10 Things A New Blogger Must know about Ad Based Earning

What is Ad Revenue for blog site?

When someone visits your website/blog, they get to see some advertisements appearing on the side or in middle of the page. Those Ads may or may not be relevant to the content of the website always. But more often than not, they are relevant to the content and that also increases the chances of someone clicking an advertisement. When that happens, your blog/website actually redirects a potential buyer to a website. Merchants pay for such customer visits on their site and you essentially earn few cents or rupees into your account.

Well, how much money blog websites are actually making?

Well, it could be as high as $100K per month if you believe this blog - How to Make Money Blogging: How This Blog Makes $100K per Month - https://smartblogger.com/make-money-blogging

Here is another good article - How to make money blogging in 2017 - https://makeawebsitehub.com/how-to-make-money-blogging

One more - How Hard is it to Make Money Blogging? - http://www.busybudgeter.com/how-hard-is-it-to-make-money-blogging

Hold on, don't get super excited. It's much easier said than done, when it comes earning out of blogging.

Sounds promising, how do I start showing those Ads on my blogs?

At high level, there is Goliath in this industry and that's Google, to be precise it's Google Adsense. In recent times even Amazon's Affiliate Program is also becoming a significant market player in this space. But there are many more Ad Network and Affiliate Programs. For Mobile Apps, one of the leading leading program is from InMobi.

For our discussion, we will focus on regular Web based blogs and restrict the discussion on Google's Adsense and Amazon's Affiliate Program.

How to setup Google Adsense Account?

As expected, Google Adsense is pretty good in getting you started with setting up of your Adsense account. So, go ahead take a look at  https://www.google.co.in/adsense/start and most likely you won't need anything additional.

How to setup Amazon Affiliate Website?

As with case with Google, even Amazon is pretty good in getting you started with their Affiliate Marketing program. Visit https://affiliate-program.amazon.in

You like to read little bit about it here.
https://makeawebsitehub.com/build-amazon-affiliate-website


Can you give some example blogs in few popular categories?



What I need to learn in order to be successful in this field?

You need to be good in your core value proposition i.e. the topics and the contents of your blog. That's the most critical aspect. Second, you need to setup your blog site. That's easy, we will cover it next. Last, in order to become a successful BlogPreneur, essentially you will have to learn about Digital Marketing.

Can you please suggest few top Learning Resources?

Take a look at the following url and you will get to know about the next upcoming course on Digital Market. It's free!!!

https://www.coursera.org/specializations/digital-marketing
https://www.coursera.org/learn/marketing-plan

You may like to take a look at the courses offered at Udemy. Usually, Udemy charges money for the courses but there are many free courses as well.

https://www.udemy.com/proven-ways-to-make-money-from-a-blog
https://www.udemy.com/start-a-business-blogging-online

I love the blogs, video blogs by Neil Patel. Here is a great a great slide deck from Neil Patel

How to Generate 195,013 Visitors a Month Without Spending a Dollar on Ads -
https://www.slideshare.net/neilkpatel/advanced-customer-acquisition-webinar


How to setup a blogging website?

Go to https://www.blogger.com, use your Google/Gmail account to login. Setup a blog and start writing your blogs.

Similarly, you may user Wordpress - https://wordpress.com or Tumblr - https://www.tumblr.com to setup your blogging website. All for free!!!

If you want have your vanity url, you may buy a domain at https://www.networksolutions.com or at https://www.enom.com or at https://in.godaddy.com and purchase a domain. Usually, for a domain with non-eye-catchy name will cost you around $13 per year.

Any additional tips and tricks?

In Progress.

Economic Data of World's Major Economies

Unlike other posts of mine, this one is just a list of Mini Dashboard & Charts of Economic Data of major world economies. The first one is the Mini Dashboard, you can access it here.

Charts are created using the Visualisation Application http://www.StatsPanda.com

Before you scroll down, here are the steps I followed for creating the charts.

1. Uploaded the spreadsheet with economic data to StatsPanda.com.
2. Created a Datasource with the Data from the uploaded spreadsheet.
3. Used the same Datasource to create the following charts & the mini dashboard.

