Advanced Python Programming

Mapping

Pandas supports element-wise operations just like NumPy (after all, pd.Series stores their data using np.array). For example, it is possible to apply transformation very easily on both pd.Series and pd.DataFrame:

    np.log(df.sys_initial) # Logarithm of a series    df.sys_initial ** 2    # Square a series    np.log(df)             # Logarithm of a dataframe    df ** 2                # Square of a dataframe

You can also perform element-wise operations between two pd.Series in a way similar to NumPy. An important difference is that the operands will be matched by key, rather than by position; if there is a mismatch in the index, the resulting value will be set to NaN. Both the scenarios are exemplified in the following example:

    # Matching index a = pd.Series([1, 2, 3], index=["a", ...