Branch-AI/piscine/week01/day05/ex02/audit/README.md

The exercice is validated is all questions of the exercice are validated

Have you checked missing values and data types ?

Have you converted string dates to datetime ?

Have you set dates as index ?

Have you used info or describe to have a first look at the data ?

The question 1 is validated if you inserted the right columns in Candlestick Plotly object. The Candlestick is based on Open, High, Low and Close columns. The index is Date (datetime).

This question 2 is validated if the output of print(transformed_df.head().to_markdown()) is as below and if there are 482 months.

Date	Open	Close	Volume	High	Low
1980-12-31 00:00:00	0.136075	0.135903	1.34485e+09	0.161272	0.112723
1981-01-30 00:00:00	0.141768	0.141316	6.08989e+08	0.155134	0.126116
1981-02-27 00:00:00	0.118215	0.117892	3.21619e+08	0.128906	0.106027
1981-03-31 00:00:00	0.111328	0.110871	7.00717e+08	0.120536	0.09654
1981-04-30 00:00:00	0.121811	0.121545	5.36928e+08	0.131138	0.108259

To get this result there are two ways: resample and groupby. There are two key steps:

• Find how to affect the aggregation on the last business day of each month. This is already implemented in Pandas and the keyword that should be used either in resample parameter or in Grouper is BM.
• Choose the right aggregation function for each variable. The prices (Open, Close and Adjusted Close) should be aggregated by taking the mean. Low should be aggregated by taking the minimum because it represents the lower price of the day, so the lowest price on the month is the lowest price of the lowest prices on the day. The same logic applied to High, leads to use the maximum to aggregate the High. Volume should be aggregated using the sum because the monthly volume is equal to the sum of daily volume over the month.

The question 3 is validated if it doesn't involve a for loop and the output is as below. The first way to do it is to compute the return without for loop is to use pct_change. And the second way to do it is to implement the formula given in the exercise in a vectorized way. To get the value at t-1 you can use shift.

```console
Date
1980-12-12         NaN
1980-12-15   -0.047823
1980-12-16   -0.073063
1980-12-17    0.019703
1980-12-18    0.028992
                ...   
2021-01-25    0.049824
2021-01-26    0.003704
2021-01-27   -0.001184
2021-01-28   -0.027261
2021-01-29   -0.026448
Name: Open, Length: 10118, dtype: float64
```