Reputation: 399
I have a dataframe which I want to resample and append the results to original dataframe as new column,
What I have:
index = pd.date_range('1/1/2000', periods=9, freq='T')
series = pd.Series(range(9), index=index)
series
time value
2000-01-01 00:00:00 0
2000-01-01 00:01:00 1
2000-01-01 00:02:00 2
2000-01-01 00:03:00 3
2000-01-01 00:04:00 4
2000-01-01 00:05:00 5
2000-01-01 00:06:00 6
2000-01-01 00:07:00 7
2000-01-01 00:08:00 8
What I want:
time value mean_resampled
2000-01-01 00:00:00 0. 2
2000-01-01 00:01:00 1. NaN
2000-01-01 00:02:00 2. NaN
2000-01-01 00:03:00 3. NaN
2000-01-01 00:04:00 4. NaN
2000-01-01 00:05:00 5. 6.5
2000-01-01 00:06:00 6. NaN
2000-01-01 00:07:00 7. NaN
2000-01-01 00:08:00 8. NaN
Note: resampling frequency is '5T'
Upvotes: 0
Views: 599
Reputation: 120409
Use resample
to compute the mean and concat
to merge your Series
with new values.
>>> pd.concat([series, series.resample('5T').mean()], axis=1) \
.rename(columns={0: 'value', 1: 'mean_resampled'})
value mean_resampled
2000-01-01 00:00:00 0 2.0
2000-01-01 00:01:00 1 NaN
2000-01-01 00:02:00 2 NaN
2000-01-01 00:03:00 3 NaN
2000-01-01 00:04:00 4 NaN
2000-01-01 00:05:00 5 6.5
2000-01-01 00:06:00 6 NaN
2000-01-01 00:07:00 7 NaN
2000-01-01 00:08:00 8 NaN
If you have a DataFrame
instead of Series
in your real case, you have just to add a new column:
>>> df['mean_resampled'] = df.resample('5T').mean()
Upvotes: 1
Reputation: 14103
index = pd.date_range('1/1/2000', periods=9, freq='T')
series = pd.Series(range(9), index=index, name='values')
sample = series.resample('5T').mean() # create a sample at some frequency
df = series.to_frame() # convert series to frame
df.loc[sample.index.values, 'mean_resampled'] = sample # use loc to assign new values
values mean_resampled
2000-01-01 00:00:00 0 2.0
2000-01-01 00:01:00 1 NaN
2000-01-01 00:02:00 2 NaN
2000-01-01 00:03:00 3 NaN
2000-01-01 00:04:00 4 NaN
2000-01-01 00:05:00 5 6.5
2000-01-01 00:06:00 6 NaN
2000-01-01 00:07:00 7 NaN
2000-01-01 00:08:00 8 NaN
Upvotes: 1