You need to be a logged in user in StatsPanda.com and your profile registration must be completed before you try out the above steps. For details, you may refer to their blogs @ http://blog.statspanda.com

Major World Economies Export, Import, GDP (in ppp terms), Debt in $ billions:

Data related to Top World Economies:

GDP (PPP & Nominal) and Debt of the countries along Export & Import:

Export (Y-Axis) vs Import (X-Axis) vs Size of Economies (GDP in PPP terms) for top World economies:

Hope you find it useful.

Stupid! You never Gonna Make Money in Gamble.

Recently I bought two dices thinking I will use them to play with my three and half year old daughter and that may help enhance her maths skills. Unfortunately, she lost interest in the dices in first 10 minutes but they made me curious enough to spend few more days with the dices and then finally to write a java program that can simulate the game of rolling two dices for millions of times at my wish.

A simple game will involve rolling two dices and add the numbers appearing on the sides facing upwards to determine winning bet (number). The person who betted on that number is the winner. Every dice has 6 faces with numbers 1 through 6. So, sum of the numbers from two dices will be one of these 11 numbers - 2, 3, 4, 5, 6 , 7, 8, 9, 10, 11, 12. Interestingly, some of the numbers from the list have higher chances of appearing than others, simply because they can be produced by more combinations. For example, 2 can be produced only by 1 + 1 but 7 can be produced by 1 + 6, 2 + 5, 3 + 4, 4 + 3 and more. That makes 7 a far more lucrative an option for a gambler to pick when compared to 2. Overall there are 6 x 6 = 36 different ways you can get one of 11 numbers.

Let's go ahead and spend some time looking into the data that the Java program generated and how gambling may use this variability in probability distribution to give rich people an adrenaline rush. This program simulates rolling of two dices by generating two random numbers in the range  of 1 - 6. Then is sums them up to come up with the winning number. It repeats the steps as many times as you ask it to.

Let's generate the frequency distribution by rolling of two dices for 10 million times. 

| Position  | Frequency | Feq in % | 

------------------------------------------

| Number 12 | 277,771 | 2.78% | 

------------------------------------------

| Number 2 | 277,148 | 2.77% | 

------------------------------------------

| Number 4 | 831,981 | 8.32% | 

------------------------------------------

| Number 3 | 555,619 | 5.56% | 

------------------------------------------

| Number 6 | 1,389,822 | 13.9% | 

------------------------------------------

| Number 5 | 1,110,738 | 11.11% | 

------------------------------------------

| Number 8 | 1,389,151 | 13.89% | 

------------------------------------------

| Number 7 | 1,666,267 | 16.66% | 

------------------------------------------

| Number 9 | 1,112,411 | 11.12% | 

------------------------------------------

| Number 11 | 555,447 | 5.55% | 

------------------------------------------

| Number 10 | 833,645 | 8.34% | 

------------------------------------------

| Total Rounds | 10,000,000 | 100% | 

------------------------------------------

This distribution is similar to what you will see if you do a simple calculation using permutation formula. Although, I personally never found permutation & combination simple.

Now, let's make it a little serious affair. To have a real gamble, we will bring in real money and a Table Owner who runs the Games of Gamble. Table owner takes certain % cut and rest of the money goes to the winning bet.

  

The games will be played by 11 Players. Each player can bet only on one specific number and can bet for $10. Table owner will charge 20% of the amount betted. The games will be played for 2 million times. So, total money involved is $220 million.

| Player Position  | Money Earned | % of Total Bet Amount |

---------------------------------------------

| Player 10 | $14,669,600 | 7% | 

---------------------------------------------

| Player 11 | $9,750,488 | 4% | 

---------------------------------------------

| Player 8 | $24,552,264 | 11% | +ve

---------------------------------------------

| Player 7 | $29,277,952 | 13% | +ve

---------------------------------------------

| Player 9 | $19,553,160 | 9% | 

---------------------------------------------

| Player 4 | $14,633,696 | 7% | 

---------------------------------------------

| Player 3 | $9,773,192 | 4% | 

---------------------------------------------

| Player 6 | $24,457,400 | 11% | +ve

---------------------------------------------

| Player 5 | $19,573,752 | 9% | 

---------------------------------------------

| Player 2 | $4,876,344 | 2% | 

---------------------------------------------

| Player 12 | $4,882,152 | 2% | 

---------------------------------------------

| Table Owner | $44,000,000 | 20% | 

---------------------------------------------

| Spend Per Player | $20,000,000 | 9% | 

---------------------------------------------

| Total Amount Betted | $220,000,000 | 100% | 

---------------------------------------------

As you can see Table Owner gains the most. With exception of him, there are only three other players - Player 7, Player 6 & Player 8 who made some money and there are 8 other players who lost money. 

