How to add secondary axis in a chart in Excel 2010?

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In this post, I’ll show you how you can add secondary axis in a chart in Excel 2010:

First up, Why do you need secondary axis?

Look at the Data and the chart that I just created:

creating a chart from Data excel 2010

Notice something? Column A is not “visible” – Is it? So Now let’s see the effect how adding a Secondary Axes:

secondary axis in a chart in excel 2010

Looks better? Here are the steps:

1. Select the chart

2. can you see charts tool options in the menu bar? Yes? Great!

3. Switch to Format Tab

4. select the column that you want to put on a secondary axes:

select column in format area data excel chart

5. After selecting the column, click on Format Selection

6. In the dialog box, select secondary axes:

secondary axis excel 2010 chartclick on close.

7. Can you see the secondary axis now? Great!

secondary axis in a chart in excel 2010

8. Let’s do one more thing!

Let’s change the chart type of the secondary axis. Here are the steps:

a. Make sure the column is selected from the format Tab

b. Switch to the Design Tab under the charts Tool

c. Click on change chart type and select the chart of your choice. I select a column chart and this is how it looks:

more than one chart type on a single chart in excel 2010

Conclusion:

In this post, we saw how to add a secondary axis. We also saw how to change the chart type of the secondary axis.

Received President’s Volunteer Service Award!

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Received President’s volunteer service award for year 2012!

Letter from US president Barack Obama:

letter from Barack Obama presidents volunteer service award

Label Pin:

label pin president's volunteer service award copy

Certificate:

certificate presidents volunteer service award copy

Related Notes:

– Check out Give Camp – It’s a great way for IT professionals to give back to society. If you do not a give camp in your country, you can always start one 🙂

Met revered APJ Abdul Kalam

Google Analytics: How to Track an email campaign?

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In this post, I’ll share how I learned to track an email campaign via Google Analytics.

First up, what do I mean by email campaign?

let’s say you email 1000 newsletter subscribers a link (URL) along w/ a summary – How do you track the traffic that is generated via this email campaign? Well – that’s where Google analytics can help you track your email campaigns. One metric would be how may people clicked on that link and visited your site.

Why should I care?

“If you can’t measure it, you can’t manage it” – Peter Drucker

If you do not measure what’s working or what’s not working, then you can’t improve – can you? Let’s take a hypothetical example. supposing it’s cost you $25 dollars to email 1000 people. How do you calculate the ROI on it? Well – track it! And the tool you can consider using is Google Analytics.

Now, Here are the steps to track an email campaign via Google Analytics:

Here’s the visual:

google analytics track email campaign

Here are the steps:

1. First Step is to create an URL.

Why do you need this? Basically this URL would have “meta data” that helps Google Analytics identify this link belongs to one of the campaigns.

How do we create it? Use this web service: http://support.google.com/analytics/bin/answer.py?hl=en&answer=1033867 to create an URL:

This is how an URL that I created looks: http://parasdoshiblog.blogspot.com/?utm_source=newsletter&utm_medium=email&utm_campaign=UTDEmailCampaign

google URL builder google analytics

2. Create an advanced segment in Google Analytics:

> Open Google Analytics.

> Select your site

> you should be in the audience overview report

> From here, click on advanced segment and click on new custom segment

google analytics advance segments> Here I’ve configured it like shown in the image below. Note the name of the campaign is same as the name of the campaign in STEP 1.

email campaign track google analytics> Save segment

> next time you visit, you’ll see this custom segment – select it and you’ll see only from the campaign that you want to track:

google analytics custom segments traffic

That’s about it for this post. your comments are very welcome!

What’s “Naive” about Naive Bayes Machine Learning Algorithm?

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In this post, I’ll post what why does the “Naive Bayes machine learning” algo have the word Naive in it?

So here is the short answer:

It “assumes” that the features are independent. (In other words: There’s no relation between the features that are used while building the model)

Let’s go a little deeper:

First up, few basic pointers.

> It’s a machine learning algorithm used for classification

> It’s based on Bayesian Statistics.

> you can read about it here: http://en.wikipedia.org/wiki/Naive_Bayes_classifier

Now, what do you mean when you mean that it is Naive because it assumes that features are independent?

