January 2019
Intermediate to advanced
378 pages
8h 27m
English
Let's now take a look at the performance of the IPO market. We are going to pull down data from IPOScoop.com, which is a service that provides ratings for upcoming IPOs. Go to https://www.iposcoop.com/scoop-track-record-from-2000-to-present/ and click on the button at the bottom of the page to download the spreadsheet. We'll load this into pandas and run a number of visualizations using our Jupyter notebook.
Unfortunately, the data is in a format that makes it impossible to just read into pandas with the normal .read_csv() method. What we'll need to do is use a library that lets us read Excel files into Python lists and then perform some preprocessing to filter out those rows that aren't of interest, primarily, ...
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