title: Pandas boolean dataframe search returns False but should be True
body: <h2>The Problem</h2>
  
  <p>I'm attempting to search through a pandas dataframe to find a single value. The dataframe columns I'm searching through are of type float64. </p>
  
  <h2>Working Example</h2>
  
  <p>Here is a working example of what I'd like, with a dataframe of type int64.</p>
  
  <pre><code>myseries = pd.Series([1,4,0,7,5], index=[0,1,2,3,4])
  myseries
  </code></pre>
  
  <p>The output is the following:</p>
  
  <pre><code>0    1
  1    4
  2    0
  3    7
  4    5
  dtype: int64
  </code></pre>
  
  <p>Now for the search:</p>
  
  <pre><code>myseries == 4
  </code></pre>
  
  <p>Results:</p>
  
  <pre><code>0    False
  1     True
  2    False
  3    False
  4    False
  dtype: bool
  </code></pre>
  
  <h2>Not Working Example</h2>
  
  <p>Here is a sample of my data.</p>
  
  <pre><code>df['difference']
  </code></pre>
  
  <p>Result</p>
  
  <pre><code>0    -2.979296
  1    -0.423903
  2     0.396515
  ...
  48    0.450493
  49   -1.216324
  Name: priceDiff1, dtype: float64
  </code></pre>
  
  <p>As you can see, it is of type float64.
  Now here's the issue. If I copy the value on row 2, and create a conditional statement like before, it doesn't return the True.</p>
  
  <pre><code>df['difference'] == 0.396515
  </code></pre>
  
  <p>Output</p>
  
  <pre><code>0     False
  1     False
  2     False
  ...
  48    False
  49    False
  Name: priceDiff1, dtype: bool
  </code></pre>
  
  <p>Row 2 should be True.
  Any assistance at this issue with this issue would be great.
  What I believe is happening, is that my query isn't setting the type to float64 and might be assuming it's a different type. I've tested this by downcasting the column type from float64 to float32, with no luck.</p>