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Analyzing second-hand concert ticket price patterns
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# import modules\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.ticker as tkr\n",
"import matplotlib.dates as mdates\n",
"from matplotlib import cm\n",
"from itertools import cycle\n",
"from matplotlib.lines import Line2D\n",
"import numpy as np\n",
"import pandas as pd\n",
"from datetime import datetime\n",
"from scipy.optimize import curve_fit\n",
"from scipy.stats import linregress, sem\n",
"from scipy.stats import norm\n",
"import seaborn as sns\n",
"%matplotlib inline\n",
"\n",
"# use fivethirtyeight plot style\n",
"plt.style.use('fivethirtyeight')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# loading multiple csv into python list\n",
"# the code below will depend on the file path of the data files on your machines\n",
"lst = []\n",
"path = 'c:/users/mra/desktop/admin/chart-it/concert tix/ticket_prices_final.csv' \n",
"frame = pd.read_csv(path, header = 0, low_memory = False) \n",
"lst.append(frame)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# use concat method to convert python list into pd dataframe\n",
"concert_tix = (pd.concat(lst, ignore_index = True))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# set 'Date' as dataframe index\n",
"concert_tix['Date'] = pd.to_datetime(concert_tix['Date'], infer_datetime_format = True)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# drop empty data points\n",
"concert_tix = concert_tix.dropna()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# strip '$' sign, extra space, and comma separator from 'Price' column before converting to float\n",
"concert_tix['Price'] = concert_tix['Price'].map(lambda x: x.lstrip('$').rstrip(' ').replace(',',\"\"))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# strip '$' sign, extra space, and comma separator from 'Price' column before converting to float\n",
"concert_tix['Section'] = concert_tix['Section'].map(lambda x: x.lower())"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: FutureWarning: convert_objects is deprecated. Use the data-type specific converters pd.to_datetime, pd.to_timedelta and pd.to_numeric.\n",
" from IPython.kernel.zmq import kernelapp as app\n"
]
}
],
"source": [
"# convert 'Price' data from string to number\n",
"concert_tix['Price'] = concert_tix['Price'].convert_objects(convert_numeric=True)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# convert 'Show Date' from string to datetime object\n",
"concert_tix['Show Date'] = pd.to_datetime(concert_tix['Show Date'], infer_datetime_format = True)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# add new column 'Days Before Show'\n",
"concert_tix['Nanoseconds Before Show'] = concert_tix['Date'] - concert_tix['Show Date']"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# add new column 'date_int' showing 'Days Before\n",
"concert_tix['Days Before Show'] = (concert_tix['Nanoseconds Before Show'] / np.timedelta64(1, 'D')).astype(int)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# stubhub data shows sales day after the show; this is an error due to time zone difference\n",
"concert_tix[\"Days Before Show\"] = concert_tix[\"Days Before Show\"].replace(to_replace = 1, value = 0)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# set 'Date' as dataframe index\n",
"concert_tix = concert_tix.set_index(\"Date\")"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# add sample size column by number of shows on any given day (i.e., days before show)\n",
"concert_tix['Sample Size - Number of Shows on Day'] = concert_tix.groupby(['Days Before Show'])['Show'].transform('nunique')"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# filter dataframe to only inlclude sales within a certain window before show date\n",
"concert_tix = concert_tix[concert_tix['Days Before Show'] > -90]"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# add outlier prices (5th and 95th percentiles) by section\n",
"concert_tix['95th %tile'] = concert_tix.groupby(['Show', 'City', 'Section'])['Price'].transform(np.percentile, 95)\n",
"concert_tix['5th %tile'] = concert_tix.groupby(['Show', 'City', 'Section'])['Price'].transform(np.percentile, 5)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# filter out outliers\n",
"concert_tix = concert_tix[(concert_tix['Price'] <= concert_tix['95th %tile']) & \\\n",
" (concert_tix['Price'] >= concert_tix['5th %tile'])]"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# since each transaction may contain more than one ticket, this transformed each datapoint from 'transaction' to 'ticket' \n",
"concert_tix = pd.DataFrame([concert_tix.reset_index().ix[i] \n",
" for i in concert_tix.reset_index().index \n",
" for _ in range(concert_tix.reset_index().ix[i]['Tickets'])])"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# add z-score column based on show/city/section ticket prices\n",
"zscore = lambda x: (x - x.mean()) / x.std()\n",
"\n",
