{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## pyecharts\n",
"- [HTML](http://htmlpreview.github.io/?https://github.com/zzsza/TIL/blob/master/python/pyecharts.html) 에서 확인하면 이쁜 그래프도 보입니다!!!\n",
"- Baidu에서 데이터 시각화를 위해 만든 오픈소스인 Echarts의 파이썬 버전\n",
"- 다양한 그래프 제공\n",
"- [공식 문서](http://pyecharts.org/#/en-us/)\n",
"- Dynamic\n",
"- 단, 옵션의 단추가 중국어\n",
"- 그래프를 그릴 때, echarts와 echartql을 로컬에서 찾으려고 함\n",
" - 따라서 nbconvert를 사용해 HTML으로 저장한 후, 쉘에서 수정\n",
" \n",
" ```\n",
" sed -i \"\" \"s|/nbextensions/echarts/echarts-gl.min|https://cdn.jsdelivr.net/npm/echarts-gl@1.1.1/dist/echarts-gl.min|g; s|/nbextensions/echarts/echarts.min|https://cdnjs.cloudflare.com/ajax/libs/echarts/4.1.0/echarts.min|g\" 파일이름.ipynb\n",
" ```"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import pyecharts\n",
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"attr = [\"Jan\", \"Feb\", \"Mar\", \"Apr\", \"May\", \"Jun\", \"Jul\", \"Aug\", \"Sep\", \"Oct\", \"Nov\", \"Dec\"]\n",
"v1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]\n",
"v2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]\n",
"bar = pyecharts.Bar(\"Bar chart\", \"precipitation and evaporation one year\")\n",
"bar.add(\"precipitation\", attr, v1, mark_line=[\"average\"], mark_point=[\"max\", \"min\"])\n",
"bar.add(\"evaporation\", attr, v2, mark_line=[\"average\"], mark_point=[\"max\", \"min\"])\n",
"bar.render()\n",
"bar.height = 500\n",
"bar.width = 800"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bar"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"attr = [\"Jan\", \"Feb\", \"Mar\", \"Apr\", \"May\", \"Jun\", \"Jul\", \"Aug\", \"Sep\", \"Oct\", \"Nov\", \"Dec\"]\n",
"v1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]\n",
"v2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]\n",
"bar = pyecharts.Bar(\"Bar chart\", \"precipitation and evaporation one year\")\n",
"bar.use_theme(\"dark\")\n",
"bar.add(\"precipitation\", attr, v1, mark_line=[\"average\"], mark_point=[\"max\", \"min\"])\n",
"bar.add(\"evaporation\", attr, v2, mark_line=[\"average\"], mark_point=[\"max\", \"min\"])\n",
"bar.height = 500\n",
"bar.width = 800\n",
"bar"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## In pandas"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"title = \"bar chart2\"\n",
"index = pd.date_range(\"8/24/2018\", periods=6, freq=\"M\")\n",
"df1 = pd.DataFrame(np.random.randn(6), index=index)\n",
"df2 = pd.DataFrame(np.random.rand(6), index=index)\n",
"\n",
"dfvalue1 = [i[0] for i in df1.values]\n",
"dfvalue2 = [i[0] for i in df2.values]\n",
"_index = [i for i in df1.index.format()]\n",
"\n",
"bar = pyecharts.Bar(title, \"Profit and loss situation\")\n",
"bar.add(\"profit\", _index, dfvalue1)\n",
"bar.add(\"loss\", _index, dfvalue2)\n",
"bar.height = 500\n",
"bar.width = 800\n",
"bar"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from pyecharts import Bar, Line, Overlap\n",
"\n",
"attr = ['A','B','C','D','E','F']\n",
"v1 = [10, 20, 30, 40, 50, 60]\n",
"v2 = [38, 28, 58, 48, 78, 68]\n",
"bar = Bar(\"Line Bar\")\n",
"bar.add(\"bar\", attr, v1)\n",
"line = Line()\n",
"line.add(\"line\", attr, v2)\n",
"\n",
"overlap = Overlap()\n",
"overlap.add(bar)\n",
"overlap.add(line)\n",
"\n",
"overlap"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from pyecharts import Pie\n",
"\n",
"attr = ['A','B','C','D','E','F']\n",
"v1 = [10, 20, 30, 40, 50, 60]\n",
"v2 = [38, 28, 58, 48, 78, 68]\n",
