ER: Bug accessing a series MultiIndex with a Timestamp (original) (raw)

I have a series with a multiindex (datetime, int).
When I try to access a slice corresponding to a date using a Timestamp I have an exception printed to screen if the size of the series is >= 1e6.
No problem if I access the same slice with a string.
No problem with an equivalent dataframe.
Tested on 0.10.1 and 0.11, I'm sorry but I don't have access to 0.12rc1.

In [1]: import pandas as pd

In [2]: pd.version Out[2]: '0.11.0'

In [3]: np.version Out[3]: '1.7.1'

In [4]: df = pd.DataFrame(randn(1000, 1000), index=pd.date_range('2000-1-1', periods=1000))

In [5]: s = df.stack() # s has 1e6 lines

In [6]: s.head() Out[6]: 2000-01-01 0 -0.555228 1 -0.152952 2 0.401490 3 -1.057106 4 -0.987895 dtype: float64

In [7]: s['2000-1-4'].head() Out[7]: 0 -1.009647 1 0.094427 2 0.105180 3 -2.166810 4 -0.767165 dtype: float64

In [8]: s[pd.Timestamp('2000-1-4')].head() Exception TypeError: TypeError('Cannot compare Timestamp with (<Timestamp: 2002-09-26 00:00:00>, 999)',) in 'pandas.index._bin_search' ignored Out[8]: 0 -1.009647 1 0.094427 2 0.105180 3 -2.166810 4 -0.767165 dtype: float64

In [9]: s2 = s[:-1].copy() # s2 has 1e6 - 1 lines

In [10]: s2['2000-1-4'].head() Out[10]: 0 -1.009647 1 0.094427 2 0.105180 3 -2.166810 4 -0.767165 dtype: float64

In [11]: s2[pd.Timestamp('2000-1-4')].head() Out[11]: 0 -1.009647 1 0.094427 2 0.105180 3 -2.166810 4 -0.767165 dtype: float64

In [12]: df2 = pd.DataFrame(s)

In [13]: df2.ix['2000-1-4'].head() Out[13]: 0 0 -1.009647 1 0.094427 2 0.105180 3 -2.166810 4 -0.767165

In [14]: df2.ix[pd.Timestamp('2000-1-4')].head() Out[14]: 0 0 -1.009647 1 0.094427 2 0.105180 3 -2.166810 4 -0.767165