{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:02.483662Z",
"start_time": "2018-11-09T03:43:01.541578Z"
}
},
"outputs": [],
"source": [
"import pandas as pd, pathlib\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:02.488698Z",
"start_time": "2018-11-09T03:43:02.485657Z"
}
},
"outputs": [],
"source": [
"data_path = pathlib.Path('../testdata/bmkg/data_jawa_barat_1980_2018.xlsx')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:10.381205Z",
"start_time": "2018-11-09T03:43:02.490655Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Nama Stasiun | \n",
" WMO ID | \n",
" Tanggal | \n",
" Suhu Minimum (°C) | \n",
" Suhu Maksimum (°C) | \n",
" Suhu Rata-rata (°C) | \n",
" Kelembaban Rata-rata (%) | \n",
" Curah Hujan (mm) | \n",
" Lama Penyinaran (jam) | \n",
" Kecepatan Angin Rata-rata (knot) | \n",
" Arah Angin Terbanyak (deg) | \n",
" Kecepatan Angin Terbesar (knot) | \n",
" Arah Angin Saat Kecepatan Maksimum (deg) | \n",
" Unnamed: 13 | \n",
" Keterangan | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" Stasiun Meteorologi Jatiwangi | \n",
" 96791 | \n",
" 01/01/1980 | \n",
" 22.6 | \n",
" 32.2 | \n",
" 25.8 | \n",
" 90 | \n",
" 13.9 | \n",
" 3.4 | \n",
" 3 | \n",
" NW | \n",
" 5 | \n",
" 315 | \n",
" NaN | \n",
" * 8888 : Data Tidak Terukur | \n",
"
\n",
" \n",
" 1 | \n",
" Stasiun Geofisika Bandung | \n",
" 96783 | \n",
" 01/01/1980 | \n",
" 20.0 | \n",
" 26.0 | \n",
" 23.0 | \n",
" 80 | \n",
" 1.0 | \n",
" 4.5 | \n",
" 2 | \n",
" W | \n",
" 4 | \n",
" 270 | \n",
" NaN | \n",
" * 9999 : Tidak Ada Data | \n",
"
\n",
" \n",
" 2 | \n",
" Stasiun Meteorologi Jatiwangi | \n",
" 96791 | \n",
" 02/01/1980 | \n",
" 21.0 | \n",
" 30.2 | \n",
" 25.7 | \n",
" 88 | \n",
" 9.4 | \n",
" 1.5 | \n",
" 4 | \n",
" NW | \n",
" 5 | \n",
" 315 | \n",
" NaN | \n",
" NaN | \n",
"
\n",
" \n",
" 3 | \n",
" Stasiun Geofisika Bandung | \n",
" 96783 | \n",
" 02/01/1980 | \n",
" 18.8 | \n",
" 27.3 | \n",
" 22.8 | \n",
" 80 | \n",
" 8888.0 | \n",
" 2.2 | \n",
" 2 | \n",
" W | \n",
" 4 | \n",
" 270 | \n",
" NaN | \n",
" NaN | \n",
"
\n",
" \n",
" 4 | \n",
" Stasiun Meteorologi Jatiwangi | \n",
" 96791 | \n",
" 03/01/1980 | \n",
" 21.6 | \n",
" 31.2 | \n",
" 26.6 | \n",
" 85 | \n",
" 0.0 | \n",
" 3.8 | \n",
" 4 | \n",
" W | \n",
" 5 | \n",
" 270 | \n",
" NaN | \n",
" NaN | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Nama Stasiun WMO ID Tanggal Suhu Minimum (°C) \\\n",
"0 Stasiun Meteorologi Jatiwangi 96791 01/01/1980 22.6 \n",
"1 Stasiun Geofisika Bandung 96783 01/01/1980 20.0 \n",
"2 Stasiun Meteorologi Jatiwangi 96791 02/01/1980 21.0 \n",
"3 Stasiun Geofisika Bandung 96783 02/01/1980 18.8 \n",
"4 Stasiun Meteorologi Jatiwangi 96791 03/01/1980 21.6 \n",
"\n",
" Suhu Maksimum (°C) Suhu Rata-rata (°C) Kelembaban Rata-rata (%) \\\n",
"0 32.2 25.8 90 \n",
"1 26.0 23.0 80 \n",
"2 30.2 25.7 88 \n",
"3 27.3 22.8 80 \n",
"4 31.2 26.6 85 \n",
"\n",
" Curah Hujan (mm) Lama Penyinaran (jam) Kecepatan Angin Rata-rata (knot) \\\n",
"0 13.9 3.4 3 \n",
"1 1.0 4.5 2 \n",
"2 9.4 1.5 4 \n",
"3 8888.0 2.2 2 \n",
"4 0.0 3.8 4 \n",
"\n",
" Arah Angin Terbanyak (deg) Kecepatan Angin Terbesar (knot) \\\n",
