " 'Harry Styles',\n", " 'Hozier',\n", " 'Isaiah',\n", " 'J Hus',\n", " 'Jack White',\n", " 'Jaded',\n", " 'Jain',\n", " 'James Arthur',\n", " 'Jazmine Sullivan',\n", " 'Jennifer Hudson',\n", " 'Jez Dior',\n", " 'Jidenna',\n", " 'Jimmy Eat World',\n", " 'John Legend',\n", " 'John Mayer',\n", " 'Jordan Bratton',\n", " 'Judas Priest',\n", " 'Juicy J',\n", " 'Justin Timberlake',\n", " 'Kaskade',\n", " 'Kent Jones',\n", " 'Kesha',\n", " 'Khalid',\n", " 'Kid Ink',\n", " 'King Los',\n", " 'Kings Of Leon',\n", " 'Kirk Franklin',\n", " 'Kodie Shane',\n", " 'Kygo',\n", " 'LCD Soundsystem',\n", " 'Labrinth',\n", " 'Lamb of God',\n", " 'Lecrae',\n", " 'Leikeli47',\n", " 'Leon Bridges',\n", " 'Lewis Del Mar',\n", " 'Little Mix',\n", " 'Lo Moon',\n", " 'London Grammar',\n", " 'Luke Christopher',\n", " 'MGMT',\n", " 'MISSIO',\n", " 'MUNA',\n", " 'Madeon',\n", " 'Mali Music',\n", " 'Mariah Carey',\n", " 'Mark Ronson',\n", " 'Martin Garrix',\n", " 'Mary Mary',\n", " 'Matthew Koma',\n", " 'Maxwell',\n", " 'Meghan Trainor',\n", " 'Michael Jackson',\n", " 'Miguel',\n", " 'Miley Cyrus',\n", " 'Modest Mouse',\n", " 'Moon Taxi',\n", " 'Morgan Saint',\n", " 'MØ',\n", " 'N.E.R.D',\n", " 'Nao',\n", " 'Nelly',\n", " 'Nicky Jam',\n", " 'Noah Cyrus',\n", " 'Nothing But Thieves',\n", " 'One Direction',\n", " 'OutKast',\n", " 'Ozzy Osbourne',\n", " 'P!nk',\n", " 'PRETTYMUCH',\n", " 'Passion Pit',\n", " 'Patti Scialfa',\n", " 'Patti Smith',\n", " 'Pentatonix',\n", " 'Pharrell Williams',\n", " 'Pink Floyd',\n", " 'Quinn XCII',\n", " 'Raphael Saadiq',\n", " 'Ray LaMontagne',\n", " 'Rick Ross',\n", " 'Ro James',\n", " 'Robbie Williams',\n", " 'Roger Waters',\n", " 'Russ',\n", " 'SZA',\n", " 'Sade',\n", " 'Sam Dew',\n", " 'Sara Bareilles',\n", " 'Shakira',\n", " 'Sigala',\n", " 'Skott',\n", " 'Solange',\n", " 'Superfruit',\n", " 'Susan Boyle',\n", " 'Swedish House Mafia',\n", " 'Syd',\n", " 'System Of A Down',\n", " 'TOMI',\n", " 'Tenacious D',\n", " 'The Chainsmokers',\n", " 'The Internet',\n", " 'The Neighbourhood',\n", " 'The Script',\n", " 'Three Days Grace',\n", " 'Tom Odell',\n", " 'Tom Walker',\n", " 'Toni Romiti',\n", " 'Tony Bennett',\n", " 'Tove Styrke',\n", " 'Train',\n", " 'Travis Scott',\n", " 'Tyler, The Creator',\n", " 'Usher',\n", " 'Vanic',\n", " 'WALK THE MOON',\n", " 'Wet',\n", " 'WizKid',\n", " 'Wolf Alice',\n", " 'Yo Gotti',\n", " 'Yung Bleu',\n", " 'ZAYN',\n", " 'Zara Larsson',\n", " 'ayokay',\n", " 'kirstin'}" ] }, "metadata": { "tags": [] }, "execution_count": 188 } ] }, { "cell_type": "code", "metadata": { "id": "12TMzZfViaS6", "colab_type": "code", "outputId": "0a993472-51a8-4ca8-fd22-3ef12d1a9939", "colab": {} }, "source": [ "unnested = ticket_sum.reset_index()\n", "unnested[unnested['primary_artist_name']=='Khalid']" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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primary_artist_namelag_report_dateNum ShowsGross USDVenue CapacityTicket Price MinTicket Price MaxPercentage Sold
