Skip to content

Instantly share code, notes, and snippets.

@sslampa

sslampa/gist:485da05400d94dc11610

Created July 10, 2015 08:53
Show Gist options
  • Save sslampa/485da05400d94dc11610 to your computer and use it in GitHub Desktop.
Save sslampa/485da05400d94dc11610 to your computer and use it in GitHub Desktop.
Download ZIP
Main Twitch
Raw
gistfile1.txt
{
"metadata": {
"name": "",
"signature": "sha256:01840308b58ae76657eca64ebdfeff37664872b9a9f794f87858707289e3c82b"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"cd C:\\tmp"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"C:\\tmp\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pandas as pd\n",
"import datetime\n",
"import time\n",
"import numpy as np\n",
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"%matplotlib inline"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Reads the .csv data\n",
"df = pd.read_csv(\"june_final.csv\", header=None, names=['id', 'name', 'followers', 'current_viewers', 'date_time'])"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Extracts individual pieces to be used later for the new datetime\n",
"df['years'] = pd.DatetimeIndex(df['date_time']).year\n",
"df['months'] = pd.DatetimeIndex(df['date_time']).month\n",
"df['days'] = pd.DatetimeIndex(df['date_time']).day\n",
"df['hours'] = pd.DatetimeIndex(df['date_time']).hour\n",
"df['minutes'] = pd.DatetimeIndex(df['date_time']).minute"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Checking to see that there is a close enough distribution between every hour.\n",
"# Some data was lost due to twitch/my server failures.\n",
"df.hist(\"hours\", bins=24)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": [
"array([[<matplotlib.axes._subplots.AxesSubplot object at 0x02D0B270>]], dtype=object)"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAEKCAYAAAD6q1UVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text": [
"<matplotlib.figure.Figure at 0x844ac70>"
]
}
],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Mean views of streamers\n",
"avg_streamer = df.groupby('name')['current_viewers'].agg(np.mean)\n",
"avg_streamer.sort(ascending=False, inplace=True)\n",
"new_avg_streamer = pd.DataFrame(avg_streamer).reset_index()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Number of periods streamer streamed\n",
"count_streamer = df.groupby('name')['current_viewers'].count()\n",
"count_streamer.sort(ascending=False, inplace=True)\n",
"new_count_streamer = pd.DataFrame(count_streamer).reset_index()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Look to find which channels are for tournaments\n",
"combined_streamer = pd.merge(new_avg_streamer, new_count_streamer, on='name')\n",
"combined_streamer.columns = ('name', 'total_viewers', 'count')\n",
"combined_streamer.sort(columns='total_viewers', ascending=False, inplace=True)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 8
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Boxplot with tournament data\n",
"ax = sns.boxplot(x='hours', y='current_viewers', data=df, fliersize=0, order=np.arange(0,24))\n",
"ax.set(ylim=(-100, 4000))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 9,
"text": [
"[(-100, 4000)]"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAYkAAAERCAYAAACO6FuTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSYiISCwlCRERifX/AYEDfubOh5BNAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x8435df0>"
]
}
],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Remove all the tournament data to compare with previous boxplot\n",
"tournament_list = ['dreamhackhs', 'viagamehs', 'esl_hearthstone', 'tempo_storm', 'wca_america', 'nvidia', 'nvidiafrance',\n",
" 'starladder_hs_ru', 'starladder_hs_eu', 'vulcunhs', 'viagamehs_ru', 'onenationofgamers', 'stormstudio_hs_ru', \n",
" 'hkesportstv', 'hearthstonefr', 'readyuptv', 'pvplive']\n",
"\n",
"# ~ -> not, isin -> in used for lists\n",
"temp_df = df[~df['name'].isin(tournament_list)]\n",
"bx = sns.boxplot(x='hours', y='current_viewers', data=temp_df, fliersize=0, order=np.arange(0,24))\n",
"bx.set(ylim=(-100, 4000))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 10,
"text": [
"[(-100, 4000)]"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAYkAAAERCAYAAACO6FuTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n",
