Learning pandas

Arithmetic on a DataFrame

Arithmetic operations using scalar values will be applied to every element of a DataFrame. To demonstrate, we will use a DataFrame object initialized with random values:

In [94]:
   # set the seed to allow replicatable results
   np.random.seed(123456)
   # create the DataFrame
   df = pd.DataFrame(np.random.randn(5, 4), 
                     columns=['A', 'B', 'C', 'D'])
   df

Out[94]:
             A         B         C         D
   0  0.469112 -0.282863 -1.509059 -1.135632
   1  1.212112 -0.173215  0.119209 -1.044236
   2 -0.861849 -2.104569 -0.494929  1.071804
   3  0.721555 -0.706771 -1.039575  0.271860
   4 -0.424972  0.567020  0.276232 -1.087401

By default, any arithmetic operation will be applied across all rows and columns of a DataFrame and will return a new DataFrame with the results (leaving ...