Exploratory Data Analysis with Python

2 tutorials

In the Pandas In Python module, we got you familiar with Pandas, a frequently used Python library for cleaning and manipulating data. In this module, we’ll reinforce certain concepts taught and focus on how to use Pandas for Exploratory Data Analysis (EDA). Pandas is a really powerful library that anyone working with data in Python should be familiar with.

We’ll also be covering another oft-used library in Python for EDA - Seaborn. This library is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn is also another powerful tool that should be in the toolkit of any budding data scientist/analyst.

Helpful prior knowledge


Learning Outcomes

By the end of this module, players would have:

  • Learnt and applied basic EDA concepts.
  • Sufficient skills to manipulate data in a dataset.
  • Experienced using Pandas and Seaborn to answer EDA queries.
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