Seaborn in Python

(Using Jupyter Notebook)

Seaborn is a library for making statistical graphics in Python. It is built on top of matplotlib and closely integrated with pandas data structures. Seaborn aims to make visualization a central part of exploring and understanding data. Its dataset-oriented plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots.

To view its working, open Jupyter Notebook and create one. After creating new notebook, here are some steps to follow.

Firstly, import following libraries.

importing libraries

To use .csv file,

loading .csv file (dataset)

Now call this dataset, to view it.

call dataset by name and load it

Now, use ‘seaborn’ for graphical representation.

loading dataset for graphical representation

For ‘regplot’ :

regplot

For ‘catplot’ :

catplot

If we use random numbers :

random numbers

Now use ‘seaborn’ view it graphically.

graphical representation

To change color:

when color is green

To assign ‘name’ to x-axis :

naming axis

graphical representation

To change position :

when vertical is true

Ignoring histogram :

When histogram is false

For rug plot :

rugplot

Readers! here are some uses to ‘seaborn in python’. If you like my article, don’t forget to clap.

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