Hi everybody,

I leave my solution for this project in the next link:

I hope it is useful for someone else and I await your comments for possible errors or suggestions.

Have a good day!

Gustavo

Hi everybody,

I leave my solution for this project in the next link:

I hope it is useful for someone else and I await your comments for possible errors or suggestions.

Have a good day!

Gustavo

Nice analysis and documentation! The solution looks correct to me - here are just some suggestions to make the code a bit shorter:

- To create a list with N zeros, you used:

```
[i * 0 for i in range(N)]
```

Alternatively, you could use:

```
[0 for i in range(N)]
```

or, even shorter:

```
[0]*N
```

- In counting the patients according to region, you apply an if-elif-else statement of the form:

```
if charge == data[0]:
cost[0] = ...
elif charge == data[1]:
cost[1] = ...
else:
...
```

Alternatively you could use the .index method of lists to find the index of charge in data and avoid the if-else completely:

```
idx = data.index(charge)
cost[idx] = ...
```

- The cost by age could also be accomplished with list comprehensions (e.g. for the cost of age 0-25):

```
cost_under_25 = [c[1] for c in cost_by_age if c[0] < 25]
average_cost_under_25 = sum(cost_under_25) / len(cost_under_25)
```

Of course, using numpy and pandas would shorten the code even futrher

Have a nice day!

Beta

Thank you so much for your comments. I’m sure that I will use these shorter ways in the future!