Subtract two columns in dataframe

My df looks as follows:

Index    Country    Val1  Val2 ... Val10
1        Australia  1     3    ... 5
2        Bambua     12    33   ... 56
3        Tambua     14    34   ... 58

I'd like to substract Val10 from Val1 for each country, so output looks like:

Country    Val10-Val1
Australia  4
Bambua     23
Tambua     24

So far I've got:

def myDelta(row):
    data = row[['Val10', 'Val1']]
    return pd.Series({'Delta': np.subtract(data)})

def runDeltas():
    myDF = getDF() \
        .apply(myDelta, axis=1) \
        .sort_values(by=['Delta'], ascending=False)
    return myDF

runDeltas results in this error:

ValueError: ('invalid number of arguments', u'occurred at index 9')

What's the proper way to fix this?

Solution 1:

Given the following dataframe:

df = pd.DataFrame([["Australia", 1, 3, 5],
                   ["Bambua", 12, 33, 56],
                   ["Tambua", 14, 34, 58]
                  ], columns=["Country", "Val1", "Val2", "Val10"]
                 )

It comes down to a simple broadcasting operation:

>>> df["Val1"] - df["Val10"]
0    -4
1   -44
2   -44
dtype: int64

Solution 2:

Using this as the df:

df = pd.DataFrame([["Australia", 1, 3, 5],
               ["Bambua", 12, 33, 56],
               ["Tambua", 14, 34, 58]
              ], columns=["Country", "Val1", "Val2", "Val10"]
             )

You can also do the subtraction and put it into a new column as follows.

>>>df['Val_Diff'] = df['Val10'] - df['Val1']

    Country     Val1    Val2  Val10 Val_Diff
0   Australia   1       3      5    4
1   Bambua      12      33     56   44
2   Tambua      14      34     58   44

Solution 3:

You can do this by using lambda function and assign to new column.

df['Val10-Val1'] = df.apply(lambda x: x['Val10'] - x['Val1'], axis=1)
print df