import pandas as pd
import jalali_pandas

# create dataframe
df = pd.DataFrame({"date": pd.date_range("2019-01-01", periods=10, freq="D")})

# convert to jalali
df["jdate"] = df["date"].jalali.to_jalali()

# convert to gregorian
df["gdate"] = df["jdate"].jalali.to_gregorian()

# parse string to jalali
df1 = pd.DataFrame({"date": ["1399/08/02", "1399/08/03", "1399/08/04"]})
df1["jdate"] = df1["date"].jalali.parse_jalali("%Y/%m/%d")


# get access to jalali year,quarter ,month, day and weekday
df['year'] = df["jdate"].jalali.year
df['month'] = df["jdate"].jalali.month
df['quarter'] = df["jdate"].jalali.quarter
df['day'] = df["jdate"].jalali.day
df['weekday'] = df["jdate"].jalali.weekday

import pandas as pd
import jalali_pandas

df = pd.DataFrame(
    {
    "date": pd.date_range("2019-01-01", periods=10, freq="M"),
    "value": range(10),
    }
)
# make sure to create a column with jalali datetime format. (you can use any name)
df["jdate"] = df["date"].jalali.to_jalali()


# group by jalali year
gp = df.jalali.groupby("year")
gp.sum()

#group by month
mean = df.jalali.groupby('mean')

#groupby year and month and day
mean = df.jalali.groupby('ymd')
# or
mean = df.jalali.groupby(['year','month','day'])


#groupby year and quarter
mean = df.jalali.groupby('yq')
# or
mean = df.jalali.groupby(['year','quarter'])