scatterplot

Description

Makes a scatter plot of numerical features against a numerical target. Helps to show the relationship between features.

scatterplot(data=None, 
            num_features=None, 
            target=None, 
            separate_by=None, 
            fig_size=(5,5), 
            save_fig=False):
    '''
    Parameters
    ------------
    
        data : DataFrame, array, or list of arrays.
            The data to plot.
        num_features: int/floats, scalar, array, or list. 
            The numeric features in the dataset, if not provided, 
            we try to infer the numeric columns from the dataframe.
        target: int/float, scalar, array or list.
            Numerical target feature to plot against.
        separate_by: str, default None.
            The feature used to seperate the plot. Called hue in seaborn.
        fig_size: tuple, Default (10,10)
            The size of the figure object.
        save_fig: bool, Default False.
            Saves the plot to the current working directory
        
    '''

Examples

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

Scatterplots can be created for every column in a DataFrame and separated by a specified target:

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

df = pd.read_csv('iris.csv')
vs.scatterplot(data=df, target='species')

A scatterplot can separated by a categorical target:

vs.scatterplot(data=df,
                target='petal_width', 
                separate_by='species')

To improve this documentation, visit the datasist-doc repository