What are the best practices for data cleaning?
An example of an AI chatbot conversation about data cleaning best practices.
What are the best practices for data cleaning?
The best practices for data cleaning include identifying and handling missing values, removing duplicates, and standardizing formats.
How do I handle missing values in my dataset?
You can handle missing values by either removing them, imputing them with mean/median/mode, or using algorithms that support missing values.
What tools can I use for data cleaning?
Popular tools for data cleaning include OpenRefine, Trifacta, and Python libraries like Pandas.
Can you explain how to remove duplicates?
To remove duplicates, you can use functions like 'drop_duplicates()' in Pandas or use SQL queries like 'SELECT DISTINCT'.
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