"0 NW 5 \n",
"1 W 4 \n",
"2 NW 5 \n",
"3 W 4 \n",
"4 W 5 \n",
"\n",
" Arah Angin Saat Kecepatan Maksimum (deg) Unnamed: 13 \\\n",
"0 315 NaN \n",
"1 270 NaN \n",
"2 315 NaN \n",
"3 270 NaN \n",
"4 270 NaN \n",
"\n",
" Keterangan \n",
"0 * 8888 : Data Tidak Terukur \n",
"1 * 9999 : Tidak Ada Data \n",
"2 NaN \n",
"3 NaN \n",
"4 NaN "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_data_jabar = pd.read_excel(data_path, skiprows=6)\n",
"raw_data_jabar.head()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:10.414185Z",
"start_time": "2018-11-09T03:43:10.384206Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Nama Stasiun | \n",
" WMO ID | \n",
" Tanggal | \n",
" Suhu Minimum (°C) | \n",
" Suhu Maksimum (°C) | \n",
" Suhu Rata-rata (°C) | \n",
" Kelembaban Rata-rata (%) | \n",
" Curah Hujan (mm) | \n",
" Lama Penyinaran (jam) | \n",
" Kecepatan Angin Rata-rata (knot) | \n",
" Arah Angin Terbanyak (deg) | \n",
" Kecepatan Angin Terbesar (knot) | \n",
" Arah Angin Saat Kecepatan Maksimum (deg) | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" Stasiun Meteorologi Jatiwangi | \n",
" 96791 | \n",
" 01/01/1980 | \n",
" 22.6 | \n",
" 32.2 | \n",
" 25.8 | \n",
" 90 | \n",
" 13.9 | \n",
" 3.4 | \n",
" 3 | \n",
" NW | \n",
" 5 | \n",
" 315 | \n",
"
\n",
" \n",
" 1 | \n",
" Stasiun Geofisika Bandung | \n",
" 96783 | \n",
" 01/01/1980 | \n",
" 20.0 | \n",
" 26.0 | \n",
" 23.0 | \n",
" 80 | \n",
" 1.0 | \n",
" 4.5 | \n",
" 2 | \n",
" W | \n",
" 4 | \n",
" 270 | \n",
"
\n",
" \n",
" 2 | \n",
" Stasiun Meteorologi Jatiwangi | \n",
" 96791 | \n",
" 02/01/1980 | \n",
" 21.0 | \n",
" 30.2 | \n",
" 25.7 | \n",
" 88 | \n",
" 9.4 | \n",
" 1.5 | \n",
" 4 | \n",
" NW | \n",
" 5 | \n",
" 315 | \n",
"
\n",
" \n",
" 3 | \n",
" Stasiun Geofisika Bandung | \n",
" 96783 | \n",
" 02/01/1980 | \n",
" 18.8 | \n",
" 27.3 | \n",
" 22.8 | \n",
" 80 | \n",
" 8888.0 | \n",
" 2.2 | \n",
" 2 | \n",
" W | \n",
" 4 | \n",
" 270 | \n",
"
\n",
" \n",
" 4 | \n",
" Stasiun Meteorologi Jatiwangi | \n",
" 96791 | \n",
" 03/01/1980 | \n",
" 21.6 | \n",
" 31.2 | \n",
" 26.6 | \n",
" 85 | \n",
" 0.0 | \n",
" 3.8 | \n",
" 4 | \n",
" W | \n",
" 5 | \n",
" 270 | \n",
"
\n",
" \n",
" 5 | \n",
" Stasiun Geofisika Bandung | \n",
" 96783 | \n",
" 03/01/1980 | \n",
" 19.1 | \n",
" 27.7 | \n",
" 22.7 | \n",
" 80 | \n",
" 8888.0 | \n",
" 3.0 | \n",
" 2 | \n",
" W | \n",
" 4 | \n",
" 270 | \n",
"
\n",
" \n",
" 6 | \n",
" Stasiun Meteorologi Jatiwangi | \n",
" 96791 | \n",
" 04/01/1980 | \n",
" 22.5 | \n",
" 30.6 | \n",
" 26.6 | \n",
" 84 | \n",
" 0.0 | \n",
" 0.7 | \n",
" 3 | \n",
" NW | \n",
" 5 | \n",
" 315 | \n",
"
\n",
" \n",
" 7 | \n",
" Stasiun Geofisika Bandung | \n",
" 96783 | \n",
" 04/01/1980 | \n",
" 19.9 | \n",
" 26.9 | \n",
" 23.3 | \n",
" 82 | \n",
" 1.0 | \n",
" 3.1 | \n",
" 2 | \n",
" W | \n",
" 5 | \n",
" 270 | \n",
"
\n",
" \n",
" 8 | \n",
" Stasiun Meteorologi Jatiwangi | \n",
" 96791 | \n",
" 05/01/1980 | \n",
" 23.1 | \n",
" 32.0 | \n",
" 26.9 | \n",
" 9999 | \n",
" 0.0 | \n",
" 4.3 | \n",
" 2 | \n",
" NW | \n",
" 2 | \n",
" 315 | \n",
"
\n",
" \n",
" 9 | \n",
" Stasiun Geofisika Bandung | \n",
