I have a pandas dataframe where the index is the date, from year 2007 to 2017.
I'd like to calculate the mean of each weekday for each year. I am able to group by year:
groups = df.groupby(TimeGrouper('A'))
years = DataFrame()
for name, group in groups:
years[name.year] = group.values
This is the way I create a new dataframe (years) where in each column I obtain each year of the time series. If I want to see the statistics of each years (for example, the mean):
print(years.mean())
But now I would like to separate each day of the week for each year, in order to obtain the mean of each weekday for all of then.
The only thing I know is:
year=df[(df.index.year==2007)]
day_week=df[(df.index.weekday==2)]
The problem with this is that I have to change 7 times the day of the week, and then repeat this for 11 years (my time series begins on 2007 and ends on 2017), so I must do it 77 times!
Is there a way to group time by years and weekday in order to make this faster?