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Data Cleaning and Analysis

Overview

In this course, we will learn about some advanced methods for data cleaning and analysis.

Prerequisites: Python, Statistics, NumPy and Pandas

Syllabus

Data Cleaning

In this section, you will learn how to combine multiple datasets using the Pandas merge and concat operations. Then, we will learn about data transformations, which are pre-processing steps we often apply to the data before analysis. Finally, we will learn about different ways to deal with duplicate data, missing values, and outliers.

Pandas: DataFrame Merge and Concatenation
Free
22 mins
Data Transformations [Under Construction]
11 mins
Handling Duplicates, Missing values and Outliers [Under Construction]
17 mins

End-to-End Project

This is a detailed project for end-to-end data cleaning and analysis. Here, you will use all the skills you have learnt so far to make sense of a real-world dataset.

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Pandas: DataFrame Merge and Concatenation

Category: Data Science and Big Data