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  {
   "cell_type": "code",
   "execution_count": 295,
   "id": "ddcaf12b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import required libraries\n",
    "import pandas as pd\n",
    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "import sklearn\n",
    "\n",
    "# Import necessary modules\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from math import sqrt\n",
    "\n",
    "# Keras specific\n",
    "import keras\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "id": "70e3b6e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8760"
      ]
     },
     "execution_count": 296,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in_columns = ['id_stacji', 'nazwa_stacji', 'typ_zbioru', 'rok', 'miesiąc']\n",
    "\n",
    "df = pd.read_csv('train/in.tsv', names=in_columns, sep='\\t')\n",
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "id": "44f404d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "720"
      ]
     },
     "execution_count": 297,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test = pd.read_csv('test-A/in.tsv', names=in_columns, sep='\\t')\n",
    "len(df_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "id": "c760402a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9480"
      ]
     },
     "execution_count": 298,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat([df,df_test])\n",
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "id": "06f39e15",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(['nazwa_stacji','typ_zbioru'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "id": "91c047f6",
   "metadata": {},
   "outputs": [
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     },
     "execution_count": 300,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "x = pd.get_dummies(df,columns = ['id_stacji','rok','miesiąc'])\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "id": "037f1315",
   "metadata": {},
   "outputs": [],
   "source": [
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  {
   "cell_type": "code",
   "execution_count": 302,
   "id": "e03bae07",
   "metadata": {},
   "outputs": [
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8755</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8756</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8757</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8758</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8759</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8760 rows × 73 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id_stacji_249180010  id_stacji_249190560  id_stacji_249200370  \\\n",
       "0                       1                    0                    0   \n",
       "1                       1                    0                    0   \n",
       "2                       1                    0                    0   \n",
       "3                       1                    0                    0   \n",
       "4                       1                    0                    0   \n",
       "...                   ...                  ...                  ...   \n",
       "8755                    0                    0                    0   \n",
       "8756                    0                    0                    0   \n",
       "8757                    0                    0                    0   \n",
       "8758                    0                    0                    0   \n",
       "8759                    0                    0                    0   \n",
       "\n",
       "      id_stacji_249200490  id_stacji_249220150  id_stacji_249220180  \\\n",
       "0                       0                    0                    0   \n",
       "1                       0                    0                    0   \n",
       "2                       0                    0                    0   \n",
       "3                       0                    0                    0   \n",
       "4                       0                    0                    0   \n",
       "...                   ...                  ...                  ...   \n",
       "8755                    0                    0                    0   \n",
       "8756                    0                    0                    0   \n",
       "8757                    0                    0                    0   \n",
       "8758                    0                    0                    0   \n",
       "8759                    0                    0                    0   \n",
       "\n",
       "      id_stacji_250190160  id_stacji_250190390  id_stacji_250210130  \\\n",
       "0                       0                    0                    0   \n",
       "1                       0                    0                    0   \n",
       "2                       0                    0                    0   \n",
       "3                       0                    0                    0   \n",
       "4                       0                    0                    0   \n",
       "...                   ...                  ...                  ...   \n",
       "8755                    0                    0                    0   \n",
       "8756                    0                    0                    0   \n",
       "8757                    0                    0                    0   \n",
       "8758                    0                    0                    0   \n",
       "8759                    0                    0                    0   \n",
       "\n",
       "      id_stacji_251170090  ...  miesiąc_3  miesiąc_4  miesiąc_5  miesiąc_6  \\\n",
