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Putting It All Together

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Putting It All Together#

This chapter covered a lot of ground. Let’s review some of the core workflows we’ve encountered:

Interacting:

  • Selecting

  • Sorting

  • Filtering

  • Data types & time series data

Aggregating & calculating:

  • Summary & descriptive statistics

  • Arithmetic operations

  • Split-apply-combine

    • .groupby() and .value_counts()

Reshaping:

  • .pivot (long to wide)

  • .melt (wide to long)

  • .pivot_table (long to wide with summary statistic)

  • .transpose (invert columns and rows)

  • .explode (making multi-value columns distinct rows)

Combining:

  • .merge (connects rows in DataFrames based on one or more key fields, similar to SQL JOIN operations)

  • .concat (concatenates or “stacks” objects together along an axis)

Resources#

And we’re just scratching the surface in terms of Pandas data reshaping operations.

A couple useful links:

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