I have the following dataframe named ***df***:

```
     V1  V2
IDS
a    1    2    
b    3    4

```

If I print out the index and the columns, this is the result:

```
> print(df.index)
Index(['a','b'],dtype='object',name='IDS',length=2)
> print(df.columns)
Index(['V1','V2'],dtype='object',length=2)

```

I want to perform a calculation on these two columns (row-wise) and add this to a new column. I have tried the following, but I can't seem to access the column as expected.

```
df['sum'] = df.apply(lambda row: row['V1'] + row['V2'], axis=1)

```

I get the following error running the last line of code:

```
KeyError: ('V1', 'occurred at index a')  

```

How do I access these columns?

---

Update: contrived example is not showing the error, here is the actual dataframe I am working with: 

```
       DATE        ...   gathering_size_100_to_26     shelter_in_place
FIPS
10001  2020-01-22  ...   2020-01-01                   2020-01-01
10002  2020-01-22  ...   2020-01-01                   2020-01-02
10003  2020-02-25  ...   2020-01-01                   2020-01-03
...    ...         ...   ...                          ...
9013   2020-02-22  ...   2020-01-01                   2020-01-01

```

I want to take the difference between 'gathering\_size\_100\_to\_26' and 'DATE', as well as 'shelter\_in\_place' and 'DATE' and replace this value in place.