Python Data Visualization

Box Plot:

Box Plot is the visual representation of the depicting groups of numerical data through their quartiles. Boxplot is also used for detect the outlier in data set. It captures the summary of the data efficiently with a simple box and whiskers and allows us to compare easily across groups. Boxplot summarizes a sample data using 25th, 50th and 75th percentiles. These percentiles are also known as the lower quartile, median and upper quartile. A box plot consist of 5 things.

• Minimum
• First Quartile or 25%
• Median (Second Quartile) or 50%
• Third Quartile or 75%
• Maximum

Histograms and Density Plots:

Histograms and density plots show the frequency of a numeric variable aloing the y-axix, and the value along the x-axis. The sns.distplot() function plots a density curve. This plot is aesthetically better than vanilla matplotlib. In y-axis it plots the probability.

Rug Plot: This plots the actual data points as small vertical bars. The rug plot is simply specified as an argument of the distplot( ).

Bivariate Distributions:

Bivarite distributions are simply two univariate distributions plotted on x and y axes respectively. They help you observe the relationship between two variables. They are also called joint distributions using sns.jointplot( ).