How can I handle missing data in a Pandas DataFrame?
An example of an AI chatbot conversation about handling missing data in Pandas.
How can I handle missing data in a Pandas DataFrame?
You can handle missing data in Pandas using methods like dropna(), fillna(), or interpolate(). What specific method are you interested in?
Can you explain how to use fillna()?
Sure! The fillna() method allows you to replace NaN values with a specified value or method. For example, df.fillna(0) replaces all NaNs with 0.
What if I want to fill missing values with the mean of the column?
You can do that by using df.fillna(df['column_name'].mean()). This will replace NaNs in 'column_name' with the mean of that column.
Are there any other methods to handle missing data?
Yes, you can also use dropna() to remove rows with NaN values or interpolate() to estimate missing values based on surrounding data.
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