histogram

Description

Makes an histogram plot of all numerical features. Helps to show uni-variate distribution of the features.

histogram(data=None, num_features=None, bins=None, show_dist_type=False, fig_size=(5,5), save_fig=False):
    '''
    Parameters
    ------------
        data : DataFrame, array, or list of arrays.
            Dataset for plotting.
       
         num_features: Scalar, array, or list. 
            The numerical features in the dataset, if not None, 
            we try to infer the numerical columns from the dataframe.
        
        bins: int
            The number of bins to use.
        
        show_dist_type: bool, Default False
            If True, Calculates the skewness of the data and display one of (Left skewed, right skewed or normal) 
        
        fig_size: tuple, Default (8,8).
            The size of the figure object.
        
        save_fig: bool, Default False.
            If True, saves the current plot to the current working directory
    
    '''

Examples

We are using the classic iris data set and a Jupyter notebook in the following examples.

An histogram can be created for every column in a DataFrame:

import pandas as pd
import datasist as ds #import datasist library

df = pd.read_csv('iris.csv')
vs.histogram(data=df)

A bin can specified when plotting an histogram:

vs.histogram(data=df, bins=15)

To improve this documentation, visit the datasist-doc repository