Pandas supports many essential functionalities that are useful to manipulate Pandas data structures. In this book, we will focus on the most important features regarding exploration and analysis.
Reindex is a critical method in the Pandas data structures. It confirms whether the new or modified data satisfies a given set of labels along a particular axis of Pandas object.
First, let's view a reindex
example on a Series object:
>>> s2.reindex([0, 2, 'b', 3]) 0 0.6913 2 0.8627 b NaN 3 0.7286 dtype: float64
When reindexed
labels do not exist in the data object, a default value of NaN
will be automatically assigned to the position; this holds true for the DataFrame case as well:
>>> df1.reindex(index=[0, 2, 'b', 3], columns=['Density', 'Year', 'Median_Age','C']) Density Year Median_Age C 0 244 2000 24.2 NaN 2 268 2010 28.5 NaN b NaN NaN ...