I was trying to write a solution, which is a different and a manual for calculating a mean and STD The way. I have created a = ["Apple", "Banana", "Cherry", "Apple"] B = [3,4,7,3] C = [5,4,1,4] D = [7,8,3,7] Pd DF = PD to import pandals DataFrame (index = class (4), column = list ("ABCD")) DF ["A"] = A DF ["B"] = BDF ["C"] = C DF ["D"] = D Again, I made a list of A duplication. Then I went through the group all the time of the objects and calculated the solution. import as np l = list (set (df.A)) df.groupby ('A', As_index = False) listMean = [0] * len (df.C) ListSTD = [0] * L in the LAN (df.C) X: s = np.mean (df [df ['A'] == x] for C =.) = Z = [index for index, enumerate In the object (df ['a']. Value] x == item i for z: listMean [i] = s in: s = np.std (df [df ['a'] == X] .cvalues) z = index for index, enumerate item (df ['a']. Value) if x ==...
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