vdmtools.utils.DataframeUtils
- class vdmtools.utils.DataframeUtils
Utility class for pandas DataFrames containing VdM scan data.
Methods
filter_by_cov_status(data, cov_status)Filter the given DataFrame by the covariance matrix status.
filter_by_fit_status(data, fit_status)Filter the given DataFrame by the fit status.
filter_by_status(data, ...)Filter the given DataFrame by the status.
match_bcids(dataframe1, dataframe2)Match BCIDs of two DataFrames.
- static filter_by_cov_status(data: DataFrame, cov_status: int) DataFrame
Filter the given DataFrame by the covariance matrix status.
- Parameters:
data (pd.DataFrame) – The DataFrame to filter.
cov_status (int) – The covariance matrix status to filter by. Can be one of 3 (good), 2 (bad).
- Returns:
The filtered DataFrame.
- Return type:
pd.DataFrame
Notes
The provided DataFrame must contain the columns “covStatus_X” and “covStatus_Y”.
- static filter_by_fit_status(data: DataFrame, fit_status: int) DataFrame
Filter the given DataFrame by the fit status.
- Parameters:
data (pd.DataFrame) – The DataFrame to filter.
fit_status (int) – The fit status to filter by. Can be one of 0 (good), 4 (bad).
- Returns:
The filtered DataFrame.
- Return type:
pd.DataFrame
Notes
The provided DataFrame must contain the columns “fitStatus_X” and “fitStatus_Y”.
- static filter_by_status(data: DataFrame, status_column_with_no_plane: str, status: int) DataFrame
Filter the given DataFrame by the status.
- Parameters:
data (pd.DataFrame) – The DataFrame to filter.
status_column_with_no_plane (str) – The name of the column containing the status for the plane with no plane.
status (int) – The status to filter by. Can be one of 0 (good), 1 (bad).
- Returns:
The filtered DataFrame.
- Return type:
pd.DataFrame
- static match_bcids(dataframe1: DataFrame, dataframe2: DataFrame) Tuple[DataFrame, DataFrame]
Match BCIDs of two DataFrames.
- Parameters:
dataframe1 (pd.DataFrame) – First DataFrame.
dataframe2 (pd.DataFrame) – Second DataFrame.
- Returns:
Tuple containing two DataFrames with matching BCIDs in their index.
- Return type:
Tuple[pd.DataFrame, pd.DataFrame]
Notes
This function expects that both DataFrames the BCID values as their index. From there, it will return two DataFrames with matching BCIDs.
Examples
>>> import pandas as pd >>> df1 = pd.DataFrame({"BCID": [1, 2, 4, 5, 7], "Values": [1, 2, 3, 4, 5]}).set_index("BCID") >>> df1 Values BCID 1 1 2 2 4 3 5 4 7 5 >>> df2 = pd.DataFrame({"BCID": [1, 2, 3, 6, 7], "Values": [1, 2, 3, 4, 5]}).set_index("BCID") >>> df2 Values BCID 1 1 2 2 3 3 6 4 7 5 >>> df1, df2 = match_bcids(df1, df2) >>> df1 Values BCID 1 1 2 2 7 5 >>> df2 Values BCID 1 1 2 2 7 5