       "0                       0  ...          0          0          0          0   \n",
       "1                       0  ...          0          0          0          0   \n",
       "2                       0  ...          1          0          0          0   \n",
       "3                       0  ...          0          1          0          0   \n",
       "4                       0  ...          0          0          1          0   \n",
       "...                   ...  ...        ...        ...        ...        ...   \n",
       "8755                    0  ...          0          0          0          0   \n",
       "8756                    0  ...          0          0          0          0   \n",
       "8757                    0  ...          0          0          0          0   \n",
       "8758                    0  ...          0          0          0          0   \n",
       "8759                    0  ...          0          0          0          0   \n",
       "\n",
       "      miesiąc_7  miesiąc_8  miesiąc_9  miesiąc_10  miesiąc_11  miesiąc_12  \n",
       "0             0          0          0           0           0           0  \n",
       "1             0          0          0           0           0           0  \n",
       "2             0          0          0           0           0           0  \n",
       "3             0          0          0           0           0           0  \n",
       "4             0          0          0           0           0           0  \n",
       "...         ...        ...        ...         ...         ...         ...  \n",
       "8755          0          1          0           0           0           0  \n",
       "8756          0          0          1           0           0           0  \n",
       "8757          0          0          0           1           0           0  \n",
       "8758          0          0          0           0           1           0  \n",
       "8759          0          0          0           0           0           1  \n",
       "\n",
       "[8760 rows x 73 columns]"
      ]
     },
     "execution_count": 302,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "id": "ede98181",
   "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>rainfall</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>43.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>72.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>25.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>89.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8755</th>\n",
       "      <td>114.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8756</th>\n",
       "      <td>101.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8757</th>\n",
       "      <td>20.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8758</th>\n",
       "      <td>93.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8759</th>\n",
       "      <td>46.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8760 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      rainfall\n",
       "0         19.4\n",
       "1         43.2\n",
       "2         72.2\n",
       "3         25.3\n",
       "4         89.3\n",
       "...        ...\n",
       "8755     114.9\n",
       "8756     101.2\n",
       "8757      20.4\n",
       "8758      93.2\n",
       "8759      46.9\n",
       "\n",
       "[8760 rows x 1 columns]"
      ]
     },
     "execution_count": 303,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = pd.read_csv('train/expected.tsv', sep='\\t', names=['rainfall'])\n",
    "#y = np.array(y).reshape(1,-1)\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "id": "9a950571",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define model\n",
    "model = Sequential()\n",
    "model.add(Dense(1024, input_dim=73, activation= \"relu\"))\n",
    "model.add(Dense(512, activation= \"relu\"))\n",
    "model.add(Dense(256, activation= \"relu\"))\n",
    "model.add(Dense(128, activation= \"relu\"))\n",
    "model.add(Dense(64, activation= \"relu\"))\n",
    "model.add(Dense(32, activation= \"relu\"))\n",
    "model.add(Dense(16, activation= \"relu\"))\n",
    "model.add(Dense(1))\n",
    "#model.summary() #Print model Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "id": "f68e43f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['id_stacji'] = np.asarray(df['id_stacji']).astype('float32')\n",
    "df['rok'] = np.asarray(df['rok']).astype('float32')\n",
    "df['miesiąc'] = np.asarray(df['miesiąc']).astype('float32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "id": "c1036c04",
   "metadata": {},
   "outputs": [],
   "source": [
    "y = np.asarray(y).astype('float32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "id": "cec44474",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(None, 73) <dtype: 'float32'>\n",
      "(None, 1) <dtype: 'float32'>\n",
      "dense_95 (None, 73) float32\n",
      "dense_96 (None, 1024) float32\n",
      "dense_97 (None, 512) float32\n",
      "dense_98 (None, 256) float32\n",
      "dense_99 (None, 128) float32\n",
      "dense_100 (None, 64) float32\n",
      "dense_101 (None, 32) float32\n",
      "dense_102 (None, 16) float32\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[None, None, None, None, None, None, None, None]"
      ]
     },
     "execution_count": 307,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[print(i.shape, i.dtype) for i in model.inputs]\n",
    "[print(o.shape, o.dtype) for o in model.outputs]\n",
    "[print(l.name, l.input_shape, l.dtype) for l in model.layers]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "id": "eb9cb318",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 1216.5399 - mean_squared_error: 1216.5399\n",
