Missing Values

Endpoint: POST /missingValues

Request Parameters

File Upload

• file (required): CSV file to be processed.
• columns (required)
  • A comma-separated list of column names to process.

Form Parameters

• numeric_method (optional, default: mean)
  • Strategy for imputing missing numeric values.
  • Supported values: mean, median, mode, constant, strong_imputation, weak_imputation, multiple_imputation.
• categorical_method (optional, default: constant)
  • Strategy for imputing missing categorical values.
  • Supported values: mode, constant.
• categorical_value (optional, default: unknown)
  • Value used for constant method in categorical columns.
• datetime_method (optional, default: forward_fill)
  • Strategy for imputing missing datetime values.
  • Supported values: forward_fill, backward_fill, constant.
• threshold (optional, default: 1.0)
  • Percentage threshold for dropping columns with missing values (range: 0.0 - 1.0).

Imputation Strategies

Numeric Data

• Mean (mean): Fills missing values with the column mean.
• Median (median): Fills missing values with the column median.
• Mode (mode): Fills missing values with the most frequent value.
• Constant (constant): Fills missing values with a user-defined value.
• Strong Imputation (strong_imputation): Uses linear regression to estimate missing values.
• Weak Imputation (weak_imputation): Uses forward fill method.
• Multiple Imputation (multiple_imputation): Uses multiple imputations via MICE.

Categorical Data

• Mode (mode): Fills missing values with the most frequent value.
• Constant (constant): Fills missing values with a user-defined value.

Datetime Data

• Forward Fill (forward_fill): Fills missing values with the previous available value.
• Backward Fill (backward_fill): Fills missing values with the next available value.
• Constant (constant): Fills missing values with a user-defined value.