I am currently working on creating a database where the tables are made from specific columns from an excel workbook. The algorithm iterates in a directory and saves the worksheet as a pandas dataframe and from there I select the columns:

```
df1 = pd.read_excel(file, 'sheet1')

```

From there I select the data I need with

```
def create_list(df1):
    i = 0
    list1 = [] 
    while isinstance(df1['foo-bar'][i], int):
        list1.append(df1['foo-bar'][i])
        i += 1
    return list1

```

The problem I'm facing is that sometimes the name of the column isn't 'foo-bar' but 'foo.bar'. Is there a way to select this column just if it contains 'foo' for example? Or an 'or' operator, that selects 'foo-bar' or 'foo.bar'?

I know that there should be a way with LIKE from sql, but I would prefer to do it with pandas.