dbproductionsLTD
commented
6 years ago Thank you so much for the extremely thoughtful and actionable feedback. It's very helpful for my continued learning.
Hope you have a wonderful weekend.
Best, Dave
On Sat, May 12, 2018 at 9:55 AM, Caealana notifications@github.com wrote:
I had a lot of fun going over your project. I was very impressed with the amount of detail and work you put into this project! You made many extra modifications, tables, and visualizations to thoroughly explore the data. I thought you showed great attention to detail in making sure your tables and visualizations could be easily interpreted.
I won't have too much to say about your code, as all of your code was written cleanly and efficiently. All of your python code worked correctly towards accomplishing the various data science tasks. You followed many of the best conventions concerning indentation and variable naming conventions. This helped in making your python code easily readable. Here https://www.python.org/dev/peps/pep-0008/ is more information on python styling conventions if you are interested.
I would suggest you practice adding in more of your own comments and a README to this github repository to give some context to your code. Comments answer questions like 'What were you thinking when you writing this code?' and 'What is the purpose of this chunk of code? Are there currently any issues with it?" Here https://guides.github.com/features/wikis/ is a helpful guide for creating READMEs that give a good introduction to your project.
On your presentation: I would suggest you introduce your project before you jump into your data and calculations. You should answer questions like, "What problem are you trying to solve?", "Why is this problem important?", "What information do you need to know about the problem?". This will help your audience feel more involved and engaged with your work.
Your presentation had great flow and story building. It was very easy to follow your thought process. I would just suggest spreading out some of your information onto more slides. Your slides were quite overcrowded with text and images. Limiting each slide to one image and topic helps to focus your audience.
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I had a lot of fun going over your project. I was very impressed with the amount of detail and work you put into this project! You made many extra modifications, tables, and visualizations to thoroughly explore the data. I thought you showed great attention to detail in making sure your tables and visualizations could be easily interpreted.
I won't have too much to say about your code, as all of your code was written cleanly and efficiently. All of your python code worked correctly towards accomplishing the various data science tasks. You followed many of the best conventions concerning indentation and variable naming conventions. This helped in making your python code easily readable. Here is more information on python styling conventions if you are interested.
I would suggest you practice adding in more of your own comments and a README to this github repository to give some context to your code. Comments answer questions like 'What were you thinking when you writing this code?' and 'What is the purpose of this chunk of code? Are there currently any issues with it?" Here is a helpful guide for creating READMEs that give a good introduction to your project.
On your presentation: I would suggest you introduce your project before you jump into your data and calculations. You should answer questions like, "What problem are you trying to solve?", "Why is this problem important?", "What information do you need to know about the problem?". This will help your audience feel more involved and engaged with your work.
Your presentation had great flow and story building. It was very easy to follow your thought process. I would just suggest spreading out some of your information onto more slides. Your slides were quite overcrowded with text and images. Limiting each slide to one image and topic helps to focus your audience.