Microsoft Excel personal macro workbook.


Personal Macro Excel Workbook

          We have already explored different Excel VBA macros here, here, and here, . While the power of Excel VBA is limited only by our creative imagination, the real limitation of a typical VBA code comes from the fact that it resides in the workbook where it was saved, and as such, can only be revoked while this file is open. This is where the personal macro workbook comes into play: if we save our code in this centralized place, we could use it in any Excel workbook on our local drive. This productivity hack would help us perform repetitive tasks (formatting and data presentation pet peeves, anyone) by automating them. The easiest way to save your code into PERSONAL.XLSB workbook is through recording a macro.

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Working with sample datasets in BigQuery

Working with sample datasets in BigQuery

          In the previous post we added public tables to our BigQuery interface. However, Google already provides sample data on various topics by default. While most of these tables are not updated, they still present some interest in terms of learning trends or insights on a multitude of topics. We will focus on 3 of these tables:
Natality (daily US births from 1969 to 2008),
GSOD (daily weather information by a station number from 1929 to 2009),
and Shakespeare (word index of Shakespeare’s works.)

          Let’s start our exploration with the Natality dataset. The graph above charts share of teenager births, comparing to grand total by year. Between 1969, nominal number of births by teenagers went up from 307,561 to 441,110. However, this is not necessarily a bad news, considering growing US population. While in 1973, almost every fifth birth (19.55%) was by a teenager mother, by 2005 this ratio dropped to every 10th birth (10.18%.) To pull relevant source data, we simply need to run the following query (which would incidentally retrieve preteen births as well [outliers representing fewer than 200 births a year.]):
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Getting started with Google BigQuery and GDELT Project

Getting started with Google BigQuery and GDELT

          Once upon the time, the new kid on the block left more established search engines in the dust, then, after reinventing web-based email service, Google introduced its Apps. Today, let’s talk about one of the myriad services Google offers to us: BigQuery. Basically, this cloud-based service allows us to utilize Google’s hardware to store our own datasets or access public data on the go. Google provides API for Java, PHP, and Python access. In addition, various third-party tools now connect directly to BigQuery: Tableau, R, JasperSoft, and Simba to name a few. We get a 1 TB monthly usage quota to query BigQuery’s data for free. Some of the downsides of this service include: premiums for storing our own data and querying in excess of the free quota. We are also limited with data manipulation tasks we can perform in BigQuery; in fact, we can only append records to our table, we cannot update or delete them. Finally, this service uses a SQL language dialect, which lacks some of the SQL commands we are accustomed to: DISTINCT comes to mind, or resort us to some convoluted workarounds (try using the TOP command.) Meet, the GDELT Project – “the largest, most comprehensive, and highest resolution open database of human society ever created.” In this tutorial, we will learn some interesting facts about different countries, using GDELT data in BigQuery.

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Coding your first JavaScript application – BMI Calculator.

Error: BMI Calculator could not be displayed, please upgrade your browser.

         We already created a BMI (Body Mass Index) Calculator using Excel VBA last month. How difficult would it be to rewrite that calculator in JavaScript to embed it on any webpage for people to use? Not that difficult , thought I, remembering happy days of browsing the original, NOT corporate owned, HTML Goodies website in search of the coolest JS mouse-over effects, some 15 years ago. You can see the working calculator above of this post, but I would be lying saying that its creation was painless. Surely, “World’s Largest Web Development Site” provides more than enough reference material for all elements required: HTML and JavaScript, as well as optional, but handy styling language – CSS. However, tweaking my code and making it work, was a very time-consuming process. Looking at my final product and comparing it to top 10 Google search results for BMI Calculator makes it all worthwhile…. Not only it incorporates more enjoyable design, it is also equipped with error handling logic.
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