Python “for” problem - Can only tuple-index with a MultiIndex

Question

I wanna take array C2, size N,1, and make a array B, size N-1,1.

B[0] = C2[1]

B[1] = C2[2]

and so on. My code is:

import numpy as np
import pandas as pd

fields = "B:D"
data = pd.read_excel(r'C:\Users\file.xlsx', "Sheet2", usecols=fields)
N = 2

# Covariance calculation

C1 = data.cov() C2 = data.var()

B = np.zeros(shape=(N,1))

for i in B:
    B[i,1] = C2[i+1,1]

But the error is:

ValueError: Can only tuple-index with a MultiIndex

I know it is a simple mistake, but cant find where :S (new python user)

sjc · Accepted Answer · 2019-12-11 17:02:23Z

1

First, are you sure you need to be using numpy arrays? This seems like a job for python lists.

Next, what do you mean to be doing with for i in B:? what type is i?

In this case, iterating over B is going to set i to [0.], and you can now see that the next line is going to fail in the substitution

    B[[0.],i] = C2[[0.]+1,1]

In addition, the call to pd.var() returns a 1-d series, so the second index isn't doing anything.

I think you want to iterate over N like

for i in range(N):
    B[i,1] = C2[i+1]

edited Dec 11, 2019 at 17:02

answered Dec 11, 2019 at 16:42

sjc

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5 Comments

user208675 Over a year ago

This way it tells me TypeError: 'int' object is not iterable

sjc Over a year ago

My mistake answering before coffee. Fixed above.

user208675 Over a year ago

TypeError: can only concatenate list (not "int") to list Is it because of my variable types? Cs is Series (3,). B is float64 (3,1)

sjc Over a year ago

I see. The variance member function in pandas returns a series (which is like a 1-d array or vector), so there's only one index to specify the location within the Series. So your C2[i+1,1] should be C2[i+1]. You don't need the second index.

user208675 Over a year ago

Works! Thank you! for i in range(N): B[i] = C2[i+1]

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