I am trying to extract month from the below join_date. below is the structure of the emp table. and i am getting an error while performing the below code:
emp['join_mth']=emp['join_date'].apply(lambda x:x[:7])
emp_id emp_name account_id join_date
1 rob 121 2019-01-01
2 sam 122 2019-02-02
3 mike 123 2019-03-03
4 tom 124 2019-04-04
type(emp['join_date'])
<class 'pandas.core.series.Series'>
emp.dtypes
emp_id object
emp_name object
account_id object
join_date object
dtype:object
fail to excute line - 10: emp['join_mth']=emp['join_date'].apply(lambda x:x[:7])
Below is the exact error:
Traceback (most recent call last):
File "<stdin>", line 39, in <module>
mapped = lib.map_infer(values, f, convert=convert_dtype)
File "pandas/_libs/lib.pyx", line 2467, in pandas._libs.lib.map_infer
File "<stdin>", line 39, in <lambda>
TypeError: 'datetime.date' object is not subscriptable
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 70, in <module>
AttributeError: module 'sys' has no attribute 'last_value'
read your error carefully it says: "'datetime.date' object is not subscriptable" so your 'join_date' is of dtype datetime.date so use typecast it to string first:
emp['join_mth']=emp['join_date'].astype(str).str[:7]
#OR
emp['join_mth']=emp['join_date'].astype(str).apply(lambda x:x[:7])
OR
Since it's of type datetime.date so you can also use:
emp['join_date']=[x.strftime("%Y-%m") for x in emp['join_date']]
#OR
emp['join_mth']=emp['join_date'].map(lambda x:x.strftime("%Y-%m"))
OR
If you only want to extract month then use:
emp['join_date']=[x.strftime("%m") for x in emp['join_date']]
#emp['join_date'].apply(lambda x:x.strftime("%m"))
#OR(use above code for string format and below for int format)
emp['join_date']=[x.month for x in emp['join_date']]
#emp['join_date'].map(lambda x:x.month)