Preprocessing first approach
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Project/Tools/Preprocessing.ipynb
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151
Project/Tools/Preprocessing.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"from nltk.corpus import stopwords"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"table = pd.read_csv(\"emoji_descriptions.csv\", names=(\"id\",\"char\", \"description\"))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>id</th>\n",
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" <th>char</th>\n",
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" <th>description</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>NaN</th>\n",
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" <td>code</td>\n",
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" <td>character</td>\n",
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" <td>descripion,</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>0.0</th>\n",
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" <td>126980</td>\n",
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" <td>🀄</td>\n",
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" <td>MAHJONG TILE RED DRAGON</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1.0</th>\n",
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" <td>129525</td>\n",
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" <td>🧵</td>\n",
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" <td>SPOOL OF THREAD</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2.0</th>\n",
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" <td>129526</td>\n",
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" <td>🧶</td>\n",
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" <td>BALL OF YARN</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3.0</th>\n",
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" <td>127183</td>\n",
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" <td>🃏</td>\n",
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" <td>PLAYING CARD BLACK JOKER</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" id char description\n",
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"NaN code character descripion,\n",
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" 0.0 126980 🀄 MAHJONG TILE RED DRAGON\n",
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" 1.0 129525 🧵 SPOOL OF THREAD\n",
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" 2.0 129526 🧶 BALL OF YARN\n",
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" 3.0 127183 🃏 PLAYING CARD BLACK JOKER"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"table.head()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"prepStep1Table = table\n",
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"print(table[3])\n",
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"# lowercasing\n",
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"#for entry in table[\"description\"][1:]:\n",
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" # prepStep1Table[\"description\"][entry] = table[\"description\"][entry].toLower()\n",
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"#print(prepStep1Table)\n",
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"#stopword removal\n",
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"#for entry in prepStep1Table[\"description\"][1:]:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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