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This article will explain in detail how to draw a column chart in Python. The content of the article is of high quality, so the editor will share it for you as a reference. I hope you will have a certain understanding of the relevant knowledge after reading this article.

If you do not have PyEcharts installed, install PyEcharts first:

Data = pd.read_excel ('DGyGYQ. Xlsx') # descending order data = data.sort_values (by= ['add'], ascending= [False]) by adding new fields

Once PyEcharts is installed, you can import the modules you need to use:

C = (# create histogram object and set the size, or not, use the default size directly to Bar (init_opts=opts.InitOpts (width= "800px", height= "400px")) # set the X-axis data series, take only the first 10 data, and convert to the list format .add _ xaxis (data. Province [: 10] .tolist () # sets Y-axis data series and display color. Only the first 10 data are taken and converted to list format. Add _ yaxis (", data. Add [: 10] .tolist () # set the title and location of the chart. Set _ global_opts (title_opts=opts.TitleOpts (title= "add TOP10", pos_left= "center")) # render the bar chart to html .render ("bar chart .html") through the render () method

Import data:

C = (# create histogram object and set the size, or not, use the default size directly to Bar (init_opts=opts.InitOpts (width= "800px", height= "400px")) # set the X-axis data series, take only the first 10 data, and convert to the list format .add _ xaxis (data. Province [: 10] .tolist () # sets Y-axis data series and display color. Only the first 10 data are taken and converted to list format. Add _ yaxis (", data. Add [: 10] .tolist () # set the title and location of the chart. Set _ global_opts (title_opts=opts.TitleOpts (title= "add TOP10", pos_left= "center")) # render the bar chart to html .render ("bar chart .html") through the render () method

Then you can draw a column chart:

C = (# create histogram object and set the size, or not, use the default size directly to Bar (init_opts=opts.InitOpts (width= "800px", height= "400px")) # set the X-axis data series, take only the first 10 data, and convert to the list format .add _ xaxis (data. Province [: 10] .tolist () # sets Y-axis data series and display color. Only the first 10 data are taken and converted to list format. Add _ yaxis (", data. Add [: 10] .tolist () # set the title and location of the chart. Set _ global_opts (title_opts=opts.TitleOpts (title= "add TOP10", pos_left= "center")) # render the bar chart to html .render ("bar chart .html") through the render () method

The effect is as follows:

C = (Bar (init_opts=opts.InitOpts (width= "800px", height= "400px")) .add _ xaxis (data. Province [: 10] .tolist () .add _ yaxis ("accumulate", data. Number of confirmed cases [: 10] .tolist () .add _ yaxis ("add", data. Add [: 10] .tolist () .set _ global_opts (title_opts=opts.TitleOpts (title= "TOP10")) .render ("histogram .html"))

The effect of the multi-data series column chart drawn is as follows:

C = (Bar (init_opts=opts.InitOpts (width= "800px", height= "400px")) .add _ xaxis (data. Province [: 10] .tolist () # sets Y axis data series and display color. Add _ yaxis (", data. Add [: 10] .tolist (), color='#FF1493') .set _ global_opts (title_opts=opts.TitleOpts (title= "add TOP10", pos_left= "center") .render ("column chart .html")) about how to draw a column chart in Python. I hope the above content can be of some help and learn more knowledge. If you think the article is good, you can share it for more people to see.

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