Reindexing the Series and DataFrame objects

Reindexing in pandas is a process that makes the data present in a Series or DataFrame match with a given set of labels along a particular axis. This is core to the functionalities of pandas as it enables label alignment across multiple objects.

The process of performing a reindex does the following:

• Reorders existing data to match a set of labels
• Inserts NaN markers where no data exists for a label
• Fills missing data for a label using a type of logic (defaulting to adding NaNs)

The following is a simple example of reindexing a Series. The following Series has an index with numerical values, and the index is modified to be alphabetic by simply assigning a list of characters to the .index property, making the values able to be accessed via the character labels in the new index:

In [60]:
   np.random.seed(1)
   s = pd.Series(np.random.randn(5))
   s

Out[60]:
   0    1.624345
   1   -0.611756
   2   -0.528172
   3   -1.072969
   4    0.865408
   dtype...