Carlos Wyller Villanueva Machado

Generation

generate functionFri, 31 Mar 2023

giving a list "VInd" with complete index data and the dataframe "global_dataframe". Group "global_dataframe" by the column "Volt" with the mean value of columns "NEVs" and "MWhT" in the dataframe "SumDF". Complete the index "Volt" in "SumDF" with the information from "VInd" replacing the values NaN in the columns with the value of 0.

def summarize_with_NaN(global_dataframe, VoltInd):
  SumDF = global_dataframe.groupby("Volt").agg({"NEVs": "mean", "MWhT": "mean"})
  VoltInd = VoltInd.fillna(0)
  
  for i, row in VoltInd.iterrows():
    if row["Volt"] not in SumDF.index:
      SumDF.loc[row["Volt"]] = np.array([row["NEVs"], row["MWhT"]])
      
  return SumDF
  
summarize_with_NaN(global_dataframe, VoltInd)

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