reg_pandas.ipynb

{
 "cells": [
  {
   "cell_type": "code",
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    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Title</th>\n",
       "      <th>Author</th>\n",
       "      <th>Genre</th>\n",
       "      <th>SubGenre</th>\n",
       "      <th>Height</th>\n",
       "      <th>Publisher</th>\n",
       "      <th>WordsInTitle</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fundamentals of Wavelets</td>\n",
       "      <td>Goswami, Jaideva</td>\n",
       "      <td>tech</td>\n",
       "      <td>signal_processing</td>\n",
       "      <td>228</td>\n",
       "      <td>Wiley</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Data Smart</td>\n",
       "      <td>Foreman, John</td>\n",
       "      <td>tech</td>\n",
       "      <td>data_science</td>\n",
       "      <td>235</td>\n",
       "      <td>Wiley</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>God Created the Integers</td>\n",
       "      <td>Hawking, Stephen</td>\n",
       "      <td>tech</td>\n",
       "      <td>mathematics</td>\n",
       "      <td>197</td>\n",
       "      <td>Penguin</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Superfreakonomics</td>\n",
       "      <td>Dubner, Stephen</td>\n",
       "      <td>science</td>\n",
       "      <td>economics</td>\n",
       "      <td>179</td>\n",
       "      <td>HarperCollins</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Orientalism</td>\n",
       "      <td>Said, Edward</td>\n",
       "      <td>nonfiction</td>\n",
       "      <td>history</td>\n",
       "      <td>197</td>\n",
       "      <td>Penguin</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>Structure and Randomness</td>\n",
       "      <td>Tao, Terence</td>\n",
       "      <td>science</td>\n",
       "      <td>mathematics</td>\n",
       "      <td>252</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>Image Processing with MATLAB</td>\n",
       "      <td>Eddins, Steve</td>\n",
       "      <td>tech</td>\n",
       "      <td>signal_processing</td>\n",
       "      <td>241</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>Animal Farm</td>\n",
       "      <td>Orwell, George</td>\n",
       "      <td>fiction</td>\n",
       "      <td>classic</td>\n",
       "      <td>180</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>Idiot, The</td>\n",
       "      <td>Dostoevsky, Fyodor</td>\n",
       "      <td>fiction</td>\n",
       "      <td>classic</td>\n",
       "      <td>197</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>Christmas Carol, A</td>\n",
       "      <td>Dickens, Charles</td>\n",
       "      <td>fiction</td>\n",
       "      <td>classic</td>\n",
       "      <td>196</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>211 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Title              Author       Genre  \\\n",
       "0        Fundamentals of Wavelets    Goswami, Jaideva        tech   \n",
       "1                      Data Smart       Foreman, John        tech   \n",
       "2        God Created the Integers    Hawking, Stephen        tech   \n",
       "3               Superfreakonomics     Dubner, Stephen     science   \n",
       "4                     Orientalism        Said, Edward  nonfiction   \n",
       "..                            ...                 ...         ...   \n",
       "206      Structure and Randomness        Tao, Terence     science   \n",
       "207  Image Processing with MATLAB       Eddins, Steve        tech   \n",
       "208                   Animal Farm      Orwell, George     fiction   \n",
       "209                    Idiot, The  Dostoevsky, Fyodor     fiction   \n",
       "210            Christmas Carol, A    Dickens, Charles     fiction   \n",
       "\n",
       "              SubGenre  Height      Publisher  WordsInTitle  \n",
       "0    signal_processing     228          Wiley             3  \n",
       "1         data_science     235          Wiley             2  \n",
       "2          mathematics     197        Penguin             4  \n",
       "3            economics     179  HarperCollins             1  \n",
       "4              history     197        Penguin             1  \n",
       "..                 ...     ...            ...           ...  \n",
       "206        mathematics     252            NaN             3  \n",
       "207  signal_processing     241            NaN             4  \n",
       "208            classic     180            NaN             2  \n",
       "209            classic     197            NaN             2  \n",
       "210            classic     196            NaN             3  \n",
       "\n",
       "[211 rows x 7 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#1-2\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import re\n",
    "\n",
    "df = pd.read_csv('Books.csv')\n",
    "\n",
    "#df[df['Publisher'].str.findall('[aeiouyAEIOUY]+?').str.len() <= 1]\n",
    "WordsInTitle = df['Title'].str.split(' ').str.len()\n",
    "df['WordsInTitle'] = WordsInTitle\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "61    Taub, Schilling\n",
       "Name: Author, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#3\n",
    "# df[df['Author'].str.match(r'.{1,}[^AaEeIiOoYyUu, \\s]{3}.{1,}')==True].Author\n",
    "df[df['Author'].str.match(r'^\\S*\\sSc')==True].Author"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>last_name</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>Hugo</td>\n",
       "      <td>Victor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>Singh</td>\n",
       "      <td>Simon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>Singh</td>\n",
