IPL 2018 Fantasy League --- A Tableau Report on the Years Gone By

Dt.03 April 2018.

 We all know that a fresh season of the Indian Premier League 2018 is about to begin.The excitement is in the air .And since the dust has now settled on all the recent controversies on ball tampering and last minute replacements ,we can now sit back and get a quick summary of the years gone by before we deep dive into this season.

I have collected data from sports websites and summarized into a series of Tableau vizzes which are self explanatory.I will share the same with you in this blog along with short commentaries on the data as well as the Tableau type of report used for representation.

Lets start with the list of Winners & Runners up for all the years This is a Tableau TIMELINE report prepared using custom shapes.

Its disheartening to see my  home team RCB missing out on all of the winner  slots for 10 years. But my karmbhoomi's team MI has done extremely well in last few years .

Even though these were the winners the league stage looked completely different with other teams finishing number 1 before the league,Here is a tableau BUMP report done on a dual axis to highlight the same.

RCB ended up in the playoffs stage 5 times never to return back with a trophy. Notably Sourav Ganguly's KKR & PWI were very  lowly ranked teams.Tells a story about how he could not master the T20 game.

So here are the most successful captains of the IPL T20 format.Well its our Mumbai boy Rohit Sharma followed by the rest.Displayed below is a Word cloud representing the same.

Now lets have a quick look at Individual Players and records.

Top 10  Individual Scores in an innings

Sehwag holds the unique record for scoring the highest runs in an IPL innings for two different teams  DD & KXP.

Chris Gayle who was almost left out this year has the highest Individual score.(175*)

No ones has scored a  double hundred,This record could break this year

Top 10 wicket takers in an Innings

Sohail Tanvir took 6 in the first ever IPL  & Adam Zampa did a 6 wicket haul for RPS.

Top Run getters in IPL history

This goes to the Indian quartet of Raina Kohli Rohit & Gautam Gambhir. Unfortunately Yuvraj has not shined in this area.They have also been the backbone of success for CSK MI & KKR .

Top wicket takers in IPL history

This honour goes to the speedster from Mumbai .MA- LIN -GA ..This statistic is somehow not shown across too many times since this game is dominated by batsmen.Yet Malinga has been phenomenal in IPL with his rare slinging action.Another silent warrior is Amit Mishra the leggie who has been currently sidelined in the Indian squad.

While Ashwin might not have played all seasons , Bhajji has a better record in IPL.

Well this wraps up the Tableau summary for the years gone by.

Based on these reports you can now predict the winners for this season.My top 4 bets are.

1. RCB never won a trophy

2. CSK in the combeack year and fan sentiments running high

3. KXP with a  hurting Gayle factor & Sehwag as coach 

4  DD with Maxwell & Gambhir both hurting and ready to make a statement 

You can predict your winners too in the comments.

Trivia: Who holds the record for the most sixes in IPL history.


For people ineterested in the Interactive dahboards .Please visit my tableau Public Profile
https://public.tableau.com/profile/ashwin.puthran#!/

note: Data has been manually collected from various resources.Let me know if you observe a discrepancy.

Tableau Vizzes from Twitter Feeds -- Part II (Arsenal tweets)

Dt: 05th  March 2018

  OK as promised  I will be sharing the Tableau vizzes from the @arsenal search on twitter feed.The twitter extract was taken after the Carabao Cup Final which unfortunately Arsenal lost.

Here is how twitter reacted to the result .I have listed some tweets which were liked by twitterrati and retweeted the maximum times

Tweets

I extracted  around a few thousand tweets and this is the frequency of the tweets over a timeline

Timeline

A quick plot of the location of the people who tweeted will give you an idea of how the English Premier League & the Arsenal football club is followed  all around the world.You would be surprised to know that after US, UK & the Netherlands the maximum tweets came from India, Indonesia, Morocco & Kenya. Now thats where the merchandise is most likely to sell.Unfortunately the club is not in India in a big way in terms of selling merchandise.Something that they can do with FDI rules being relaxed in the retail space.

