province.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import altair as alt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from altair import expr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from altair import datum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_rows', 500)\n",
    "pd.set_option('display.max_columns', 500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "prov_list = ['aceh','bali','banten','bangka belitung','bengkulu','yogyakarta','jakarta','jambi','jawa barat','jawa tengah','jawa timur','kalimantan barat','kalimantan timur','kalimantan tengah','kalimantan selatan','kalimantan utara','kepulauan riau','nusa tenggara barat','sumatera selatan','sumatera barat','sulawesi utara','sumatera utara','sulawesi tenggara','sulawesi selatan','sulawesi tengah','lampung','riau','maluku utara','maluku','papua barat','papua','sulawesi barat','nusa tenggara timur','gorontalo'\n",
    "            ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_excel(\"daily_increment_positif.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.set_index(\"tanggal\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"total\"] = data.sum(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "prov = data[prov_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "prov_long = prov.reset_index().melt(id_vars=\"tanggal\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "selection = alt.selection_multi(fields=['variable'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "selection2 = alt.selection_multi(fields=['variable'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "base = alt.Chart(prov_long)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "cumsumbase = base.transform_window(\n",
    "    sort=[{'field': 'tanggal'}],\n",
    "    frame=[None, 0],\n",
    "    cumulative_sum='sum(value)',\n",
    "    groupby = ['variable']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "cumsumlinear = cumsumbase.mark_line().encode(\n",
    "    x='tanggal:T',\n",
    "    y = alt.Y('cumulative_sum:Q',scale=alt.Scale(type=\"linear\"),title = 'kasus'),\n",
    "    color = alt.Color('variable:N',legend=None)\n",
    ").transform_filter(selection & selection2).properties(width=400,height=250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "cumsumlog = cumsumbase.mark_line().encode(\n",
    "    x='tanggal:T',\n",
    "    y = alt.Y('cum_log:Q',scale=alt.Scale(type=\"log\"),title = 'kasus'),\n",
    "    color = alt.Color('variable:N',legend=None)\n",
    ").transform_filter(selection & selection2).transform_calculate(cum_log = expr.if_(datum.cumulative_sum == 0,expr.NaN,datum.cumulative_sum)).properties(width=400,height=250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "cumsumstacked = cumsumbase.mark_area().encode(\n",
    "    x='tanggal:T',\n",
    "    y = alt.Y('cumulative_sum:Q',scale=alt.Scale(type=\"linear\"),title = 'kasus',stack=\"normalize\"),\n",
    "    color = alt.Color('variable:N',legend=None)\n",
    ").transform_filter(selection & selection2).properties(width=400,height=250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_base = base.mark_bar(size=13).transform_aggregate(prov_sum = 'sum(value)',groupby=['variable']).encode(\n",
    "    y = alt.Y('variable:N',sort='-x',title = 'provinsi'),\n",
    "    x = alt.X('prov_sum:Q',title = 'kasus'),\n",
    "    color = 'variable:N')\n",
    "bar = bar_base.add_selection(selection).properties(width=300,height=alt.Step(16))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "mark = bar_base.mark_text(dx=15 ).encode(text = 'prov_sum:Q',color = alt.value('black')).add_selection(selection2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "charts = (cumsumlinear  & cumsumstacked) |(bar + mark) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
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       "</script>"
      ],
      "text/plain": [
       "alt.HConcatChart(...)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "charts.properties(\n",
    "    title='Indonesia Covid-19'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "charts.save('indonesia_covid.json')"
   ]
  }
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