CODEWITHSUNDEEP
pythonpandasnumpy
fardy013
fardy013

Reputation: 33

pandas formation index looping

How to I do the following type of process using a for loop in pandas (indexing the the location index of the column)

z1 = math.sqrt( (df.loc[0,"A #1"] - a_mean[0])**2 + (df.loc[0,"B #1"] - b_mean[0]) **2)

z2 = math.sqrt( (df.loc["A #2"] - a_mean[0])**2 + (df.loc[0,"B #2"] - b_mean[0]) **2)

    input: 

a_mean = [ 1, 2, 3]
b_mean = [1, 2, 3 ]

     x#1     A #1     A #2   A #3    B#1    B#2   B#3

0     1       2       3       4       5     6      7
1     1       2       3       4       5     6      7

output: 
       (z list [1]   (z list [2)
 z1 0  answers         answers
 z2 1     ?               ?

Upvotes: 0

Views: 47

Answers (1)

Antoine Zambelli
Antoine Zambelli

Reputation: 764

Is this what you mean?

z = []
for i in range(1,n):
    z_p = []
    for s in range(0,3):
        z_p.append(math.sqrt( (df.loc["A #"+str(i)] - a_mean[s])**2 + (df.loc[s,"B #"+str(i)] - a_mean[s]) **2))
    z.append(z_p)

Another possibility is to use dataframe.apply, though you might need multiple calls if you have a lot of functions to apply to each column.

Upvotes: 1

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