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Learn about data science tools
Updated on Sep, 2026
Programming, Data Science, Python
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Pandas is the most demanding python library for Data Science, it comes with a plethora of tools. It provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real-world data analysis in Python.
If you are planning to develop or improve your career in Data Science or Machine Learning, is a must to learn about Pandas.
This Course of Pandas offers a complete view of this powerful tool for implementing data analysis, data cleaning, data transformation, different data formats, text manipulation, regular expressions, data I/O, data statistics, data visualization, time series and more.
What you see in the course?
Data Series and Dataframes,
Indexing and Multi Indexing,
Group data by condition,
Concat, Append, Join,
Pandas and Categorical Data,
Explorative data analysis,
Utility functions and custom functions,
Regular expressions,
Data transformation,
Time series and more.
This course is a practical course with many examples because the easiest way to learn is by practicing!, we'll integrate all the knowledge we have learned in a Capstone Project, developing a preliminary analysis, cleaning, filtering, transforming, and visualising data using the famous IMDB dataset.
How Pandas library works with it's building blocks
Know a complete Panda's set of tools for data analysis, data manipulation and data visualization
Practical examples including time series and the analysis of finantial market
Learn advanced tools from Pandas such as Time Series, Text Manipulation, Regular expressions and more
Check out the detailed breakdown of what’s inside the course
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