"text": [
"<matplotlib.figure.Figure at 0x1076ed10>"
]
}
],
"prompt_number": 10
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# This shows the mean of the dataset including tournaments\n",
"total_streamer1 = df.groupby(by=['hours'])['current_viewers'].agg(np.mean)\n",
"total_streamer1.sort(ascending=False, inplace=True)\n",
"total_streamer1 = pd.DataFrame(total_streamer1).reset_index()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 11
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Shows the mean of the dataset without tournaments\n",
"total_streamer2 = temp_df.groupby(by=['hours'])['current_viewers'].agg(np.mean)\n",
"total_streamer2.sort(ascending=False, inplace=True)\n",
"total_streamer2 = pd.DataFrame(total_streamer2).reset_index()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Table showing the mean of the dataset with the tournament channels vs without\n",
"streamer_mean = pd.merge(total_streamer1, total_streamer2, on='hours')\n",
"streamer_mean.sort(columns='hours', inplace=True)\n",
"streamer_mean.columns = ('hours', 'withTournament', 'withoutTournament')"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 13
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Make individual team datasets\n",
"#archon_df = df[df['name'].isin(archon)]\n",
"#c9_df = df[df['name'].isin(c9)]\n",
"#complexity_df = df[df['name'].isin(complexity)]\n",
"#liquid_df = df[df['name'].isin(liquid)]\n",
"#nihilum_df = df[df['name'].isin(nihilum)]\n",
"#tempoStorm_df = df[df['name'].isin(tempoStorm)]\n",
"#tsm_df = df[df['name'].isin(tsm)]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 16
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Creates a dataframe with days between 5/30/15 - 6/30/15\n",
"date_tmp = pd.date_range(start=datetime.datetime(2015, 5, 30), end=datetime.datetime(2015, 6, 30)).tolist()\n",
"date_df = pd.DataFrame(date_tmp).reset_index()\n",
"date_df.columns = ('index', 'date')\n",
"date_list = pd.to_datetime(date_df['date']).tolist()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 17
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Creates the full list of dates + time\n",
"datetime_list = []\n",
"hour_list = np.arange(0,24)\n",
"min_list = (0, 10, 20, 30, 40, 50)\n",
"\n",
"for x in date_list:\n",
" day1 = x.day\n",
" month1 = x.month\n",
" year1 = x.year\n",
" \n",
" for y in hour_list:\n",
" for z in min_list:\n",
" datetime_list.append(datetime.datetime(year1, month1, day1, y, z))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Creates database using the datetime as the index and 0 in each column\n",
"datetime_df = pd.DataFrame(index=datetime_list, columns=['A'])\n",
"datetime_df.fillna(0, inplace=True)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Replaces any bad minutes (those that don't have 0 in the singles digits) in the main dataframe\n",
"zeroes = np.arange(0, 10)\n",
"tens = np.arange(10, 20)\n",
"twenties = np.arange(20, 30)\n",
"thirties = np.arange(30, 40)\n",
"fourties = np.arange(40, 50)\n",
"fifties = np.arange(50, 60)\n",
"df['minutes'].replace(fourties, 40, inplace=True)\n",
"df['minutes'].replace(zeroes, 0, inplace=True)\n",
"df['minutes'].replace(tens, 10, inplace=True)\n",
"df['minutes'].replace(twenties, 20, inplace=True)\n",
"df['minutes'].replace(thirties, 30, inplace=True)\n",
"df['minutes'].replace(fifties, 50, inplace=True)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 21
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Turns individual pieces back into a datetime object\n",
"for index, row in df.iterrows():\n",
" df.ix[index, 'test'] = datetime.datetime(row['years'], row['months'], row['days'], row['hours'], row['minutes'])"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 22
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>id</th>\n",
" <th>name</th>\n",
" <th>followers</th>\n",
" <th>current_viewers</th>\n",
" <th>date_time</th>\n",
" <th>years</th>\n",
" <th>months</th>\n",
" <th>days</th>\n",
" <th>hours</th>\n",
" <th>minutes</th>\n",
" <th>test</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>29795919</td>\n",
" <td>nl_kripp</td>\n",
" <td>524793</td>\n",
" <td>13097</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>80549470</td>\n",
" <td>viagamehs</td>\n",
" <td>24227</td>\n",
