DOC: Updated docstring DatetimeIndex.tz_localize #20050

IHackPy · 2018-03-08T10:22:44Z

Kindly review this docstring DatetimeIndex.tz_localize

jorisvandenbossche

Thanks for the PR! I added a first round of comments

jorisvandenbossche · 2018-03-08T10:36:54Z

pandas/core/indexes/datetimes.py

-        pytz/dateutil), or remove timezone from tz-aware DatetimeIndex
+        DatetimeIndex.tz_localize used for Localize tz-naive DatetimeIndex.
+
+	tz_localize method is use to convert naive DatetimeIndex into any other localize


Your indentation is one space off (this line should be indented the same as the first line of the docstring)

jorisvandenbossche · 2018-03-08T10:41:31Z

pandas/core/indexes/datetimes.py

@@ -1937,15 +1937,18 @@ def tz_convert(self, tz):
                     mapping={True: 'infer', False: 'raise'})
    def tz_localize(self, tz, ambiguous='raise', errors='raise'):
        """
-        Localize tz-naive DatetimeIndex to given time zone (using
-        pytz/dateutil), or remove timezone from tz-aware DatetimeIndex
+        DatetimeIndex.tz_localize used for Localize tz-naive DatetimeIndex.


We should try to avoid to repeat the name of the method in the beginning of this summary line. What do you think of "Localize a tz-naive DatetimeIndex" ?
At the same time, we could try to make this even clearer. For example use "timezone" instead of "tz".

jorisvandenbossche · 2018-03-08T10:42:53Z

pandas/core/indexes/datetimes.py


        Parameters
        ----------
        tz : string, pytz.timezone, dateutil.tz.tzfile or None
            Time zone for time. Corresponding timestamps would be converted to
            time zone of the TimeSeries.
-            None will remove timezone holding local time.
+            None will remove timezone holding local time


Please leave this final '.' (the updated validation script will also give a message about this)

jorisvandenbossche · 2018-03-08T10:45:31Z

pandas/core/indexes/datetimes.py


        Returns
        -------
        localized : DatetimeIndex

+	Examples
+    	--------


same comment here about the indentation (it seems you are mixing tabs and spaces. It is best to configure your editor to introduce 4 spaces when you do tab)

jorisvandenbossche · 2018-03-08T10:46:35Z

pandas/core/indexes/datetimes.py

+    	In the example below, We put the date range from 01 March 2018 to 08 March 2018
+	& convert this to US/Eastern Time zone
+
+    	>>> import pandas as pd


The import of pandas is not needed (check https://python-sprints.github.io/pandas/guide/pandas_docstring.html#conventions-for-the-examples)

jorisvandenbossche · 2018-03-08T10:47:05Z

typescript

@@ -0,0 +1,135 @@
+Script started on 2018-03-06 11:15:57+0530
+[1m[7m#[27m[1m[0m                                                                                ]2;root@localhost: /home/ihackpy/Panda/pandas-dir]1;..da/pandas-dir[0m[27m[24m[J[01;32m➜  [36mpandas-dir[00m [01;34mgit:([31mdocstringhead[34m) [33m✗[00m [K[?1h=[?2004hlls[?1l>[?2004l
+]2;ls --color=tty]1;lsappveyor.yml  [0m[01;34mconda.recipe[0m  [01;34mpandas[0m            setup.cfg        [01;32mtest.sh[0m


Can you remove this file again?

Sorry I don't know HOw this file added sorry for the inconvenience

jorisvandenbossche · 2018-03-08T10:47:23Z

pandas/core/indexes/datetimes.py

        Raises
        ------
        TypeError
-            If the DatetimeIndex is tz-aware and tz is not None.
+            If the DatetimeIndex is tz-aware and tz is not None


Same here: please keep the '.'

jorisvandenbossche · 2018-03-08T11:01:11Z

Can you do a check of PEP8 with running git diff upstream/master -u -- "*.py" | flake8 --diff (see https://python-sprints.github.io/pandas/guide/pandas_pr.html#push-your-changes-to-pandas for more explanation)

codecov · 2018-03-08T11:16:02Z

Codecov Report

Merging #20050 into master will decrease coverage by 0.01%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master   #20050      +/-   ##
==========================================
- Coverage   91.71%    91.7%   -0.02%     
==========================================
  Files         150      150              
  Lines       49112    49122      +10     
==========================================
  Hits        45045    45045              
- Misses       4067     4077      +10

Flag	Coverage Δ
#multiple	`90.08% <ø> (-0.02%)`	⬇️
#single	`41.86% <ø> (-0.01%)`	⬇️

Impacted Files	Coverage Δ
pandas/core/indexes/datetimes.py	`95.65% <ø> (ø)`	⬆️
pandas/plotting/_converter.py	`65.07% <0%> (-1.74%)`	⬇️
pandas/core/window.py	`96.31% <0%> (ø)`	⬆️
pandas/core/indexes/base.py	`96.66% <0%> (ø)`	⬆️
pandas/util/testing.py	`83.85% <0%> (+0.2%)`	⬆️
pandas/core/reshape/tile.py	`93.37% <0%> (+0.42%)`	⬆️

Continue to review full report at Codecov.

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jreback · 2018-03-08T11:37:10Z

pandas/core/indexes/datetimes.py

@@ -1937,8 +1937,11 @@ def tz_convert(self, tz):
                     mapping={True: 'infer', False: 'raise'})
    def tz_localize(self, tz, ambiguous='raise', errors='raise'):
        """
-        Localize tz-naive DatetimeIndex to given time zone (using
-        pytz/dateutil), or remove timezone from tz-aware DatetimeIndex
+	DatetimeIndex.tz_localize used for Localize tz-naive DatetimeIndex.


used to localize a tz-aware DatetimeIndex to tz-naive

jreback · 2018-03-08T11:37:31Z

pandas/core/indexes/datetimes.py

-        pytz/dateutil), or remove timezone from tz-aware DatetimeIndex
+	DatetimeIndex.tz_localize used for Localize tz-naive DatetimeIndex.
+
+	tz_localize method is use to convert naive DatetimeIndex into any other 


tz-aware -> tz-naive

pep8speaks · 2018-03-08T12:30:14Z

Hello @himanshuawasthi95! Thanks for updating the PR.

Cheers ! There are no PEP8 issues in this Pull Request. 🍻

Comment last updated on March 14, 2018 at 08:54 Hours UTC

jorisvandenbossche · 2018-03-08T12:33:00Z

@himanshuawasthi95 You are still mixing tabs and spaces. Please try to fix that first.

IHackPy · 2018-03-08T12:42:36Z

Locally showing perfect I use vim for editing but don't know when I push code it shows wrong indentation is any tool which help me to remove this issue

jorisvandenbossche · 2018-03-08T12:45:23Z

I am not familiar with vim myself, but you will somehow have to say to vim that tabs should not be introduces as tabs but as 4 spaces (it may 'look' good, but that doesn't mean it is not mixing tabs and spaces). See eg https://stackoverflow.com/questions/1878974/redefine-tab-as-4-spaces

jorisvandenbossche · 2018-03-08T12:46:26Z

Or also see the second answer in https://stackoverflow.com/questions/426963/replace-tab-with-spaces-in-vim

jorisvandenbossche · 2018-03-09T08:23:33Z

I am afraid it is not yet solved.
You can check the output of git diff upstream/master -u -- "*.py" | flake8 --diff , it will still contain errors related to tabs/spaces. See also #20050 (comment)

jorisvandenbossche · 2018-03-09T08:45:52Z

Tabs/spaces issues seems to be solved!

jorisvandenbossche

Can you add an example for the None behaviour as well? (removing the timezone)

jorisvandenbossche · 2018-03-09T08:55:32Z

pandas/core/indexes/datetimes.py

@@ -1937,8 +1937,10 @@ def tz_convert(self, tz):
                     mapping={True: 'infer', False: 'raise'})
    def tz_localize(self, tz, ambiguous='raise', errors='raise'):
        """
-        Localize tz-naive DatetimeIndex to given time zone (using
-        pytz/dateutil), or remove timezone from tz-aware DatetimeIndex
+        Convert aware Datetime index to TimeZone naive Datetime index.