       "      <td>Simon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>Rowling</td>\n",
       "      <td>J</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "    last_name    name\n",
       "96       Hugo  Victor\n",
       "133     Singh   Simon\n",
       "136     Singh   Simon\n",
       "200   Rowling       J"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# d = df['Author'].str.extract('(?P<last_name>\\w*)(?P<name>, \\w+)')\n",
    "# d['name'] = d['name'].str.slice(2,)\n",
    "\n",
    "\n",
    "# d = d[(d['last_name'].str.findall('a').str.len()==0)&(d['last_name'].str.findall('e').str.len()==0)]\n",
    "# d = d[(d['name'].str.findall('a').str.len()==0)&(d['name'].str.findall('e').str.len()==0)]\n",
    "# d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Pirsig, Robert'}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#4\n",
    "\n",
    "title_max = len(df['Title'].max())\n",
    "author = set(df[df['Title'].str.len() == title_max].Author)\n",
    "author"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2                      God Created the Integers\n",
       "44                      Hidden Connections, The\n",
       "55         Soft Computing & Intelligent Systems\n",
       "75        Social Choice & Welfare, Vol 39 No. 1\n",
       "105    Maugham's Collected Short Stories, Vol 3\n",
       "134                      Pattern Classification\n",
       "138                                Final Crisis\n",
       "167                         Jim Corbett Omnibus\n",
       "169                             Batatyachi Chal\n",
       "175                            Think Complexity\n",
       "210                          Christmas Carol, A\n",
       "Name: Title, dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#5\n",
    "\n",
    "df[df['Title'].str.contains(r'^\\S*\\sC')== True].Title\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Dmytro\\anaconda3\\lib\\site-packages\\pandas\\core\\strings.py:1954: UserWarning: This pattern has match groups. To actually get the groups, use str.extract.\n",
      "  return func(self, *args, **kwargs)\n"
     ]
    },
    {
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       "      <th>Title</th>\n",
       "      <th>Author</th>\n",
       "      <th>Genre</th>\n",
       "      <th>SubGenre</th>\n",
       "      <th>Height</th>\n",
       "      <th>Publisher</th>\n",
       "      <th>WordsInTitle</th>\n",
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       "Empty DataFrame\n",
       "Columns: [Title, Author, Genre, SubGenre, Height, Publisher, WordsInTitle]\n",
       "Index: []"
      ]
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     "execution_count": 8,
     "metadata": {},
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   "source": [
    "df[df['Title'].str.contains(r'\\b(a-zA-Z{1})\\b')== True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Title</th>\n",
       "      <th>Author</th>\n",
       "      <th>Genre</th>\n",
       "      <th>SubGenre</th>\n",
       "      <th>Height</th>\n",
       "      <th>Publisher</th>\n",
       "      <th>WordsInTitle</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Catch 22</td>\n",
       "      <td>Heller, Joseph</td>\n",
       "      <td>fiction</td>\n",
       "      <td>classic</td>\n",
       "      <td>178</td>\n",
       "      <td>Random House</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>Social Choice &amp; Welfare, Vol 39 No. 1</td>\n",
       "      <td>Various</td>\n",
       "      <td>tech</td>\n",
       "      <td>economics</td>\n",
       "      <td>235</td>\n",
       "      <td>Springer</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Maugham's Collected Short Stories, Vol 3</td>\n",
       "      <td>Maugham, William S</td>\n",
       "      <td>fiction</td>\n",
       "      <td>classic</td>\n",
       "      <td>171</td>\n",
       "      <td>Vintage</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>Numbers Behind Numb3rs, The</td>\n",
       "      <td>Devlin, Keith</td>\n",
       "      <td>science</td>\n",
       "      <td>mathematics</td>\n",
       "      <td>202</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>Superman Earth One - 1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fiction</td>\n",
       "      <td>comic</td>\n",
       "      <td>259</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Superman Earth One - 2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fiction</td>\n",
       "      <td>comic</td>\n",
       "      <td>258</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>Journal of Economics, vol 106 No 3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>science</td>\n",
       "      <td>economics</td>\n",
       "      <td>235</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>20000 Leagues Under the Sea</td>\n",
       "      <td>Verne, Jules</td>\n",
       "      <td>fiction</td>\n",
       "      <td>novel</td>\n",
       "      <td>190</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                                        Title              Author    Genre  \\\n",
       "52                                   Catch 22      Heller, Joseph  fiction   \n",
       "75      Social Choice & Welfare, Vol 39 No. 1             Various     tech   \n",
       "105  Maugham's Collected Short Stories, Vol 3  Maugham, William S  fiction   \n",
       "143               Numbers Behind Numb3rs, The       Devlin, Keith  science   \n",
       "144                    Superman Earth One - 1                 NaN  fiction   \n",
       "145                    Superman Earth One - 2                 NaN  fiction   \n",
