title: How can I illustrate Python-Pandas describe() tables in one statement?
body: <p>I was trying to analyse a group of data sets. However, I could not find a way to show effectively. I thought maybe <code>groupby()</code> can solve it but I was planning to show all the tables at once and I do not know how should I illustrate it. My other solution is showing each column in a comparison; first, second, then third. This is what I mainly want to achieve E.g.: </p>
  
  <pre><code>                  Mean  Std   Max  Min
  First_Result_Set
  Second_Result_Set
  Third_Result_Set
  </code></pre>
  
  <p>This is my another solution (may not be good):</p>
  
  <pre><code>                               Mean  Std   Max  Min
  First_Result_Set_first_column
  Second_Result_Set_first_column
  Third_Result_Set_first_column
  </code></pre>
  
  <p>Any suggestion or solution would be helpful.
  Codes:</p>
  
  <pre><code>def analyse_data(self, np_array, raw=45, column=3):
      df = pd.DataFrame(np_array.reshape(raw, column),
                        columns=("Time", "Random Score", "AI Score"))
      data_result = df.describe()
      print(data_result)
      return data_result
  
  analyse_cache_ab_classes_depth_5 = file.analyse_data(cache_ab_classes_depth_5)
  
  analyse_cache_ab_classes_depth_4 = file.analyse_data(cache_ab_classes_depth_4)
  
  analyse_cache_ab_classes_depth_3 = file.analyse_data(cache_ab_classes_depth_3)
  </code></pre>
  
  <p>Output: </p>
  
  <pre><code>            Time  Random Score   AI Score
  count  45.000000     45.000000  45.000000
  mean    1.054444      2.355556  12.488889
  std     0.423377      2.496867   7.225656
  min     0.400000      0.000000   0.000000
  25%     0.850000      0.000000   6.000000
  50%     0.960000      2.000000  14.000000
  75%     1.180000      4.000000  16.000000
  max     2.620000      8.000000  28.000000
  
              Time  Random Score   AI Score
  count  45.000000     45.000000  45.000000
  mean    2.021333      5.644444  35.288889
  std     0.889095      4.270169  12.764692
  min     0.780000      0.000000  12.000000
  25%     1.310000      2.000000  28.000000
  50%     1.780000      4.000000  34.000000
  75%     2.590000      8.000000  42.000000
  max     4.220000     18.000000  76.000000
  
              Time  Random Score   AI Score
  count  45.000000     45.000000  45.000000
  mean    0.207333      1.822222  15.333333
  std     0.077295      2.124413   6.993503
  min     0.110000      0.000000   4.000000
  25%     0.150000      0.000000  10.000000
  50%     0.180000      2.000000  16.000000
  75%     0.250000      2.000000  20.000000
  max     0.380000     10.000000  30.000000
  </code></pre>