" 96783 | \n",
" 05/01/1980 | \n",
" 20.6 | \n",
" 28.8 | \n",
" 23.8 | \n",
" 80 | \n",
" 8888.0 | \n",
" 6.4 | \n",
" 2 | \n",
" W | \n",
" 4 | \n",
" 270 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Nama Stasiun WMO ID Tanggal Suhu Minimum (°C) \\\n",
"0 Stasiun Meteorologi Jatiwangi 96791 01/01/1980 22.6 \n",
"1 Stasiun Geofisika Bandung 96783 01/01/1980 20.0 \n",
"2 Stasiun Meteorologi Jatiwangi 96791 02/01/1980 21.0 \n",
"3 Stasiun Geofisika Bandung 96783 02/01/1980 18.8 \n",
"4 Stasiun Meteorologi Jatiwangi 96791 03/01/1980 21.6 \n",
"5 Stasiun Geofisika Bandung 96783 03/01/1980 19.1 \n",
"6 Stasiun Meteorologi Jatiwangi 96791 04/01/1980 22.5 \n",
"7 Stasiun Geofisika Bandung 96783 04/01/1980 19.9 \n",
"8 Stasiun Meteorologi Jatiwangi 96791 05/01/1980 23.1 \n",
"9 Stasiun Geofisika Bandung 96783 05/01/1980 20.6 \n",
"\n",
" Suhu Maksimum (°C) Suhu Rata-rata (°C) Kelembaban Rata-rata (%) \\\n",
"0 32.2 25.8 90 \n",
"1 26.0 23.0 80 \n",
"2 30.2 25.7 88 \n",
"3 27.3 22.8 80 \n",
"4 31.2 26.6 85 \n",
"5 27.7 22.7 80 \n",
"6 30.6 26.6 84 \n",
"7 26.9 23.3 82 \n",
"8 32.0 26.9 9999 \n",
"9 28.8 23.8 80 \n",
"\n",
" Curah Hujan (mm) Lama Penyinaran (jam) Kecepatan Angin Rata-rata (knot) \\\n",
"0 13.9 3.4 3 \n",
"1 1.0 4.5 2 \n",
"2 9.4 1.5 4 \n",
"3 8888.0 2.2 2 \n",
"4 0.0 3.8 4 \n",
"5 8888.0 3.0 2 \n",
"6 0.0 0.7 3 \n",
"7 1.0 3.1 2 \n",
"8 0.0 4.3 2 \n",
"9 8888.0 6.4 2 \n",
"\n",
" Arah Angin Terbanyak (deg) Kecepatan Angin Terbesar (knot) \\\n",
"0 NW 5 \n",
"1 W 4 \n",
"2 NW 5 \n",
"3 W 4 \n",
"4 W 5 \n",
"5 W 4 \n",
"6 NW 5 \n",
"7 W 5 \n",
"8 NW 2 \n",
"9 W 4 \n",
"\n",
" Arah Angin Saat Kecepatan Maksimum (deg) \n",
"0 315 \n",
"1 270 \n",
"2 315 \n",
"3 270 \n",
"4 270 \n",
"5 270 \n",
"6 315 \n",
"7 270 \n",
"8 315 \n",
"9 270 "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_jabar = raw_data_jabar.iloc[:,:-2]\n",
"data_jabar.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:10.517127Z",
"start_time": "2018-11-09T03:43:10.415184Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"RangeIndex: 52376 entries, 0 to 52375\n",
"Data columns (total 13 columns):\n",
"Nama Stasiun 52376 non-null object\n",
"WMO ID 52376 non-null int64\n",
"Tanggal 52376 non-null object\n",
"Suhu Minimum (°C) 52376 non-null float64\n",
"Suhu Maksimum (°C) 52376 non-null float64\n",
"Suhu Rata-rata (°C) 52376 non-null float64\n",
"Kelembaban Rata-rata (%) 52376 non-null int64\n",
"Curah Hujan (mm) 52376 non-null float64\n",
"Lama Penyinaran (jam) 52376 non-null float64\n",
"Kecepatan Angin Rata-rata (knot) 52376 non-null int64\n",
"Arah Angin Terbanyak (deg) 52376 non-null object\n",
"Kecepatan Angin Terbesar (knot) 52376 non-null int64\n",
"Arah Angin Saat Kecepatan Maksimum (deg) 52376 non-null int64\n",
"dtypes: float64(5), int64(5), object(3)\n",
"memory usage: 5.2+ MB\n"
]
}
],
"source": [
"data_jabar.info()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Ubah nama kolom, untuk lebih mudah digunakan"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:10.587087Z",
"start_time": "2018-11-09T03:43:10.519127Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"['Nama Stasiun ',\n",
