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There's a different behavior between 0.16.0 and 0.17.0 on a DatetimeIndex creation with a frequency greater than the dates range:
import pandas as pd pd.DatetimeIndex(start=pd.Timestamp('2015-04-15'), end=pd.Timestamp('2015-04-18'), freq='7D')
With previous versions I had a DatetimeIndex of length 2: [2015-04-15, 2015-04-22].
[2015-04-15, 2015-04-22]
With 0.17.0 I get an index with only one value: ['2015-04-15'].
['2015-04-15']
Is it a bug/regression? Is there a way to reproduce the previous behavior?
Here are the the results of pd.show_versions():
pd.show_versions()
INSTALLED VERSIONS ------------------ commit: None python: 2.7.10.final.0 python-bits: 32 OS: Windows OS-release: 7 machine: AMD64 processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel byteorder: little LC_ALL: None LANG: None pandas: 0.16.0 nose: 1.3.7 Cython: 0.23.4 numpy: 1.10.1 scipy: 0.16.0 statsmodels: 0.6.1 IPython: 4.0.0 sphinx: 1.3.1 patsy: 0.4.0 dateutil: 2.4.1 pytz: 2015.7 bottleneck: 1.0.0 tables: 3.2.2 numexpr: 2.4.4 matplotlib: 1.4.3 openpyxl: 2.2.6 xlrd: 0.9.4 xlwt: 1.0.0 xlsxwriter: 0.7.7 lxml: 3.4.4 bs4: 4.4.1 html5lib: None httplib2: None apiclient: None sqlalchemy: 1.0.9 pymysql: None psycopg2: None
INSTALLED VERSIONS ------------------ commit: None python: 2.7.10.final.0 python-bits: 32 OS: Windows OS-release: 7 machine: AMD64 processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel byteorder: little LC_ALL: None LANG: None pandas: 0.17.0 nose: 1.3.7 pip: 7.1.2 setuptools: 18.4 Cython: 0.23.4 numpy: 1.10.1 scipy: 0.16.0 statsmodels: 0.6.1 IPython: 4.0.0 sphinx: 1.3.1 patsy: 0.4.0 dateutil: 2.4.1 pytz: 2015.7 blosc: None bottleneck: 1.0.0 tables: 3.2.2 numexpr: 2.4.4 matplotlib: 1.4.3 openpyxl: 2.2.6 xlrd: 0.9.4 xlwt: 1.0.0 xlsxwriter: 0.7.7 lxml: 3.4.4 bs4: 4.4.1 html5lib: None httplib2: None apiclient: None sqlalchemy: 1.0.9 pymysql: None psycopg2: None
The text was updated successfully, but these errors were encountered:
In [19]: DatetimeIndex(start=pd.Timestamp('2015-04-15'), periods=2, freq='7D') Out[19]: DatetimeIndex(['2015-04-15', '2015-04-22'], dtype='datetime64[ns]', freq='7D')
IIRC this was a bug previously, @sinhrks ?
Sorry, something went wrong.
it was #10885?
@kawochen right! thanks.
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There's a different behavior between 0.16.0 and 0.17.0 on a DatetimeIndex creation with a frequency greater than the dates range:
With previous versions I had a DatetimeIndex of length 2:
[2015-04-15, 2015-04-22]
.With 0.17.0 I get an index with only one value:
['2015-04-15']
.Is it a bug/regression? Is there a way to reproduce the previous behavior?
Here are the the results of
pd.show_versions()
:The text was updated successfully, but these errors were encountered: