pyecharts繪制各種數據可視化圖表案例附效果+代碼

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1、pyecharts繪制餅圖（顯示百分比）

# 導入模塊
from pyecharts import options as opts
from pyecharts.charts import Pie
#準備數據
label=['Mac口紅','Tom Ford口紅','聖羅蘭','紀梵希','花西子','迪奧','阿瑪尼','香奈兒']
values = [300,300,300,300,44,300,300,300]
# 自定義函數
def pie_base():
    c = (
        Pie()
        .add("",[list(z) for z in zip(label,values)])
        .set_global_opts(title_opts = opts.TitleOpts(title="口紅品牌分析"))
        .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{c} {d}%"))   # 值得一提的是，{d}%為百分比
    )
    return c
# 調用自定義函數生成render.html
pie_base().render()

2、pyecharts繪制柱狀圖

#導入模塊
from pyecharts.globals import ThemeType
from pyecharts import options as opts
from pyecharts.charts import Bar
#準備數據
l1=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']
l2=[100,200,300,400,500,400,300]
bar = (
    Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
    .add_xaxis(l1)
    .add_yaxis("柱狀圖標簽", l2)
    .set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-基本示例", subtitle="副標題"))
)
# 生成render.html
bar.render()

3、pyecharts繪制折線圖

#導入模塊
import pyecharts.options as opts
from pyecharts.charts import Line
#準備數據
x=['星期一','星期二','星期三','星期四','星期五','星期七','星期日']
y1=[100,200,300,400,100,400,300]
y2=[200,300,200,100,200,300,400]
line=(
    Line()
    .add_xaxis(xaxis_data=x)
    .add_yaxis(series_name="y1線",y_axis=y1,symbol="arrow",is_symbol_show=True)
    .add_yaxis(series_name="y2線",y_axis=y2)
    .set_global_opts(title_opts=opts.TitleOpts(title="Line-雙折線圖"))
)
#生成render.html
line.render()

4、pyecharts繪制柱形折線組合圖

from pyecharts import options as opts
from pyecharts.charts import Bar, Grid, Line
#x軸的值為列表,包含每個月份
x_data = ["{}月".format(i) for i in range(1, 13)]
bar = (
    Bar()
    .add_xaxis(x_data)
#第一個y軸的值、標簽、顏色
    .add_yaxis(
        "降雨量",
        [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 68.6, 22.0, 6.6, 4.3],
        yaxis_index=0,
        color="#5793f3",
    )

# #第二個y軸的值、標簽、顏色
#     .add_yaxis(
#         "蒸發量",
#         [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3],
#         yaxis_index=1,
#         color="#5793f3",
#     )

#右縱坐標
    .extend_axis(
        yaxis=opts.AxisOpts(
            name="降雨量",
            type_="value",
            min_=0,
            max_=250,
            position="right",
            axisline_opts=opts.AxisLineOpts(
                linestyle_opts=opts.LineStyleOpts(color="#d14a61")
            ),
            axislabel_opts=opts.LabelOpts(formatter="{value} ml"),
        )
    )
#左縱坐標
    .extend_axis(
        yaxis=opts.AxisOpts(
            type_="value",
            name="溫度",
            min_=0,
            max_=25,
            position="left",
            axisline_opts=opts.AxisLineOpts(
                linestyle_opts=opts.LineStyleOpts(color="#d14a61")
            ),
            axislabel_opts=opts.LabelOpts(formatter="{value} °C"),
            splitline_opts=opts.SplitLineOpts(
                is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1)
            ),
        )
    )
    .set_global_opts(
        yaxis_opts=opts.AxisOpts(
            name="降雨量",
            min_=0,
            max_=250,
            position="right",
            offset=0,
            axisline_opts=opts.AxisLineOpts(
                linestyle_opts=opts.LineStyleOpts(color="#5793f3")
            ),
            axislabel_opts=opts.LabelOpts(formatter="{value} ml"),
        ),
        title_opts=opts.TitleOpts(title="Grid-多 Y 軸示例"),
        tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),
    )
)
line = (
    Line()
    .add_xaxis(x_data)
    .add_yaxis(
        "平均溫度",
        [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2],
        yaxis_index=2,
        color="#675bba",
        label_opts=opts.LabelOpts(is_show=False),
    )
)
bar.overlap(line)
grid = Grid()
grid.add(bar, opts.GridOpts(pos_left="5%", pos_right="20%"), is_control_axis_index=True)
grid.render()

5、pyecharts繪制散點圖

# 導入模塊
from pyecharts import  options as opts
from pyecharts.charts import Scatter
 
# 設置銷售數據
week = ["周一","周二","周三","周四","周五","周六","周日"]
c =Scatter()     # 散點圖繪制
c.add_xaxis(week)
c.add_yaxis("商傢A",[80,65,46,37,57,68,90])
c.set_global_opts(title_opts=opts.TitleOpts(title="一周的銷售額（萬元）"))    # 設置圖表標題
c.render()

