Define an interger variable "NVEI" Define an interger variable "NNewInd" Define the dataframe "RdataFrame" with columns: - "absGap" - "dG1", "dG2", "dG3",etc. With "NVEI" columns. - "Id1","Id2","Id3", etc. With "NNewInd" columns. For the first index 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 absolute error, "absGap", and detailed error per "Volt" value, "detGap", between "sKPI" and "gKPI". - 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.

NVEI = 4
NNewInd=2
RdataFrame=pd.DataFrame(
    {"absGap":[np.nan]*1000,
    "dG1":[np.nan]*1000,
    "dG2":[np.nan]*1000,
    "dG3":[np.nan]*1000,
    "dG4":[np.nan]*1000,
    "Id1":[np.nan]*1000,
    "Id2":[np.nan]*1000,
    "Id3":[np.nan]*1000,
    "Id4":[np.nan]*1000,
    }
)
RdataFrame.loc[0,"dG1"]=gKPI.loc["time",1]

for i in range(1000):
    SDFrame = global_dataframe.sample(frac=0.1)
    sKPI=KPI(SDFrame)
    absGap=abs(sKPI.loc["time",1]-gKPI.loc["time",1])
    detGap=np.array(