How to Pass Pandas Dataframe and Column to a Function

Question

So I have a large amount of columns within a pandas dataframe and I need to pass groups of them through a function. The function is large but I'll create an example below. I am not sure how to pass the reference of df.varName to the function without getting the issue of the variable not being defined. When I try a function such as:

def bianco2(df, varX, varT):
    stdX = np.std(df.varX)
    stdT = np.std(df.varT)
    newVar = stdX + stdT
    return newVar

I get the error that varX isn't defined. So I wrote the function where I would pass the whole phrase:

def bianco3(varX, varT):
    stdX = np.std(varX)
    stdT = np.(varT)
    newVar = stdX + stdT
    return newVar

Where "varX = df.varX".

This worked but isn't practical for a large number of variables because I would still have to manually update each varX and varT. So I tried creating a list of variables in the format df.varX and then using a for loop to pass the list of variables. The issue is python sees it as a string and not a reference. I looked at using functools.partial but was unsuccessful.

Any ideas on how to write this in a simple format and be able to pass panda columns to a function?

Not sure what you mean. How would you call bianco2? Try posting a minimal reproducible example. — Stop harming Monica
– Stop harming Monica, Commented Feb 22, 2017 at 21:19

Shijo · Accepted Answer · 2017-02-22 21:20:34Z

5

You may want to try this ?

def bianco2(df, varX, varT):
    stdX = np.std(df[varX])
    stdT = np.std(df[varT])
    newVar = stdX + stdT
    return newVar

print bianco2(df,'Customer','Policy')

input

   Policy  Customer  Employee CoveredDate   LapseDate
0     123      1234      1234  2011-06-01  2013-01-01
1     124      1234      1234  2016-01-01  2013-01-01
2     124      5678      5555  2014-01-01  2013-01-01

output

  2095.39309492

answered Feb 22, 2017 at 21:20

Shijo

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1 Comment

dbianco Over a year ago

Thanks Shijo! That should simplify my issue.

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