code/Common_Excel_Operations_Done_In_Pandas.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4a263538",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import libraries\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "180c3b49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   A  B  C   D\n",
       "0  1  4  7  10\n",
       "1  2  5  8  11\n",
       "2  3  6  9  12"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create & View Dataset\n",
    "data = {\n",
    "    \"A\" : [1, 2, 3],\n",
    "    \"B\" : [4, 5, 6],\n",
    "    \"C\" : [7, 8, 9],\n",
    "    \"D\" : [10, 11, 12],\n",
    "}\n",
    "df = pd.DataFrame(data)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "62d748cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['A', 'B', 'C', 'D'], dtype='object')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the Column Names\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "efb68ad9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the Number of Columns in Dataset\n",
    "len(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d98a8856",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the Number of Rows in Dataset\n",
    "len(df.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0b250cc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    2\n",
       "2    3\n",
       "Name: A, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select Specific Column by Column Name\n",
    "df[\"A\"]  # Returned as a pandas series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ac807b3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    2\n",
       "2    3\n",
       "Name: A, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select Specific Column by Position\n",
    "df.iloc[:, 0]  # Returned as a pandas series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d9abc0e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A     2\n",
       "B     5\n",
       "C     8\n",
       "D    11\n",
       "Name: 1, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select Specific Row by Index Number\n",
    "df.loc[1]  # Returned as a pandas series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7fecfadb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A     2\n",
       "B     5\n",
       "C     8\n",
       "D    11\n",
       "Name: 1, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select Specific Row by Position\n",
    "df.iloc[1]  # Returned as a pandas series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d3a9fc2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select Specific Cell (Column & Row)\n",
    "df.loc[1, \"A\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a2de4848",
   "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",
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       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
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       "      <td>11</td>\n",
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       "</table>\n",
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      "text/plain": [
       "   A  B  C   D\n",
       "1  2  5  8  11"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter Dataset For Specific Value in Column\n",
    "df_filtered = df[df[\"A\"] == 2]\n",
    "df_filtered"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ffe59fdc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
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       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
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      "text/plain": [
       "   A  B  C   D\n",
       "0  1  4  7  10\n",
       "2  3  6  9  12"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter Dataset With List Comprehension on a Single Column of Data\n",
    "df_filtered = df[[val % 2 == 0 for val in df[\"B\"]]]  # Looks for even numbers in column B\n",
    "df_filtered"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ce5c44c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
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       "      <td>11</td>\n",
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      "text/plain": [
       "   A  B  C   D\n",
       "0  1  4  7  10\n",
       "1  2  5  8  11"
      ]
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     "execution_count": 13,
     "metadata": {},
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   ],
   "source": [
    "# Filter Dataset With List Comprehension Across Entire Row of Data\n",
    "df_filtered = df[[df.loc[row, \"A\"] == 1 or df.loc[row, \"B\"] == 5 for row in df.index]]\n",
    "df_filtered"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0611be64",
   "metadata": {},
   "outputs": [
    {
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      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "   A   D  C  B\n",
       "0  1  10  7  4\n",
       "1  2  11  8  5\n",
       "2  3  12  9  6"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reorder Columns\n",
    "df_reordered = df.loc[:, [\"A\", \"D\", \"C\", \"B\"]]\n",
    "df_reordered"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0e62dad2",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
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       "      <td>2</td>\n",
       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
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      "text/plain": [
       "   A  B\n",
       "0  1  4\n",
       "1  2  5\n",
       "2  3  6"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove Columns\n",
    "df_removed = df.loc[:, [\"A\", \"B\"]]  # Give only the column(s) you want to keep\n",
    "df_removed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ea46a53c",
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>E.13.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>11</td>\n",
       "      <td>E.14.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>E.15.16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "   A  B  C   D        E\n",
       "0  1  4  7  10  E.13.14\n",
       "1  2  5  8  11  E.14.15\n",
       "2  3  6  9  12  E.15.16"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create New Column With List Comprehension\n",
    "df[\"E\"] = [f\"E.{val}.{val + 1}\" for val in range(13, 16)]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "952a9bdb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>B</th>\n",
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       "      <th>0</th>\n",
       "      <td>100</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>E.13.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>11</td>\n",
       "      <td>E.14.15</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>E.15.16</td>\n",
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      "text/plain": [
       "     A  B  C   D        E\n",
       "0  100  4  7  10  E.13.14\n",
       "1    2  5  8  11  E.14.15\n",
       "2    3  6  9  12  E.15.16"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Replace Values\n",
    "df.replace(1, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "be2834dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>F</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>E.13.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>11</td>\n",
       "      <td>E.14.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "      <td>E.15.16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   F  B  C   D        E\n",
       "0  1  4  7  10  E.13.14\n",
       "1  2  5  8  11  E.14.15\n",
       "2  3  6  9  12  E.15.16"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rename Column\n",
    "df_renamed = df.rename(columns={\"A\": \"F\"})\n",
    "df_renamed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ec6a4f10",
   "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",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>E.13.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>E.15.16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     A    B    C     D        E\n",
       "0  1.0  4.0  7.0  10.0  E.13.14\n",
       "2  3.0  6.0  9.0  12.0  E.15.16"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove Blank Rows\n",
    "\n",
    "# I need to add a blank row to demonstrate this...\n",
    "df.iloc[1] = np.nan  # Sets every value on row 1 to NaN (Not a Number)\n",
    "\n",
    "df.dropna(how=\"all\", inplace=True)\n",
    "df  # Note the index jumps from 0 -> 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "db294c42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>E.13.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>555.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>555</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       A      B      C      D        E\n",
       "0    1.0    4.0    7.0   10.0  E.13.14\n",
       "2  555.0  555.0  555.0  555.0      555"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reminder about .iloc vs loc\n",
    "df.iloc[1] = 555\n",
    "df  # Note that .iloc references relative positions, not exact index numbers and names like .loc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "401fd215",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>E.13.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>555.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>555.0</td>\n",
       "      <td>555</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       A      B      D        E\n",
       "0    1.0    4.0   10.0  E.13.14\n",
       "2  555.0  555.0  555.0      555"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove Blank Columns\n",
    "\n",
    "# I need to add a blank column to demonstrate this...\n",
    "df[\"C\"] = np.NaN  # Sets every value on columnn C to NaN (Not a Number)\n",
    "\n",
    "# Find columns that are not blank\n",
    "columns_that_are_not_blank = [i[0] for i in zip(df.columns, df.isna().all()) if i[1] == False]\n",
    "\n",
    "# Remove them as was shown above\n",
    "df = df.loc[:, columns_that_are_not_blank]  # Give only the column(s) you want to keep\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2b6fc9a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>E.13.14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     A    B     D        E\n",
       "0  1.0  4.0  10.0  E.13.14"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove Rows with Blanks in a Given Column\n",
    "\n",
    "# I need to add a blank value in a column to demonstrate this...\n",
    "df.loc[2, \"D\"] = np.NaN\n",
    "\n",
    "df.dropna(subset=[\"D\"], inplace=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "cf810957",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1.0</th>\n",
       "      <th>4.0</th>\n",
       "      <th>10.0</th>\n",
       "      <th>E.13.14</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [1.0, 4.0, 10.0, E.13.14]\n",
       "Index: []"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove Header Rows\n",
    "\n",
    "# determine which row should be the new header row\n",
    "header_row = 0\n",
    "\n",
    "# store new header names\n",
    "cols = [_ for _ in df.iloc[header_row]]\n",
    "\n",
    "# Remove rows up until that point\n",
    "df = df.drop(df.head(header_row + 1).index)\n",
    "\n",
    "# Reset df.columns with new column names\n",
    "df.columns = cols\n",
    "df"
   ]
  }
 ],
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