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Data cleansing using python: handling missing data values, outliers, and standardized values.

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agungbudiwirawan/Data_Science_in_Telco-Data_Cleansing

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Data Science in Telco: Data Cleansing

Overview

The goal of this project is to clean the data before it is processed. Data cleaning, such as handling duplication of values, overcoming missing values, overcoming outliers, and standardizing values.

Library

  • Pandas
  • Matplotlib

Algorithm

  • Handling missing values by droping rows
  • Handling missing values by filling them using the median
  • Handling outliers by interquartile range
  • Standardizing the value by replacing the value

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Data cleansing using python: handling missing data values, outliers, and standardized values.

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