{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 1\n",
    "Import NumPy under the alias `np`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 2\n",
    "Import pandas under the alias `pd`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 3\n",
    "Given `df1` and `df2` below, concatenate the two DataFrames."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],\n",
    "               'B': ['B0', 'B1', 'B2', 'B3'],\n",
    "               'C': ['C0', 'C1', 'C2', 'C3'],\n",
    "               'D': ['D0', 'D1', 'D2', 'D3']},\n",
    "              index=[0, 1, 2, 3])\n",
    "\n",
    "\n",
    "df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],\n",
    "                  'B': ['B4', 'B5', 'B6', 'B7'],\n",
    "                  'C': ['C4', 'C5', 'C6', 'C7'],\n",
    "                  'D': ['D4', 'D5', 'D6', 'D7']},\n",
    "                   index=[4, 5, 6, 7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <td>C2</td>\n",
       "      <td>D2</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A3</td>\n",
       "      <td>B3</td>\n",
       "      <td>C3</td>\n",
       "      <td>D3</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A4</td>\n",
       "      <td>B4</td>\n",
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       "      <td>D4</td>\n",
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       "      <td>D6</td>\n",
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       "      <th>7</th>\n",
       "      <td>A7</td>\n",
       "      <td>B7</td>\n",
       "      <td>C7</td>\n",
       "      <td>D7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "    A   B   C   D\n",
       "0  A0  B0  C0  D0\n",
       "1  A1  B1  C1  D1\n",
       "2  A2  B2  C2  D2\n",
       "3  A3  B3  C3  D3\n",
       "4  A4  B4  C4  D4\n",
       "5  A5  B5  C5  D5\n",
       "6  A6  B6  C6  D6\n",
       "7  A7  B7  C7  D7"
      ]
     },
     "execution_count": 4,
     "metadata": {},
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    }
   ],
   "source": [
    "#Solution goes here\n",
    "pd.concat([df1, df2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Problem 4\n",
    "Given `df1` and `df2` below, concatenate the two DataFrames along their columns (instead of along their rows)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <td>A0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>1</th>\n",
       "      <td>A1</td>\n",
       "      <td>B1</td>\n",
       "      <td>C1</td>\n",
       "      <td>D1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A2</td>\n",
       "      <td>B2</td>\n",
       "      <td>C2</td>\n",
       "      <td>D2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A3</td>\n",
       "      <td>B3</td>\n",
       "      <td>C3</td>\n",
       "      <td>D3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>A4</td>\n",
       "      <td>B4</td>\n",
       "      <td>C4</td>\n",
       "      <td>D4</td>\n",
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       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A5</td>\n",
       "      <td>B5</td>\n",
       "      <td>C5</td>\n",
       "      <td>D5</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A6</td>\n",
       "      <td>B6</td>\n",
       "      <td>C6</td>\n",
       "      <td>D6</td>\n",
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       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A7</td>\n",
       "      <td>B7</td>\n",
       "      <td>C7</td>\n",
       "      <td>D7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     A    B    C    D    A    B    C    D\n",
       "0   A0   B0   C0   D0  NaN  NaN  NaN  NaN\n",
       "1   A1   B1   C1   D1  NaN  NaN  NaN  NaN\n",
       "2   A2   B2   C2   D2  NaN  NaN  NaN  NaN\n",
       "3   A3   B3   C3   D3  NaN  NaN  NaN  NaN\n",
       "4  NaN  NaN  NaN  NaN   A4   B4   C4   D4\n",
       "5  NaN  NaN  NaN  NaN   A5   B5   C5   D5\n",
       "6  NaN  NaN  NaN  NaN   A6   B6   C6   D6\n",
       "7  NaN  NaN  NaN  NaN   A7   B7   C7   D7"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Solution goes here\n",
    "pd.concat([df1, df2], axis=1)"
   ]
  }
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