"pie = Pie(\"pie chart\", title_pos=\"center\", width=600)\n",
"pie.add(\"A\", attr, v1, center=[25, 50], is_random=True, radius=[30, 75], rosetype='radius')\n",
"pie.add(\"B\", attr, v2, center=[75, 50], is_randome=True, radius=[30, 75], rosetype='area', is_legend_show=False,\n",
" is_label_show=True)\n",
"pie"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 가로 그래프"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bar = Bar(\"가로 그래프\")\n",
"bar.add(\"A\", attr, v1)\n",
"bar.add(\"B\", attr, v2, is_convert=True)\n",
"bar.width=800\n",
"bar"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 슬라이더"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import random\n",
"\n",
"attr = [\"{}th\".format(i) for i in range(30)]\n",
"v1 = [random.randint(1, 30) for _ in range(30)]\n",
"bar = Bar(\"Bar - datazoom - slider \")\n",
"bar.add(\"\", attr, v1, is_label_show=True, is_datazoom_show=True)\n",
"# bar.render()\n",
"bar"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"days = [\"{}th\".format(i) for i in range(30)]\n",
"days_v1 = [random.randint(1, 30) for _ in range(30)]\n",
"bar = Bar(\"Bar - datazoom - xaxis/yaxis\")\n",
"bar.add(\n",
" \"\",\n",
" days,\n",
" days_v1,\n",
" is_datazoom_show=True,\n",
" datazoom_type=\"slider\",\n",
" datazoom_range=[10, 25],\n",
" is_datazoom_extra_show=True,\n",
" datazoom_extra_type=\"slider\",\n",
" datazoom_extra_range=[10, 25],\n",
" is_toolbox_show=False,\n",
")\n",
"# bar.render()\n",
"bar"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3D"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from pyecharts import Bar3D\n",
"\n",
"bar3d = Bar3D(\"3D Graph\", width=1200, height=600)\n",
"x_axis = [\n",
" \"12a\", \"1a\", \"2a\", \"3a\", \"4a\", \"5a\", \"6a\", \"7a\", \"8a\", \"9a\", \"10a\", \"11a\",\n",
" \"12p\", \"1p\", \"2p\", \"3p\", \"4p\", \"5p\", \"6p\", \"7p\", \"8p\", \"9p\", \"10p\", \"11p\"\n",
" ]\n",
"y_axis = [\n",
" \"Saturday\", \"Friday\", \"Thursday\", \"Wednesday\", \"Tuesday\", \"Monday\", \"Sunday\"\n",
" ]\n",
"data = [\n",
" [0, 0, 5], [0, 1, 1], [0, 2, 0], [0, 3, 0], [0, 4, 0], [0, 5, 0],\n",
" [0, 6, 0], [0, 7, 0], [0, 8, 0], [0, 9, 0], [0, 10, 0], [0, 11, 2],\n",
" [0, 12, 4], [0, 13, 1], [0, 14, 1], [0, 15, 3], [0, 16, 4], [0, 17, 6],\n",
" [0, 18, 4], [0, 19, 4], [0, 20, 3], [0, 21, 3], [0, 22, 2], [0, 23, 5],\n",
" [1, 0, 7], [1, 1, 0], [1, 2, 0], [1, 3, 0], [1, 4, 0], [1, 5, 0],\n",
" [1, 6, 0], [1, 7, 0], [1, 8, 0], [1, 9, 0], [1, 10, 5], [1, 11, 2],\n",
" [1, 12, 2], [1, 13, 6], [1, 14, 9], [1, 15, 11], [1, 16, 6], [1, 17, 7],\n",
" [1, 18, 8], [1, 19, 12], [1, 20, 5], [1, 21, 5], [1, 22, 7], [1, 23, 2],\n",
" [2, 0, 1], [2, 1, 1], [2, 2, 0], [2, 3, 0], [2, 4, 0], [2, 5, 0],\n",
" [2, 6, 0], [2, 7, 0], [2, 8, 0], [2, 9, 0], [2, 10, 3], [2, 11, 2],\n",
" [2, 12, 1], [2, 13, 9], [2, 14, 8], [2, 15, 10], [2, 16, 6], [2, 17, 5],\n",
" [2, 18, 5], [2, 19, 5], [2, 20, 7], [2, 21, 4], [2, 22, 2], [2, 23, 4],\n",
" [3, 0, 7], [3, 1, 3], [3, 2, 0], [3, 3, 0], [3, 4, 0], [3, 5, 0],\n",
" [3, 6, 0], [3, 7, 0], [3, 8, 1], [3, 9, 0], [3, 10, 5], [3, 11, 4],\n",
" [3, 12, 7], [3, 13, 14], [3, 14, 13], [3, 15, 12], [3, 16, 9], [3, 17, 5],\n",
" [3, 18, 5], [3, 19, 10], [3, 20, 6], [3, 21, 4], [3, 22, 4], [3, 23, 1],\n",
" [4, 0, 1], [4, 1, 3], [4, 2, 0], [4, 3, 0], [4, 4, 0], [4, 5, 1],\n",
" [4, 6, 0], [4, 7, 0], [4, 8, 0], [4, 9, 2], [4, 10, 4], [4, 11, 4],\n",
" [4, 12, 2], [4, 13, 4], [4, 14, 4], [4, 15, 14], [4, 16, 12], [4, 17, 1],\n",
