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NPS sentiment analysis
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{
"cells": [
{
"cell_type": "code",
"execution_count": 202,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import math\n",
"import pandas as pd\n",
"import matplotlib.pylab as plt\n",
"plt.style.use('fivethirtyeight')\n",
"%matplotlib inline\n",
"\n",
"pd.options.mode.chained_assignment = None # turn off index slice warnings"
]
},
{
"cell_type": "code",
"execution_count": 183,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Date', 'Product Type', 'Customer Type', 'Sales Channel',\n",
" 'Sales Representative', 'Name', 'NPS', 'Comment', 'Repurchase',\n",
" 'Key Improvement', 'SurveyCompleted', 'CustomerReferenceID',\n",
" 'Would you be willing to provide a testimonial that may be used in future marketing',\n",
" '6.0', 'Unnamed: 14'],\n",
" dtype='object')"
]
},
"execution_count": 183,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dfTemp = pd.read_csv('./NG_Comments_20160913.csv')\n",
"dfTemp.columns"
]
},
{
"cell_type": "code",
"execution_count": 184,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Date</th>\n",
" <th>NPS</th>\n",
" <th>Comment</th>\n",
" <th>Repurchase</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>12/09/2016 12:05:37 a.m.</td>\n",
" <td>10</td>\n",
" <td>Very good price, great online account features</td>\n",
" <td>Highly Likely</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>11/09/2016 11:39:46 p.m.</td>\n",
" <td>10</td>\n",
" <td></td>\n",
" <td>Highly Likely</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>11/09/2016 11:13:47 p.m.</td>\n",
" <td>10</td>\n",
" <td>helpful service</td>\n",
" <td>Highly Likely</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>11/09/2016 11:02:24 p.m.</td>\n",
" <td>1</td>\n",
" <td>The charges are cheaper</td>\n",
" <td>Highly Likely</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>11/09/2016 10:53:49 p.m.</td>\n",
" <td>10</td>\n",
" <td>Im happy with the service so far</td>\n",
" <td>Highly Likely</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Date NPS \\\n",
"20 12/09/2016 12:05:37 a.m. 10 \n",
"21 11/09/2016 11:39:46 p.m. 10 \n",
"22 11/09/2016 11:13:47 p.m. 10 \n",
"23 11/09/2016 11:02:24 p.m. 1 \n",
"24 11/09/2016 10:53:49 p.m. 10 \n",
"\n",
" Comment Repurchase \n",
"20 Very good price, great online account features Highly Likely \n",
"21 Highly Likely \n",
"22 helpful service Highly Likely \n",
"23 The charges are cheaper Highly Likely \n",
"24 Im happy with the service so far Highly Likely "
]
},
"execution_count": 184,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cols = ['Date', 'NPS', 'Comment', 'Repurchase' ]\n",
"dfNPS = dfTemp[cols]\n",
"dfNPS['Comment'].fillna('', inplace=True)\n",
"dfNPS.iloc[20:25,:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Sentiment analysis using AFINN\n",
"http://www2.imm.dtu.dk/pubdb/views/publication_details.php?id=6010\n",
"\n",
"AFINN is a list of English words rated for valence with an integer between minus five (negative) and plus five (positive). The words have been manually labeled by Finn Årup Nielsen in 2009-2011\n",
"\n",
"The [afinn Pypi library](https://github.com/fnielsen/afinn), when worknig iwth english, uses the 'AFINN-en-165.txt' to score words"
]
},
{
"cell_type": "code",
"execution_count": 185,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from afinn import Afinn\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In AFINN, words are given a sentiment score. A snaphot of this is show below"
]
},
{
"cell_type": "code",
"execution_count": 186,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>thrilled</th>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dislikes</th>\n",
" <td>-2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>acceptable</th>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>oks</th>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>loomed</th>\n",
" <td>-1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0\n",
"thrilled 5\n",
"dislikes -2\n",
"acceptable 1\n",
"oks 2\n",
"loomed -1"
]
},
"execution_count": 186,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"afinn = Afinn()\n",
"pd.DataFrame.from_dict(afinn.read_word_file(afinn.full_filename('AFINN-en-165.txt' )), orient='index').iloc[100:105, :]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To determine the sentiment of the NPS comments, we can apply the AFINN score method to each comment"
]
},
{
"cell_type": "code",
"execution_count": 187,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Date</th>\n",
" <th>NPS</th>\n",
" <th>Comment</th>\n",
" <th>Repurchase</th>\n",
" <th>sentiment</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>12/09/2016 12:05:37 a.m.</td>\n",
" <td>10</td>\n",
" <td>Very good price, great online account features</td>\n",
" <td>Highly Likely</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>11/09/2016 11:39:46 p.m.</td>\n",
" <td>10</td>\n",
" <td></td>\n",
" <td>Highly Likely</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>11/09/2016 11:13:47 p.m.</td>\n",
" <td>10</td>\n",
" <td>helpful service</td>\n",
" <td>Highly Likely</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>11/09/2016 11:02:24 p.m.</td>\n",
" <td>1</td>\n",
" <td>The charges are cheaper</td>\n",
" <td>Highly Likely</td>\n",
" <td>-2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>11/09/2016 10:53:49 p.m.</td>\n",
" <td>10</td>\n",
" <td>Im happy with the service so far</td>\n",
" <td>Highly Likely</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Date NPS \\\n",
"20 12/09/2016 12:05:37 a.m. 10 \n",
"21 11/09/2016 11:39:46 p.m. 10 \n",
"22 11/09/2016 11:13:47 p.m. 10 \n",
"23 11/09/2016 11:02:24 p.m. 1 \n",
"24 11/09/2016 10:53:49 p.m. 10 \n",
"\n",
" Comment Repurchase sentiment \n",
"20 Very good price, great online account features Highly Likely 6.0 \n",
"21 Highly Likely 0.0 \n",
"22 helpful service Highly Likely 2.0 \n",
"23 The charges are cheaper Highly Likely -2.0 \n",
"24 Im happy with the service so far Highly Likely 3.0 "
]
},
"execution_count": 187,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dfNPS.loc[:,'sentiment'] = dfNPS.loc[:,'Comment'].apply(lambda x: afinn.score(x))\n",
"dfNPS.iloc[20:25, :]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The table below provides a summary of the distribution of sentiment by NPS"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th>sentiment</th>\n",
" <th>-14.0</th>\n",
" <th>-13.0</th>\n",
" <th>-11.0</th>\n",
" <th>-10.0</th>\n",
" <th>-9.0</th>\n",
" <th>-8.0</th>\n",
" <th>-7.0</th>\n",
" <th>-6.0</th>\n",
" <th>-5.0</th>\n",
" <th>-4.0</th>\n",
" <th>...</th>\n",
" <th>10.0</th>\n",
" <th>11.0</th>\n",
" <th>12.0</th>\n",
" <th>13.0</th>\n",
" <th>14.0</th>\n",
" <th>15.0</th>\n",
" <th>16.0</th>\n",
" <th>17.0</th>\n",
" <th>18.0</th>\n",
" <th>19.0</th>\n",
" </tr>\n",
" <tr>\n",
" <th>NPS</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" <td>7</td>\n",
" <td>8</td>\n",
" <td>15</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>0</td>\n",
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" <td>2</td>\n",
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" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
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" <th>2</th>\n",
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" <td>0</td>\n",
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" <tr>\n",
" <th>4</th>\n",
" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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" <tr>\n",
" <th>5</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" <td>6</td>\n",
" <td>10</td>\n",
" <td>24</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
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" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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" <tr>\n",
" <th>6</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>10</td>\n",
" <td>11</td>\n",
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" <tr>\n",
" <th>7</th>\n",
" <td>0</td>\n",
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" <td>0</td>\n",
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" <td>1</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" <td>16</td>\n",
" <td>...</td>\n",
" <td>4</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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" <tr>\n",
" <th>8</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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" <td>0</td>\n",
" <td>0</td>\n",
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" <td>1</td>\n",
" <td>5</td>\n",
" <td>19</td>\n",
" <td>23</td>\n",
" <td>...</td>\n",
" <td>8</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>4</td>\n",
" <td>7</td>\n",
" <td>18</td>\n",
" <td>30</td>\n",
" <td>...</td>\n",
" <td>12</td>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>5</td>\n",
" <td>15</td>\n",
" <td>20</td>\n",
" <td>50</td>\n",
" <td>...</td>\n",
" <td>31</td>\n",
" <td>17</td>\n",
" <td>12</td>\n",
" <td>5</td>\n",
" <td>3</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>11 rows × 33 columns</p>\n",
"</div>"
],
"text/plain": [
"sentiment -14.0 -13.0 -11.0 -10.0 -9.0 -8.0 -7.0 -6.0 -5.0 \\\n",
"NPS \n",
"0 0 1 1 0 4 1 9 7 8 \n",
"1 1 0 0 0 2 2 0 3 9 \n",
"2 0 0 0 0 0 2 2 6 9 \n",
"3 0 0 0 0 1 1 1 2 4 \n",
"4 0 0 0 0 0 1 0 0 7 \n",
"5 0 0 0 1 2 4 2 6 10 \n",
"6 0 0 0 1 0 2 4 4 10 \n",
"7 0 0 0 0 0 1 3 1 7 \n",
"8 0 0 0 0 0 0 1 5 19 \n",
"9 0 0 0 1 0 0 4 7 18 \n",
"10 0 0 0 0 2 3 5 15 20 \n",
"\n",
"sentiment -4.0 ... 10.0 11.0 12.0 13.0 14.0 15.0 16.0 \\\n",
"NPS ... \n",
"0 15 ... 0 0 0 0 0 0 0 \n",
"1 9 ... 0 0 0 1 0 0 0 \n",
"2 5 ... 2 0 1 0 0 0 0 \n",
"3 8 ... 0 0 0 0 0 0 0 \n",
"4 13 ... 0 0 0 0 0 0 0 \n",
"5 24 ... 0 1 0 0 0 0 0 \n",
"6 11 ... 1 0 0 0 0 0 0 \n",
"7 16 ... 4 3 1 1 0 0 0 \n",
"8 23 ... 8 2 2 2 1 0 0 \n",
"9 30 ... 12 4 2 1 0 0 0 \n",
"10 50 ... 31 17 12 5 3 5 1 \n",
"\n",
"sentiment 17.0 18.0 19.0 \n",
"NPS \n",
"0 0 0 0 \n",
"1 0 0 0 \n",
"2 0 0 0 \n",
"3 0 0 0 \n",
"4 0 0 0 \n",
"5 0 0 0 \n",
"6 0 0 0 \n",
"7 0 0 0 \n",
"8 1 0 0 \n",
"9 0 0 1 \n",
"10 1 1 1 \n",
"\n",
"[11 rows x 33 columns]"
]
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.crosstab(dfNPS.NPS, dfNPS.sentiment)"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"source": [
"The following violin plots show the distribution of sentiment with NPS graphically.\n",
"\n",
"The left plot show the distribution of the sentiment for each comment with a certain NPS score. \n",
"\n",
"The right plot shows similar information but the size of the 'violin' is scaled by the number of comments in each NPS bucket. It is clear from this that most NPS scores are eight and above."
