Define an interger variable "NVEI" with the value 128 Define an interger variable "NNewInd" with the value 16 Define the dataframe "RdataFrame" with columns: - "absGap" - "dG1", "dG2", "dG3",etc. With "NVEI" columns. - "Id1","Id2","Id3", etc. With "NNewInd" columns. For the index [0] of "RdataFrame", in the columns "dG1", "dG2", etc. Put the information of the column "time" of "gKPI" Start a loop of 1000 "Sample" in "Samples", per each sample: - Get sub dataframe "SDFrame" componed by 10% of the indexes of "global_dataframe" choosen randomly. Store the list "Indexes" of indexes choosen transposed. - Call "KPI" for "SDFrame" as "sKPI". - Calculate total error, "absGap", and detailled error "detGap" between "sKPI" and "gKPI" grouped by "time" column. - Store "absGap" and "detGap" in the dataframe "RdataFrame" in columns "aGap", "dG1", "dG2", "dG3",etc. - Store "Indexes" in the dataframe "RdataFrame" in the columns "Id1","Id2","Id3",etc.

global_dataframe = get_global_dataframe()
    global_dataframe = check_columns(global_dataframe)
    gKPI = KPI(global_dataframe)
    gKPI = gKPI.groupby('time').sum()
    
    NVEI = 128
    NNewInd = 16
    RdataFrame = pd.DataFrame(columns=['absGap'] + ['dG'+str(i) for i in range(1, NVEI+1)] + ['Id'+str(i) for i in range(1, NNewInd+1)])
    
    for i in gKPI.columns:
        RdataFrame[i][0] = gKPI[i][0]
        
    for sample in range(1000):
        SDFrame, Indexes = get_sample_dataframe(global_dataframe)
        
        sKPI = KPI(SDFrame)
        sKPI = sKPI.groupby('time').sum()
        
        absGap, detGap