"Datetime index" -> DatetimeIndex
"TimeZone" -> time zone

And it is the other way around: you now say "convert aware to naive", but it is "localize naive to aware"

@jorisvandenbossche can you illustrate more "Can you add an example for the None behaviour as well? (removing the timezone)"

jorisvandenbossche · 2018-03-09T08:56:36Z

pandas/core/indexes/datetimes.py

@@ -1964,18 +1966,32 @@ def tz_localize(self, tz, ambiguous='raise', errors='raise'):

            .. versionadded:: 0.19.0

-        infer_dst : boolean, default False
-            .. deprecated:: 0.15.0
-               Attempt to infer fall dst-transition hours based on order


You can leave this one (although it will give an error in the validation script, but you can ignore that)

I will add this again.

@jorisvandenbossche why adding this back? looks leftover

@jreback @jorisvandenbossche I add this again or not ???????

@jreback no, the deprecation is still there (the fact that the deprecation is still there is certainly a left-over, but let's remove that (both the actual deprecation and the docs) in a separate PR)

@himanshuawasthi95 Yes, please add back

jorisvandenbossche · 2018-03-09T09:00:22Z

pandas/core/indexes/datetimes.py

+        >>> df
+        DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03', '2018-03-04',
+               '2018-03-05'],
+              dtype='datetime64[ns]', freq='D')


Can you clean up the alignment a bit here? If I run this in a console, I get this:

>>> df DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03', '2018-03-04', '2018-03-05'], dtype='datetime64[ns]', freq='D')

Ideally it should look the same (notice the different vertical alignment with your code)

jreback · 2018-03-10T12:33:51Z

pandas/core/indexes/datetimes.py

@@ -1937,8 +1937,10 @@ def tz_convert(self, tz):
                     mapping={True: 'infer', False: 'raise'})
    def tz_localize(self, tz, ambiguous='raise', errors='raise'):
        """
-        Localize tz-naive DatetimeIndex to given time zone (using
-        pytz/dateutil), or remove timezone from tz-aware DatetimeIndex
+        Convert aware to naive.


Localize a tz-naive DatetimeIndex to tz-aware DatetimeIndex

@jreback
can I add this line in extended summary :
tz_localize() takes a naive datetime object and interprets it as if it is in that timezone. It does not move the time to another timezone. tz_localize function helps to switch b/w time zone aware and time zone unaware objects.

interprets -> sets it in that timezone with the current timestamps.

tz_localize function helps to switch b/w time zone aware and time zone unaware objects.

not sure this last line is necessary

@jreback If it is give more clearity then It is okey other wise I can remove ??????

jreback · 2018-03-10T12:34:31Z

pandas/core/indexes/datetimes.py

+        Convert aware to naive.
+
+        Localize timezone-naive DatetimeIndex to given time zone,
+        or remove timezone from timezone aware DatetimeIndex.


this is almost a duplicate of the top

jreback · 2018-03-10T12:34:55Z

pandas/core/indexes/datetimes.py

+        Examples
+        --------
+        In the example below, We put the date range from 01 March 2018
+        to 08 March 2018 & convert this to US/Eastern Time zone


don't say convert. this is localizing, almost like 'setting' a time-zone.

jreback · 2018-03-10T12:35:33Z

pandas/core/indexes/datetimes.py

+        >>> df.tz_localize(tz='US/Eastern')
+        DatetimeIndex(['2018-03-01 00:00:00-05:00',
+        '2018-03-02 00:00:00-05:00', '2018-03-03 00:00:00-05:00',
+        '2018-03-04 00:00:00-05:00', '2018-03-05 00:00:00-05:00'],


showing the reverse example is also useful, IOW .tz_localize(None), removes the timezone and makes it tz-naive.

