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  {
   "cell_type": "code",
   "execution_count": 1,
   "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": 2,
   "id": "70e3b6e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8760"
      ]
     },
     "execution_count": 2,
     "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": 3,
   "id": "44f404d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "720"
      ]
     },
     "execution_count": 3,
     "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": 4,
   "id": "c760402a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9480"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat([df,df_test])\n",
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "06f39e15",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(['nazwa_stacji','typ_zbioru'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "91c047f6",
   "metadata": {},
   "outputs": [
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       "[9480 rows x 73 columns]"
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     },
     "execution_count": 6,
     "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": 7,
   "id": "037f1315",
   "metadata": {},
   "outputs": [],
   "source": [
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  {
   "cell_type": "code",
   "execution_count": 8,
   "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": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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": 9,
     "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": 10,
   "id": "9a950571",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define model\n",
    "model = Sequential()\n",
    "model.add(Dense(16, input_dim=73, activation= \"relu\"))\n",
    "model.add(Dense(32, 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": 11,
   "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": 12,
   "id": "c1036c04",
   "metadata": {},
   "outputs": [],
   "source": [
    "y = np.asarray(y).astype('float32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cec44474",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(None, 73) <dtype: 'float32'>\n",
      "(None, 1) <dtype: 'float32'>\n",
      "dense (None, 73) float32\n",
      "dense_1 (None, 16) float32\n",
      "dense_2 (None, 32) float32\n",
      "dense_3 (None, 64) float32\n",
      "dense_4 (None, 32) float32\n",
      "dense_5 (None, 16) float32\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[None, None, None, None, None, None]"
      ]
     },
     "execution_count": 13,
     "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": 14,
   "id": "eb9cb318",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "274/274 [==============================] - 1s 1ms/step - loss: 1904.0205 - mean_squared_error: 1904.0205\n",
      "Epoch 2/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 977.0018 - mean_squared_error: 977.0018\n",
      "Epoch 3/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 930.0125 - mean_squared_error: 930.0125\n",
      "Epoch 4/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 902.6553 - mean_squared_error: 902.6553\n",
      "Epoch 5/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 863.2485 - mean_squared_error: 863.2485\n",
      "Epoch 6/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 811.9504 - mean_squared_error: 811.9504\n",
      "Epoch 7/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 770.9260 - mean_squared_error: 770.9260\n",
      "Epoch 8/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 724.6091 - mean_squared_error: 724.6091\n",
      "Epoch 9/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 692.6209 - mean_squared_error: 692.6209\n",
      "Epoch 10/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 659.7095 - mean_squared_error: 659.7095\n",
      "Epoch 11/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 625.7371 - mean_squared_error: 625.7371\n",
      "Epoch 12/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 602.4116 - mean_squared_error: 602.4116\n",
      "Epoch 13/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 577.0346 - mean_squared_error: 577.0346\n",
      "Epoch 14/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 552.9323 - mean_squared_error: 552.9323\n",
      "Epoch 15/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 529.7372 - mean_squared_error: 529.7372\n",
      "Epoch 16/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 515.2844 - mean_squared_error: 515.2844\n",
      "Epoch 17/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 501.1700 - mean_squared_error: 501.1700\n",
      "Epoch 18/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 489.9219 - mean_squared_error: 489.9219\n",
      "Epoch 19/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 484.0696 - mean_squared_error: 484.0696\n",
      "Epoch 20/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 470.3400 - mean_squared_error: 470.3400\n",
      "Epoch 21/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 459.1194 - mean_squared_error: 459.1194\n",
      "Epoch 22/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 455.5881 - mean_squared_error: 455.5881\n",
      "Epoch 23/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 446.4247 - mean_squared_error: 446.4247\n",
      "Epoch 24/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 440.6260 - mean_squared_error: 440.6260\n",
      "Epoch 25/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 434.9443 - mean_squared_error: 434.9443\n",
      "Epoch 26/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 429.9223 - mean_squared_error: 429.9223\n",
      "Epoch 27/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 424.0781 - mean_squared_error: 424.0781\n",
      "Epoch 28/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 420.9750 - mean_squared_error: 420.9750\n",
      "Epoch 29/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 416.1357 - mean_squared_error: 416.1357\n",
      "Epoch 30/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 409.1339 - mean_squared_error: 409.1339\n",
      "Epoch 31/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 404.7644 - mean_squared_error: 404.7644\n",
      "Epoch 32/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 403.4354 - mean_squared_error: 403.4354\n",
      "Epoch 33/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 398.6223 - mean_squared_error: 398.6223\n",
      "Epoch 34/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 391.9509 - mean_squared_error: 391.9509\n",
      "Epoch 35/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 391.3186 - mean_squared_error: 391.3186\n",
      "Epoch 36/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 388.1175 - mean_squared_error: 388.1175\n",
      "Epoch 37/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 385.9730 - mean_squared_error: 385.9730\n",
      "Epoch 38/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 382.0468 - mean_squared_error: 382.0468\n",
      "Epoch 39/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 376.9197 - mean_squared_error: 376.9197\n",
      "Epoch 40/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 378.0434 - mean_squared_error: 378.0434\n",
      "Epoch 41/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 372.7451 - mean_squared_error: 372.7451\n",
      "Epoch 42/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 368.2292 - mean_squared_error: 368.2292\n",
      "Epoch 43/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 369.8233 - mean_squared_error: 369.8233\n",
      "Epoch 44/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 365.3695 - mean_squared_error: 365.3695\n",
      "Epoch 45/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 363.1947 - mean_squared_error: 363.1947\n",
      "Epoch 46/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 358.6509 - mean_squared_error: 358.6509\n",
      "Epoch 47/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 363.4928 - mean_squared_error: 363.4928\n",
      "Epoch 48/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 359.9735 - mean_squared_error: 359.9735\n",
      "Epoch 49/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 353.2738 - mean_squared_error: 353.2738\n",
