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resample time series python

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Innocent Iguana answered on August 13, 2021 Popularity 6/10 Helpfulness 6/10

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# Up-sampling = Adding more frequency (Increased no of rows)
# example : converting weekly data to daily data
# We need some method to fill in the values for more rows
upsampled_df = weekly_df.resample('D').ffill() # alternatives: .bfill(), .interpolate(), etc

# Down-sampling = Reducing frequency (Decreased no of rows)
# example : converting weekly data to monthly data
# We need some method to summarize / aggregate the values for reduced rows
downsampled_df = weekly_df.resample('M').mean() # alternatives: .median(), .std(), .first() etc

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Contributed on Jan 15 2023

Innocent Iguana

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# Set start and end dates
start = '2016-1-1'
end = '2016-2-29'

# Create time series of consting of monthly values
monthly_index = pd.date_range(start=start, end=end, freq='M')
monthly_series = pd.Series(data=[1,2], index=monthly_index)

# Create index to resample into
weekly_index = pd.date_range(start=start, end=end, freq='W')

# resample monthly time series using weekly_index
print(monthly_series.reindex(weekly_index))
print(monthly_series.reindex(weekly_index, method='bfill'))
print(monthly_series.reindex(weekly_index, method='ffill'))

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Contributed on Jan 15 2023

Innocent Iguana

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python resample time series

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#Resample to monthly frequency
df.resample('M').asfreq()

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Tags: time-series python time-serie

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Contributed on Aug 13 2021

M.U

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