But we know it was not practical. How can you expect a Gambler to try his luck only with one number? Let's take out that restriction along with few other restrictions - number of players could be anything between 1 to 11, players can bet any amount ranging from $10 to $1000 on any number and Table Owner will not have any pre-defined cut. However, we will still not allow more than one bet to be placed against one number. Number of players and the amount they bet in one particular round will be randomly determined by the program. The game will continue for 1 million times.

TOTAL AMOUNT BETTED BY EACH PLAYER POSITION

------------------------------------

Player Position 4 | $276,025,231

------------------------------------

Player Position 5 | $275,850,639

------------------------------------

Player Position 6 | $275,374,362

------------------------------------

Player Position 7 | $275,526,040

------------------------------------

Player Position 2 | $275,613,052

------------------------------------

Player Position 3 | $274,947,829

------------------------------------

Player Position 10 | $275,777,883

------------------------------------

Player Position 11 | $275,233,244

------------------------------------

Player Position 12 | $275,308,337

------------------------------------

Player Position 8 | $275,197,852

------------------------------------

Player Position 9 | $274,973,749

------------------------------------

Total Betted Amount | $3,029,828,218

------------------------------------

TOTAL AMOUNT WON BY EACH PLAYER POSITION 

-----------------------------------------------

| Player Position 4 | $175,887,913 | 5.81% | 

-----------------------------------------------

| Player Position 5 | $234,566,644 | 7.74% | 

-----------------------------------------------

| Player Position 6 | $292,437,606 | 9.65% | +ve

----------------------------------------------- 

| Player Position 7 | $350,616,777 | 11.57% | +ve

-----------------------------------------------

| Player Position 2 | $57,980,399 | 1.91% |

-----------------------------------------------

| Player Position 3 | $118,038,318 | 3.90% |

-----------------------------------------------

| Player Position 10 | $176,005,502 | 5.81% |

-----------------------------------------------

| Player Position 11 | $117,401,400 | 3.87% |

-----------------------------------------------

| Player Position 12 | $58,484,553 | 1.93% |

-----------------------------------------------

| Player Position 8 | $294,861,804 | 9.73% |

-----------------------------------------------

| Player Position 9 | $233,939,146 | 7.72% | +ve

-----------------------------------------------

| Table Owner | $919,608,156 | 30.35%

-----------------------------------------------

| Total Amount Betted | $3,029,828,218 | 100.00%

-----------------------------------------------

Take a look, in this case we had no pre-determined cut for the Table Owner but he still made a billion ;). As for the playing positions, same trend continues i.e. Playing Position 6, 7, 8 gave positive returns and rest all numbers lost money. If that's the case why would any one put money on any other number? They won't put money anywhere other than 7. Obviously, this is not a fair game.

So, lets design a Fair Game. Goal would be to neutralise the effect of position by giving differential returns.  

Here are two tables showing how much will be your return for every $ you bet on each of the positions if yours is the winning bet:

Table Owner doesn't charge anything

----------------------

| Number 12 | $36 |

----------------------

| Number 2 | $36 |

----------------------

| Number 4 | $12 |

----------------------

| Number 3 | $18 |

----------------------

| Number 6 | $7 |

----------------------

| Number 5 | $9 |

----------------------

| Number 8 | $7 |

----------------------

| Number 7 | $6 |

----------------------

| Number 9 | $9 |

----------------------

| Number 11 | $18 |

----------------------

| Number 10 | $12 |

----------------------

Table owner takes a cut of 20%.