      "Epoch 2/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 794.1711 - mean_squared_error: 794.1711\n",
      "Epoch 3/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 580.7461 - mean_squared_error: 580.7461\n",
      "Epoch 4/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 484.1317 - mean_squared_error: 484.1317\n",
      "Epoch 5/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 441.7448 - mean_squared_error: 441.7448\n",
      "Epoch 6/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 392.2047 - mean_squared_error: 392.2047\n",
      "Epoch 7/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 361.4105 - mean_squared_error: 361.4105\n",
      "Epoch 8/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 312.9633 - mean_squared_error: 312.9633\n",
      "Epoch 9/100\n",
      "274/274 [==============================] - 2s 7ms/step - loss: 275.2529 - mean_squared_error: 275.2529\n",
      "Epoch 10/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 246.7625 - mean_squared_error: 246.7625\n",
      "Epoch 11/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 195.6685 - mean_squared_error: 195.6685\n",
      "Epoch 12/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 168.8491 - mean_squared_error: 168.8491\n",
      "Epoch 13/100\n",
      "274/274 [==============================] - 2s 7ms/step - loss: 150.1201 - mean_squared_error: 150.1201\n",
      "Epoch 14/100\n",
      "274/274 [==============================] - 2s 7ms/step - loss: 122.6171 - mean_squared_error: 122.6171\n",
      "Epoch 15/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 100.8923 - mean_squared_error: 100.8923\n",
      "Epoch 16/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 87.8484 - mean_squared_error: 87.8484\n",
      "Epoch 17/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 77.6876 - mean_squared_error: 77.6876\n",
      "Epoch 18/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 63.2032 - mean_squared_error: 63.2032\n",
      "Epoch 19/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 57.2543 - mean_squared_error: 57.2543\n",
      "Epoch 20/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 45.0924 - mean_squared_error: 45.0924\n",
      "Epoch 21/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 49.1593 - mean_squared_error: 49.1593\n",
      "Epoch 22/100\n",
      "274/274 [==============================] - 2s 7ms/step - loss: 58.2306 - mean_squared_error: 58.2306\n",
      "Epoch 23/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 48.0242 - mean_squared_error: 48.0242\n",
      "Epoch 24/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 38.6356 - mean_squared_error: 38.6356\n",
      "Epoch 25/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 30.9926 - mean_squared_error: 30.9926\n",
      "Epoch 26/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 29.7819 - mean_squared_error: 29.7819\n",
      "Epoch 27/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 32.5139 - mean_squared_error: 32.5139\n",
      "Epoch 28/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 40.1129 - mean_squared_error: 40.1129\n",
      "Epoch 29/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 51.6793 - mean_squared_error: 51.6793\n",
      "Epoch 30/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 37.1284 - mean_squared_error: 37.1284\n",
      "Epoch 31/100\n",
      "274/274 [==============================] - 2s 5ms/step - loss: 30.2074 - mean_squared_error: 30.2074\n",
      "Epoch 32/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 27.1982 - mean_squared_error: 27.1982\n",
      "Epoch 33/100\n",
      "274/274 [==============================] - 2s 7ms/step - loss: 26.5477 - mean_squared_error: 26.5477\n",
      "Epoch 34/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 25.7544 - mean_squared_error: 25.7544\n",
      "Epoch 35/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 24.1754 - mean_squared_error: 24.1754\n",
      "Epoch 36/100\n",
      "274/274 [==============================] - 2s 5ms/step - loss: 27.5213 - mean_squared_error: 27.5213\n",
      "Epoch 37/100\n",
      "274/274 [==============================] - 2s 5ms/step - loss: 30.3435 - mean_squared_error: 30.3435\n",
      "Epoch 38/100\n",
      "274/274 [==============================] - 2s 5ms/step - loss: 32.7374 - mean_squared_error: 32.7374\n",
      "Epoch 39/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 29.2545 - mean_squared_error: 29.2545\n",
      "Epoch 40/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 28.4834 - mean_squared_error: 28.4834\n",
      "Epoch 41/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 22.9177 - mean_squared_error: 22.9177\n",
      "Epoch 42/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 21.6796 - mean_squared_error: 21.6796\n",
      "Epoch 43/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 20.2429 - mean_squared_error: 20.2429\n",
      "Epoch 44/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 21.2112 - mean_squared_error: 21.2112\n",
      "Epoch 45/100\n",
      "274/274 [==============================] - 2s 5ms/step - loss: 25.0341 - mean_squared_error: 25.0341\n",
      "Epoch 46/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 22.3963 - mean_squared_error: 22.3963\n",
      "Epoch 47/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 23.1122 - mean_squared_error: 23.1122\n",
      "Epoch 48/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 28.0343 - mean_squared_error: 28.0343\n",
      "Epoch 49/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 22.2908 - mean_squared_error: 22.2908\n",