Mapped

Someone asked me about sentimental analysis and the most popular hashtags. I tried to analyse this by splitting the extracted tweets and getting the first hashtag on each one of them.Of course with some more SQL you could get all the hashtags but the first hashtag was good enough for me.This is how the hashtag cloud came up.

Hashtag Cloud

Of course #Wengerout was one of the more widely used hashtags .Fortunately/unfortunately he is not going anywhere :-)

Finally I wanted to know how we could summarize info on various twitter vizzes  onto one amazing dashboard which could be presented to the executives of these institutions.This is what I came up with. Of course the more creative ones will get better it better designed :-)

Dashboard

Well this is how amazing it can be. If someone tells you that they have expertise on R and Big Data and want  to demonstrate solutions , you got to ask them if they could get this done on a bigger scale.If they can do this then they have got it.As they say the proof of the pudding is in the eating :-)

Thats it for now .Will be back with more interesting features on Tableau reporting.
Signing off

Note:If anyone  knows what #coyg means then please leave me a comment .New generation language :-|

Tableau Vizzes from Twitter Feeds -- Part I

Dt:27 Feb 2018

  Last Sunday when I was at  a social gathering I met one of my classmates from my engineering college.He told me that he had read my blogs on about building Tableau vizzes & was particularly interested in my findings as he was working on similar reports with Microsoft's Power BI.While we continued talking on the subject , he mentioned that he has worked on building reports over  data extracted from twitter feeds & asked me to check if its possible with Tableau.

  With traditional BI tools , extracting data from  the internet meant that you would have to spend a lot of time researching and exploring solutions to get the whole thing to work. But with some of the modern day visualization tools the opportunities are easier to explore & implement.I was reading up on the internet and I found out that QlikView & QlikSense can connect to twitter feeds .The parent company provides a connector and has  made it available for free trial.I intend to try this out when I explore QlikSense in the months to come.

   For Tableau I read up that Cdata provides some connectors(ODBC drivers) which can connect to twitter (Not sure if they work well with Tableau ).These connectors can also be used for traditional BI tools .However  I could not find a place where I could get these connectors for free.Currently they go for at least 299$/year for desktop subscriptions.

  The next best possible solution to get twitter feeds on Tableau was by using Tableau Junkie's web data connector  (Hosted here  http://tableaujunkie.com/post/119681578798/creating-a-twitter-web-data-connector ) .The guy also talks about building your own web data connector using Twitter API .I will try to build one for myself when I get some time.

   For now I used Tableau Junkie's Webdata connector to pick up tweets with mentions for @narendramodi. Here is what I came up with at the end of this exploration.

Analyzing tweets with words like 'mission' addressed to @narendramodi.

Analyzing the frequency of tweets with mention of @narendramodi

This concludes Part- I of our discovery on twitter integration with Tableau.
It looks like we could conduct some sentiment analysis using this metadata. All you would require is some good experience with string SQL functions(& not R for now :p)  .I will reserve that for advance analysis at a later stage.

Tomorrow I will publish Part-II where we discover twitter mentions of the Arsenal Football Club along with some geo tagging  & will also explore Tableau Dashboards.

Till then good bye !!!

Note: This article is dedicated to Mr.M from MAK who inspired me to research this.Always remember MAK makes it possible

Credits : http://tableaujunkie.com/     The website has lot of content on BI which you may be interested to read.It also hosts quite a few web data connectors .

Indian Literacy Revolution -- Tableau Maps

Dt: 22 Feb 2018.

   I have been trying to get my hands on one  of the most talked about visualization tools in the market these days. Visualization is all about perceiving data , I thought it would be interesting if I could blend my learning along with getting a perspective on  data which is relevant to people of India and which will help us understand the Indian demographics better.

   In order to achieve this objective I tried to look at the data from the Census carried out by government of India every decade.For my analysis this time around I looked at India's literacy rate in all its states as reported by  2001 & 2011 Census.It would be interesting to see how India is slowly getting converted from a mostly illiterate country to a mostly literate nation.This change in the last decade is eventually going to ensure that we will be the World's largest literate workforce by 2021.

  Since this data is geographical in nature and I have been fascinated by all those  Map based visualizations which experts provide nowadays, I tried to create my first Map  based visualizations to analyse this data.

