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* Comment calculer quelques statistiques de base

** L'entrée

On considère cette série :

 #+NAME: input
 | 14.0 | 7.6 | 11.2 | 12.8 | 12.5 | 9.9 | 14.9 | 9.4 | 16.9 | 10.2 | 14.9 | 18.1 | 7.3 | 9.8 | 10.9 | 12.2 | 9.9 | 2.9 | 2.8 | 15.4 | 15.7 | 9.7 | 13.1 | 13.2 | 12.3 | 11.7 | 16.0 | 12.4 | 17.9 | 12.2 | 16.2 | 18.7 | 8.9 | 11.9 | 12.1 | 14.6 | 12.1 | 4.7 | 3.9 | 16.9 | 16.8 | 11.3 | 14.4 | 15.7 | 14.0 | 13.6 | 18.0 | 13.6 | 19.9 | 13.7 | 17.0 | 20.5 | 9.9 | 12.5 | 13.2 | 16.1 | 13.5 | 6.3 | 6.4 | 17.6 | 19.1 | 12.8 | 15.5 | 16.3 | 15.2 | 14.6 | 19.1 | 14.4 | 21.4 | 15.1 | 19.6 | 21.7 | 11.3 | 15.0 | 14.3 | 16.8 | 14.0 | 6.8 | 8.2 | 19.9 | 20.4 | 14.6 | 16.4 | 18.7 | 16.8 | 15.8 | 20.4 | 15.8 | 22.4 | 16.2 | 20.3 | 23.4 | 12.1 | 15.5 | 15.4 | 18.4 | 15.7 | 10.2 | 8.9 | 21.0 |

** Les calculs

L'énoncé est « Calculer la moyenne et l'écart-type, le min, la médiane et le max
des données suivantes ».

Ceci se fait en une seule ligne de code avec pandas.

#+NAME: describe
#+BEGIN_SRC python :results value :var i=[[1]] :exports both :session e4574272-89b0-46a9-878c-dee64eea663b
  from pandas import DataFrame, set_option
  from tabulate import tabulate
  set_option("display.precision", 2)
  desc = DataFrame(i).T.describe()
  tabulate(desc, headers="keys", tablefmt="orgtbl", floatfmt=".2f")
#+END_SRC

#+RESULTS: describe
#+begin_example
|       |      0 |
|-------+--------|
| count |   1.00 |
| mean  |   1.00 |
| std   | nan    |
| min   |   1.00 |
| 25%   |   1.00 |
| 50%   |   1.00 |
| 75%   |   1.00 |
| max   |   1.00 |
#+end_example

#+CALL: describe(i=input)

#+RESULTS:
#+begin_example
|       |      0 |
|-------+--------|
| count | 100.00 |
| mean  |  14.11 |
| std   |   4.33 |
| min   |   2.80 |
| 25%   |  11.85 |
| 50%   |  14.50 |
| 75%   |  16.80 |
| max   |  23.40 |
#+end_example