@jreback when I add another example it shows error how I add that example in the docstring

n [11]: pd.date_range('2018-03-01', '2018-03-05').tz_localize('US/Eastern').tz_localize(None) Out[11]: DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03', '2018-03-04', '2018-03-05'], dtype='datetime64[ns]', freq='D')

@jreback @jorisvandenbossche I made required change.

jreback · 2018-03-10T14:33:51Z

pandas/core/indexes/datetimes.py

+        >>> df.tz_localize(tz='US/Eastern')
+        DatetimeIndex(['2018-03-01 00:00:00-05:00',
+        '2018-03-02 00:00:00-05:00', '2018-03-03 00:00:00-05:00',
+        '2018-03-04 00:00:00-05:00', '2018-03-05 00:00:00-05:00'],


n [11]: pd.date_range('2018-03-01', '2018-03-05').tz_localize('US/Eastern').tz_localize(None) Out[11]: DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03', '2018-03-04', '2018-03-05'], dtype='datetime64[ns]', freq='D')

jreback · 2018-03-10T14:34:01Z

pandas/core/indexes/datetimes.py

+        In the example below, We put the date range from 01 March 2018
+        to 08 March 2018 & convert this to US/Eastern Time zone
+
+        >>> df = pd.date_range('2018-03-01', '2018-03-05')


don't use df, dti is better

any thing else in summary section ???

jreback · 2018-03-10T15:13:46Z

pandas/core/indexes/datetimes.py

-        pytz/dateutil), or remove timezone from tz-aware DatetimeIndex
+        Localize tz-naive DatetimeIndex to tz-aware DatetimeIndex.
+
+        tz_localize() takes a naive datetime object and interprets it as if it


takes a naive DatetimeIndex

jreback · 2018-03-10T15:14:00Z

pandas/core/indexes/datetimes.py

+        >>> dti = pd.date_range('2018-03-01', '2018-03-05')
+        >>> dti
+        DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03',
+        '2018-03-04', '2018-03-05'], dtype='datetime64[ns]', freq='D')


can you add a blank line between cases

jreback · 2018-03-10T15:14:46Z

pandas/core/indexes/datetimes.py

+        '2018-03-02 00:00:00-05:00', '2018-03-03 00:00:00-05:00',
+        '2018-03-04 00:00:00-05:00', '2018-03-05 00:00:00-05:00'],
+        dtype='datetime64[ns, US/Eastern]', freq='D')
+        >>> dti.tz_localize(None)


this last won't work, you need to do
dti.tz_localize('US/Eastern').tz_localize(None), which gets you back the original

it works well

it works but its not very useful. The point is to take a tz-aware, IOW some you previously used tz_localize on, or just constructed directly and the remove the tz.

How about you construct a new dti with a tz (IOW pass directly to date_range), then use .tz_localize(None) on it.

@jreback both gives same result

oh K Will do that

IHackPy · 2018-03-10T15:49:06Z

@jreback i changes example as required

IHackPy · 2018-03-10T18:56:56Z

@datapythonista @jorisvandenbossche @jreback Review

datapythonista

Looks good, added some comments.

Also, in the extended summary, I'd avoid repeating the name of the method at the beginning of each parameter.

In the ambigous parameter, the accepted values should be in curly brackets (except bool-ndarray), and include 'raise'.

