Skip to content

CLN: remove need for tz_localize, tz_convert in Series, use the generic #6377

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 1 commit into from
Feb 17, 2014
Merged

CLN: remove need for tz_localize, tz_convert in Series, use the generic #6377

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
63 changes: 28 additions & 35 deletions pandas/core/generic.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -201,6 +201,7 @@ def _setup_axes(

def set_axis(a, i):
setattr(cls, a, lib.AxisProperty(i))
cls._internal_names_set.add(a)

if axes_are_reversed:
m = cls._AXIS_LEN - 1
Expand Down Expand Up @@ -392,6 +393,10 @@ def _expand_axes(self, key):

return new_axes

def set_axis(self, axis, labels):
""" public verson of axis assignment """
setattr(self,self._get_axis_name(axis),labels)

def _set_axis(self, axis, labels):
self._data.set_axis(axis, labels)
self._clear_item_cache()
Expand Down Expand Up @@ -3288,7 +3293,7 @@ def truncate(self, before=None, after=None, axis=None, copy=True):

def tz_convert(self, tz, axis=0, copy=True):
"""
Convert TimeSeries to target time zone. If it is time zone naive, it
Convert the axis to target time zone. If it is time zone naive, it
will be localized to the passed time zone.

Parameters
Expand All @@ -3304,24 +3309,18 @@ def tz_convert(self, tz, axis=0, copy=True):
ax = self._get_axis(axis)

if not hasattr(ax, 'tz_convert'):
ax_name = self._get_axis_name(axis)
raise TypeError('%s is not a valid DatetimeIndex or PeriodIndex' %
ax_name)

new_data = self._data
if copy:
new_data = new_data.copy()

new_obj = self._constructor(new_data)
new_ax = ax.tz_convert(tz)

if axis == 0:
new_obj._set_axis(1, new_ax)
elif axis == 1:
new_obj._set_axis(0, new_ax)
self._clear_item_cache()
if len(ax) > 0:
ax_name = self._get_axis_name(axis)
raise TypeError('%s is not a valid DatetimeIndex or PeriodIndex' %
ax_name)
else:
ax = DatetimeIndex([],tz=tz)
else:
ax = ax.tz_convert(tz)

return new_obj.__finalize__(self)
result = self._constructor(self._data, copy=copy)
result.set_axis(axis,ax)
return result.__finalize__(self)

def tz_localize(self, tz, axis=0, copy=True, infer_dst=False):
"""
Expand All @@ -3342,24 +3341,18 @@ def tz_localize(self, tz, axis=0, copy=True, infer_dst=False):
ax = self._get_axis(axis)

if not hasattr(ax, 'tz_localize'):
ax_name = self._get_axis_name(axis)
raise TypeError('%s is not a valid DatetimeIndex or PeriodIndex' %
ax_name)

new_data = self._data
if copy:
new_data = new_data.copy()

new_obj = self._constructor(new_data)
new_ax = ax.tz_localize(tz, infer_dst=infer_dst)

if axis == 0:
new_obj._set_axis(1, new_ax)
elif axis == 1:
new_obj._set_axis(0, new_ax)
self._clear_item_cache()
if len(ax) > 0:
ax_name = self._get_axis_name(axis)
raise TypeError('%s is not a valid DatetimeIndex or PeriodIndex' %
ax_name)
else:
ax = DatetimeIndex([],tz=tz)
else:
ax = ax.tz_localize(tz, infer_dst=infer_dst)

return new_obj.__finalize__(self)
result = self._constructor(self._data, copy=copy)
result.set_axis(axis,ax)
return result.__finalize__(self)

#----------------------------------------------------------------------
# Numeric Methods
Expand Down
63 changes: 1 addition & 62 deletions pandas/core/series.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1726,7 +1726,7 @@ def rank(self, method='average', na_option='keep', ascending=True,
False for ranks by high (1) to low (N)
pct : boolean, defeault False
Computes percentage rank of data

Returns
-------
ranks : Series
Expand Down Expand Up @@ -2323,67 +2323,6 @@ def weekday(self):
return self._constructor([d.weekday() for d in self.index],
index=self.index).__finalize__(self)

def tz_convert(self, tz, copy=True):
"""
Convert TimeSeries to target time zone

Parameters
----------
tz : string or pytz.timezone object
copy : boolean, default True
Also make a copy of the underlying data

Returns
-------
converted : TimeSeries
"""
new_index = self.index.tz_convert(tz)

new_values = self.values
if copy:
new_values = new_values.copy()

return self._constructor(new_values,
index=new_index).__finalize__(self)

def tz_localize(self, tz, copy=True, infer_dst=False):
"""
Localize tz-naive TimeSeries to target time zone
Entries will retain their "naive" value but will be annotated as
being relative to the specified tz.

After localizing the TimeSeries, you may use tz_convert() to
get the Datetime values recomputed to a different tz.

Parameters
----------
tz : string or pytz.timezone object
copy : boolean, default True
Also make a copy of the underlying data
infer_dst : boolean, default False
Attempt to infer fall dst-transition hours based on order

Returns
-------
localized : TimeSeries
"""
from pandas.tseries.index import DatetimeIndex

if not isinstance(self.index, DatetimeIndex):
if len(self.index) > 0:
raise Exception('Cannot tz-localize non-time series')

new_index = DatetimeIndex([], tz=tz)
else:
new_index = self.index.tz_localize(tz, infer_dst=infer_dst)

new_values = self.values
if copy:
new_values = new_values.copy()

return self._constructor(new_values,
index=new_index).__finalize__(self)

@cache_readonly
def str(self):
from pandas.core.strings import StringMethods
Expand Down