{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "name": "taruma_hk60_resample", "version": "0.3.2", "provenance": [], "collapsed_sections": [] }, "kernelspec": { "name": "python3", "display_name": "Python 3" } }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "f7sSLaY7hEV5", "colab_type": "text" }, "source": [ "Berdasarkan isu [#60](https://github.com/taruma/hidrokit/issues/60): __Menentukan kriteria berdasarkan total nilai bulanan__\n", "\n", "Deskripsi permasalahan:\n", "- Saya memiliki __dataset harian__ nilai a, b, c selama 50 tahun.\n", "- Saya ingin mengkategorikan nilai di kolom a, __berdasarkan__ nilai total bulanan-nya.\n", "- Hasil pengategorian tersebut dibuat pada kolom baru bernama 'kategori'." ] }, { "cell_type": "code", "metadata": { "id": "cn82ATqtg5FL", "colab_type": "code", "colab": {} }, "source": [ "# import library\n", "import pandas as pd\n", "import numpy as np" ], "execution_count": 0, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "MoRqkKdnhUFd", "colab_type": "code", "outputId": "1d3cf757-b39c-47fe-826f-4d323058b595", "colab": { "base_uri": "https://localhost:8080/", "height": 170 } }, "source": [ "# buat dataset random\n", "SEED = 110891\n", "np.random.seed(SEED)\n", "date_index = pd.date_range('20000101', '20501231')\n", "dataset = pd.DataFrame(\n", " index=date_index,\n", " data=np.random.rand(len(date_index), 3)*10,\n", " columns='a b c'.split()\n", ")\n", "dataset.info()" ], "execution_count": 0, "outputs": [ { "output_type": "stream", "text": [ "\n", "DatetimeIndex: 18628 entries, 2000-01-01 to 2050-12-31\n", "Freq: D\n", "Data columns (total 3 columns):\n", "a 18628 non-null float64\n", "b 18628 non-null float64\n", "c 18628 non-null float64\n", "dtypes: float64(3)\n", "memory usage: 582.1 KB\n" ], "name": "stdout" } ] }, { "cell_type": "code", "metadata": { "id": "WqdHuxfphyI8", "colab_type": "code", "outputId": "fe12e39a-364d-4429-ee32-169dea51fb64", "colab": { "base_uri": "https://localhost:8080/", "height": 204 } }, "source": [ "dataset.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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abc
2000-01-012.8777663.2133782.609509
2000-01-026.0870790.5288142.181410
2000-01-037.7885538.5975643.401175
2000-01-047.9524443.1823241.600600
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" ], "text/plain": [ " a b c\n", "2000-01-01 2.877766 3.213378 2.609509\n", "2000-01-02 6.087079 0.528814 2.181410\n", "2000-01-03 7.788553 8.597564 3.401175\n", "2000-01-04 7.952444 3.182324 1.600600\n", "2000-01-05 1.721316 7.618591 5.018759" ] }, "metadata": { "tags": [] }, "execution_count": 3 } ] }, { "cell_type": "code", "metadata": { "id": "WQJzzyVsqiC9", "colab_type": "code", "outputId": "c9d6ca08-6fda-4e38-b47e-11acbb869dea", "colab": { "base_uri": "https://localhost:8080/", "height": 1000 } }, "source": [ "# menghitung total ch setiap bulannya\n", "total_summary = dataset.groupby([dataset.index.year, dataset.index.month]).sum()\n", "total_summary" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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abc
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2146.883002163.938908125.541164
3149.917733162.343038153.770483
4151.332312146.398578131.572011
5148.824870159.312776178.204217
6142.645200141.804644162.177388
7170.140213130.409430191.273702
8170.068540159.861622179.001989
9178.699585157.825042144.558428
10145.530305191.522354178.904414
11128.861376152.381631121.446012
12128.531776145.206447160.007800
20011165.739167150.058786160.826603
2141.511927134.187962130.801650
3135.688425177.826575173.841181
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5159.875967168.663616120.514476
6155.665123153.639577153.308357
7142.746376139.065767147.011501
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20021167.053233155.069400171.605847
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3183.218227164.571052154.357133
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6151.163008130.519755151.762828
...............