       "153        Journal of Economics, vol 106 No 3                 NaN  science   \n",
       "168               20000 Leagues Under the Sea        Verne, Jules  fiction   \n",
       "\n",
       "        SubGenre  Height     Publisher  WordsInTitle  \n",
       "52       classic     178  Random House             2  \n",
       "75     economics     235      Springer             8  \n",
       "105      classic     171       Vintage             6  \n",
       "143  mathematics     202           NaN             4  \n",
       "144        comic     259           NaN             5  \n",
       "145        comic     258           NaN             5  \n",
       "153    economics     235           NaN             7  \n",
       "168        novel     190           NaN             5  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#7\n",
    "\n",
    "df_v2 = df[df.Title.str.contains('[0-9]')==True]\n",
    "df_v2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-10-474981f9de79>:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_v2['digit'] = digit\n"
     ]
    },
    {
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       "      <th>Title</th>\n",
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       "      <th>Genre</th>\n",
       "      <th>SubGenre</th>\n",
       "      <th>Height</th>\n",
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       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Catch 22</td>\n",
       "      <td>Heller, Joseph</td>\n",
       "      <td>fiction</td>\n",
       "      <td>classic</td>\n",
       "      <td>178</td>\n",
       "      <td>Random House</td>\n",
       "      <td>2</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>Social Choice &amp; Welfare, Vol 39 No. 1</td>\n",
       "      <td>Various</td>\n",
       "      <td>tech</td>\n",
       "      <td>economics</td>\n",
       "      <td>235</td>\n",
       "      <td>Springer</td>\n",
       "      <td>8</td>\n",
       "      <td>391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Maugham's Collected Short Stories, Vol 3</td>\n",
       "      <td>Maugham, William S</td>\n",
       "      <td>fiction</td>\n",
       "      <td>classic</td>\n",
       "      <td>171</td>\n",
       "      <td>Vintage</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>Numbers Behind Numb3rs, The</td>\n",
       "      <td>Devlin, Keith</td>\n",
       "      <td>science</td>\n",
       "      <td>mathematics</td>\n",
       "      <td>202</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>Superman Earth One - 1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fiction</td>\n",
       "      <td>comic</td>\n",
       "      <td>259</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Superman Earth One - 2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fiction</td>\n",
       "      <td>comic</td>\n",
       "      <td>258</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>Journal of Economics, vol 106 No 3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>science</td>\n",
       "      <td>economics</td>\n",
       "      <td>235</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>1063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>20000 Leagues Under the Sea</td>\n",
       "      <td>Verne, Jules</td>\n",
       "      <td>fiction</td>\n",
       "      <td>novel</td>\n",
       "      <td>190</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Title              Author    Genre  \\\n",
       "52                                   Catch 22      Heller, Joseph  fiction   \n",
       "75      Social Choice & Welfare, Vol 39 No. 1             Various     tech   \n",
       "105  Maugham's Collected Short Stories, Vol 3  Maugham, William S  fiction   \n",
       "143               Numbers Behind Numb3rs, The       Devlin, Keith  science   \n",
       "144                    Superman Earth One - 1                 NaN  fiction   \n",
       "145                    Superman Earth One - 2                 NaN  fiction   \n",
       "153        Journal of Economics, vol 106 No 3                 NaN  science   \n",
       "168               20000 Leagues Under the Sea        Verne, Jules  fiction   \n",
       "\n",
       "        SubGenre  Height     Publisher  WordsInTitle  digit  \n",
       "52       classic     178  Random House             2     22  \n",
       "75     economics     235      Springer             8    391  \n",
       "105      classic     171       Vintage             6      3  \n",
       "143  mathematics     202           NaN             4      3  \n",
       "144        comic     259           NaN             5      1  \n",
       "145        comic     258           NaN             5      2  \n",
       "153    economics     235           NaN             7   1063  \n",
       "168        novel     190           NaN             5  20000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "digit = df_v2.Title.str.replace(r'\\D{1,}', r'').str.strip()\n",
    "digit = digit.str.replace(r' ', r'+')\n",
    "df_v2['digit'] = digit\n",
    "df_v2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      []\n",
       "1      []\n",
       "2      []\n",
       "3      []\n",
       "4      []\n",
       "       ..\n",
       "206    []\n",
       "207    []\n",
       "208    []\n",
       "209    []\n",
       "210    []\n",
       "Name: Title, Length: 211, dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df[df['Title'].str.findall('\\b\\w\\b{3}').str.len() != 0]\n",
    "df['Title'].str.findall('\\w{3}?')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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