notebooks/show_all_columns.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Show all columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setup\n",
    "\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create toy data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create toy data\n",
    "\n",
    "from random import randint\n",
    "\n",
    "columns = [f'col_{i}' for i in range(30)]\n",
    "data = []\n",
    "for i in range(5):\n",
    "    data.append(tuple(randint(0, 11) for c in columns))\n",
    "    \n",
    "df = pd.DataFrame.from_records(data, columns=columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## By default Pandas truncates the number of columns it displays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>col_0</th>\n",
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       "      <th>col_9</th>\n",
       "      <th>...</th>\n",
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       "      <th>col_29</th>\n",
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       "      <td>2</td>\n",
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       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
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       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
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       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   col_0  col_1  col_2  col_3  col_4  col_5  col_6  col_7  col_8  col_9  ...  \\\n",
       "0      2      9     11      9      4      0     11      9      4     11  ...   \n",
       "1      0     11      6      9      5      2     11      1      8      2  ...   \n",
       "2      4      9      6      6      9     10     11      9      6      0  ...   \n",
       "3      9      6      9      6      2      1      2      7      4      1  ...   \n",
       "4      9      1     10      2      4      3      9      7      6      5  ...   \n",
       "\n",
       "   col_20  col_21  col_22  col_23  col_24  col_25  col_26  col_27  col_28  \\\n",
       "0       8       6       4       5       8       4      11       5       4   \n",
       "1       7       6      10       2       2       0       2       3       2   \n",
       "2      11       2       4       1      11       7       6       8       3   \n",
       "3      10      10       1       6       8       5       3       2       6   \n",
       "4      11       0       1       3       8      10       2       7       4   \n",
       "\n",
       "   col_29  \n",
       "0       2  \n",
       "1       6  \n",
       "2       2  \n",
       "3       5  \n",
       "4       3  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
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    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## You can use the `max_columns` option to show all columns\n",
    "\n",
    "I prefer to use the `option_context` context manager so I can change this option on a case-by-case basis. Note that inside the context manager block, I have to use `display` to show the DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <td>1</td>\n",
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       "      <td>2</td>\n",
       "      <td>4</td>\n",
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       "      <td>7</td>\n",
       "      <td>6</td>\n",
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       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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      ],
      "text/plain": [
       "   col_0  col_1  col_2  col_3  col_4  col_5  col_6  col_7  col_8  col_9  \\\n",
       "0      2      9     11      9      4      0     11      9      4     11   \n",
       "1      0     11      6      9      5      2     11      1      8      2   \n",
       "2      4      9      6      6      9     10     11      9      6      0   \n",
       "3      9      6      9      6      2      1      2      7      4      1   \n",
       "4      9      1     10      2      4      3      9      7      6      5   \n",
       "\n",
       "   col_10  col_11  col_12  col_13  col_14  col_15  col_16  col_17  col_18  \\\n",
       "0       8       4       4       8       6       1       4       0       9   \n",
       "1       3       6       2       7      10      10      11      11       5   \n",
       "2       4       3       3       7       3       6       4       9       4   \n",
       "3      11       3       4      11      11       2      10       0       9   \n",
       "4      10       9       4       6       6       4       1      10       1   \n",
       "\n",
       "   col_19  col_20  col_21  col_22  col_23  col_24  col_25  col_26  col_27  \\\n",
       "0       2       8       6       4       5       8       4      11       5   \n",
       "1       3       7       6      10       2       2       0       2       3   \n",
       "2       9      11       2       4       1      11       7       6       8   \n",
       "3       5      10      10       1       6       8       5       3       2   \n",
       "4       6      11       0       1       3       8      10       2       7   \n",
       "\n",
       "   col_28  col_29  \n",
       "0       4       2  \n",
       "1       2       6  \n",
       "2       3       2  \n",
       "3       6       5  \n",
       "4       4       3  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display\n",
    "\n",
    "with pd.option_context('display.max_columns', None):\n",
    "    display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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