Inspiration
we were inspired to build a vizualization tool that goes beyond what the eyes can see
What it does
Given a large dataset of messages received from exchanges, we have cleaned this dataset and have created graphs in order to see the evolution of the prices of every OrderID, as well as some pre-defined 'error_code' which corresponds to a different anomaly that can happen.
How we built it
First, on R we cleaned the dataset to create separate csv files with the categories that were important to our data analysis. With these csv files, we then created graphs from these csv files, one with the prices and then the error codes showing on the bottom.
Challenges we ran into
We ran into challenges when cleaning up the data file and creating new columns with error_codes depending on the time of the messages of each OrderID. Another challenge we ran into was to create the graphs which dynamically updated over time.
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