title: Working with .csv data as a Pandas DataFrame, getting redundancy error when applying logic
body: <p>Been working on this project all day and it's destroying me. Currently have finished web scraping and have a final .csv which contains the elements of a pandas dataframe. Working with this dataframe in a new file, and currently have the following:</p>
  <pre><code>df = pd.read_csv('active_homes.csv')
  
  for i in range(len(df)):
      add = df['Address'][i]
      price = df['Price'][i]
      if (price&lt;100000) == True:
          print(price)
  </code></pre>
  <p>'<strong>active_homes.csv</strong>' looks like this:</p>
  <p>Address,Status,Price,Meta</p>
  <p>&quot;387 8th St, Burlington, CO 80807&quot;,For Sale,169500,&quot;4bed2bath1,560sqft&quot;</p>
  <p>,and the resulting df's <strong>shape</strong> is (1764, 4).</p>
  <p>This should, in theory, print the price for each iteration of price&lt;100000.</p>
  <p>In practice, it prints this:</p>
  <p><a href="https://i.stack.imgur.com/c2uPa.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/c2uPa.png" alt="example terminal output" /></a></p>
  <p>I have confirmed that at each iteration of the above for loop, it is collecting the correct 'Price' and 'Address' information, and have also confirmed that at each interval the logic (price&lt;100000) is working correctly. However, it is still doing the above. I was originally trying to just drop the rows of the dataframe that were &lt;100000 but that wasn't doing anything. I was also trying to reassign the data to a new dataframe and it would either return an empty dataframe, or return a dataframe with duplicate data of this house (with the 'Price' of 58900).</p>
  <p>So far, from all of that, I believe that the program is recognizing the amount of correct houses &lt; 100000, but for some reason the assignment is sticking for the one address. It also does the same thing without assignment, as in:</p>
  <pre><code>for i in range(len(df)):
      if (df['Price'][i]&lt;100000) == True:
          print(df['Price'][i])
  </code></pre>
  <p>Any help in identifying the error would be much appreciated.</p>