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Data profiling in Pandas using Python

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  • Difficulty Level : Basic
  • Last Updated : 04 May, 2020
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Pandas is one of the most popular Python library mainly used for data manipulation and analysis. When we are working with large data, many times we need to perform Exploratory Data Analysis. We need to get the detailed description about different columns available and there relation, null check, data types, missing values, etc. So, Pandas profiling is the python module which does the EDA and gives detailed description just with a few lines of code.

Installation:

pip install pandas-profiling

Example:




#import the packages
import pandas as pd
import pandas_profiling
   
# read the file
df = pd.read_csv('Geeks.csv')
   
# run the profile report
profile = df.profile_report(title='Pandas Profiling Report')
   
# save the report as html file
profile.to_file(output_file="pandas_profiling1.html")
   
# save the report as json file
profile.to_file(output_file="pandas_profiling2.json")

Output:

python-data-profiling-1

HTML File:

python-data-profiling-html-file

JSON File:

python-data-profiling-json-file

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