logistic_looking_st_the__data.py

# summarize the data
print df.describe()
#             admit         gre         gpa   prestige
# count  400.000000  400.000000  400.000000  400.00000
# mean     0.317500  587.700000    3.389900    2.48500
# std      0.466087  115.516536    0.380567    0.94446
# min      0.000000  220.000000    2.260000    1.00000
# 25%      0.000000  520.000000    3.130000    2.00000
# 50%      0.000000  580.000000    3.395000    2.00000
# 75%      1.000000  660.000000    3.670000    3.00000
# max      1.000000  800.000000    4.000000    4.00000

# take a look at the standard deviation of each column
print df.std()
# admit      0.466087
# gre      115.516536
# gpa        0.380567
# prestige   0.944460

# frequency table cutting presitge and whether or not someone was admitted
print pd.crosstab(df['admit'], df['prestige'], rownames=['admit'])
# prestige   1   2   3   4
# admit                   
# 0         28  97  93  55
# 1         33  54  28  12

# plot all of the columns
df.hist()
pl.show()