Pandas df.notnull(): Identify Non-Null Values in DataFrames

The df.notnull() function in Pandas returns a boolean DataFrame with the same shape as the input DataFrame (df). Each element of the boolean DataFrame will be 'True' if the corresponding element of the input DataFrame is not null (i.e., not NaN), and 'False' otherwise.

This function is useful for:

• Identifying missing values: You can use it to locate null values within your data.
• Filtering DataFrames: You can use the output of df.notnull() to filter your DataFrame and keep only the rows or columns with non-null values.
• Data Cleaning: It can help you understand the extent of missing data and guide your data cleaning strategies.