Let’s take an example:

Suppose, you are building a “credit card approval” model based on Income and CreditScore

(SideNote: For those who do not know what is credit score, here you go: http://en.wikipedia.org/wiki/Credit_score_in_the_United_States)

And you have the following columns in the training data (Note: In machine learning, think of this columns as features)

IncomeCreditScoreApproved
HighHighYes
HighMediumYes
LowHighYes
LowLowNO

Here the features are Income & CreditScore and the target of the classification model is Approved.

In real world, there’s some relation between “income” and “creditscore”. Agree? Great! But Naive Bayes doesn’t think so. Let me reiterate the point of this blog post and see if it makes more sense now: it assumes that the features are “independent” and that’s why it is Naive!

I hope this helps. your comments are very welcome!

Recapping my social media activities during Jan 1 – Feb 24 2013:

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Recapping my social media activities during Jan 1 – Feb 20 2013:

  • Interesting resource covering topics Opinion Mining, Sentiment Analysis, and Opinion Spam Detection: http://bit.ly/NGlNYD
  • SQL Server Technical Article: Leveraging a Hadoop cluster from SQL Server Integration Services (SSIS) http://bit.ly/13aZWhx
  • querying Hive using SQL-like commands: http://on.fb.me/TDQujY
  • [Resource] Getting Started with Microsoft HDInsight http://bit.ly/Wru0zv #Hadoop #Microsoft
  • Reading: “Next Generation Data Warehouse Platforms: #TDWI 2009 Q4 Best Practices Report”; Interesting stats on the total data volume that organizations manage: http://on.fb.me/ZnQ0O1
  • Presentation Tips: When you move, they look at you. When you stop, they look at the screen – http://bit.ly/uQ5Amf
  • “In pioneer days they used oxen for heavy pulling, and when one ox couldn’t budge a log, they didn’t try to grow a larger ox. We shouldn’t be trying for bigger computers, but for more systems of computers”
    – Grace Hopper
  • Download Slides about Dr Dewitt’s PASS Talks [2008-2011] http://bit.ly/XrD2xa
  • WOW! Nice data visualization: interactive map Foursquare published last week? Check out Dallas: http://4sq.com/W3EIjo
  • [resource] Great answer on Quora on What is random forests? http://b.qr.ae/UErw4f
  • The marketing landscape has truly changed! Nice slide deck: http://slidesha.re/WGp3aj http://on.fb.me/VvZLs0
  • Learning about Google Analytics in Web Analytic’s course: http://on.fb.me/Uq8i4Z
  • World heat map showing Network Readiness Index 2012: http://bit.ly/12w5aqK http://on.fb.me/WPsvAf
  • Does High Speed Broadband Increase Economic Growth? Here’s the URL, consider thinking about it before reading it: http://onforb.es/OldnpW
  • Exploring Weka, a popular machine learning tool. http://on.fb.me/WXLsAM

That’s about it for this post.

If we want to read related past posts, here they are:

OCT 3 – OCT 10 2012

OCT 11 – OCT 18 2012

OCT 19 – NOV 11 2012

NOV 12 – DEC 31 2012

Let’s connect and converse on any of these people networks!

paras doshi blog on facebookparas doshi twitter paras doshi google plus paras doshi linkedin

Resource: 12 recorded sessions from the 24hop business analytics edition are online! #passbac #msbi

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Recently, PASS hosted a 24hop business analytics event:

And now, the 12 one hour sessions ranging from data visualization, predictive analytics to Big Data are online for you to watch! They also serve as “Trailer” for what you can expect at the PASS Business Analytics conference!

Here’s the URL: http://passbaconference.com/Sessions/SneakPeeks.aspx

And I was following some of these sessions live on the event day – and I can tell you, these sessions are great resources!

Also, I participated in the twitter contest (by Microsoft BI) that was happening along w/ the event – and this is what I got for my win!

24 hop twitter contest prize

hoodie w/ embedded earphones!

That’s about it for this post. Enjoy the recordings!

