TallerPreParcial. Ejercicio 3. ConteoCombinacionesDados

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Awesome! Everything worked as it should have: your code passed all the test cases. Congratulations!

Sorry, but your code failed to solve the problem. It does not solve correctly the problem you were asked for.
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Test your code with different inputs. You can do it in your machine or you can use the "custom input" in the tools section.

PRESENTATION ERROR

The data in your output is correct, but it is not formatted in the proper way. Check the problem statement to understand the correct format of the output.
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COMPILATION ERROR

Your code does not compile :/. Something is faulty in your code:
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Tips: Check for infinite loops. Try to find another solution, one that takes less time to compute.

MEMORY LIMIT EXCEEDED

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Tips: Check the data structures you are using, or find a more "optimal" solution, a solution that uses less memory.

OUTPUT LIMIT EXCEEDED

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Tips: Check for print expressions in a loop.

GRADING RUNTIME ERROR

Error related to notebook file submissions. This points out a runtime error while running the grading testing code.
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This might be also caused by a too small time limit in the task configuration (talk to your professor about it).

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El ejercicio debe ser resuelto adjuntando un archivo .ipynb sólo con la función que resuelva el problema. Tenga en cuenta que no puede usar funciones pre-establecidas de python

Enunciado del problema

Contar combinaciones de dados Un jugador debe lanzar dos dados numerados de 1 a 6, y su puntaje es la suma de los valores obtenidos. Un puntaje dado puede ser obtenido con varias combinaciones posibles. Por ejemplo, el puntaje 4 se logra con las siguientes tres combinaciones: 1+3, 2+2 y 3+1. Escriba una función llamada "Dados" que reciba un puntaje, y muestre como resultado de la cantidad de combinaciones de dados con las que se puede obtener ese puntaje.

Ejemplos

Entrada Ejemplo 1

Salida Ejemplo 1

Entrada Ejemplo 2

Salida Ejemplo 2

Entrada Ejemplo 3

Salida Ejemplo 3

Paste this command into your terminal:

The password to connect is

In general, when submitting a notebook, all Python 3.6 code is supported on UNCode. However, Ipython notebooks and python code differ in some functionalities, then UNCode might support them or not. Also, there are some things you should bear in mind when creating your notebook.

Python modules:
You are able to use the next python modules in addition to the pre installed python modules:
import pandas, numpy, matplotlib, scipy, scikit-learn, seaborn, datascience, plotly, cufflinks, bokeh, tabulate, nltk, tensorflow, Keras

Installing modules:
All the modules and data you require are already installed and supported by UNCode.
Then, when you have lines installing a module, for instance: !pip install pandas or using conda, these lines are automatically removed from your notebook to avoid runtime execution errors.

In case you want to use one module and it is not in the previous list, do not hesitate on reaching out for support.
Print expressions:
Usually while executing your notebook on your runtime you might add some print expressions, though, these expressions are deleted and these outputs are not shown in the submission feedback.
Internet access in grading environment:
The internet access when your code is being graded is dependant on the task. Some tasks might allow it or not.
In case you are allowed to access internet, this mainly will work to download files or data, for instance datasets. As stated above, you cannot install modules.
In case there is not access, be careful when using code that requires internet access as it will fail while grading.
Magic functionality execution:
Magic functions are not allowed when your notebook is graded. For example the next line:
%matplotlib inline
In case your notebook contains some lines like this, they will be automatically removed to avoid runtime execution errors.
Commands execution:
Python Notebooks provide a functionality to execute commands like these:
!ls
!pwd
However, this kind of lines are transformed as follows:
!ls is turned into the following code:
import subprocess
call = subprocess.run(["ls"], stdout=subprocess.PIPE)
print(call.stdout.decode('utf-8')
That code will do the same for you as in the notebook. However, you are not allowed to assign the result of command execution to variables, for instance the next line will return an error:
result = !ls.
Google Colab modules
When you use Google Colaboratory (Colab) and you want to load and read data from Google Drive, you are required to use some python modules unique in Colab. These modules are not supported by UNCode. Then, make sure when you submit your notebook, you do not include it.

Max file size: 1.0MB
Extensions autorisées: .ipynb

Date limite	30/11/2021 23:59:24
Limite de soumission	No limitation