<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>EDA | Ukant Jadia</title><link>https://ukantjadia.github.io/tag/eda/</link><atom:link href="https://ukantjadia.github.io/tag/eda/index.xml" rel="self" type="application/rss+xml"/><description>EDA</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Fri, 01 Mar 2024 00:00:00 +0000</lastBuildDate><image><url>https://ukantjadia.github.io/media/icon_hu5e29e1df12b63ca0c9252c8db4842f1b_8915_512x512_fill_lanczos_center_3.png</url><title>EDA</title><link>https://ukantjadia.github.io/tag/eda/</link></image><item><title>Super Market Data - A In-Depth EDA</title><link>https://ukantjadia.github.io/project/eda-super-market-data/</link><pubDate>Fri, 01 Mar 2024 00:00:00 +0000</pubDate><guid>https://ukantjadia.github.io/project/eda-super-market-data/</guid><description>&lt;h1 id="retail-data-analysis">Retail-Data-Analysis&lt;/h1>
&lt;h2 id="problem-statement">Problem Statement&lt;/h2>
&lt;p>In today&amp;rsquo;s tough business world, companies need useful insights to grow and make money. But without data analysis, making decisions can be hard. This project aims to look at sales and profit data to find trends and chances for improvement. Using these insights, businesses can improve strategies and lead the market.&lt;/p>
&lt;h2 id="project-description">Project Description&lt;/h2>
&lt;ul>
&lt;li>Identify the region and city with the highest sales. &lt;a href="#sales-with-region-and-city">Link&lt;/a>&lt;/li>
&lt;li>Ship Mode&amp;rsquo;s Impact on Profitability and Sales. &lt;a href="#ship-mode">Link&lt;/a>&lt;/li>
&lt;li>Analyze the category and subcategory with the highest profit. &lt;a href="#profit-and-category-sub-category">Link&lt;/a>&lt;/li>
&lt;li>Identify the segment with the highest profit and sales. &lt;a href="profit-and-segment">Link&lt;/a>&lt;/li>
&lt;/ul>
&lt;h2 id="images">Images&lt;/h2>
&lt;p>
&lt;figure >
&lt;div class="d-flex justify-content-center">
&lt;div class="w-100" >&lt;img alt="1710550289626" srcset="
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width="760"
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loading="lazy" data-zoomable />&lt;/div>
&lt;/div>&lt;/figure>
&lt;figure >
&lt;div class="d-flex justify-content-center">
&lt;div class="w-100" >&lt;img alt="1710550303579" srcset="
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&lt;/div>&lt;/figure>
&lt;figure >
&lt;div class="d-flex justify-content-center">
&lt;div class="w-100" >&lt;img alt="1710550312211" srcset="
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&lt;/div>&lt;/figure>
&lt;figure >
&lt;div class="d-flex justify-content-center">
&lt;div class="w-100" >&lt;img alt="1710550318773" srcset="
/project/eda-super-market-data/image/index/1710550318773_hubcacf259d3ebafad10886870d39de7cb_22762_c2548c313ff6a73545fa457eaf8cad21.webp 400w,
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width="760"
height="409"
loading="lazy" data-zoomable />&lt;/div>
&lt;/div>&lt;/figure>
&lt;/p>
&lt;div>
&lt;iframe id="inlineFrameExample"
title="Analysis Notebook"
width="100%"
height="100%"
src="https://ukant.tech/Retail-Data-Analysis/">
&lt;/iframe>
&lt;/div></description></item><item><title>Exploratory Data Analysis - COVID-19 Data</title><link>https://ukantjadia.github.io/project/covid-19-eda/</link><pubDate>Thu, 23 Feb 2023 00:00:00 +0000</pubDate><guid>https://ukantjadia.github.io/project/covid-19-eda/</guid><description>&lt;p>This is an EDA Sample Project on the India geographical dataset of COVID-19.&lt;/p>
&lt;p>Problem Definition for COVID-19 EDA Sample Project:&lt;/p>
&lt;ol>
&lt;li>Analyze the association between the number of doses taken and the number of deaths in each state.&lt;/li>
&lt;li>Calculate the growth rate of confirmed cases and death rate by state.&lt;/li>
&lt;li>Calculate the distribution of doses among the population of each state.&lt;/li>
&lt;li>Compare the population of each state based on the different doses taken.&lt;/li>
&lt;/ol>
&lt;p>I followed complete workflow stages to complete the task in terms of data extraction and visualization for better understanding.&lt;/p>
&lt;p>Workflow stages for COVID-19 EDA Project:&lt;/p>
&lt;ol>
&lt;li>Question or Problem Definition.&lt;/li>
&lt;li>Acquire training and testing data.&lt;/li>
&lt;li>Wrangle, prepare and cleanse the data(preprocessing and cleaning data).&lt;/li>
&lt;li>Analyze, identify patterns, and explore the data(Visualization and information extraction).&lt;/li>
&lt;li>Conclusion (Extracted information).&lt;/li>
&lt;/ol>
&lt;p>Earlier I learned about visualization with Seaborn. Along with that, I try to utilize those skills and&lt;/p>
&lt;p>Collab notebook link: &lt;a href="https://colab.research.google.com/drive/1XGbvb6vHTmOpxEebnkjjiewxd1P6M5Tw?usp=sharing" target="_blank" rel="noopener">Link&lt;/a>&lt;/p>
&lt;p>Dataset link: &lt;a href="https://lnkd.in/dh--vGh2" target="_blank" rel="noopener">Link&lt;/a>&lt;/p>
&lt;p>My Website link: &lt;a href="https://www.ukant.tech" target="_blank" rel="noopener">https://www.ukant.tech&lt;/a>&lt;/p></description></item></channel></rss>