data/convert_weather.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import pyarrow as pa\n",
    "import numpy as np\n",
    "import json\n",
    "from datetime import date, datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "with_json = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def json_serial(obj):\n",
    "    return int(obj.strftime(\"%s\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>recorddate</th>\n",
       "      <th>station</th>\n",
       "      <th>AWND</th>\n",
       "      <th>PRCP</th>\n",
       "      <th>SNOW</th>\n",
       "      <th>SNWD</th>\n",
       "      <th>TMAX</th>\n",
       "      <th>TMAX_F</th>\n",
       "      <th>TMIN</th>\n",
       "      <th>TMIN_F</th>\n",
       "      <th>...</th>\n",
       "      <th>WT22</th>\n",
       "      <th>elevation</th>\n",
       "      <th>gsn_flag</th>\n",
       "      <th>hcn_crn_flag</th>\n",
       "      <th>id</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>name</th>\n",
       "      <th>state</th>\n",
       "      <th>wmo_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20120101</td>\n",
       "      <td>USS0006H19S</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>356.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>33.98</td>\n",
       "      <td>-15.4</td>\n",
       "      <td>4.28</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2572.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.3300</td>\n",
       "      <td>-106.5000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WY South Brush Creek</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20120101</td>\n",
       "      <td>USC00390043</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>42.08</td>\n",
       "      <td>-2.8</td>\n",
       "      <td>26.96</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>512.1</td>\n",
       "      <td>HCN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.4892</td>\n",
       "      <td>-99.0631</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SD ACADEMY 2NE</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20120101</td>\n",
       "      <td>SWE00138512</td>\n",
       "      <td>NaN</td>\n",
       "      <td>124.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.4500</td>\n",
       "      <td>14.8900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>VADSTENA</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20120101</td>\n",
       "      <td>USC00163807</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.6</td>\n",
       "      <td>78.08</td>\n",
       "      <td>17.2</td>\n",
       "      <td>62.96</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.2414</td>\n",
       "      <td>-89.9914</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LA GRAND ISLE</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20120101</td>\n",
       "      <td>USC00163800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.6</td>\n",
       "      <td>69.08</td>\n",
       "      <td>15.6</td>\n",
       "      <td>60.08</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.8</td>\n",
       "      <td>HCN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.4183</td>\n",
       "      <td>-92.0442</td>\n",
       "      <td>NaN</td>\n",
       "      <td>LA GRAND COTEAU</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   recorddate      station  AWND   PRCP  SNOW   SNWD  TMAX  TMAX_F  TMIN  \\\n",
       "0    20120101  USS0006H19S   NaN    0.0   NaN  356.0   1.1   33.98 -15.4   \n",
       "1    20120101  USC00390043   NaN    0.0   0.0    0.0   5.6   42.08  -2.8   \n",
       "2    20120101  SWE00138512   NaN  124.0   NaN    0.0   NaN     NaN   NaN   \n",
       "3    20120101  USC00163807   NaN    0.0   NaN    NaN  25.6   78.08  17.2   \n",
       "4    20120101  USC00163800   NaN    0.0   NaN    NaN  20.6   69.08  15.6   \n",
       "\n",
       "   TMIN_F   ...    WT22  elevation  gsn_flag  hcn_crn_flag  id  latitude  \\\n",
       "0    4.28   ...     NaN     2572.5       NaN           NaN NaN   41.3300   \n",
       "1   26.96   ...     NaN      512.1       HCN           NaN NaN   43.4892   \n",
       "2     NaN   ...     NaN       90.0       NaN           NaN NaN   58.4500   \n",
       "3   62.96   ...     NaN        0.6       NaN           NaN NaN   29.2414   \n",
       "4   60.08   ...     NaN       16.8       HCN           NaN NaN   30.4183   \n",
       "\n",
       "   longitude  name                 state  wmo_id  \n",
       "0  -106.5000   NaN  WY South Brush Creek     NaN  \n",
       "1   -99.0631   NaN        SD ACADEMY 2NE     NaN  \n",
       "2    14.8900   NaN              VADSTENA     NaN  \n",
       "3   -89.9914   NaN         LA GRAND ISLE     NaN  \n",
       "4   -92.0442   NaN       LA GRAND COTEAU     NaN  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('weather-10m.csv', encoding='utf-8')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['recorddate', 'station', 'AWND', 'PRCP', 'SNOW', 'SNWD', 'TMAX',\n",
       "       'TMAX_F', 'TMIN', 'TMIN_F', 'WT01', 'WT02', 'WT03', 'WT04', 'WT05',\n",
       "       'WT06', 'WT07', 'WT08', 'WT09', 'WT10', 'WT11', 'WT12', 'WT13', 'WT14',\n",
