In addition to Weibo, there is also WeChat
Please pay attention
WeChat public account
Shulou
2025-01-30 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > Development >
Share
Shulou(Shulou.com)06/01 Report--
This article will explain in detail how pyecharts can realize data visualization. Xiaobian thinks it is quite practical, so share it with you for reference. I hope you can gain something after reading this article.
1. overview
Pyecharts is Baidu open source, suitable for data visualization tools, flexible configuration, relatively beautiful display charts, smooth.
2. installation
Installation in Python 3 environment:
pip3 install pyecharts3. Data visualization code 3.1 histogram from pyecharts import options as optsfrom pyecharts.charts import Barfrom pyecharts.faker import Faker c = ( Bar() .add_xaxis(Faker.choose()) .add_yaxis("Merchant A", Faker.values(), stack="stack1") .add_yaxis("Merchant B", Faker.values(), stack="stack1") .set_series_opts(label_opts=opts.LabelOpts(is_show=False)) .set_global_opts(title_opts=opts.TitleOpts(title="Bar-Stacked Data (All)")) .render("bar_stack0.html"))
Executing the above code will generate mycharts.html file in relative directory, which will be opened through page.
3.2 Line charts import pyecharts.options as optsfrom pyecharts.charts import Line ""Gallery use pyecharts 1.1.0 Reference: https://echarts.apache.org/examples/editor.html? c=line-smooth Currently unavailable function: None "" x_data = ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"]y_data = [820, 932, 901, 934, 1290, 1330, 1320] ( Line() .set_global_opts( tooltip_opts=opts.TooltipOpts(is_show=False), xaxis_opts=opts.AxisOpts(type_="category"), yaxis_opts=opts.AxisOpts( type_="value", axistick_opts=opts.AxisTickOpts(is_show=True), splitline_opts=opts.SplitLineOpts(is_show=True), ), ) .add_xaxis(xaxis_data=x_data) .add_yaxis( series_name="", y_axis=y_data, symbol="emptyCircle", is_symbol_show=True, is_smooth=True, label_opts=opts.LabelOpts(is_show=False), ) .render("smoothed_line_chart.html"))
3.3 pie chart from pyecharts import options as optsfrom pyecharts.charts import Piefrom pyecharts.faker import Faker c = ( Pie() .add( "", [list(z) for z in zip(Faker.choose(), Faker.values())], radius=["40%", "75%"], ) .set_global_opts( title_opts=opts.TitleOpts(title="Pie-Radius"), legend_opts=opts.LegendOpts(orient="vertical", pos_top="15%", pos_left="2%"), ) .set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}")) .render("pie_radius.html"))
About "pyecharts how to achieve data visualization" this article is shared here, I hope the above content can be of some help to everyone, so that you can learn more knowledge, if you think the article is good, please share it to let more people see.
Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.
Views: 0
*The comments in the above article only represent the author's personal views and do not represent the views and positions of this website. If you have more insights, please feel free to contribute and share.
Continue with the installation of the previous hadoop.First, install zookooper1. Decompress zookoope
"Every 5-10 years, there's a rare product, a really special, very unusual product that's the most un
© 2024 shulou.com SLNews company. All rights reserved.