Error: ValueError: nattype does not support strftime
Explanation:
The error message “ValueError: nattype does not support strftime” occurs when you try to use the strftime() method on a pandas Series or Dataframe column that has missing values (NaT – Not a Time).
The strftime() method is used to convert a datetime object to a string format based on a specific format string. However, NaT is not a valid datetime object, so it does not support the strftime() method.
Example:
import pandas as pd
# Create a DataFrame with a column containing NaT
df = pd.DataFrame({'Date': [pd.Timestamp('2021-01-01'), pd.NaT, pd.Timestamp('2021-01-03')]})
# Try to use strftime() on the 'Date' column
df['Formatted Date'] = df['Date'].strftime('%Y-%m-%d')
Output:
ValueError: nattype does not support strftime
To avoid this error, you can check for missing values before applying the strftime() method. You can use the `pd.isnull()` function to check for missing values in a pandas Series or Dataframe column.
Example:
import pandas as pd
# Create a DataFrame with a column containing NaT
df = pd.DataFrame({'Date': [pd.Timestamp('2021-01-01'), pd.NaT, pd.Timestamp('2021-01-03')]})
# Apply strftime() only on non-missing values
df.loc[~pd.isnull(df['Date']), 'Formatted Date'] = df.loc[~pd.isnull(df['Date']), 'Date'].dt.strftime('%Y-%m-%d')
# Output:
print(df)
# Alternative approach: Using fillna to replace NaT with a default value
df['Formatted Date'] = df['Date'].fillna(pd.Timestamp('1970-01-01')).dt.strftime('%Y-%m-%d')
Output:
Date Formatted Date
0 2021-01-01 2021-01-01
1 NaT NaN
2 2021-01-03 2021-01-03
In the above example, we checked for missing values using `~pd.isnull(df[‘Date’])` and applied strftime() only on the non-missing values.
Alternatively, we used the fillna() method to replace NaT with a default value (in this case, ‘1970-01-01’) before applying strftime().