The Hands-On, Example-Rich Introduction to Pandas Data Analysis in
Python
Today, analysts must manage data characterized by extraordinary variety,
velocity, and volume. Using the open source Pandas library, you can use
Python to rapidly automate and perform virtually any data analysis task,
no matter how large or complex. Pandas can help you ensure the veracity
of your data, visualize it for effective decision-making, and reliably
reproduce analyses across multiple datasets.
Pandas for Everyone brings together practical knowledge and
insight for solving real problems with Pandas, even if you're new to
Python data analysis. Daniel Y. Chen introduces key concepts through
simple but practical examples, incrementally building on them to solve
more difficult, real-world problems.
Chen gives you a jumpstart on using Pandas with a realistic dataset and
covers combining datasets, handling missing data, and structuring
datasets for easier analysis and visualization. He demonstrates powerful
data cleaning techniques, from basic string manipulation to applying
functions simultaneously across dataframes.
Once your data is ready, Chen guides you through fitting models for
prediction, clustering, inference, and exploration. He provides tips on
performance and scalability, and introduces you to the wider Python data
analysis ecosystem.
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Work with DataFrames and Series, and import or export data
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Create plots with matplotlib, seaborn, and pandas
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Combine datasets and handle missing data
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Reshape, tidy, and clean datasets so they're easier to work with
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Convert data types and manipulate text strings
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Apply functions to scale data manipulations
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Aggregate, transform, and filter large datasets with groupby
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Leverage Pandas' advanced date and time capabilities
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Fit linear models using statsmodels and scikit-learn libraries
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Use generalized linear modeling to fit models with different response
variables
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Compare multiple models to select the "best"
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Regularize to overcome overfitting and improve performance
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Use clustering in unsupervised machine learning
