{"id":169,"date":"2017-12-29T16:02:43","date_gmt":"2017-12-29T16:02:43","guid":{"rendered":"https:\/\/fcpython.com\/?p=169"},"modified":"2020-12-18T20:09:26","modified_gmt":"2020-12-18T20:09:26","slug":"boxplots-in-seaborn","status":"publish","type":"post","link":"https:\/\/fcpython.com\/visualisation\/boxplots-in-seaborn","title":{"rendered":"Boxplots in Seaborn"},"content":{"rendered":"
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Boxplots are a relatively common chart type used to show distribution of numeric variables. The box itself will display the middle 50% of values, with a line showing the median value. The whiskers of the box show the highest and lowest values, excluding any outliers.<\/p>\n

This article will plot some data series of a teams’ player ages. This should allow us to compare the age profiles of teams quite easily and spot teams with young or aging squads.<\/p>\n

Let’s get our modules imported along with a data frame of player information.<\/p>\n<\/div>\n<\/div>\n<\/div>\n

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<\/span>import<\/span> pandas<\/span> as<\/span> pd<\/span>\r\nimport<\/span> seaborn<\/span> as<\/span> sns<\/span>\r\nimport<\/span> matplotlib.pyplot<\/span> as<\/span> plt<\/span>\r\n%<\/span>matplotlib<\/span> inline\r\n\r\n\r\ndata<\/span> =<\/span> pd<\/span>.<\/span>read_csv<\/span>(<\/span>"..\/..\/Data\/Violin.csv"<\/span>,<\/span> encoding<\/span> =<\/span> "ISO-8859-1"<\/span>)<\/span>\r\n\r\ndata<\/span>.<\/span>head<\/span>()<\/span>\r\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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