"concert_tix['Ticket Price Z-score'] = concert_tix.groupby(['Show','City','Section'])['Price'].transform(zscore)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# rank calculation function\n",
"ranks = lambda x: (x.rank() / len(x))"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# add percentile column based on show/city/section ticket prices\n",
"concert_tix['Percentile'] = (1 - concert_tix['Ticket Price Z-score'].apply(norm.sf))\n",
"concert_tix['Percentile'] = concert_tix.groupby(['Show','City','Section'])['Percentile'].transform(ranks)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# add sample size columns by section\n",
"concert_tix['Sample Size - Sales per Sections'] = concert_tix.groupby(['Show','City','Section'])['Price'].transform('count')"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# filter dataframe to exclude sections and days with small sample sizes\n",
"# concert_tix = concert_tix[(concert_tix['Sample Size - Sales per Sections'] > 20)]\n",
"# concert_tix = concert_tix[(concert_tix['Sample Size - Number of Shows on Day'] > 5)]"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
" from IPython.kernel.zmq import kernelapp as app\n"
]
},
{
"data": {
"text/plain": [
"Show City \n",
"Ed Sheeran Washington, DC 0.104214\n",
"Billy Joel NYC 0.100652\n",
"Foo Fighters Los Angeles 0.080787\n",
"Chris Brown Anaheim, CA 0.073663\n",
"Madonna NYC 0.054462\n",
"ASAP Rocky NYC 0.052349\n",
"Ed Sheeran Cuyahoga, OH 0.049571\n",
"Empire of the Sun Los Angeles 0.044379\n",
"AC/DC San Francisco 0.043896\n",
"Garth Brooks Dallas 0.041360\n",
"Ariana Grande NYC 0.039911\n",
" Houston 0.033993\n",
"Ed Sheeran Toronto 0.032544\n",
"Of Monsters and Men NYC 0.025722\n",
"Empire of the Sun San Francisco 0.024876\n",
"Tim McGraw San Francisco 0.020650\n",
"Alabama Shakes Columbia, MD 0.019744\n",
"Armin Van Buuren Washington, DC 0.017691\n",
"Stromae Washington, DC 0.016484\n",
"ASAP Rocky Chicago 0.014370\n",
"Alabama Shakes Toronto 0.013948\n",
"Counting Crows San Francisco 0.013283\n",
"Def Leppard Phoenix 0.012378\n",
"ASAP Rocky Toronto 0.010747\n",
"Nick Jonas Orland 0.010687\n",
"Stromae Boston 0.010627\n",
" Toronto 0.008695\n",
" Chicago 0.008151\n",
"Chris Cornnell San Diego 0.007306\n",
"R-Kelly Philadelphia 0.005978\n",
"Of Monsters and Men Columbia, MD 0.003804\n",
"Nick Jonas Tempe 0.003079\n",
"Name: Price, dtype: float64"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# sample size by show for dataframe\n",
"concert_tix.groupby(['Show','City']).count().sort('Price', ascending=False)['Price'] \\\n",
"/ concert_tix.groupby(['Show', 'City']).count().sort('Price', ascending=False)['Price'].sum()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# create groupby objects for plots; filtered to exclude days with less than four different active sections\n",
"concert_tix_groupby = concert_tix.groupby(['Days Before Show'])['Ticket Price Z-score'].mean()\n",
"concert_tix_groupby_percentile = concert_tix.groupby(['Days Before Show'])['Percentile'].mean()\n",
"\n",
"# this groupby object is of the standard errors and will be used to plot the error bars \n",
"concert_tix_groupby_sem = concert_tix.groupby(['Days Before Show'])['Ticket Price Z-score'].apply(sem).reset_index()['Ticket Price Z-score'].interpolate(method='values').mul(1.96)\n",
"concert_tix_groupby_percentile_sem = concert_tix.groupby(['Days Before Show'])['Percentile'].apply(sem).reset_index()['Percentile'].interpolate(method='values').mul(1.96)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# function to calculate best line fit for the charts below\n",
"def func3(x, a, b, c, d):\n",
" return a*x**3 + b*x**2 +c*x + d\n",
"\n",
"def func2(x, a, b, c):\n",
" return a*x**2 + b*x +c\n",
"\n",
"def func1(x, a, b):\n",
" return a*x + b"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(-90, 0)"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\matplotlib\\collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
" if self._edgecolors == str('face'):\n"
]
},
{
"data": {
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VXstms9l48803OXXqFFqtlqlTp9KgQQPH9du3b2flypWoVCoeeOABBg0aVKHH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\nm4iIlBQFm4iIlBQFm4iIlBQFm4iIlJSfUMHrkVooGbkAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x91b3710>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Plot scatter plot of 'ticket price z-score' mean against 'days before show'\n",
"\n",
"x = concert_tix_groupby.reset_index()['Days Before Show']\n",
"y = concert_tix_groupby.reset_index()['Ticket Price Z-score']\n",
"\n",
"popt, pcov = curve_fit(func3, x, y)\n",
"\n",
"ax1 = concert_tix_groupby.reset_index().interpolate(method='values').plot(kind='scatter', x='Days Before Show', y='Ticket Price Z-score')\n",
"plt.plot(x, func3(x, *popt))\n",
"ax1.set_xlim(-90,0)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(-90, 0)"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\matplotlib\\collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
" if self._edgecolors == str('face'):\n"
]
},
{
"data": {