Btw, no need to add comments to ask for review when you push new changes. github notifies reviewers when you push.

datapythonista · 2018-03-10T21:15:41Z

pandas/core/indexes/datetimes.py

@@ -1985,23 +1985,20 @@ def tz_localize(self, tz, ambiguous='raise', errors='raise'):
        we perform reverse operation where we remove tize zone & make it


Can you just leave the type in Returns (so, get rid of the "localized" name). Also, a short explanation on what is returned would be useful.

@datapythonista
I'm understand that I have to remove localized from return section & write like this :
Returns

DatetimeIndex

or I should write some explanation on returns section like this:
Returns

Some Explanation
I'm confused about it ?

and parameter ambiguous : {'infer', 'NaT', default 'raise'}, bool-ndarray . write like this ???

For return, first line as you say, then another line with explanation. You can check the first example here:
https://python-sprints.github.io/pandas/guide/pandas_docstring.html#section-4-returns-or-yields.

For parameter, I didn't see a case exactly like this before, but for the convention I'd say something like:

{'raise', 'infer', 'NaT'} or bool array-like, default 'raise'

is there any change with summary & with example section

datapythonista · 2018-03-10T21:23:00Z

pandas/core/indexes/datetimes.py

-
-        Out[5]: DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03',
+        >>> dti.tz_localize('US/Eastern').tz_localize(None)
+        DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03',
        '2018-03-04', '2018-03-05'], dtype='datetime64[ns]', freq='D')


More a personal opinion, but couple of things that I think would make the examples more clear:

Use 3 dates instead of 5

Add short sentences between commands on what's going on (e.g. "The values for the times are the same, but the index contains the timezone")

Save the output of dti.tz_localize(tz='US/Eastern') so it can be reused in the last command, instead of doing to two localizations in the same line. May be naming dti tz_naive first, and tz_aware later would make them more clear too.

datapythonista

Looking great, added couple of last comments.

datapythonista · 2018-03-11T10:49:52Z

pandas/core/indexes/datetimes.py

+
+        This method takes a naive DatetimeIndex object and interprets it as
+        if it is in that timezone. It does not move the time to another
+        timezone.


I found the interprets word a bit unclear. I think something like "Make a naive DatetimeIndex time zone aware, by attaching a time zone. It does not change the values."

Surely you can write it in a better way, but hopefully you see what I mean.

@datapythonista hows this otherwise I'm going to co[py paste same you suggest above :)

"This method takes a naive DatetimeIndex object and make this time zone aware. It does not move the time to another timezone.
Time zone localization helps to switch b/w time zone aware and time zone unaware objects."

datapythonista · 2018-03-11T10:51:27Z

pandas/core/indexes/datetimes.py

+        '2018-03-02 00:00:00-05:00', '2018-03-03 00:00:00-05:00'],
+        dtype='datetime64[ns, US/Eastern]', freq='D')
+
+        #localize aware time zone into naive time zone.


Sorry, that was my fault, but when I said to add comments to the examples, I didn't mean Python comments, but just the sentence. So, without the #, in capital letters, and with a blank line after it (also the one before you already have).

datapythonista · 2018-03-11T10:52:08Z

pandas/core/indexes/datetimes.py

+        DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03'],
+        dtype='datetime64[ns]', freq='D')
+
+        #localize DatetimeIndex in US?Eastern time zone.


Typo, ? instead of / in the time zone.

Can you also remove the # at the beginning of the line?

jorisvandenbossche · 2018-03-11T11:01:47Z

pandas/core/indexes/datetimes.py

+        DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03'],
+        dtype='datetime64[ns]', freq='D')
+
+        #localize DatetimeIndex in US?Eastern time zone.


Can you also remove the # at the beginning of the line?

jorisvandenbossche · 2018-03-11T11:04:21Z

pandas/core/indexes/datetimes.py


        Parameters
        ----------
        tz : string, pytz.timezone, dateutil.tz.tzfile or None
            Time zone for time. Corresponding timestamps would be converted to
            time zone of the TimeSeries.
            None will remove timezone holding local time.
-        ambiguous : 'infer', bool-ndarray, 'NaT', default 'raise'
+        ambiguous : {'infer', 'NaT', default 'raise'}, bool-ndarray


I would make this str {'infer', 'NaT', 'raise'} or boolean array, default 'raise'

But that is probably too long, so you can do:

ambiguous : str {'infer', 'NaT', 'raise'} or bool array, \ default 'raise' - 'infer': ...

