1. Rock, paper, and scissors

In this mini-project, we will build a rock, paper, scissors game in the following steps:

  • Define a list ["rock", "paper", "scissors"], use choice() function from random module to randomly select an element from the list, name it computer_choice.

  • Now ask for user input. The input value should be in the list. Name the input your_choice.

  • Using if, elif, and else to determine who wins.

2. Using Jupyter Notebook

drawing

Jupyter is a loose acronym meaning Julia, Python, and R. The word “notebook” denotes documents that contain both code and rich text elements, such as figures, links, equations, etc. Because of the mix of code and text elements, these documents are the ideal place to bring together an analysis description, and its results, as well as, they can be executed perform the data analysis in real time.

Jupyter is a free, open-source, interactive web tool known as a computational notebook, which researchers can use to combine software code, computational output, explanatory text and multimedia resources in a single document. Jupyter is recommended by Nature as data scientists’ computational notebook of choice.

  • Jupyter is installed along with Anaconda. Open Anaconda Powershell Prompt (anaconda3), change working directory using cd.

  • Type and run jupyter notebook. This will open your default web browser, and Jupyter dashboard will show up.

  • Create a new note by clicking New then Python3 (ipykernel).

  • Go over User Interface Tour under the Help tab to familiarize yourself with the layout.

  • Copy the following lines to a cell, run the cell, see what happens. We will take a closer look at matplotlib in the future sections.

# import matplotlib
import matplotlib.pyplot as plt

# Get some data
temperatrue = [15.4, 16.3, 19.0, 22.7, 26.0, 28.0,
               28.9, 28.7, 27.7, 25.3, 21.2, 17.0]
month = range(1,13)

# Plot a line
plt.plot(month, temperatrue)

# Add x and y labels
plt.xlabel("Month")
plt.ylabel("Temperature")

# Add figure title
plt.title("Monthly mean temperature in Shenzhen (degree)")

# Show plot
plt.show

Here are some further readings for Jupyter Notebook: