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Learning pandas eBook (PDF)
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Chapters
Chapter 1: Getting started with pandas
Chapter 2: Analysis: Bringing it all together and making decisions
Chapter 3: Appending to DataFrame
Chapter 4: Boolean indexing of dataframes
Chapter 5: Categorical data
Chapter 6: Computational Tools
Chapter 7: Creating DataFrames
Chapter 8: Cross sections of different axes with MultiIndex
Chapter 9: Data Types
Chapter 10: Dealing with categorical variables
Chapter 11: Duplicated data
Chapter 12: Getting information about DataFrames
Chapter 13: Gotchas of pandas
Chapter 14: Graphs and Visualizations
Chapter 15: Grouping Data
Chapter 16: Grouping Time Series Data
Chapter 17: Holiday Calendars
Chapter 18: Indexing and selecting data
Chapter 19: IO for Google BigQuery
Chapter 20: JSON
Chapter 21: Making Pandas Play Nice With Native Python Datatypes
Chapter 22: Map Values
Chapter 23: Merge, join, and concatenate
Chapter 24: Meta: Documentation Guidelines
Chapter 25: Missing Data
Chapter 26: MultiIndex
Chapter 27: Pandas Datareader
Chapter 28: Pandas IO tools (reading and saving data sets)
Chapter 29: pd.DataFrame.apply
Chapter 30: Read MySQL to DataFrame
Chapter 31: Read SQL Server to Dataframe
Chapter 32: Reading files into pandas DataFrame
Chapter 33: Resampling
Chapter 34: Reshaping and pivoting
Chapter 35: Save pandas dataframe to a csv file
Chapter 36: Series
Chapter 37: Shifting and Lagging Data
Chapter 38: Simple manipulation of DataFrames
Chapter 39: String manipulation
Chapter 40: Using .ix, .iloc, .loc, .at and .iat to access a DataFrame
Chapter 41: Working with Time Series
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