内容简介:Exploring movies on Netflix, Hulu, Prime Video, and Disney+.We live in the era of big data. We can collect lots of data which allows to infer meaningful results and make informed business decisions. To get the most out of data, a robust and thorough data a
Exploring movies on Netflix, Hulu, Prime Video, and Disney+.
We live in the era of big data. We can collect lots of data which allows to infer meaningful results and make informed business decisions. To get the most out of data, a robust and thorough data analysis process is needed. In this post, we will try to explore a dataset about the movies on streaming platforms. The data is available here on Kaggle.
We can directly download Kaggle datasets into a Google Colab environment. Here is a step-by-step explanation on how to do it:
Let’s start with downloading the dataset and read it into a pandas dataframe.
import pandas as pd import numpy as np!kaggle datasets download -d ruchi798/movies-on-netflix-prime-video-hulu-and-disneydf = pd.read_csv("/content/movies-on-netflix-prime-video-hulu-and-disney.zip")df.drop(["Unnamed: 0", "ID", "Type"], axis=1, inplace=True)df.head()
“Unnamed: 0” and “ID” columns are redundant as they do not provide any information about the movies so we drop them. “Type” column indicates whether the title is a movie or TV show. We drop them because all of the rows contain data on movies.
以上所述就是小编给大家介绍的《A Practical Guide for Exploratory Data Analysis: Movies on Streaming Platforms》,希望对大家有所帮助,如果大家有任何疑问请给我留言,小编会及时回复大家的。在此也非常感谢大家对 码农网 的支持!
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