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A collection of exercises for practicing pandas, the Python data analysis library, organized by topic like filtering, grouping, merging, and visualization.
A collection of exercises for practicing pandas, the Python data analysis library, organized by topic like filtering, grouping, merging, and visualization.Is this a tutorial or a set of practice problems?It's a set of practice exercises, not a tutorial. For each topic there are three files: exercise instructions, solutions without code, and solutions with code and comments.
It's a set of practice exercises, not a tutorial. For each topic there are three files: exercise instructions, solutions without code, and solutions with code and comments.How is the content organized and where do I start?Exercises are grouped into topics such as Getting and knowing, Filtering and Sorting, Grouping, Apply, Merge, Stats, Visualization, Creating Series and DataFrames, Time Series, and Deleting, each with multiple dataset-based exercises (e.g. Chipotle, Titanic, Pokemon).
Exercises are grouped into topics such as Getting and knowing, Filtering and Sorting, Grouping, Apply, Merge, Stats, Visualization, Creating Series and DataFrames, Time Series, and Deleting, each with multiple dataset-based exercises (e.g. Chipotle, Titanic, Pokemon).What do I need to run the exercises?You need Python and the pandas library, since the exercises are provided as Jupyter Notebooks.
You need Python and the pandas library, since the exercises are provided as Jupyter Notebooks.If I get stuck, should I jump straight to the code solution?The author recommends checking the solution-without-code file first and trying to work out the answer yourself before looking at the full code solution.
The author recommends checking the solution-without-code file first and trying to work out the answer yourself before looking at the full code solution.Are there video walkthroughs for the exercises?Yes, there are video tutorials of data scientists solving the exercises, linked under a 'Video Solutions' section referencing a series called Data Talks - Pandas Learning By Doing.
Yes, there are video tutorials of data scientists solving the exercises, linked under a 'Video Solutions' section referencing a series called Data Talks - Pandas Learning By Doing.What kind of datasets are used in the exercises?A variety of real-world-style datasets such as Chipotle orders, Titanic passengers, Pokemon stats, US baby names, wine and iris data, Euro12 football stats, and stock/financial data.
A variety of real-world-style datasets such as Chipotle orders, Titanic passengers, Pokemon stats, US baby names, wine and iris data, Euro12 football stats, and stock/financial data.What are similar projects?pydata-book, Data-Science-For-Beginners, Python-100-Days, 100-Days-Of-ML-Code, mlcourse.ai, Ai-Learn, numpy-100, Python-programming-exercises
pydata-book, Data-Science-For-Beginners, Python-100-Days, 100-Days-Of-ML-Code, mlcourse.ai, Ai-Learn, numpy-100, Python-programming-exercisesWhich topics is it in?practice, exercises, pandas, data-analysis, numpy, python-library, academic, curriculum, dataset, jupyter notebook, data-visualization, data-science
practice, exercises, pandas, data-analysis, numpy, python-library, academic, curriculum, dataset, jupyter notebook, data-visualization, data-science