
Pandas for Beginners: Learn Data Analysis with Python
Master basics of Pandas – top python library for data analysis

2 h

Data Manipulation with pandas
Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.

4 h

Analyzing Police Activity with pandas
Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

4 h
pandas Essential Training
Discover how to work with the pandas library and tools for data analysis and data structuring.

2 h 14 m

Streamlined Data Ingestion with pandas
Learn how to get data from common file formats and systems like CSV files, spreadsheets, JSON, SQL databases, and APIs.

4 h

Analyzing Marketing Campaigns with pandas
Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

4 h

Writing Efficient Code with pandas
Learn efficient techniques in pandas to optimize your Python code.

4 h
Faster pandas
Discover how to make your pandas code faster and more efficient. This course covers vectorization, common errors, pandas performance, memory management, Numba, Cython, and other topics.

1 h 24 m

Reshaping Data with pandas
Reshape DataFrames from wide to long, stack and unstack rows and columns, and deal with multi-index DataFrames.

4 h

Introduction to pandas Course
Pandas provides fast, flexible, and expressive data structures that have been designed to make working with relational or “labeled” data not only easy, but also intuitive

3 h 35 m

Data Wrangling with Pandas for Machine Learning Engineers
Pandas has become the gold standard for data wrangling in applied machine learning.

1 h

Data Wrangling with Pandas for Machine Learning Engineers
This course will teach you the basics of data wrangling in Python using Pandas, including basic syntax, functions, and dataframe manipulation.

1 h

Pandas Playbook: Manipulating Data
This course focuses on the core functionalities of Pandas for data wrangling, teaching you how to tackle everyday tasks for a data analyst, or data scientist.

2 h 25 m
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