It is a bit ugly in the code, but will render OK in plain text docstring and in html docstring.

A little bit below for the "errors" keyword, can you make the type description there: errors : {'raise', 'coerce'}, default 'raise' (so with curly braces)

errors : {'raise', 'coerce'}, default 'raise'
we have to define str{'raise', 'coerce'} I thought its already understood

Yes, in this case errors : {'raise', 'coerce'}, default 'raise' is good (without the 'str')

datapythonista

Almost there, looks good, just couple of comments for the Return and Examples sections.

datapythonista · 2018-03-11T14:42:58Z

pandas/core/indexes/datetimes.py

@@ -1991,15 +1992,17 @@ def tz_localize(self, tz, ambiguous='raise', errors='raise'):
        DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03'],


Returns should contain a description. See the example in: https://python-sprints.github.io/pandas/guide/pandas_docstring.html#section-4-returns-or-yields

datapythonista · 2018-03-11T14:47:25Z

pandas/core/indexes/datetimes.py

@@ -1991,15 +1992,17 @@ def tz_localize(self, tz, ambiguous='raise', errors='raise'):
        DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03'],
        dtype='datetime64[ns]', freq='D')

-        #localize DatetimeIndex in US?Eastern time zone.
+        localize DatetimeIndex in US/Eastern time zone.


The explanations of the examples need improvements. The first paragraph is outdated (end date is not the 8th). And I don't think you need to say that, it's clear from the code. So I would just get rid of it.

In this case, it should start with a capital L. May be you can add here what you were explaining before, that dti is naive (and also what you're already saying, that you're localizing to US/Eastern). Personally I'd rename dti to tz_aware, so it's more obvious.

You are saying this :

In [2]: tz_aware = pd.date_range('2018-03-01', '2018-03-03')

In [3]: tz_aware
Out[3]: DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03'], dtype='datetime64[ns]', freq='D')

In [4]: tz_aware.tz_localize(tz='US/Eastern')
Out[4]:
DatetimeIndex(['2018-03-01 00:00:00-05:00', '2018-03-02 00:00:00-05:00',
'2018-03-03 00:00:00-05:00'],
dtype='datetime64[ns, US/Eastern]', freq='D')

In [5]: tz_aware.tz_localize(None)
Out[5]: DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03'], dtype='datetime64[ns]', freq='D')

Almost. But in In [2] that's not a tz_aware index, it's a naive one. And in In [4] you do want to save the output, as that's the aware one that you'll one to convert to naive in In [5].

Make sure that the example makes sense for you too. Reviewers can also be wrong.

but thats why we added comment before where we analyse aware and naive

I agree, but I think the variable names can still help by being descriptive, even if you explain what you're doing. Feel free to keep dti if you prefer it over tz_naive. But for me it's more clear to see what the example does, if the variables are more descriptive. All objects in the example could be dti, and it doesn't help much IMO, but naming one tz_naive and the other tz_aware, makes it clear what every object used has.

Sorry if I'm not being able to explain what I mean clearer enough.