5251Khalid2016-08-010.00.00.00.000.000.00
5252Khalid2016-09-010.00.00.00.000.000.00
5253Khalid2016-10-010.00.00.00.000.000.00
5254Khalid2016-11-010.00.00.00.000.000.00
5255Khalid2016-12-010.00.00.00.000.000.00
5256Khalid2017-01-010.00.00.00.000.000.00
5257Khalid2017-02-012.017625.01175.030.0033.002.00
5258Khalid2017-03-012.017625.01175.030.0033.002.00
5259Khalid2017-04-013.031125.01925.048.0056.003.00
5260Khalid2017-05-019.0955332.027273.0242.00364.008.72
5261Khalid2017-06-0113.02939943.067966.0410.50592.5012.51
5262Khalid2017-07-0118.03209470.079099.0521.50769.5017.51
5263Khalid2017-08-0122.03583261.092565.0623.00908.5021.48
5264Khalid2017-09-0123.03672520.095772.0648.00962.5022.38
5265Khalid2017-10-0124.05282769.0113213.0743.001112.5023.28
5266Khalid2017-11-0125.05334425.0118086.0752.001127.5024.22
5267Khalid2017-12-0126.06920625.0134578.0797.001352.5025.22
5268Khalid2018-01-0127.07408066.0140538.0832.001462.5026.22
5269Khalid2018-02-0127.07408066.0140538.0832.001462.5026.22
5270Khalid2018-03-0127.07408066.0140538.0832.001462.5026.22
5271Khalid2018-04-0128.07556751.0146922.0855.001505.5026.99
5272Khalid2018-05-0144.012967469.0245867.01496.152294.1040.53
5273Khalid2018-06-0148.014089309.0263068.01603.102466.9543.53
5274Khalid2018-07-0148.014089309.0263068.01603.102466.9543.53
5275Khalid2018-08-0148.014089309.0263068.01603.102466.9543.53
5276Khalid2018-09-0149.014472266.0270690.01648.102531.9544.53
5277Khalid2018-10-0149.014472266.0270690.01648.102531.9544.53
5278Khalid2018-11-0150.016319695.0286811.01690.103288.9545.53
5279Khalid2018-12-0152.017773959.0305273.01831.503620.4547.34
5280Khalid2019-01-0152.017773959.0305273.01831.503620.4547.34
5281Khalid2019-02-0152.017773959.0305273.01831.503620.4547.34
5282Khalid2019-03-0152.017773959.0305273.01831.503620.4547.34
5283Khalid2019-04-0152.017773959.0305273.01831.503620.4547.34
5284Khalid2019-05-0152.017773959.0305273.01831.503620.4547.34
5285Khalid2019-06-0156.021054025.0356758.02021.343980.1951.02
5286Khalid2019-07-0163.027008151.0430941.02255.044511.1456.86
5287Khalid2019-08-0165.028661168.0455703.02323.494699.5958.83
5288Khalid2019-09-0165.028661168.0455703.02323.494699.5958.83
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" ], "text/plain": [ " primary_artist_name lag_report_date Num Shows Gross USD \\\n", "5251 Khalid 2016-08-01 0.0 0.0 \n", "5252 Khalid 2016-09-01 0.0 0.0 \n", "5253 Khalid 2016-10-01 0.0 0.0 \n", "5254 Khalid 2016-11-01 0.0 0.0 \n", "5255 Khalid 2016-12-01 0.0 0.0 \n", "5256 Khalid 2017-01-01 0.0 0.0 \n", "5257 Khalid 2017-02-01 2.0 17625.0 \n", "5258 Khalid 2017-03-01 2.0 17625.0 \n", "5259 Khalid 2017-04-01 3.0 31125.0 \n", "5260 Khalid 2017-05-01 9.0 955332.0 \n", "5261 Khalid 2017-06-01 