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Introduction to Python
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• ## .mfe-app-workspace-kj242g{position:absolute;top:-8px;}.mfe-app-workspace-11ezf91{display:inline-block;}.mfe-app-workspace-11ezf91:hover .Anchor__copyLink{visibility:visible;}Introduction to Python

Run the hidden code cell below to import the data used in this course.

### Take Notes

Add notes about the concepts you've learned and code cells with code you want to keep.

```.mfe-app-workspace-11z5vno{font-family:JetBrainsMonoNL,Menlo,Monaco,'Courier New',monospace;font-size:13px;line-height:20px;}```# area variables (in square meters)
hall = 11.25
kit = 18.0
liv = 20.0
bed = 10.75
bath = 9.50

# Create list areas
areas = [hall, kit, liv, bed, bath]

# Print areas
print(areas)
``````
``````# area variables (in square meters)
hall = 11.25
kit = 18.0
liv = 20.0
bed = 10.75
bath = 9.50

areas = [hall, kit, "living room", liv, bed, "bathroom", bath]

# Print areas
print(areas)``````
``````x = ["a", "b", "c", "d"]
x[:2]
x[2:]
x[:]``````

``# Add your code snippets here``

### Explore Datasets

Use the arrays imported in the first cell to explore the data and practice your skills!

• Print out the weight of the first ten baseball players.
• What is the median weight of all baseball players in the data?
• Print out the names of all players with a height greater than 80 (heights are in inches).
• Who is taller on average? Baseball players or soccer players? Keep in mind that baseball heights are stored in inches!
• The values in `soccer_shooting` are decimals. Convert them to whole numbers (e.g., 0.98 becomes 98).
• Do taller players get higher ratings? Calculate the correlation between `soccer_ratings` and `soccer_heights` to find out!
• What is the average rating for attacking players (`'A'`)?