       "       'WT15', 'WT16', 'WT17', 'WT18', 'WT19', 'WT20', 'WT21', 'WT22',\n",
       "       'elevation', 'gsn_flag', 'hcn_crn_flag', 'id', 'latitude', 'longitude',\n",
       "       'name', 'state', 'wmo_id'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.drop([\"SNOW\"], axis=1)\n",
    "renamed = data.rename(index=str, columns={\n",
    "    \"TMAX\": \"TEMP_MAX\", \n",
    "    \"TMIN\": \"TEMP_MIN\",\n",
    "    \"PRCP\": \"PRECIPITATION\",\n",
    "    \"elevation\": \"ELEVATION\", \n",
    "    \"AWND\": \"WIND\", \n",
    "    \"latitude\": \"LATITUDE\", \n",
    "    \"longitude\": \"LONGITUDE\",\n",
    "    \"SNWD\": \"SNOW\"\n",
    "})\n",
    "\n",
    "renamed['RECORD_DATE'] = pd.to_datetime(renamed.recorddate, format='%Y%m%d').dt.date\n",
    "\n",
    "renamed = renamed[[\"RECORD_DATE\", \"TEMP_MAX\", \"TEMP_MIN\", \"PRECIPITATION\", \"ELEVATION\", \"WIND\", \"SNOW\", \"LATITUDE\", \"LONGITUDE\"]]\n",
    "\n",
    "renamed['WIND'].fillna(0, inplace=True)\n",
    "renamed['SNOW'].fillna(0, inplace=True)\n",
    "\n",
    "renamed['WIND'] = renamed['WIND'] / 10\n",
    "# temperature is already corrected in the data\n",
    "# renamed['TEMP_MIN'] = renamed['TEMP_MIN'] / 10\n",
    "# renamed['TEMP_MAX'] = renamed['TEMP_MAX'] / 10\n",
    "renamed['PRECIPITATION'] = renamed['PRECIPITATION'] / 10\n",
    "\n",
    "cleaned = renamed.dropna()\n",
    "\n",
    "right_types = cleaned.astype({\n",
    "    'TEMP_MAX': 'float32',\n",
    "    'TEMP_MIN': 'float32',\n",
    "    'PRECIPITATION': 'float32',\n",
    "    'ELEVATION': 'float32',\n",
    "    'WIND': 'float32',\n",
    "    'SNOW': 'float32',\n",
    "    'LATITUDE': 'float32',\n",
    "    'LONGITUDE': 'float32'\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RECORD_DATE</th>\n",
       "      <th>TEMP_MAX</th>\n",
       "      <th>TEMP_MIN</th>\n",
       "      <th>PRECIPITATION</th>\n",
       "      <th>ELEVATION</th>\n",
       "      <th>WIND</th>\n",
       "      <th>SNOW</th>\n",
       "      <th>LATITUDE</th>\n",
       "      <th>LONGITUDE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>1.1</td>\n",
       "      <td>-15.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2572.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>41.3300</td>\n",
       "      <td>-106.5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>5.6</td>\n",
       "      <td>-2.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>512.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.4892</td>\n",
       "      <td>-99.0631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>25.6</td>\n",
       "      <td>17.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.2414</td>\n",
       "      <td>-89.9914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>20.6</td>\n",
       "      <td>15.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.4183</td>\n",
       "      <td>-92.0442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>-6.6</td>\n",
       "      <td>-17.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>581.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>49.2167</td>\n",
       "      <td>-102.9667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  RECORD_DATE  TEMP_MAX  TEMP_MIN  PRECIPITATION  ELEVATION  WIND   SNOW  \\\n",
       "0  2012-01-01       1.1     -15.4            0.0     2572.5   0.0  356.0   \n",
       "1  2012-01-01       5.6      -2.8            0.0      512.1   0.0    0.0   \n",
       "3  2012-01-01      25.6      17.2            0.0        0.6   0.0    0.0   \n",
       "4  2012-01-01      20.6      15.6            0.0       16.8   0.0    0.0   \n",
       "5  2012-01-01      -6.6     -17.1            0.0      581.0   0.0   90.0   \n",
       "\n",
       "   LATITUDE  LONGITUDE  \n",
       "0   41.3300  -106.5000  \n",
       "1   43.4892   -99.0631  \n",
       "3   29.2414   -89.9914  \n",
       "4   30.4183   -92.0442  \n",
       "5   49.2167  -102.9667  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "weather-10k\n",
      "weather-200k\n",
      "weather-500k\n",
      "weather-1m\n",
      "weather-3m\n",
      "weather-10m\n"
     ]
    }
   ],
   "source": [
    "for size, name in [(10000, 'weather-10k'), (200000, 'weather-200k'), (500000, 'weather-500k'), (1000000, 'weather-1m'), (3000000, 'weather-3m'), (10000000, 'weather-10m')]:\n",
    "    print(name)\n",
    "\n",
    "    smaller = right_types[:size]\n",
    "    \n",
    "    table = pa.Table.from_pandas(smaller)\n",
    "    \n",
    "    if with_json:\n",
    "        d = {}\n",
    "        for column in smaller.columns:\n",
    "            d[column]=list(smaller[column])\n",
    "\n",
    "        with open(f'{name}.json', 'w') as f:\n",
    "            json.dump(d, f, default=json_serial, separators=(',', ':'))\n",
    "\n",
    "    # table = table.column('ARRIVAL').cast(pa.TimestampValue, True)\n",
    "\n",
    "    writer = pa.RecordBatchFileWriter(f'{name}.arrow', table.schema)\n",
    "    writer.write(table)\n",
    "    writer.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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