Skip to content

DOC: update the pandas.Index.is_categorical docstring #20167

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 7 commits into from
Mar 12, 2018
Merged

DOC: update the pandas.Index.is_categorical docstring #20167

Changes from 1 commit
Commits
Show all changes
7 commits
Select commit Hold shift + click to select a range
354795e
pandas.Index.is_categorical from base.py documented
mariadelmarbibiloni Mar 10, 2018
1755bee
pandas.Index.is_categorical from base.py documented and some errors s…
mariadelmarbibiloni Mar 10, 2018
5a972b4
pandas.Index.is_categorical from base.py with new examples and extend…
mariadelmarbibiloni Mar 11, 2018
e6e12c6
Added See Also.
TomAugspurger Mar 11, 2018
a4586f2
Added back whitepace
TomAugspurger Mar 11, 2018
218737a
to_frame formatting
TomAugspurger Mar 12, 2018
1461f4a
Merge remote-tracking branch 'upstream/master' into mariadelmarbibilo…
TomAugspurger Mar 12, 2018
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
36 changes: 35 additions & 1 deletion pandas/core/indexes/base.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1156,7 +1156,7 @@ def to_frame(self, index=True):
>>> idx = pd.Index(['Ant', 'Bear', 'Cow'], name='animal')
>>> idx.to_frame()
animal
animal
animal
Ant Ant
Bear Bear
Cow Cow
Expand Down Expand Up @@ -1471,6 +1471,40 @@ def is_object(self):
return is_object_dtype(self.dtype)

def is_categorical(self):
"""
Check if the index type is categorical.

The given object must be a pandas dataframe or pandas Series.
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

dataframe -> DataFrame


Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I agree! Thank you :)

Returns
----------
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

This should be the same length as "Returns"

boolean
True if index is categorical.

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thanks a lot for the See Also!

Examples
--------
>>> s = pd.Series(["Watermelon","Orange","Apple",
Copy link

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Space after ","

Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

space after the commas

... "Watermelon"]).astype('category')
>>> df = pd.DataFrame({'Weight (grams)':[2000,230,160,1300]}, index=s)
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

spcae after the colon. Space after commas.

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thank you for your comments ^^ !! We have already changed it.

Copy link

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Space after ","

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thanks, we appreciate your comments! We have already changed it :)

>>> df
Weight (grams)
Watermelon 2000
Orange 230
Apple 160
Watermelon 1300
>>> df.index.is_categorical()
True

>>> df = pd.Series(["Peter","Adam","Elisabeth","Margareth"])
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

call the ser = since it's a series :)

>>> df
0 Peter
1 Adam
2 Elisabeth
3 Margareth
dtype: object
>>> df.index.is_categorical()
False
"""
return self.inferred_type in ['categorical']

def is_interval(self):
Expand Down