The visualizations below show India's literacy rate in 2001 & 2011.Notice the improvement and also the states which are marching forward after the country was armed with RTE(Right to Education ).RTE will ensure more literacy by the time we reach the next census

Literacy rate in 2001 

See the glorious improvement in 2011

As you could see now states like Maharashtra Haryana Tamil Nadu & the north eastern states are now giving Kerala a run for its money :-)

Finally it was fun plotting India's map.Gave me a sense of satisfaction & pride.One thing that was off was that Tableau by default does not show POK as part of India.However they have managed to keep all parties happy by letting you see a map that would satisfy your country's borders.If you tweak the locale settings then you can manage to see entire Kashmir as part of India.  

Signing off for now...will target  demonstrating  another fun aspect of Tableau visualizations in my next blog.

Income Tax Collection in India - Hard Facts

Dt :9 Feb 2018.

I have referred to the following two public documents to publish graphical results using Tableau Public.

Income Tax Return Statistics AY 2015-16 Version 1.0 December 2017
Income Tax Return Statistics AY 2014-15 Version 1.1 January 2018

I have considedred Gross Income of Individual tax payers for the purpose of this analysis.

I will limit myself to minimum commentary and let the  Tableau Vizzes explain the story

Spread of Returns Filed Across Income Slabs

Spread Of Total Gross Income reported against Income Slabs

Income Slabs where maximum returns are Filed

The Truth Pie --- Reveals the truth behind the current government's slab revisions during Budgets

Out of the 4 Crore Individual tax payers close to 2.8 crore  fall below the Rs.5 Lakh slab.

Increase in Income reported in AY 2015-16

Surprisingly the people earning more than 500 crores have contributed less this time around.

New Tax Payers Added

Extra Income Reported 

If you look at all the graphs you would realize that the government has increased its tax collection from Individual tax filers.

This number is expected to shoot  up drastically after the post demonetization IT return statistics are out.

We will wait for them....

IPL - Chennai Super Kings -- Tableau Public Analysis Vizzes

Dt: 8 February 2018

I have been looking at various visualization tools over the years to understand  how quickly one can adapt and create reports using each one of them.The tool that I have had the most fun using has undoubtedly been Tableau .

I was looking up their website and found out that they now have something which is called as Tableau Public.This essentially is a free tool with all capabilities ,The only catch is that the reports crated will be public and shared on their platforms.
But heck its a good solution for everyone of us who would like to learn the tool without having to spend big bucks.

So without spending much time I did set up some data from the biggest public event this year which was the IPL 2018 mega auctions .For my experiment today I chose the most popular IPL team over the years which is CSK.

Here are some of the reports which I could set up within a couple of hours once the data was set up.

CSK IPL 2018 Big Spends (Sheet 1)

CSK Talent Hunt

Lastly lets look  at the types of players they Invested in.

Looks like CSK invested the most on Allrounders both in terms of money & talent .We can predict that they are planning to win their next IPL by relying on their allrounders.

Thats it for the day. !!!

Note:
The reports are shared on Tableau Public 
https://public.tableau.com/profile/ashwin.puthran#!/

How the BJP fooled Middle class Indians -- Salaried Income tax payers better off in Congress era.

Dt: 6th Feb 2018

This excel will help you answer all BJP supporters who are in your face insisting that honorable Mr Arun Jaitley ,our FM has given the middle class a lot of sops over the last 5 years.


We all  middle class voted in large numbers for the BJP but after all budgets were delivered we feel left out and there is solid reason for this feeling to have cropped up.Essentially I will explain with this piece of mathematical number crunching what the FM has actually given the middle class in the form of tax sops .

This sheet will tell you how a person earning around Rs.10 Lakh per annum will have to bear a notional annual loss of close to Rs 1 Lakh if he tries to go about saving an extra 10-15k Rs in taxes.

So stand your ground when the supporters throw false data at  you to justify the FM's claims.We were looking at a 5 year period which would lead to abolition of income taxes in India or at least rationalization considering very few are in the tax net.The narrative therefore is clear , that the middle class has been given nothing in terms of tax sops during the BJP regime of 2014-2018