subset observations (Rows) and subset variables (columns)

Question 1

Extract rows that meet logical criteria.

Answer 1

df[df.Length > 7]

Question 2

Remove duplicate rows (only considers columns).

Answer 2

df.drop_duplicates()

Question 3

Select first n rows.

Answer 3

df.head(n)

Question 4

Select last n rows.

Answer 4

df.tail(n)

Question 5

Randomly select fraction of rows.

Answer 5

df.sample(frac=0.5)

Question 6

Randomly select n rows.

Answer 6

df.sample(n=10)

Question 7

Select rows by position.

Answer 7

df.iloc[10:20]

Question 8

Get the rows of a DataFrame sorted by the n largest values of columns.

Answer 8

DataFrame.nlargest(n, columns, keep=’first’)

Question 9

Get the rows of a DataFrame sorted by the n smallest values of columns.

Answer 9

DataFrame.nlargest(n, columns, keep=’first’)

Question 10

Select multiple columns with specific names.

Answer 10

df[[‘width’,’length’,’species’]]

Question 11

Select single column with specific name.

Answer 11

df[‘width’] or df.width

Question 12

Select columns whose name matches regular expression regex.

Answer 12

df.filter(regex=’regex’)

Question 13

Select all columns between x2 and x4 (inclusive).

Answer 13

df.loc[:,’x2’:’x4’]

Question 14

Select columns in positions 1, 2 and 5 (first column is 0).

Answer 14

df.iloc[:,[1,2,5]]

Question 15

Select rows meeting logical condition, and only the specific columns .

Answer 15

df.loc[df[‘a’] > 10, [‘a’,’c’]]