Given a simple data frame
df = pd.DataFrame(np.random.rand(5,3))
I can select the records with the labels 1 and 3 using
df.loc[[1,3]]
But, if I change alter the index so it uses dates...
df.index = pd.date_range('1/1/2010', periods=5)
this no longer works:
df.loc[['2010-01-02', '2010-01-04']]
KeyError: "None of [['2010-01-02', '2010-01-04']] are in the [index]"
How can .loc be used with dates in this context?
One possible solution is convert dates to DatetimeIndex or to_datetime and then it works nice:
print (df.loc[pd.DatetimeIndex(['2010-01-02', '2010-01-04'])])
0 1 2
2010-01-02 0.827821 0.285281 0.781960
2010-01-04 0.872664 0.895636 0.368673
print (df.loc[pd.to_datetime(['2010-01-02', '2010-01-04'])])
0 1 2
2010-01-02 0.218419 0.806795 0.454356
2010-01-04 0.038826 0.741220 0.732816
You can use the boolean mask from isin:
In [151]:
df[df.index.isin(['2010-01-02', '2010-01-04'])]
Out[151]:
0 1 2
2010-01-02 0.939004 0.236200 0.495362
2010-01-04 0.254485 0.345047 0.273453
Unfortunately partial datetime string matching with a list won't work currently so either this or actual datetime values need to be passed
