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        "author": "chuboy",
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        "classifiers": [
            "Topic :: Scientific/Engineering :: Visualization"
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        "description": "# lazyplotly\nA wrapper of interactive visualization package plotly. Sometimes we are just too lazy to make nested dictionary. Especially creating dropdown menus or slide bars is a way too exhuasting. Moreover, variables of different kind of chart are renamed into a single taxonomy.\n### What is simplified as easy as possible\n1. creating widgets such as dropdown menu or a slider bar\n2. combine different type of charts together into subplots\n3. automatically calculate grid rows and columns of subplots\n4. configuring different type of variable, using them in a single taxonomy\n5. initiate settings for jupyter notebook users\n### Installation\n```\n$ pip install plotly lazyplotly\n```\n### Quick Start\n```\nimport lazyplotly as lp\n\n# using list data type to fit\nbar_1 = lp.bar(x=[1,2,3,4,5], y=[23,43,62,24,33], cmap=lp.cmap[16], name='male')\n\n# using dataframe to fit\ndf = dict(x=[1,2,3,4,5],y=[48,32,43,54,62])\nbar_2 = lp.bar(x='x', y='y', df=df, cmap=lp.cmap[16], name='female')\n\n# combine all charts into dropdown menu, and save as a html file\nlp.dropdown(\n    datas = [[bar_1,bar_2],[bar_2, bar_1]],\n    btn_labels = ['male v.s. female','female v.s. male'], \n    xlabel = 'category', ylabel='value', title='MyAwesomeTitle',\n    output = 'MyAwesomePlot.html'\n)\n```\n![](https://github.com/billju/lazyplotly/raw/master/images/dropdown.png)\n### Custom extension\n```\n# using dataframe object by setting xy variables with column name\ndf = dict(order=[1,2,3,4,5],trend=[22,33,47,57,46],lower=[21,32,43,54,32],upper=[23,34,51,60,60])\narea = lp.area(x='order', y='lower', y2='upper', df=df, color='rgba(0,176,246,0.2)', name='CI')\nline = lp.line(x='order', y='trend', df=df)\nline['line'] = dict(dash = 'dash', color='steelblue')\n\n# add output variable to export as a html file\nlp.plot(\n    data = [area, line],\n    rangeslider = True,\n    layout = dict(title='Time Series with confidence interval'), # layout extension\n    config = dict(displayModeBar=True), # util icons on right top side\n)\n```\n![](https://github.com/billju/lazyplotly/raw/master/images/time_series.png)\n### Subplot\n```\nimport numpy as np\nimport pandas as pd\ndf = pd.DataFrame(dict(\n    monday = np.random.normal(5, 1, 100),\n    tuesday = np.random.normal(5, 1.5, 100),\n    wednesday = np.random.normal(5, 2, 100),\n    thursday = np.random.normal(5, 2.5, 100),\n    friday = np.random.normal(5, 3, 100),\n    saturday = np.random.normal(5, 3.5, 100),\n    sunday = np.random.normal(5, 4, 100),\n))\ndata = []\nfor x in df.columns:\n    for y in df.columns:\n        if x==y:\n            data.append(lp.histogram(x=df[x], name=x))\n        else:\n            data.append(lp.scatter(x=df[x], y=df[y], name=f'{x}-{y}'))\n# making subplot\nlp.plot(data, rows=7)\n\n# or a boxplot collection\nlp.plot([lp.box(y=df[col], name=col) for col in df.columns])\n```\n![](https://github.com/billju/lazyplotly/raw/master/images/subplot.png)\n![](https://github.com/billju/lazyplotly/raw/master/images/boxplot.png)\n### Sunburst, Pie, Donut\n```\ndf = dict(\n    parents = ['', 'Eve', 'Eve', 'Seth', 'Seth', 'Eve', 'Eve', 'Awan', 'Eve' ],\n    labels = ['Eve', 'Cain', 'Seth', 'Enos', 'Noam', 'Abel', 'Awan', 'Enoch', 'Azura'],\n    values = [10, 14, 12, 10, 2, 6, 6, 4, 4]\n)\nsunburst = lp.pie(x='parents',x2='labels',y='values', df=df)\npie = lp.pie(x='labels', y='values', df=df)\ndonut = lp.pie(x='labels', y='values', df=df, hole=0.4)\nlp.plot([sunburst, pie, donut], cols=3)\n```\n![](https://github.com/billju/lazyplotly/raw/master/images/pie.png)\n### 3D scatter\n```\nimport numpy as np\ndf = dict(\n    x=np.random.randint(100,size=100),\n    y=np.random.randint(100,size=100),\n    z=np.random.randint(100,size=100)\n)\nscatter3d = lp.scatter3d(x='x',y='y',z='z', df=df, cmap=lp.cmap[16])\nmesh3d = lp.mesh3d(x='x',y='y',z='z', df=df, color=lp.color[0])\nlp.plot([scatter3d,mesh3d], no_padding=True)\n```\n![](https://github.com/billju/lazyplotly/raw/master/images/scatter3d.png)\n\n### Sankey Diagram\n```\n# sankey diagram\ndf = dict(\n    origin=['Eve', 'Cain', 'Abel', 'Abel', 'Noam'],\n    destin=['Abel', 'Abel', 'Awan', 'Enoch', 'Abel'],\n    count=[23,27,50,60,60]\n)\nsankey = lp.sankey(x='origin', y='destin', z='count', df=df)\nlp.plot(sankey)\n```\n![](https://github.com/billju/lazyplotly/raw/master/images/sankey.png)\n### Map\n```\ntoken = 'your mapbox api access token, get your own one at https://account.mapbox.com/'\ndf = dict(\n    lon=[121.1,121.2,121.5,121.3],\n    lat=[24.1,24.3,24.5,24.2],\n    volume=[20,30,40,50],\n    stop=['A','B','C','detail information about bus stop D']\n)\nscattermapbox = lp.scattermapbox(x='lon',y='lat',z='volume',tooltip='stop',name='bus route',df=df)\nscattermapbox['mode'] = 'markers+lines'\nlp.mapbox(scattermapbox,token=token,zoom=9)\n```\n![](https://github.com/billju/lazyplotly/raw/master/images/mapbox.png)\n### APIs\n```\nlp.cmap     # show all colorscales available in plotly\nlp.color    # show all defined css color name in plotly\nplot(data=[], layout=dict, output=bool, config=dict,cols=int, rows=int,\n    rangeslider=bool,no_padding=bool, title=str, xlabel=str, ylabel=str)\ndropdown(datas=[[]], btn_labels=[], layout=dict, output=bool, config=dict,\n    no_padding=bool, title=str, xlabel=str, ylabel=str)\nslider(datas=[[]], prefix=str, layout=dict, output=bool, config=dict,\n    no_padding=bool, title=str, xlabel=str, ylabel=str)\nbar(x, y, df, name, color, cmap)\nscatter(x, y, df, name, color)\nscatter3d(x, y, z, df, name, color, cmap)\nline(x, y, df, name, color)\nline3d(x, y, z, df, name, color)\narea(x, y, y2, df, name, color)\narea3d(x, y, z, df, name, color)\nmesh3d(x, y, z, df, name, color)\nbox(y, df, name, color)\nhistogram(x, df, name, color, <int>bins, <bool>cum, <bool>prob)\npie(x, x2, y, df, name, hole, color)\nheatmap(df, cmap)\nsankey(x, y, z, df)\nscattermapbox(x, y, z, tooltip, df, name)\nmapbox(data, token, zoom, output, config)\n```\n\n",
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