benchmark/analysis.py
def minimize_ms_dataframes_helper(dfs: List[pd.DataFrame]) -> pd.DataFrame:
    """
    Create a new in-memory DataFrame that, for each row of all the dataframes in dfs, keeps only the row with the
    minimum 'ms' value.
    :param dfs: List of DataFrames for a single program
    :return: new DataFrame minimized row-wise wrt the value of the 'ms' column
    """
    columns = ['ms', 'output', 'n', 'm', 'filename']
    min_df = pd.DataFrame(columns=columns)

    n_rows = dfs[0].shape[0]
    for row in range(n_rows):
        min_index, _ = get_min_at_row(dfs, row, column='ms')
        data = dfs[min_index].loc[row]
        min_df = min_df.append(data)

    return min_df.round(decimals=N_DECIMALS)

    Create a new in-memory DataFrame that, for each row of all the dataframes in dfs, keeps only the row with the
    minimum 'ms' value.
    :param dfs: List of DataFrames for a single program
    :return: new DataFrame minimized row-wise wrt the value of the 'ms' column
    
Create a new in-memory DataFrame that, for each row of all the dataframes in dfs, keeps only the row with the
minimum 'ms' value.
Create a new in - memory DataFrame that for each row of all the dataframes in dfs keeps only the row with the minimum ' ms ' value .
def minimize_ms_dataframes_helper(dfs: List[pd.DataFrame]) -> pd.DataFrame:
    columns = ['ms', 'output', 'n', 'm', 'filename']
    min_df = pd.DataFrame(columns=columns)
    n_rows = dfs[0].shape[0]
    for row in range(n_rows):
        min_index, _ = get_min_at_row(dfs, row, column='ms')
        data = dfs[min_index].loc[row]
        min_df = min_df.append(data)
    return min_df.round(decimals=N_DECIMALS)
def minimize_ms_dataframes_helper ( dfs : List [ pd . DataFrame ] ) -> pd . DataFrame : columns = [ 'ms' , 'output' , 'n' , 'm' , 'filename' ] min_df = pd . DataFrame ( columns = columns ) n_rows = dfs [ 0 ] . shape [ 0 ] for row in range ( n_rows ) : min_index , _ = get_min_at_row ( dfs , row , column = 'ms' ) data = dfs [ min_index ] . loc [ row ] min_df = min_df . append ( data ) return min_df . round ( decimals = N_DECIMALS )
Create a new in-memory DataFrame that, for each row of all the dataframes in dfs, keeps only the row with the
minimum 'ms' value.
Create a new in - memory DataFrame that for each row of all the dataframes in dfs keeps only the row with the minimum ' ms ' value .
"""
    Create a new in-memory DataFrame that, for each row of all the dataframes in dfs, keeps only the row with the
    minimum 'ms' value.
    :param dfs: List of DataFrames for a single program
    :return: new DataFrame minimized row-wise wrt the value of the 'ms' column
    """
new DataFrame minimized row-wise wrt the value of the 'ms' column
new DataFrame minimized row - wise wrt the value of the ' ms ' column
dfs
List[pd.DataFrame]
List of DataFrames for a single program
List of DataFrames for a single program