      "Epoch 50/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 21.7871 - mean_squared_error: 21.7871\n",
      "Epoch 51/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 19.8841 - mean_squared_error: 19.8841\n",
      "Epoch 52/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 20.5390 - mean_squared_error: 20.5390\n",
      "Epoch 53/100\n",
      "274/274 [==============================] - 2s 5ms/step - loss: 22.3869 - mean_squared_error: 22.3869\n",
      "Epoch 54/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 20.6540 - mean_squared_error: 20.6540\n",
      "Epoch 55/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 18.3056 - mean_squared_error: 18.3056\n",
      "Epoch 56/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 22.7574 - mean_squared_error: 22.7574\n",
      "Epoch 57/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 20.1425 - mean_squared_error: 20.1425\n",
      "Epoch 58/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 17.5521 - mean_squared_error: 17.5521\n",
      "Epoch 59/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 18.2735 - mean_squared_error: 18.2735\n",
      "Epoch 60/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 17.6372 - mean_squared_error: 17.6372\n",
      "Epoch 61/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 15.2790 - mean_squared_error: 15.2790\n",
      "Epoch 62/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 12.9527 - mean_squared_error: 12.9527\n",
      "Epoch 63/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 13.2732 - mean_squared_error: 13.2732\n",
      "Epoch 64/100\n",
      "274/274 [==============================] - 2s 7ms/step - loss: 18.0740 - mean_squared_error: 18.0740\n",
      "Epoch 65/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 23.5823 - mean_squared_error: 23.5823\n",
      "Epoch 66/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 22.4731 - mean_squared_error: 22.4731\n",
      "Epoch 67/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 17.0889 - mean_squared_error: 17.0889\n",
      "Epoch 68/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 13.5507 - mean_squared_error: 13.5507\n",
      "Epoch 69/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 14.6270 - mean_squared_error: 14.6270\n",
      "Epoch 70/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 15.7420 - mean_squared_error: 15.7420\n",
      "Epoch 71/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 15.6920 - mean_squared_error: 15.6920\n",
      "Epoch 72/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 17.8469 - mean_squared_error: 17.8469\n",
      "Epoch 73/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 20.0690 - mean_squared_error: 20.0690\n",
      "Epoch 74/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 16.4538 - mean_squared_error: 16.4538\n",
      "Epoch 75/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 13.7226 - mean_squared_error: 13.7226\n",
      "Epoch 76/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 11.6082 - mean_squared_error: 11.6082\n",
      "Epoch 77/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 11.4206 - mean_squared_error: 11.4206\n",
      "Epoch 78/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 12.9487 - mean_squared_error: 12.9487\n",
      "Epoch 79/100\n",
      "274/274 [==============================] - 2s 7ms/step - loss: 14.9138 - mean_squared_error: 14.9138\n",
      "Epoch 80/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 16.7601 - mean_squared_error: 16.7601\n",
      "Epoch 81/100\n",
      "274/274 [==============================] - 2s 7ms/step - loss: 16.3490 - mean_squared_error: 16.3490\n",
      "Epoch 82/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 12.4280 - mean_squared_error: 12.4280\n",
      "Epoch 83/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 9.2046 - mean_squared_error: 9.2046\n",
      "Epoch 84/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 8.5721 - mean_squared_error: 8.5721\n",
      "Epoch 85/100\n",
      "274/274 [==============================] - 2s 7ms/step - loss: 9.8912 - mean_squared_error: 9.8912\n",
      "Epoch 86/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 10.4523 - mean_squared_error: 10.4523\n",
      "Epoch 87/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 19.6175 - mean_squared_error: 19.6175\n",
      "Epoch 88/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 16.5808 - mean_squared_error: 16.5808\n",
      "Epoch 89/100\n",
      "274/274 [==============================] - 2s 5ms/step - loss: 15.8564 - mean_squared_error: 15.8564\n",
      "Epoch 90/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 12.2800 - mean_squared_error: 12.2800\n",
      "Epoch 91/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 10.0090 - mean_squared_error: 10.0090\n",
      "Epoch 92/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 9.4647 - mean_squared_error: 9.4647\n",
      "Epoch 93/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 10.7999 - mean_squared_error: 10.7999\n",
      "Epoch 94/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 10.2449 - mean_squared_error: 10.2449\n",
      "Epoch 95/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 10.0525 - mean_squared_error: 10.0525\n",
      "Epoch 96/100\n",
      "274/274 [==============================] - 2s 5ms/step - loss: 11.3375 - mean_squared_error: 11.3375\n",
      "Epoch 97/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 11.6955 - mean_squared_error: 11.6955\n",
      "Epoch 98/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 11.2546 - mean_squared_error: 11.2546\n",
