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Introduction to Python

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

# Importing course packages; you can add more too!
import numpy as np
import math

# Import columns as numpy arrays
baseball_names = np.genfromtxt(
    fname="baseball.csv",  # This is the filename
    delimiter=",",  # The file is comma-separated
    usecols=0,  # Use the first column
    skip_header=1,  # Skip the first line
    dtype=str,  # This column contains strings
)
baseball_heights = np.genfromtxt(
    fname="baseball.csv", delimiter=",", usecols=3, skip_header=1
)
baseball_weights = np.genfromtxt(
    fname="baseball.csv", delimiter=",", usecols=4, skip_header=1
)
baseball_ages = np.genfromtxt(
    fname="baseball.csv", delimiter=",", usecols=5, skip_header=1
)

soccer_names = np.genfromtxt(
    fname="soccer.csv",
    delimiter=",",
    usecols=1,
    skip_header=1,
    dtype=str,
    encoding="utf", 
)
soccer_ratings = np.genfromtxt(
    fname="soccer.csv",
    delimiter=",",
    usecols=2,
    skip_header=1,
    encoding="utf", 
)
soccer_positions = np.genfromtxt(
    fname="soccer.csv",
    delimiter=",",
    usecols=3,
    skip_header=1,
    encoding="utf", 
    dtype=str,
)
soccer_heights = np.genfromtxt(
    fname="soccer.csv",
    delimiter=",",
    usecols=4,
    skip_header=1,
    encoding="utf", 
)
soccer_shooting = np.genfromtxt(
    fname="soccer.csv",
    delimiter=",",
    usecols=8,
    skip_header=1,
    encoding="utf", 
)
Hidden output

Take Notes

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

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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')?
# Print out the weight of the first ten baseball players.
print(baseball_names[0:10])
# What is the median weight of all baseball players in the data?
print('The median weigth of all baseball players in data is: ' + str(np.median(baseball_heights)))
# Print out the names of all players with a height greater than 80 (heights are in inches)

print(baseball_names[baseball_heights >= 80 ], soccer_names[soccer_heights >= 80 ])
# Who is taller on average? Baseball players or soccer players? Keep in mind that baseball heights are stored in inches!
print('The avarege of Baseball heights is:'+ str(np.mean(baseball_heights)))
print('The avarege of Soccer heights is:'+ str(np.mean(soccer_heights/2.5)))
print('The taller average is Baseball playes that is :' + str(np.mean(baseball_heights)))
# The values in soccer_shooting are decimals. Convert them to whole numbers (e.g., 0.98 becomes 98).
print (str(soccer_shooting*100))
# Do taller players get higher ratings? Calculate the correlation between soccer_ratings and soccer_heights to find out!

taller_soccer_ratings = soccer_ratings[soccer_heights <= 181.75042387249914]
shorter_soccer_ratings = soccer_ratings[soccer_heights >= 181.75042387249914] 


# Resize the arrays to the same size
taller_soccer_ratings = taller_soccer_ratings[:len(shorter_soccer_ratings)]
shorter_soccer_ratings = shorter_soccer_ratings[:len(taller_soccer_ratings)]

#print( taller_soccer_ratings )
#print( shorter_soccer_ratings )
print('The Average of taller players ratings is : ' + str(np.mean(taller_soccer_ratings)))
print('The Average of Shorter players ratings is : ' + str(np.mean(shorter_soccer_ratings)))
print('The taller players dont get the higher rating')

print( np.corrcoef (taller_soccer_ratings, shorter_soccer_ratings) )
# What is the average rating for attacking players ('A')?
print ('The average rating for attacking players is : '+ str ( np.mean (soccer_ratings[soccer_positions == 'A'])))