import pandas

def csv_to_df(path, rows, type):

    df = pandas.read_csv(path, encoding = "ISO-8859-1", skiprows=[i for i in range(1,10)])
    df_split = df["[HEADER]"].str.split(";", expand = True)
    df_result = pandas.DataFrame()
    columns = df_split.iloc[0]
    fields = ["Date"]
    indexToStore = [0]
    if(type == "conso"):
        new_df = pandas.DataFrame()
        new_df['Date'] = df_split.iloc[:,0]
        for j in range(1, len(columns)):
            for value in rows:
                if(columns[j] == value):
                    print(value + " : " + str(j))
                    indexToStore.append(j)
                    #new_df[value] = df_split.iloc[:,j]
                #fields.append(value)
        #print(fields)
        print("INDEX : " + str(indexToStore))
        test_df = df_split[indexToStore]
        for i in range(0, len(rows)):
            fields.append(rows[i])
        test_df.columns = fields
        df_result = test_df
    else :
        for i in range(0, len(rows)):
            fields.append(rows[i])
            df_split.columns = fields
            df_result = df_split
    return df_result

#csv_to_df("./Projet/jeu de données/0100001707/Froid alim - C1+/Temp. ext.reprise condenseur.csv", ["CV"], "temp")
csv_to_df("./Projet/jeu de données/0100001707/Comptage/Tarif Vert A8.csv", ["TOT_A", "PUISSANCE_A"], "conso")