pandas is one of the most commonly used Python library in data analysis and machine learning. It is versatile and can be used to handle many different types of data. Before feeding a model with training data, one would most probably pre-process the data and perform feature extraction on data stored as pandas DataFrame. I have been using pandas extensively in my work, and have recently discovered that the time required to manipulate data stored in a DataFrame can vary hugely depending on the method you used.