word-count-program.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d3d3046d",
   "metadata": {},
   "source": [
    "### Import pandas library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "3932b402",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fec71609",
   "metadata": {},
   "source": [
    "### Read input text file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "fae6cf10",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lines</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>hi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>this is input file for word count program in p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>to demonstrate how word count program can be w...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Pandas is a very useful Python library for dat...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               lines\n",
       "0                                                 hi\n",
       "1  this is input file for word count program in p...\n",
       "2  to demonstrate how word count program can be w...\n",
       "3  Pandas is a very useful Python library for dat..."
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"word-count.txt\", sep='\\t', header=None, names=['lines'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efeab258",
   "metadata": {},
   "source": [
    "### Covert all letters to lowercase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "43fdb4fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['lines'] = df['lines'].str.lower()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40ac96bd",
   "metadata": {},
   "source": [
    "### Split sentences to get words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "b4228912",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>lines</th>\n",
       "      <th>words</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>hi</td>\n",
       "      <td>[hi]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>this is input file for word count program in p...</td>\n",
       "      <td>[this, is, input, file, for, word, count, prog...</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>to demonstrate how word count program can be w...</td>\n",
       "      <td>[to, demonstrate, how, word, count, program, c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>pandas is a very useful python library for dat...</td>\n",
       "      <td>[pandas, is, a, very, useful, python, library,...</td>\n",
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      "text/plain": [
       "                                               lines  \\\n",
       "0                                                 hi   \n",
       "1  this is input file for word count program in p...   \n",
       "2  to demonstrate how word count program can be w...   \n",
       "3  pandas is a very useful python library for dat...   \n",
       "\n",
       "                                               words  \n",
       "0                                               [hi]  \n",
       "1  [this, is, input, file, for, word, count, prog...  \n",
       "2  [to, demonstrate, how, word, count, program, c...  \n",
       "3  [pandas, is, a, very, useful, python, library,...  "
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['words'] = df['lines'].str.split()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e8cebea",
   "metadata": {},
   "source": [
    "### Remove lines column as no longer needed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "da50928d",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>words</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[hi]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[this, is, input, file, for, word, count, prog...</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[to, demonstrate, how, word, count, program, c...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[pandas, is, a, very, useful, python, library,...</td>\n",
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      "text/plain": [
       "                                               words\n",
       "0                                               [hi]\n",
       "1  [this, is, input, file, for, word, count, prog...\n",
       "2  [to, demonstrate, how, word, count, program, c...\n",
       "3  [pandas, is, a, very, useful, python, library,..."
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.pop(\"lines\")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60fe5e8d",
   "metadata": {},
   "source": [
    "### Explode words array to get individual words in each row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "80675ffb",
   "metadata": {},
   "outputs": [
    {
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       "      <th>words</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>hi</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>this</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>is</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>input</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>file</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>row</td>\n",
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       "      <td>labels</td>\n",
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       "      <td>of</td>\n",
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       "      <th>3</th>\n",
       "      <td>a</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>dataframe.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>109 rows × 1 columns</p>\n",
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      "text/plain": [
       "         words\n",
       "0           hi\n",
       "1         this\n",
       "1           is\n",
       "1        input\n",
       "1         file\n",
       "..         ...\n",
       "3          row\n",
       "3       labels\n",
       "3           of\n",
       "3            a\n",
       "3   dataframe.\n",
       "\n",
       "[109 rows x 1 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.explode('words')\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d1cd0c8",
   "metadata": {},
   "source": [
    "### Group by on words via value_counts method and rename columns and sort on count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "83dc20e1",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>word</th>\n",
       "      <th>count</th>\n",
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       "      <td>pandas</td>\n",
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       "      <td>in</td>\n",
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       "      <th>4</th>\n",
       "      <td>can</td>\n",
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       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>data,</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>including</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>tabular,</td>\n",
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       "      <th>67</th>\n",
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       "      <td>1</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>68 rows × 2 columns</p>\n",
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      ],
      "text/plain": [
       "          word  count\n",
       "0         data      6\n",
       "1            a      6\n",
       "2       pandas      5\n",
       "3           in      4\n",
       "4          can      4\n",
       "..         ...    ...\n",
       "63  structured      1\n",
       "64       data,      1\n",
       "65   including      1\n",
       "66    tabular,      1\n",
       "67  dataframe.      1\n",
       "\n",
       "[68 rows x 2 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df['words'].value_counts().reset_index()\n",
    "df.columns=['word', 'count']\n",
    "df.sort_values('count', ascending=False)\n",
    "df"
   ]
  }
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