      "Epoch 50/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 350.3524 - mean_squared_error: 350.3524\n",
      "Epoch 51/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 349.1338 - mean_squared_error: 349.1338\n",
      "Epoch 52/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 351.0474 - mean_squared_error: 351.0474\n",
      "Epoch 53/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 341.8802 - mean_squared_error: 341.8802\n",
      "Epoch 54/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 341.5201 - mean_squared_error: 341.5201\n",
      "Epoch 55/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 339.8927 - mean_squared_error: 339.8927\n",
      "Epoch 56/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 337.5977 - mean_squared_error: 337.5977\n",
      "Epoch 57/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 341.8250 - mean_squared_error: 341.8250\n",
      "Epoch 58/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 334.7910 - mean_squared_error: 334.7910\n",
      "Epoch 59/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 333.3398 - mean_squared_error: 333.3398\n",
      "Epoch 60/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 330.1293 - mean_squared_error: 330.1293\n",
      "Epoch 61/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 331.5085 - mean_squared_error: 331.5085\n",
      "Epoch 62/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 327.4076 - mean_squared_error: 327.4076\n",
      "Epoch 63/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 328.1978 - mean_squared_error: 328.1978\n",
      "Epoch 64/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 322.5495 - mean_squared_error: 322.5495\n",
      "Epoch 65/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 324.4060 - mean_squared_error: 324.4060\n",
      "Epoch 66/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 319.2129 - mean_squared_error: 319.2129\n",
      "Epoch 67/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 320.8315 - mean_squared_error: 320.8315\n",
      "Epoch 68/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 315.9987 - mean_squared_error: 315.9987\n",
      "Epoch 69/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 314.6494 - mean_squared_error: 314.6494\n",
      "Epoch 70/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 310.7572 - mean_squared_error: 310.7572\n",
      "Epoch 71/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 310.8293 - mean_squared_error: 310.8293\n",
      "Epoch 72/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 310.2863 - mean_squared_error: 310.2863\n",
      "Epoch 73/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 309.2907 - mean_squared_error: 309.2907\n",
      "Epoch 74/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 306.9155 - mean_squared_error: 306.9155\n",
      "Epoch 75/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 304.8138 - mean_squared_error: 304.8138\n",
      "Epoch 76/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 303.4693 - mean_squared_error: 303.4693\n",
      "Epoch 77/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 302.1253 - mean_squared_error: 302.1253\n",
      "Epoch 78/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 300.5882 - mean_squared_error: 300.5882\n",
      "Epoch 79/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 300.8849 - mean_squared_error: 300.8849\n",
      "Epoch 80/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 297.9424 - mean_squared_error: 297.9424\n",
      "Epoch 81/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 296.6845 - mean_squared_error: 296.6845\n",
      "Epoch 82/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 301.2429 - mean_squared_error: 301.2429\n",
      "Epoch 83/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 294.7325 - mean_squared_error: 294.7325\n",
      "Epoch 84/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 293.9087 - mean_squared_error: 293.9087\n",
      "Epoch 85/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 294.8573 - mean_squared_error: 294.8573\n",
      "Epoch 86/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 291.5350 - mean_squared_error: 291.5350\n",
      "Epoch 87/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 288.5298 - mean_squared_error: 288.5298\n",
      "Epoch 88/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 290.0951 - mean_squared_error: 290.0951\n",
      "Epoch 89/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 286.3828 - mean_squared_error: 286.3828\n",
      "Epoch 90/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 282.4638 - mean_squared_error: 282.4638\n",
      "Epoch 91/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 290.5275 - mean_squared_error: 290.5275\n",
      "Epoch 92/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 282.0305 - mean_squared_error: 282.0305\n",
      "Epoch 93/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 281.5406 - mean_squared_error: 281.5406\n",
      "Epoch 94/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 287.6223 - mean_squared_error: 287.6223\n",
      "Epoch 95/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 277.7972 - mean_squared_error: 277.7972\n",
      "Epoch 96/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 279.9403 - mean_squared_error: 279.9403\n",
      "Epoch 97/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 275.0088 - mean_squared_error: 275.0088\n",
      "Epoch 98/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 276.8479 - mean_squared_error: 276.8479\n",
      "Epoch 99/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 275.8300 - mean_squared_error: 275.8300\n",
      "Epoch 100/100\n",
      "274/274 [==============================] - 0s 1ms/step - loss: 274.4589 - mean_squared_error: 274.4589\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x2ae269e2610>"
      ]
     },
     "execution_count": 14,
     "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": 15,
   "id": "b01ccebe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17.28555466278129"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import math\n",
    "math.sqrt(298.7904)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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('dev-0/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": 17,
   "id": "a3b6fff0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9480"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test = pd.concat([x_test,df_train])\n",
    "len(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "cdf89362",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9480"
      ]
     },
     "execution_count": 18,
     "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": 19,
   "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",
       "2                       0  ...          1          0          0          0   \n",
       "3                       0  ...          0          1          0          0   \n",
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       "...                   ...  ...        ...        ...        ...        ...   \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": 19,
     "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": 20,
   "id": "657a7976",
   "metadata": {},
   "outputs": [
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       "<p>720 rows × 73 columns</p>\n",
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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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       "..                   ...                  ...                  ...   \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": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test = x_test.iloc[:-8760]\n",
    "x_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1163c550",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "23/23 [==============================] - 0s 909us/step\n"
     ]
    }
   ],
   "source": [
    "pred= model.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6c24ee76",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "23/23 [==============================] - 0s 955us/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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