Pandas Dataframe apply() method provides a row object, but how do you access the index value

apply, pandas, python

Solution

I believe what you want is this:

def my_test(row):
   return "{}.{}".format(row.name, row['b'])

THis works because:

"{}.{}".format("ham", "cheese")

returns

'ham.cheese'

and if you reference a single row, the name attribute returns the index. For the example above:

df.iloc[0].name

returns

b                           foo
c                      1.417726
Value    0.7842562355491481.foo
Name: 0.784256235549, dtype: object

Therefore this function is equivalent to finding the index of the ith row and executing this command

"{}.{}".format(df.iloc[i].name, df.iloc[i]['b'])

then the apply function does this for all rows.

Problem

I am new to Panda's and DataFrames and have run into an issue. The DataFrame.apply() method passes a row parameter to the provided function. However I can't seem to find out what the index value corresponding to that row is from this row parameter. An example ``` df = DataFrame ({'a' : np.random.randn(6), 'b' : ['foo', 'bar'] * 3, 'c' : np.random.randn(6)}) df = df.set_index('a') def my_test2(row): return "{}.{}".format(row['a'], row['b']) df['Value'] = df.apply(my_test2, axis=1) ``` Yields a KeyError ``` KeyError: ('a', u'occurred at index -1.16119852166') ``` The problem is that the row['a'] in the my_test2 method fails. If I don't do the df.set_index('a') it works fine, but I do want to have an index on a. I tried duplicating column a (once as index, and once as a column) and this works, but this just seems ugly and problematic. Any ideas on how to get the corresponding index value given the row object? Many thanks in advance.

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