I am trying to use pandas to compute daily climatology. My code is:
import pandas as pd dates = pd.date_range('1950-01-01', '1953-12-31', freq='D') rand_data = [int(1000*random.random()) for i in xrange(len(dates))] cum_data = pd.Series(rand_data, index=dates) cum_data.to_csv('test.csv', sep="t")
cum_data is the data frame containing daily dates from 1st Jan 1950 to 31st Dec 1953. I want to create a new vector of length 365 with the first element containing the average of rand_data for January 1st for 1950, 1951, 1952 and 1953. And so on for the second element…
Any suggestions how I can do this using pandas?
Advertisement
Answer
You can groupby the day of the year, and the calculate the mean for these groups:
cum_data.groupby(cum_data.index.dayofyear).mean()
However, you have the be aware of leap years. This will cause problems with this approach. As alternative, you can also group by the month and the day:
In [13]: cum_data.groupby([cum_data.index.month, cum_data.index.day]).mean() Out[13]: 1 1 462.25 2 631.00 3 615.50 4 496.00 ... 12 28 378.25 29 427.75 30 528.50 31 678.50 Length: 366, dtype: float64