" <td>4723</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>60978448</td>\n",
" <td>hsdogdog</td>\n",
" <td>42454</td>\n",
" <td>2709</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>20650414</td>\n",
" <td>tidesoftime</td>\n",
" <td>95628</td>\n",
" <td>1671</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>31187787</td>\n",
" <td>hotform</td>\n",
" <td>14934</td>\n",
" <td>1012</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>29884841</td>\n",
" <td>vernnotice</td>\n",
" <td>147179</td>\n",
" <td>935</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>60216187</td>\n",
" <td>simcopter1</td>\n",
" <td>16757</td>\n",
" <td>612</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>67479479</td>\n",
" <td>mryagut</td>\n",
" <td>10899</td>\n",
" <td>555</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>36852689</td>\n",
" <td>ryzentv</td>\n",
" <td>32355</td>\n",
" <td>483</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>60494876</td>\n",
" <td>mackenseize</td>\n",
" <td>20332</td>\n",
" <td>338</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>42596387</td>\n",
" <td>m989876525</td>\n",
" <td>4975</td>\n",
" <td>258</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>47896635</td>\n",
" <td>hearthstonefr</td>\n",
" <td>43748</td>\n",
" <td>234</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>51989691</td>\n",
" <td>inspectoraubriellama</td>\n",
" <td>5361</td>\n",
" <td>207</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>43865938</td>\n",
" <td>puzzomns</td>\n",
" <td>1393</td>\n",
" <td>178</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>84391327</td>\n",
" <td>telethor</td>\n",
" <td>4034</td>\n",
" <td>167</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>28081485</td>\n",
" <td>happyzerg</td>\n",
" <td>10194</td>\n",
" <td>125</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>89082781</td>\n",
" <td>billyisms</td>\n",
" <td>487</td>\n",
" <td>126</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>65465714</td>\n",
" <td>koronekohs</td>\n",
" <td>1184</td>\n",
" <td>105</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>66086067</td>\n",
" <td>khsjohnny</td>\n",
" <td>5518</td>\n",
" <td>94</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>71440174</td>\n",
" <td>sonecarox</td>\n",
" <td>1271</td>\n",
" <td>86</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>31117934</td>\n",
" <td>ray_sung</td>\n",
" <td>917</td>\n",
" <td>60</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>30557587</td>\n",
" <td>gamecatt</td>\n",
" <td>15953</td>\n",
" <td>57</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>43184697</td>\n",
" <td>fes_on</td>\n",
" <td>300</td>\n",
" <td>57</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>91761304</td>\n",
" <td>devodest</td>\n",
" <td>38</td>\n",
" <td>50</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>42746543</td>\n",
" <td>mantastlc</td>\n",
" <td>7230</td>\n",
" <td>46</td>\n",
" <td>2015-05-30 22:42:38</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>29795919</td>\n",
" <td>nl_kripp</td>\n",
" <td>524793</td>\n",
" <td>13097</td>\n",
" <td>2015-05-30 22:42:50</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>80549470</td>\n",
" <td>viagamehs</td>\n",
" <td>24227</td>\n",
" <td>4723</td>\n",
" <td>2015-05-30 22:42:50</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>60978448</td>\n",
" <td>hsdogdog</td>\n",
" <td>42454</td>\n",
" <td>2709</td>\n",
" <td>2015-05-30 22:42:50</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>20650414</td>\n",
" <td>tidesoftime</td>\n",
" <td>95628</td>\n",
" <td>1671</td>\n",
" <td>2015-05-30 22:42:50</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>31187787</td>\n",
" <td>hotform</td>\n",
" <td>14934</td>\n",
" <td>1012</td>\n",
" <td>2015-05-30 22:42:50</td>\n",
" <td>2015</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>40</td>\n",
" <td>2015-05-30 22:40:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98420</th>\n",
" <td>38869748</td>\n",
" <td>nalguidan</td>\n",
" <td>1094</td>\n",
" <td>86</td>\n",
" <td>2015-06-30 22:20:21</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>20</td>\n",
" <td>2015-06-30 22:20:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98421</th>\n",
" <td>82369114</td>\n",
