Rename_Columns_in_Pandas_Dataframe.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Renaming Columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is the Jupyter notebook for the YouTube Video (found [here](https://youtu.be/_Um3vVZQMok)) about renaming columns in Pandas Datframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>Subject ID</th>\n",
       "      <th>First Name</th>\n",
       "      <th>Day</th>\n",
       "      <th>Age</th>\n",
       "      <th>Response Time</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Miss\\Col</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>John</td>\n",
       "      <td>Sixth</td>\n",
       "      <td>23</td>\n",
       "      <td>0.562719</td>\n",
       "      <td>0</td>\n",
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       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Billie</td>\n",
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       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Don</td>\n",
       "      <td>Sixth</td>\n",
       "      <td>27</td>\n",
       "      <td>0.522961</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Joseph</td>\n",
       "      <td>Sixth</td>\n",
       "      <td>21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "   Subject ID First Name    Day  Age  Response Time  Gender  Miss\\Col\n",
       "0           1       John  Sixth   23       0.562719       0       NaN\n",
       "1           2     Billie  Sixth   22            NaN       0       NaN\n",
       "2           3     Robert  Sixth   20            NaN       0       NaN\n",
       "3           4        Don  Sixth   27       0.522961       0       NaN\n",
       "4           5     Joseph  Sixth   21            NaN       0       NaN"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv('./Simdata/play_data.csv',\n",
    "                index_col=0)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1 Change the Name of a Single Column:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns={'Subject ID':'SubID'},\n",
    "         inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2 Change the Name of Two Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns={'Subject ID':'SubID',\n",
    "                  'Day':'Session'},\n",
    "         inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3 Change the Name of Three Columns\n",
    "As you can see, we just add a dictionary-value pair for each column we want to rename:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns={'Subject ID':'SubID',\n",
    "                  'Day':'Session',\n",
    "                  'Response Time':'RT'},\n",
    "         inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This way we can rename multiple columns in the dataframe. I.e., we can rename 2, 3, 4, 5, and so on, if we want to."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4 Rename Columns with df.columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "      <th>Session</th>\n",
       "      <th>Age</th>\n",
       "      <th>RT</th>\n",
       "      <th>Sex</th>\n",
       "      <th>MissingVals</th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>John</td>\n",
       "      <td>Sixth</td>\n",
       "      <td>23</td>\n",
       "      <td>0.562719</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Billie</td>\n",
       "      <td>Sixth</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>3</th>\n",
       "      <td>4</td>\n",
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       "      <td>Sixth</td>\n",
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       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Joseph</td>\n",
       "      <td>Sixth</td>\n",
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       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
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      "text/plain": [
       "   ID    Name Session  Age        RT  Sex  MissingVals\n",
       "0   1    John   Sixth   23  0.562719    0          NaN\n",
       "1   2  Billie   Sixth   22       NaN    0          NaN\n",
       "2   3  Robert   Sixth   20       NaN    0          NaN\n",
       "3   4     Don   Sixth   27  0.522961    0          NaN\n",
       "4   5  Joseph   Sixth   21       NaN    0          NaN"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv('./Simdata/play_data.csv',\n",
    "                index_col=0)\n",
    "df.head()\n",
    "\n",
    "new_cols = ['ID', 'Name', 'Session',\n",
    "           'Age', 'RT', 'Sex', 'MissingVals']\n",
    "\n",
    "df.columns = new_cols\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 5 Changing Column Names when Reading Data to a Dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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       "      <td>Billie</td>\n",
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       "   Subject ID First Name    Day  Age  Response Time  Gender  Miss\\Col\n",
       "0           1       John  Sixth   23       0.562719       0       NaN\n",
       "1           2     Billie  Sixth   22            NaN       0       NaN\n",
       "2           3     Robert  Sixth   20            NaN       0       NaN\n",
       "3           4        Don  Sixth   27       0.522961       0       NaN\n",
       "4           5     Joseph  Sixth   21            NaN       0       NaN"
      ]
     },
     "execution_count": 7,
     "metadata": {},
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   "source": [
    "import pandas as pd\n",
    "\n",
    "new_cols = ['ID', 'Name', 'Session',\n",
    "           'Age', 'RT', 'Sex', 'MissingVals']\n",
    "\n",
    "\n",
    "df = pd.read_csv('./Simdata/play_data.csv',\n",
    "                index_col=0)\n",
    "df.head()"
   ]
  }
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