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Waiting for the complete script execution box to pop up and press OK.Q:

How to compare the exprimental data from multiple columns

I have an input column with a float value range in which i put a list of positive and negative numbers. My goal is to figure out that the input column matches the output only if the exprimental results from the two columns are equal or not.
I have tried the below code for this:
raw_input = np.array(raw_input)
raw_output = np.array(raw_output)

def check(input_column, output_column):
return input_column.exp(output_column) == output_column

check([1,2], [4,6])

I get an error ‘arguments did not match any overloaded call’

A:

This is what you want:
raw_input = np.array(raw_input)
raw_output = np.array(raw_output)

def check(input_column, output_column):
return input_column.exp(output_column) == output_column

check(raw_input, raw_output)

However, there is a problem here, the function does not take all the necessary arguments, so when you do check([1,2], [4,6]), it does not compare the two arrays but it actually compares the float result of the arrays to the arrays themselves. And that is why you get an error. You may want to consider the below example, if you want to compare the array values:
raw_input = np.array(raw_input)
raw_output = np.array(raw_output)

def check(input_column, output_column):
res =

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https://colab.research.google.com/drive/12zsTSFhhEKXnHLCqlUCzs1Rq3kDXzyhj

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