Hey, I am seeking assistance from the community to discover different approaches for counting the missing values in a given dataset. Handling missing values is crucial in data analysis and can lead to issues in machine learning models if not addressed appropriately. One of the ways to handle missing values is by determining the number of missing values in the dataset. In Python, there are various techniques to count missing values, such as using the isnull() method to locate the missing values and then using the sum() method to calculate the total number of missing values in each column. However, I am open for other suggestions from the community.
'A': [1, 2, None, 4], 'B': [None, 6, 7, None], 'C': [None, None, None, None]