title: How to sub-select rows for equality with float dtype using pandas
body: <p>I have the following dataset example.</p>
  
  <pre><code>df_csv_y =  pd.read_csv('y_factors.csv')
  
                   time    value
  0       736527.481944  27.20001
  1       736527.482639  27.10001
  2       736527.483333  27.10001
  3       736527.484028  27.10001
  4       736527.484722  27.10001
                ......
  </code></pre>
  
  <p>And I tried the index using the code below.</p>
  
  <pre><code>df_csv_y[df_csv_y.time== 736527.482639]
  </code></pre>
  
  <p>I indexed the values that existed in the dataset, but the results were as follows.</p>
  
  <pre><code>Empty DataFrame
  Columns: [time, value]
  Index: []
  </code></pre>
  
  <p>I get the result when I retrieve an integer, but I can not retrieve the float data like the time column of the dataset above.</p>
  
  <p>i want to know how solve this problem.</p>