The basic mathematical operators work on DataFrames. For example, a new column can be obtained as a result of adding, multiplying, subtracting, or dividing two columns:

In [67]: ore1DF["add_iron_copper"] = ore1DF["iron"] + ore1DF["copper"]

The following is the output:

Logical operators such as  | (or), & (and), and ^ (not) work on DataFrames. Consider the following two DataFrames:

logical_df1 = pd.DataFrame({'Col1' : [1, 0, 1], 'Col2' : [0, 1, 1] }, dtype=bool)
logical_df2 = pd.DataFrame({'Col1' : [1, 0, 0], 'Col2' : [0, 0, 1] }, dtype=bool)

Now, performing the logical or between these two columns yields the following result:

logical_df1 | logical_df2

The following is the output:

Operations can also be performed on DataFrames using the NumPy functions:

np.sqrt(ore1DF)

The following is the output: