Easily animate beautiful maps in R using leaflet and shiny.

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Photo by Timo Wielink on Unsplash

Every day, we as data scientists and data analysts have to work with different kinds of data. And we all know that visualization of the data and our findings is key, especially when presenting it to co-workers or clients. After all, it is far easier to tell a story with a chart than it is with plain numbers or text. When you’re presenting data via a dashboard, not only static visualization becomes important, you will also want to display changes in your data dynamically.

In this post, I will demonstrate how you can easily animate charts based on geospatial data using the leaflet and shiny libraries in R. …


Calculate and visualize implied volatility surfaces using freely available data and R to improve your risk assessment of options

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Photo by Ishant Mishra on Unsplash

Note from Towards Data Science’s editors: While we allow independent authors to publish articles in accordance with our rules and guidelines, we do not endorse each author’s contribution. You should not rely on an author’s works without seeking professional advice. See our Reader Terms for details.

Disclaimer

This article does not offer investment advice and nothing in it should be construed as investment advice. It provides information and education for individuals who can make their investment decisions without advice.

The information contained in this article is not, and should not be read as, an offer or recommendation to buy or sell or a solicitation of an offer or recommendation to buy or sell any securities. …


Making sense of correlation matrices in an intuitive, interactive way using plotly.

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Photo by Clint Adair on Unsplash

Everyone working with data knows that beautiful and explanatory visualization is key. After all, it's much easier to tell a story with a chart than it is with a plain table. This is especially important when you’re creating reports and dashboards whose aim it is to give your users and clients a quick overview over sometimes very complex and big datasets.

One type of data that is not trivial to visualize in an explanatory way is a correlation matrix. …


Simple improvements and customisation that make your charts stand out

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Photo by Luke Chesser on Unsplash

We’ve all been there at the end of a data science project: we’ve cleaned all the data, we’ve explored it, gained valuable insight and made the results accessible to the business via a webtool. We have even gone so far and made awesome interactive visualisations using plotly!

The only problem is, the out-of-the-box formatting of those charts are mediocre. Co-workers are impressed with analytical insight but you hear them say things like “I wish the charts were nicer so we can show it to clients!” or “why is the cursor looking so weird?” …


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Photo by Austin Distel on Unsplash

This article will walk you through how to obtain trade data for a given cryptocurrency (we will be using the Kraken exchange API) and resample it to obtain OHLC data for a desired frequency.

Introduction

Cyptocurrency trading has gained enormous popularity in recent years. To conceive profitable trading strategies requires well thought out strategies and proper backtesting on reliable data. Fortunately, obtaining this data is significantly easier than for traditional asset classes, as many crypto exchanges offer APIs to download the data for free. …

About

Stefan Haring

Quant/Data Scientist/Retail Investor. Risk/Data Management/Analytics for Investment Banks, Hedge Funds & Asset Managers

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