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Combining

Table of contents

  1. Comparison
  2. 3 Methods for Combining
    1. concat()
    2. join()
    3. merge()
import pandas as pd

Comparison

In order of increasing complexity, these are concat(), join(), and merge()

concat()join()merge()
가로로 합치기 O
세로로 합치기 O		가로로 합치기 X
세로로 합치기 O		가로로 합치기 X
세로로 합치기 O
left_on X
right_on X		left_on O
right_on X		left_on O
right_on O
join : {‘inner’, ‘outer’}how : {‘left’, ‘right’, ‘outer’, ‘inner’}how : {‘left’, ‘right’, ‘outer’, ‘inner’, ‘cross’}

3 Methods for Combining

concat()

Concatenate pandas objects along a particular axis(rows[default] or columns).

pandas.concat(objs, axis=0, join='outer')

pandas document - pandas.concat

  1. objs : a sequence or mapping of Series or DataFrame objects
  2. axis : {0/’index’, 1/’columns’}, default 0
  3. join : {‘inner’, ‘outer’}, default ‘outer’

join()

Join columns with other DataFrame either on index or on a key column(of given DataFrame).

df.join(other, on='column_name') : uses column_name of df and (only) index of other.
Thus if we want to join using the key columns, we need to set key to be the index in both df and other. The joined DataFrame will have key as its index.

DataFrame.join(other, on=None, how='left', lsuffix='', rsuffix='')

pandas document - pandas.DataFrame.join

  1. other : DataFrame, Series, or list of DataFrame
  2. on : str, list of str, or array-like, optional
    • specify column or index to join on (criteria)
    • if None, then index-on-index
  3. how : {‘left’, ‘right’, ‘outer’, ‘inner’}, default ‘left’
    • left : use calling frame’s index (or column if on is specified)
    • right : use other’s index.
    • outer : union , and sort it lexicographically.
    • inner : intersection, preserving the order of the calling’s one(left keys).
    • cross : cartesian product, preserves the order of the left keys.
  4. lsuffix, rsuffix : str, default ‘’

merge()

DataFrame.merge(right, how='inner', | on=None, | left_on=None, right_on=None, | left_index=False, right_index=False, sort=False, suffixes=('_x', '_y'))

pandas.merge(left, right, how='inner', | on=None, | left_on=None, right_on=None, | left_index=False, right_index=False, sort=False, suffixes=('_x', '_y')

pandas document - pandas.DataFrame.merge

pandas document - pandas.merge

  1. left : DataFrame
  2. right: DataFrame or named Series
  3. how : {‘left’, ‘right’, ‘outer’, ‘inner’, ‘cross’}, default ‘inner’
  4. on : label or list
    • Column or index level names to join on in the left DataFrame. Must be common.
  5. left_on, right_on : label or list, or array-like
  6. left_index, right_index : bool, default False
    • Use the index from the left DataFrame as the join key(s).
  7. sort : bool, default False
  8. suffixes : list-like, default is (“_x”, “_y”)