Reputation: 310
Trying to separate a dataframe by date ranges in an efficient way, so far I have only come up with:
mask0 = df['Date of survey'].between('2010-01-01', '2010-12-31')
mask1 = df['Date of survey'].between('2011-01-01', '2011-12-31')
mask2 = df['Date of survey'].between('2012-01-01', '2012-12-31')
...
maskn = df['Date of survey'].between('nnnn-01-01', 'nnnn-12-31')
Any ideas would be greatly appreciated! (I'd be using the masks to subset the dataframe and get the mean sums of each column variable for each year).
Upvotes: 1
Views: 56
Reputation: 862511
Better here is use DataFrame.resample
by years with aggregate functions like mean
and sum
:
df1 = df.resample('A', on='Date of survey').agg(['mean','sum'])
Or use DataFrame.groupby
by years by Series.dt.year
:
df2 = df.groupby(df['Date of survey'].dt.year).agg(['mean','sum'])
Upvotes: 1