292 lines
8.4 KiB
Plaintext
292 lines
8.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 36,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[nltk_data] Downloading package stopwords to\n",
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"[nltk_data] C:\\Users\\Maren\\AppData\\Roaming\\nltk_data...\n",
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"[nltk_data] Unzipping corpora\\stopwords.zip.\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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"execution_count": 36,
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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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"import pandas as pd\n",
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"import nltk\n",
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"nltk.download('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": 33,
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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\")"
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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": 15,
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"metadata": {},
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"outputs": [
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"data": {
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" <thead>\n",
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" <th>code</th>\n",
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" <td>0</td>\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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" <td>NaN</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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" <th>2</th>\n",
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" <td>2</td>\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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" <td>3</td>\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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" <td>NaN</td>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>4</td>\n",
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" <td>129296</td>\n",
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" <td>🤐</td>\n",
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" <td>ZIPPER-MOUTH FACE</td>\n",
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" <td>NaN</td>\n",
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"3 3 127183 🃏 PLAYING CARD BLACK JOKER NaN\n",
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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": 46,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"C:\\Users\\Maren\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
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"A value is trying to be set on a copy of a slice from a DataFrame\n",
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"\n",
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"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
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" \"\"\"\n",
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"C:\\Users\\Maren\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:10: SettingWithCopyWarning: \n",
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"A value is trying to be set on a copy of a slice from a DataFrame\n",
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"\n",
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"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
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" # Remove the CWD from sys.path while we load stuff.\n"
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]
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{
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"data": {
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" <th>code</th>\n",
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" <th>description</th>\n",
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" <th>Unnamed: 4</th>\n",
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" <td>0</td>\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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" <td>NaN</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>1</td>\n",
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" <td>129525</td>\n",
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" <td>🧵</td>\n",
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" <td>spool thread</td>\n",
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" <td>NaN</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>2</td>\n",
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" <td>129526</td>\n",
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" <td>🧶</td>\n",
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" <td>ball yarn</td>\n",
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" <td>NaN</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>3</td>\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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" <td>NaN</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>4</td>\n",
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" <td>129296</td>\n",
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" <td>🤐</td>\n",
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" <td>zipper-mouth face</td>\n",
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" <td>NaN</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"text/plain": [
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" Unnamed: 0 code character description Unnamed: 4\n",
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"0 0 126980 🀄 mahjong tile red dragon NaN\n",
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"1 1 129525 🧵 spool thread NaN\n",
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"2 2 129526 🧶 ball yarn NaN\n",
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"3 3 127183 🃏 playing card black joker NaN\n",
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"4 4 129296 🤐 zipper-mouth face NaN"
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]
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},
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"execution_count": 46,
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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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"prepStep1Table = table\n",
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"\n",
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"# lowercasing and stopword removal\n",
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"for entry in range(len(table[\"description\"][1:])):\n",
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" table[\"description\"][entry] = table[\"description\"][entry].lower()\n",
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" newEntry = []\n",
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" for word in table[\"description\"][entry].split(\" \"):\n",
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" if word not in set(stopwords.words('english')):\n",
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" newEntry.append(word)\n",
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" table[\"description\"][entry] = (\" \").join(newEntry).lower()\n",
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" \n",
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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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}
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],
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"display_name": "Python 3",
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"name": "python3"
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"language_info": {
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"name": "ipython",
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