Removing words/characters from string in dataframe cell?

Question

I have a dataframe with a column that contains street intersections

|          Locations           |
--------------------------------
|W Madison Ave & S Randall Blvd|
|N Clemson St & E Tower Ave    |
|E Thompson St & S Garfield Ln |

I'd like to remove the directional characters (N, S, E, W) as well as the suffixes of the streets (Blvd, St, Ave, etc...) so that my output looks like this

|     Locations     |
---------------------
|Madison & Randall  |
|Clemson & Tower    |
|Thompson & Garfield|

I can't do a str.replace() because it would be removing characters from the words I need to stay. I tried using lstrip() and rstrip() but that wouldn't fix the characters I'd like removed from the middle of the string.

I also tried experimenting with Series.apply()

banned = ['N', 'S', 'E', 'W', 'Ave', 'Blvd', 'St', 'Ln']
df["Locations"].apply(lambda x: [item for item in x if item not in banned])

But this essentially does a str.replace() and places everything in a list in the dataframe instead.

Answer 1

You are close - you can split values first and then join:

f = lambda x: ' '.join([item for item in x.split() if item not in banned])
df["Locations"] = df["Locations"].apply(f)

Or list comprehension:

df["Locations"] = [' '.join([item for item in x.split() 
                  if item not in banned]) 
                  for x in df["Locations"]]


print (df)
             Locations
0    Madison & Randall
1      Clemson & Tower
2  Thompson & Garfield