Begin your data analysis journey with Python by mastering the fundamentals of the pandas library
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Master Data Analysis with Python - Intro to Pandas 2022 targets those who want to completely master doing data analysis with pandas. This course provides an introduction to the two primary pandas objects, the DataFrame and Series. This is a brand new free course updated for the latest version of pandas.
This course is taught by expert instructor Ted Petrou, author of the highly-rated text books Pandas Cookbook and Master Data Analysis with Python. Ted has taught over 1,000 hours of live in-person data science courses that use the pandas library. Pandas is a difficult library to use effectively and is often taught incorrectly with poor practices. Ted is extremely adept at using pandas and is known for developing best practices on how to use the library.
All of the material and exercises are written in Jupyter Notebooks available for you to download. This allows you to read the notes, run the code, and write solutions to the exercises all in a single place.
This course targets those who have an interest in becoming experts and completely mastering the pandas library for data analysis in a professional environment. This course does not cover all of the pandas library, just a small and fundamental portion of it. If you are looking for a brief introduction of the entire pandas library, this course is not it. It takes many dozens of hours, lots of practice, and rigorous understanding to be successful using pandas for data analysis in a professional environment.
Intro to Pandas is first in the Master Data Analysis with Python series which includes the following sequence of courses:
Intro to Pandas
Selecting Subsets of Data with Pandas
Essential Pandas Commands
Grouping Data with Pandas
Time Series with Pandas
Cleaning Data with Pandas
Joining Data with Pandas
Data Visualization
Advanced Pandas
Exploratory Data Analysis
This course assumes no previous pandas experience. The only prerequisite knowledge is to understand the fundamentals of Python.
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