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pandas (functions (loc, iloc, read_csv, iterrows), pandas (functions (loc,…

- - - - cars['cars_per_cap']
      - Print out drives_right column as Series
        print(cars.loc[:,'drives_right'])
    - - cars[['cars_per_cap']]
      - cars[3:6]
      - cars.loc['RU']
        cars.iloc[4]
      - cars.loc[['RU', 'AUS']]
        cars.iloc[[4, 1]]
      - cars.loc[['RU','MOR'],['country','drives_right']]
      - Print out drives_right column as DataFrame
        print(cars.loc[:,['drives_right']])
        Print out cars_per_cap and drives_right as DataFrame
        print(cars.loc[:,['cars_per_cap','drives_right']])
      - sel = cars[:][dr==True]
        here all records in cars are retrieved
        where dr column is true
        OR
        sel = cars[cars['drives_right'] == True]
      - cpc = cars['cars_per_cap']
        between = np.logical_and(cpc>100,cpc<500)
        medium = cars[between]