Working with Missing Data & GroupBy in Pandas.
Missing values indicate we do not have the information about a feature (column) of a particular observation (row). Why not just remove that observation from the dataset and go ahead? We can but should not. The reasons are:
We typically have many features of an observation so we don’t want to lose the observation just because of one missing feature. Data is valuable.
We typically have more than one observation with missing values. In some cases, we cannot afford to remove many observations from the dataset. Again, data is valuable.
Pandas groupby is used for grouping the data according to the categories and apply a function to the categories. ... Pandas dataframe. groupby() function is used to split the data into groups based on some criteria. pandas objects can be split on any of their axes.
Pandas DataFrame Operations: • Python Pandas DataFrame Operations