Assign True/False condition based on existing columns

Just do any

df.loc[:,'col2':].any(1)
0     True
1    False
2     True
3     True
dtype: bool

#df['col10']=df.loc[:,'col2':].any(1)

You have done two wrong things here. One is missed iterating through rows and second is involved col1 in the expression. Here's what I've tried in a similar way that you've tried.

df['col10'] = False
for index, row in df.iterrows():
    if row['col2'] or row['col3'] or row['col4'] or row['col5'] or row['col6'] or row['col7'] or row['col8'] or row['col9']:
        df.iloc[index,9] = True
    else:
        df.iloc[index,9] = False

A single line solution to the question would be:

df['col10'] = df.loc[:,'col2':].any(1)