13.0 2939943.0 \n", "5262 Khalid 2017-07-01 18.0 3209470.0 \n", "5263 Khalid 2017-08-01 22.0 3583261.0 \n", "5264 Khalid 2017-09-01 23.0 3672520.0 \n", "5265 Khalid 2017-10-01 24.0 5282769.0 \n", "5266 Khalid 2017-11-01 25.0 5334425.0 \n", "5267 Khalid 2017-12-01 26.0 6920625.0 \n", "5268 Khalid 2018-01-01 27.0 7408066.0 \n", "5269 Khalid 2018-02-01 27.0 7408066.0 \n", "5270 Khalid 2018-03-01 27.0 7408066.0 \n", "5271 Khalid 2018-04-01 28.0 7556751.0 \n", "5272 Khalid 2018-05-01 44.0 12967469.0 \n", "5273 Khalid 2018-06-01 48.0 14089309.0 \n", "5274 Khalid 2018-07-01 48.0 14089309.0 \n", "5275 Khalid 2018-08-01 48.0 14089309.0 \n", "5276 Khalid 2018-09-01 49.0 14472266.0 \n", "5277 Khalid 2018-10-01 49.0 14472266.0 \n", "5278 Khalid 2018-11-01 50.0 16319695.0 \n", "5279 Khalid 2018-12-01 52.0 17773959.0 \n", "5280 Khalid 2019-01-01 52.0 17773959.0 \n", "5281 Khalid 2019-02-01 52.0 17773959.0 \n", "5282 Khalid 2019-03-01 52.0 17773959.0 \n", "5283 Khalid 2019-04-01 52.0 17773959.0 \n", "5284 Khalid 2019-05-01 52.0 17773959.0 \n", "5285 Khalid 2019-06-01 56.0 21054025.0 \n", "5286 Khalid 2019-07-01 63.0 27008151.0 \n", "5287 Khalid 2019-08-01 65.0 28661168.0 \n", "5288 Khalid 2019-09-01 65.0 28661168.0 \n", "\n", " Venue Capacity Ticket Price Min Ticket Price Max Percentage Sold \n", "5251 0.0 0.00 0.00 0.00 \n", "5252 0.0 0.00 0.00 0.00 \n", "5253 0.0 0.00 0.00 0.00 \n", "5254 0.0 0.00 0.00 0.00 \n", "5255 0.0 0.00 0.00 0.00 \n", "5256 0.0 0.00 0.00 0.00 \n", "5257 1175.0 30.00 33.00 2.00 \n", "5258 1175.0 30.00 33.00 2.00 \n", "5259 1925.0 48.00 56.00 3.00 \n", "5260 27273.0 242.00 364.00 8.72 \n", "5261 67966.0 410.50 592.50 12.51 \n", "5262 79099.0 521.50 769.50 17.51 \n", "5263 92565.0 623.00 908.50 21.48 \n", "5264 95772.0 648.00 962.50 22.38 \n", "5265 113213.0 743.00 1112.50 23.28 \n", "5266 118086.0 752.00 1127.50 24.22 \n", "5267 134578.0 797.00 1352.50 25.22 \n", "5268 140538.0 832.00 1462.50 26.22 \n", "5269 140538.0 832.00 1462.50 26.22 \n", "5270 140538.0 832.00 1462.50 26.22 \n", "5271 146922.0 855.00 1505.50 26.99 \n", "5272 245867.0 1496.15 2294.10 40.53 \n", "5273 263068.0 1603.10 2466.95 43.53 \n", "5274 263068.0 1603.10 2466.95 43.53 \n", "5275 263068.0 1603.10 2466.95 43.53 \n", "5276 270690.0 1648.10 2531.95 44.53 \n", "5277 270690.0 1648.10 2531.95 44.53 \n", "5278 286811.0 1690.10 3288.95 45.53 \n", "5279 305273.0 1831.50 3620.45 47.34 \n", "5280 305273.0 1831.50 3620.45 47.34 \n", "5281 305273.0 1831.50 3620.45 47.34 \n", "5282 305273.0 1831.50 3620.45 47.34 \n", "5283 305273.0 1831.50 3620.45 47.34 \n", "5284 305273.0 1831.50 3620.45 47.34 \n", "5285 356758.0 2021.34 3980.19 51.02 \n", "5286 430941.0 2255.04 4511.14 56.86 \n", "5287 455703.0 2323.49 4699.59 58.83 \n", "5288 455703.0 2323.49 4699.59 58.83 " ] }, "metadata": { "tags": [] }, "execution_count": 33 } ] } ] }