What are some effective data cleaning methods in Pandas?
An example of an AI chatbot conversation about data cleaning methods using Pandas.
What are some effective data cleaning methods in Pandas?
Some effective data cleaning methods in Pandas include handling missing values, removing duplicates, and converting data types.
How can I handle missing values in my DataFrame?
You can handle missing values using methods like fillna(), dropna(), or by using interpolation.
What does the drop_duplicates() function do?
The drop_duplicates() function removes duplicate rows from your DataFrame, keeping the first occurrence by default.
Can you show me an example of using fillna()?
Sure! You can use df.fillna(value) to replace NaN values with a specified value, like df.fillna(0) to replace NaNs with 0.
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