rename

In [1]:

# https://dplyr.tidyverse.org/reference/rename.html
%run nb_helpers.py

from datar.data import iris
from datar.all import *

nb_header(rename, rename_with)

# https://dplyr.tidyverse.org/reference/rename.html %run nb_helpers.py from datar.data import iris from datar.all import * nb_header(rename, rename_with)

Try this notebook on binder.

★ rename

¶

Rename columns¶

See original API
https://dplyr.tidyverse.org/reference/rename.html

Args:¶

  _data: A data frame
  **kwargs: Columns to rename

Returns:¶

  The dataframe with new names

★ rename_with

¶

Rename columns with a function¶

See original API
https://dplyr.tidyverse.org/reference/rename.html

Args:¶

  _data: A data frame
  _fn: A function to apply to column names
  *args: the columns to rename and non-keyword arguments for the _fn.
    If *args is not provided, then assuming all columns, and
    no non-keyword arguments are allowed to pass to the function, use
    keyword arguments instead.

  **kwargs: keyword arguments for _fn

Returns:¶

  The dataframe with new names

In [2]:

rename(iris, petal_length='Petal_Length')

rename(iris, petal_length='Petal_Length')

Out[2]:

	Sepal_Length	Sepal_Width	petal_length	Petal_Width	Species
	<float64>	<float64>	<float64>	<float64>	<object>
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
...	...	...	...	...	...
4	5.0	3.6	1.4	0.2	setosa
145	6.7	3.0	5.2	2.3	virginica
146	6.3	2.5	5.0	1.9	virginica
147	6.5	3.0	5.2	2.0	virginica
148	6.2	3.4	5.4	2.3	virginica
149	5.9	3.0	5.1	1.8	virginica

150 rows × 5 columns

In [3]:

rename_with(iris, str.upper)

rename_with(iris, str.upper)

Out[3]:

	SEPAL_LENGTH	SEPAL_WIDTH	PETAL_LENGTH	PETAL_WIDTH	SPECIES
	<float64>	<float64>	<float64>	<float64>	<object>
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
...	...	...	...	...	...
4	5.0	3.6	1.4	0.2	setosa
145	6.7	3.0	5.2	2.3	virginica
146	6.3	2.5	5.0	1.9	virginica
147	6.5	3.0	5.2	2.0	virginica
148	6.2	3.4	5.4	2.3	virginica
149	5.9	3.0	5.1	1.8	virginica

150 rows × 5 columns

In [4]:

iris >> rename_with(str.upper, starts_with("Petal"))

iris >> rename_with(str.upper, starts_with("Petal"))

Out[4]:

	Sepal_Length	Sepal_Width	PETAL_LENGTH	PETAL_WIDTH	Species
	<float64>	<float64>	<float64>	<float64>	<object>
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
...	...	...	...	...	...
4	5.0	3.6	1.4	0.2	setosa
145	6.7	3.0	5.2	2.3	virginica
146	6.3	2.5	5.0	1.9	virginica
147	6.5	3.0	5.2	2.0	virginica
148	6.2	3.4	5.4	2.3	virginica
149	5.9	3.0	5.1	1.8	virginica

150 rows × 5 columns

In [5]:

iris >> rename_with(lambda x: x.replace('_', '.').lower())

iris >> rename_with(lambda x: x.replace('_', '.').lower())

Out[5]:

	sepal.length	sepal.width	petal.length	petal.width	species
	<float64>	<float64>	<float64>	<float64>	<object>
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
...	...	...	...	...	...
4	5.0	3.6	1.4	0.2	setosa
145	6.7	3.0	5.2	2.3	virginica
146	6.3	2.5	5.0	1.9	virginica
147	6.5	3.0	5.2	2.0	virginica
148	6.2	3.4	5.4	2.3	virginica
149	5.9	3.0	5.1	1.8	virginica

150 rows × 5 columns

In [6]:

# names can be selected by indexes
iris >> rename(Sp=4)

# names can be selected by indexes iris >> rename(Sp=4)

Out[6]:

	Sepal_Length	Sepal_Width	Petal_Length	Petal_Width	Sp
	<float64>	<float64>	<float64>	<float64>	<object>
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
...	...	...	...	...	...
4	5.0	3.6	1.4	0.2	setosa
145	6.7	3.0	5.2	2.3	virginica
146	6.3	2.5	5.0	1.9	virginica
147	6.5	3.0	5.2	2.0	virginica
148	6.2	3.4	5.4	2.3	virginica
149	5.9	3.0	5.1	1.8	virginica

150 rows × 5 columns