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...