I hope this commit define exactly what you want in example section

sorry for disappointing you :(

datapythonista · 2018-03-11T14:48:26Z

pandas/core/indexes/datetimes.py

        >>> tz_aware = dti.tz_localize(tz='US/Eastern')

        >>> tz_aware
        DatetimeIndex(['2018-03-01 00:00:00-05:00',
        '2018-03-02 00:00:00-05:00', '2018-03-03 00:00:00-05:00'],
        dtype='datetime64[ns, US/Eastern]', freq='D')

-        #localize aware time zone into naive time zone.
+        localize aware time zone into naive time zone.
+
        >>> tz_naive = tz_aware.tz_localize(None)

        >>> tz_naive


As you're not doing anything with tz_naive more than displaying it, I wouldn't save it to a variable first, I'd show the output direclty.

datapythonista · 2018-03-11T14:48:38Z

pandas/core/indexes/datetimes.py

        >>> tz_aware = dti.tz_localize(tz='US/Eastern')

        >>> tz_aware
        DatetimeIndex(['2018-03-01 00:00:00-05:00',
        '2018-03-02 00:00:00-05:00', '2018-03-03 00:00:00-05:00'],
        dtype='datetime64[ns, US/Eastern]', freq='D')

-        #localize aware time zone into naive time zone.
+        localize aware time zone into naive time zone.


Same as before.

datapythonista · 2018-03-11T17:20:56Z

pandas/core/indexes/datetimes.py

+        '2018-03-02 00:00:00-05:00', '2018-03-03 00:00:00-05:00'],
+        dtype='datetime64[ns, US/Eastern]', freq='D')
+
+        Localize aware time zone into naive time zone.


"time zone aware index" instead of "aware time zone"?

datapythonista · 2018-03-11T17:21:33Z

pandas/core/indexes/datetimes.py

+        --------
+        >>> tz_naive = pd.date_range('2018-03-01', '2018-03-03')
+
+        >>> tz_naive


The blank line between them seems unnecessary. (also later in tz_aware)

datapythonista · 2018-03-11T17:22:15Z

pandas/core/indexes/datetimes.py


        Raises
        ------
        TypeError
            If the DatetimeIndex is tz-aware and tz is not None.
+


I think we don't leave this line here, the validation script probably complains.

datapythonista · 2018-03-11T17:24:35Z

pandas/core/indexes/datetimes.py

        Returns
        -------
-        localized : DatetimeIndex
+        DatetimeIndex
+            It returns naive time or aware time


I'd describe it more in terms of the functionality than the types. Something like "Index converted to the specified time zone." (The "It returns" seems redundant, and I think the spec requires a period at the end)

I copied your line "index converted to the specified time zone". because It gives perfect means

datapythonista · 2018-03-11T17:29:39Z

The example looks much better now. Just added couple of minor comments.

Sorry if I made you feel you were disappointing anyone. You're doing a great job, discussions in reviews are a normal and very beneficial part of open source. As you get more experience probably the discussions will be a bit shorter. But we've all been there (and we often are), in these PRs that require several iterations to look great. :)

datapythonista · 2018-03-11T18:13:14Z

lgtm

IHackPy · 2018-03-11T18:14:05Z

Thats why I love community thanks for supporting and guiding

IHackPy · 2018-03-11T18:14:48Z

Thanks alot :)

jorisvandenbossche

Did some final edits, looks good!

jorisvandenbossche · 2018-03-14T08:56:07Z

@himanshuawasthi95 Thanks for the PR!

IHackPy · 2018-03-14T09:03:21Z

thank @jorisvandenbossche @datapythonista @jreback

Updated DocString DatetimeIndex.tz_localize

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DOC: update the DatetimeIndex.tz_convert(tz) docstring #20096

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jorisvandenbossche merged commit 6126ad6 into pandas-dev:master Mar 14, 2018

		@@ -1985,23 +1985,20 @@ def tz_localize(self, tz, ambiguous='raise', errors='raise'):
		we perform reverse operation where we remove tize zone & make it

		@@ -1991,15 +1992,17 @@ def tz_localize(self, tz, ambiguous='raise', errors='raise'):
		DatetimeIndex(['2018-03-01', '2018-03-02', '2018-03-03'],

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DOC: Updated docstring DatetimeIndex.tz_localize #20050

DOC: Updated docstring DatetimeIndex.tz_localize #20050

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