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
Advanced Pandas
Learn to handle complex data-sets and analyze your data in a principled way with Pandas.
2 h 5 m
Pandas Playbook: Visualization
In this course, you will learn how to create a wide range of plots for your data, and how to customize them to make them both attractive and informative for your audience.
2 h 18 m
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
Data Wrangling with Pandas for Machine Learning Engineers
Pandas has become the gold standard for data wrangling in applied machine learning.
1 h
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