----------------------

| Number 10 | $10 |

----------------------

| Number 11 | $15 |

----------------------

| Number 8 | $6 |

----------------------

| Number 7 | $5 |

----------------------

| Number 9 | $7 |

----------------------

| Number 4 | $10 |

----------------------

| Number 3 | $14 |

----------------------

| Number 6 | $6 |

----------------------

| Number 5 | $7 |

----------------------

| Number 12 | $29 |

----------------------

| Number 2 | $29 |

----------------------

Take a look at the above tables once again and you will realise the returns on the Winning number looks pretty good and at the same time it's fair. No number has any advantage over another number when it comes to overall return over sufficiently large number of games of gamble. At the same time it can accommodate the risk appetite of any gambler by giving differentiated returns, inversely proportional to the probability of a number coming up as a winning bet. Voila! we just designed a game of gamble which is probably closest to what you would see in a casino.

Let's check the returns for various numbers - 8, 7, 12 over 3 million bets for each of them when the Table Owner takes a 30% cut. Amount of each bet is $10. Returns are similar irrespective of probability of the number coming up.

Gambler betting on 7

 -----------------------------------------------

| Table Owner | $9,526,117 | 31.75%

-----------------------------------------------

| Player 7 | $20,473,883 | 68.25%

-----------------------------------------------

| Total Amount Betted | $30,000,000 | 100.00%

-----------------------------------------------

Gambler betting on 8

-----------------------------------------------

| Table Owner | $9,218,150 | 30.73%

-----------------------------------------------

| Player 8 | $20,781,850 | 69.27%

-----------------------------------------------

| Total Amount Betted | $30,000,000 | 100.00%

-----------------------------------------------

Gambler betting on 12

-----------------------------------------------

| Table Owner | $9,019,975 | 30.07%

-----------------------------------------------

| Player 12 | $20,980,025 | 69.93%

-----------------------------------------------

| Total Amount Betted | $30,000,000 | 100.00%

-----------------------------------------------

Next, I am going to try the same gamble i.e. Payoff Matrix is fair and Table Owner takes a cut, with rest of the factors are randomised. In the example below number of players ranges from 6 to 20, game continues for 10 to 100,000 times, betted amount ranges from $10 to $1000 and Table Owner takes a cut of 20%. Outcome is similar. On an average, all the players lose the amount that the Table Owner charges. 

No of Rounds 9973

No Of Players 18

TOTAL AMOUNT BETTED BY GAMBLERS 

-----------------------------------------

| Player 10 | $5,049,130 | 5.57%

-----------------------------------------

| Player 11 | $5,049,573 | 5.57%

-----------------------------------------

| Player 8 | $5,041,264 | 5.56%

-----------------------------------------

| Player 7 | $5,052,238 | 5.57%

-----------------------------------------

| Player 9 | $5,039,512 | 5.56%

-----------------------------------------

| Player 4 | $5,064,714 | 5.58%

-----------------------------------------

| Player 3 | $5,022,313 | 5.54%

-----------------------------------------

| Player 6 | $5,003,299 | 5.52%

-----------------------------------------

| Player 5 | $5,069,510 | 5.59%

-----------------------------------------

| Player 0 | $5,032,736 | 5.55%

-----------------------------------------

| Player 2 | $5,090,774 | 5.61%

-----------------------------------------

| Player 1 | $5,014,831 | 5.53%

-----------------------------------------

| Player 16 | $5,026,509 | 5.54%

-----------------------------------------

| Player 17 | $5,028,077 | 5.54%

-----------------------------------------

| Player 12 | $5,015,401 | 5.53%

-----------------------------------------

| Player 13 | $5,024,943 | 5.54%

-----------------------------------------

| Player 14 | $5,047,221 | 5.56%

-----------------------------------------

| Player 15 | $5,024,303 | 5.54%

-----------------------------------------

| Total Amount Betted | $90,696,348 | 100.00%

-----------------------------------------

Total Amount Won

--------------------------------------------

| Player 10 | $4,211,682 | 4.64%

--------------------------------------------

| Player 11 | $4,117,135 | 4.54%

--------------------------------------------

| Player 8 | $3,931,574 | 4.33%

--------------------------------------------

| Player 7 | $4,170,266 | 4.60%

--------------------------------------------

| Player 9 | $4,144,855 | 4.57%

--------------------------------------------

| Player 4 | $4,310,571 | 4.75%

--------------------------------------------

| Player 3 | $4,013,216 | 4.42%

--------------------------------------------

| Player 6 | $3,910,301 | 4.31%

--------------------------------------------

| Player 5 | $4,083,093 | 4.50%

--------------------------------------------

| Player 0 | $4,090,285 | 4.51%

--------------------------------------------

| Player 2 | $4,209,126 | 4.64%

--------------------------------------------

| Player 1 | $3,955,758 | 4.36%

--------------------------------------------

| Player 16 | $4,161,625 | 4.59%

--------------------------------------------

| Player 17 | $3,849,358 | 4.24%

--------------------------------------------

| Player 12 | $3,904,212 | 4.30%

--------------------------------------------

| Player 13 | $4,074,304 | 4.49%

--------------------------------------------

| Player 14 | $4,022,716 | 4.44%

--------------------------------------------

| Player 15 | $3,983,948 | 4.39%

--------------------------------------------

| Table Owner | $17,552,323 | 19.35%

--------------------------------------------

| Total Amount Won | $90,696,348 | 100.00%

--------------------------------------------

If you had generated the Payoff Matrix without paying anything to the Table Owner, the long term returns for the Gamblers would reflect the same i.e. amount betted and won would be almost the same. But that's not how real world works. Such patterns hold good only for sufficiently large amount games. For lesser number of games the results could be very unpredictable. Gamblers may make a killing or may lose significantly. In fact, the Table Owner may not make any money or may end up earning much more than the planned cut. 

Across all of the data shared above, one point becomes pretty obvious - that a gambler will never make money irrespective of where he puts his bet on. That's true even when he spends all his wealth and his lifetime playing a fair game of gamble. Gambling is meant for adrenaline rush & one pays for that service. That's it. No one is smart enough to make money in gambling over period of time, unless you run the Game of Gamble. 

Hope you enjoyed reading the post.

10 Things you must know about Charts, Graphs & Visualization

"In God we trust, all others must bring data" said W. Edwards Deming. But we all know it is easier said than understood when data is actually presented in front of you. Often you need a statistician to interpret it. And they are rare! What you need is a straight and simple way to represent data that brain can interpret relatively easily. Here comes the need for Charts, Graphs and other visualization.

I started exploring the various Charts & Graphs libraries for generating insight for my hobby project www.fanffair.com. Goal was to identify the top posts based on statistical analysis of Like, Share and Comments data associated each post and share the top posts on fanffair Facebook Page. That in turn led to second hobby project of mine www.statspanda.com. In this blog post, I am going to share my notes, learning & observations as I sifted through various charting libraries ranging from Google Charts, morris.js, raphael.js, xCharts, nvd3, Flot charts, dygraphs, Rickshaw, Highcharts et al to D3.js.

All of the above are the charting libraries that either you download or use as hosted-library and invoke the JavaScript methods to create a chart or graph in your web application, albeit some of them are pretty straight and simple to use while libraries like D3.js requires some amount of programming skills and knowledge of HTML, Javascript etc. But unlike Charting libraries, D3.js gives all the power and flexibility for creating exotic visualizations. You can as well pick some of the visualization created and curated by Mike Bostok.

If you want to avoid either of the options, then you can go for online services that take your data and generate the charts and graphs online. There are many such services, some of them are really big. Many of them are often categorized as data analytics companies as they deal a lot in the data layer. I have provided a list of such services/companies in later part of this post. In fact, statspanda.com will qualify for this category.

There is a fourth category where companies sell ready-to-use Dashborad softwares. They have pre-built charts and graphs but not limited to charting and graphs. One needs to customize, implement and host them on their own.

To start with, I will cover various chart types and some basics around their usage. I will also briefly touch upon the technologies used behind these charting libraries. Then I will move on to talk very briefly about some of the libraries I have explored closely. This will be followed by a list of companies who sell Charts and Graphs as service or as Dashboard software.  

Popular Chart Types (#1)

Line Chart
Spline Chart
Bar Chart
Pie Chart
Doughnut Chart
Area Chart
Bubble Chart
Scatter Plot
Bullet Chart
Gauge Chart
Combination Chart
Creative Visualization

Sample Charts generated using StatsPanda.com



Factors Behind Making a Choice (#2)

There are host of factors that may influence your choice of a particular type of chart or visualization. Here are few factors that I could compile 

Size of Data points - this is probably the most important factor behind making a choice. For example, a Pie Chart may not work very well if your data point is more than say 30 but Line Chart may still be good choice. Similarly, an Area Chart or Line chart may represent a very large set of data. However, remember number of data points also indicates whether it's a low level or high level data. Millions of raw data feeds may translate into couple of data points when aggregated by those factors.

