python数据分析pyecharts【饼状图、直方图、词云、地图】

本文主要是介绍python数据分析pyecharts【饼状图、直方图、词云、地图】，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

饼状图

直方图

词云

地图

饼状图

from pyecharts.charts import Pie
from pyecharts import options as optsdata = {'神农架林区': 2.6016,'恩施州': 3.0729,'十堰市': 3.4300,'宜昌市': 3.4555,'襄阳市': 4.0543,'咸宁市': 4.1145,'荆门市': 4.1777,'潜江市': 4.2574,'黄冈市': 4.4093,'黄石市': 4.4914,'随州市': 4.6480,'鄂州市': 4.8873,'荆州市': 4.9619,'仙桃市': 5.0019,'天门市': 5.0204,'孝感市': 5.0245,'武汉市': 5.3657}
x_data = [i for i in data.keys()]
y_data = [i for i in data.values()]
pie = Pie()
pie.width = "1500px"
pie.add("", [list(z) for z in zip(x_data, y_data)], radius=["40%", "75%"])
pie.set_global_opts(title_opts=opts.TitleOpts(title="2023年1~9月17个城市地表水环境质量状况排名", pos_bottom="0px", pos_left="36.5%"))
# b为x轴，c为y轴，d为百分比
pie.set_series_opts(label_opts=opts.LabelOpts(formatter="{b} {d}%"))
pie.render("饼状图.html")

直方图

import pyecharts.options as opts
from pyecharts.charts import Bardata = {'神农架林区': 2.6016,'恩施州': 3.0729,'十堰市': 3.4300,'宜昌市': 3.4555,'襄阳市': 4.0543,'咸宁市': 4.1145,'荆门市': 4.1777,'潜江市': 4.2574,'黄冈市': 4.4093,'黄石市': 4.4914,'随州市': 4.6480,'鄂州市': 4.8873,'荆州市': 4.9619,'仙桃市': 5.0019,'天门市': 5.0204,'孝感市': 5.0245,'武汉市': 5.3657}
x_data = [i for i in data.keys()]
y_data = [i for i in data.values()]
bar = Bar()
bar.width = '1500px'
bar.add_yaxis("2023年1~9月17个城市地表水环境质量状况排名", y_data, color='#85C1E9')
bar.add_xaxis(x_data)
# bar.set_global_opts(xaxis_opts=opts.AxisOpts(name="城市"),yaxis_opts=opts.AxisOpts(name="CWQI"))
# bar.set_global_opts(xaxis_opts=opts.AxisOpts(name="城市", axislabel_opts={"rotate":45}),yaxis_opts=opts.AxisOpts(name="CWQI"))
bar.set_global_opts(xaxis_opts=opts.AxisOpts(name="城市", axislabel_opts={"interval": "0"}),yaxis_opts=opts.AxisOpts(name="CWQI"))
bar.render("直方图.html")

词云

from pyecharts.charts import WordCloud
from collections import Counter
import jieba# 读取网页并过滤
with open("网页内容.txt", encoding="utf8") as f:asd = f.read()
# 分词后-》过滤-》计算频率
asds = jieba.lcut(asd)
wordCount = []
for asd in asds:if (len(asd) > 1):wordCount.append(asd)
word_counter = Counter(wordCount)
words_list = word_counter.most_common(10000)
print(words_list)
wc = WordCloud()
wc.width = "1500px"
wc.add("", data_pair=words_list)
wc.render("词云.html")

地图

from pyecharts.charts import Map
from pyecharts import options as opts
data = {'神农架林区': 2.6016,
#'恩施土家族苗族自治州': 3.0729,'十堰市': 3.4300,'宜昌市': 3.4555,'襄阳市': 4.0543,'咸宁市': 4.1145,'荆门市': 4.1777,'潜江市': 4.2574,'黄冈市': 4.4093,'黄石市': 4.4914,'随州市': 4.6480,'鄂州市': 4.8873,'荆州市': 4.9619,'仙桃市': 5.0019,'天门市': 5.0204,'孝感市': 5.0245,'武汉市': 5.3657}
x_data = [i for i in data.keys()]
y_data = [i for i in data.values()]
map=Map()
map.width="1500px"
map.height="650px"
map.add("",[list(z) for z in zip(x_data,y_data)],"湖北")
# map.set_global_opts(visualmap_opts=opts.VisualMapOpts(is_show=True))
map.set_global_opts(visualmap_opts=opts.VisualMapOpts(is_show=True,max_=max(y_data),min_=(min(y_data))))
map.render(path="地图.html")