Recap and case study

Pandas Joins for Spreadsheet Users

John Miller

Principal Data Scientist

Chapter 1 - Introduction to joining data

$$

  • Common situations

  • Concatenate data by row or column

    pd.concat([df1, df2], axis=0)
  • Pandas as a powerful tool

$$ punts

Pandas Joins for Spreadsheet Users

Chapter 2 - VLOOKUP-style joins

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One-to-one, VLOOKUP-style joins 

pd.merge(left_df, right_df, 
         how='inner', 
         on='key_column')

left merge

Pandas Joins for Spreadsheet Users

Chapter 3- One-to-many joins

$$ Joins (merges) on key column

df1.merge(df2, how='inner', 
          on='key_column')

$$

Joins on unique index

df1.join(df2, how='left')

$$ one to many example

Pandas Joins for Spreadsheet Users

Chapter 4 - Advanced joins

Advanced parameters

  • left_index, right_index
  • suffixes
  • indicator
  • sort
pd.merge_ordered(left_df, right_df, 
                 how='outer')

pd.merge_asof(left_df, right_df, 
               direction='backward')

pandas

Pandas Joins for Spreadsheet Users

Thank you!

Pandas Joins for Spreadsheet Users

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