I have recently included a new column in the table called

and my intention now is to populate this column with values for each entry, based on the conditions of the

and

column values.

Query:

My dataframe consists of values like

My objective is to create a new column by combining values from column A and B, such as

I am under the impression that this can be achieved using a lambda function, but I am struggling to comprehend the process.

Question:

I have a dataframe with values like

```
A B
1 4
2 6
3 9
```

It is necessary to create an additional column by combining the values in column A and B, referred to as

adding values

.

```
A B C
1 4 5
2 6 8
3 9 12
```

I think a lambda function can achieve this, but I’m unsure about the implementation.

Solution 1:

Very simple:

```
df['C'] = df['A'] + df['B']
```

Solution 2:

Expanding on Anton’s response, an alternative approach would be to include all the columns in the following manner:

```
df['sum'] = df[list(df.columns)].sum(axis=1)
```

Solution 3:

One option is to utilize the DeepSpace answer as the easiest approach. Nonetheless, if the preference is to use an anonymous function, the apply method can be employed.

```
df['C'] = df.apply(lambda row: row['A'] + row['B'], axis=1)
```

Solution 4:

As mentioned in the comment by @EdChum, you have the option of utilizing the

sum

function to accomplish this.

```
df['C'] = df[['A', 'B']].sum(axis=1)
In [245]: df
Out[245]:
A B C
0 1 4 5
1 2 6 8
2 3 9 12
```