title: Max and min values in pandas
body: <p>I have the following data:</p>
  
  <pre><code>High    Low Open    Close   Volume  Adj Close
  Date                        
  1999-12-31  1472.420044 1458.189941 1464.469971 1469.250000 374050000   1469.250000
  2000-01-03  1478.000000 1438.359985 1469.250000 1455.219971 931800000   1455.219971
  2000-01-04  1455.219971 1397.430054 1455.219971 1399.420044 1009000000  1399.420044
  2000-01-05  1413.270020 1377.680054 1399.420044 1402.109985 1085500000  1402.109985
  2000-01-06  1411.900024 1392.099976 1402.109985 1403.449951 1092300000  1403.449951
  ... ... ... ... ... ... ...
  2020-01-06  3246.840088 3214.639893 3217.550049 3246.280029 3674070000  3246.280029
  2020-01-07  3244.909912 3232.429932 3241.860107 3237.179932 3420380000  3237.179932
  2020-01-08  3267.070068 3236.669922 3238.590088 3253.050049 3720890000  3253.050049
  2020-01-09  3275.580078 3263.669922 3266.030029 3274.699951 3638390000  3274.699951
  2020-01-10  3282.989990 3268.010010 3281.810059 3273.739990 920449258   3273.739990
  5039 rows × 6 columns
  </code></pre>
  
  <p>Since this is the daily data this was resampled to weekly to find the 52 week high and low. </p>
  
  <pre><code>weekly_high = data.High.groupby(pd.Grouper(freq='M')).tail(52)
  weekly_low = data.Low.groupby(pd.Grouper(freq='M')).tail(52)
  </code></pre>
  
  <p>Here is the problem:</p>
  
  <pre><code>weekly_high.max()
  </code></pre>
  
  <p>yields: 3282.989990234375</p>
  
  <pre><code>weekly_low.min()
  </code></pre>
  
  <p>yeilds: 666.7899780273438</p>
  
  <p>These value are are issue because 3283.0 is the high so why am i getting in deimals? Secondly weekly low is is 666 which i know for a fact is incorrect. How can i fix this?</p>