      "Epoch 99/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 10.2126 - mean_squared_error: 10.2126\n",
      "Epoch 100/100\n",
      "274/274 [==============================] - 2s 6ms/step - loss: 8.5690 - mean_squared_error: 8.5690\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x20e6929d2e0>"
      ]
     },
     "execution_count": 308,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.compile(loss= \"mean_squared_error\" , optimizer=\"adam\", metrics=[\"mean_squared_error\"])\n",
    "model.fit(x, y, epochs=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "id": "bad4d35a",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_test = pd.read_csv('test-A/in.tsv', sep='\\t', names=in_columns)\n",
    "#y_test = pd.read_csv('test-A/expected.tsv', sep='\\t',names=['rainfall'])\n",
    "#x_test = x_test.drop(['nazwa_stacji', 'typ_zbioru'],axis=1)\n",
    "df_train = pd.read_csv('train/in.tsv', names=in_columns, sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "id": "a3b6fff0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9480"
      ]
     },
     "execution_count": 310,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test = pd.concat([x_test,df_train])\n",
    "len(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "id": "cdf89362",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9480"
      ]
     },
     "execution_count": 311,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test = x_test.drop(['nazwa_stacji', 'typ_zbioru'],axis=1)\n",
    "len(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "id": "fe00b876",
   "metadata": {},
   "outputs": [
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       "<p>9480 rows × 73 columns</p>\n",
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       "8759                    0                    0                    0   \n",
       "\n",
       "      id_stacji_251170090  ...  miesiąc_3  miesiąc_4  miesiąc_5  miesiąc_6  \\\n",
       "0                       0  ...          0          0          0          0   \n",
       "1                       0  ...          0          0          0          0   \n",
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       "3                       0  ...          0          1          0          0   \n",
       "4                       0  ...          0          0          1          0   \n",
       "...                   ...  ...        ...        ...        ...        ...   \n",
       "8755                    0  ...          0          0          0          0   \n",
       "8756                    0  ...          0          0          0          0   \n",
       "8757                    0  ...          0          0          0          0   \n",
       "8758                    0  ...          0          0          0          0   \n",
       "8759                    0  ...          0          0          0          0   \n",
       "\n",
       "      miesiąc_7  miesiąc_8  miesiąc_9  miesiąc_10  miesiąc_11  miesiąc_12  \n",
       "0             0          0          0           0           0           0  \n",
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       "...         ...        ...        ...         ...         ...         ...  \n",
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       "\n",
       "[9480 rows x 73 columns]"
      ]
     },
     "execution_count": 312,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test = pd.get_dummies(x_test,columns = ['id_stacji','rok','miesiąc'])\n",
    "x_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "id": "657a7976",
   "metadata": {},
   "outputs": [
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      ],
      "text/plain": [
       "     id_stacji_249180010  id_stacji_249190560  id_stacji_249200370  \\\n",
       "0                      0                    0                    1   \n",
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       "\n",
       "     id_stacji_249200490  id_stacji_249220150  id_stacji_249220180  \\\n",
       "0                      0                    0                    0   \n",
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       "\n",
       "     id_stacji_250190160  id_stacji_250190390  id_stacji_250210130  \\\n",
       "0                      0                    0                    0   \n",
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       "719                    0                    0                    0   \n",
       "\n",
       "     id_stacji_251170090  ...  miesiąc_3  miesiąc_4  miesiąc_5  miesiąc_6  \\\n",
       "0                      0  ...          0          0          0          0   \n",
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       "\n",
       "     miesiąc_7  miesiąc_8  miesiąc_9  miesiąc_10  miesiąc_11  miesiąc_12  \n",
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       "\n",
       "[720 rows x 73 columns]"
      ]
     },
     "execution_count": 313,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test = x_test.iloc[:-8760]\n",
    "x_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "id": "1163c550",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "23/23 [==============================] - 0s 2ms/step\n"
     ]
    }
   ],
   "source": [
    "pred= model.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "id": "6c24ee76",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "23/23 [==============================] - 0s 2ms/step\n"
     ]
    }
   ],
   "source": [
    "pred= model.predict(x_test)\n",
    "out = pd.DataFrame(pred)\n",
    "out.to_csv('test-A/out.tsv',sep='\\t',header=False, index=False)"
   ]
  }
 ],
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