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lines changed- Merging DataFrames with pandas
- 01 Preparing data
- 01 Reading DataFrames from multiple files
- 02 Reading DataFrames from multiple files in a loop
- 03 Combining DataFrames from multiple data files
- 04 Sorting DataFrame with the Index & columns
- 05 Reindexing DataFrame from a list
- 06 Reindexing using another DataFrame Index
- 07 Adding unaligned DataFrames
- 08 Broadcasting in arithmetic formulas
- 09 Computing percentage growth of GDP
- 10 Converting currency of stocks
- 02 Concatenating data
- 01 Appending Series with nonunique Indices
- 02 Appending pandas Series
- 03 Concatenating pandas Series along row axis
- 04 Appending DataFrames with ignore_index
- 05 Concatenating pandas DataFrames along column axis
- 06 Reading multiple files to build a DataFrame
- 07 Concatenating vertically to get MultiIndexed rows
- 08 Slicing MultiIndexed DataFrames
- 09 Concatenating horizontally to get MultiIndexed columns
- 10 Concatenating DataFrames from a dict
- 11 Concatenating DataFrames with inner join
- 12 Resampling & concatenating DataFrames with inner join
- 03 Merging data
- 01 Merging company DataFrames
- 02 Merging on a specific column
- 03 Merging on columns with non-matching labels
- 04 Merging on multiple columns
- 05 Joining by Index
- 06 Choosing a joining strategy
- 07 Left & right merging on multiple columns
- 08 Merging DataFrames with outer join
- 09 Using merge_ordered()
- 10 Using merge_asof()
- 04 Case Study - Summer Olympics
- 01 Loading Olympic edition DataFrame
- 02 Loading IOC codes DataFrame
- 03 Building medals DataFrame
- 04 Counting medals by country or edition in a pivot table
- 05 Computing fraction of medals per Olympic edition
- 06 Computing percentage change in fraction of medals won
- 07 Building hosts DataFrame
- 08 Reshaping for analysis
- 09 Merging to compute influence
- 10 Plotting influence of host country
- datasets
- Automobile fuel efficiency
- Baby names
- Exchange rates
- GDP
- Oil prices
- Pittburgh weather data
- S&P 500 Index
- Summer Olympic medals
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