4-5. Frame - Data Cleaning

  1. Fill NA: Replace NA with another value.

  2. Drop NA: Remove rows or columns containing NA.

  3. Fill Outlier: Replace outliers in specific columns.

  4. Drop Outlier: Remove outliers in specific columns.

  5. Drop Duplicates: Remove duplicate values.

Fill NA

  1. Method: Choose the filling method.

1-1. Value: Replace NA with the specified input value.

1-2. Forward/Back Fill: Replace NA with values from the front/back. If NA is consecutive, you can set the 'Limit' to determine how many values to fill.

1-3. Statistics: Fill in with statistical properties.

Drop NA

  1. How

1-1. Select Options: Keep only rows with the number of non-NA values set by the threshold, and delete the rest.

1-2. Any: Delete rows if there is at least one NA in the row.

1-3. All: Delete rows if all values in the row are NA.

  1. Ignore Index: Choose whether to reset the index after row deletion.

Drop Duplicates

  1. Keep: Choose the value to retain among the duplicate values. Selecting False will result in the deletion of all duplicate values.

  2. Ignore Index: Choose whether to reset the index after duplicate values deletion.

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