" <td>vicioussyndicategaming</td>\n",
" <td>629</td>\n",
" <td>76</td>\n",
" <td>2015-06-30 22:20:21</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>20</td>\n",
" <td>2015-06-30 22:20:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98422</th>\n",
" <td>31264406</td>\n",
" <td>bombaacme</td>\n",
" <td>574</td>\n",
" <td>56</td>\n",
" <td>2015-06-30 22:20:21</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>20</td>\n",
" <td>2015-06-30 22:20:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98423</th>\n",
" <td>47939440</td>\n",
" <td>duendepablo</td>\n",
" <td>2054</td>\n",
" <td>59</td>\n",
" <td>2015-06-30 22:20:21</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>20</td>\n",
" <td>2015-06-30 22:20:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98424</th>\n",
" <td>32560951</td>\n",
" <td>apdrop</td>\n",
" <td>17190</td>\n",
" <td>55</td>\n",
" <td>2015-06-30 22:20:21</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>20</td>\n",
" <td>2015-06-30 22:20:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98425</th>\n",
" <td>29795919</td>\n",
" <td>nl_kripp</td>\n",
" <td>545211</td>\n",
" <td>18426</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98426</th>\n",
" <td>27396889</td>\n",
" <td>reynad27</td>\n",
" <td>269947</td>\n",
" <td>9487</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98427</th>\n",
" <td>60978448</td>\n",
" <td>hsdogdog</td>\n",
" <td>46396</td>\n",
" <td>3390</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98428</th>\n",
" <td>30777889</td>\n",
" <td>itshafu</td>\n",
" <td>321560</td>\n",
" <td>2313</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98429</th>\n",
" <td>25871845</td>\n",
" <td>bmkibler</td>\n",
" <td>57123</td>\n",
" <td>768</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98430</th>\n",
" <td>22186763</td>\n",
" <td>xixo</td>\n",
" <td>29787</td>\n",
" <td>733</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98431</th>\n",
" <td>37470342</td>\n",
" <td>pvplive</td>\n",
" <td>25550</td>\n",
" <td>478</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98432</th>\n",
" <td>28382854</td>\n",
" <td>applejacked</td>\n",
" <td>66139</td>\n",
" <td>437</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98433</th>\n",
" <td>88398452</td>\n",
" <td>milleniumtvhs</td>\n",
" <td>10391</td>\n",
" <td>351</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98434</th>\n",
" <td>45330716</td>\n",
" <td>reall1992</td>\n",
" <td>10126</td>\n",
" <td>335</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98435</th>\n",
" <td>47896635</td>\n",
" <td>hearthstonefr</td>\n",
" <td>46833</td>\n",
" <td>314</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98436</th>\n",
" <td>31187787</td>\n",
" <td>hotform</td>\n",
" <td>17797</td>\n",
" <td>254</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98437</th>\n",
" <td>60216187</td>\n",
" <td>simcopter1</td>\n",
" <td>17794</td>\n",
" <td>233</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98438</th>\n",
" <td>42596387</td>\n",
" <td>m989876525</td>\n",
" <td>5939</td>\n",
" <td>228</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98439</th>\n",
" <td>92743746</td>\n",
" <td>starladder_hs_en</td>\n",
" <td>4686</td>\n",
" <td>189</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98440</th>\n",
" <td>55803438</td>\n",
" <td>arybeats</td>\n",
" <td>2745</td>\n",
" <td>140</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98441</th>\n",
" <td>89082781</td>\n",
" <td>billyisms</td>\n",
" <td>1157</td>\n",
" <td>139</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98442</th>\n",
" <td>84391327</td>\n",
" <td>telethor</td>\n",
" <td>5119</td>\n",
" <td>125</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98443</th>\n",
" <td>83644826</td>\n",
" <td>hughgamez</td>\n",
" <td>323</td>\n",
" <td>116</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98444</th>\n",
" <td>38869748</td>\n",
" <td>nalguidan</td>\n",
" <td>1094</td>\n",
" <td>91</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98445</th>\n",
" <td>82369114</td>\n",
" <td>vicioussyndicategaming</td>\n",
" <td>629</td>\n",
" <td>76</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98446</th>\n",
" <td>32560951</td>\n",
" <td>apdrop</td>\n",
" <td>17190</td>\n",
