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ts_shape.transform ¤

Transform

Row-level filtering, column transformations, and timestamp utilities.

  • IntegerFilter: Equality/inequality/range filters for integer columns.
  • filter_value_integer_match: Select rows equal to a value.
  • filter_value_integer_not_match: Select rows not equal to a value.

  • filter_value_integer_between: Select rows within [min, max].

  • DoubleFilter: NaN removal and numeric ranges for floating-point columns.

  • filter_nan_value_double: Drop rows with NaN in the column.

  • filter_value_double_between: Select rows within [min, max].

  • StringFilter: Equality, contains, regex cleaning, and change detection.

  • filter_na_value_string: Drop rows with NA values.
  • filter_value_string_match: Select rows equal to a string.
  • filter_value_string_not_match: Select rows not equal to a string.
  • filter_string_contains: Select rows containing a substring.
  • regex_clean_value_string: Regex-based cleaning or replacement.

  • detect_changes_in_string: Detect row-to-row changes in a string column.

  • BooleanFilter: Detect raising/falling edges of boolean states.

  • filter_falling_value_bool: True→False transitions.

  • filter_raising_value_bool: False→True transitions.

  • IsDeltaFilter: Select rows by the is_delta flag.

  • filter_is_delta_true: Only True.

  • filter_is_delta_false: Only False.

  • DateTimeFilter: Before/after/between filters for timestamps.

  • filter_after_date: After a given date.
  • filter_before_date: Before a given date.
  • filter_between_dates: Between start and end dates.
  • filter_after_datetime: After a given datetime.
  • filter_before_datetime: Before a given datetime.

  • filter_between_datetimes: Between start and end datetimes.

  • CustomFilter: Free-form DataFrame.query string conditions.

  • filter_custom_conditions: Apply a query string to filter rows.

  • IntegerCalc: Numeric column calculations.

  • scale_column: Multiply by a factor.
  • offset_column: Add a constant.
  • divide_column: Divide by a constant.
  • subtract_column: Subtract a constant.
  • calculate_with_fixed_factors: Multiply then add.
  • mod_column: Modulo operation.

  • power_column: Raise to a power.

  • LambdaProcessor: Apply vectorized callables to columns.

  • apply_function: Apply a Python callable over a column's values.

  • TimestampConverter: Convert integer timestamps to tz-aware datetimes.

  • convert_to_datetime: Convert s/ms/us/ns to datetime in a timezone.

  • TimezoneShift: Timezone localization/conversion helpers.

  • shift_timezone: Convert timezones in-place.
  • add_timezone_column: Add a converted timestamp column.
  • detect_timezone_awareness: Check tz-awareness of a column.
  • revert_to_original_timezone: Convert back to original tz.
  • calculate_time_difference: Difference between two timestamp columns.

Modules: