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[Depr] raise_on_error kwarg with errors kwarg in astype#14878 #14967

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m-charlton
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@m-charlton m-charlton commented Dec 22, 2016

Please check that the entry in whatsnew/v0.20.0.txt. Unsure that the update was in the
_whatsnew_0200.deprecations or _whatsnew_0200.prior_deprecations so put it in the
former.

@@ -3073,7 +3075,9 @@ def astype(self, dtype, copy=True, raise_on_error=True, **kwargs):
the same type. Alternatively, use {col: dtype, ...}, where col is a
column label and dtype is a numpy.dtype or Python type to cast one
or more of the DataFrame's columns to column-specific types.
raise_on_error : raise on invalid input
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leave this in here and just say DEPRECATED.

@jorisvandenbossche IIRC that is our convention?

add a versionadded tag 0.20.0 for errors

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Will do.

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yes, can leave it (but put it at the end)

raise_on_error : raise on invalid input
errors : {'raise', 'ignore'}, default 'raise'
- ``raise`` : allow exceptions to be raised on invalid input
- ``ignore`` : suppress raising exceptions on invalid input
kwargs : keyword arguments to pass on to the constructor
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I think you need a blank line before kwargs (to make the sub-list work)

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I've just checked and the sublist is rendered fine with, or without a line between ignore
and kwargs. I can add an extra line if that is the convention,


def _astype(self, dtype, copy=False, raise_on_error=True, values=None,
def _astype(self, dtype, copy=False, errors='raise', values=None,
klass=None, mgr=None, **kwargs):
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can you check the errors in ['raise', 'ignore'] at the beginning of the function and raise a ValueError otherwise (and add a test for this)

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Sure, there are two 'public' astype(...) methods:

  • NDFrame.astype(...) in pandas/core/generic.py
  • Block.astype(...) in pandas/core/internals.py

In addition there is a 'protected' Block._astype(...) method in
pandas/core/internals.py. Should I only put the checks in the 'public'
methods?

Bearing in mind that the raise_on_error kwarg is going to be deprecated for
DataFrame.where() and replaced with the errors kwarg it would make sense to
put the code that checks the validity of the arguments in one place. Do we have
any existing code where we put such validity checking functions/methods?

I notice that both NDFrame & Block inherit from PandasObject but, I'm not
sure that this is the correct thing to do. Should I put a function in
pandas/core/base.py?

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Block is completely internal
u can put the check there

we have centralized checks but no need in this case

out in _astype as that's where it's actually used
parameter validation is best down where it's actually

@jreback jreback added the Deprecate Functionality to remove in pandas label Dec 23, 2016
@jreback jreback added this to the 0.20.0 milestone Dec 23, 2016
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codecov-io commented Dec 23, 2016

Current coverage is 84.75% (diff: 100%)

Merging #14967 into master will increase coverage by 0.10%

@@             master     #14967   diff @@
==========================================
  Files           144        145     +1   
  Lines         51030      51144   +114   
  Methods           0          0          
  Messages          0          0          
  Branches          0          0          
==========================================
+ Hits          43198      43348   +150   
+ Misses         7832       7796    -36   
  Partials          0          0          

Powered by Codecov. Last update 8b497e4...0ae8550

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Update after review

instead
errors : {'raise', 'ignore'}, default 'raise'
- ``raise`` : allow exceptions to be raised on invalid input
- ``ignore`` : suppress raising exceptions on invalid input
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maybe specify what happens of there is an error? (original is returned)


if errors not in errors_legal_values:
invalid_arg = "Expected value of kwarg 'errors' to be one of %s. "\
"Supplied value is '%s'" % (', '.join("'%s'" % arg for arg in
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style comment: can you do the string continuation with putting ( ) around it instead of the \. And can you use ´.format(..)´ instead of % (can be on a separate line)

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Will do. I'll change the output message to:

Expected value of kwarg 'errors' to be one of ['raise', 'ignore']. Supplied value 'True'

This will do away with the need for the messy formatting.

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@m-charlton can you change this to the {} formatting syntax?

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Will do

@@ -566,6 +566,13 @@ def test_astype(self):
else:
self.assertEqual(tmgr.get('d').dtype.type, t)

def test_illegal_arg_for_errors_in_astype(self):
""" ValueError exception raised when illegal value used for errors """
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Can you turn this into a normal comment (with #)? Otherwise the test name does not show up in the nosetests output.
You can also add the issue number

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I would also move the test to the high-level astype tests for frame/series

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will do

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I've looked at the existing test cases in pandas/tests/series &
pandas/tests/frame and can't find a natural place to put this test.

I was thinking of adding a new file called say test_astype.py in
pandas/tests/frame, as there is an existing test_apply.py

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no just grep for astype and you will see lots of tests

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ok this test is fine here.

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@jorisvandenbossche jorisvandenbossche Jan 2, 2017

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@m-charlton astype tests are located in pandas/tests/frame/test_dtypes.py (you actually updated some tests there)

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Will do

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small error message formatting change. ping when pushed and green.

@jorisvandenbossche
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@m-charlton Can you also add a test confirming that the old keyword still works but gives a deprecation warning?

You can do this with:

        with tm.assert_produces_warning(FutureWarning):
            res = df.astype(.., raise_on_error=False)
        exp = df.astype(.., errors='ignore')

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xref #14877 we should try to clarify that the errors keyword only is meant for errors during the type conversion. Maybe we can change the "invalid input" to something else? Eg "invalid data for the provided dtype"?

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m-charlton commented Jan 3, 2017

Back from Christmas/New Year break. Will makes changes today and push for review

Tests added for deprected 'raise_on_error' kwarg & new 'errors' kwarg.
Clarified docstring for DataFrame.astype method
@@ -523,6 +523,24 @@ def test_timedeltas(self):
result = df.get_dtype_counts().sort_values()
assert_series_equal(result, expected)

def test_illegal_arg_for_errors_in_astype(self):
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you can make this a single test.

as the same test in tests/series/test_dtypes.py as well

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jreback commented Jan 3, 2017

minor test change. ping on green.

Unit tests for DataFrame.astype merged. Dupliacted those tests for
Series.astype. Both testing deprecation of 'raise_on_error' kwarg.
@jorisvandenbossche jorisvandenbossche merged commit b957f6f into pandas-dev:master Jan 3, 2017
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@m-charlton Thanks a lot!

@m-charlton m-charlton deleted the depr_arg_raise_on_error_in_astype#14878 branch January 4, 2017 10:13
gfyoung added a commit to forking-repos/pandas that referenced this pull request Oct 27, 2018
gfyoung added a commit to forking-repos/pandas that referenced this pull request Oct 27, 2018
tm9k1 pushed a commit to tm9k1/pandas that referenced this pull request Nov 19, 2018
Pingviinituutti pushed a commit to Pingviinituutti/pandas that referenced this pull request Feb 28, 2019
Pingviinituutti pushed a commit to Pingviinituutti/pandas that referenced this pull request Feb 28, 2019
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DEPR: change .astype(.., raise_on_error) -> errors
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