Data wrangling in Python refers to the process of cleaning, transforming, and organizing raw data into a more structured format for analysis. It involves tasks such as data cleaning, data integration, handling missing values, data formatting, and feature engineering.
Data analysts can best utilize data wrangling in Python to ensure the data is reliable, consistent, and suitable for analysis. In this video, Gaelim shares 12 essential Data Wrangling functions in Python to be familiar with.
*****Video Details*****
00:00 Introduction
00:38 Dataset 1
00:42 Libraries to import
01:16 Dataset 2
01:35 Merging data set
02:13 Droping columns
02:44 Fill missing values
03:15 Replacing missing values
03:44 Replacing a specific value
04:25 Replacing Continue reading “12 Data Wrangling Functions In Python That You Should Know”