How to do it...

  1. Read in the college dataset with the institution name as the index, and select a single column as a Series with the indexing operator:
>>> college = pd.read_csv('data/college.csv', index_col='INSTNM')
>>> city = college['CITY']
>>> city.head()
INSTNM Alabama A & M University Normal University of Alabama at Birmingham Birmingham Amridge University Montgomery University of Alabama in Huntsville Huntsville Alabama State University Montgomery Name: CITY, dtype: object
  1. The .iloc indexer makes selections only by integer location. Passing an integer to it returns a scalar value:
>>> city.iloc[3]
Huntsville
  1. To select several different integer locations, pass a list to .iloc. This returns a Series:
>>> city.iloc[[10,20,30]]
INSTNM Birmingham Southern College Birmingham George C Wallace State Community College-Hanceville Hanceville Judson College Marion Name: CITY, dtype: object
  1. To select an equally spaced partition of data, use slice notation:
>>> city.iloc[4:50:10]
INSTNM Alabama State University Montgomery Enterprise State Community College Enterprise Heritage Christian University Florence Marion Military Institute Marion Reid State Technical College Evergreen Name: CITY, dtype: object
  1. Now we turn to the .loc indexer, which selects only with index labels. Passing a single string returns a scalar value:
>>> city.loc['Heritage Christian University']
Florence
  1. To select several disjoint labels, use a list:
>>> np.random.seed(1)
>>> labels = list(np.random.choice(city.index, 4))
>>> labels
['Northwest HVAC/R Training Center', 'California State University-Dominguez Hills', 'Lower Columbia College', 'Southwest Acupuncture College-Boulder']

>>> city.loc[labels]
INSTNM
Northwest HVAC/R Training Center Spokane California State University-Dominguez Hills Carson Lower Columbia College Longview Southwest Acupuncture College-Boulder Boulder Name: CITY, dtype: object
  1. To select an equally spaced partition of data, use slice notation. Make sure that the start and stop values are strings. You can use an integer to specify the step size of the slice:
>>> city.loc['Alabama State University':
'Reid State Technical College':10]
INSTNM
Alabama State University Montgomery Enterprise State Community College Enterprise Heritage Christian University Florence Marion Military Institute Marion Reid State Technical College Evergreen Name: CITY, dtype: object
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