]
},
{
"cell_type": "code",
"execution_count": 207,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def violin_sentiment(df, y):\n",
" fig, axes = plt.subplots(1, 2, figsize=(15,10), facecolor = 'white')\n",
" sns.violinplot(x=\"NPS\", y=y, data=df, palette=\"muted\", bw=.2, ax=axes[0], width=2, font=10)\n",
" sns.violinplot(x=\"NPS\", y=y, data=df, palette=\"muted\", bw=.2, scale='count', ax=axes[1], width=2)\n",
" for ax in axes:\n",
" subtitle = '\\n Scaled by count' if (ax==axes[1]) else \"\"\n",
" ax.set_title('Sentiment v NPS' + subtitle)\n",
" ax.set_axis_bgcolor('white')\n",
" ax.grid(b=True, which='major', color='#d3d3d3', linestyle='-')"
]
},
{
"cell_type": "code",
"execution_count": 208,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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8vDy99dZb+vDDD90uxc+mTZs0Y8YM7dixQzNmzNCmTZvcLqnRov0HgKanpqZG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\nQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f0440e3f1d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"violin_sentiment(dfNPS, 'sentiment')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Looking further at these charts, a few things are apparent:\n",
"* there are a lot of comments with a zero sentiment\n",
"* there are a lot more comments for high NPS scores, than for lower ones.\n",
"* there doesn't appear to be much ofd a trend in increasing sentiment with increasing NPS"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can see the distribution of comments by NPS in the bar chart below and, to get better feeling for any trend in sentiment with NPS, we can look at the weighted mena sentiment for each NPS score. \n",
"\n",
"A weighted mean will remove the impact of the zero sentiment comments and make the more negative or more positive a comment is have a larger overall impact on sentiment and we can normalise it by the comment counts to get a trend of snetiment"
]
},
{
"cell_type": "code",
"execution_count": 209,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"\n",
"def weighted_sentiment(df, y):\n",
" dfCross = pd.crosstab(df.NPS, dfNPS[y]) # capture cross tab summary\n",
" dfCounts = dfNPS.groupby('NPS').count() # count number of comments per NPSsocre\n",
" dfCross = dfCross.multiply(dfCross.columns.values, axis=1) # multiply NPS-sentiment count by sentiment\n",
" dfCross = dfCross.divide(dfCounts['Comment'].values, axis=0) # Normalise the weighted scores by the count of comments\n",
" dfCross['Sum'] = dfCross.sum(axis=1) # Sum the normalised weighted sentiments\n",
" \n",
" fig, axes = plt.subplots(1, 2,figsize=(10,5), facecolor='white')\n",
" axes[0].bar(dfCounts.index, dfCounts['Comment'])\n",
" axes[1].plot(dfCross.index, dfCross['Sum'])\n",
" for ax in axes:\n",
" ax.set_axis_bgcolor('white')\n",
" ax.grid(b=True, which='major', color='#d3d3d3', linestyle='-')\n",
" ax.set_xlim([0,10])\n",
" ax.set_xlabel('NPS')\n",
" ax.set_ylabel('Count')\n",
"\n",
" axes[0].set_title('Count of comments by NPS')\n",
" axes[1].set_title('Weighted sentiment')\n",
" axes[1].set_ylim([-1,2])"
]
},
{
"cell_type": "code",
"execution_count": 210,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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RUlNT4eDgAHt7e8mobGpqKjw8PGBvb4+MjAy4urpCpVJBCAE7OztkZ2dLtq3o\nXLL27dtXeXtqi4SEBL1uH8A26gt9b2NOTo6uQ6iUIUOGaH7u2bMnLl68WKFEV59/l/r+WQXYRn1R\nF9uYW1yGyb8k4WZxiaS8fwtLvOfjALlMpimrTL+qs+XFvLy8sG/fPgDAvn374OvrCzc3NyQkJCA/\nPx8FBQU4e/YsOnfuDB8fH0RHRwMAYmJi0L17dygUCrRs2RJnzpwBAOzfvx++vr66ag4RUZ2Xn5+P\nSZMmaVbBOXXqFJ5++mkdR0VE+qqgVI0ZMUpcvCVNcgOammORtzTJrawaGdFNTExEREQElEolDAwM\nsG/fPqxYsQIhISH49ttv4eTkhKFDh0KhUGD27NmYOHEi5HI5Zs6cCQsLC/Tv3x+xsbEYO3YsjI2N\nERERAQAIDQ1FWFgYhBDo2LHjA+8iJiKiO8rrjwMCAtCkSRMEBgaiV69eGDVqFExMTNC2bVv07dtX\n1yETkR66rVLjjYNK/JlxW1Lu7WSGcF9HGMifPMkFAJmoJ7fX3jvcbWVlpcNIqlddvGzxuNhG/aDv\nbawPfU59aCOg/59VgG3UF3WljaVlAm8eUiJWWSgp97A3wSe9nWFqUP6Eg8r0OXwyGhERERHVCJVa\nIPRYilaS287WGB/7Oz0wya0sJrpEREREVO3UQmBRfCoOXM+XlD9tbYRPejvDwkhR5edkoktERERE\n1UoIgYiT6dh7JU9S3szSEJ8GOsPKuOqTXICJLhERERFVIyEEVp/JxHcXpcuDNTY3wGd9nGFrWn1r\nIzDRJSIiIqJq8/mfWYj665akrJGpAusCneFoblit52aiS0RERETV4qu/buHTc1mSMmtjOdYFOqNZ\ng4c/jrwqMNElIiIioiq3658crDydISmzMJRjbW9ntLI2rpEYmOgSERERUZX6+d9cLDmeJikzUciw\nJsAJbWxNaiwOJrpEREREVGUOXs/HgthU3PtEMkO5DKv8neBub1qjsTDRJSIiIqIqEa8swDtHU1B2\nT5ZrIAOW93SEZ2OzGo+HiS4RERERPbEzqUWYdegmStX/ZbkyAO/5OMKvqYVOYmKiS0RERERPJDHj\nNl47qMTte4dyAYR52aNfC0sdRcVEl4iIiIiewD+3ijH912QUlKol5XO62OG5p6x0FNUdTHSJiIiI\nqFKu5ZZg6oFk5JRIk9wZ7rYY28ZaR1H9h4kuERERET02ZX4ppvySjMzbZZLyie0bYlIHGx1FJcVE\nl4iIiIg8IjNgAAAgAElEQVQeS3qhClMOJCOlUCUpH+1qhRnutjqKShsTXSIiIiKqsNSCUkw5kIwb\neaWS8iGtGmBOVzvIZDIdRabNQNcBEBEREVHtJ4TA/67kYfmpdOTfd+NZkIsFFnjaQ16LklyAiS4R\nERERPUJaoQpLjqfiaHKhVl1PZ3Ms8XGEQl67klyAiS4RERERPYAQAj/+m4dlp9KRd9/KCgDg7WSG\nZX6OMFTUviQXYKJLREREROXIKFJhyfE0HE4q0KozUcgw06MRRre2qnXTFe7FRJeIiIiINIQQiL6a\njw9OpmmtjwsA7nYmeNfbAS4NjHQQ3eNhoktEREREAICsIhWWnkxDzHXtUVxjhQzT3W0xtrV1rZyP\nWx4mukRERESEX67l4f0T6cguLtOq69DIBIu8HdDCqvaP4t6LiS4RERFRPZZ1W4WIk+n45Vq+Vp2R\nXIap7jYIbtOwzozi3ouJLhEREVE99ev1fCw9noZb5YzitrM1xiJvB7SyNtZBZFWDiS4RERFRPZNd\nXIYPTqYh+qr2KK6BHJjiZosX2zWEQR0cxb0XE10iIiKieuTgjTujuJm3tUdx29gYY7G3A55qWHdH\nce/FRJeIiIioHsgtLsOy39Lx45U8rToDOfBKB1tMaN8QhnV8FPdeTHSJiIiI9NzRpAIsPp6KjCLt\nUVzXhnfm4rra6Mco7r2Y6BIRERHpqbySMqz8LQM/XM7VqjOQAZM62GBSe5ta+wjfJ8VEl4iIiEgP\nxSYXYPHxNKQVqrTqnrY2wiJvB7SxNdFBZDWHiS4RERGRHskvKcOHpzOw+5L2KK5CBrzUriEmu9nA\nSCHXQXQ1i4kuERERkZ44frMQi+JSkVLOKG5LKyMs9nFAOz0fxb0XE10iIiKiOq6gVI1N1w0QczZZ\nq04uA15s2xCvdrSBcT0Yxb0XE10iIiKiOuxMahEWxKZAWaDQqmvRwBCLvB3Rwa7+jOLei4kuERER\nUR318795CItLgUotLZcBCG5rjakdbWFiUL9Gce+ls0S3sLAQ77zzDnJyclBaWorp06fjqaeewpw5\ncyCEgJ2dHZYtWwZDQ0Ps2bMHmzdvhkKhwIgRIzB8+HCoVCqEhIRAqVRCoVAgPDwcTZo00VVziIjq\njIsXL2L69OmYMGECXnjhBUldXFwcVq1aBYVCgZ49e2LatGk6ipKIHmXzX7ew6nSGVnkzS0Ms8naA\nu72pDqKqXXSW6O7evRstW7bEm2++ibS0NLz44otwd3fHuHHj0LdvX6xatQo7d+7EkCFDsHbtWuzc\nuRMGBgYYPnw4goKCEBMTAysrK6xYsQKxsbFYuXIlVq1apavmEBHVCUVFRViyZAm8vLzKrV+6dCk2\nbtwIe3t7TX/cqlWrGo6SiB5GLQRWnc7AV39na9WNbW2NGR62MK3Ho7j30lmi27BhQ1y4cAEAkJOT\nAxsbG5w6dQqLFy8GAPj7+2Pjxo1o3rw53NzcYG5uDgDo1KkTTp8+jfj4eDz33HMAAG9vb4SGhuqm\nIURUZ1xLzkJadmGVH9fe2gwuzjZVftzqYGxsjA0bNmD9+vVadTdu3IC1tTUcHBwAAH5+fjh+/DgT\nXaJapKRMjYVxqYi+mi8pN5ADk5uW4pWudjqKrHbSWaLbv39/7Nq1C0FBQcjNzcVnn32GadOmwdDQ\nEABga2uLtLQ0ZGZmwsbmvy8QGxsbpKenIyMjQ1Muk8kgl8uhUqlgYMBpx0RUvrTsQizeeLrKjxs2\nsXOdSXTlcjmMjIzKrbu3XwXu9Lc3btyoqdCI6BHyS8ow+/BNnEwpkpSbG8qx0q8xzDOv6Ciy2ktn\nWeGePXvg5OSEDRs24MKFC5g7d66kXghR7n4PKler1eWWExFR5TyovyWimpdeqMKMmGRcvFUiKW9k\nqkBkgDNcbYyRkKmj4GoxnSW6Z86cga+vLwDA1dUV6enpMDU1RUlJCYyMjJCamgoHBwfY29sjPT1d\ns19qaio8PDxgb2+PjIwMuLq6QqW6syhyRUdzExISqr5BtYi+tw9gG/VFTbexoNCweo5bUKDVlqZN\nm1bLuapTef2tvb19hfbV98+rvrcPYBtrs5u3ZVh22RAZJTJJuaOxGnNaFKNU+Q8SlHfK6mobK6Iy\n/arOEl0XFxf8/vvv6NOnD5KTk2Fubo5u3bohOjoagwcPxr59++Dr6ws3NzfMnz8f+fn5kMlkOHv2\nLObNm4e8vDxER0fDx8cHMTEx6N69e4XP3b59+2psmW4lJCTodfsAtlFf6KKNpxKTquW45ubmaN9O\nuupLTk5OtZyrOjk7O6OgoABKpRL29vY4dOgQVq5cWaF99fnzyr9H/VBX23guvQhLY5TIKZFeue7Q\nyASr/Z3Q0OS/tXPrahsrqjL9qs4S3VGjRiE0NBTBwcEoKyvD4sWL0aJFC7zzzjvYvn07nJycMHTo\nUCgUCsyePRsTJ06EXC7HzJkzYWFhgf79+yM2NhZjx46FsbExIiIidNUUIqI6IzExEREREVAqlTAw\nMMC+ffsQEBCAJk2aIDAwEAsXLsSsWbMAAAMHDoSLi4uOIyaqvw7fyEfI0RTcLpNOI+rpbI4IX0eY\nGnJlhUfRWaJrZmaGjz76SKt848aNWmVBQUEICgqSlMnlcoSHh1dbfERE+qhdu3bYsmXLA+u7dOmC\nbdu21WBERFSeXf/kYOmJNKjvmyr/3FMNMK+7PQzksvJ3JAkuUUBERERUSwghsP6PLKz7I0ur7hU3\nG0xxs4FMxiS3opjoEhEREdUCKrVA+Ik07LqUKymXy4C53ewx/BkrHUVWdzHRJSKdKIVJtd0cVpce\n4EBEBABFKjXmHk3B4aQCSbmxQoZwX0f4N7XQUWR1GxNdItKJnMIyrPy26h/eANStBzgQEWUXl+H1\ng0r8kX5bUm5lJMdH/k5wtzfVUWR1HxNdIiIiIh1R5pdi+q/JuJpbKil3NDfAJ72d0dKq/CcZUsUw\n0SUiIiLSgQtZxZgRk4yMojJJ+dMNjRAZ4Ax7M6ZpT4rvIBEREVENO3mzELMP30R+qfRBEF0cTPFh\nr8awNFI8YE96HEx0iYiIiGpQ9L95WBCXApU0x0WQiwXe83GAkYIPgqgqTHSJiIiIashXf93CytMZ\nWuUvtLbGrC6NIOcauVWKiS4RERFRNVMLgY/OZGDLX9ladW92aoTgttZ8EEQ1YKJLREREVI1KywQW\nxqXi56t5knIDGbDI2wH9WzbQUWT6j4kuERERUTXJLynDW4dv4kRKkaTczECGlX6N4elkrqPI6gcm\nukRERETVIKNIhRm/KnHhVrGk3NZEgTUBTmhja6KjyOoPJrpEREREVexabgmmHUiGskAlKW9maYhP\nejujiaWhjiKrX5joEhEREVWhP9Nv47WDycgulq4f1t7WGKsDnGBjwvSrpvCdJiIiIqoiR5Ly8c6R\nFNwuE5LyHs5mWObbGKaGXCO3JjHRJSIiIqoC313MRsTJdKilOS6GtGqA+Z72MJBz+bCaxkSXiIiI\n6AmohUDk2UxsSrylVfdyBxtM62jDNXJ1hIkuERERUSWVlgm8G5+Kn/6VrpErlwEh3eww4hlrHUVG\nABNdIiIiokrJKynD7EM3cSpVukauiUKGCF9H+DW10FFkdBcTXSIiIqLHlFJQipkxSlzKLpGUNzS+\ns0Zuu0ZcI7c2YKJLRERE9Bgu3irGzBgl0gq118iN7O2EppZGOoqM7sdEl4iIiKiCjt8sxFuHb6Kg\nVLpGrpudCT7q5YSGJgodRUblYaJLREREVAH/u5yLxfGpUN23fFhAM3Ms9XGEiQHXyK1tmOgSERER\nPYQQAhv+vIW15zK16sa0tsbszo2g4Bq5tRITXSIiIqIHUKkFwk+kYdelXK26WZ0bYVwba66RW4sx\n0SUiIiIqR2GpGu8cvYljyYWSckO5DEt8HBDU3FJHkVFFMdElIiIiuk9GkQqvxSjxd1axpLyBkRyr\nejmhk4OpjiKjx8FEl4iIiOge/+aUYMavyVAWSJcPa2xugMjezmhpxeXD6ooK3R44e/bscstHjBhR\npcEQEdEd7HeJdONsWhEmRN/QSnLb2Bhj87NNmeTWMQ8d0Y2JiUFMTAyOHj2KBQsWSOpyc3Nx/fr1\nag2OiKi+Yb9LpDu/XMvD/GOpKFFL1w/zcTLDsp6NYWbI5cPqmocmuh07dkRRUREOHDgABwcHSZ2z\nszNefvnlag2OiKi+Yb9LpBtf/XULH57OwH1L5GLoUw0Q2t0eBlw+rE56aKJra2uLAQMGoEWLFmjb\ntm1NxUREVG+x3yWqWWVqgQ9PZ2Dr+WytuqkdbTC5gw2XD6vDKnQzWmFhISZNmgSlUgm1WvrIu337\n9lVLYERE9Rn7XaLqd1ulxvzYVPx6PV9SbiADFng5YHCrBjqKjKpKhRLdkJAQjBkzBm3btoVCwWc4\nExFVN/a7RNUru7gMbxxU4lz6bUm5uaEcK3o6wtPJXEeRUVWqUKJrZGSESZMmVXcsRET0/9jvElWf\npLxSzIhJxrXcUkm5nakCawKc4WpjrKPIqKpV6PbBwMBAHDx4sLpjISKi/8d+l6h6JGbcxovRN7SS\n3FZWRtj8bFMmuXqmQiO6J0+exJdffgkLCwtYWkofd8e5YkREVY/9LlHVO5KUj3eOpOB2mXRtha4O\npljZqzEsjThNSN9UKNGdNWtWtZx8z549+OKLL2BgYIDXXnsNrq6umDNnDoQQsLOzw7Jly2BoaIg9\ne/Zg8+bNUCgUGDFiBIYPHw6VSoWQkBAolUooFAqEh4ejSZMm1RInEVFNq65+Nzw8HOfOnYNMJkNo\naCg6dOigqQsICICTkxNkMhlkMhlWrFgBe3v7aomDqKbFZMgR9ftN3LdELvq3sMRCL3sYKbhGrj6q\nUKLr4uJS5SfOzs7GJ598gu+//x4FBQX4+OOPER0djeDgYAQFBWHVqlXYuXMnhgwZgrVr12Lnzp0w\nMDDA8OHDERQUhJiYGFhZWWHFihWIjY3FypUrsWrVqiqPk4hIF6qj3z116hSuXbuGbdu24fLly5g3\nbx62bdumqZfJZNiwYQNMTEyq/NxEuiKEwCe/Z2LTDUOtupfaNcQMD1vIuXyY3qpQouvn5weZTAYh\n7vw3SCaTQS6Xw8LCAidOnKjUiePi4uDj4wNTU1OYmppi8eLF6N27NxYvXgwA8Pf3x8aNG9G8eXO4\nubnB3PzO3Y+dOnXC6dOnER8fj+eeew4A4O3tjdDQ0ErFQURUG1VHvxsfH4/AwEAAQKtWrZCbm4uC\nggJN/yqE0JyPSB+UlKmxOD4NP/6bJymXy4B3utphpKu1jiKjmlKhRPf8+fOS1zk5Odi5c6emc6yM\n5ORkFBUVYerUqcjLy8P06dNx+/ZtGBre+R+Xra0t0tLSkJmZCRsbG81+NjY2SE9PR0ZGhqb87heA\nSqWCgUGFmkREVKtVR7+bkZGB9u3ba143bNgQGRkZkmMuXLgQSUlJ6NKlS7VNnyCqCbnFZZh1+CZO\npxZJyk0UMoT7OqJXUwsdRUY1qVJZoZWVFSZOnIihQ4di1KhRlTqxEEIzfSE5ORnjx4+XjCQ8aFTh\nQeX3L6j+MAkJCY8XbB2j7+0D2Eb9oH0ZsaoUFBSU+/4VFFbPOcs7X9OmTav0HFXR797v/v709ddf\nh6+vL6ytrTFt2jTs378fQUFBFTqWvn9e9b19gH61Ma0YWHnZEMpi6bxbSwOB2S1L0CjnKhJydBRc\nNdOn3+P9KtOvVijRTU1NlbxWq9U4f/48MjMzH/uEdzVq1AgeHh6Qy+Vo2rQpzM3NYWBggJKSEhgZ\nGSE1NRUODg6wt7dHenq6JBYPDw/Y29sjIyMDrq6uUKlUdxpTwdHce0c09E1CQoJetw9gG/XFoZMX\nqu3Y5ubmaN9O++bUU4lJNXa+nJwn+xatjn73br95V1paGuzs7DSvhwwZovm5Z8+euHjxYoUTXX3+\nvNaHv0d9auOf6bex9JASWcVlknJHYzXWP9sCTS2NdBRZ9dOn32N5KtOvVmqOrlwuh729/RNd1vLx\n8UFoaCgmT56M7OxsFBYWokePHoiOjsbgwYOxb98++Pr6ws3NDfPnz0d+fj5kMhnOnj2LefPmIS8v\nD9HR0fDx8UFMTAy6d+9e6ViIiGqb6up3IyMjMXLkSCQmJsLBwQFmZmYAgPz8fLz++utYt24dDA0N\ncerUKfTr169K2kJUU2Ku5yP0WAqK71s+zMPeBJMdcvQ6yaXyVWqOblVwcHBA3759MXLkSMhkMoSF\nhaF9+/Z4++23sX37djg5OWHo0KFQKBSYPXs2Jk6cCLlcjpkzZ8LCwgL9+/dHbGwsxo4dC2NjY0RE\nRFR5jEREulId/a6HhwfatWuH0aNHQ6FQICwsDLt374alpSUCAwPRq1cvjBo1CiYmJmjbti369u1b\n5TEQVQchBL7+Oxsfns7A/RMc+zW3wLveDvjnbz2dq0APVaFEVwiBvXv3IjY2FpmZmWjUqBF69er1\nxJ3gyJEjMXLkSEnZxo0btbYLCgrSunwml8sRHh7+ROcnIqqtqqvfvX9E2NXVVfNzcHAwgoODn+j4\nRDWtTC2w/Ld0fHtBO5F9uX1DTHXn8mH1WYUS3WXLluG3337DoEGD0KBBA2RnZ+Ozzz7DP//8gxkz\nZlR3jERE9Q77XaJHKyxVY+7RFBxJLpCUK2TAvO72GPq0lY4io9qiQonukSNHsGvXLhgb//f855Ej\nR2LEiBHscImIqgH7XaKHSy9U4fWDSvydVSwpNzeUY3lPR3g5VX4pPtIfFUp0y8rKYGQkncBtYmLy\nWEt6ERFRxbHfJXqwS7eKMfOgEikFKkm5o5kBPg5wwtMNjR+wJ9U3FUp0u3XrhqlTp2LkyJGaS2g7\nduyAp6dndcdHRFQvsd8lKt/xm4WYc/gm8kul/+lrbWOM1f5OsDfjg6PoPxX6NISGhmLz5s344osv\nkJWVBQsLCzz77LMYN25cdcdHRFQvsd8l0vbDpRwsOZ4G1X1LK/g6myHCtzHMDOXl70j11kM/Efn5\n+Rg3bhyOHz+OV155BV9//TV+/vlneHt7V/pZ60RE9GDsd4m0CSHwye+ZeDdeO8kd8YwVPuzlxCSX\nyvXQT8WHH36I5s2bw9vbW1I+c+ZM2NjYIDIyslqDIyKqb9jvEkmVlKkx71gqNvyZJSmXAXizcyPM\n7WYHAzmXD6PyPTTRPXbsGObPn691Q4SBgQHCwsLw66+/VmtwRET1Dftdov/kFJdh6gElfr6aJyk3\nVsiwrKcjxrdtCBnXyKWHeOgcXYVCARMTk3LrTE1NefcvEVEVY79LdEdSXilmxiTjam6ppLyhsQIf\n+TeGm52pjiKjuuShI7oGBgZIT08vt+769euQyzkfhoioKrHfJQL+SC/C+J9vaCW5Lg0MEfVsEya5\nVGEP7TGff/55zJgxA1evXpWU//3335g+fTrGjBlTnbEREdU77HepvjtwLQ+v/JKMW8VlknIPexNE\n9WuKppZGD9iTSNtDpy689NJLyMjIwJAhQ+Do6IhGjRohNTUVmZmZmDRpEpe5ISKqYux3qb4SQmDL\n39n46HQG7ltYAc82t8S73vYwUvCKBj2eR66jO2fOHLzyyiv4/fffkZOTg4YNG8Ld3R2WlpY1ER8R\nUb3DfpfqG5VaYPmpdGy/mKNV93IHG0zraMObzqhSKvTACCsrK/j5+VV3LERE9P/Y71J9UViqRsjR\nmziaXCgpN5AB8zzt8dxTVjqKjPQBn5NHREREOpFWqMLrB5U4n1UsKbcwlGO5X2N4NjbTUWSkL5jo\nEhERUY3751YxXotRIqVQJSl3NDPAmgAnPNXQWEeRkT5hoktEREQ16riyAG8dSUFBqXRd6DY2xvjI\n3wn2ZkxPqGrwk0REREQ1Zvc/OXj/RBpU9y2t4OtshgjfxjAz5MoKVHWY6BIREVG1E0Lgsz+y8Nkf\nWVp1o1yt8FYXOxjIubICVS0mukRERFStVGqB8BNp2HUpV1IuAzCrcyO80Maay4dRtWCiS0RERNWm\nSKVGyNEUHEkqkJQbK2RY2sMRvZtZ6Cgyqg+Y6BIREVG1yC4uw+sHlfgj/bak3MpIjtUBTuhoZ6qj\nyKi+YKJLREREVU6ZX4oZvybj39xSSbmjuQHW9nZGCysjHUVG9QkTXSIiIqpSF28VY/qvycgoKpOU\nP93QCJEBzlw+jGoMP2lERERUZX5LKcSbh24i/741crs4mOLDXo1haaTQUWRUHzHRJSIioirxy7U8\nzDuWilK1dJHcIBcLvOfjACMF18ilmsVEl4iIiJ7YN+ezsfxUOu57DgTGtLbGW10aQc7lw0gHmOgS\nERFRpQkhsOZsJjYl3tKqe72TLV5s25Br5JLOMNElIiKiSilVCyyOT8XeK3mScgMZsNDbAQNbNtBR\nZER3MNElIiKix1ZYqsacIzcRpyyUlJsayLDCrzG8ncx1FBnRf5joEhER0WPJKlJh5kEl/soslpQ3\nNFZgTW8ntLM10VFkRFJMdImIiGqBwlI1Pj6bgbNpRWhjY4KRrlZoWwsTxht5JZj+qxI38qQPgmhq\naYjIACc0a8AHQVDtwUSXiIhIx0rLBGYdUuJEShEA4OKtEvxwORcdGplgtKsVAl0sasXSXH9l3sbM\nGCWybksfBNHGxhhrApxga8q0gmoXfiKJiIh0SC0E5semaJLce/2ZcRt/ZtzGit8yMOzpBhj2jBUc\nzQ11ECVwXFmA2YdvolAlXUDMq7EZlvs1hrmh7hNxovvxU0lERKQjQggsO5WO/dfyH7rdreIybEi4\nhYG7r2L2YSVOpRRCiPtXrK0+P17JxcwYpVaSO6CFJVb7OzHJpVqLI7pEREQ6suHPW/j2Qo6krJml\nIZwtDBF/s1Br+zIBxFwvQMz1ArS0MsIoVysMaNmg2hJNIQS2/JWNVWcytOomtGuImR62fBAE1WpM\ndImIiHRgx8UcrD2XKSmzM1Xg00BnOFkY4lpuCbZfyMGey7nIL1Vr7X8lpwThJ9Px8dlMDGxpiVGu\n1mhhVXU3gqmFwIenM/D139mSchmAt7o0wtg2DavsXETVReeJbnFxMQYOHIjp06fD09MTc+bMgRAC\ndnZ2WLZsGQwNDbFnzx5s3rwZCoUCI0aMwPDhw6FSqRASEgKlUgmFQoHw8HA0adJE180hIqrVwsPD\nce7cOchkMoSGhqJDhw6auri4OKxatQoKhQI9e/bEtGnTdBipfjtwLQ/hJ9MkZZZGcnzS+06SCwAu\nDYwwp6sdprvb4qd/8/DthWxcyi7ROlZBqRrfXsjBtxdy0M3RFKNdreHbxBwG8sqPtJaUqREWl4p9\nV6VTKgzlMrzn44C+zS0rfWyimqTzSTVr166FtbU1AGD16tUIDg7GV199hWbNmmHnzp0oKirC2rVr\nERUVhc2bNyMqKgq5ubnYu3cvrKyssHXrVkyZMgUrV67UcUuIiGq3U6dO4dq1a9i2bRuWLFmCpUuX\nSuqXLl2KyMhIfPPNN4iNjcXly5d1FKl+O5VSiNBjqVDfM93VWCHDan8nPN3QWGt7M0M5hj9jhe0D\nm2FDUBP0cbGA4gE57MmUIsw6fBODdl/FF39mIeu26rHjyy8pw8wYpVaSa2Eoxye9nZjkUp2i00T3\nypUruHLlCvz8/CCEwKlTp+Dv7w8A8Pf3R1xcHM6dOwc3NzeYm5vD2NgYnTp1wunTpxEfH4/AwEAA\ngLe3N86cOaPLphAR1Xr39putWrVCbm4uCgoKAAA3btyAtbU1HBwcIJPJ4Ofnh+PHj+syXL10Pus2\n3jx0E6X3ZLkKGfCBryM87E0fuq9MJkNnB1Ms69kYPz3fAq+42cDWRFHutimFKkT+nol+O69ifmwK\nEjJuVyi+9EIVJu1Pwsn7VoBoZKrAhqAm6OpoVqHjENUWOk10P/jgA4SEhGheFxUVwdDwziUbW1tb\npKWlITMzEzY2NpptbGxskJ6ejoyMDE25TCaDXC6HSvX4/3MlIqov7u03AaBhw4bIyMgot87GxgZp\naWlax6DKu55750ELBffNtw3zcoBfU4vHOpa9mQGmdrTFz8+3QHgPR7jblf9giVK1wI9X8hD88w28\n8NN17Lmci+Iy7fm+AHA1pwQTom/g4i3p9IjmDQwR1a8pXG20R5uJajudzdH9/vvv4eHhAWdn53Lr\nH7RsyoPK1ery/3CJiKh8D1ueqiaXrqoP0gtVmP6r9oMW3ujUCINbNaj0cQ0VMvRrYYl+LSxxIasY\n317Ixs//5uF2mfbv76/MYiyMS8Wq0+l47ikrjHjGSjMf+FKBDKv33UB2sfS7tEMjE6z2d0LDB4wc\nE9V2Okt0Dx8+jKSkJBw8eBCpqakwNDSEmZkZSkpKYGRkhNTUVDg4OMDe3h7p6ema/VJTU+Hh4QF7\ne3tkZGTA1dVVM5JrYFCx5iQkJFRLm2oLfW8fwDbqh+pb9L6goKDc96+gsHrOWd75mjZtWi3nehJ3\n+8270tLSYGdnp6m7v6+1t7ev8LH1/fP6JO0rLAOW/mOIpCLpRdRn7VXoLJKRkJD8pOFpPG8J9G0L\nHMlS4EC6Amkl2pN5s4vV+DLxFqISs+BhpUYbC4HvlIYoEdIk171BGWY45yD5Ug6qLkLd0vfPKaDf\nbaxMv6qzRHfVqlWanyMjI9GkSROcOXMG0dHRGDx4MPbt2wdfX1+4ublh/vz5yM/Ph0wmw9mzZzFv\n3jzk5eUhOjoaPj4+iImJQffu3St87vbt21dHk2qFhIQEvW4fwDbqi0MnL1Tbsc3NzdG+nfYqLKcS\nk2rsfDk5OQ/YWnd8fHwQGRmJkSNHIjExEQ4ODjAzuzPn0tnZGQUFBVAqlbC3t8ehQ4ce6yZfff68\nPsnfY3GZGtMOKHG9SDrndWBLSyzydqi2NWi7A5gtBOKUhfj2QjZikwtx/xivgAxnchQ4U85H9bmn\nGmBed/snWrmhtqkP/aq+t7Ey/arOlxe712uvvYa3334b27dvh5OTE4YOHQqFQoHZs2dj4sSJkMvl\nmNJ945kAABa5SURBVDlzJiwsLNC/f3/ExsZi7NixMDY2RkREhK7DJyKq1Tw8PNCuXTuMHj0aCoUC\nYWFh2L17NywtLREYGIiFCxdi1qxZAICBAwfCxcVFxxHXbSq1wNyjKTiTJk1yfZ3NEOZVfUnuXXKZ\nDD2czdHD2Rw38krw3cUcfH8pF3klD5/q94qbDaa42UDGB0GQHqgVie6MGTM0P2/cuFGrPigoCEFB\nQZIyuVyO8PDwao+NiEif3E1k73J1ddX83KVLF2zbtq2mQ9JLQgi8fyINB28USMo72pngg56NYVjD\nI6VNLY0wq7Mdpna0RfS/efj2Qg4u3CqWbCOXASHd7DDiGesajY2oOtWKRJeIiEiffPJ7JnZfypWU\ntbIywmp/J5ga6G7BI1MDOYY+bYXnnmqAc+m38e2FbBxJKoCpTI35Pk7o9ZirPxDVdkx0iYiIqtDW\nv2/hi4RbkjJHcwN80tsJVsa1Y/UCmUwGd3tTuNubQgiBPxMS4cYkl/SQzp+MRkREpC9+/jcXy3/L\nkJRZG8uxtrczHMyrb6WRJyGTyaBH95wRSXBEl4gAANeSs5CWXVjlx7W3NoOLs82jNySq42KTCxAW\nmyopMzWQYU2AM1pYGekoKqL6jYkuEQEA0rILsXjj6So/btjEzkx0Se/9mX4bbx2+CdU9a3gZyIGV\nfo3RvlH5Ty0jourHqQtERERP4EpOCV47mCx5GpkMwGJvR3g5mesuMCJioktERFRZKQWlmH4gWevR\nuXO62uHZFpY6ioqI7mKiS0T/1969R0V533kc/wyDQACR66CiYaPparxg8VrD2qhRbOlurAl4ScCT\nZFezycbWJKZBbT0n2Ri8xFiaaCKFNPXEPRilNRxrizGxJkZXOKIYTEzqpa7Kyk3AcIlyefYPs1QK\nRDQDz8wz79dfnOcZ5vn+zsCXD8/85vcDcAuqrzTrifdLdLG+qc3xfxsZqnlDWYsWcAUEXQAAblJD\nY4t+8kGJztRcbXP8ge8E6YlRzEkHXAVBFwCAm9DYYujZD/9Xn1R81eb41NsDtHS8g61zARdC0AUA\noItaDEPPHyjVxyVtl+IbG3mbXvqnvrKzIC3gUgi6AAB0gWEYeuVwhf5w5ss2x4eE+OqVyf3ka+dP\nKuBq+K0EAKAL3jpepS2fVbc5NiCwl167t796+7jG1r4A2iLoAgBwAztO1uhXRyrbHAvzs2vjtP4K\nv429lwBXxW8nAADfoLDGS+lHy9ocC+zlpQ33Rmlgb7b2BVwZd3QBAOhEYWmDXjvjrZbrtvb18bJp\n/eR+GhLqa15hALqEoAsAQAc+rfxKP91bokbjbyspeNmktEl9Nbavv4mVAegqpi4AAHCdhsYWZXxy\nSW9/WqUmo+255RMcmnp7oDmFAbhpBF0AAL7253O1Wl1Qrot1Te3O/cd3w3T/d/qYUBWAW0XQBQB4\nvJLaRq0pKNe+83Udnk++K1j/OiKkh6sC8G0RdAEAHquxxdCWz6q0qeiSvmo22p2P9PfWnMgGPTwm\nnK19ATdE0AUAeKQjZQ166VCZTlZfbXfObpMevCtY/x4TptOff0rIBdwUQRcA4FGqvmpWemGF3j11\nucPzMRF+Wj7BoX8MYfkwwN0RdAEAHqHFMPTuyctKL6xQzdWWdueDfLz009Hh+vGdQfLiDi5gCQRd\nAIDl/aXqil46VKaj5V91eP6+wb3109HhCvXjzyJgJfxGAwAsq6GxRZuOXdKWz9qviStJg/r4aNkE\nh8ZE3tbzxQHodgRdAIAl7T1XqzX55bpY335NXD+7TQtiQpVyV4h62ZmmAFgVQRcAYCkltY1aXVCu\nDztZE/f7UQF6bnyE+gf26uHKAPQ0gi4AwBIaWwy9/WmVMo51vCZuX39v/WxchCYPDGC5MMBDEHSB\nLjh74ZLKquud/ryOYH9FR4U6/XkBT1NYem1N3FM1Ha+J+9BdwXosJkz+vbxMqA6AWQi6QBeUVdfr\nhTcPO/15Vzw6hqALfAs3WhN3VISflrEmLuCxCLoAALfTYhjacfKyftXJmrh9vl4TdyZr4gIejaAL\nAHArf6m6opWHylTUyZq4MwcH6Sejw1gTFwBBFwDgHuobW7TpWKW2fFatDj5rpsFfr4k7mjVxAXyN\noAsAcGmNLYZyT17WpmOVKm9obnfez27TwphQJbMmLoC/Q9AFALikFsPQe2drtfFopf7ny8YOH/P9\nAQF6bhxr4gLoGEEXAOBSDMPQgZJ6vXa0UicuXenwMX39vfWz8RGaMjCwh6sD4E4IugAAl1FU3qBX\nj1TqcGlDh+d97TbNGxqsBSNDWRMXwA2ZGnTXrFmjwsJCNTc3a+HChRo5cqSeffZZGYahiIgIrVmz\nRr169VJubq42b94su92upKQkJSYmqqmpSampqSopKZHdbldaWpoGDBhg5nAAwKV1pW8OHz5cY8aM\nkWEYstls+u1vf9sju4idrLqi145Wal8n2/babddWU1gYE6rIAKYpAOga04LuoUOHdOrUKWVnZ6u6\nulqzZs3S9773PSUnJ2vGjBlav369cnJyNHPmTG3cuFE5OTny9vZWYmKi4uPj9cEHH6hPnz56+eWX\n9fHHH2vdunVav369WcMBAJe3c+fOG/bNoKAgbd68ucdquvBlo14/Vqldp79UBwspSJLiowP1xHfD\nFB3k02N1AbAG0973GT9+vNLT0yVda6z19fUqKCjQ1KlTJUlTpkzRgQMHVFRUpJiYGAUEBMjX11ej\nR4/W4cOHdfDgQU2bNk2SdPfdd6uwsNCsoQCAW+hK3zSMzuKmc1U2NGlVfpl+nPtX/aGTkHt3f3/9\nV8JArf5+P0IugFti2h1dm80mPz8/SdL27ds1efJk7d+/X716XXtLKiwsTGVlZaqsrFRo6N+2SA0N\nDVV5ebkqKipaj9tsNnl5eampqUne3kw7BoCOdKVvXrlyRUuWLFFJSYni4+P18MMPO7WGL682a/Px\nKm05Ua2Gpo5D9chwP/0kNkxj+/o79doAPI/pqXDPnj3KyclRVlaW4uPjW493dlehs+MtLe23gOxM\ncXHxzRXpZqw+Pqnnx1hX3z1zAuvq6jodi/XH2H3zLDu7Zk+OceDAgd1yra7atm2btm/f3jq/1jAM\nHTt2rM1jOuqbqampuu+++yRJDz30kMaNG6fhw4ff8Ho3+nm92iK9V27XzlK7aps7nvMb5deipH7N\nGt3nimwVNSquuOFlewx91RoYo3u7lb5qatD96KOPlJGRoaysLAUGBiogIEBXr16Vj4+PSktLFRkZ\nKYfDofLy8tbvKS0tVWxsrBwOhyoqKjRkyBA1NTVJUpfv5o4YMaJbxuMKiouLLT0+yZwxFhw/3y3P\nGxAQoBHD23+I0hPG+Of8z7vlet90zZ4cY01NTbdcq6uSkpKUlJTU5tjSpUtv2DfnzJnT+vXEiRP1\nxRdfdCnodvbz2tRiKPfUZW06dkll9U0dPqZfgLceHxWmhDt6y+7lehs+0FetgTG6v1vpq6bN0a2t\nrdXatWv1xhtvqHfv3pKuNdW8vDxJUl5eniZNmqSYmBgVFxertrZWdXV1OnLkiMaMGaO4uDj96U9/\nkiR98MEHmjBhgllDAQC3cKO+eebMGT3zzDOSrq3QUFhYqDvvvPOWrtViGNr91y/1QO5Z/ed/l3UY\nckN87frZuAjtmBmtfxkc5JIhF4B7M+2O7q5du1RdXa3Fixe3LmOzevVqLV++XFu3blX//v01a9Ys\n2e12PfPMM3r00Ufl5eWlRYsWKTAwUAkJCfr444/14IMPytfXV6tWrTJrKADgFjrrmxkZGZowYYJG\njRqlfv36KTExUXa7Xffee69Gjhx5U9foymYPgb28NH9YiB66K5i1cAF0K9OC7uzZszV79ux2x998\n8812x+Lj49vM35UkLy8vpaWldVt9AGA1nfXNhQsXtn69ZMmSW37+G2324ONl09yhffTIiFAF+9pv\n+ToA0FWmfxgNAOD+Fu8tYbMHAC6HoAu4oEb5ddsHpxzB/oqOCr3xA4Gb0FnInR4dqCdGhekf+rAO\nLoCeR9AFXFBNfbPWbT3cLc+94tExBF10u4n9/PVkbJiGhfmZXQoAD0bQBQA4zchwPy2KDdM4NnsA\n4AIIugCAb21QHx89+d0wTR4Y0LpJBQCYjaALAPjW3vnn21kHF4DLYQFDAMC3RsgF4IoIugAAALAk\ngi4AAAAsiaALAAAASyLoAgAAwJIIugAAALAkgi4AAAAsiaALAAAASyLoAgAAwJIIugAAALAkgi4A\nAAAsiaALAAAASyLoAgAAwJIIugAAALAkgi4AAAAsiaALAAAASyLoAgAAwJIIugAAALAkgi4AAAAs\niaALAAAASyLoAgAAwJIIugAAALAkgi4AAAAsiaALAAAASyLoAgAAwJIIugAAALAkgi4AAAAsydvs\nAsxQcPy805/TEeyv6KhQpz8v2muUX7e8hhKvIwAAVuKRQfeFNw87/TlXPDrGYwPS2QuXVFZd3y3P\n3VHwrKlv1rqtzn8NJc9+HQEAsBqPDLpwrrLq+m7550EieAIAgFtH0O1mPX23k7f1AQAArnH7oJuW\nlqaioiLZbDYtW7ZMI0eONLukNnr6bidv6wP4Jvn5+Vq8eLHS0tJ0zz33tDufm5urzZs3y263Kykp\nSYmJiSZUCQDO4dZBt6CgQGfPnlV2drZOnTql5cuXKzs72+yyAMAlnTt3Tm+99ZbGjBnT4fmGhgZt\n3LhROTk58vb2VmJiouLj4xUUFNTDlQKAc7j18mIHDx7UtGnTJEmDBw/W5cuXVVdXZ3JVAOCaHA6H\nNmzYoMDAwA7PFxUVKSYmRgEBAfL19dXo0aNVWFjYw1UCgPO4ddCtqKhQaOjf3koPCQlRRUWFiRUB\ngOvy9fWVzWbr9Pzf99TQ0FCVl5f3RGkA0C1shmEYZhdxq1asWKHJkydr6tSpkqQHH3xQaWlpio6O\nbvfYmpqani4PACRJffr06fFrbtu2Tdu3b5fNZpNhGLLZbFq0aJHi4uK0dOlS/eAHP2g3R3fnzp0q\nLi5WamqqJOmXv/yloqKilJSU1OE16KsAzNLVvurWc3QdDkebO7hlZWWKiIgwsSIAcA1JSUmdBtTO\nOByONndwS0tLFRsb6+zSAKDHuPXUhbi4OOXl5UmSjh8/rsjISPn7+5tcFQC4vo7ezBs1apSKi4tV\nW1ururo6HTlypNMPrgGAO3DrqQuS9Morryg/P192u10rVqzQkCFDzC4JAFzSvn37lJmZqTNnzig0\nNFQRERHKyspSRkaGJkyYoFGjRmn37t3KzMyUl5eXUlJS9KMf/cjssgHglrl90AUAAAA64tZTFwAA\nAIDOEHQBAABgSQRdAAAAWJLHBN20tDTNnTtX8+bN0yeffGJ2Od1izZo1mjt3rpKSkvTee++ZXU63\nuXLliqZPn64dO3aYXUq3yM3N1cyZM/XAAw9o3759ZpfjdPX19Vq0aJHmz5+vefPmaf/+/WaX5DRf\nfPGFpk+fri1btkiSLl68qJSUFCUnJ+upp55SY2OjyRU6F33VGqzeUyVr91Ur91Tp2/dVjwi6BQUF\nOnv2rLKzs/Xiiy9q5cqVZpfkdIcOHdKpU6eUnZ2tX//613rppZfMLqnbbNy4UcHBwWaX0S2qq6u1\nYcMGZWdna9OmTXr//ffNLsnpfv/732vQoEHavHmz0tPTLfP72NDQoBdffFETJ05sPZaenq6UlBS9\n/fbbuv3225WTk2Nihc5FX7UOK/dUyfp91ao9VXJOX/WIoHvw4EFNmzZNkjR48GBdvnxZdXV1Jlfl\nXOPHj1d6erokKSgoSA0NDR2uk+nuTp8+rdOnT7fb0ckqDhw4oLi4ON12220KDw/XCy+8YHZJThcS\nEqKqqipJ13bWun7LWXfm6+urzMxMORyO1mP5+fmaMmWKJGnKlCk6cOCAWeU5HX3VGqzeUyXr91Wr\n9lTJOX3VI4Lu3+/fHhIS0mZHNSuw2Wzy8/OTdG3rz3vuuecb97R3V6tXr27dntSKLly4oIaGBj3+\n+ONKTk7WwYMHzS7J6RISElRSUqL4+HilpKToueeeM7skp/Dy8pKPj0+bYw0NDerVq5ckKSwsrM2u\nY+6OvmoNVu+pkvX7qlV7quScvurWWwDfKqv9R369PXv26He/+52ysrLMLsXpduzYodjYWEVFRUmy\n5utoGIaqq6u1ceNGnT9/XvPnz9fevXvNLsupcnNz1b9/f2VmZurEiRNavny5pd7S74wVf16vZ+Xx\nWbWvekJPlazfVz21p0pd+5n1iKDrcDja3GkoKytTRESEiRV1j48++kgZGRnKyspSYGCg2eU43b59\n+3T+/Hnt3btXFy9elK+vr/r27dtm7o67Cw8PV2xsrGw2mwYOHKiAgABdunTJUm9FFRYWatKkSZKk\noUOHqqysTIZhWO5OmSQFBATo6tWr8vHxUWlpaZu339wdfdX9eUJPlazfVz2pp0o331c9YupCXFyc\n8vLyJEnHjx9XZGSk/P39Ta7KuWpra7V27Vq98cYb6t27t9nldIv169dr27Zt2rp1q5KSkvTEE09Y\nriHHxcXp0KFDMgxDVVVVqq+vt0wz/n/R0dE6evSopGtvKQYEBFi2IU+cOLG19+Tl5bX+MbIC+qr7\n84SeKlm/r3pST5Vuvq96xB3d2NhYDR8+XHPnzpXdbteKFSvMLsnpdu3aperqai1evLj1P7k1a9ao\nb9++ZpeGmxAZGakZM2Zo9uzZstlslvxZnTNnjpYtW6aUlBQ1Nzdb5oMhx48f16pVq1RSUiJvb2/l\n5eXp5ZdfVmpqqrZu3ar+/ftr1qxZZpfpNPRVuAur91Wr9lTJOX3VZlh1Ug4AAAA8mkdMXQAAAIDn\nIegCAADAkgi6AAAAsCSCLgAAACyJoAsAAABLIugCAADAkgi68EhDhw7Vz3/+8zbH8vPzlZKS0vr1\niBEjlJCQoB/+8IeaMWOGHnvsMZ07d6718Tt37tT999+vhIQExcfH68knn1RZWVmPjgMAXAV9Fa6I\noAuPVVBQoBMnTrQ5dv1uMlFRUdq1a5f++Mc/Ki8vT2PHjtWSJUskSSdPnlRaWpo2bNigXbt2KS8v\nTwMGDNDy5ct7dAwA4Eroq3A1BF14rKefflorV67s8uOTk5NVVFSk2tpanTx5UuHh4erXr5+ka438\n6aef1rp167qrXABwefRVuBqCLjySzWbTjBkzJEm7d+/u0vc0NTXJbrfLx8dHo0ePVklJiR5//HHt\n2bNHNTU18vHxUVBQUHeWDQAui74KV0TQhUdbunSp1q5dq6tXr37j41paWpSZmalJkybJx8dHDodD\n27dvl8Ph0MqVKzVx4kQ98sgj+vzzz3uocgBwTfRVuBJvswsAzDRs2DCNGzdOv/nNbxQbG9vm3IUL\nF5SQkCDDMGSz2RQTE6NVq1a1no+Ojtbzzz8vSTp9+rQyMjK0YMECffjhhz06BgBwJfRVuBKCLjze\nU089pfvvv18DBgxoc/z/PzTRkc8++0x+fn664447JEmDBg3SL37xC40dO1bV1dUKDg7u9roBwFXR\nV+EqmLoAj2QYRuvXERERSk5O1quvvtrl79+/f79SU1NVWVnZeuzdd9/VnXfeSTMG4JHoq3BF3NGF\nR7p+uRtJeuSRR/TOO++0O96ZBQsWyDAMzZ8/Xy0tLWpqatKwYcP0+uuvd0e5AODy6KtwRTbj+n/B\nAAAAAItg6gIAAAAsiaALAAAASyLoAgAAwJIIugAAALAkgi4AAAAsiaALAAAASyLoAgAAwJIIugAA\nALAkgi4AAAAs6f8ApTPzY4owzKMAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f0440d73fd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"weighted_sentiment(dfNPS, 'sentiment')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can see from this that there is a generatl trend in imporving sentiment as NPS scores increase, which is what you would expect."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Try it with NLTK\n",
"http://www.slideshare.net/waitingkuo0527/sentiment-analysisbynltk\n",
"\n",
"Some of the comments have punctuation in them. The afinn package splits words on spaces so words with adjacent punctuation may include the punctiation when split and not be recognised in the AFINN data set.\n",
"\n",
"To manage this, we can use NLTK to tokenise the words."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Load the AFINN data set"
]
},
{
"cell_type": "code",
"execution_count": 211,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sentiment_dicitonary = {}\n",
"\n",
"for line in open(afinn.full_filename('AFINN-en-165.txt' )):\n",
" word, score = line.split('\\t')\n",
" sentiment_dicitonary[word] = int(score)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For each comment in the NPS comments, tokenise the comment using NLTK, look up the sentiment for each word from AFINN and sum up the total sentiment for each comment"
]
},
{
"cell_type": "code",
"execution_count": 212,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from nltk.tokenize import word_tokenize\n",
"\n",
"def sent_tok(comment):\n",
" words = word_tokenize(comment)\n",
" sentiment = sum(sentiment_dicitonary.get(word, 0) for word in words)\n",
" return sentiment\n",
"\n",
"dfNPS.loc[:,'sentiment_tok'] = dfNPS.loc[:,'Comment'].apply(lambda x: sent_tok(x))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can see from the table below that there are differences in the sentiment scores."
]
},
{
"cell_type": "code",
"execution_count": 213,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>NPS</th>\n",
" <th>Comment</th>\n",
" <th>Repurchase</th>\n",
" <th>sentiment</th>\n",
" <th>sentiment_tok</th>\n",
" <th>sentiment_toksent</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>10</td>\n",
" <td>Very good price, great online account features</td>\n",
" <td>Highly Likely</td>\n",
" <td>6.0</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>10</td>\n",
" <td></td>\n",
" <td>Highly Likely</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>10</td>\n",
" <td>helpful service</td>\n",
" <td>Highly Likely</td>\n",
" <td>2.0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1</td>\n",
