title: Pandas Dataframe Series To List - Suppress Float Scientific Notation
body: <p>I have a Pandas DataFrame with a float column that I convert to a list, then convert to a string, and then write to a text file for another use. </p>
  
  <p>For example:</p>
  
  <pre><code>df=pd.DataFrame([[0.0068149439999999999, 0.90550613999999996], [7.5699999999999997e-05, 0.48159182100000003], 
            [0.009679478, 0.50158892700000002], [0.020792602, 0.56266469899999993]], columns=['ColumnA', 'ColumnB'])
  
  TextToWrite='ColumnA = (' + str(df['ColumnA'].tolist())[1:-1] + ')'
  f=open('myfile.txt', 'w')
  f.write(TextToWrite)
  </code></pre>
  
  <p>However, I need the converted floats to not be in Scientific notation (7.5699999999999997e-05, in this example). What is the best way suppress scientific notation for these floats and does it make more sense to do it upfront in the Pandas DataFrame or after the series is already converted to a list?</p>
  
  <p>I looked into the "float_format" argument, which can be done with "to_csv" and "to_string" commands, but I'm not sure how I can do that and still write the string to the text file in the same format I do above. </p>