" 'WMO ID',\n",
" 'Tanggal',\n",
" 'Suhu Minimum (°C)',\n",
" 'Suhu Maksimum (°C)',\n",
" 'Suhu Rata-rata (°C)',\n",
" 'Kelembaban Rata-rata (%)',\n",
" 'Curah Hujan (mm)',\n",
" 'Lama Penyinaran (jam)',\n",
" 'Kecepatan Angin Rata-rata (knot)',\n",
" 'Arah Angin Terbanyak (deg)',\n",
" 'Kecepatan Angin Terbesar (knot)',\n",
" 'Arah Angin Saat Kecepatan Maksimum (deg)']"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nama_kolom_asli = data_jabar.columns.tolist()\n",
"nama_kolom_asli"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:10.756982Z",
"start_time": "2018-11-09T03:43:10.593081Z"
}
},
"outputs": [],
"source": [
"nama_baru = [\n",
" 'name_stat', 'id_stat', 'date', 'suhu_min', 'suhu_max', 'suhu_mean',\n",
" 'lembab_mean', 'curah_hujan', 'lama_sinar', 'cepat_angin_mean',\n",
" 'arah_angin_mode', 'cepat_angin_max', 'arah_cepat_angin_max'\n",
"]\n",
"\n",
"# Simpan informasi satuan\n",
"satuan_kolom = dict(suhu_min='Celcius', suhu_max='Celcius', suhu_mean='Celcius',\n",
" lembab_mean='%', curah_hujan='mm', lama_sinar='jam', cepat_angin_mean='knot',\n",
" arah_angin_mode='deg', cepat_angin_max='knot', arah_cepat_angin_max='deg')"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:10.997303Z",
"start_time": "2018-11-09T03:43:10.763305Z"
}
},
"outputs": [],
"source": [
"data_jabar.columns = nama_baru"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:11.103239Z",
"start_time": "2018-11-09T03:43:11.004297Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" name_stat | \n",
" id_stat | \n",
" date | \n",
" suhu_min | \n",
" suhu_max | \n",
" suhu_mean | \n",
" lembab_mean | \n",
" curah_hujan | \n",
" lama_sinar | \n",
" cepat_angin_mean | \n",
" arah_angin_mode | \n",
" cepat_angin_max | \n",
" arah_cepat_angin_max | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" Stasiun Meteorologi Jatiwangi | \n",
" 96791 | \n",
" 01/01/1980 | \n",
" 22.6 | \n",
" 32.2 | \n",
" 25.8 | \n",
" 90 | \n",
" 13.9 | \n",
" 3.4 | \n",
" 3 | \n",
" NW | \n",
" 5 | \n",
" 315 | \n",
"
\n",
" \n",
" 1 | \n",
" Stasiun Geofisika Bandung | \n",
" 96783 | \n",
" 01/01/1980 | \n",
" 20.0 | \n",
" 26.0 | \n",
" 23.0 | \n",
" 80 | \n",
" 1.0 | \n",
" 4.5 | \n",
" 2 | \n",
" W | \n",
" 4 | \n",
" 270 | \n",
"
\n",
" \n",
" 2 | \n",
" Stasiun Meteorologi Jatiwangi | \n",
" 96791 | \n",
" 02/01/1980 | \n",
" 21.0 | \n",
" 30.2 | \n",
" 25.7 | \n",
" 88 | \n",
" 9.4 | \n",
" 1.5 | \n",
" 4 | \n",
" NW | \n",
" 5 | \n",
" 315 | \n",
"
\n",
" \n",
" 3 | \n",
" Stasiun Geofisika Bandung | \n",
" 96783 | \n",
" 02/01/1980 | \n",
" 18.8 | \n",
" 27.3 | \n",
" 22.8 | \n",
" 80 | \n",
" 8888.0 | \n",
" 2.2 | \n",
" 2 | \n",
" W | \n",
" 4 | \n",
" 270 | \n",
"
\n",
" \n",
" 4 | \n",
" Stasiun Meteorologi Jatiwangi | \n",
" 96791 | \n",
" 03/01/1980 | \n",
" 21.6 | \n",
" 31.2 | \n",
" 26.6 | \n",
" 85 | \n",
" 0.0 | \n",
" 3.8 | \n",
" 4 | \n",
" W | \n",
" 5 | \n",
" 270 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" name_stat id_stat date suhu_min suhu_max \\\n",
"0 Stasiun Meteorologi Jatiwangi 96791 01/01/1980 22.6 32.2 \n",