6、pyecharts繪制玫瑰圖

from pyecharts import options as opts
from pyecharts.charts import Pie

label=['Mac口紅','Tom Ford口紅','聖羅蘭','紀梵希','花西子']
values = [100,200,250,350,400]
c = (
    Pie()
    .add(
        "",
        [list(z) for z in zip(label,values)],
        radius=["30%", "75%"],
        center=["50%", "50%"],
        rosetype="radius",
        label_opts=opts.LabelOpts(is_show=False),
    )
    .set_global_opts(title_opts=opts.TitleOpts(title="標題"))
    .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{c} {d}%"))   # 值得一提的是，{d}%為百分比
    .render("玫瑰圖.html")
)

7、pyecharts繪制詞雲圖

# 導入WordCloud及配置模塊
from pyecharts import options as opts
from pyecharts.charts import WordCloud
from pyecharts.globals import SymbolType
 
# 添加詞頻數據
words = [
    ("Sam S Club", 10000),
    ("Macys", 6181),
    ("Amy Schumer", 4386),
    ("Jurassic World", 4055),
    ("Charter Communications", 2467),
    ("Chick Fil A", 2244),
    ("Planet Fitness", 1868),
    ("Pitch Perfect", 1484),
    ("Express", 1112),
    ("Home", 865),
    ("Johnny Depp", 847),
    ("Lena Dunham", 582),
    ("Lewis Hamilton", 555),
    ("KXAN", 550),
    ("Mary Ellen Mark", 462),
    ("Farrah Abraham", 366),
    ("Rita Ora", 360),
    ("Serena Williams", 282),
    ("NCAA baseball tournament", 273),
    ("Point Break", 265),
]
 
# WordCloud模塊，鏈式調用配置，最終生成html文件
c = (
    WordCloud()
    .add("", words, word_size_range=[20, 100], shape=SymbolType.DIAMOND)
    .set_global_opts(title_opts=opts.TitleOpts(title="詞雲圖"))
    .render("wordcloud_diamond.html")
)

8、pyecharts繪制雷達圖

from pyecharts import options as opts
from pyecharts.charts import Radar
v1 = [[8.5,50000,15000,8000,13000,5000]]
v2 = [[8.1,42000,13000,7000,15000,7000]]
def radar_base() ->Radar:
    c = (
        Radar()
        .add_schema(
            schema=[
                opts.RadarIndicatorItem(name='KDA',max_=10),
                opts.RadarIndicatorItem(name='輸出', max_=60000),
                opts.RadarIndicatorItem(name='經濟', max_=20000),
                opts.RadarIndicatorItem(name='生存', max_=10000),
                opts.RadarIndicatorItem(name='推進', max_=20000),
                opts.RadarIndicatorItem(name='刷野', max_=10000),
            ]
        )
        .add(
            '射手',v1,
            color='blue',
            #通過顏色屬性 將其填充
            areastyle_opts=opts.AreaStyleOpts(
                opacity=0.5,
                color='blue'
            ),
        )
        .add(
            '法師',v2,
            color='red',
            areastyle_opts=opts.AreaStyleOpts(
                opacity=0.5,
                color='red'
            ),
        )
        .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
        .set_global_opts(title_opts=opts.TitleOpts(title='英雄成長屬性對比'))
    )
    return c
radar_base().render("雷達圖.html")

9、pyecharts繪制散點圖

from pyecharts import options as opts
from pyecharts.charts import Scatter
from pyecharts.commons.utils import JsCode
from pyecharts.faker import Faker
c = (
    Scatter()
    .add_xaxis(Faker.choose())
    .add_yaxis(
        "商傢A",
        [list(z) for z in zip(Faker.values(), Faker.choose())],
        label_opts=opts.LabelOpts(
            formatter=JsCode(
                "function(params){return params.value[1] +' : '+ params.value[2];}"
            )
        ),
    )
    .set_global_opts(
        title_opts=opts.TitleOpts(title="Scatter散點圖-多維度數據"),
        tooltip_opts=opts.TooltipOpts(
            formatter=JsCode(
                "function (params) {return params.name + ' : ' + params.value[2];}"
            )
        ),
        visualmap_opts=opts.VisualMapOpts(
            type_="color", max_=150, min_=20, dimension=1
        ),
    )
    .render("散點圖.html")
)

10、pyecharts繪制嵌套餅圖

import pyecharts.options as opts
from pyecharts.charts import Pie
from pyecharts.globals import ThemeType
list1  = [300,55,400,110]
attr1 = ["學習", "運動","休息", "娛樂"]
list2  = [40,160,45,35,80,400,35,60]
attr2 = ["閱讀", "上課", "運動", "討論", "編程", "睡覺","聽音樂", "玩手機"]