Types of Data Points - Next, check if you are dealing with only one type of data or there multiple different types of data that need to be plotted. Often combination charts are used if data types are different or different set of data need to represented. Example - using a combination of Bar Chart & Line chart for representing revenue and profit numbers of one company viz-a-viz using multiple Line Charts for representing revenue numbers of different companies.

Relationship of Data Points - If multiple Data Types are being presented in a Combination Chart, then if the different types data are related or not also influence the choice of a Chart type.

Complexity Of Relationship - How the data sets are related matters in the selection of a chart. Complex relationships like many-to-many relations or multiple-relations between two data points are not easy represent in regular Charts & Graphs and calls for creative visualization.

Static vs Animation vs Flow Representation - Most of the Charts and Visualizations really capture a snapshot or static state of data. In certain cases you may need to show a transition from one snapshot of data to the other (i.e. animated) or capture the states that the data pass through (i.e. data flow). A good example is Sankey Chart.   

A general rule of thumb as per a paper from IBM

• Pie chart: 3-10
  
• Bar chart: fewer than 50
  
• Line chart: fewer than 500
  
• Bubble plot: fewer than 500
  
• Scatter plot: fewer than 10,000
• Creative Visualization comes handy for data points > 10,000  

Rendering Engines (#3)

SVG - Scalable Vector Graphics (SVG) is an XML-based vector image format for two-dimensional graphics with support for interactivity and animation. The SVG specification is an open standard developed by the World Wide Web Consortium (W3C) since 1999. Widely supported. Traditionally, MS-Internet Explorer has been a laggard but starting with IE 8 SVG is supported in IE. Some of the popular libraries like morris.js, D3.js and others built on top of D3.js use SVG.

Canvas (HTML5) - Introduced as part of HTML 5 spec. example: flot, chartjs, jqPlot and other Javascript based visualisation libraries.

VML - Vector Markup Language (VML) is an XML-based file format for two-dimensional vector graphics. Developed and promoted by Microsoft.

Chart Performance (#4)

Check out Charts performance at http://jsperf.com/charts-comparison-d3-js-kendo-highcharts-echart-flot-gr 


HTML5 Based Libraries (#5)

chartjs.org - Offers six chart types. HTML5 Canvas based, responsive. One of the best options for the chart types it supports.

canvasjs.com - Pretty good & rich collection of Charts. Free for non-commercial use.


D3.js & D3.js Based Libraries (#6)

d3.js is the best and gives highest amount of flexibility but that comes at the cost of added complexity in terms of programming skills while developing a chart or graph. If you want to avoid that, please refer to some of the libraries and that pretty straight to use.

NVD3 d3.js based charts library, has good options. Some of them are unique when compared to other generally available charts e.g. Scatter / Bubble Chart, Stacked Area Chart. Reads data from CSV and other text formats.

C3.js - Another D3.js based charting library. Pretty comprehensive set of charts, simple and easy to use, provides good documentation and available under The MIT License (MIT). C3.js has a pretty active Google Group, easy to get support.

Rickshaw built on top of d3.js. Very neat library for creating time series graphs, line chart, bar chart etc. It is free, open source and available under MIT License

http://d3pie.org - nice pie charts, offers good options. Available under The MIT License (MIT)

xCharts - D3.js based library. Uses HTML, CSS, SVG. Default charts have polished look but very limited options. It was developed by https://www.tenxer.com/ and has been made free with no strings attached.

dimplejs - it's crazy, it's very good. Reads data from CSV and other text formats. It's an open source project by http://align-alytics.com/

dc.js - It's amazing. Just look at this - http://dc-js.github.io/dc.js/ . It's available under Apache License, Version 2.0 (the "License")
Few cool examples - http://dc-js.github.io/dc.js/examples/cust.html

http://d3plus.org Built on top of d3.js, simple to use. It has limited set of examples/apis but some of them are pretty good e.g. Geo Map, Tree Map, Simple Network.

https://github.com/mbostock/d3/wiki/Gallery - d3 example library in one page.

http://bl.ocks.org/mbostock - Amazing Charts and Visualization examples by Mike Bostock, the creator of D3.js and many other libraries used for rich visualization.

http://bost.ocks.org/mike/ - Another repository by Mike Bostock.



