I have multiple simple functions that need to be implemented on every row of certain columns of my dataframe. The dataframe is very like, 10 million+ rows. My dataframe is something like this:

```
Date      location   city        number  value
12/3/2018   NY       New York      2      500
12/1/2018   MN       Minneapolis   3      600
12/2/2018   NY       Rochester     1      800
12/3/2018   WA       Seattle       2      400

```

I have functions like these:

```
def normalized_location(row):
    if row['city'] == " Minneapolis":
        return "FCM"
    elif row['city'] == "Seattle":
        return "FCS"
    else:
        return "Other"

```

and then I use:

```
df['Normalized Location'] =df.apply (lambda row: normalized_location (row),axis=1)

```

This is extremely slow, how can I make this more efficient?