Final answer:
To get rid of NaN values in Pandas, you can either use the dropna() method to remove rows or columns containing NaN, or use fillna() to replace NaN values with a specified value.
Step-by-step explanation:
The question is about how to handle NaN values (Not a Number) in Pandas, which is a Python library used for data analysis and manipulation. You can remove NaN values using several methods, depending on your needs.
Dropping NaN Values
To remove rows with NaN values from a DataFrame, you can use the dropna() method:
dataframe = dataframe.dropna()
This will drop all rows where any NaN values are present. If you want to drop columns, you can specify the axis:
dataframe = dataframe.dropna(axis=1)
Filling NaN Values
Alternatively, you can fill NaN values with a specific value using the fillna() method:
dataframe = dataframe.fillna(value)
Where value is the value you want to use to replace the NaN values.