" [4, 18, 8], [4, 19, 5], [4, 20, 3], [4, 21, 7], [4, 22, 3], [4, 23, 0],\n",
" [5, 0, 2], [5, 1, 1], [5, 2, 0], [5, 3, 3], [5, 4, 0], [5, 5, 0],\n",
" [5, 6, 0], [5, 7, 0], [5, 8, 2], [5, 9, 0], [5, 10, 4], [5, 11, 1],\n",
" [5, 12, 5], [5, 13, 10], [5, 14, 5], [5, 15, 7], [5, 16, 11], [5, 17, 6],\n",
" [5, 18, 0], [5, 19, 5], [5, 20, 3], [5, 21, 4], [5, 22, 2], [5, 23, 0],\n",
" [6, 0, 1], [6, 1, 0], [6, 2, 0], [6, 3, 0], [6, 4, 0], [6, 5, 0],\n",
" [6, 6, 0], [6, 7, 0], [6, 8, 0], [6, 9, 0], [6, 10, 1], [6, 11, 0],\n",
" [6, 12, 2], [6, 13, 1], [6, 14, 3], [6, 15, 4], [6, 16, 0], [6, 17, 0],\n",
" [6, 18, 0], [6, 19, 0], [6, 20, 1], [6, 21, 2], [6, 22, 2], [6, 23, 6]\n",
" ]\n",
"range_color = ['#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',\n",
" '#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026']\n",
"bar3d.add(\n",
" \"\",\n",
" x_axis,\n",
" y_axis,\n",
" [[d[1], d[0], d[2]] for d in data],\n",
" is_visualmap=True,\n",
" visual_range=[0, 20],\n",
" visual_range_color=range_color,\n",
" grid3d_width=200,\n",
" grid3d_depth=80,\n",
")\n",
"bar3d.width=700\n",
"bar3d.height=500\n",
"\n",
"bar3d"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Boxplot"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from pyecharts import Boxplot\n",
"\n",
"boxplot = Boxplot(\"Box plot\")\n",
"x_axis = ['expr1', 'expr2', 'expr3', 'expr4', 'expr5']\n",
"y_axis = [\n",
" [850, 740, 900, 1070, 930, 850, 950, 980, 980, 880,\n",
" 1000, 980, 930, 650, 760, 810, 1000, 1000, 960, 960],\n",
" [960, 940, 960, 940, 880, 800, 850, 880, 900, 840,\n",
" 830, 790, 810, 880, 880, 830, 800, 790, 760, 800],\n",
" [880, 880, 880, 860, 720, 720, 620, 860, 970, 950,\n",
" 880, 910, 850, 870, 840, 840, 850, 840, 840, 840],\n",
" [890, 810, 810, 820, 800, 770, 760, 740, 750, 760,\n",
" 910, 920, 890, 860, 880, 720, 840, 850, 850, 780],\n",
" [890, 840, 780, 810, 760, 810, 790, 810, 820, 850,\n",
" 870, 870, 810, 740, 810, 940, 950, 800, 810, 870]\n",
"]\n",
"_yaxis = boxplot.prepare_data(y_axis) \n",
"boxplot.add(\"boxplot\", x_axis, _yaxis)\n",
"boxplot"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 퍼널"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from pyecharts import Funnel\n",
"\n",
"attr = [\"A\", \"B\", \"C\", \"D\", \"E\", \"F\"]\n",
"value = [20, 40, 60, 80, 100, 120]\n",
"funnel = Funnel(\"퍼널 그래프\")\n",
"funnel.add(\n",
" \"퍼널\",\n",
" attr,\n",
" value,\n",
" is_label_show=True,\n",
" label_pos=\"inside\",\n",
" label_text_color=\"#fff\",\n",
")\n",
"funnel.width=700\n",
"funnel.height=500\n",
"funnel"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Gauge"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
"\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from pyecharts import Gauge\n",
"\n",
"gauge = Gauge(\"Gauge Graph\")\n",
"gauge.add(\"이용률\", \"가운데\", 66.66)\n",
"gauge"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.5"
},
"varInspector": {
"cols": {
"lenName": 16,
"lenType": 16,
"lenVar": 40
},
"kernels_config": {
"python": {
"delete_cmd_postfix": "",
"delete_cmd_prefix": "del ",
"library": "var_list.py",
"varRefreshCmd": "print(var_dic_list())"
},
"r": {
"delete_cmd_postfix": ") ",
"delete_cmd_prefix": "rm(",
"library": "var_list.r",
"varRefreshCmd": "cat(var_dic_list()) "
}
},
"types_to_exclude": [
"module",
"function",
"builtin_function_or_method",
"instance",
"_Feature"
],
"window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 2
}