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# Introduction to Python

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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;}```# Most list operations that should violate some rule just intelligently append, replace or insert the elements when subsetting
x = ["a", "b", "c", "d"]
x[1:1] = ["s", "t", "v"]
#x
#['a', 's', 't', 'v', 'b', 'c', 'd']
x[2:8] = ["s", "t", "v"] # index 8 doesn't exist, doesn't matter just appends what it can
#x
#['a', b', 's', 't', 'v']
x[5:8] = ["s", "t", "v"] # 5 doesn't exist, doesn't matter just appends
#x
#['a', b', 'c', 'd', s', 't', 'v']``````

### 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'`)?
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