Branch-AI/piscine/week01/day04/ex04/audit/README.md

The exercice is validated is all questions of the exercice are validated and if the for loop hasn't been used. The goal is to use groupby and apply.

The question 1 is validated if the output is:

```python
    df = pd.DataFrame(range(1,11), columns=['sequence'])
    print(winsorize(df, [0.20, 0.80]).to_markdown())
```

|    |   sequence |
|---:|-----------:|
|  0 |        2.8 |
|  1 |        2.8 |
|  2 |        3   |
|  3 |        4   |
|  4 |        5   |
|  5 |        6   |
|  6 |        7   |
|  7 |        8   |
|  8 |        8.2 |
|  9 |        8.2 |

The question 2 is validated if the output is a Pandas Series or DataFrame with the first 11 rows equal to the output below. The code below give a solution.

|    |   sequence |
|---:|-----------:|
|  0 |       1.45 |
|  1 |       2    |
|  2 |       3    |
|  3 |       4    |
|  4 |       5    |
|  5 |       6    |
|  6 |       7    |
|  7 |       8    |
|  8 |       9    |
|  9 |       9.55 |
| 10 |      11.45 |


```python
def winsorize(df_series, quantiles):
"""
    df: pd.DataFrame or pd.Series
    quantiles: list [0.05, 0.95]

"""
min_value = np.quantile(df_series, quantiles[0])
max_value = np.quantile(df_series, quantiles[1])

return df_series.clip(lower = min_value, upper = max_value)


df.groupby("group")[['sequence']].apply(winsorize, [0.05,0.95])
```

• https://towardsdatascience.com/how-to-use-the-split-apply-combine-strategy-in-pandas-groupby-29e0eb44b62e