Issues with try/except, attempting to convert strings to integers in pandas data frame where possible

insert the columm.append into the try:

for col in list_of_columns:    column = []    for row in list(df[col]):        try:            column.append(remove_html(row))        except ValueError:            pass    del df[col]    df[col] = columnreturn df

consider the pd.DataFrame df

df = pd.DataFrame(dict(A=[1, '2', '_', '4']))

You want to use the function pd.to_numeric...
Note
pd.to_numeric operates on scalars and pd.Series. It doesn't operate on a pd.DataFrame
Also
Use the parameter errors='coerce' to get numbers where you can and NaN elsewhere.

pd.to_numeric(df['A'], 'coerce')0    1.01    2.02    NaN3    4.0Name: A, dtype: float6

Or, to get numbers where you can, and what you already had elsewhere

pd.to_numeric(df['A'], 'coerce').combine_first(df['A'])0    11    22    _3    4Name: A, dtype: object

you can then assign it back to your df

df['A'] = pd.to_numeric(df['A'], 'coerce').combine_first(df['A'])

Works like this:

def clean_df(df):df = df.astype(str)list_of_columns = list(df.columns)for col in list_of_columns:    column = []    for row in list(df[col]):        try:            column.append(int(remove_html(row)))        except ValueError:            column.append(remove_html(row))    del df[col]    df[col] = columnreturn df