Read the dataframe "global_dataframe" from a csv file in current directory called "Sum Data.csv". Define "KPI": Grouping the dataframe by column "Volt" and get mean information of columns "NEVs" and "MWhT". Execute "KPI" for "global_dataframe" as "gKPI". Calculate "NNewInd" as round the 10% of indexes of "global_dataframe". Calculate "NVEl" as number of different elements in the column "Volts" of "global_dataframe". Define the dataframe "RdataFrame" with columns: 1."absGap" 2. "dG1", "dG2", "dG3",etc. With "NVEI" columns. 3. "Id1","Id2","Id3", etc. With "NNewInd" columns.

def main():
    global_dataframe = pd.read_csv("Sum Data.csv", index_col=0)
    gKPI = global_dataframe.groupby("Volt").mean()[["NEVs", "MWhT"]]
    NNewInd = math.floor(0.1 * len(global_dataframe.index))
    NVEl = len(global_dataframe["Volt"].unique())
    RdataFrame = pd.DataFrame(columns=["absGap"] + ["dG" + str(x) for x in range(1, NVEl + 1)] + ["Id" + str(x) for x in range(1, NNewInd + 1)])
    pass