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Relabeling and Naming

Table of contents

  1. ‘ReLabeling’ (renaming)
    1. rename()
    2. set_index() $\longleftrightarrow$ reset_index()
  2. ‘Naming’ (renaming)
    1. dataframe.index.name (attribute)
    2. rename_axis()
import pandas as pd

‘ReLabeling’ (renaming)

rename()

Alter axes labels. (usually column labels)

Recommanded use only for ‘relabeling’ column.
For ‘relabeling’ index, use set_index() below.

DataFrame.rename(mapper, axis, | index, columns, inplace)     # row/column label 변경
Series.rename(index, inplace)
Index.rename(name, inplace)

pandas document - pandas.DataFrame.rename

pandas document - pandas.Series.rename

pandas document - pandas.Index.rename

  1. mapper : dict-like or function
  2. axis : {0 or ‘index’, 1 or ‘columns’}, default 0
  3. index : dict-like or function
  4. columns : dict-like or function
  5. inplace : bool, default False

set_index() $\longleftrightarrow$ reset_index()

set_index() : Set the index (row labels and name) using one or more existing columns or arrays(of the correct length).

dataframe.set_index(keys, inplace=False)        # 기존 index 를 columns 중 하나로 대체
  1. keys : label or array-like or list of labels/arrays
    • label of a column / list of labels of columns
    • List-like (of the correct length)

(cf) set index() 사용 시 기존의 index 는 삭제됨.

dataframe['new_column_name'] = dataframe.index
dataframe.set_index('coloumn_name', inplace=True)

>>> dataframe
# 기존의 index 를 새로운 칼럼에 저장하고,
# 기존의 column 중 하나로 index 를 대체.

reset_index() : Reset(remove) the index, or a level of it.

dataframe.reset_index(level=None, drop=False, inplace=False)    # opposite of set_index()
  1. level : int, str, tuple, or list, default None
    • Only remove the given levels from the index. Removes all levels by default.
  2. drop : bool, default False
    • Do not try to insert index into dataframe columns. This resets the index to the default integer index.
  3. inplace : bool, default False

pandas document - pandas.DataFrame.set_index

pandas document - pandas.DataFrame.reset_index

‘Naming’ (renaming)

dataframe.index.name (attribute)

dataframe.index.name = 'row_axis_name'

pandas.Index.name → ‘name’ of row_axis
pandas.Series.name → ‘label’ of row/column

rename_axis()

Set the ‘name’ of the axis for the index or columns.

DataFrame.rename_axis(mapper, axis, | index, columns, inplace)     # row/column label 변경
Series.rename_axis(mapper, axis, | index, inplace)

>>> dataframe.rename_axis("wines", axis='rows').rename_axis("fields", axis='columns')
fields	country 	designation	  points	price
wines													
0	      Italy	   Vulkà Bianco	      87      NaN
...         ...             ...      ...      ...

pandas document - pandas.DataFrame.rename_axis

  1. mapper : scalar, list-like, optional
  2. axis : {0 or ‘index’, 1 or ‘columns’}, default 0
  3. index : scalar, list-like, dict-like or function, optional
  4. columns : scalar, list-like, dict-like or function, optional
  5. inplace : bool, default False