Data Wrangling with Python Project

In this introductory week, you will gain an understanding of the data wrangling pipeline, which serves as a structured approach to transform raw data into a cleaned and organized dataset for analysis. You will learn the key stages involved in the pipeline, setting the foundation for the rest of the course.

In this week, you will learn how to identify and define the scope and objectives of your data wrangling project. You will explore various data sources, understand their structure, and assess the suitability of each source for the project.

This week covers the data collection and integration stage of the data wrangling process. You will learn techniques for data collection, validate the collected data, and integrate data from multiple sources.

This week focuses on gaining a comprehensive understanding of the dataset through statistical analysis and data visualization. You will learn how to perform descriptive statistics, create informative visualizations, and conduct exploratory data analysis (EDA).

In this week, you will delve into essential data processing and manipulation techniques. You will learn how to handle missing values, detect and handle outliers, perform data sampling and dimensionality reduction, apply data scaling and discretization, and explore data cubes and pivot tables.