January 2020
Beginner to intermediate
432 pages
11h 24m
English
Content preview from Python for Finance Cookbook
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How it works...
In Step 1, we loaded the required libraries. Then, we loaded the CSV data, downloaded from Kaggle (available at https://www.kaggle.com/mlg-ulb/creditcardfraud) into Python, using the pd.read_csv function.
The dataset we selected for this exercise contains information about transactions made by credit cards in September 2013 by European cardholders. The transactions happened within a period of 2 days. All the numerical variables with a name starting with V are the principal components, obtained by running the PCA on the original dataset (original features are not included, due to confidentiality). The only two features with clear interpretation are Time (seconds elapsed between each transaction and the first transaction in ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.