Exploratory Data Analysis

21 Ways to Visualize a Timeseries

21 Ways to Visualize a Timeseries

We explore a variety of distinct ways to visualize the same simple dataset

Reading Time: 26 min.
What this blog post is about (and what it isn’t): With the ever more widespread adoption of Data Science, defined as the intensive use of data in various forms of decision making, there is a renewed interest in Visualization as an effective channel for humans to understand data at various stages of the data lifecycle. There is a large variety of data visualization tools which can produce an ever more bewildering variety of visualization types
Data Quality and Exploratory Data Analysis using Python

Data Quality and Exploratory Data Analysis using Python

Reading Time: 0 min.
Data Quality and Exploratory Data Analysis using Python: In two new Open Risk Academy courses we figure step by step how to use python to work to review risk data from a data quality perspective and how to perform exploratory data analysis with pandas, seaborn and statsmodels: Introduction to Risk Data Review Exploratory Data Analysis using Pandas, Seaborn and Statsmodels
RegDB Explorer

RegDB Explorer

Reading Time: 1 min.
The RegDB Explorer is a web app that helps you get the big picture when it comes to regulatory documentation. In a simple visual setting you can see the time sequence of publications, the topic and number of pages and select/click-through to any document published by the Basel Committee on Banking Supervision.(The app data are derived from the published BIS repositories with minimal adjustments) You can find the RegDB explorer here.