title: Filtering pandas column
body: <p>I'm trying to do preprocessing where I'm finding all text submitted by an individual in the US. All users in the US can be placed into the same location. The exact location in the US is not needed.<br />
  I have a dataset similar to:</p>
  <pre><code>created_at    text       lang       location                 by
  Wed Jul 8    some text.  english.   New York, NY.          User 1
  Wed Jul 8    some text.  english.   Washington, DC.        User 1
  Wed Jul 8    some text.  english.   Baltimore.             User 1
  Wed Jul 8    some text.  english.   DC, US.                User 1
  Wed Jul 8    some text.  english.   The United States.     User 1
  Wed Jul 8    some text.  english.   US.                    User 1
  Wed Jul 8    some text.  english.   Poland.                User 1
  Wed Jul 8    some text.  english.   1234332.               User 1
  Wed Jul 8    some text.  english.   The Earth.              User 1
  Wed Jul 8    some text.  english.   Nottingham.              User 1
  Wed Jul 8    some text.  english.   Leicestershire, England  User 1
  Wed Jul 8    some text.  english.   ⬛️⬛️⬛️⬛️⬛️⬛️ [REDACTED]    User 1
  Wed Jul 8    some text.  english.   天国の門                  User 1
  
  </code></pre>
  <p>Instead of going through the dataset and removing all non-US states, states, county, etc one by one. Is there an easily access df.locations and get all locations ex New York, NY, Washington, DC, DC, Us, Baltimore, The United States, and US? This is only a small portion of the data this is why I'm trying to find a more streamlined approach.</p>