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    <title>DEV Community: AK</title>
    <description>The latest articles on DEV Community by AK (@akashdve).</description>
    <link>https://dev.to/akashdve</link>
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      <title>DEV Community: AK</title>
      <link>https://dev.to/akashdve</link>
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    <item>
      <title>Hacking Myself</title>
      <dc:creator>AK</dc:creator>
      <pubDate>Sun, 10 Jan 2021 16:24:35 +0000</pubDate>
      <link>https://dev.to/akashdve/hacking-myself-1dp5</link>
      <guid>https://dev.to/akashdve/hacking-myself-1dp5</guid>
      <description>&lt;h2&gt;
  
  
  What I built
&lt;/h2&gt;

&lt;p&gt;I have built a small handy web app for basic data exploration. It can accept either a url or a file(.csv/.xlsx/.json/.df) and provide basic data insights. As title suggest, I had a chance to hack myself to the fullest and explore my new limits because I have to built it in really short time (1 day - read about dohackathon on 9th Jan :D). &lt;/p&gt;

&lt;h3&gt;
  
  
  Category Submission:
&lt;/h3&gt;

&lt;ul&gt;
&lt;li&gt;Program for the People&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;
  
  
  App Link
&lt;/h3&gt;

&lt;p&gt;&lt;a href="https://dataexplorer-webapp-pv6l3.ondigitalocean.app/"&gt;https://dataexplorer-webapp-pv6l3.ondigitalocean.app/&lt;/a&gt;&lt;/p&gt;

&lt;h3&gt;
  
  
  Screenshots
&lt;/h3&gt;

&lt;p&gt;&lt;a href="https://res.cloudinary.com/practicaldev/image/fetch/s--446K5rTD--/c_limit%2Cf_auto%2Cfl_progressive%2Cq_auto%2Cw_880/https://dev-to-uploads.s3.amazonaws.com/i/0glm86ctxdx3o8x51o9z.png" class="article-body-image-wrapper"&gt;&lt;img src="https://res.cloudinary.com/practicaldev/image/fetch/s--446K5rTD--/c_limit%2Cf_auto%2Cfl_progressive%2Cq_auto%2Cw_880/https://dev-to-uploads.s3.amazonaws.com/i/0glm86ctxdx3o8x51o9z.png" alt="Main Screen"&gt;&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;&lt;a href="https://res.cloudinary.com/practicaldev/image/fetch/s--rAfojcaw--/c_limit%2Cf_auto%2Cfl_progressive%2Cq_auto%2Cw_880/https://dev-to-uploads.s3.amazonaws.com/i/rbhe10t70eeo7nfoa2z5.png" class="article-body-image-wrapper"&gt;&lt;img src="https://res.cloudinary.com/practicaldev/image/fetch/s--rAfojcaw--/c_limit%2Cf_auto%2Cfl_progressive%2Cq_auto%2Cw_880/https://dev-to-uploads.s3.amazonaws.com/i/rbhe10t70eeo7nfoa2z5.png" alt="Showing raw data and heatmap"&gt;&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;&lt;a href="https://res.cloudinary.com/practicaldev/image/fetch/s--SlRPwacc--/c_limit%2Cf_auto%2Cfl_progressive%2Cq_auto%2Cw_880/https://dev-to-uploads.s3.amazonaws.com/i/jvflvddksvpufnmv7n38.png" class="article-body-image-wrapper"&gt;&lt;img src="https://res.cloudinary.com/practicaldev/image/fetch/s--SlRPwacc--/c_limit%2Cf_auto%2Cfl_progressive%2Cq_auto%2Cw_880/https://dev-to-uploads.s3.amazonaws.com/i/jvflvddksvpufnmv7n38.png" alt="Displaying Pairplots"&gt;&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;&lt;a href="https://res.cloudinary.com/practicaldev/image/fetch/s--7VznI-qB--/c_limit%2Cf_auto%2Cfl_progressive%2Cq_auto%2Cw_880/https://dev-to-uploads.s3.amazonaws.com/i/uwq1csahsvvyk129mv5u.png" class="article-body-image-wrapper"&gt;&lt;img src="https://res.cloudinary.com/practicaldev/image/fetch/s--7VznI-qB--/c_limit%2Cf_auto%2Cfl_progressive%2Cq_auto%2Cw_880/https://dev-to-uploads.s3.amazonaws.com/i/uwq1csahsvvyk129mv5u.png" alt="Columnwise Insights and WordClouds"&gt;&lt;/a&gt;&lt;/p&gt;

&lt;h3&gt;
  
  
  Description
&lt;/h3&gt;

&lt;p&gt;First Step: Provide a url / Upload a file&lt;/p&gt;

&lt;p&gt;Second Step: Step back and relax&lt;/p&gt;

&lt;p&gt;You will see a Heat Map representing correlation between numeric columns followed by bunch of pair plots.&lt;/p&gt;

&lt;p&gt;Related to column-level insights, in next section, you will have to choose columns to view the min/max/count/freq properties.&lt;/p&gt;

&lt;p&gt;Next, to view insights from non-numeric columns, WordCloud is the good way to see the most frequent words. Here you will have to select non-numeric columns to form wordclouds for each columns.&lt;/p&gt;

&lt;h3&gt;
  
  
  Link to Source Code
&lt;/h3&gt;

&lt;p&gt;&lt;a href="https://github.com/akashdve/dataexplorer_webapp"&gt;https://github.com/akashdve/dataexplorer_webapp&lt;/a&gt;&lt;/p&gt;

&lt;h3&gt;
  
  
  Permissive License
&lt;/h3&gt;

&lt;p&gt;BSD-3&lt;/p&gt;

&lt;h2&gt;
  
  
  Background
&lt;/h2&gt;

&lt;p&gt;(What made you decide to build this particular app? What inspired you?)&lt;br&gt;
I would love to share that I came to know about this hackathon a day before the deadline and I really wanted to take part. As soon as I decided, a wide-stream of ideas was rushing into my mind making it more harder to choose. Choosing the simple way, finally, I opted to make a simple web app which can reduce some coding effort of mine as well as others. &lt;/p&gt;

&lt;p&gt;I always find datasets very fascinating and I try to pull out some insights from it. But here's the problem I face is I always needed to write similar code for every new jupyter notebook. &lt;/p&gt;

&lt;p&gt;Why to write the same code for calculating mean/sum/count/min/max etc. for every datasets ? &lt;br&gt;
I thought of having a simple, basic and quicker way to do this job. I didn't have much time to implement every feature and functionality as I have developed this app overnight but suggestions are welcome.&lt;/p&gt;

&lt;h3&gt;
  
  
  How I built it
&lt;/h3&gt;

&lt;p&gt;(How did you utilize DigitalOcean’s App Platform? Did you learn something new along the way? Pick up a new skill?)&lt;br&gt;
I learned to deploy my code without having to worry about the DevOps and other server related configurations. Also, I find the DigitalOcean App platform is a faster way to deploy and prototype your code.&lt;/p&gt;

&lt;h3&gt;
  
  
  Additional Resources/Info
&lt;/h3&gt;

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      <category>dohackathon</category>
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