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        <title>TFL - Tag - ANK</title>
        <link>https://nithishkumarakula.netlify.app/tags/tfl/</link>
        <description>TFL - Tag - ANK</description>
        <generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>nakula.mam2023@london.edu (Nithish Kumar Akula)</managingEditor>
            <webMaster>nakula.mam2023@london.edu (Nithish Kumar Akula)</webMaster><copyright>This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</copyright><lastBuildDate>Mon, 19 Sep 2022 00:00:00 &#43;0000</lastBuildDate><atom:link href="https://nithishkumarakula.netlify.app/tags/tfl/" rel="self" type="application/rss+xml" /><item>
    <title>Excess rentals in TfL bike sharing</title>
    <link>https://nithishkumarakula.netlify.app/london_bikes/</link>
    <pubDate>Mon, 19 Sep 2022 00:00:00 &#43;0000</pubDate>
    <author>Nithish Kumar</author>
    <guid>https://nithishkumarakula.netlify.app/london_bikes/</guid>
    <description><![CDATA[We often use TFL bike rides, but the frequency with which varies on various factors. Lets pull the data from TFL and examine the variance in the bikes hired from the expected monthly and weekly rentals.
Let’s pull the TFL data from their data repository, and perform EDA on this.
Let’s examine how the graphs looks like for the monthly bikes hired from 2017 to current year in comparision to the average bikes hired from 2016 to 2019, which acts as our expected rentals parameter.]]></description>
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