Pandas dataframe with multiple frequency data

Question

I have a pandas dataframe data with three frequencies (in some data there are even more)

    Date        value frequency  
23/10/2016 20:31    0    00:06
23/10/2016 20:36    0.5  00:05
23/10/2016 20:43    0.2  00:07
23/10/2016 20:49    0.1  00:06
23/10/2016 20:54    0    00:05
23/10/2016 21:00    2    00:06
23/10/2016 21:06    4    00:06
23/10/2016 21:12    5    00:06
23/10/2016 21:18    6    00:06
23/10/2016 21:24    10   00:06
23/10/2016 21:31    0    00:07
23/10/2016 21:37    0    00:06
23/10/2016 21:43    0    00:06
23/10/2016 21:48    7    00:05
23/10/2016 21:55    10   00:07
23/10/2016 22:00    0    00:05
23/10/2016 22:06    0    00:06
23/10/2016 22:12    0    00:06
23/10/2016 22:18    0    00:06
23/10/2016 22:25    0    00:07
23/10/2016 22:31    0    00:06

What I want of this data is I want to re sample to 15 mins, is there a way that panda handle multiple frequency data while creating index and that can be used for re-sampling the data.

I tried like this :

df=my_data_frame
df.index=df['Date']
df.resample('15T').sum()

This is giving me weird result like this :

Date                value
10/01/2016 22:15    0
10/01/2016 22:30    0
10/01/2016 22:45    0
10/01/2016 23:00    0
10/01/2016 23:15    0
10/01/2016 23:30    0
10/01/2016 23:45    0
11/01/2016 0:00 
11/01/2016 0:15 
11/01/2016 0:30 
11/01/2016 0:45 
11/01/2016 1:00 
11/01/2016 1:15 
11/01/2016 1:30 
11/01/2016 1:45 
11/01/2016 2:00 
11/01/2016 2:15 
11/01/2016 2:30 
11/01/2016 2:45 
11/01/2016 3:00

Index has been changed... ?

@Allen, I want 15 min re-sample data. I have also shown the result what I got after I re sample. I have a feeling that there might be a problem while setting index. — PUJA
– PUJA, Commented Jul 9, 2017 at 23:57
@ayhan, here is goes {Timestamp('2016-01-10 00:00:00', freq='15T'): 0.0, Timestamp('2016-01-10 00:15:00', freq='15T'): 0.0, Timestamp('2016-01-10 00:30:00', freq='15T'): 0.0, Timestamp('2016-01-10 00:45:00', freq='15T'): 0.0, Timestamp('2016-01-10 01:00:00', freq='15T'): 0.0}' — PUJA
– PUJA, Commented Jul 10, 2017 at 0:25

piRSquared · Accepted Answer · 2017-07-10 00:05:39Z

1

Pretty sure your dates are strings

df.index = pd.to_datetime(df.Date)
df.value.resample('15T').sum()

answered Jul 10, 2017 at 0:05

piRSquared

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2 Comments

piRSquared Over a year ago

@ayhan not sure. I'll test it out

PUJA Over a year ago

I even tried this df.index=pd.DatetimeIndex(df['Date']). This is also giving me the same result. I have data only for September, but after I re-sample I am getting data for other months as well.

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