"image/png": 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MixcvJioqilGjRlX6OLt27aJ///4AdOnShdTU1FK3p6am8u6775KVlcXgwYO5\n4447qvRkGppgmW9VVVXpmvsty8nbf9hIySl79YxQnYa/J4by98QwwstZGaAmaits1PB3EqIixe/j\nfKuTJtaD5LRNoKDEAL9DeW4e+MnCawOjMPzVY1f8uj/39V/d94NPATZ//nx69OjBvHnz8Hg8rFix\nAo1Gw8SJE7HZbKxevdqnALPZbJjNZ5cx0Wq1eDwe78oeV111FTfeeCPh4eE89thjJCYmMnjw4Eof\nNy0tzZenUadqq0aDVsvDo1sDoLiySUs7XaPHC8S+LGspm+zs7FIHl48VaFmTaeI3a9mrYoRoFIZG\nO7m2iYMInYXjh2qr2rMyq3iSZTW8LkHq9Dc11OmPGku+j3UuN62PHcPTrQ17bWd7QI7Z3Ez4/jRN\n0zIwuFzcMyIRs86Kx1POcOG/tGvXzqcafAqwP/74gxdeeMEbOCVdeumlrF271qeNhYeHY7PZvJdL\nhhfAmDFjvAE3aNAg9u7d61OA+fpk60paWlrQ1wiBrXPyaFOplmPxsN6T+W7e3Wtjw5GCMudxaYD+\njZw80OcCYsOC97Tn8jf3L6nTf/xZY6n38agOtImPYuYvuWw+eXb1m+xCDbkXxtE0PYMl6/b7dSCU\nTwFmNBpLBU9JFosFo9G3Yrp3705ycjLDhg1j9+7dpXai1Wpl7NixrFy5EpPJxC+//MLIkSN9elyh\nPud2zeU5PXyYls8nB/PLncs1sLmB8R3NuE8eDOrwEqKhKKuLfWafRjy3/Qw//Hl2QJnboCezXQKR\nx4/7dfs+BVj//v15++236dq1K7Gxsd7rrVYrH3zwAX379vVpY0OHDmXr1q2MHz8egOnTp7Nhwwbs\ndjtJSUlMnjyZiRMnotfr6du3LwMGDKjGUxJqERVhxOFW+Hd6Ph+m2cgrLHtIfJdoPfd2CqfbX2uu\npVWwTrDa58QJoTbnvtf0Wg0zekXy4q9n+ObY2RDz6PWcSkzAqtER5adt+xRg999/P+PHj2fMmDG0\nbdsWgNdee807zH3WrFk+bUyj0TBlypRS1yUkJHh/vvrqq7n66qt9eqz6rCF8CLsVhW+OFrAs1cYp\ne9lNrpZmHfd2NDMo1rdJyA1xTpwQwShEq+HJnpHotXn890iB9/pcFzy42cLrg6KIC6/5SvY+Ddtq\n3rw5K1as4NZbb0Wr1RIfH4/D4eDaa6/lgw8+kJNZ+tGejBymLdnOtCXb2ZORU9fl+J2iKGw95eDe\nTTnM/jV7HKuLAAAgAElEQVSvzPBq+tdcrneGNmbwBUafwkvtc+KEqG90Gg2PXRzBiITSSw+eLvDw\n8GYLf+a7a7wNnyMwKiqKu+66i4kTJwJFIwrtdjtNmzatcRGiSH1f+WGfpZBFf1jZUc4JJcNDNIxt\nF8bo1mGYQoJrArIQouq0Gg0Pd4vA7aFUS+yk3cNDm3N4fWA0zWtwPNunFpjD4WDGjBmlJizv3r2b\nESNGMHv27GqtyiEajj9tbp7fnsu9P+SUGV56LdzUJpQPr2jCre3CqxVessKFEMFJq9Hw6MURXBVf\nuiV2It/Do1ssZBdUPKS+Ij61wBYtWkRycjL333+/97ouXbrw2GOPsWDBApo2bco999xT7SJEkfIm\nJqv1mNgZp4cP9tn4tIJV4ofFGRnXwcwF4TUfVSgrXAgRnHQaDU/0iMCtKHxbYmDHEZubx362MG9Q\nFBHVWIjApwD75ptveOCBB0hKSvJeZzabGT16NIqi8OGHH0qA+cm5H8L+GpgQyBB0uBU+PZjPB2n5\nWMsZWdizqZ4Jncy0jyp7onJ1SXAJEZx0Gg1P9ojE5TnDphJD7PefcfHk1lzm9o8itIq9Lz5FXm5u\nLhdccEGZt8XHx5OZmVmljYqKFS+W6a+BCYEaGOJRFDYcsXPbxiwW/WErM7zaROh4qX8jXhkQ5ffw\nEkIEtxCthmm9IunbzFDq+pTsQmZsy8VZzmmRyuNTgLVq1Yqvv/66zNu+//57WrZsWaWNisAJ1Oi8\nbacc3FPByMJmoVqmXBzBkqGN6dvMt5GFQojAq+2zheu1Gp7t3YiujUt/gd2W6WTWr2fwVOHMzj51\nId56663MmDEDi8XC0KFDady4MTk5OXz//ff88MMPPP3001V7BsIntXVMTKPxX5diWm4hi/+w8ktm\n+SML/9EujFFtwvy2SrwQonYEai6lKUTDrH6NeOgnC+lnzg4C/P64gyZGK//sGuHT4/gUYFdffTX5\n+fm8/fbbJCcne6+Pioriscce49prr61i+YGh1sEPJdX0mNi5IfivmzpxPCu/xi/SE/lu3km18fXR\nstcsDNHADa1D+Uf7cBoZav/EdkKImgn0NJ4IvZa5A6L41485HLGdnRP2yUG7fwNs7969JCUlkZSU\nxOHDh7FYLJjNZlq1aoVOF5xr0tWnVRmKX0DVfYGVDEGAaUu2V/tFmuf08EFaPmsqWLPwijgj4/00\nsrAu1IcvPkKoQbSxKMQmJ+eQ5aj6cHqfvhpPnjyZL7/8Eo1GQ0JCAt27dycxMTFow0tWZThf8cCQ\n6nK4FVam5zP22yxW7i87vHo01bNoSDTTezVSbXjV95VQhChPXc2ljA3TMad/I8KrMf/TpwDT6/VE\nRflr+UVRXf54gVX1MTyKwldH7Ny+MYuFf1jLXHC3dYSOOf0a8eqAKDqoeGShfPERDV1xb83z9/QK\naK9V20Z6nuvTiKpmmE9diJMmTeL111/HYrHQvn17wsLCzrtPMK2HqNYzFfvCH5N1fX2MbaccLPrD\nxv4zZa+00tSk5e4O4VzdwoRORhUKUS/U1WdlzxgDT/aM5LntZ3z+HZ8CbNasWXg8Hp599tkyb9do\nNPz8888+bzQQ6vOqDP54PhU9xj5L0cjC7Q1szcL6/MVHCDW4Is5EFUbR+xZgU6dOrW49dUo+fKom\n06nh39tzSy31UlKIBka2CuW29uFEGevnyML6/MVHCDWIc9sBU6X3Ax8DbMSIETWpRwQ5i8PDin02\nPjsYgZuyw+vyv0YWXqjSwRlVIcElRN0oPg49/+GBPt3f59OpuN1uvv32W7Zu3UpmZiaPPPIIv//+\nO506daJVq1bVrVfUIbtLYdWBfP6dnk++SwHO7w7s2VTPvZ3Mqh6cUZIMkRei/vApwKxWKw8++CC7\nd++mSZMmZGdnk5+fz4YNG5g7dy6LFy+mffv2tV1rUFLjB6LLo7A+w87yffnklDP3IjEyhPs6hdMn\nxrezIatBfZobKER9VHwc2lc+HchYsGABR48e5Z133mHt2rUoioJGo+G5556jZcuWLFq0qNoFq5na\n5gx5FIWNxwq447tsXtttLTO8modqeapHJHN7htE+lHoTXjJEXgh1qMoXS58C7LvvvmPChAl07ty5\n1PWRkZHceeed7N69u2oV1gNq+kBUFIX/nXJw3w85PLv9DMds55/KO1Kv4aZmdt6/vAktPHZmLN2h\nmmAWQjRMPgWYzWajefPmZd5mMpkoKCgo8zZR937PLuThLRYe/zmXtNzz53MZdfCPdmF8NKwJVzVx\nYs93qiaYwfeVs+WMzULUPz4dA0tMTGT9+vUMGDDgvNuSk5NJTEz0e2HBLtjnDB0842JpqpWfTjjL\nvF2rgetamrjzonCamNQ5srCqx7RkiLwQ9YtPATZu3DgeffRRLBYLQ4YMAWDbtm18+umnfP7557zw\nwgu1WmSwCsYPxD9tbpbvtfFVOavEA1x2oZFxHcKJN5/981vyHOgM5qAP5mLVXdg4GJ+LEKJ6fAqw\nSy65hOeff5433niDV155BYD58+cTHR3Nk08+yRVXXFGrRfpLbYwYDJYPxNMFblbsy2d9hh1XOcnV\nO0bPPR3NXHTOkPjSLRmTT8GsxtGXQoj6pdIAS0lJ4cSJE7Ro0YIvvviCjIwMVZxO5VxldTfVhw9h\ni8PDv9OLTm/iLOdsBB2jQ7i3o5keTQ3n3VadlkwwDEdXS0tRCFF7yg2wvLw8HnrooVIjDLt168bz\nzz9P9+7dA1Kcv5z7Ib18fRq3DW/Hos/UOycor9DDqv35rNpvx+4uu8nVKkLH+A5mBsX6by5XoE96\nV5Fg7MIVQgROuaMQFy1axN69e7n33nt57bXXePDBBzl06FC9ON7V46ImLPpMPSPtSsp3efgwzcbY\nb7J4f19+meF1QVjRXK5lQxsz+AJjheGl9tF5NT3PmRBCvcptgSUnJzNp0iRuueUWAAYOHEizZs2Y\nNm0adrud0NDQgBVZU+d2N/W+qCk/7jpZx1VVTYFL4bNDdj5Ot5HrLLvF1cSo5faLwrm2pQm91vcW\nV3FLJjs7mzaVtESl604IESzKDbCsrCw6diy9pEePHj3weDycOHGC1q1b13px/nRud5NaPoQdboW1\nh+x8lF7+sk+NDBrGtg1nZKvQap/eJCrCSOYJq0/3la47IUQwKDfAXC4Xen3p0WqRkZEAOJ1lzy0K\ndiU/bIP9Q9jhVliXYeejtHyyygmu8BANN7cNY3SbUMJCAnt6k2DcZ0KIhsXn1ehLUqpyxrEgFowf\nwr4EV1iIhtFtQvl7mzAiDPXzvFxCCFGZKgVYfVnYNRgVuBS+yLDzcXo+2eUEl0kHo1qHMaZtGI0C\nHFz1YcqBEKJ+qTDAZs+eTVhYmPdyccvrhRde8A7iKF6Z/u233650Yx6Phzlz5pCeno7BYGDq1KnE\nx8efd79Zs2bRqFEjJk+eXKUno0b5Lg9rD9lZmZ5PTjmDM4y6ojMh39I2nOg6OBNyMMz7EkKIc5Ub\nYD169PD5el9bZps2bcLlcrFs2TJSUlKYN28eL7/8cqn7rFmzhv3799OrVy+fHlOt8go9fHrQzuoD\n+