Good day. I am working on 2 dataframes that i will later be comparing, playersData & allStar . playersData['Year'] is type int64, while allStar is type object. i tried to convert the playersData['Year'] using the following code:
playersData['Year'] = playersData['Year'].astype(str).astype(int)
but it shows error saying:
ValueError: invalid literal for int() with base 10: 'nan'
the code I used is from the link: https://www.kite.com/python/answers/how-to-convert-a-pandas-dataframe-column-from-object-to-int-in-python
here is reference pics regarding types of my dataframes:
Try Dropping all the nan values from the dataset.
playersData.dropna(inplace=True)
You can either drop rows containing NaN values or replace them with a constant (In case there were few other columns containing valuable info, dropping rows might not be a good option).
If you want to drop playersData.dropna(inplace=True)
or playersData = playersData.dropna()
Replacing with a constant (Ex: 0) playersData['Year'].fillna(0, inplace=True)
or playersData['Year'] = playersData['Year'].fillna(0)
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