i get an empty df although i know some rows should be in it

any thoughts how to fix this?

the df after the 7th line run looks like this:

the holy_date looks like this: ['2020-01-01','2020-01-06']

from numpy.ma.extras import isin
import holidays
df = df[(df['country'] == 'Portugal')]
min_year = (pd.DatetimeIndex(df.long_date).year.min())
max_year = (pd.DatetimeIndex(df.long_date).year.max()) 1
holy_date = [i.strftime('%Y-%m-%d') for i in [*holidays.CountryHoliday('Portugal',years = np.arange(min_year,max_year,1)).keys()]]
df.long_date= pd.to_datetime(df.long_date).dt.date
df = pd.concat([df,df.long_date.isin(holy_date).rename('bh')],axis =1)
df[df['bh']==True]

CodePudding user response：

The problem come from the fact that you are trying to identify strings in a datetime column. What you should do is to eliminate the row

df.long_date= pd.to_datetime(df.long_date).dt.date

and use this instead: I added a few dates to your data

long_date   country
0  2020-11-07  Portugal
1  2020-11-01  Portugal
2  2020-10-01  Portugal
3  2020-06-11  Portugal

and

from numpy.ma.extras import isin
import holidays
import pandas as pd
df = pd.read_csv('holyday.csv', sep=";")
print(df)
df = df[(df['country'] == 'Portugal')]
min_year = (pd.DatetimeIndex(df.long_date).year.min())
max_year = (pd.DatetimeIndex(df.long_date).year.max()) 1

holy_date = [i.strftime('%Y-%m-%d') for i in [*holidays.CountryHoliday('Portugal',years = np.arange(min_year,max_year,1)).keys()]]
holy_date = list(holy_date)
#df.long_date= pd.to_datetime(df.long_date).dt.date
df = pd.concat([df,df['long_date'].isin(holy_date).rename('bh')],axis =1)
print(df)
df[df['bh']==True]

produces this:

    long_date   country
0  2020-11-07  Portugal
1  2020-11-01  Portugal
2  2020-10-01  Portugal
3  2020-06-11  Portugal
    long_date   country     bh
0  2020-11-07  Portugal  False
1  2020-11-01  Portugal   True
2  2020-10-01  Portugal  False
3  2020-06-11  Portugal   True



    long_date   country    bh
1  2020-11-01  Portugal  True
3  2020-06-11  Portugal  True