ZypILiSWoUxJjGMxqa66SoMpnlfQghRUrkBVhvn+Nq1axf9+/cHoEuXLqSmppa6/bfffuP333/n\nhhtuICMjw+/bDwYWh4fVB/L59KAdWzlrPpl0cH2rUG5ODK+z4BJCiGBXrUEc1WWz2TCbzd7LWq0W\nj8eDVqvl9OnTLF26lJdeeolvvvmmSo+blpbm71L97uc/0vk6y0iyxYBTKbvFatQqXB7t4MrGTiJC\ncsk6AlkBrvPcfanVarlnRCJL1u0H4J4RiWSdOkrmiXLWrSqHVqtFE1LUHa248vF4qvb7ldUZjNRQ\nI0id/qaGOoO9xnbt2vl0v4AGWHh4ODabzXu5OLwAvv32WywWCw899BBZWVkUFBTQqlUrrrvuukof\n19cnWxcy8lws3nGCrWcMlLPiE+EhGka1CeXGNoEfnFFSWlpaufvy+XuigOJBHGWfG64i/jyOVlGd\nwUINNYLU6W9qqFMNNfoqoAHWvXt3kpOTGTZsGLt37y61E8eMGcOYMWMAWLduHRkZGT6FV7BKyS7k\n43Qbm084UTh/EV0omoB8U5swklqHYtYHd1dhTY55yXE0IURtCGiADR06lK1btzJ+/HgApk+fzoYN\nG7Db7SQlJZW6rxqH7HsUhS0nnXycnk9KdmG592tq0jImMYwRCaE47E5cBYWglw/zc8nQfSFERQIa\nYBqNhilTppS6LiEh4bz7jRgxIlAl+UWBS2HD0QJW78/niM1d7v3iw3Xc0jaMK+NNGHSaBjM8vTpL\ndzWUfSOEqL6ABlh9k1Xg5rNDdj4/ZC93KDxAgsnFXV0ac8kFRnR/tSwbWrdaVZbuamj7RghRPRJg\n1bDXUsgnB+xsPFZQ7tmPAfo2M3BL2zDCszNof+GFgSswSEkACSH8SQLMRy6Pwo8nHHxywM7uCo5v\n6TRweZyRmxPDSWxUtHvTcs6/n5pWxA802TdCCF9IgFUiq8DN+owC1mbYOV1Q/twls17D3xJCGdU6\nlJhQnU+PHewr4tcl2TdCiMpIgJVBURR2Zxfy+SE7m447KuwmjAvXMbp1KMNbmqp1ShP5cC6f7Bsh\nREUkwErIK/Tw9ZGi1tahvPJHEwL0aqpndJsw+jc3oFXhkH8hhFC7Bh9gxa2t9YcL+P54AY4Kcsug\nBXNOLo1zcxnfPZGOsdJCEEKIutJgAyzH4eGrIwWsP2znsLXi1lZ8uI6rL9Cz+as/yDtTQAEytFsI\nIepagwqwQo/Czyed/N8ROz+fdJa7NiGAVgODY41c3yqUnk31nLE62VrDBWhBVpcQQgh/qfcBpigK\nf+S4+PpoARuPF1Q44RigWaiWES1DuTbBRFPT2dGE/hjaHajVJSQkhRANQb0NsCNWF98ec/D10QKO\nVbC8ExTN3RoUa+S6BBO9Ywze1TLOVZOh3YFaXUKWYBJCNBT1KsD+zHfz3bECNh5zkH7GVen9W0Xo\nGN7CxFXxoT6fODKYWzWyBJMQoiGpNwFW6FEY/312uWc5Lhah13BFnInhLU1c1CgkYKvey+oSQgjh\nX/UmwPRaDYNijXx1tKCM22BAcyNXxpvo18yAQVc387Zqe3UJCUkhRENSbwIM4LK4swGmBS5uqufy\nOBOXXmAkog7PdFxSbQeKLMEkhGgo6lWA9Y4x0LeZgf7NDVx6gZEmJt/WJKxvJLiEEA1BvQowvVbD\nS/2j6roMIYQQARAc/WpCCCFEFUmACSGEUCUJsApY8hzeVS2EEEIEl3p1DMyfZEULIYQIbtICK0PJ\nFS0sVmfRz9ISE0KIoCIBJoQQQpUkwMpQvKJFlNlAlNkgK1oIIUQQkmNg5ZAVLYQQIrhJgFXAH8Fl\nyXOgM5j9UI0QQoiSJMBqUemRjCYZySiEEH4kx8BqiYxkFEKI2iUBJoQQQpUkwGqJjGQUQojaJcfA\nalHxSMbs7GzayPEvIYTwq4AGmMfjYc6cOaSnp2MwGJg6dSrx8fHe2zdu3Mj777+PRqNh+PDhjBkz\nJpDl1YqoCCOZJ6x1XYYQQtQ7Ae1C3LRpEy6Xi2XLljF58mTmzZvnvc3tdrNgwQIWLFjAsmXLWL16\nNbm5uYEsTwghhIoEtAW2a9cu+vfvD0CXLl1ITU313qbT6Vi1ahVarZasrCw8Hg96vT6Q5flF8UhD\nOd4lhBC1K6AtMJvNhtl8dlKvVqvF4/GUuvzdd99x22230atXL0wmUyDLq7E9GTlMW7KdaUu2sycj\np67LEUKIek1jsViUQG1s3rx5dOnShWHDhgEwYsQI1q1bd979FEVh5syZ9O7dmxEjRlT6uGlpaX6v\ntap0BjOvfnIQi9UJQJTZwMOjW+N2yvEvIYSoinbt2vl0v4B2IXbv3p3k5GSGDRvG7t27SxVptVp5\n5JFHmD9/Pnq9ntDQULRa3xqIvj7Z2lTUdXiw1HWNGzcmKuIC0tLSgqLGykid/qOGGkHq9Dc11KmG\nGn0V0AAbOnQoW7duZfz48QBMnz6dDRs2YLfbSUpK4pprruG+++5Dp9PRvn17rrnmmkCWVyPF875K\nngRTjoMJIUTtCWiAaTQapkyZUuq6hIQE789JSUkkJSUFsiS/khXshRAicGQis59JcAkhRGDIUlJC\nCCFUSQJMCCGEKtWrALPkOWp0ypKa/r4QQojAqTfHwEqfPLJjlU8eWdPfF0IIEVj1ogVW05NHyskn\nhRBCfepFgAkhhGh46kWA1fTkkXLySSGEUJ96cwysppOIZRKyEEKoS70JMKh58EhwCSGEetSLLkQh\nhBANjwSYEEIIVZIAE0IIoUoSYEIIIVRJAkwIIYQqSYAJIYRQJQkwIYQQqiQBJoQQQpUkwIQQQqiS\nBJgQQghVkgATQgihShJgQgghVEkCTAghhCpJgAkhhFAlCTAhhBCqJAEmhBBClSTAhBBCqJIEmBBC\nCFWSABNCCKFKEmBCCCFUSQJMCCGEKkmACSGEUKWQQG7M4/EwZ84c0tPTMRgMTJ06lfj4eO/tGzZs\nYOXKleh0OhITE3niiSfQaDSBLFEIIYRKBLQFtmnTJlwuF8uWLWPy5MnMmzfPe1tBQQGLFy9m4cKF\nLFmyBKvVyo8//hjI8oQQQqhIQANs165d9O/fH4AuXbqQmprqvc1oNLJs2TKMRiMAbrfb+7MQQghx\nroAGmM1mw2w2n924VovH4wFAo9EQHR0NwMqVKykoKKBv376BLK/WtGvXrq5L8InU6T9qqBGkTn9T\nQ51qqNFXAT0GFh4ejs1m8172eDxotdpSl998802OHDnCiy++GMjShBBCqExAW2Ddu3dn8+bNAOze\nvfu8bwKzZ8/G6XQyd+5c6T4UQghRIY3FYlECtTFFUbyjEAGmT59Oamoqdrudjh07cscdd9CjRw/v\n/ceMGcPQoUMDVZ4QQggVCWiACSGEEP4iE5mFEEKokgSYEEIIVZIAE0IIoUoSYEIIIVQpoPPA/OHM\nmTM888wz5OXlYTKZmDp1KrGxsezevZvXXnsNnU5Hv379GD9+fJ3WWVBQwLRp08jLy0Ov1zNz5kya\nNGkSdHW+9957/Pzzz0DRvs3Ozua///1v0NXpdruZN28eqampFBYWct999zFgwICgqlNRFEaMGEHL\nli0B6Nq1K5MmTQqqGks6dOgQd999Nxs2bECv1wddnXa7nenTp3vfQ08//TQxMTFBV6fVamXGjBnk\n5+dTWFjIgw8+SNeuXYOuToDvvvuOjRs38txzzwEEZY2VrZlbkupaYMuXL6d79+4sWbKE2267jZdf\nfhmAF198keeee44lS5bw+++/s2/fvjqtc/369bRq1YrFixczbNgwPvjgg6Cs84477mDhwoUsXLiQ\n5s2bM3PmzKCs87///S9ut5slS5Ywd+5cDh48GHR1Hj16lA4dOnj356RJkwCYM2dO0NRYzGq18vrr\nr2MwGLzXBVudn3/+OR07dmTx4sUMHz6cFStWAMH1Nwf46KOP6NevH4sWLWLGjBnMnTs3KOt85ZVX\nWLhwIYpyduB5sP3NoeI1c8+lugA7ePAgAwYMAKBbt278+uuv2Gw2XC4XcXFxAPTv35///e9/dVkm\nRqOR3NxcoGgJLb1eH5R1Fvvuu++IjIykb9++WK3WoKvz559/JiYmhoceeohZs2Zx6aWXBl2dqamp\nZGZmMnHiRB566CEyMjKwWq0UFhYGTY1Q1FJ88cUXmTRpknfBgGCs8+abb+auu+4C4MSJE0RERATl\ne2js2LEkJSUB4HK5MBqNQVlnt27deOKJJ7yXg/FvDhWvmXuuoO5C/Pzzz/n3v/9d6rrY2Fh++OEH\n2rdvT3JyMgUFBdhsNsLDw733CQsL49ixY3VWp0aj4dFHH+X9999nzJgx5OXlsXjxYqxWa1DVCTBj\nxgw6duzIe++9xwsvvAAQdPsTICoqCqPRyGuvvcaOHTt49tlnee655+qszrJqfPzxx7nzzju5/PLL\n2bVrF08//TQvvfRS0O3L2NhYrrrqKu9KOIqiBOXfvPi1OWnSJA4cOMAbb7wR1O+h06dP88wzz/Dw\nww/XaZ3l1XjllVeyfft273V1/TcvT3lr5pZcdrBYUAfYyJEjGTlyZKnr8vPzeeWVV7jvvvsYNGgQ\nsbGx562xaLPZiIiIqNM6Z82a5f1mlp6ezhNPPMGSJUuCrk6AAwcOEBER4f0mFoz7c9q0aQwePBiA\nnj17cvjw4Tqts6waCwoKCAkpekt1796d06dPExYWFnT7cvTo0axdu5a1a9eSnZ3Nv/71L1555ZWg\nq7PYW2+9RUZGBg899BArVqwIyjrT09OZNm0aDzzwAD169MBqtQbVa7Msdf0+L09la+aWpLouxB07\ndjBy5EgWL15MfHw83bt3Jzw8HL1ez7Fjx1AUha1bt5Zakqou2O1277ebqKgo8vPzg7JOgG3btjFw\n4EDvZbPZHHR1du/enZ9++gmAffv2ccEFFwTd/ly2bBkff/yxt8bmzZsH5b785JNPvMfpGjduzJtv\nvhl0+xKKjnd/+eWXAJhMJnQ6XVDWeeDAAZ588kmef/557+GNYPy7nytYa6xszdySVLeU1NGjR5k5\ncyaKohAZGcmMGTOIiooiJSWFV199FY/HQ//+/ZkwYUKd1vnnn38ya9YsHA4Hbreb++67j759+wZd\nnQBz586lX79+DBkyxHtdsNVZWFjIiy++6B28MWXKFNq3bx9UdRaPRrPb7eh0Oh577DESEhKCqsZz\nJSUlsWrVKvR6fdDVmZ2dzcyZM3E6nbjdbu6//366desWdHU++uijpKenc8EFFwBFwTB37tygqxOK\nGgBr1qzh+eefB4LvfQ5lr5mbkJBQ5n1VF2BCCCEEqLALUQghhAAJMCGEEColASaEEEKVJMCEEEKo\nkgSYEEIIVZIAE0IIoUpBvRKHaNgmTJjAr7/+6r2s0WgIDQ2lZcuWXHvttdx4443odLo6rPCsfv36\nlbqs1WqJiIige/fuTJgwgcTExCo9nsvl4sUXX2Tjxo14PB6eeOIJrrnmGn+W7LPffvuN999/n927\nd2O1WomOjqZHjx7ceeedpZ7XhAkTvAsuCxEIEmAiqLVr144nn3wSKDqlSl5eHps3b2bevHns3LmT\nWbNmodFo6rjKIiNGjGDUqFFA0cTrzMxMVqxYwcSJE1m5ciXR0dE+P9aWLVv44osvuOOOOxg0aFC5\nEzlr2//+9z8eeOABhg4dylNPPUVkZCR//vkn//73v7nrrrtYtGgRnTp18t4/WP4WomGQABNBLSws\njM6dO5e6rvgD/ZVXXmHDhg0MHz68jqorrVmzZufV2qFDB2688Ua+/fZbbrzxRp8fq/hMBn/7299o\n0aKFX+usiuXLl9OpUydmz57tva5Hjx4MGTKEG2+8kWXLlvHKK6/UWX2iYZNjYEKVbrrpJmJiYliz\nZo33uoKCAhYsWMDo0aMZPHgwl112Gf/85z+95zg6cOAA/fr1Y/Xq1aUeKycnh4EDB3qv/+qrr7j1\n1lsZMmQIV155JVOmTOHw4cPVqrN4cdSSLROPx8OKFSu8dY4aNYoPP/zQe/vMmTO9Jxy88cYbvQuz\nut1uVq9ezdixYxkyZAjXX389b775Jg6Ho9TvTp48mZdeeonLLruMUaNG4XK5Kt1mebKysvB4POdd\nbzabeeSRR7jiiitKXa8oCh9++CEjR47kkksu4fbbbz/vFB2HDx9mypQpXHvttQwZMoSJEyeyc+dO\noCi4BwwY4D1/HhQtKdWvXz8ef/zxUo8zatQoXn311Uqfg6i/pAUmVEmj0dC7d2++/vpr72rVzzzz\nDDt37uT+++8nLi6OI0eOsHjxYp566ilWr15NmzZt6NKlC19++WWp1tCGDRsICQlh+PDh3tOg3H33\n3fTq1Yvs7GzeeustHnroIT755JMKa/J4PLhcLqDogzwzM5OFCxfStGnTUh/0L7/8Mp999hl33nkn\nF198MTt37mT+/PlkZ2fzz3/+k/HjxxMbG8s777zDiy++6D1LwOzZs/nyyy+5/fbb6dmzJ3v37mXp\n0qXs3buX+fPnex//119/Ra/XM3fuXKxWKyEhIbz00ksVbrM8l1xyCStWrGDChAlcc8019OrVy3t2\n3CuvvPK8+6ekpFBYWMjDDz+MVqtlwYIFPPbYY3z++edERUVx4MABxo0bR4sWLXj00UcJCQlh5cqV\nTJo0iTfeeIPevXvTtWtX/ve///GPf/wDgF9++QXAG3IAGRkZHDt2rNT6naLhkQATqtWkSRNcLhe5\nubmYzWYKCgp45JFHvB+sPXr0IC8vjzfeeIPMzExiYmK4/vrrmTVrFhkZGd7jSuvXr+fSSy/FbDaz\nc+dOTCYTd9xxh/dsxc2aNWPz5s3k5+cTFhZWbj3Lly9n+fLlpa7TarXMmjWLqKgooKj1sWbNGu69\n917uvvtuAPr27YvJZGLhwoWMGTOGuLg4b2i1b9+euLg4Dhw4wBdffMGECRO8J3ns27cvMTExPP30\n0yQnJ3PJJZcARS21KVOmEBsb69M2//73v9O8efMyn9OECROw2+189tln3gE1jRs3ZsCAAYwZM4aL\nLrqo1P1DQkJ4/fXXadSokffygw8+SEpKCoMHD2bp0qXo9XoWLlzoPVvDoEGDuOWWW3jjjTd4//33\nGTRoEO+88w4ul4uQkBC2bdtGhw4dSE1NJT09nbZt27JlyxbMZnNQrJ4u6o50IQrV02g06PV65s2b\nx5VXXsmpU6f45ZdfWLNmDT/++CMATqcTKGo1hIaGek/TkZ6ezr59+/jb3/4GQO/evSkoKOCWW27h\nzTffZNu2bXTq1IkJEyZUGF4A119/Pe+99x7vvfce7777Li+99BIDBgzgqaeeIjk5GShqTSiKwpAh\nQ3C5XN5/l1xyCR6Ph23btpX52Dt27ADgqquuKnX9sGHD0Gq13tuhqNuyOLx82WZxC6csISEhPPbY\nY/xyiIkAAAX7SURBVKxbt44ZM2Zw7bXXYjQaWb9+PXfeeSf/+c9/St2/devW3vACuPDCCwHIy8vz\nPo+BAweWOpGiTqdj2LBh7N27F5vNxuDBgykoKOC3337z1j9q1CgaNWrkfZ4//fQTAwYMCJpRqKJu\nSAtMqFZmZiYmk8n7gbllyxZee+01MjIyCAsLo127dueFTlhYGFdccQX//e9/mThxIuvWrSM2Npa+\nffsC0LlzZ9544w0++ugj/vOf//DBBx8QGRnJTTfdxL333lthPU2bNqVDhw6lrrvkkku4+eabWbhw\nIZdccgkWiwWAW2+99bzf12g0nD59uszHPnPmDFDU6iwpJCSEqKgob0AAhIaGlrpPdbdZUnR0NNdd\ndx3XXXcdAHv27OGZZ57hzTffZPjw4URGRgJF5+0qqfhEhMXH0c6cOXPecyj5vKxWK4mJicTGxrJ1\n61aaN2/O8ePH6d27Nz169GD79u1cf/317Ny5k2nTplVat6jfJMCEKrndbnbs2EG3bt3QaDQcPXqU\nxx9/nCFDhvDaa695u+BWr17Nli1bSv3uyJEjWbduHb/99hvffPMN119/fanb+/TpQ58+fSgsLGTH\njh18+umnLFu2jMTExPMGLVRGq9XSvn17fvjhB+DsoI758+efd/ZbRVGIiYkp83GKAyIrK8v73KBo\nvpjFYvF2URY/TknV3WZKSgoPP/wwL7zwAn369Cl1W8eOHbnvvvt48sknOXr0aKmh9BWJjIwsMzCz\nsrIAvF9GBg8ezLZt24iLiyM2Npa4uDh69uzJsmXL2LZtGy6Xq9RJWEXDJF2IQpU+/fRTMjMzGT16\nNFDUInA6ndx+++2lPuCLz+xaciRdt27dSEhIYOHChZw+fZoRI0Z4b3vrrbe48847AdDr9fTr148p\nU6YAcOLEiSrX6XK52Lt3r3cofPExm5ycHDp06OD9V1BQwKJFi7wf5Ofq1asXUDTgpKSvvvoKj8dD\n9+7dvdedOxerZ8+e1dpmQkICTqeTjz/++LxQBDh06BBGo5GWLVv6siu8tWzevBmr1eq9zu1289VX\nX3HRRRd5W3CDBw9mz549/PDDD97n3rt3b3Jzc1mxYgUXX3zxeWEsGh5pgYmgZrPZSElJQVEUFEXB\nYrHw888/8+mnn3LNNdcwdOhQoKhFoNPpeOuttxg7dixOp5N169bx+++/A2C320s9bvEQ9F69enmP\n0wD079+fFStW8PTTT3PNNdegKAqrVq3CaDRy6aWXVljrqVOn2L17t/ey1WrlP//5D0eOHOHZZ58F\noG3btgwfPpwXX3yRP//8k86dO3P06FEWLVpEVFRUuSt2tG7dmuuuu46lS5fidDrp2bMn+/btY+nS\npfTs2ZPBgwd773tu2CQmJlZrmxERETz44IPMnj2be+65h5EjRxIXF4fdbmfz5s2sWbOGyZMnYzab\ny932ucaPH8/mzZuZNGmSd6DMypUrOX78eKkh8b169UKv15OcnMyMGTO8zyM6Oppdu3bxwAMPVLgd\n0TBIgImgpdFoSE9PZ9y4cd7LYWFhtG3blilTpnjnRwHEx8fz/PPPs2TJEh599FGio6MZPnw4Dz/8\nMCNHjmTnzp20b9/ee//Bgwfz5ptvntd92LNnT2bPns17773Hk08+iaIodOzYkfnz53uHj5dn/fr1\nrFu37rxaZ82axeWXX+6934wZM3jvvfdYu3Ytb7/9NtHR0Vx66aVMmDCBkJCzb8lzW1LTpk2jRYsW\nfPHFF6xYsYKYmBj+/ve/M378eO99NRpNmath+LrNcyUlJdGyZUtWrlzJokWLsFgsmEwmOnXqxEsv\nveQd+VjRtktq06YNb7/9NgsXLvSe1r5z58689dZbXHzxxd77GQwG+vbty48//uhtgUFRsH377bel\ntisaLo3FYqn4K5MQ9dCHH37I8uXLWb9+vXe4vBBCXaQFJhqU9evXs3//flavXs1tt90m4SWEiskg\nDtGgFIfXkCFDvBOChRDqJF2IQgghVElaYEIIIVRJAkwIIYQqSYAJIYRQJQkwIYQQqiQBJoQQQpX+\nH9zRCzX2I04VAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x8c2ea20>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Plot scatter plot of 'ticket price z-score' mean against 'days before show'\n",
"\n",
"x = concert_tix_groupby.reset_index()['Days Before Show']\n",
"y = concert_tix_groupby_percentile.reset_index()['Percentile']\n",
"\n",
"popt, pcov = curve_fit(func3, x, y)\n",
"\n",