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612 rows × 3 columns

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" ], "text/plain": [ " a b c\n", "2000 1 162.847727 156.897045 144.812644\n", " 2 146.883002 163.938908 125.541164\n", " 3 149.917733 162.343038 153.770483\n", " 4 151.332312 146.398578 131.572011\n", " 5 148.824870 159.312776 178.204217\n", " 6 142.645200 141.804644 162.177388\n", " 7 170.140213 130.409430 191.273702\n", " 8 170.068540 159.861622 179.001989\n", " 9 178.699585 157.825042 144.558428\n", " 10 145.530305 191.522354 178.904414\n", " 11 128.861376 152.381631 121.446012\n", " 12 128.531776 145.206447 160.007800\n", "2001 1 165.739167 150.058786 160.826603\n", " 2 141.511927 134.187962 130.801650\n", " 3 135.688425 177.826575 173.841181\n", " 4 167.878367 163.536799 167.083027\n", " 5 159.875967 168.663616 120.514476\n", " 6 155.665123 153.639577 153.308357\n", " 7 142.746376 139.065767 147.011501\n", " 8 142.728787 174.440000 148.623053\n", " 9 116.060098 165.032239 153.688107\n", " 10 168.868071 164.222337 170.667792\n", " 11 140.969798 155.106032 121.242189\n", " 12 123.714519 163.179190 166.616499\n", "2002 1 167.053233 155.069400 171.605847\n", " 2 120.012374 146.039734 153.264692\n", " 3 183.218227 164.571052 154.357133\n", " 4 154.822616 120.226232 102.963488\n", " 5 169.889488 152.184870 142.519123\n", " 6 151.163008 130.519755 151.762828\n", "... ... ... ...\n", "2048 7 148.672508 167.142954 164.381128\n", " 8 126.655985 148.710034 144.413049\n", " 9 183.513775 114.640279 169.897208\n", " 10 135.829907 151.918643 176.459592\n", " 11 146.398529 125.322861 148.996056\n", " 12 159.041660 156.619241 165.230088\n", "2049 1 157.052500 139.911295 145.751750\n", " 2 117.204951 135.909696 128.467320\n", " 3 140.775834 172.049295 186.388653\n", " 4 142.940225 156.801915 141.438030\n", " 5 175.040427 157.488158 156.365536\n", " 6 140.708484 133.383572 147.509383\n", " 7 145.790755 165.487569 154.127876\n", " 8 149.804165 169.480737 138.583017\n", " 9 158.301834 164.360739 164.492783\n", " 10 159.818715 141.081036 142.240236\n", " 11 96.027429 154.389690 154.491933\n", " 12 168.802017 140.951503 148.711046\n", "2050 1 175.387880 156.662521 203.628996\n", " 2 137.018246 133.811524 144.568716\n", " 3 161.716170 143.697188 143.519191\n", " 4 162.027600 135.305125 156.008888\n", " 5 154.067237 161.674996 169.782035\n", " 6 153.781478 158.463390 171.016871\n", " 7 149.692955 171.071892 144.742615\n", " 8 163.018816 161.417455 157.176567\n", " 9 142.620717 171.070855 117.322726\n", " 10 138.459144 137.613439 164.343386\n", " 11 150.625937 147.692128 164.288570\n", " 12 157.485470 184.238850 160.089807\n", "\n", "[612 rows x 3 columns]" ] }, "metadata": { "tags": [] }, "execution_count": 4 } ] }, { "cell_type": "code", "metadata": { "id": "J54gY_fKjDGg", "colab_type": "code", "outputId": "797a17fc-cb3e-46b0-c669-8c33918a7d8b", "colab": { "base_uri": "https://localhost:8080/", "height": 34 } }, "source": [ "# Memilih nilai spesifik bulan dan tahun pada kolom tertentu\n", "TAHUN, BULAN, KOLOM = 2000, 1, 'a'\n", "total_summary.loc[(TAHUN, BULAN), KOLOM]" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "162.84772662835172" ] }, "metadata": { "tags": [] }, "execution_count": 5 } ] }, { "cell_type": "code", "metadata": { "id": "LmiD9JurjS5L", "colab_type": "code", "colab": {} }, "source": [ "# \n", "\n", "def total_each_month(x, column='ch', summary=None):\n", " year = x['index'].year\n", " month = x['index'].month\n", " return summary.loc[(year, month), column]\n", "\n", "def criteria(value):\n", " if value < 130:\n", " return \"rendah\"\n", " elif