Panda Dataframe - iterate through a dataframe and ignore NaN

I have a dataframe with the customer Id, first name, address1, address2 etc and I would like to merge all the address columns into one single address column.

How do I skip columns that have an empty string or None in their address1 column?

I use the following function but somehow but it looks like the loop enters the else part of the loop even though I add a break statement:

for index, row in customers_df.iterrows():
    if customers_df['address1'][index] != "None":
        customers_df['complete_address'] = customers_df["address1"].map(str) + ", " + customers_df["address2"].map(str) + ", " + customers_df["zip"].map(str) + ", " + customers_df["town"].map(str) + ", Switzerland"
        break
    else:
        customers_df['complete_address'] = np.nan

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