- choose the row index, column index, value that are used for new DataFrame from original DataFrame’s column index + Use aggregation method → Make new DataFrame (pivot table)
- 1st : split data by the specific standard (grouping)
- 2nd : The methods for data aggregation or data change are applied to each group (Mapping applied to group : agg, transform, apply, filter)
- 3rd : combine (Two Dataframe Connection posting)
- concat
- simple connection between 2 dataframe
- merge
- connection standard : common data on specific column → combine those records (df1 has n records & df2 has m records that have common data on specific column compared with counterpart df → Number of total intersection records is n x m)
- join
- connection standard : common row index
- Option used for 3 methods
- inner : intersection set
- outer : union set (contains intersection set)
- left : left set (contains intersection set)
- right : right set (contains intersection set)
- Extract the records which satisfy the condition from dataframe
- Method