" <td>The charges are cheaper</td>\n",
" <td>Highly Likely</td>\n",
" <td>-2.0</td>\n",
" <td>-2</td>\n",
" <td>-2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>10</td>\n",
" <td>Im happy with the service so far</td>\n",
" <td>Highly Likely</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" NPS Comment Repurchase \\\n",
"20 10 Very good price, great online account features Highly Likely \n",
"21 10 Highly Likely \n",
"22 10 helpful service Highly Likely \n",
"23 1 The charges are cheaper Highly Likely \n",
"24 10 Im happy with the service so far Highly Likely \n",
"\n",
" sentiment sentiment_tok sentiment_toksent \n",
"20 6.0 6 6 \n",
"21 0.0 0 0 \n",
"22 2.0 2 2 \n",
"23 -2.0 -2 -2 \n",
"24 3.0 3 3 "
]
},
"execution_count": 213,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dfNPS.iloc[20:25,1:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Looking at the violin plots and weighted sentiments, we can see that the sentiments are similar to before, albiet a little less extreme"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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Yhg4AaCto0+zyLYR/+eWXGjx4sJ566ilJ0o033qgzzzxTF1xwgS644AK99dZb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\nCYtZB7pC+IHx8+jffPNN346NL7zwgrYXF+t7mfU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6oxrXKabBDQqnOfBZJar2Wm14onZG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vAal2uhMNesSYfzRBDRCDeZTKF2+62trWzdujUu6R8HDx7ki18M1KSUlJTgdrvp6OiIqtnTzp07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\nOAAAAAAAjhDCAQAAAABw5P8BTq18I0Q3P+cAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f045e4cbcc0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"violin_sentiment(dfNPS, 'sentiment_tok')"
]
},
{
"cell_type": "code",
"execution_count": 201,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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WC3Nzc71thvqfqva/CoUCMpkMZ86cMVi+e/fuCv3zve4EAcCCBQswZcoU/Pe//8X+/fvx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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f0440d0a470>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"weighted_sentiment(dfNPS, 'sentiment_tok')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can also try splitting the comments into individual sentences, if comments have more than one sentence, and average the sentiment of each sentence"
]
},
{
"cell_type": "code",
"execution_count": 205,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from nltk.tokenize import sent_tokenize\n",
"\n",
"def sent_senttok(comment):\n",
" sentences = sent_tokenize(comment)\n",
" sentiment = 0\n",
" for sentence in sentences:\n",
" words = word_tokenize(sentence)\n",
" sentiment += sum(sentiment_dicitonary.get(word, 0) for word in words)\n",
" return sentiment/len(sentences)\n",
"\n",
"dfNPS.loc[:,'sentiment_toksent'] = dfNPS.loc[:,'Comment'].apply(lambda x: sent_tok(x))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These results look similar to those of just tokenising each word"
]
},
{
"cell_type": "code",
"execution_count": 214,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>NPS</th>\n",
" <th>Comment</th>\n",
" <th>Repurchase</th>\n",
" <th>sentiment</th>\n",
" <th>sentiment_tok</th>\n",
" <th>sentiment_toksent</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>10</td>\n",
" <td>Very good price, great online account features</td>\n",
" <td>Highly Likely</td>\n",
" <td>6.0</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>10</td>\n",
" <td></td>\n",
" <td>Highly Likely</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>10</td>\n",
" <td>helpful service</td>\n",
" <td>Highly Likely</td>\n",
" <td>2.0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>1</td>\n",
" <td>The charges are cheaper</td>\n",
" <td>Highly Likely</td>\n",
" <td>-2.0</td>\n",
" <td>-2</td>\n",
" <td>-2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>10</td>\n",
" <td>Im happy with the service so far</td>\n",
" <td>Highly Likely</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" NPS Comment Repurchase \\\n",
"20 10 Very good price, great online account features Highly Likely \n",
"21 10 Highly Likely \n",
"22 10 helpful service Highly Likely \n",
"23 1 The charges are cheaper Highly Likely \n",
"24 10 Im happy with the service so far Highly Likely \n",
"\n",
" sentiment sentiment_tok sentiment_toksent \n",
"20 6.0 6 6 \n",
"21 0.0 0 0 \n",
"22 2.0 2 2 \n",
"23 -2.0 -2 -2 \n",
"24 3.0 3 3 "
]
},
"execution_count": 214,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dfNPS.iloc[20:25, 1:]"
]
},
{
"cell_type": "code",
"execution_count": 215,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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5ubn+/9+9e7dbIQMAoiA/P19bt25Vo0aN1KRJE6/DiZn09HT//9erV8/DSGyp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kEF00BRVEj9r1Up4QXAqNQwZhWg5+zJkf0dHR2SysvtImJMTAuu/1MKgUuXRsZcLldU8ly8eJHY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\naAaG9BwY0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lUIw8PDsWLFiq6HjWtPUk9trajQHZY+d+5c3HzzzT1qyczOzsa9996LAwcO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\nAIKMYRwAAAAAgCBjGAcAAAAAIMj+Brmb7iUXgzxRAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f045e4e2c50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"violin_sentiment(dfNPS, 'sentiment_toksent')"
]
},
{
"cell_type": "code",
"execution_count": 216,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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WC3Nzc71thvqfqva/CoUCMpkMZ86cMVi+e/fuCv3zve4EAcCCBQswZcoU/Pe//8X+/fvx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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f045e4f1080>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"weighted_sentiment(dfNPS, 'sentiment_toksent')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The similarity between the sentiments for word and sentence tokenisation can be explained by the below.\n",
"\n",
"The distribution of the numbers of sentences per comments clearly shows that most comments are either zero length or have one sentence. \n",
"\n",
"In fact, of the 36,695 comments, 31,392 or 86% of the comments have zero or one sentence."
]
},
{
"cell_type": "code",
"execution_count": 119,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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fv77K8S5cuABbW1sYGxsDABwcHJCYmIgzZ85g6NChAAAXFxeEhYWhuLgYKSkp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\nBIiIZIwhQEQkYwwBIiIZYwgQEcnY/wO/CCF75+0bcwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f0448e58518>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_ = dfNPS['Comment'].apply(lambda x: len(sent_tokenize(x)))\n",
"df_ = pd.DataFrame(df_)['Comment'].value_counts().sort_index()\n",
"fig, ax = plt.subplots(figsize=(5, 5), facecolor='white')\n",
"ax.bar(df_.index, df_.values)\n",
"ax.set_title('Distribution of comments by number of sentences')\n",
"ax.set_xlabel('Sentence length')\n",
"ax.set_ylabel('Comment count')\n",
"ax.set_axis_bgcolor('white')\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Naive bayes classification "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The Movie review data set contains several thousand movie reivews tagged as negative or positive reviews.\n",
"http://www.cs.cornell.edu/people/pabo/movie-review-data/\n",
"\n",
"We can try to use these reviews to train a naive bayes comment classifier"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"First we read in the movie review data and split it into negative and positive groups"
]
},
{
"cell_type": "code",
"execution_count": 124,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from nltk.corpus import PlaintextCorpusReader\n",
"polarity_dir = '/mnt/hgfs/UNISA/INFS-5101 Social Media Data Analytics/txt_sentoken/'\n",
"\n",
"pos_sent = PlaintextCorpusReader(polarity_dir + 'pos', '.*').raw().split('\\n')\n",
"neg_sent = PlaintextCorpusReader(polarity_dir + 'neg', '.*').raw().split('\\n')"
]
},
{
"cell_type": "code",
"execution_count": 151,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"There are 32938 positive, and 31784 negative sentences\n"
]
}
],
"source": [
"print(\"There are {0} positive, and {1} negative sentences\".format(len(pos_sent), len(neg_sent)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The positve and negative rated comments are made up of sentences. In order to use them to train a naive base classifier, we need to:\n",
"* split the sentences into words\n",
"* combine them into a training set, and tag them as positive or negative'; and\n",
"\n",
"The NLTK naive bayes classifier then takes in a list of all the comments with each comment broken into words and tagged as pos or neg. The Classifier can then calculate a porbaibility distribution of each word being positive or negative."
