The key to make good visuzlization is to start with something basic, and iterate over to make it better. One can clearly see the trend in the data. The pandas boxplot looks okay for a for first pass analysis. Let us say we want to plot a boxplot of life expectancy by continent, we would use pandas like One way to plot boxplot using pandas dataframe is to use boxplot function that is part of pandas. Once you have created a pandas dataframe, one can directly use pandas plotting option to plot things quickly. Python’s pandas have some plotting capabilities. We will plot boxplots in four ways, first with using Pandas’ boxplot function and then use Seaborn plotting library in three ways to get a much improved boxplot. We will use pandas to filter and subset the original dataframe. Let us filter the gapminder data such that we will keep gapminder data from all countries but only for the year 2007. Pandas’ read_csv can easily load the data as a dataframe from a URL. We will directly download the gapminder data from Software Carpentry github page. Let us load the gapminder data to make boxplots. Let us first load the necessary packages needed to plot boxplots in Python. In this post, we will see how to make boxplots using Python’s Pandas and Seaborn. If you are interested in learning more about the history and evolution of boxplots, check out Hadley Wickham’s 2011 paper 40 years of Boxplots. The advantage of comparing quartiles is that they are not influenced by outliers. These percentiles are also known as the lower quartile, median and upper quartile. Boxplots summarizes a sample data using 25th, 50th and 75th percentiles. Boxplot captures the summary of the data efficiently with a simple box and whiskers and allows us to compare easily across groups. Boxplot, introduced by John Tukey in his classic book Exploratory Data Analysis close to 50 years ago, is great for visualizing data distributions from multiple groups.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |