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Rapidata results

RapidataResults #

Bases: dict

A specialized dictionary class for handling Rapidata API results. Extends the built-in dict class with specialized methods.

to_pandas #

to_pandas(split_details: bool = False) -> DataFrame
Warning

This method is currently under development. The structure of the results may change in the future.

Converts the results to a pandas DataFrame.

For Compare results, creates standardized A/B columns for metrics. For regular results, flattens nested dictionaries into columns with underscore-separated names.

Parameters:

Name Type Description Default
split_details bool

If True, splits each datapoint by its detailed results, creating a row for each response with global metrics copied.

 False

Returns:

Type Description
DataFrame

pd.DataFrame: A DataFrame containing the processed results

Raises:

Type Description
ValueError

If split_details is True but no detailed results are found
Source code in src/rapidata/rapidata_client/order/rapidata_results.py 
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def to_pandas(self, split_details: bool = False) -> pd.DataFrame:
    """
    Warning:
        This method is currently under development. The structure of the results may change in the future.

    Converts the results to a pandas DataFrame.

    For Compare results, creates standardized A/B columns for metrics.
    For regular results, flattens nested dictionaries into columns with underscore-separated names.

    Args:
        split_details: If True, splits each datapoint by its detailed results,
                      creating a row for each response with global metrics copied.

    Returns:
        pd.DataFrame: A DataFrame containing the processed results

    Raises:
        ValueError: If split_details is True but no detailed results are found
    """
    if "results" not in self or not self["results"]:
        return pd.DataFrame()

    if self["info"].get("orderType") is None:
        print("Warning: Results are old and Order type is not specified. Dataframe might be wrong.")

    # Check for detailed results if split_details is True
    if split_details:
        if not self._has_detailed_results():
            raise ValueError("No detailed results found in the data")
        return self._to_pandas_with_detailed_results()

    if self["info"].get("orderType") == "Compare" or self["info"].get("orderType") == "Ranking":
        return self._compare_to_pandas()

    # Get the structure from first item
    first_item = self["results"][0]
    columns = []
    path_map = {}  # Maps flattened column names to paths to reach the values

    # Build the column structure once
    self._build_column_structure(first_item, columns, path_map)

    # Extract data using the known structure
    data = []
    for item in self["results"]:
        row = []
        for path in path_map.values():
            value = self._get_value_from_path(item, path)
            row.append(value)
        data.append(row)

    return pd.DataFrame(data, columns=Index(columns))

to_json #

to_json(path: str = './results.json') -> None

Saves the results to a JSON file.

Parameters:

Name Type Description Default
path str

The file path where the JSON should be saved. Defaults to "./results.json".

 './results.json'
Source code in src/rapidata/rapidata_client/order/rapidata_results.py 
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def to_json(self, path: str="./results.json") -> None:
    """
    Saves the results to a JSON file.

    Args:
        path: The file path where the JSON should be saved. Defaults to "./results.json".
    """
    with open(path, 'w') as f:
        json.dump(self, f)