You're reading from The Data Analysis Workshop

Product typeBook

Published inJul 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781839211386

Edition1st Edition

Languages

Python

Tools

Jupyter

Concepts

Data Science

Authors (3):

Gururajan Govindan

Shubhangi Hora

Konstantin Palagachev

View More author details

Splitting the Features

In the previous section, we saw how the missing values are filled with different types of imputation.

In this section, we will be splitting the dependent variables in the DataFrame into y and the independent variables into X. The dependent variables are an outcome of a process. In our case, this process is whether a company is bankrupt or not. Independent variables (also called features) are the input to our process, which in this case is the rest of the variables.

Splitting the features acts as a precursor to our next step, where we select the most important X variables that determine the dependent variable.

We will need to split the features for mean-imputed DataFrames, as shown in the following code:

#First DataFrame
X0=mean_imputed_df1.drop('Y',axis=1)
y0=mean_imputed_df1.Y
#Second DataFrame
X1=mean_imputed_df2.drop('Y',axis=1)
y1=mean_imputed_df2.Y
#Third DataFrame
X2=mean_imputed_df3.drop('Y',axis=1)
y2=mean_imputed_df3...

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The Data Analysis Workshop

Published in: Jul 2020Publisher: PacktISBN-13: 9781839211386

Authors (3)

Gururajan Govindan

Gururajan Govindan is a data scientist, intrapreneur, and trainer with more than seven years of experience working across domains such as finance and insurance. He is also an author of The Data Analysis Workshop, a book focusing on data analytics. He is well known for his expertise in data-driven decision-making and machine learning with Python.
Read more about Gururajan Govindan

Shubhangi Hora

Shubhangi Hora is a data scientist, Python developer, and published writer. With a background in computer science and psychology, she is particularly passionate about healthcare-related AI, including mental health. Shubhangi is also a trained musician.
Read more about Shubhangi Hora

Konstantin Palagachev

Konstantin Palagachev holds a Ph.D. in applied mathematics and optimization, with an interest in operations research and data analysis. He is recognized for his passion for delivering data-driven solutions and expertise in the area of urban mobility, autonomous driving, insurance, and finance. He is also a devoted coach and mentor, dedicated to sharing his knowledge and passion for data science.
Read more about Konstantin Palagachev

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Splitting the Features

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