"ax1 = concert_tix_groupby_percentile.reset_index().interpolate(method='values').plot(kind='scatter', x='Days Before Show', y='Percentile')\n",
"plt.plot(x, func3(x, *popt))\n",
"ax1.set_xlim(-90,0)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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BzKjTsHR0DCk5DtpH6IKia0uv1fC7dqGMaR3iVZ1hwZ48eoxtRmxI4P8cgUQSkRDV5FIU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\n5ogAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x89007b8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot rolling mean ticket price z-score by 'days before show'\n",
"ax = pd.rolling_mean(concert_tix_groupby,5).plot()"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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w9KfurGkBlMqmpwA1PiX0ieqKMX/+fOzZswdLliwBAKxevRrbt2+Hx+PBjBkz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\nLy8vs23BwcGsXr0atVpNcHAwra2tAKxdu7bf72UyGe/fvx/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"text/plain": [
"<matplotlib.figure.Figure at 0xc785828>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot rolling standard deviation of ticket price z-score by 'days before show'\n",
"ax = pd.rolling_std(concert_tix_groupby,5).plot()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0xdf18978>"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\matplotlib\\collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
" if self._edgecolors == str('face'):\n"
]
},
{
"data": {
"image/png": 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ghmlaeXbWu27JLcDnZdP7dJ2BUGCMY1P1RM6Lz+po+8XY79hak+6zj+k9KTGg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\nm5GSkgK1Wo0BAwZoXSMQCHD9+nU4Oztrt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"text/plain": [
"<matplotlib.figure.Figure at 0x91152b0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#plot mean price over time, standard error and trend line\n",
"days_before_show = -90 # for chart x-axis only\n",
"moving_avg = 5\n",
"\n",
"# sets up the plog figure\n",
"plt.figure(figsize=(10, 6)) \n",
"ax = plt.subplot(111) \n",
"ax.spines[\"top\"].set_visible(False) \n",
"ax.spines[\"right\"].set_visible(False) \n",
"ax.get_xaxis().tick_bottom() \n",
"ax.get_yaxis().tick_left() \n",
"plt.ylim(-1.0, 0.8)\n",
"plt.xlim(days_before_show + moving_avg, 0) \n",
"\n",
"# calculate error bars\n",
"x = concert_tix_groupby.reset_index()['Days Before Show'].interpolate(method='values')\n",
"y_rolling = pd.rolling_mean(concert_tix_groupby.reset_index()['Ticket Price Z-score'].interpolate(method='values'), moving_avg)\n",
"y = concert_tix_groupby.reset_index()['Ticket Price Z-score'].interpolate(method='values')\n",
"sem_y = pd.rolling_mean(concert_tix_groupby_sem, moving_avg)\n",
"\n",
"# plot error bars and fill\n",
"plt.plot(x, y_rolling, color='orange', label='15 day rolling average')\n",
"plt.fill_between(x, y_rolling - sem_y, y_rolling + sem_y, color=\"#3F5D7D\") \n",
"\n",
"# calculate and plot regression\n",
"x = concert_tix_groupby.reset_index()['Days Before Show'].interpolate(method='values')\n",
"y = concert_tix_groupby.reset_index()['Ticket Price Z-score'].interpolate(method='values')\n",
"popt, pcov = curve_fit(func2, x, y)\n",
"plt.plot(x, func2(x, *popt), color='red', label='Trend')\n",
"\n",
"plt.ylabel(\"Ticket Price Z-score\", size=14)\n",
"plt.yticks(size=14)\n",
"\n",
"plt.xlabel(\"Days Before Show\", size=14)\n",
"plt.xticks(size=14)\n",
"ax.grid(False)\n",
"\n",
"ax.text(-56, -1.35, \"From: chart-it (MikeRAzar.com/chart-it)\", fontsize=12) "
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\matplotlib\\collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
" if self._edgecolors == str('face'):\n"
]
},
{
"data": {
"image/png": 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uIcU/x6VsVdV0lE5+i8s1JbGldrJL2XWRqwhR986fk9Ohl03cGvMtTya8x8iA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tyZhmkTBjg7rCZjWQ7Z+TeamLDyf9dVOr5MQmQygq2tXzDD4OuRDzr8+bdTi8oxzGsXWF6A34oH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\nwZd+HQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xdc330f0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#plot mean price over time, standard error and trend line\n",
"days_before_show = -95 # for chart x-axis only\n",
"moving_avg = 5\n",
"\n",
"# sets up the plog figure\n",
"plt.figure(figsize=(10, 6)) \n",
"ax = plt.subplot(111) \n",
"ax.spines[\"top\"].set_visible(False) \n",
"ax.spines[\"right\"].set_visible(False) \n",
"ax.get_xaxis().tick_bottom() \n",
"ax.get_yaxis().tick_left() \n",
"plt.ylim(0.2, 0.7)\n",
"plt.xlim(days_before_show + moving_avg, 0) \n",
"\n",
"# calculate error bars\n",
"x = concert_tix_groupby_percentile.reset_index()['Days Before Show'].interpolate(method='values')\n",
"y_rolling = pd.rolling_mean(concert_tix_groupby_percentile.reset_index()['Percentile'].interpolate(method='values'), moving_avg)\n",
"y = concert_tix_groupby_percentile.reset_index()['Percentile'].interpolate(method='values')\n",
"sem_y = pd.rolling_mean(concert_tix_groupby_percentile_sem, moving_avg)\n",
"\n",