inner_data_pair = [list(z) for z in zip(attr1, list1)]
outer_data_pair = [list(z) for z in zip(attr2, list2)]
(
    Pie(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
    .add(
        series_name="時長占比",
        data_pair=inner_data_pair,
        radius=[0, "30%"],
        label_opts=opts.LabelOpts(position="inner"),
    )
    .add(
        series_name="時長占比",
        radius=["40%", "55%"],
        data_pair=outer_data_pair,
        label_opts=opts.LabelOpts(
            position="outside",
            formatter="{a|{a}}{abg|}\n{hr|}\n {b|{b}: }{c}  {per|{d}%}  ",
            background_color="#eee",
            border_color="#aaa",
            border_width=1,
            border_radius=4,
            rich={
                "a": {"color": "#999", "lineHeight": 22, "align": "center"},
                "abg": {
                    "backgroundColor": "#e3e3e3",
                    "width": "100%",
                    "align": "right",
                    "height": 22,
                    "borderRadius": [4, 4, 0, 0],
                },
                "hr": {
                    "borderColor": "#aaa",
                    "width": "100%",
                    "borderWidth": 0.5,
                    "height": 0,
                },
                "b": {"fontSize": 16, "lineHeight": 33},
                "per": {
                    "color": "#eee",
                    "backgroundColor": "#334455",
                    "padding": [2, 4],
                    "borderRadius": 2,
                },
            },
        ),
    )
    .set_global_opts(legend_opts=opts.LegendOpts(pos_left="left", orient="vertical"))
    .set_series_opts(
        tooltip_opts=opts.TooltipOpts(
            trigger="item", formatter="{a} <br/>{b}: {c} ({d}%)"
        )
    )
    .render("嵌套餅圖.html")
)

11、pyecharts繪制中國地圖

#導入模塊
from pyecharts import options as opts
from pyecharts.charts import Map
import random
# 設置商傢A所存在的相關省份，並設置初始數量為0
ultraman = [
['四川', 0],
['臺灣', 0],
['新疆', 0],
['江西', 0],
['河南', 0],
['遼寧', 0],
['青海', 0],
['福建', 0],
['西藏', 0]
]

# 設置商傢B存在的相關省份，並設置初始數量為0
monster = [
['廣東', 0],
['北京', 0],
['上海', 0],
['臺灣', 0],
['湖南', 0],
['浙江', 0],
['甘肅', 0],
['黑龍江', 0],
['江蘇', 0]
]
def data_filling(array):
    ''' 
     作用：給數組數據填充隨機數
    '''
    for i in array:
        # 隨機生成1到1000的隨機數
        i[1] = random.randint(1,1000)
data_filling(ultraman)
data_filling(monster)
def create_china_map():
    (
        Map()
        .add(
            series_name="商傢A",
            data_pair=ultraman,
            maptype="china",
            # 是否默認選中，默認為True
            is_selected=True,
            # 是否啟用鼠標滾輪縮放和拖動平移，默認為True
            is_roam=True,
            # 是否顯示圖形標記，默認為True
            is_map_symbol_show=False,
            # 圖元樣式配置
            itemstyle_opts={
                # 常規顯示
                "normal": {"areaColor": "white", "borderColor": "red"},
                # 強調顏色
                "emphasis": {"areaColor": "pink"}
            }
        )
        .add(
            series_name="商傢B",
            data_pair=monster,
            maptype="china",
        )
        # 全局配置項
        .set_global_opts(
            # 設置標題
            title_opts=opts.TitleOpts(title="中國地圖"),
            # 設置標準顯示
            visualmap_opts=opts.VisualMapOpts(max_=1000, is_piecewise=False)
        )
        # 系列配置項
        .set_series_opts(
            # 標簽名稱顯示，默認為True
            label_opts=opts.LabelOpts(is_show=True, color="blue")
        )
        # 生成本地html文件
        .render("中國地圖.html")
    )
    #調用自定義函數
create_china_map()

12、pyecharts繪制世界地圖

from pyecharts import options as opts
from pyecharts.charts import Map
import random
# 設置商傢A所存在的相關國傢，並設置初始數量為0
ultraman = [
['Russia', 0],
['China', 0],
['United States', 0],
['Australia', 0]
]
# 設置商傢B存在的相關國傢，並設置初始數量為0
monster = [
['India', 0],
['Canada', 0],
['France', 0],
['Brazil', 0]
]
def data_filling(array):
    for i in array:
        # 隨機生成1到1000的隨機數
        i[1] = random.randint(1,1000)
        print(i)

data_filling(ultraman)
data_filling(monster)

def create_world_map():
    '''
     作用：生成世界地圖
    '''
    (   # 大小設置
        Map()
        .add(
            series_name="商傢A",
            data_pair=ultraman,
            maptype="world",
        )
        .add(
            series_name="商傢B",
            data_pair=monster,
            maptype="world",
        )
        # 全局配置項
        .set_global_opts(
            # 設置標題
            title_opts=opts.TitleOpts(title="世界地圖"),
            # 設置標準顯示
            visualmap_opts=opts.VisualMapOpts(max_=1000, is_piecewise=False),
        )
        # 系列配置項
        .set_series_opts(
            # 標簽名稱顯示，默認為True
            label_opts=opts.LabelOpts(is_show=False, color="blue")
        )
        # 生成本地html文件
        .render("世界地圖.html")
    )

create_world_map()

到此這篇關於pyecharts繪制各種數據可視化圖表案例附效果+代碼的文章就介紹到這瞭,更多相關pyecharts可視化圖表內容請搜索WalkonNet以前的文章或繼續瀏覽下面的相關文章希望大傢以後多多支持WalkonNet！

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