Pure JavaScript (#7)

Flot Charts - Flot Charts are pure Javascript library. 

Google Charts - It has very rich set of charts & graphs, simple to use. You may like look at AngularJs Google Chart Tools directive as well.

jqPlot - Pure Javascript charting library.  Offers good set of options. Look and feel is not very polished. 

morris.js - raphael.js based library. Simple to use. Cool fluid look and feel. Limited options, most of the common scenarios are covered. Uses HTML, CSS, SVG

dygraphs - has good options for time series graphs but look and feel is not very polished. However, dygraphs can handle huge datasets running into millions of data points. It takes .txt and .csv file as inputs.


Mini Charting Libraries (#8)

Peity is a simple jquery.com plugin that converts an element's content into a simple mini pie line or bar chart.

jQuery Sparkline generates sparklines (small inline charts) directly in the browser using data supplied either inline in the HTML, or via javascript.

Commercial Offerings (#9)

This section covers a list of Charts and Graphs libraries. 

HighCharts - Offers very rich set of options. Probably one of the best libraries. Available free for non-commercial use, under Creative Commons License

Canvas JS - HTML5 JavaScript Charting Library with a simple API and 10x better performance compared SVG/Flash based charts. Charts are responsive & can run across devices including iPhone, Android, Desktops, etc. Offers good set of Charts and Graphs.

ZingChart - Javascript Charting library. Offers a rich set of options. Visually appealing and good for large data sets. 

JSChart - Javascript Charts. Limited options.

Ember Charts - Open source. Offers limited popular options of Charts, Tables etc.


Charts & Graphs as Service (#10)

statspanda.com : Offers creation and hosting of Charts, Graphs & Dashboards as Service. Purely REST Api driven, also provides a REST API Console.

tableau.com : Grand Daddy of Visualisation. Offers Desktop, Cloud based service as well as Back-end data integration. Has huge array of very creative Charts Graphs and Dashboards. 

datawrapper.de : Creation of embeddable Charts, Maps. Primarily used by publishing, news and media companies. 

chartio.com : Provides data integration layer with various sources like CSV, Amazon RedShift or Stripe etc. It then convert the data into intuitive Visualisation such as Charts, Graphs etc. 

chartblocks.com : Basic chart building tool. It reads the data from spreadsheet and gives tools to customise the cha. The charts can be shared in popular social media or can be embedded as iFrame. 

infogr.am : Create charts and infographics and publish them easily, primarily used by the news and media companies. 

jaspersoft.com : Create Charts, Graphs, Dashboard and embed or publish. Good integration with Amazon AWS (RDS, Redshift) . Owned by TIBCO. Focuses on Apps and On-prem Applications for embedding the Charts, Graphs and Dashboards created/hosted on their platform.

Amazon QuickSight : Works with AWS dataset to create visualisation. Offers good set of Graphs, Tables and other Visualisation. Amazon QuickSight uses a new, Super-fast, Parallel, In-memory Calculation Engine (“SPICE”) to perform advanced calculations and render visualizations rapidly. 

domo.com : Offers good set of connectors. Dashboards are designed for specific roles and for different industry verticals. Rich set of chart, graphs and other visualization are offered. Provides good integration with Amazon. 

gooddata.com : Primary positioning as Business Intelligence platform for real time analytics. Offers good set of charts, graphs and dashboard options. Has good set of Connectors.

keen.io : Keen IO is an API platform that lets developers collect and study custom events at a massive scale and converts them to visualisation. It's designed in a way so that users can embed the visualisation like Charts, Dashboards in their apps, websites. All popular Charts and Graphs are available for the Dashboards. 

chartbeat.com : Focused at Advertising and Publishing industries. Provides insights using Charts, Graphs and other visualisation.

vida.io : Create attractive visualisation, embed and use them, can create Dashboard. 

plot.ly : Plotly is the data visualization and collaboration platform for engineers and data scientists. Provides integration with Python, Excel, MATLAB & R. Offering available in three different formats - Cloud, On Prem, and Desktop Tool. 