"# plot error bars and fill\n",
"plt.plot(x, y_rolling, color='orange', label='15 day rolling average')\n",
"plt.fill_between(x, y_rolling - sem_y, y_rolling + sem_y, color=\"#3F5D7D\", alpha=0.8) \n",
"\n",
"\n",
"# calculate and plot regression\n",
"x = concert_tix_groupby_percentile.reset_index()['Days Before Show'].interpolate(method='values')\n",
"y = concert_tix_groupby_percentile.reset_index()['Percentile'].interpolate(method='values')\n",
"popt, pcov = curve_fit(func2, x, y)\n",
"plt.plot(x, func2(x, *popt), color='red', label='Trend', linewidth=3.0, ls='--')\n",
"\n",
"plt.ylabel(\"Percentile of Average Ticket Price\", size=14)\n",
"plt.yticks(size=14)\n",
"\n",
"plt.xlabel(\"Days Before Show\", size=14)\n",
"plt.xticks(size=14)\n",
"\n",
"def func_pct(x, pos): \n",
" s = '{0:.0f}'.format(x * 100)\n",
" return s\n",
"\n",
"y_format = tkr.FuncFormatter(func_pct) # make formatter\n",
"ax.yaxis.set_major_formatter(y_format)\n",
"\n",
"# arrows and labels\n",
"ax.text(x=-49,y=0.66,s='Sell Here', fontsize=14, color='black')\n",
"ax.arrow(-45, 0.655, 9, -0.02, head_width=0.02, head_length=1.2, color='black')\n",
"\n",
"ax.text(x=-29,y=0.48,s='Buy Here', fontsize=14, color='black')\n",
"ax.arrow(-30, 0.50, 27, 0, head_width=0.018, head_length=2, color='black', zorder=10)\n",
"ax.arrow(-30, 0.50, -19.5, 0, head_width=0.018, head_length=2, color='black', zorder=10)\n",
"\n",
"ax.text(-60, 0.1, \"From: chart-it (MikeRAzar.com/chart-it)\", fontsize=12) \n",
"ax.grid(False)\n",
"\n",
"ax.spines['bottom'].set_visible(True)\n",
"ax.spines['bottom'].set_visible(True)\n",
"ax.spines['bottom'].set_color('grey')\n",
"ax.grid(True)\n",
"\n",
"ax.grid(b=True, which='minor')"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\matplotlib\\collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
" if self._edgecolors == str('face'):\n"
]
},
{
"data": {
"image/png": 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staOhdWC1NkEQUN+qQVO7NkgjIyIiolA3iQMVBV+adgy/WfAGpoYPfyN8S0IufnnZW4gW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YMRpz+EqcFf15uOFeqRg6ciFmFvSR/8J2cyrtQENLlXvbIMD4V9DNV109EqrB54/8L9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\npngAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xc2465c0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#plot mean price over time, standard error and trend line\n",
"days_before_show = -40 # for chart x-axis only\n",
"\n",
"# sets up the plog figure\n",
"plt.figure(figsize=(12, 9)) \n",
"ax = plt.subplot(111) \n",
"ax.spines[\"top\"].set_visible(False) \n",
"ax.spines[\"right\"].set_visible(False) \n",
"ax.get_xaxis().tick_bottom() \n",
"ax.get_yaxis().tick_left() \n",
"plt.ylim(0.1, 0.8)\n",
"plt.xlim(days_before_show + moving_avg, 0) \n",
"\n",
"# calculate error bars\n",
"x = concert_tix_groupby_percentile.reset_index()['Days Before Show'].interpolate(method='values')\n",
"y_rolling = concert_tix_groupby_percentile.reset_index()['Percentile'].interpolate(method='values')\n",
"y = concert_tix_groupby_percentile.reset_index()['Percentile'].interpolate(method='values')\n",
"sem_y = concert_tix_groupby_percentile_sem\n",
"\n",
"# plot error bars and fill\n",
"plt.plot(x, y_rolling, color='orange', label='15 day rolling average')\n",
"plt.fill_between(x, y_rolling - sem_y, y_rolling + sem_y, color=\"#3F5D7D\", alpha=0.8) \n",
"\n",
"plt.ylabel(\"Percentile of Average Ticket Price\", size=14)\n",
"plt.yticks(size=14)\n",
"\n",
"plt.xlabel(\"Days Before Show\", size=14)\n",
"plt.xticks(size=14)\n",
"\n",
"def func_pct(x, pos): \n",
" s = '{0:.0f}'.format(x * 100)\n",
" return s\n",
"\n",
"y_format = tkr.FuncFormatter(func_pct) # make formatter\n",
"ax.yaxis.set_major_formatter(y_format)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"20"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#number of artists in dataset\n",
"len(concert_tix.groupby(['Show']).count().index.unique())"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"16562"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#number of ticket sales in dataset\n",
"len(concert_tix)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"17"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#number of ticket sales in dataset\n",
"len(concert_tix.groupby(['City']).count().index.unique())"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"32"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#number of shows in dataset\n",
"len(concert_tix.groupby(['Show','City']).count().index.unique())"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(array([ 0., 2000., 4000., 6000., 8000., 10000.]),\n",
" <a list of 6 Text xticklabel objects>)"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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KvbrThDsbQeOZXq/HE088AYZh0KdPH8TExDglSyC4Jkbl3tN2njoaE5LfAgB0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\nEMUmEIKQ/wdV5s07srEQzQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xe1b3240>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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caM6eBN39GiAmTnm5YYC5VDc0tQaOY0IeDiP5bdxxxx2YPHkykpOTkZubKztn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\ngaA6s4pKA0F1ZhWVBoLqzCoqDYT/B8uPkKh9ywrMAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xe1b3978>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# example of z-scaling\n",