]
},
{
"cell_type": "code",
"execution_count": 152,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def format_sentence(sentence):\n",
" return {word: True for word in word_tokenize(sentence)}"
]
},
{
"cell_type": "code",
"execution_count": 153,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"pos_data = []\n",
"for line in pos_sent:\n",
" pos_data.append([format_sentence(line), 'pos'])\n",
" \n",
"neg_data = []\n",
"for line in neg_sent:\n",
" neg_data.append([format_sentence(line), 'neg'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Combine the negative and positive data into a training set and test set, train the Naive bayes classifier and test its accuracy"
]
},
{
"cell_type": "code",
"execution_count": 169,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"train_data = pos_data[:25000] + neg_data[:25000]\n",
"test_data = pos_data[25000:] + neg_data[25000:]"
]
},
{
"cell_type": "code",
"execution_count": 170,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from nltk.classify import NaiveBayesClassifier\n",
"from nltk.classify.util import accuracy"
]
},
{
"cell_type": "code",
"execution_count": 171,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"model = NaiveBayesClassifier.train(train_data)"
]
},
{
"cell_type": "code",
"execution_count": 176,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The accuracy of the model is 65.41%\n"
]
}
],
"source": [
"print(\"The accuracy of the model is {0:4.2f}%\".format(accuracy(model, test_data)*100))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can now apply the naive bayes classifier to each comment in the NPS data frame and predict is as positive or negative"
]
},
{
"cell_type": "code",
"execution_count": 177,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"0 pos\n",
"1 pos\n",
"2 pos\n",
"3 neg\n",
"4 neg\n",
"Name: sent_NB, dtype: object"
]
},
"execution_count": 177,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dfNPS['sent_NB'] = dfNPS['Comment'].apply(lambda x: model.classify(format_sentence(x)))\n",
"dfNPS['sent_NB'].head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To see how sentiment shifts with NPS, we can compare the ratio between negative and positive classifications of comments across all NPS scores"
]
},
{
"cell_type": "code",
"execution_count": 178,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th>sent_NB</th>\n",
" <th>neg</th>\n",
" <th>pos</th>\n",
" </tr>\n",
" <tr>\n",
" <th>NPS</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>118</td>\n",
" <td>282</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>73</td>\n",
" <td>164</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>80</td>\n",
" <td>172</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>115</td>\n",
" <td>227</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>126</td>\n",
" <td>273</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>741</td>\n",
" <td>1847</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>413</td>\n",
" <td>1354</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>805</td>\n",
" <td>2894</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>1647</td>\n",
" <td>6071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>1681</td>\n",
" <td>6418</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>2364</td>\n",
" <td>8830</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"sent_NB neg pos\n",
"NPS \n",
"0 118 282\n",
"1 73 164\n",
"2 80 172\n",
"3 115 227\n",
"4 126 273\n",
"5 741 1847\n",
"6 413 1354\n",
"7 805 2894\n",
"8 1647 6071\n",
"9 1681 6418\n",
"10 2364 8830"
]
},
"execution_count": 178,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_ = pd.crosstab(dfNPS['NPS'], dfNPS['sent_NB'])\n",
"df_"
]
},
{
"cell_type": "code",
"execution_count": 164,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x7f04438e9668>"
]
},
"execution_count": 164,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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88Hg8bNq0CU5OTmW+KUJIXgWhROQr64mmdmYY3MSm0mIiFUdvMg8ICMCpU6cg\nFosBAA4ODggMDMSwYcNKnMwvXLiAVq1aYcqUKYiOjsakSZM4yZzH48Hf3197DULIm7scnYnrsQrO\ntnntHSHg0wQhU6Q3mefk5MDSkjupQCgUQqlU6jiisP79+2v/HR0djdq1a3P2M8bAGCt4GCGkjFQa\nhm03uROEOjlboGsdmiBkqvQmcx8fH4wbNw6+vr6wsbFBcnIyfv755zKNMx89ejTi4+Oxa9euQvtW\nrlyJqKgoSKVSLFiwoNTnJoS8dupJKp6mvB5SzAMwv0NNqutpwvQm8yVLluDUqVO4ePEi5HI57Ozs\nMGXKFE5ru6SOHTuG+/fv4+OPP8apU6e02+fOnYsePXrAzs4OM2fOxLlz59CnT59Sn58QAmTmaLDz\nnyTOtoGNreEmoQlCpozHDNC/ERERAQcHBzg7OwMABgwYgO+//x4SSeGqJkeOHIFMJsPs2bOLPFdK\nyusF9R89elQxARNShZ1KMMfpxNfPn0Q8hrVN0iARUVdmVdCsWTPtv21tbUt8nEFmDdy4cQPR0dFY\nunQpEhMToVAotIk8PT0dc+fOxa5duyASiXDjxo0Sj2GXSqUVGbZRCg0NpfuuZkpz7/GZKvwe9BzI\nN4ZlvIcEfdq5VkxwFaw6ft/zN1hLwyDJfMyYMVi6dCnGjh0LpVKJFStWIDAwENbW1vDx8UHPnj0x\natQoiMVitGjRAr6+voYIixCTsyssCVn5JgjZmwsw0YMmCFUHBknm5ubm2Lx5s87948aNw7hx4wwR\nCiEm63GyEiefpHK2zWgjgZUZ1e6tDkq00Nbhw4cxYcIEjBkzBgAQFBSEpKQkPUcSQgxp261E5Cvr\niYY2IrzTrOR9rqRq05vMv/jiC4SEhGDcuHGQyXKX0FQqlfj0008rPDhCSMlcjcnEX9GZnG1z2jtC\nRBOEqg29yfz8+fPYuXMnfHx8wOfnvnzUqFF4+fJlhQdHCNFPrWHYepNb17O9kwV61q2h4whiivQm\nczMzMygUuVOC8yYcZGVl0YxNQozEmWdpeJjMrTmwoIMjTRCqZvQ+AB04cCBGjx6N4cOHIz09HYcP\nH8apU6cwZMgQQ8RHCCmGQlV4glDfhlbwcKR1jqobvcl89uzZqFu3LoKDg9GsWTOEh4dj2rRp8PHx\nMUR8hJBiHLknR1zm68pfIj4PH7ajup7Vkd5kvmXLFvTr1w9Dhw41RDyEkBKSKVQ4EJHM2TbG3RZ1\nrESVFBHRkUyPAAAgAElEQVSpTHqTeVZWFmbNmgWRSIR+/fqhX79+cHNzM0RshJBi7P5XhowcjfZr\nGzM+prQsvEQGqR70PgBdunQpLly4gC1btoDP52PhwoXo378/duzYYYj4CCFFeJ6SjROPuNO+328t\ngY05TRCqrkpcO8rDwwMzZszARx99hEaNGmH37t0VGRchpBhf3UpEvln7qGslwkhXu8oLiFQ6vd0s\nycnJCA4Oxh9//IHr16+jVatW8PX1xZo1awwRHyGkgJtxCgRHZXC2zWnvAJGAhiJWZ3qTec+ePdG5\nc2f06dMH69atK9WSjISQ8qVhhScItXIUw6e+VSVFRIyF3mR++fJlWFtbGyIWQoge556nIyKJW7KR\nJggRoJhkPmjQIJw+fRqdO3cu9EFhjIHH4yE8PLzCAySE5MpWa7DjNreuZ6/6NdDWyaKSIiLGRGcy\n9/f3BwCcO3euyP0ajabI7YSQinHsQQqiM15PEBLygDk0QYj8R2cyr1WrFgBg8eLFOHToUKH9PXr0\nQEhISMVFRgjRSlGq4X9Hxtn2rqstGtiYVVJExNjoTOZBQUE4efIkIiIiMHnyZM6+9PR07QqKhJCK\nt/eODGnZr/8athLx8X5rh0qMiBgbncm8f//+aNiwIWbPno1BgwZxDxIK0aFDhwoPjhACxGfzcfyZ\nnLNtckt72ItpghB5TWcyNzMzQ9u2bXHy5Ek4OBRuAWzYsAGLFy+u0OAIIUBgvDlU+R5ROdcQYow7\nTRAiXHqHJmZnZ2P58uWIjIzUPvTMzMxEbGwsJXNCKlhYggKhadx+8dltHSAWUjcn4dL7iVi0aBHU\najUGDx6MZ8+eYdCgQbCxscHOnTsNER8h1RZjDFtvcociNpeYo18jmvdBCtObzOPj4/H5559j2LBh\nsLKywogRI7B582Z89dVXhoiPkGrrQmQGwhKyONvmd3AEnyYIkSLoTeYCgQDx8fG5L+bzkZKSAnt7\ne0RFRVV4cIRUVzkahu23uK1yT5caeMvZspIiIsZOb5/5pEmT0Lt3b9y8eRPe3t4YO3YsXFxcaI0W\nQirQiYcpeJmWo/2az8tdTIsQXfQm8xEjRuDtt9+GUCjEggUL4O7ujqSkJAwcONAQ8RFS7aRlq7H7\nX+4EoXea2qCJnXklRUSqAr3J/MaNGwCAJ0+eAMidGVqrVi08e/YMiYmJaNSoEczMaBYaIeXl24hk\nyJVq7dfmPIYZbahVToqnN5mvWbMGL168gEajgYODA2QyGfh8PmrVqoXU1FQAwMaNG9G9e/cKD5YQ\nUxeXkYND97gThPo4KOFoofdHlVRzej8hffr0gbW1NcaOHQuhUAi1Wo1jx44hKysLU6ZMwd9//43P\nP/+ckjkh5WBnWBKU+UoIOVoI0MdBWcwRhOTSO5rl9OnTmDBhAoTC3LwvEAgwduxYBAUFAQC6dOmC\n7Ozsio2SkGrggUyJ00/SONtmtHaAmOYHkRIo0cfk+PHjSE9PBwAolUoEBQVpE/jevXthZ0dTiwl5\nU9tvJyJfWU80sjXDkKY2lRYPqVr0drNs2bIFK1aswMqVK8Hn88EYQ5MmTbB27VoAQHh4OL744osK\nD5QQU3Y1OgNXojM52+a1d4CQTxOESMnoTeYeHh44ceIElEolUlJSYGVlBUvL1xMXaCYoIW9GrWHY\nWmCCkLSWBXq41KikiEhVpLebhTGGw4cPY/r06Zg7dy4sLS0RFBSEpKQkQ8RHiMk7+ywND5O5z53m\nUV1PUkp6k/kXX3yBkJAQ+Pn5QSbLncigVCrx6aefVnhwhJi6LJUGO//hNoz6NrSCh4O4kiIiVZXe\nZH7+/Hns3LkTPj4+2upCo0aNwsuXLys8OEJM3ZH7csRmvq7rKeLzMLst1fUkpac3mZuZmUGhUACA\n9s++rKwsMMaKO4wQoocsS4UD4cmcbaPcbOFiLaqkiEhVpvcB6MCBAzF69GgMHz4c6enpOHz4ME6d\nOoUhQ4YYIj5CTJb/nWSk57wuIWRtxsfUVpJKjIhUZXqT+ezZs1G3bl0EBwejWbNmCA8Px7Rp0+Dj\n42OI+AgxSS9TsxHwgDttf2orCWzNqa4nKZsSLfgwdOhQDB06tMwXycrKwieffIKkpCRkZ2fjgw8+\nQM+ePbX7r1y5gq1bt0IgEMDT0xMzZ84s87UIqQp23E6CKl9PZZ0aQox2o2WlSdnpTea//PILtm3b\nhpiYGG0NUMYYeDwewsPDS3SRCxcuoFWrVpgyZQqio6MxadIkTjJft24d9u/fDycnJ/j5+cHX1xdN\nmjQp2x0RYuT+TVDg/Mt0zrbZ7RxgJqB5+6Ts9Cbz9evXY8mSJfDw8NCOZimt/v37a/8dHR2N2rVr\na7+OjIyEnZ0datWqBQDw8vLC1atXKZkTk6SrrqdvQ6rrSd6M3mRuY2ODvn37lsvFRo8ejfj4eOza\ntUu7LTExERLJ64c+EokEkZGR5XI9QozNn5EZ+IfqepIKoDeZjxw5EkeOHMGwYcMgFr/ZRIZjx47h\n/v37+Pjjj3Hq1KkiX1OaIY+hoaFvFE9VRfddNakYsOGpFYDXDzlbWeWAF3UXoXpK6lb1e38T1e3e\nmzVrVqbj9Cbz3bt3Qy6XY82aNRAIcj+Epe0zj4iIgIODA5ydneHu7g61Wg2ZTAaJRAInJyckJCRo\nXxsXFwcnJ6cSnVcqlZbodaYkNDSU7ruK+uGBHPHZrz/rfB6w0ruJ3nJwpnDvZVUd7z0lJaVMx+lN\n5sePHy/TifO7ceMGoqOjsXTpUiQmJkKhUGi7VlxcXJCRkYHo6Gg4OTkhODgYmzdvfuNrEmJM0rPV\n2BXGres5tAnV9STlR28yd3FxeeOLjBkzBkuXLsXYsWOhVCqxYsUKBAYGwtraGj4+Pli5ciUWLFgA\nIHeSUoMGDd74moQYk28jkpGcr66nWMCjup6kXBmksKC5uXmxrW2pVIpjx44ZIhRCDC4+U1Worud4\nD3vUtKS6nqT80MBWQirYzn+SkJWvrqeDWIAJLewrMSJiikqczDUaDZKSkrQThwgh+j1KVuLUk1TO\nthltHGAponYUKV96P1GRkZGYNGkSWrZsie7du6N169aYPn064uLiDBEfIVXatlsF6nraiDCU6nqS\nCqA3mS9fvhyenp64fv067t27h7/++gvt27fH8uXLDREfIVXW1ZjMQnU957R3pLqepELoTebx8fGY\nNGkSrKysAAC2traYPn06oqL0zHIgpBrTMIavCtT1bO9kAa+6VNeTVAy9yVwgEBSaXh8VFaWdQEQI\nKezsszTclyk52+ZTXU9SgfSOjZo5cyaGDRuGzp07w8bGBsnJybh58ybWrFljiPgIqXKUag2+uc2t\n69mngRVaOlJdT1Jx9Cbzfv36oU2bNrhy5QpkMhk6dOiAlStXalc5JIRwHS1Q11PIBz5sR3U9ScXS\nm8w/+ugjbN68Ge+++y5n+4gRIxAQEFBhgRFSFcmVauy7U7Cupx3qUl1PUsF0JvMLFy7gwoULCAkJ\nKTRyJTU1FS9fvqzw4Aipavz/lXHqelqJqK4nMQydybxNmzZQKBQ4f/58oS4VFxcXTJ06tcKDI6Qq\niUzLxvGHhet62lFdT2IAOpO5g4MDBgwYgEaNGqFFixaGjImQKunr20lQ5ZsgXbuGEKPdqa4nMQy9\nQxMpkROi352ELJx7UaCuZ1sHmFNdT2Ig9Ekj5A0xxrD1VgJnW3OJOfo2orqexHAomRPyhoKjMnA7\nnlvXc157qutJDKtEyfzixYv49NNP8dFHHwEALl++DIVCUaGBEVIV5GgYtheYtt/dxRIda1tWUkSk\nutKbzHfv3o2vvvoKrq6uCAsLAwDcuXMHK1asqPDgCDF2QY9T8Dw1R/s1nwfMpQlCpBLoTeY//PAD\njhw5ggkTJkAkyp34MGPGjBIXcybEVGXkaArV9RzcxAZN7amuJzE8vclcKBRCKMwdwZi3SBBjrLhD\nCKkWvo1IhiyLW9fzA6rrSSqJ3un8PXr0wPvvv4/33nsPWVlZuHjxIn744Qd0797dEPERYpTiM1X4\n/i532v64FvZworqepJLobZkvWrQIHTp0wO7duyESieDv74+33noLixYtMkR8hBilXWHcup4SsQAT\nPKiuJ6k8epsRgYGBeO+99zBr1ixDxEOI0XsiV+Jkgbqe01tLUIPqepJKpPfTd+nSJfTu3RuTJ09G\nQEAAUlJSDBEXIUZr261EaPI9NmpoI8I7zWjaPqlcelvm33zzDbKyshASEoLz589j27ZtaN68Ofr3\n749hw4YZIkZCjMb1mExcflWgrmc7R4ioriepZCX6u1AsFqN3797YsGED9u3bB7FYjE8//bSiYyPE\nqGgYw7YCE4TaOYnRsx7V9SSVT2/LXKPRIDQ0VLu+OZ/Ph6+vL2bOnGmI+AgxGr8+S8O9gnU929ek\nup7EKOhN5l26dEHNmjXRp08f7NixA25uboaIixCjolRrsOOfwnU9W9Wkup7EOOhN5keOHEGTJk0M\nEQshRuv4/RTEZnDres5uRxOEiPHQmcynTp0Kf39/fPDBBzr/jPztt98qLDBCjEWKUg3/cO60/ZGu\ndqhnbVZJERFSmM5kPmfOHADA2rVrDRYMIcZo7x0Z0rK5dT2ntaa6nsS46EzmrVu3BgAcP34cmzdv\nLrR/xIgRCAgIqLjICEeKUo3zL9KRnCZEB8booZuBvErLwfEH3Lqek1vaU11PYnR0JvO80SshISFY\nvnw5Z19qaipevnxZ4cGRXDlqhg/Ov/pvJEUNqP6VYQYt6GQQO/5J5NT1dLYUYoy7XeUFRIgOOpN5\nmzZtoFAocP78edSqVYuzz8XFBVOnTq3w4EiuU09SOUPiDoQn411XWzha0KJOFemXZ2n47Tm3rues\ndg4QC2naPjE+OrOBg4MDBgwYgMaNG6N58+aGjInkk6NmhR6+ZWsYDt2VY14HKoJQUR4lK7H67zjO\nNjd7c/Snup7ESOkdzTJ37lwazVKJTj1J5QyJyxPwUI5JLe1hS3235S4tW42PLsZwVkUU8XlY3sWJ\n6noSo0WjWYxYUa3yPJkqhqP35dR3Xs40jGHZ5ThEpuVwtn/SsSY8HGiCEDFeOjv/8kazeHh4ICcn\nBx07dkTz5s1x5coV/P3333B3dzdYkNWVrlZ5nqP35cjI0ejcT0pv7x0ZLr3K4Gwb1tQGw2hVRGLk\n9D7JWbJkCW7evAkAWLVqFR49egSVSoVPPvmkVBf68ssvMXr0aIwYMQK///47Z1+vXr3g5+eHcePG\nYfz48YiPjy/VuU1RjpphX4FW+cDG1rDkv07eqdkaBDyUFzyUlFHIqwzsLlDT08PBHIs71qykiAgp\nOb3DIR48eIDt27dDoVDgwoULCA4Oho2NDQYMGFDii1y7dg1PnjzBsWPHIJfL8c4776B3797a/Twe\nD/7+/hCL6c/YPKefpiImX6tcxOdhdlsH8FITcDrx9ft06K4co93saITFG4pMy8anl2ORv7qtvbkA\nm7xqw0xA7y0xfno/pXkPPy9fvoyWLVvCxsYGAKBS6f7zv6COHTviq6++AgDY2NhAoVBwikIzxqhI\ndD45agb/O9wW4rBmNqhVQ4Re9tmwEL5+CJeUpS5U9YaUjkKlwUcXYzizPPk8YIOnM5xriCoxMkJK\nTm8yl0qlmDRpElavXg0/Pz8AwM6dO9G0adMSX4TH42lb3QEBAfDy8io0QmblypV47733sGXLltLE\nb5KKapVP+q++pJWQYYQrt//2YEQycjT0y7AsGGNY83c8HiVnc7bPbeeIt5wtKykqQkpPbzfLqlWr\ncPnyZdjb22sfijo7O2Ps2LGlvtj58+fx008/Yd++fZztc+fORY8ePWBnZ4eZM2fi3Llz6NOnT6nP\nbwqKa5Xn8Wtuj2P3U5D9XwKPzVDh7NNUDGlKD+lK6+j9FPzyPI2zrXcDK4xrQbM8SdXCYyXo34iO\njsbVq1eRlJQER0dHdO3atdCsUH1CQkKwY8cO7Nu3D9bWuideHDlyBDKZDLNnzy5yf/4apI8ePSpV\nDFXBpWQRvo993SIU8hjWNUmDRMT9Nh2OFSM42Vz7tZOZGmsap4Oql5Xcw0wBtryoATVev2m1zdRY\n2igdYuomJ5WkWbNm2n/b2pa8gaa3ZR4UFIR169ahU6dOsLGxwe3bt7F+/XqsW7cOPj4+JbpIeno6\nNm7ciIMHDxZK5Onp6Zg7dy527doFkUiEGzduoG/fviU6r1QqLdHrqoocNcOKk88BvO5iGe5qhz4d\nXbVfh4aGQiqVok56Di4HPYfqvxwfny1Ack03+DY0zRmKefddXuIzVfjkzEuoodZusxLxsbNvAzS0\nNa6lbcv73quS6njv+RuspaE3me/btw8nT55EnTp1tNtevnyJDz/8sMTJ/OzZs5DL5Zg3bx7Yfyv+\nde7cGa6urvDx8UHPnj0xatQoiMVitGjRAr6+vmW6maquuL7ygupYidC/sTVOPXndRbAvXIY+Daxo\nRUU9ctQMiy7FIClLzdm+ulsto0vkhJSU3mSek5PDSeQAUL9+fWRnZ+s4orCRI0di5MiROvePGzcO\n48aNK/H5TFFJ+soLmuQhweknadrhdI+SsxHyKgOeda0qMNKqb/PNBIQlZHG2TW1pD+969L6Rqktv\nz6CLiwv27t2L9PTc1ePS0tKwd+9euLi4VHhw1UlpWuV5GtqawacBNwH530mmYZ7FOP0kFccfcP+M\n7VrHkpZFIFWe3mS+du1aXLt2DR07dkSLFi3QuXNn3Lx5k9ZsKUc5aoZ9BVrl7zQtvlWeZ0pLbsWb\nO4lZuBGrKNf4TMV9WRbWXePOLq5TQ4h13Z0hoCfHpIrT281Su3Zt+Pv7Q6VSQS6Xw97eHgIBrdRX\nnk4/TUV0wVZ5y+Jb5XncJObo4WKJkFeZ2m37wmXoWJvGSOeXolTjo+AYKPOthGgu4GFzz9pUNYiY\nBL3JXCaTYc+ePbh9+zZSUlJgZ2cHqVSKqVOnws6OxuK+KV2t8tLMPJzSSsJJ5tdjFfg3QYHWNS3K\nLc6qTK1hWHo5lvMLEwCWdnKCu4SWkCCmQW83y+zZsyGTyTBt2jSsXr0aU6ZMQUxMDGbNmmWI+Eze\nm7TK87SpaYG3anET9747yeUSnynYFZaEK9GZnG0jXW0xuIlNJUVESPnT2zKPjY3FkSNHONt69+6N\nnj17VlRM1UZ5tMrzTGklwY24V9qvL73KwAOZEm4S82KOMn1/RqbDP5z7i611TTE+ltJKiMS06G2Z\nu7q6Ijo6mrMtLi6OSsmVg/Jolefp6GyBVo7cLoP9OgpbVBcvUrOx4i9u6TcHsQAbPWtDJKAHnsS0\n6G2Z29vbY/DgwejUqRNsbW2RnJyMW7duoWvXrli+fLn2dWvWrKnQQE1NebbKgdzFzCa3tMf84Bjt\ntt9fpGNmajYa2FS/iTCZORosCI5Ber7iHUIe8KVnbThZUiFsYnr0fqpdXFwwceJE7dd16tSBh4dH\nRcZULZRnqzyPZ90aaGZnhkfy3AldDMCB8GR81rV06+hUdYwxfPZ3HJ6mcCe2ze9QE+1r0UNhYpr0\nJnNdC16RssvRlG+rPA+fx8PklhIsuRyr3XbmaSreby1BHavqsy739/fk+P1FOmdbv4bWGONOq0oS\n00Vrw1WCn5+Uf6s8T+8GVqhv/Tpxqxjw3d3qM7LlRmwmvrqVyNnWzN4Myzs70Zo1xKRRMjewHE3h\nNVjKo1WeR1DEL4bAR6lIVJS8MlRVFZuRg8WXYpG/Toe1GR+bvWrDQkQfdWLadH7C//rrLwDApUuX\nDBZMdVCwVS7ko9xa5XkGNLKBc76HfNkahkN3Tbvws1KtwccXY5CsfL0SIg/Auu7OqGdd/R4Ak+pH\nZzJftmwZIiMjsW7dOsTHxyMuLq7Qf6R0im6V25Z7nUmRgIcJBRbpCngoR4pSreOIqu/L6wmISFJy\ntk1vLUEPlxqVFBEhhqXzAWiHDh3g6+sLjUYDT0/PQvt5PB7u3btXocGZmqJa5ZPLuVWeZ2hTG+y9\nI4PsvzW7M1UMx+7LMd0EVwf86VEKfnrMLWrt6VID01pLdBxBiOnR2TLftGkT7t69i7feegv3798v\n9B8l8tIxVKs8j1jIh19z7to5R+7LkZFv3LUpiEjMwvrrCZxt9axFWNu9Fvj0wJNUI3qHJn7//ffl\nUgO0ujNkqzzPCFdbHIhIRlp2bgJPzdbgx4cphbpgqipZlgofX4xBTr4nnmIBD5u8asPajFZCJNWL\n3kf8J0+exJAhQ3DhwgU8e/YMv//+OwYPHozz588bIj6TYOhWeR4rMwHGuHNb59/fTUaWquq3zlUa\nhiUhsYjN5I7SWdGlFlztq/d6NKR60tsy9/f3f+MaoNVdZbTK84xxt8P3d5Oh+K/yc1KWGiefpGKU\nW9Vevvibf5JwvUARjrHudujXyDQLWhOij96WeXnUAK3OcjQM+8IN3yrPY2cuwAhX7szHgxHJnK6J\nqub3F2k4GMGdCNXeyQJzOzhWUkSEVD6qAVrBzjxNxav0ymmV5/Frbg+zfGXRYjNU+OVZmkFjKC9P\n5Ep8doU7LLamhQAbPJ0hotJvpBordQ3QLl26UA3QEqqsvvKCaloKMbQptxDD/nAZ1FWsdZ6ercZH\nF2OQqXodt5APbPSqDUcLWgmRVG9VugZofKbKqJczNYZWeZ4JHvY48SgFeSUwX6Tm4I+X6ejTsGr0\nMWsYsOJKHF6k5nC2L5TWRBsqj0dIyddmEQqFcHR0NJpEDgBjz75EWIJxVqIvqlU+tBJa5XnqWInQ\nv8DDwX3hMjBWNVrnvyaZ48/IDM62QY2tCz0PIKS6qtKrDyUq1Jh27hVOPk6p7FAKMaZWeZ7JLSXI\n36v8MDkbIa8ydL7eWPwdnYGgBO5wQ3eJOZZ2opUQCclTpZM5kNsC/uzveHx5IwEqI+kD1tUqr11J\nrfI8DW3N4NPAirPN/06yUbfO7yRkYUlILFi+X0O2/62EKBZW+Y8vIeWmRB3OVWEG6NH7cjyRK7HB\nszbszCu3K8gYW+V5prSUcAo33EnMQmicAm85W1ZiVEULfJSCL64ncIZR8gB80cO5WhXbIKQk9DZt\ngoKCjHYGqLhAUd7rsQr4nX2JR8lKHUdUPGNtledxk5ijhws3cReMt7JlqzVYezUOq6/GFxoPP6ut\nA7rUoZUQCSlIb8t83759RjsDdL9vXSwIjuFM6X6VrsKEXyOxtpszetW3KuboinHWiFvleaa0kiDk\nVab26+uxCtxJyEKrmuJKjCpXfKYKCy/F4N+ErEL7JnrYG917SYixqNIzQJs7iHG4fz20c+ImIYWK\n4aOLMdgdlgSNAfuDc1vl3JmJxtQqz9OmpgWkBQob+4dXfuv8n3gFxp59WSiRiwU8TKuTibntHemB\nJyE6VPkZoBILIXb71MXwZjaF9u36V4aFl2KQaaBlX88+TUVU+utx0MbYKs8zpRV3re9LURl4WEnd\nU4wx/PgwBdN+j0KigltAo66VCN/2q4eOtjk6jiaEAGWYAdq5c2ejmwEqEvCwrHMtLO1UE8ICDbcL\nLzMw4ddIRKVVbDKoKq3yPJ2cLdDSgTvcb18l9J0r1RqsvhqPddfiUXAxx651LHGofz1aBZGQEqjS\nM0ALGuFqh8a25vj4Ygzk+UqkPZZnw+/sS3zpWRsda1fMqI2q1CoHcitFTWklwfzgGO2231+kY2Zq\nNhrYGKZmZlxGDj6+GIPwpMJ/EUxuaY+ZbRwgoPVWCCkRncl8+/btmDNnDpYtW6azn3LNmjUVFlhZ\ndahlgcP962F+cDQeJr/u10/J1mDmH6/wkbQmRrvZlmvfa1Gt8iFNbIy2VZ7Hs24NNLMzwyN57vvE\nABwIT8ZnXSt+2OmtOAUWXorRlrXLYyHkYVXXWujdoGosM0CIsdDZzeLgkFsr0tnZGbVq1SryP2NV\nx0qEg7710KfABBk1A768kYBVf8cjW11+/ehFt8qNv/4kn8crFOeZp6mIyai4LinGGI4/kGP671GF\nEnk9axG+61uPEjkhZaCzZT527FgAgJWVFSZOnFho/4YNGyosqPJgIeJjfQ9nuNon45t/kpB/TMvJ\nJ6l4lpqNTZ61UfMNF+rS1SqvKpNaejewws4wESL/e6agYsC3Ecn4pKNTuV9Lqdbg82vxOPWk8PK7\n3V0s8Xl3Zyr3RkgZ6cxkDx8+xP3797F//344Ojpypnynpqbi2LFjWLx4sUGCLKu8fuGmdmb49K84\nTjHjfxOy4PdLJLZ41YaHY9nHV1fVVnkeAZ+HSR72WH01Xrst6HEqprWSwKEcl5WN+a9//G4R/ePT\nWkkwo42ECjAT8gZ0/rRmZWXh5s2bSE1NxfHjxzn7RCIRFi5cWOHBlRevelb4rp8Z5v0ZrW2BArkT\nVCb/FoUVXZwwoHHhoY36qDQM+8Krbqs8z8DGNtjzr0w7+UqpZjh0T4657cunck9obCYWXorlPJQG\ngBoiPtZ0rQXvSpjcRYip0ZnMW7dujdatW6N58+YYPXp0of23b98u1YW+/PJL3Lp1C2q1Gu+//z56\n9+6t3XflyhVs3boVAoEAnp6emDlzZqnOXRKNbc1wqF89LLkciyvRr2c/ZmsYlv0Vh4fJSsxp51iq\n0RNnn6VxfjlUtVZ5HpGAh/Ee9vjyRoJ22w8P5JjoYQ/bN1jnhjGGo/fl2HIzUbuOep6GNiJs7lkH\njW0NM3KGEFOn9+/o0aNH49atW4iMjNR2tWRkZGDHjh24evVqiS5y7do1PHnyBMeOHYNcLsc777zD\nSebr1q3D/v374eTkBD8/P/j6+qJJkyZlvCXdbMwF2O5dB9tvJ+K7u3LOvu/uyvEoORvrezjDpgQJ\nTFXEGixVsVWe552mNvC/I9M+lMxUMRx7IMf01g5lOp9CpcG6q/E4U0R5Oq+6NbCmWy3qHyekHOlN\n5hs2bEBgYCCaNWuG8PBwuLu748WLF5gzZ06JL9KxY0e0adMGAGBjYwOFQgHGGHg8HiIjI2FnZ6cd\nHXRQcnIAAA4eSURBVOPl5YWrV69WSDIHcvuI53eoCVd7c6z+Ox7Z+RZy+jsmE36/RGKbt/4Wo6m0\nyvOIhXz4NbfD9ttJ2m1H78kxrrk9LEWlW2o2Oj0HH12MwX1Z4f7xGW0kmNaK+scJKW96f0p///13\n/P777/j+++/h7OyMo0ePYuPGjUhISNB3qBaPx4NYnPuQMSAgAF5eXtpx3omJiZBIXidBiUSC+Pj4\nIs9TngY0tsF+37qoacFtHUam5WD8L5G4FJWu40jTa5XnGeFqC2uz1x+JlGwNfnxYusIfV2MyMfbs\ny0KJ3ErEx7aetTG9tQMlckIqgN6WuVAohLV17rhfjSZ3NEi3bt2wfv16zJ07t1QXO3/+PH766Sfs\n27dP52tKUyghNDS0VNcvyiIXHna9ssQTxeu3IiNHg3l/RmNITSX6OyhRMPf8JRchMu31TFIBGN5i\nUQgNjXzjeEqiPO5bFy8bc/yc+Hp0z/6weDTLeAJ9jXPGgN9lZvgxXswpJAEAtc3UmFk3DTXikhEa\nV/bYKvK+jR3de/XRrFmzMh2nN5m7u7tj+vTp+Oabb9CoUSNs3boVzZs3R1pa4b7Q4oSEhGDPnj3Y\nt28frKxej15wcnLitPLj4uLg5FSyMc5SqbRUMejiqdbg82sJOPkkVbuNgYegBDEyLR3xWZdasPgv\nm6k0DKtPvQDwuotlaDNb+HZ2LZdY9AkNDS23+y5KU6Uaf/z0DApV7i/VFDUfkbZNMdLNTucxihwN\nVl2Nw2/xhf+a6VWvBlZ3c0aNUnbVFFTR923M6N6r172npJStDKben7D169ejc+fOEAqFWLJkCcLD\nw7Fr1y4sWbKkxBdJT0/Hxo0bsWvXLm0rP4+LiwsyMjIQHR0NlUqF4OBgdO/evfR38gbMBHys7OKE\nRW/VRIF6Fzj3Ih2TfotC9H9jyU2tr7wgO3MB3i1QJPlgRHKhIhF5otJyMOG3SPz2nJvIeQBmt3XA\nRq/ab5zICSH66W2Zi8ViTJo0CQDQoEGDYrtIdDl79izkcjnmzZunffDZuXNnuLq6wsfHBytXrsSC\nBQsAAAMHDkSDBg1KfY03xePxMMbdDk1szbDoUgxSsl9PMHqQrMTYs5HY0MPZJPvKCxrX3B7H76do\nHw7HZKjwy7M0DG7CHYt/JToDS0JikZrNXRrB2oyPz7s7o7sLVQQixFCKnTS0a9cu3L9/H+3bt8fU\nqVPB5+e2sEJDQ7FhwwYEBASU6CIjR47EyJEjde6XSqU4duxYKUOvGB1rW+JQ//qYHxyNx/LXC3XJ\nlWpMP/+K81ohz7Ra5XlqWgoxpKkNAvI9/DwQLsOARtYQ8HlgjOFgRDK+/icJBRvsTe3MsNmrNuob\naOVFQkgunX//rl27Fo8fP4a3tzdCQkKwe/duPH/+HDNnzsSHH36I/v37GzJOg6prLcK3feuhV73i\nW5ZDmppeqzzPRA97TpfT89QcXIhMR2aOBosuxWL77cKJvHcDK3zbtx4lckIqgc6W+Y0bN/Dzzz9D\nJBKhb9++8PHxwcGDBzFu3Dhs3LgRNWqY9p/QliI+NnrVxt47MuwKK1y0wVRb5XnqWInQv5E1Tj99\n/aB7V5gMu8NkeJLCLRnI5wEftnPAhBb2VNaNkEqiM5nz+XyIRLmtTltbW9ja2iIgIAD29sZbcKG8\n8Xk8TG/tgGZ25lj2V6x2hAdg2q3yPJNaSvDz0zTtipNPUwrXfbUxy12dsksd0/7lToix09nNUrCF\nZWZmVq0SeX696ud2HzS1y+0+aGpnhllty2cRKmPWyNYMbxezCFYzezMc7l+fEjkhRkBny1ytViM+\nPl47iafg1wCMukBFeWtmb44fBtZHfKYKTpbCatOdMKWVPc6/LDx+vG9DK6zo/Hr8PSGkculM5i9e\nvICXlxcneXt6emr/zePxcO/evYqNzsjweDzUMvJScOXNXSLG2/Wt8Md/CZ3PA+a1d4Rfc7tq8wuN\nkKpAZzK/f/++IeMgRmx111pwriFEkkKFUW52aOtkUdkhEUIKKL9SMsRkWYr4+Fhas7LDIIQUgzo8\nCSHEBFAyJ4QQE0DJnBBCTAAlc0IIMQGUzAkhxARQMieEEBNAyZwQQkwAJXNCCDEBlMwJIcQEUDIn\nhBATQMmcEEJMACVzQggxAZTMCSHEBFAyJ4QQE0DJnBBCTAAlc0IIMQGUzAkhxARQMieEEBNAyZwQ\nQkwAJXNCCDEBlMwJIcQEUDInhBATQMmcEEJMACVzQggxAZTMCSHEBFAyJ4QQE0DJnBBCTAAlc0II\nMQGUzAkhxAQIDXWhhw8fYtasWZg4cSLGjh3L2derVy/UqVMHPB4PPB4PmzZtgpOTk6FCI4SQKs8g\nyVyhUGDt2rXo0qVLkft5PB78/f0hFosNEQ4hhJgcg3SzmJubw9/fX2drmzEGxpghQiGEEJNkkJY5\nn8+HmZlZsa9ZuXIloqKiIJVKsWDBAkOERQghJsNgfebFmTt3Lnr06AE7OzvMnDkT586dQ58+ffQe\nl5KSYoDojEuzZs3ovqsZuvfqee+lZRSjWYYMGQKJRAI+nw9PT088fPiwskMihJAqpdKTeXr6/9u7\n/5Cm9j+O489hLcuyLH+llmQFYhEsLBARM9TR/okMU2ETJCSMgpQgywqKTNMiJLQyJYgCzX6YhLEy\nxBJFhSgisjAhUjGzXGFKZu7+IY28qHW/3+s5d2fvx19yth1eY/O1s8+29xlk586dfP/+HYC2tjZW\nr16tciohhHAuiiyzvHjxgvz8fHp6epg1axZWq5XNmzcTFBREbGwsmzZtIikpCXd3d8LCwjAajVPu\na+HChUpEFkIIp6Kzy9dIhBDC6am+zCKEEOL/J2UuhBAaIGUuhBAa4HRlnpeXR3JyMikpKTx//lzt\nOIoqKCggOTmZxMREHjx4oHYcRX379o24uDiqq6vVjqKompoatm7dyvbt22loaFA7jiKGhobYu3cv\nqamppKSk0NjYqHYkRbx+/Zq4uDiuXbsGQG9vLxaLBbPZTGZmpuMbf1NxqjJva2vj7du3VFRUcOLE\nCXJzc9WOpJiWlhbevHlDRUUFly5d4uTJk2pHUlRJSQmLFi1SO4aibDYbxcXFVFRUcPHiRR4+fKh2\nJEXcvn2bkJAQrly5QlFRkUv8n082v6qoqAiLxcLVq1dZvnw5N2/enHYfTlXmzc3NxMbGArBy5Uq+\nfPnC169fVU6ljI0bN1JUVASAp6cnw8PDLjPPprOzk87OTqKjo9WOoqimpiYiIyOZO3cu3t7eHD9+\nXO1IivDy8mJgYAAY/5X34sWLVU408yabX9Xa2kpMTAwAMTExNDU1TbsPpyrz/v7+CQ+sl5cX/f39\nKiZSjk6nc0yVrKqqIjo6Gp1Op3IqZZw6dYrs7Gy1Yyiuu7ub4eFhMjIyMJvNNDc3qx1JESaTiZ6e\nHuLj47FYLBw4cEDtSDNusvlVw8PDzJ49G4AlS5bw4cOHaffxn5jN8r9ylSPTX9XV1XHr1i3Ky8vV\njqKI6upqDAYDgYGBgGs95na7HZvNRklJCV1dXaSmplJfX692rBlXU1NDQEAAZWVltLe3k5OT89sl\nBq37k+e9U5W5r6/vhCPxvr4+fHx8VEykrMePH1NaWkp5eTnz589XO44iGhoa6Orqor6+nt7eXubM\nmYO/v/+Us/G1xNvbG4PBgE6nY9myZXh4ePDp0yfNLzs8efKEqKgoAEJDQ+nr68Nut7vMO9GfPDw8\nGBkZQa/X8/79+9+esMepllkiIyOxWq3A+IgAPz8/5s2bp3IqZQwODlJYWMiFCxdYsGCB2nEUc/bs\nWaqqqqisrCQxMZHdu3e7RJHD+PO9paUFu93OwMAAQ0NDmi9ygODgYJ4+fQqMLzV5eHi4XJEDRERE\nOPrOarU6XuCm4lRH5gaDgTVr1pCcnIybmxtHjx5VO5Jiamtrsdls7Nu3z3GUUlBQgL+/v9rRxAzx\n8/PDaDSyY8cOdDqdyzzfk5KSOHToEBaLhR8/frjEB7+Tza86ffo02dnZVFZWEhAQwLZt26bdh8xm\nEUIIDXCqZRYhhBCTkzIXQggNkDIXQggNkDIXQggNkDIXQggNkDIXQggNkDIXLik0NJTDhw9P2Nba\n2orFYnH8vXbtWkwmE1u2bMFoNLJr1y7evXvnuP7du3dJSEjAZDIRHx/Pnj176OvrU/R+CPGTlLlw\nWW1tbbS3t0/Y9usvDQMDA6mtreXevXtYrVbCw8PZv38/AB0dHeTl5VFcXExtbS1Wq5WgoCBycnIU\nvQ9C/CRlLlxWVlbWP5qVbTabefbsGYODg3R0dODt7c3SpUuB8ReBrKwszpw5M1NxhZiWlLlwSTqd\nDqPRCMD9+/f/6Dajo6O4ubmh1+tZv349PT09ZGRkUFdXx+fPn9Hr9Xh6es5kbCGmJGUuXNrBgwcp\nLCxkZGRk2uuNjY1RVlZGVFQUer0eX19fbty4ga+vL7m5uURERJCWlsarV68USi7ERE41aEuIf1tY\nWBgbNmzg8uXLGAyGCZd1d3djMpkcg83WrVtHfn6+4/Lg4GCOHTsGjJ8NqbS0lPT0dB49eqTofRAC\npMyFIDMzk4SEBIKCgiZs//kB6GRevnyJu7s7K1asACAkJIQjR44QHh6OzWZzufOVCvXJMotwSb8O\nC/Xx8cFsNnPu3Lk/vn1jYyPZ2dl8/PjRse3OnTusWrVKilyoQo7MhUv6+8kO0tLSuH79+h+fBCE9\nPR273U5qaipjY2OMjo4SFhbG+fPnZyKuEL8l88yFEEIDZJlFCCE0QMpcCCE0QMpcCCE0QMpcCCE0\nQMpcCCE0QMpcCCE0QMpcCCE0QMpcCCE0QMpcCCE04C/7+VcvNc3YQAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f04438324e0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_['ratio'] = df_['pos']/(df_['neg'] )\n",
"\n",
"fig, ax = plt.subplots(figsize=(5,5), facecolor='white')\n",
"ax.plot(df_.index, df_['ratio'])\n",
"\n",
"ax.set_axis_bgcolor('white')\n",
"ax.set_title('Comparison of sentiment ratio to NPS')\n",
"ax.set_xlabel('NPS')\n",
"ax.set_ylabel('Ratio of positive to negative comments')"
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [Root]",
"language": "python",
"name": "Python [Root]"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
@quizzicol
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