zoomdata.com : Focused at Visualisation for Big Data, can handle large volume of data. Provides integration with Hadoop, NoSQL, ElasticSearch, Solr and Spark.

datahero.com : Provides connectors to a large array of Cloud Based data sources like Box, Dropbox, Stripe, Hubspot, MailChimp, Google Drive, Google Analytics, MixPanel etc. You can then convert the data to a Chart, Graph and other visualisation. You can create one dashboard composed of multiple Charts, Graphs from different Datasources. Have focused offerings for various industry verticals.

getdataseed.com : Provides data exploration tool sets that can import data from Excel Spreadsheet and from fetch Dropbox, Google Drive or any public url. Can convert the data into Charts, Graphs, Maps and other Visualisation. Provides REST Api integration. 

anaplan.com : Excel Spreadsheet on Cloud with ability to create crisp Charts, Graphs, Dashboards and other visualisation on the fly. Excel Spreadsheet like data is editable. Has focused offerings around Finance, Sales, Operations and HR.

collabion.com : Creates Charts, Graphs and Dashboards from SharePoint Data. Need to Downloaded and installed, need to Server Licenses.

www.domo.com : Offers good options of Charts, Graphs and other visualisation. Provides wide range of connectors for various datasources and Apps ranging from Excel, Google sheets, Box, Facebook, Marketo, Salesforce etc. Solutions are tailored for various roles, industry verticals and operations.

www.klipfolio.com : Offers creation of company Dashboards composed of cool Charts, Graphs and other visualisation. Provides a wide range of connectors to all major datasources and various options for data infusion. 

Microsoft Power BI : Available as Desktop Application and mobile Apps for iOS, Android and Windows Phones. Wide range of Charts, Graphs can be glued to a Dashboard quickly, supports drag and drop features. Provides wide range of Datasource connectors. Supports natural language query inside a Dashboard.

RJMetrics.com : Offers creation of Charts, Graphs and Dashboards on Cloud. Has good Data Integration with popular Datasources. RJMetrics Pipeline transfers the to Redshift. Good for large volume of Data - from less than 5 million rows to upside of 500 million rows sync up. 

http://kilometer.io : SaaS Analytics Tool

https://chartmogul.com : Subscription Analytics

gramener.com They are into creative visualization. Provides visualization of the data from various business operations like Sales, Marketing, HR etc. 

Finally, I still feel the blog looks like a work in progress. In fact, I would spend more time taking a deeper look into all the companies listed under #10. However, I hope you found the post useful even in current shape and form.

How to Add Charts, Graphs and Visualization to a Blog Post

Over last few months, I have written few blog posts where I used pretty sophisticated Charts, Graphs and Visualization. They make the blog post lot more meaningful and readable, readers love those charts, tables & displays. In this post, I will share the service I use for those visuals and few quick steps on how to create a chart and add that to your blog.

I use the services of http://www.StatsPanda.com, it's in public beta and it's free for "Individual" users.

StatsPanda.com Home Page

Once you login using your Facebook account, it redirects to registration page and during registration it gives two options - "Individual" and "Enterprise". Choose "Individual".

Go to API Console. I will suggest that you spend some time exploring the listed Visualization APIs. You may have to spend some time trying out the APIs in order to understand the JSON Inputs structures. It's not super complicated, although it may take some time. Initially you can use the example input data provided along with API Documentation.

API Console to create Charts, Graphs etc

Once decided, go ahead and create the Chart of your choice and that would give you a unique url and iFrame Code for your chart. For this blog I created a Stacked Area Chart with the example data that API Console provided. In the above screenshot, you can see a greyed out box right below the chart. The content of that box is copied below for your reference. You can straight away use that in your blog.

<iframe src="http://www.statspanda.com/charts/ui/nvd3/stacked-area-chart?unique_key=dc27b99e933da8969218fb3d8e06aeafdc61e170dad7c5aed1b5d41381b2d8" style="border: #E8E8E8 1px solid; height: 300px; width: 100%;"></iframe>

Here is an example how the Visualisation really appears in a blog once you include the iFrame code snippet to your blog.



The chart is dynamic and not a jpg pic, data is being served from the Website. In fact, if you want you can "Edit" the input JSON Data and have a different chart of same type.

Hopefully you find it useful and able to use the charts and graphs in your blogs.