Python Bytes

The live stream recording on YouTube. Special guest: Jay Miller Sponsored by us! Support our work through: Our courses at Talk Python Training Test & Code Podcast Patreon Supporters Brian #1: Analyzing Kickstarter Campaigns with Python Data Science Tools Article title: “Kickstarter Projects — Do They Succeed?” Aditya Patkar Using a Kaggle dataset of 378,661-ish projects up to 2018. Looks at using pandas data frames to explore the data. Using .describe() data frame method to learn a lot. Uses matplotlib and seaborn to analyze the data further. Odd statement that I’m not sure is straight faced or a really dry joke: “The data from 1970 seems to be bad or insignificant data.” Examples of using heat maps, line graphs, bar charts, to look at different aspects. Some results: 35.64% of projects are successful (meaning goal hit) tech asks for the most for goals, and has the highest average per backer. Comics has the lowest pledged amount per backer average. Nice that you can use the techniques to ask yo