" <td>66</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98447</th>\n",
" <td>47939440</td>\n",
" <td>duendepablo</td>\n",
" <td>2054</td>\n",
" <td>62</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98448</th>\n",
" <td>31264406</td>\n",
" <td>bombaacme</td>\n",
" <td>574</td>\n",
" <td>59</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98449</th>\n",
" <td>61369223</td>\n",
" <td>rinigrandviper</td>\n",
" <td>1608</td>\n",
" <td>41</td>\n",
" <td>2015-06-30 22:30:59</td>\n",
" <td>2015</td>\n",
" <td>6</td>\n",
" <td>30</td>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" <td>2015-06-30 22:30:00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>98450 rows \u00d7 11 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 23,
"text": [
" id name followers current_viewers \\\n",
"0 29795919 nl_kripp 524793 13097 \n",
"1 80549470 viagamehs 24227 4723 \n",
"2 60978448 hsdogdog 42454 2709 \n",
"3 20650414 tidesoftime 95628 1671 \n",
"4 31187787 hotform 14934 1012 \n",
"5 29884841 vernnotice 147179 935 \n",
"6 60216187 simcopter1 16757 612 \n",
"7 67479479 mryagut 10899 555 \n",
"8 36852689 ryzentv 32355 483 \n",
"9 60494876 mackenseize 20332 338 \n",
"10 42596387 m989876525 4975 258 \n",
"11 47896635 hearthstonefr 43748 234 \n",
"12 51989691 inspectoraubriellama 5361 207 \n",
"13 43865938 puzzomns 1393 178 \n",
"14 84391327 telethor 4034 167 \n",
"15 28081485 happyzerg 10194 125 \n",
"16 89082781 billyisms 487 126 \n",
"17 65465714 koronekohs 1184 105 \n",
"18 66086067 khsjohnny 5518 94 \n",
"19 71440174 sonecarox 1271 86 \n",
"20 31117934 ray_sung 917 60 \n",
"21 30557587 gamecatt 15953 57 \n",
"22 43184697 fes_on 300 57 \n",
"23 91761304 devodest 38 50 \n",
"24 42746543 mantastlc 7230 46 \n",
"25 29795919 nl_kripp 524793 13097 \n",
"26 80549470 viagamehs 24227 4723 \n",
"27 60978448 hsdogdog 42454 2709 \n",
"28 20650414 tidesoftime 95628 1671 \n",
"29 31187787 hotform 14934 1012 \n",
"... ... ... ... ... \n",
"98420 38869748 nalguidan 1094 86 \n",
"98421 82369114 vicioussyndicategaming 629 76 \n",
"98422 31264406 bombaacme 574 56 \n",
"98423 47939440 duendepablo 2054 59 \n",
"98424 32560951 apdrop 17190 55 \n",
"98425 29795919 nl_kripp 545211 18426 \n",
"98426 27396889 reynad27 269947 9487 \n",
"98427 60978448 hsdogdog 46396 3390 \n",
"98428 30777889 itshafu 321560 2313 \n",
"98429 25871845 bmkibler 57123 768 \n",
"98430 22186763 xixo 29787 733 \n",
"98431 37470342 pvplive 25550 478 \n",
"98432 28382854 applejacked 66139 437 \n",
"98433 88398452 milleniumtvhs 10391 351 \n",
"98434 45330716 reall1992 10126 335 \n",
"98435 47896635 hearthstonefr 46833 314 \n",
"98436 31187787 hotform 17797 254 \n",
"98437 60216187 simcopter1 17794 233 \n",
"98438 42596387 m989876525 5939 228 \n",
"98439 92743746 starladder_hs_en 4686 189 \n",
"98440 55803438 arybeats 2745 140 \n",
"98441 89082781 billyisms 1157 139 \n",
"98442 84391327 telethor 5119 125 \n",
"98443 83644826 hughgamez 323 116 \n",
"98444 38869748 nalguidan 1094 91 \n",
"98445 82369114 vicioussyndicategaming 629 76 \n",
"98446 32560951 apdrop 17190 66 \n",
"98447 47939440 duendepablo 2054 62 \n",
"98448 31264406 bombaacme 574 59 \n",
"98449 61369223 rinigrandviper 1608 41 \n",
"\n",
" date_time years months days hours minutes \\\n",
"0 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"1 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"2 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"3 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"4 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"5 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"6 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"7 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"8 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"9 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"10 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"11 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"12 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"13 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"14 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"15 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"16 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"17 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"18 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"19 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"20 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"21 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"22 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"23 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"24 2015-05-30 22:42:38 2015 5 30 22 40 \n",