"1 Stasiun Geofisika Bandung 96783 01/01/1980 20.0 26.0 \n",
"2 Stasiun Meteorologi Jatiwangi 96791 02/01/1980 21.0 30.2 \n",
"3 Stasiun Geofisika Bandung 96783 02/01/1980 18.8 27.3 \n",
"4 Stasiun Meteorologi Jatiwangi 96791 03/01/1980 21.6 31.2 \n",
"\n",
" suhu_mean lembab_mean curah_hujan lama_sinar cepat_angin_mean \\\n",
"0 25.8 90 13.9 3.4 3 \n",
"1 23.0 80 1.0 4.5 2 \n",
"2 25.7 88 9.4 1.5 4 \n",
"3 22.8 80 8888.0 2.2 2 \n",
"4 26.6 85 0.0 3.8 4 \n",
"\n",
" arah_angin_mode cepat_angin_max arah_cepat_angin_max \n",
"0 NW 5 315 \n",
"1 W 4 270 \n",
"2 NW 5 315 \n",
"3 W 4 270 \n",
"4 W 5 270 "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_jabar.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Ubah tipe data"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:11.266192Z",
"start_time": "2018-11-09T03:43:11.107237Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"RangeIndex: 52376 entries, 0 to 52375\n",
"Data columns (total 13 columns):\n",
"name_stat 52376 non-null object\n",
"id_stat 52376 non-null int64\n",
"date 52376 non-null object\n",
"suhu_min 52376 non-null float64\n",
"suhu_max 52376 non-null float64\n",
"suhu_mean 52376 non-null float64\n",
"lembab_mean 52376 non-null int64\n",
"curah_hujan 52376 non-null float64\n",
"lama_sinar 52376 non-null float64\n",
"cepat_angin_mean 52376 non-null int64\n",
"arah_angin_mode 52376 non-null object\n",
"cepat_angin_max 52376 non-null int64\n",
"arah_cepat_angin_max 52376 non-null int64\n",
"dtypes: float64(5), int64(5), object(3)\n",
"memory usage: 5.2+ MB\n"
]
}
],
"source": [
"data_jabar.info()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"`id_stat` diubah menjadi `object`; `date` jadi `TimeStamp`;"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:11.640082Z",
"start_time": "2018-11-09T03:43:11.267191Z"
}
},
"outputs": [],
"source": [
"data_jabar.id_stat = data_jabar.id_stat.apply(str)\n",
"data_jabar.date = pd.to_datetime(data_jabar.date, format='%d/%m/%Y')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Ambil data Per stasiun"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:11.807994Z",
"start_time": "2018-11-09T03:43:11.642080Z"
}
},
"outputs": [],
"source": [
"# cek jumlah stasiun\n",
"data_jabar = data_jabar.sort_values(['id_stat','date']).reset_index(drop=True)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:11.825979Z",
"start_time": "2018-11-09T03:43:11.808989Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" name_stat | \n",
" id_stat | \n",
" date | \n",
" suhu_min | \n",
" suhu_max | \n",
" suhu_mean | \n",
" lembab_mean | \n",
" curah_hujan | \n",
" lama_sinar | \n",
" cepat_angin_mean | \n",
" arah_angin_mode | \n",
" cepat_angin_max | \n",
" arah_cepat_angin_max | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" Stasiun Meteorologi Citeko | \n",
" 96751 | \n",
" 1985-01-01 | \n",
" 18.1 | \n",
" 24.7 | \n",
" 20.3 | \n",
" 90 | \n",
" 9.0 | \n",
" 9999.0 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
"
\n",
" \n",
" 1 | \n",
" Stasiun Meteorologi Citeko | \n",
" 96751 | \n",
" 1985-01-02 | \n",
" 18.0 | \n",
" 24.1 | \n",
" 20.7 | \n",
" 88 | \n",
" 11.0 | \n",
