Python pandas DataFrame loc selection for a range of rows and columns

Question

Here is a head() of my DataFrame df:

                     Temperature  DewPoint  Pressure
Date                                                
2010-01-01 00:00:00         46.2      37.5       1.0
2010-01-01 01:00:00         44.6      37.1       1.0
2010-01-01 02:00:00         44.1      36.9       1.0
2010-01-01 03:00:00         43.8      36.9       1.0
2010-01-01 04:00:00         43.5      36.8       1.0

I want to select from August 1 to August 15 2010 and display only the Temperature column.

What I am trying to do is: df.loc[['2010-08-01','2010-08-15'],'Temperature']

But this is throwing me an error.

Generally speaking what I want to learn is how, using loc method I can easily take a range of row i to row k and column j to p and show it in dataframe using loc method:

df.loc[[i:k],[j:p]]

Thank you very much in advance!!! Steve

does df['Temperature'].loc['2010-08-01':'2010-08-15'] work? — EdChum
– EdChum, Commented Feb 2, 2017 at 21:48
EdChum, yes it works, but why can't I do the same with loc[[i:k],[j:p]]? Why I need to "externally" define on what column I work? What if I want 2 columns? — Steve
– Steve, Commented Feb 2, 2017 at 21:51
For example this won't work: df['Temperature','DewPoint'].loc['2010-08-01':'2010-08-15'] — Steve
– Steve, Commented Feb 2, 2017 at 21:52
The issue here is that slice ranges with partial date string matching may not work here, it's the datetime that is the issue — EdChum
– EdChum, Commented Feb 2, 2017 at 21:52
That's a syntax error should be df[['Temperature','DewPoint']].loc['2010-08-01':'2010-08-15'] you need additional square brackets, it would evern without the loc — EdChum
– EdChum, Commented Feb 2, 2017 at 21:53

EdChum · Accepted Answer · 2017-02-02 22:33:08Z

2

I think if you want to be able to pass a slice for the index and columns then you can use ix to achieve this:

In [19]:
df.ix['2010-01-01':, 'DewPoint':]

Out[19]:
                     DewPoint  Pressure
Date                                   
2010-01-01 00:00:00      37.5       1.0
2010-01-01 01:00:00      37.1       1.0
2010-01-01 02:00:00      36.9       1.0
2010-01-01 03:00:00      36.9       1.0
2010-01-01 04:00:00      36.8       1.0

The docs detail numerous ways of selecting data

answered Feb 2, 2017 at 22:33

EdChum

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