drop_duplicates DataFrame
Finding unduplicated lists is task number 1 on day 2, so enjoy this quick review on deduplicating a list based on a few paramaters. This narration discusses uses for drop_duplicates. Usually, drop_duplicates is not used in isolation. There are usually steps before the process. The movies DataFrame has a list of movies with director_name and gross. I first want all movies with a gross above 1 MM, and of those movies, the top-grossing moving by the director. This is how I would approach the task with pandas and chaining. First, Import the packages and data: Google Colab space with all the executable code import pandas as pd import numpy as np loc = r'C:\....movie.csv' m = pd.read_csv(loc) pd.set_option('display.max_columns',None) pd.options.display.min_rows = 10 Second, apply the desired steps. At 1, filter out the unnecessary data. At 2, sort the values by the director's name and gross amount for the movie. At 3, drop the duplicates by the dire...