value >= 130 and value <= 160:\n", " return \"sedang\"\n", " else:\n", " return \"tinggi\"\n", "\n", "KOLOM = 'a'\n", " \n", "dataset['total_a'] = dataset.reset_index().apply(lambda x: total_each_month(x, column=KOLOM, summary=total_summary), axis=1).values\n", "dataset['kategori'] = dataset['total_a'].apply(criteria)" ], "execution_count": 0, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "v7iE2vvC2TSu", "colab_type": "code", "outputId": "e9c09b23-974f-4875-9e86-e6a8ced3961f", "colab": { "base_uri": "https://localhost:8080/", "height": 204 } }, "source": [ "dataset.head()" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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abctotal_akategori
2000-01-012.8777663.2133782.609509162.847727tinggi
2000-01-026.0870790.5288142.181410162.847727tinggi
2000-01-037.7885538.5975643.401175162.847727tinggi
2000-01-047.9524443.1823241.600600162.847727tinggi
2000-01-051.7213167.6185915.018759162.847727tinggi
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" ], "text/plain": [ " a b c total_a kategori\n", "2000-01-01 2.877766 3.213378 2.609509 162.847727 tinggi\n", "2000-01-02 6.087079 0.528814 2.181410 162.847727 tinggi\n", "2000-01-03 7.788553 8.597564 3.401175 162.847727 tinggi\n", "2000-01-04 7.952444 3.182324 1.600600 162.847727 tinggi\n", "2000-01-05 1.721316 7.618591 5.018759 162.847727 tinggi" ] }, "metadata": { "tags": [] }, "execution_count": 7 } ] }, { "cell_type": "code", "metadata": { "id": "ZrisfWzl2LSn", "colab_type": "code", "outputId": "49283388-6ed6-4e63-9324-ab18107a5e0b", "colab": { "base_uri": "https://localhost:8080/", "height": 359 } }, "source": [ "dataset.sample(n=10, random_state=SEED)" ], "execution_count": 0, "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "
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abctotal_akategori
2048-11-111.2238140.4365035.906254146.398529sedang
2006-04-057.4941723.3345111.982660161.010925tinggi
2038-06-191.7374481.2666652.950612130.366532sedang
2022-06-147.9991641.0794374.436997171.157052tinggi
2012-10-249.0060641.9422240.583746160.424030tinggi
2007-06-100.7906716.9431351.963164139.102825sedang
2008-03-317.3622423.0706369.000031143.855427sedang
2004-08-206.6968452.6765293.607975179.573750tinggi
2014-12-281.0353548.8117850.589958143.172699sedang
2044-07-113.6865248.4405040.009692151.676157sedang
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" ], "text/plain": [ " a b c total_a kategori\n", "2048-11-11 1.223814 0.436503 5.906254 146.398529 sedang\n", "2006-04-05 7.494172 3.334511 1.982660 161.010925 tinggi\n", "2038-06-19 1.737448 1.266665 2.950612 130.366532 sedang\n", "2022-06-14 7.999164 1.079437 4.436997 171.157052 tinggi\n", "2012-10-24 9.006064 1.942224 0.583746 160.424030 tinggi\n", "2007-06-10 0.790671 6.943135 1.963164 139.102825 sedang\n", "2008-03-31 7.362242 3.070636 9.000031 143.855427 sedang\n", "2004-08-20 6.696845 2.676529 3.607975 179.573750 tinggi\n", "2014-12-28 1.035354 8.811785 0.589958 143.172699 sedang\n", "2044-07-11 3.686524 8.440504 0.009692 151.676157 sedang" ] }, "metadata": { "tags": [] }, "execution_count": 8 } ] }, { "cell_type": "markdown", "metadata": { "id": "l277kxD6I_y3", "colab_type": "text" }, "source": [ "# Changelog\n", "\n", "```\n", "- 20190717 - 1.0.0 - Initial\n", "```\n", "\n", "#### Copyright © 2019 [Taruma Sakti Megariansyah](https://taruma.github.io)\n", "\n", "Source code in this notebook is licensed under a [MIT License](https://choosealicense.com/licenses/mit/). Data in this notebook is licensed under a [Creative Common Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/). " ] } ] }