Lec031.ipynb

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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas import Series, DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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   "source": [
    "# 単純なアレイを用意します。\n",
    "\n",
    "arr1 = np.arange(9).reshape((3, 3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 1, 2],\n",
       "       [3, 4, 5],\n",
       "       [6, 7, 8]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
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    {
     "data": {
      "text/plain": [
       "array([[0, 1, 2, 0, 1, 2],\n",
       "       [3, 4, 5, 3, 4, 5],\n",
       "       [6, 7, 8, 6, 7, 8]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 2つのアレイを列方向（axis=1）に連結します\n",
    "\n",
    "np.concatenate([arr1, arr1], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
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    {
     "data": {
      "text/plain": [
       "array([[0, 1, 2],\n",
       "       [3, 4, 5],\n",
       "       [6, 7, 8],\n",
       "       [0, 1, 2],\n",
       "       [3, 4, 5],\n",
       "       [6, 7, 8]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 行方向（axis=0）に\n",
    "\n",
    "np.concatenate([arr1, arr1], axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
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    {
     "data": {
      "text/plain": [
       "T    0\n",
       "U    1\n",
       "V    2\n",
       "X    3\n",
       "Y    4\n",
       "T    0\n",
       "U    1\n",
       "V    2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pandas.Seriesでやってみます。\n",
    "\n",
    "ser1 = Series([0, 1, 2], index=['T', 'U', 'V'])\n",
    "ser2 = Series([3, 4], index=['X', 'Y'])\n",
    "\n",
    "# concatで、デフォルトは axis=0\n",
    "pd.concat([ser1, ser2, ser1])"
   ]
  },
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   "cell_type": "code",
   "execution_count": 7,
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>T</th>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>U</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>X</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
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       "     0    1\n",
       "T  0.0  NaN\n",
       "U  1.0  NaN\n",
       "V  2.0  NaN\n",
       "X  NaN  3.0\n",
       "Y  NaN  4.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 列方向に連結すると、DataFrameが出来ます。\n",
    "\n",
    "pd.concat([ser1, ser2], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
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    {
     "data": {
      "text/plain": [
       "cat1  T    0\n",
       "      U    1\n",
       "      V    2\n",
       "cat2  X    3\n",
       "      Y    4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 階層的なindexを付けてSeriesを連結することもできます。\n",
    "\n",
    "pd.concat([ser1, ser2], keys=['cat1', 'cat2'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
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       "      <th>U</th>\n",
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       "      <th>V</th>\n",
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       "      <th>X</th>\n",
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       "   cat1  cat2\n",
       "T   0.0   NaN\n",
       "U   1.0   NaN\n",
       "V   2.0   NaN\n",
       "X   NaN   3.0\n",
       "Y   NaN   4.0"
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   "source": [
    "# 列方向に連結すると、列の名前になります。\n",
    "\n",
    "pd.concat([ser1, ser2], axis=1, keys=['cat1', 'cat2'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
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   "source": [
    "# DataFrameでも同じ事ができます。\n",
    "\n",
    "dframe1 = DataFrame(np.random.randn(4, 3),\n",
    "                    columns=['X', 'Y', 'Z'])\n",
    "dframe2 = DataFrame(np.random.randn(3, 3),\n",
    "                    columns=['Y', 'Q', 'X'])"
   ]
  },
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   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
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       "          X         Y         Z\n",
       "0  2.230077  0.565566  0.147030\n",
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       "          Y         Q         X\n",
       "0 -0.883876 -0.804876  1.586765\n",
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    "dframe2"
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       "      <td>2.230077</td>\n",
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       "      <th>1</th>\n",
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       "      <th>2</th>\n",
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       "          X         Y         Z         Q\n",
       "0  2.230077  0.565566  0.147030       NaN\n",
       "1 -0.096306 -1.161655 -0.504702       NaN\n",
       "2 -1.628548  0.123159  0.339923       NaN\n",
       "3  1.916046  0.114036  0.405891       NaN\n",
       "0  1.586765 -0.883876       NaN -0.804876\n",
       "1  0.164667  0.472801       NaN  0.543786\n",
       "2 -0.304232  0.139137       NaN  0.699790"
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     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# DataFrameを連結します。\n",
    "\n",
    "pd.concat([dframe1, dframe2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          X         Y         Z         Q\n",
       "0  2.230077  0.565566  0.147030       NaN\n",
       "1 -0.096306 -1.161655 -0.504702       NaN\n",
       "2 -1.628548  0.123159  0.339923       NaN\n",
       "3  1.916046  0.114036  0.405891       NaN\n",
       "4  1.586765 -0.883876       NaN -0.804876\n",
       "5  0.164667  0.472801       NaN  0.543786\n",
       "6 -0.304232  0.139137       NaN  0.699790"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# もとのindexを無視することもできます。\n",
    "\n",
    "pd.concat([dframe1, dframe2], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# 公式ドキュメントはこちらです。\n",
    "url = 'https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html'"
   ]
  }
 ],
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