How to work with missing data

Data is missing in pandas when it has a value of NaN (also seen as np.nan - the form from NumPy). This NaN value means that there is no value specified for the particular index label in a particular Series.

How can data be missing? There are a number of reasons why a value can be NaN:

• A join of two sets of data does not have matched values
• Data that you retrieved from an external source is incomplete
• The NaN value is not known at a given point in time and will be filled in later
• There is a data collection error retrieving a value, but the event must still be recorded in the index
• Reindexing of data has resulted in an index that does not have a value
• The shape of data has changed and there are now additional rows or columns, which at the time of reshaping could not be determined
• There are likely more reasons, but the general point is that these situations do occur and you, as a user of pandas, will need to address these situations to be able to perform effective data...