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View Code? Open in Web Editor NEWIntroduction to Data Science: A Python Approach to Concepts, Techniques and Applications
Home Page: http://www.springer.com/gp/book/9783319500164
Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications
Home Page: http://www.springer.com/gp/book/9783319500164
In the first table in Chapter 2, Section: Manipulating data there is a claim that pandas std() is an unbiased standard deviation. That is not correct, std() is a sample standard deviation which is known to be biased.
It appears that recent updates to Pandas, as well as other libraries have caused some of the notebooks to break.
In section 3.3.3 about Outliers Treatment it suggests that we can clean up values that exceed the median by 2 or 3 deviation standard:
df2 = df.drop( df.index[(df.income =='>50K\n') &
(df['age'] > df[’age’].median() + 35) &
(df['age'] > df[’age’].median() -15)
])
This boolean indexed is erroneous because it only cleans values that are more than 35 above the median. A correction might be changing operators >
by <
, and &
by |
:
df2 = df.drop( df.index[(df.income=='>50K\n') &
((df['age'] > df['age].median() + 35) | (df['age'] < df['age].median() - 15))])
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