" 9999.0 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
"
\n",
" \n",
" 2 | \n",
" Stasiun Meteorologi Citeko | \n",
" 96751 | \n",
" 1985-01-03 | \n",
" 17.6 | \n",
" 25.5 | \n",
" 21.0 | \n",
" 86 | \n",
" 7.0 | \n",
" 9999.0 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
"
\n",
" \n",
" 3 | \n",
" Stasiun Meteorologi Citeko | \n",
" 96751 | \n",
" 1985-01-04 | \n",
" 17.8 | \n",
" 25.6 | \n",
" 21.7 | \n",
" 88 | \n",
" 7.0 | \n",
" 9999.0 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
"
\n",
" \n",
" 4 | \n",
" Stasiun Meteorologi Citeko | \n",
" 96751 | \n",
" 1985-01-05 | \n",
" 17.5 | \n",
" 23.7 | \n",
" 21.0 | \n",
" 87 | \n",
" 13.0 | \n",
" 9999.0 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" name_stat id_stat date suhu_min suhu_max \\\n",
"0 Stasiun Meteorologi Citeko 96751 1985-01-01 18.1 24.7 \n",
"1 Stasiun Meteorologi Citeko 96751 1985-01-02 18.0 24.1 \n",
"2 Stasiun Meteorologi Citeko 96751 1985-01-03 17.6 25.5 \n",
"3 Stasiun Meteorologi Citeko 96751 1985-01-04 17.8 25.6 \n",
"4 Stasiun Meteorologi Citeko 96751 1985-01-05 17.5 23.7 \n",
"\n",
" suhu_mean lembab_mean curah_hujan lama_sinar cepat_angin_mean \\\n",
"0 20.3 90 9.0 9999.0 9999 \n",
"1 20.7 88 11.0 9999.0 9999 \n",
"2 21.0 86 7.0 9999.0 9999 \n",
"3 21.7 88 7.0 9999.0 9999 \n",
"4 21.0 87 13.0 9999.0 9999 \n",
"\n",
" arah_angin_mode cepat_angin_max arah_cepat_angin_max \n",
"0 9999 9999 9999 \n",
"1 9999 9999 9999 \n",
"2 9999 9999 9999 \n",
"3 9999 9999 9999 \n",
"4 9999 9999 9999 "
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_jabar.head()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:11.950907Z",
"start_time": "2018-11-09T03:43:11.826978Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"array(['96751', '96753', '96783', '96791', '96793'], dtype=object)"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Cek jumlah stasiun yang ada berdasarkan id_stat\n",
"data_jabar.id_stat.unique()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:12.127808Z",
"start_time": "2018-11-09T03:43:11.955902Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" name_stat | \n",
" date | \n",
" suhu_min | \n",
" suhu_max | \n",
" suhu_mean | \n",
" lembab_mean | \n",
" curah_hujan | \n",
" lama_sinar | \n",
" cepat_angin_mean | \n",
" arah_angin_mode | \n",
" cepat_angin_max | \n",
" arah_cepat_angin_max | \n",
"
\n",
" \n",
" id_stat | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
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" | \n",
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" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" \n",
" \n",
" 96751 | \n",
" 11934 | \n",
" 11934 | \n",
" 11934 | \n",
" 11934 | \n",
" 11934 | \n",
" 11934 | \n",
" 11934 | \n",
" 11934 | \n",
" 11934 | \n",
" 11934 | \n",
" 11934 | \n",
" 11934 | \n",
"
\n",
" \n",
" 96753 | \n",
" 12330 | \n",
" 12330 | \n",
" 12330 | \n",
" 12330 | \n",
" 12330 | \n",
" 12330 | \n",
" 12330 | \n",
" 12330 | \n",
" 12330 | \n",
" 12330 | \n",
" 12330 | \n",
" 12330 | \n",
"
\n",
" \n",
" 96783 | \n",
" 13817 | \n",
" 13817 | \n",
" 13817 | \n",
" 13817 | \n",
" 13817 | \n",
" 13817 | \n",
