Data cleaning is the process of fixing or removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset. When combining multiple data sources, there are many opportunities for data to be duplicated or mislabeled.
Dropping missing values, or filling them in with an automated workflow.
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Avoiding UnicoodeDecodeErrors when loading CSV files.
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Transforming numeric variables to have helpful properties.
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Recognizing dates as composed of day, month, and year.
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Efficiently fixing typos in your data.
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