Currently facing an issue (data cleaning) of looking at multiple columns in a df that contain the word "food" and then creating a new column named 'food' with the found value

I can search for each specific column however running into issues when searching through the entire dataset (looking at every column and not overriding the previous entry)

```
s = df['tag_1'].str.contains('food')
df['food'] = df.tag_1.where(s)

```

Current:

| tag\_1 | tag\_2 | tag\_3 |
| --- | --- | --- |
| placeholder | placeholder | French food |
| British food | placeholder | placeholder |
| placeholder | German food | placeholder |

Ideal:

| tag\_1 | tag\_2 | tag\_3 | food |
| --- | --- | --- | --- |
| placeholder | placeholder | French food | French food |
| British food | placeholder | placeholder | British food |
| placeholder | German food | placeholder | German food |