Sentiment Analysis using LingPipe on windows 7:

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In this post, I’ll point you to the resource using which you can perform sentiment analysis using LingPipe on a windows OS. Along with that I’ll share couple of issues that I ran into when I was trying to run this demo on a Windows 7:

So first up, here’s the resource:

http://alias-i.com/lingpipe/demos/tutorial/sentiment/read-me.html

Now here are a couple of issues that I had:

1. Error: could not find or load the main class PolarityBasic

lingpipe could not find or load main class polaritybasic

To solve this error, you’ll need to build the files given under the C:lingpipe-4.1.0demostutorialsentiment – we use ANT for this. Let’s see how to do that:

2. Building sentiment.jar using ant jar

After successfully downloading ant on windows and setting the ANT_HOME variable to c:apache-ant-1.8.4 – I was still getting the error that ant is not a recognized command.

So I ran following commands:

C:>set ANT_HOME=C:apache-ant-1.8.1
C:>set JAVA_HOME=C:jdk1.6.0_24
C:>set PATH=%ANT_HOME%bin;%JAVA_HOME%bin
C:>ant -version
// it worked!

Thanks: http://stackoverflow.com/questions/5607664/installing-ant-ant-home-is-set-incorrectly-on-windows-7

Now I ran the following command:

build sentiment.jar ant lingpipe

3. In the tutorial they used POLARITY_DIR – I didn’t use that, Instead I just inputted c:review_polarity because that’s where I unzipped the movie review dataset:

movie review sentiment analysis polarity

Here’s the screenshot about the command that does basic polarity analysis:

sentiment analysis lingpipe windows

And Thanks: http://stackoverflow.com/questions/15010184/lingpipe-and-sentiment-analysis/15011482

Steps to Install Weka on desktop running windows OS:

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Weka is a popular free open source machine learning tool. In this post, I’ll note the steps that I took to install it on windows machine:

1. Search “Download Weka”. As of today, the URL is http://www.cs.waikato.ac.nz/ml/weka/downloading.html

2. Now, it’ll have options to download the Weka. Here, based on your

– Machine configuration (x86 vs x64)

– Java version and the corresponding Weka version

So let’s check that:

3. To check the Java version installed on your computer, open up command prompt and type Java -version

weka install machine learning windowsNote that I’ve java version 1.7

let’s see if it’s compatible w/ the weka version:

weka java version

As you can see, the version of weka that I’ll be installing requires Java 1.7 and I already have that – so for now my machine, I selected the option:

Click here to download a self-extracting executable without the Java VM

Also remember to check the operation system type (x86 vs x64) and download the corresponding version of weka.

4. After downloading, install it. I left all the options default.

5. After successful installation, I launched weka by going to:

start > all programs > weka 3.6.9 > weka 3.6.9

weka gui chooser machine learning

That’s about it for this post.

Found something interesting by exploring a “List of companies by revenue” Data Set:

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I like exploring data sets to find interesting patterns from them. To that end, I was exploring a data-set: List of companies by revenue and I added a column to calculate Revenue/Employee to explore the dataset:

And I found an outlier!

Here’s the outlier: Exor

Here’s what it’s interesting:

It’s revenue in 2012 is: 109.15 billion USD

And number of employees is just 40!

Just think of Revenue/Employee !

To put things in perspective, Lets Compare that with its neighbor in the data-set:

Rank | Company | Industry | Revenue in USD billion | Employees

48Koch IndustriesConglomerate110.0060000.00
49EXORInvestment109.1540.00
50Cardinal HealthPharmaceuticals107.5540000.00
51CVS CaremarkRetail107.10202000.00
52IBMComputer services106.92433362.00

I got to know about this by quickly creating a data visualization to explore the data-set:

list of companies by revenue

And removing Trafigura, Vitol and Exor, this is what we have:

power view excel 2013 rank revenue employees

Observation: oil and gas industry have relatively higher revenue/employee ration.

That’s about it for this post. Thanks for reading about my data exploration!

My First Five Toastmaster International club speeches:

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In this post, I want to share the title of the first five Toastmaster speeches that I delivered over the past few months:

1. Ice Breaker

2. Glossophobia (Fear of Public Speaking)

3. Get ready to outsource your computing

4. What’s it like for folks who live below poverty line?

5. what’s it like to start a startup?

Related Post:
Half way through Toastmaster’s competent communicator manual
Want to practice public speaking? Join Toastmaster’s!