Recently, we are studying the use of pyecharts, which is a visual tool of python. Then we want to play together with Wechat and see the effect directly.

[Img-0BvoMCek-1565876828599 (https://upload-images.jianshu.io/upload_images/17885815-83e5faa94bc6d8e2?ImageMogr2/auto-orient/strip)]

Environmental configuration

pip install pyecharts
pip install snapshot_selenium
pip install echarts-countries-pypkg
pip install echarts-china-provinces-pypkg
pip install echarts-china-cities-pypkg
pip install echarts-china-counties-pypkg
pip install wxpy

Getting Friends

The main purpose is to get the basic data of friends, which is used to make data visualization code as follows:

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from wxpy import Bot, Chat

class Demo(Chat):

    @staticmethod
    def get_friend():
        bot = Bot()
        friends = bot.friends(update=True)

        friend_data = []
        for friend in friends:
            if friend.sex == 1:
                sex = "male"
            elif friend.sex == 2:
                sex = "female"
            else:
                sex = ""
            friend_dict = {
                "city": friend.city,
                "province": friend.province,
                "sex": sex,
                "signature": friend.signature,

            }
            friend_data.append(friend_dict)

        return friend_data

Returns a list of Wechat friends, including data on friends cities, provinces, gender and personality signatures.

Geographic coordinate map

Geographic coordinate map in pyecharts is mainly based on Geo module

def geo_base():
    city_data = get_data()
    geo = Geo(init_opts=opts.InitOpts(theme="vintage"))
    for city in city_data:
        try:
            geo.add_schema(maptype="china", itemstyle_opts=opts.ItemStyleOpts(color="gray"))
            geo.add("Wechat Friends Distribution Map", [city], type_="effectScatter", symbol_size=10)
            geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
            geo.set_global_opts(visualmap_opts=opts.VisualMapOpts(), title_opts=opts.TitleOpts(title="Wechat Friends Distribution Map"), )
        except Exception as e:
            print(e)
            pass

    # geo.render("geo.html")
    make_snapshot(driver, geo.render(), "geo.png")

After running, a geo.png image will be generated in the current directory

This picture is a map of Weixin friends'distribution in China.

Thermogram

Thermodynamic diagram is also based on the unique difference of Geo module. In add ition function, type is heatmap.

The code is as follows:

def heat_map():
    city_data = get_data()
    geo = Geo(init_opts=opts.InitOpts(theme="vintage"))
    for city in city_data:
        try:
            geo.add_schema(maptype="Guangdong", itemstyle_opts=opts.ItemStyleOpts(color="gray"))
            geo.add("Guangdong Friends Thermal Map", [city], type_="heatmap", symbol_size=10)
            geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
            geo.set_global_opts(visualmap_opts=opts.VisualMapOpts(), title_opts=opts.TitleOpts(title="Thermogram"), toolbox_opts=opts.ToolboxOpts())
        except :
            pass

    geo.render("heat.html")

For example, the data of a province can be selected, and the effect after operation is as follows:

The above is the thermodynamic map of the distribution of Guangdong friends in Weixin.

National Distribution Map

Map is an extension based on Map module. The main function is add.

 def add(
    # Series name for tooltip display, legend Legend legend Legend filtering.
    series_name: str,

    # Data item (coordinate point name, coordinate point value)
    data_pair: Sequence,

    # Map type, refer specifically to pyecharts.datasets.map_filenames.json file
    maptype: str = "china",

    # Is Legend Selected
    is_selected: bool = True,

    # Whether to turn on mouse zoom and pan roaming.
    is_roam: bool = True,

    # The central point of the current perspective, expressed in latitude and longitude
    center: Optional[Sequence] = None,

    # Scale-up ratio of current perspective.
    zoom: Optional[Numeric] = 1,

    # Name mapping for custom locales
    name_map: Optional[dict] = None,

    # Marked Graphic Shape
    symbol: Optional[str] = None,

    # Whether to display markup graphics
    is_map_symbol_show: bool = True,

    # Label Configuration Item, refer to `series_options.LabelOpts'.`
    label_opts: Union[opts.LabelOpts, dict] = opts.LabelOpts(),

    # Tip box component configuration item, refer to `series_options.TooltipOpts'.`
    tooltip_opts: Union[opts.TooltipOpts, dict, None] = None,

    # Metastyle configuration entry, refer to `series_options.ItemStyleOpts'.`
    itemstyle_opts: Union[opts.ItemStyleOpts, dict, None] = None,
)

The code is as follows:

def map_base():
    province_data = province_list()
    maps = Map()
    maps.add("", province_data, "china")
    maps.set_global_opts(title_opts=opts.TitleOpts(title="Wechat Friends Distribution Map"), visualmap_opts=opts.VisualMapOpts())

    make_snapshot(driver, geo.render(), "map.png")

After running, is it interesting to generate the pictures shown at the beginning of the article?

Word nephogram

Cloud Map of Friends City Distribution Words

c = (
            WordCloud()
            .add("", city_list, word_size_range=[15, 50], shape="diamond", word_gap=10)
            .set_global_opts(title_opts=opts.TitleOpts(title="diamond"))
        )
        make_snapshot(driver, c.render(), "world.png")

The results are as follows:

Bar graph

First look at the effect:

The code is as follows:

def bar_datazoom_slider() -> Bar:
    city_data = get_data()
    c = (
        Bar(init_opts=opts.InitOpts(page_title="Bar graph"))
        .add_xaxis([city[0] for city in city_data])
        .add_yaxis("Number of cities", [city[1] for city in city_data])
        .set_global_opts(
            title_opts=opts.TitleOpts(title="Friends City Distribution Bar Map"),
            datazoom_opts=[opts.DataZoomOpts(orient="vertical")]
        )
    )
    return c

Finally, another interesting way is to offer your Weixin avatars:

Look at the picture first.

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