Remove Null Values From Excel File Using Python | Remove Empty Cells Using Python | Pandas | Python

Published: 18 July 2020
on channel: Falcon Infomatic

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Introduction:
Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

Problem Statement:
Sometimes CSV file has null values, which are later displayed as NaN in Data Frame.

Solution:
Pandas dropna() method allows the user to analyze and drop Rows/Columns with Null values in different ways.

Syntax:
DataFrameName.dropna(axis=0, how='any', thresh=None, subset=None, inplace=False)

Parameters:
axis: axis takes int or string value for rows/columns. Input can be 0 or 1 for Integer and ‘index’ or ‘columns’ for String.
how: how takes string value of two kinds only (‘any’ or ‘all’). ‘any’ drops the row/column if ANY value is Null and ‘all’ drops only if ALL values are null.
thresh: thresh takes integer value which tells the minimum amount of na values to drop.
subset: It’s an array which limits the dropping process to passed rows/columns through the list.
inplace: It is a boolean which makes the changes in data frame itself if True.

Source Code & Link:
https://drive.google.com/drive/folder...

If you have any doubts please let me know in the comment section.

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