"df = pd.DataFrame(np.random.randn(10000, 3), columns=list('ABC'))\n",
"df = df.cumsum()\n",
"df1 = (df - df.mean()) / df.std()\n",
"\n",
"df.plot(legend=False, figsize=(3, 3)); plt.ylabel('Ticket Price', size=10)\n",
"plt.yticks(size=10); plt.xticks(size=0)\n",
"\n",
"df1.plot(legend=False, figsize=(3, 3));plt.ylabel('Ticket Price Z-score', size=10)\n",
"plt.yticks(size=10); plt.xticks(size=0)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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TDRs28P3337N9+3bjxrzc3FxeeuklBgwY0KCDFBGR5qVeex6zZs2iuLiYRYsW0bVrVx5/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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x8e28cf8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# histogram of ticket prices\n",
"ax = concert_tix['Price'].T.plot(kind='hist', bins= 50, figsize=(5, 3), fontsize=14)\n",
"ax.set_ylabel(\"Tickets\")\n",
"ax.set_xlabel(\"Ticket Price\")\n",
"ax.spines[\"top\"].set_visible(False) \n",
"ax.spines[\"right\"].set_visible(False)\n",
"ax.set_xlim(0,500)\n",
"\n",
"def func_comma(x, pos): \n",
" s = '{:0,d}'.format(int(x))\n",
" return s\n",
"\n",
"y_format = tkr.FuncFormatter(func_comma) # make formatter\n",
"ax.yaxis.set_major_formatter(y_format)\n",
"ax.grid(False)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0xdc10208>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# histogram of ticket price z-scores\n",
"ax = concert_tix['Ticket Price Z-score'].T.plot(kind='hist', bins=20, figsize=(5, 3), fontsize=14)\n",
"ax.set_xlabel(\"Ticket Price Z-Score\")\n",
"ax.set_ylabel(\"Tickets\")\n",
"ax.spines[\"top\"].set_visible(False) \n",
"ax.spines[\"right\"].set_visible(False)\n",
"ax.set_xlim(-3,3)\n",
"\n",
"def func_comma(x, pos): \n",
" s = '{:0,d}'.format(int(x))\n",
" return s\n",
"\n",
"y_format = tkr.FuncFormatter(func_comma) # make formatter\n",
"ax.yaxis.set_major_formatter(y_format)\n",
"ax.grid(False)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\matplotlib\\collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
" if self._edgecolors == str('face'):\n"
]
},
{
"data": {
"image/png": 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qemQeM+VwO9TxZIckybfQp0Q0ISPPkC/sG3WWYgAAgOmCYAcAWMJV4pKzyKmD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\nYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xde62b70>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot some sections for reference\n",
"fig, ax = plt.subplots(figsize=(15,10))\n",
"plt.figsize=(14, 10)\n",
"\n",
"color= cycle(['b', 'g', 'r', 'c', 'm', 'y', 'k', 'orange'])\n",
"linecycler = cycle(['>' ,'^', '<', 'x', '*', 'h', 's', '+'])\n",
"\n",
"for i, group in concert_tix[(concert_tix['City'] == 'Washington, DC') & (concert_tix['Show'] == 'Ed Sheeran') & (concert_tix['Section'].str.startswith('floor'))].groupby(['Show', 'City', 'Section']):\n",
" group.plot(kind='scatter',x='Days Before Show', y='Percentile', ax=ax, color=next(color), marker=next(linecycler), s=100)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"0 0.528116\n",
"1 0.562812\n",
"2 0.625790\n",
"3 0.630252\n",
"4 0.503400\n",
"5 0.526662\n",
"6 0.549633\n",
"7 0.484995\n",
"8 0.518929\n",
"9 0.595860\n",
"10 0.503280\n",
"11 0.552834\n",
"12 0.600354\n",
"13 0.310867\n",
"14 0.579123\n",
"15 0.566368\n",
"16 0.632079\n",
"17 0.588763\n",
"18 0.516552\n",
"19 0.456447\n",
"20 0.501904\n",
"21 0.530542\n",
"22 0.558914\n",
"23 0.524214\n",
"24 0.518810\n",
"25 0.498338\n",
"26 0.459549\n",
"27 0.474821\n",
"28 0.518475\n",
"29 0.479704\n",
" ... \n",
"60 0.524453\n",
"61 0.505761\n",
"62 0.658071\n",
"63 0.464448\n",
"64 0.509533\n",
"65 0.542334\n",
"66 0.557863\n",
"67 0.510584\n",
"68 0.526102\n",
"69 0.498584\n",
"70 0.506767\n",
"71 0.513379\n",
"72 0.562816\n",
"73 0.548105\n",
"74 0.582702\n",
"75 0.501975\n",
"76 0.500177\n",
"77 0.517853\n",
"78 0.556277\n",
"79 0.615121\n",
"80 0.546919\n",
"81 0.550668\n",
"82 0.538402\n",
"83 0.538391\n",
"84 0.580087\n",
"85 0.532724\n",
"86 0.569070\n",
"87 0.519379\n",
"88 0.550344\n",
"89 0.572628\n",
"Name: Percentile, dtype: float64"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"concert_tix.groupby(['Days Before Show'])['Percentile'].apply(np.std).reset_index()['Percentile'].interpolate(method='values').mul(1.96)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
}
],
"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": "3.4.3"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
@ashiyag
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ashiyag commented Apr 6, 2016

Anyway I could get access to the csv file used/input on how data was scraped? I'm trying to do something similar for a class project.

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