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    <title>Archives on Dario Arcos-Díaz, PhD</title>
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    <description>Recent content in Archives on Dario Arcos-Díaz, PhD</description>
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      <title>COVID-19 Germany local incidence and ICU occupancy (in German)</title>
      <link>https://arcosdiaz.com/archive/2021-01-01-covid19-germany-dashboard/</link>
      <pubDate>Fri, 01 Jan 2021 00:00:00 +0000</pubDate>
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      <description>Some time ago at the beginning of the COVID-19 pandemic, I decided to create a Twitter bot to automatically gather the latest data in Germany and share it to the Twittersphere. I also created and deployed a dashboard heroku app.</description>
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      <title>Fitbit activity and sleep data: a time-series analysis with Generalized Additive Models</title>
      <link>https://arcosdiaz.com/archive/2018-04-01-fitbit_prophet/</link>
      <pubDate>Sun, 01 Apr 2018 00:00:00 +0000</pubDate>
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      <description>This is a time-series analysis of activity and sleep data from a fitbit user throughout a year. I use this data to predict an additional year of the life of the user using Generalized Additive Models.</description>
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      <title>Exploratory analysis of Medicare drug cost data 2011-2015</title>
      <link>https://arcosdiaz.com/archive/2017-02-06-medicare-drug-cost/</link>
      <pubDate>Mon, 06 Feb 2017 00:00:00 +0000</pubDate>
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      <description>Health care systems world-wide are under pressure due to the high costs associated with disease. In this post, I performed an analysis of Medicare data in the USA. Furthermore I used a drug-disease open database to cluster the costs by disease. I identified the most expensive diseases (mostly chronic diseases such as Diabetes) and the most expensive medicines.</description>
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      <title>Visualizing parallel event series in Python</title>
      <link>https://arcosdiaz.com/archive/2017-02-06-event-tracker/</link>
      <pubDate>Mon, 06 Feb 2017 00:00:00 +0000</pubDate>
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      <description>In this post, I will use Python to visualize two different series of events, plotting them on top of each other to gain insights from time series data.</description>
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      <title>Simulating the revenue of a product with Monte-Carlo random walks</title>
      <link>https://arcosdiaz.com/archive/2016-10-15-product-revenue-forecast/</link>
      <pubDate>Sat, 15 Oct 2016 00:00:00 +0000</pubDate>
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      <description>I take a look at how we can model the future revenue of a product by making certain assumptions and running a Monte Carlo simulation.</description>
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