" 13817 | \n",
" 13817 | \n",
" 13817 | \n",
" 13817 | \n",
" 13817 | \n",
" 13817 | \n",
"
\n",
" \n",
" 96791 | \n",
" 13807 | \n",
" 13807 | \n",
" 13807 | \n",
" 13807 | \n",
" 13807 | \n",
" 13807 | \n",
" 13807 | \n",
" 13807 | \n",
" 13807 | \n",
" 13807 | \n",
" 13807 | \n",
" 13807 | \n",
"
\n",
" \n",
" 96793 | \n",
" 488 | \n",
" 488 | \n",
" 488 | \n",
" 488 | \n",
" 488 | \n",
" 488 | \n",
" 488 | \n",
" 488 | \n",
" 488 | \n",
" 488 | \n",
" 488 | \n",
" 488 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" name_stat date suhu_min suhu_max suhu_mean lembab_mean \\\n",
"id_stat \n",
"96751 11934 11934 11934 11934 11934 11934 \n",
"96753 12330 12330 12330 12330 12330 12330 \n",
"96783 13817 13817 13817 13817 13817 13817 \n",
"96791 13807 13807 13807 13807 13807 13807 \n",
"96793 488 488 488 488 488 488 \n",
"\n",
" curah_hujan lama_sinar cepat_angin_mean arah_angin_mode \\\n",
"id_stat \n",
"96751 11934 11934 11934 11934 \n",
"96753 12330 12330 12330 12330 \n",
"96783 13817 13817 13817 13817 \n",
"96791 13807 13807 13807 13807 \n",
"96793 488 488 488 488 \n",
"\n",
" cepat_angin_max arah_cepat_angin_max \n",
"id_stat \n",
"96751 11934 11934 \n",
"96753 12330 12330 \n",
"96783 13817 13817 \n",
"96791 13807 13807 \n",
"96793 488 488 "
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Ada 5 stasiun, lihat juga jumlah data yang dimiliki\n",
"data_jabar.groupby('id_stat').count()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:12.220751Z",
"start_time": "2018-11-09T03:43:12.129807Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"{'96751': 'Stasiun Meteorologi Citeko',\n",
" '96753': 'Stasiun Klimatologi Bogor',\n",
" '96783': 'Stasiun Geofisika Bandung',\n",
" '96791': 'Stasiun Meteorologi Jatiwangi',\n",
" '96793': 'Pos Meteorologi Penggung'}"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# buat dictionary id dan nama stasiun (hal ini bisa menggunakan database dalam metadata_station)\n",
"info_stat_jabar = dict()\n",
"for i, j in zip(data_jabar.id_stat.unique().tolist(), data_jabar.name_stat.unique().tolist()):\n",
" info_stat_jabar[i] = j\n",
"info_stat_jabar"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Diketahui bahwa untuk \n",
"- 96751: Stasiun Meteorologi Citeko - `11934` hari\n",
"- 96753: Stasiun Klimatologi Bogor - `12330` hari\n",
"- 96783: Stasiun Geofisika Bandung - `13817` hari\n",
"- 96791: Stasiun Meteorologi Jatiwangi - `13807` hari\n",
"- 96793: Pos Meteorologi Penggung - `488` hari\n",
"\n",
"__catatan: angka tersebut masih memiliki nilai `9999` dan `8888`__"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:12.397698Z",
"start_time": "2018-11-09T03:43:12.222749Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" suhu_min | \n",
" suhu_max | \n",
" suhu_mean | \n",
" lembab_mean | \n",
" curah_hujan | \n",
" lama_sinar | \n",
" cepat_angin_mean | \n",
" arah_angin_mode | \n",
" cepat_angin_max | \n",
" arah_cepat_angin_max | \n",
"
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" \n",
" date | \n",
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" 18.1 | \n",
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" 20.3 | \n",
