Calculate average, max and min based on water year - pandas

Question

I can calculate the yearly averages, max and min values based on taking the first day of a year as January First like:
yearly_avg=df2.groupby(years).mean()
yearly_sum=df2.groupby(years).sum()
yearly_MAX=df2.groupby(years).max()
yearly_MIN=df2.groupby(years).min()
I need to calculate averages, max and min numbers based on the water year where October 1st is the first day of a year. As an explanation of "water year": https://en.wikipedia.org/wiki/Water_year
Here is my sample file stored here:
https://drive.google.com/file/d/1AYi9vp3_DPXHoCPB_YkMQp68FvC_INrV/view?usp=sharing
How can I do that?
Thanks.

Answer 1

Just set the year to start on October instead of January. I am just happy your columns were already datetime types, this made it easier!
df = pd.read_excel('sample_water_year.xlsx')
df['# YEAR'] = df.Dates.dt.to_period('A-Sep') #year ends on sep
Note that you will have to subtract 1 as it does not change the initial year value set.
df['# YEAR'] = df['# YEAR'] - 1
Then simply find the summary statistics:
yearly_avg = df.groupby('# YEAR').mean()
yearly_sum = df.groupby('# YEAR').sum()
yearly_MAX = df.groupby('# YEAR').max()
yearly_MIN = df.groupby('# YEAR').min()
Hopefully this helps!