I am reading a dataframe:
df = pd.read_csv("file_path")
df['time'] = pd.to_datetime(df['time'], format="%Y-%m-%d")
When I want to access df['time'].dt in order to get year, month, etc. I get the error that:
'Timestamp' object has no attribute 'dt'.
There are many posts on StackOverflow related to my question. I tried the suggested solutions which was using to_pydatetime() but it did not work. I appreciate any help regarding this.
In order to get/extract a parameter like hour or year of a Timestamp data type in pandas, you can use the methods with the name of the attribute.
Example:
ref: https://pandas.pydata.org/docs/reference/api/pandas.Timestamp.hour.html https://pandas.pydata.org/docs/reference/api/pandas.Timestamp.year.html
OK, then, I'm confused about what code you actually have. The error message you cite says that you have a Timestamp object, not a Series. IF you have a Series, then you need dt. If you have an individual element, then you do not need dt. Here is a snippet based on your code that works perfectly. If this is not what you have, then you need to modify the question.
import pandas as pd
data = [
'2019-06-06',
'2020-04-01',
'2021-01-01'
]
df = pd.DataFrame(data, columns=['time'] )
print(df)
df['time'] = pd.to_datetime(df['time'], format="%Y-%m-%d")
print(df)
print(df['time'].dt.year)
Output:
time
0 2019-06-06
1 2020-04-01
2 2021-01-01
time
0 2019-06-06
1 2020-04-01
2 2021-01-01
0 2019
1 2020
2 2021
Name: time, dtype: int64