"25 2015-05-30 22:42:50 2015 5 30 22 40 \n",
"26 2015-05-30 22:42:50 2015 5 30 22 40 \n",
"27 2015-05-30 22:42:50 2015 5 30 22 40 \n",
"28 2015-05-30 22:42:50 2015 5 30 22 40 \n",
"29 2015-05-30 22:42:50 2015 5 30 22 40 \n",
"... ... ... ... ... ... ... \n",
"98420 2015-06-30 22:20:21 2015 6 30 22 20 \n",
"98421 2015-06-30 22:20:21 2015 6 30 22 20 \n",
"98422 2015-06-30 22:20:21 2015 6 30 22 20 \n",
"98423 2015-06-30 22:20:21 2015 6 30 22 20 \n",
"98424 2015-06-30 22:20:21 2015 6 30 22 20 \n",
"98425 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98426 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98427 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98428 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98429 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98430 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98431 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98432 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98433 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98434 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98435 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98436 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98437 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98438 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98439 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98440 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98441 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98442 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98443 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98444 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98445 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98446 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98447 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98448 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"98449 2015-06-30 22:30:59 2015 6 30 22 30 \n",
"\n",
" test \n",
"0 2015-05-30 22:40:00 \n",
"1 2015-05-30 22:40:00 \n",
"2 2015-05-30 22:40:00 \n",
"3 2015-05-30 22:40:00 \n",
"4 2015-05-30 22:40:00 \n",
"5 2015-05-30 22:40:00 \n",
"6 2015-05-30 22:40:00 \n",
"7 2015-05-30 22:40:00 \n",
"8 2015-05-30 22:40:00 \n",
"9 2015-05-30 22:40:00 \n",
"10 2015-05-30 22:40:00 \n",
"11 2015-05-30 22:40:00 \n",
"12 2015-05-30 22:40:00 \n",
"13 2015-05-30 22:40:00 \n",
"14 2015-05-30 22:40:00 \n",
"15 2015-05-30 22:40:00 \n",
"16 2015-05-30 22:40:00 \n",
"17 2015-05-30 22:40:00 \n",
"18 2015-05-30 22:40:00 \n",
"19 2015-05-30 22:40:00 \n",
"20 2015-05-30 22:40:00 \n",
"21 2015-05-30 22:40:00 \n",
"22 2015-05-30 22:40:00 \n",
"23 2015-05-30 22:40:00 \n",
"24 2015-05-30 22:40:00 \n",
"25 2015-05-30 22:40:00 \n",
"26 2015-05-30 22:40:00 \n",
"27 2015-05-30 22:40:00 \n",
"28 2015-05-30 22:40:00 \n",
"29 2015-05-30 22:40:00 \n",
"... ... \n",
"98420 2015-06-30 22:20:00 \n",
"98421 2015-06-30 22:20:00 \n",
"98422 2015-06-30 22:20:00 \n",
"98423 2015-06-30 22:20:00 \n",
"98424 2015-06-30 22:20:00 \n",
"98425 2015-06-30 22:30:00 \n",
"98426 2015-06-30 22:30:00 \n",
"98427 2015-06-30 22:30:00 \n",
"98428 2015-06-30 22:30:00 \n",
"98429 2015-06-30 22:30:00 \n",
"98430 2015-06-30 22:30:00 \n",
"98431 2015-06-30 22:30:00 \n",
"98432 2015-06-30 22:30:00 \n",
"98433 2015-06-30 22:30:00 \n",
"98434 2015-06-30 22:30:00 \n",
"98435 2015-06-30 22:30:00 \n",
"98436 2015-06-30 22:30:00 \n",
"98437 2015-06-30 22:30:00 \n",
"98438 2015-06-30 22:30:00 \n",
"98439 2015-06-30 22:30:00 \n",
"98440 2015-06-30 22:30:00 \n",
"98441 2015-06-30 22:30:00 \n",
"98442 2015-06-30 22:30:00 \n",
"98443 2015-06-30 22:30:00 \n",
"98444 2015-06-30 22:30:00 \n",
"98445 2015-06-30 22:30:00 \n",
"98446 2015-06-30 22:30:00 \n",
"98447 2015-06-30 22:30:00 \n",
"98448 2015-06-30 22:30:00 \n",
"98449 2015-06-30 22:30:00 \n",
"\n",
"[98450 rows x 11 columns]"
]
}
],
"prompt_number": 23
}
],
"metadata": {}
}
]
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment