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本篇內(nèi)容介紹了“怎么使用pyecharts繪制各種數(shù)據(jù)可視化圖表”的有關(guān)知識(shí)，在實(shí)際案例的操作過(guò)程中，不少人都會(huì)遇到這樣的困境，接下來(lái)就讓小編帶領(lǐng)大家學(xué)習(xí)一下如何處理這些情況吧！希望大家仔細(xì)閱讀，能夠?qū)W有所成！
# 導(dǎo)入模塊
from pyecharts import options as opts
from pyecharts.charts import Pie
#準(zhǔn)備數(shù)據(jù)
label=['Mac口紅','Tom Ford口紅','圣羅蘭','紀(jì)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(shù)
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=":{c} jgc7tqi%")) # 值得一提的是，esmrar2%為百分比
)
return c
# 調(diào)用自定義函數(shù)生成render.html
pie_base().render()
#導(dǎo)入模塊
from pyecharts.globals import ThemeType
from pyecharts import options as opts
from pyecharts.charts import Bar
#準(zhǔn)備數(shù)據(jù)
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(biāo)簽", l2)
.set_global_opts(title_opts=opts.TitleOpts(title="柱狀圖-基本示例", subtitle="副標(biāo)題"))
)
# 生成render.html
bar.render()
#導(dǎo)入模塊 import pyecharts.options as opts from pyecharts.charts import Line #準(zhǔn)備數(shù)據(jù) 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()
from pyecharts import options as opts
from pyecharts.charts import Bar, Grid, Line
#x軸的值為列表,包含每個(gè)月份
x_data = ["{}月".format(i) for i in range(1, 13)]
bar = (
Bar()
.add_xaxis(x_data)
#第一個(gè)y軸的值、標(biāo)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(gè)y軸的值、標(biāo)簽、顏色
# .add_yaxis(
# "蒸發(fā)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(biāo)
.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(biāo)
.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()
# 導(dǎo)入模塊
from pyecharts import options as opts
from pyecharts.charts import Scatter
# 設(shè)置銷售數(shù)據(jù)
week = ["周一","周二","周三","周四","周五","周六","周日"]
c =Scatter() # 散點(diǎn)圖繪制
c.add_xaxis(week)
c.add_yaxis("商家A",[80,65,46,37,57,68,90])
c.set_global_opts(title_opts=opts.TitleOpts(title="一周的銷售額（萬(wàn)元）")) # 設(shè)置圖表標(biāo)題
c.render()
from pyecharts import options as opts
from pyecharts.charts import Pie
label=['Mac口紅','Tom Ford口紅','圣羅蘭','紀(jì)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(biāo)題"))
.set_series_opts(label_opts=opts.LabelOpts(formatter=":{c} b1uyqlt%")) # 值得一提的是，fpzqvuv%為百分比
.render("玫瑰圖.html")
)
# 導(dǎo)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(shù)據(jù)
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?zhǔn)秸{(diào)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="詞云圖"))
.render("wordcloud_diamond.html")
)
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(jīng)濟(jì)', max_=20000),
opts.RadarIndicatorItem(name='生存', max_=10000),
opts.RadarIndicatorItem(name='推進(jìn)', max_=20000),
opts.RadarIndicatorItem(name='刷野', max_=10000),
]
)
.add(
'射手',v1,
color='blue',
#通過(guò)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(zhǎng)屬性對(duì)比'))
)
return c
radar_base().render("雷達(dá)圖.html")
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(
"商家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(diǎn)圖-多維度數(shù)據(jù)"),
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(diǎn)圖.html")
)
import pyecharts.options as opts
from pyecharts.charts import Pie
from pyecharts.globals import ThemeType
list1 = [300,55,400,110]
attr1 = ["學(xué)習(xí)", "運(yùn)動(dòng)","休息", "娛樂(lè)"]
list2 = [40,160,45,35,80,400,35,60]
attr2 = ["閱讀", "上課", "運(yùn)動(dòng)", "討論", "編程", "睡覺(jué)","聽(tīng)音樂(lè)", "玩手機(jī)"]
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(shí)長(zhǎng)占比",
data_pair=inner_data_pair,
radius=[0, "30%"],
label_opts=opts.LabelOpts(position="inner"),
)
.add(
series_name="時(shí)長(zhǎng)占比",
radius=["40%", "55%"],
data_pair=outer_data_pair,
label_opts=opts.LabelOpts(
position="outside",
formatter="{a|{a}}{abg|}\n{hr|}\n {b|: }{c} {per|agvrxmu%} ",
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/>: {c} (v34pagn%)"
)
)
.render("嵌套餅圖.html")
)
#導(dǎo)入模塊
from pyecharts import options as opts
from pyecharts.charts import Map
import random
# 設(shè)置商家A所存在的相關(guān)省份，并設(shè)置初始數(shù)量為0
ultraman = [
['四川', 0],
['臺(tái)灣', 0],
['新疆', 0],
['江西', 0],
['河南', 0],
['遼寧', 0],
['青海', 0],
['福建', 0],
['西藏', 0]
]
# 設(shè)置商家B存在的相關(guān)省份，并設(shè)置初始數(shù)量為0
monster = [
['廣東', 0],
['北京', 0],
['上海', 0],
['臺(tái)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(shù)組數(shù)據(jù)填充隨機(jī)數(shù)
'''
for i in array:
# 隨機(jī)生成1到1000的隨機(jī)數(shù)
i[1] = random.randint(1,1000)
data_filling(ultraman)
data_filling(monster)
def create_china_map():
(
Map()
.add(
series_name="商家A",
data_pair=ultraman,
maptype="china",
# 是否默認(rèn)選中，默認(rèn)為True
is_selected=True,
# 是否啟用鼠標(biāo)滾輪縮放和拖動(dòng)平移，默認(rèn)為True
is_roam=True,
# 是否顯示圖形標(biāo)記，默認(rèn)為True
is_map_symbol_show=False,
# 圖元樣式配置
itemstyle_opts={
# 常規(guī)顯示
"normal": {"areaColor": "white", "borderColor": "red"},
# 強(qiáng)調(diào)顏色
"emphasis": {"areaColor": "pink"}
}
)
.add(
series_name="商家B",
data_pair=monster,
maptype="china",
)
# 全局配置項(xiàng)
.set_global_opts(
# 設(shè)置標(biāo)題
title_opts=opts.TitleOpts(title="中國(guó)地圖"),
# 設(shè)置標(biāo)準(zhǔn)顯示
visualmap_opts=opts.VisualMapOpts(max_=1000, is_piecewise=False)
)
# 系列配置項(xiàng)
.set_series_opts(
# 標(biāo)簽名稱顯示，默認(rèn)為True
label_opts=opts.LabelOpts(is_show=True, color="blue")
)
# 生成本地html文件
.render("中國(guó)地圖.html")
)
#調(diào)用自定義函數(shù)
create_china_map()
from pyecharts import options as opts
from pyecharts.charts import Map
import random
# 設(shè)置商家A所存在的相關(guān)國(guó)家，并設(shè)置初始數(shù)量為0
ultraman = [
['Russia', 0],
['China', 0],
['United States', 0],
['Australia', 0]
]
# 設(shè)置商家B存在的相關(guān)國(guó)家，并設(shè)置初始數(shù)量為0
monster = [
['India', 0],
['Canada', 0],
['France', 0],
['Brazil', 0]
]
def data_filling(array):
for i in array:
# 隨機(jī)生成1到1000的隨機(jī)數(shù)
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(shè)置
Map()
.add(
series_name="商家A",
data_pair=ultraman,
maptype="world",
)
.add(
series_name="商家B",
data_pair=monster,
maptype="world",
)
# 全局配置項(xiàng)
.set_global_opts(
# 設(shè)置標(biāo)題
title_opts=opts.TitleOpts(title="世界地圖"),
# 設(shè)置標(biāo)準(zhǔn)顯示
visualmap_opts=opts.VisualMapOpts(max_=1000, is_piecewise=False),
)
# 系列配置項(xiàng)
.set_series_opts(
# 標(biāo)簽名稱顯示，默認(rèn)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()
“怎么使用pyecharts繪制各種數(shù)據(jù)可視化圖表”的內(nèi)容就介紹到這里了，感謝大家的閱讀。如果想了解更多行業(yè)相關(guān)的知識(shí)可以關(guān)注億速云網(wǎng)站，小編將為大家輸出更多高質(zhì)量的實(shí)用文章！
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