I would like to know how to filter different dates at all the different time levels, i.e. find dates by year, month, day, hour, minute and/or day. For example, how do I find all
I would just create a string series, then use str.contains() with wildcards. That will give you whatever granularity you're looking for.
s = df['timeStamp'].map(lambda x: x.strftime('%Y-%m-%d %H:%M:%S'))
print(df[s.str.contains('2014-..-.. ..:..:..')])
print(df[s.str.contains('2014-..-02 ..:..:..')])
print(df[s.str.contains('....-02-.. ..:..:..')])
print(df[s.str.contains('....-..-.. 18:03:10')])
Output:
timeStamp
0 2014-01-02 21:03:04
1 2014-02-02 21:03:05
timeStamp
0 2014-01-02 21:03:04
1 2014-02-02 21:03:05
timeStamp
1 2014-02-02 21:03:05
2 2016-02-04 18:03:10
timeStamp
2 2016-02-04 18:03:10
I think this also solves your question about boolean indices:
print(s.str.contains('....-..-.. 18:03:10'))
Output:
0 False
1 False
2 True
Name: timeStamp, dtype: bool