Chevron Left
Back to Analyze Box Office Data with Plotly and Python

Learner Reviews & Feedback for Analyze Box Office Data with Plotly and Python by Coursera Project Network

4.5
stars
236 ratings

About the Course

Welcome to this project-based course on Analyzing Box Office Data with Plotly and Python. In this course, you will be working with the The Movie Database (TMDB) Box Office Prediction data set. The motion picture industry is raking in more revenue than ever with its expansive growth the world over. Can we build models to accurately predict movie revenue? Could the results from these models be used to further increase revenue? We try to answer these questions by way of exploratory data analysis (EDA) and feature engineering. We will primarily use Plotly for data visualization. Plotly Python which is Plotly's Python graphing library makes interactive, publication-quality graphs ready for both online and offline use. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Top reviews

SD

Apr 29, 2020

I have learnt the skill of Python Panda Programming and application of Plotty using for statistical data

graphical representation

YS

May 3, 2020

The guided project was very nicely explained and gave me a hands on experience with Feature Engineering and Data Visualization.

Filter by:

1 - 25 of 35 Reviews for Analyze Box Office Data with Plotly and Python

By Pearl S

•

Jun 19, 2020

This is marked as a Beginner project, but there is a prerequisite that is not mentioned anywhere. The prerequisite project is marked as an Intermediate level project, so it doesn't quite make sense. It needs to be clear that the other project is a prerequisite for this one. I took this to get an introduction to Plotly and Python - alot of time was spent on how to clean and group data through Python, which I guess was helpful, but more description around the correct syntax for functions would have been helpful.

By afif r a

•

Aug 2, 2020

its amazing for beginner

By manya g

•

May 27, 2020

it was not much hands on

By marvin m

•

Oct 28, 2020

There are alot of bugs in the code. I spent more hours debugging the codes (which I still have not found the errors). While I appreciate the skilling up on debugging - it just ate up too much time and killed the momentum.

By Yashodhan M

•

Jul 21, 2020

After gathering the fundamental knowledge in python, the next thing I wanted to do was study about data visualization. I was totally taking this course to check whether I am liking this particular domain. Trust me after completing both the projects i.e. Seaborn and Plotly I can at least tell myself that I love data visualization. Yes, the syntax is confusing for first timers but you won't enjoy courses where they teach you theory so I purposely took these two courses. Thanks a lot for sharing your knowledge

By SHOMNATH D

•

Apr 30, 2020

I have learnt the skill of Python Panda Programming and application of Plotty using for statistical data

graphical representation

By Yash S

•

May 4, 2020

The guided project was very nicely explained and gave me a hands on experience with Feature Engineering and Data Visualization.

By Charudatt M

•

Sep 16, 2020

Good to have hands-on experience

By Sheildon G

•

Jun 1, 2020

very interesting and refreshing

By Aymal K K

•

Apr 27, 2020

Good EDA Concepts are discussed

By Shriniwas S U

•

May 2, 2020

Satisfied with task

By Rahul m

•

Apr 23, 2020

Very interesting

By SAMRATH P S

•

May 28, 2020

fantastic!!

By Partheepan

•

Apr 20, 2020

Very Useful

By Vaibhavi b K

•

Sep 13, 2020

intersting

By Doss D

•

Jun 30, 2020

Thank you

By Abhishek P G

•

Jun 12, 2020

satisfied

By Veeramanickam M

•

Apr 23, 2020

Thank you

By Deepa P

•

Sep 30, 2020

Good

By Kavitha A S

•

Jul 14, 2020

good

By Vajinepalli s s

•

Jun 18, 2020

nice

By tale p

•

Jun 17, 2020

good

By MICHAEL S

•

May 13, 2023

The content and instructor were good. My complaints are as follows:

1) The course files, which were nicely zipped up for you, were a hot mess of redundant files that were combined between Part 1 (another course) and Part 2 (this course). All that was needed was the final Part1+2 combined notebook and the 2 CSV files.

2) I was not able to easily replicate this on my own personal computer. There is one problem after another stemming from the many pre-requisite imports and statements listed at the top of the notebook. Fortunately, the notebook in the zipfile shows the graph output for each command without having to re-run the notebook.

3) The instructor did not elaborate enough on the topics that were asked on the quiz. There is even 1 question on "modes" which is an argument not even used in the course notebook.

By Anantharaman K

•

Jul 12, 2020

The course gives us a look into feature engineering. The code explanation was OK. But it actually puts emphasis on the learners to be familiar with pandas and matplotlib libraries basics. So might be a little scarier for absolute beginners.

By Kumar G

•

Jun 21, 2020

i raise a query during class time but not get resolved maybe it happen due to some technical issue.please fix this.thanks for the guided projects.