freeCodeCamp/curriculum/challenges/english/11-machine-learning-with-python/machine-learning-with-python-projects/rock-paper-scissors.md

---
id: 5e46f8d6ac417301a38fb92d
title: Rock Paper Scissors
challengeType: 10
forumTopicId: 462376
dashedName: rock-paper-scissors
---

# --description--

You will be [working on this project with our Replit starter code](https://replit.com/github/freeCodeCamp/boilerplate-rock-paper-scissors).

We are still developing the interactive instructional part of the machine learning curriculum. For now, you will have to use other resources to learn how to pass this challenge.

# --instructions--

Create a function named `calculate()` in `mean_var_std.py` that uses Numpy to output the mean, variance, standard deviation, max, min, and sum of the rows, columns, and elements in a 3 x 3 matrix. 

The input of the function should be a list containing 9 digits. The function should convert the list into a 3 x 3 Numpy array, and then return a dictionary containing the mean, variance, standard deviation, max, min, and sum along both axes and for the flattened matrix. 

The returned dictionary should follow this format:

```py
{
  'mean': [axis1, axis2, flattened],
  'variance': [axis1, axis2, flattened],
  'standard deviation': [axis1, axis2, flattened],
  'max': [axis1, axis2, flattened],
  'min': [axis1, axis2, flattened],
  'sum': [axis1, axis2, flattened]
}
```

If a list containing less than 9 elements is passed into the function, it should raise a `ValueError` exception with the message: "List must contain nine numbers." The values in the returned dictionary should be lists and not Numpy arrays.

For example, `calculate([0,1,2,3,4,5,6,7,8])` should return:

```py
{
  'mean': [[3.0, 4.0, 5.0], [1.0, 4.0, 7.0], 4.0], 
  'variance': [[6.0, 6.0, 6.0], [0.6666666666666666, 0.6666666666666666, 0.6666666666666666], 6.666666666666667], 
  'standard deviation': [[2.449489742783178, 2.449489742783178, 2.449489742783178], [0.816496580927726, 0.816496580927726, 0.816496580927726], 2.581988897471611],
  'max': [[6, 7, 8], [2, 5, 8], 8],
  'min': [[0, 1, 2], [0, 3, 6], 0],
  'sum': [[9, 12, 15], [3, 12, 21], 36]
}
```

The unit tests for this project are in `test_module.py`.

## Development

For development, you can use `main.py` to test your `calculate()` function. Click the "run" button and `main.py` will run.

## Testing 

We imported the tests from `test_module.py` to `main.py` for your convenience. The tests will run automatically whenever you hit the "run" button.

## Submitting

Copy your project's URL and submit it below.

# --hints--

It should pass all Python tests.

```js

```

# --solutions--

```py
  # Python challenges don't need solutions,
  # because they would need to be tested against a full working project.
  # Please check our contributing guidelines to learn more.
```