{"id":159,"date":"2017-12-29T16:02:43","date_gmt":"2017-12-29T16:02:43","guid":{"rendered":"https:\/\/fcpython.com\/?p=159"},"modified":"2020-12-18T20:09:26","modified_gmt":"2020-12-18T20:09:26","slug":"lollipop-charts-in-matplotlib","status":"publish","type":"post","link":"https:\/\/fcpython.com\/visualisation\/lollipop-charts-in-matplotlib","title":{"rendered":"Lollipop Charts in Matplotlib"},"content":{"rendered":"
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Matplotlib’s chart functions are quite simple and allow us to create graphics to our exact specification.<\/p>\n

The example below will plot the Premier League table from the 16\/17 season, taking you through the basics of creating a bar chart and customising some of its features. First of all, let’s get our modules loaded and data in place.<\/p>\n<\/div>\n<\/div>\n<\/div>\n

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import<\/span> pandas<\/span> as<\/span> pd<\/span>\r\nimport<\/span> numpy<\/span> as<\/span> np<\/span>\r\nimport<\/span> matplotlib.pyplot<\/span> as<\/span> plt<\/span>\r\n\r\n#This next line makes our charts show up in the notebook<\/span>\r\n%<\/span>matplotlib<\/span> inline\r\n\r\ntable<\/span> =<\/span> pd<\/span>.<\/span>read_csv<\/span>(<\/span>\"..\/..\/data\/1617table.csv\"<\/span>)<\/span>\r\ntable<\/span>.<\/span>head<\/span>()<\/span>\r\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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