" 90 | \n",
" 9.0 | \n",
" 9999.0 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
"
\n",
" \n",
" 1985-01-02 | \n",
" 18.0 | \n",
" 24.1 | \n",
" 20.7 | \n",
" 88 | \n",
" 11.0 | \n",
" 9999.0 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
"
\n",
" \n",
" 1985-01-03 | \n",
" 17.6 | \n",
" 25.5 | \n",
" 21.0 | \n",
" 86 | \n",
" 7.0 | \n",
" 9999.0 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
"
\n",
" \n",
" 1985-01-04 | \n",
" 17.8 | \n",
" 25.6 | \n",
" 21.7 | \n",
" 88 | \n",
" 7.0 | \n",
" 9999.0 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
"
\n",
" \n",
" 1985-01-05 | \n",
" 17.5 | \n",
" 23.7 | \n",
" 21.0 | \n",
" 87 | \n",
" 13.0 | \n",
" 9999.0 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
" 9999 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" suhu_min suhu_max suhu_mean lembab_mean curah_hujan \\\n",
"date \n",
"1985-01-01 18.1 24.7 20.3 90 9.0 \n",
"1985-01-02 18.0 24.1 20.7 88 11.0 \n",
"1985-01-03 17.6 25.5 21.0 86 7.0 \n",
"1985-01-04 17.8 25.6 21.7 88 7.0 \n",
"1985-01-05 17.5 23.7 21.0 87 13.0 \n",
"\n",
" lama_sinar cepat_angin_mean arah_angin_mode cepat_angin_max \\\n",
"date \n",
"1985-01-01 9999.0 9999 9999 9999 \n",
"1985-01-02 9999.0 9999 9999 9999 \n",
"1985-01-03 9999.0 9999 9999 9999 \n",
"1985-01-04 9999.0 9999 9999 9999 \n",
"1985-01-05 9999.0 9999 9999 9999 \n",
"\n",
" arah_cepat_angin_max \n",
"date \n",
"1985-01-01 9999 \n",
"1985-01-02 9999 \n",
"1985-01-03 9999 \n",
"1985-01-04 9999 \n",
"1985-01-05 9999 "
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"stat_citeko = data_jabar[data_jabar.id_stat == '96751'].drop(['name_stat', 'id_stat'], axis=1).copy()\n",
"stat_citeko = stat_citeko.set_index('date')\n",
"stat_citeko.head()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:12.476653Z",
"start_time": "2018-11-09T03:43:12.399698Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"401"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Hitung jumlah data curah hujan yang memiliki nilai 9999 dan 8888\n",
"stat_citeko_ch = stat_citeko.curah_hujan\n",
"mask = (stat_citeko_ch == 9999) | (stat_citeko_ch == 8888)\n",
"mask.sum()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:12.615792Z",
"start_time": "2018-11-09T03:43:12.480648Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"DatetimeIndex(['1985-01-01', '1985-01-02', '1985-01-03', '1985-01-04',\n",
" '1985-01-05', '1985-01-06', '1985-01-07', '1985-01-08',\n",
" '1985-01-09', '1985-01-10',\n",
" ...\n",
" '2017-12-23', '2017-12-24', '2017-12-25', '2017-12-26',\n",
" '2017-12-27', '2017-12-28', '2017-12-29', '2017-12-30',\n",
" '2017-12-31', '2018-01-01'],\n",
" dtype='datetime64[ns]', name='date', length=11934, freq=None)"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Pada tanggal berapa saja datanya memiliki nilai 8888 atau 9999\n",
"mask.index"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"ExecuteTime": {
"end_time": "2018-11-09T03:43:14.726381Z",
"start_time": "2018-11-09T03:43:12.619784Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
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