An introduction to Python's quintessential data analysis library. Perform SQL-like merges of data using Python's Pandas. Square one of cleaning your Pandas Dataframes: dropping empty or problematic data. Easily drop data into Pandas from a SQL database, or upload your DataFrames to a SQL table. Let Pandas do the heavy lifting for you when turning JSON into a DataFrame. Speed up data analysis by parallelizing your DataFrames. Parse data from PDFs into Pandas DataFrames by using Python's Tabula library. Create beautiful data visualizations out-of-the-box with Python’s Seaborn. A guide to DataFrame manipulation using groupby, melt, pivot tables, pivot, transpose, and stack. Use Panda's Multiindex to make your data work harder for you.