Monthly Archives: September 2012

How to Use Bitly

There comes a time where you have the most legit Tweet you could possibly imagine. Everything’s perfect; it’s catchy, easy to read, funny, and within the 140 character limit. However, you want to post the URL to that picture, but it would put you over the character limit. Enter, Bitly. This is how to use bitly.

How Does Bitly Work?

Bit.ly uses what’s called a 301 redirect. It’s the most efficient method for redirection. A great explanation of how redirects work was found at StackOverFlow. User, Abel, described the process as so:

No, they don’t use files. When you click on a [shortened] link, an HTTP request is sent to there server with the full URL, like http://bit.ly/duSk8wK (not a real one). They read the path part (here duSk8wK), which maps to their database. In the database, they find a description (sometimes), your name (sometimes) and the real URL. Then they issue a redirect, which is a HTTP 301 response and the target URL in the header.

This direct redirect is important. If you were to use files or first load HTML and then redirect, the browser would add TinyUrl to the history, which is not what you want. Also, the site that is redirected to, will see that referrer (the site that you originally come from) as being the site the TinyUrl link is on (i.e., twitter.com, or your own site, wherever the link is). This is just as important, so that site owners can see where people are coming from. This too, would not work if a page gets loaded that redirects.

How to Shorten a Link with Bitly

After signing up with Bit.ly, you should be redirected to your home dashboard. In the upper right, you’ll see a text field that looks like this:

how to use bitly

For manual link shortening, simply paste the original link in the text field and press enter. You will then be displayed the new bit.ly link, that can then be used for Twitter, Facebook, shits n giggles, etc.

WordPress–>Bit.ly–>Twitter

If you’re looking to promote your blog on Twitter, and want to do so automatically every time you publish a post, the following is for you:

  1. Go to your WordPress plugin page. Add new. Search for “WP to Twitter”. Install and activate. 
  2. (I’ll save configuration of other options for another post)
  3. If you scroll down, you’ll see a two input fields for Bit.ly’s services
Bitly options -- WP to Twitter

 

 

 

 

4. Go back to Bitly and your dashboard. Click your username at the top right, click Settings, then Advanced.

5. At the bottom, you’ll see “Legacy API Key”. I did it a while ago so I’m not sure what it says originally, but you’ll be pressing something like “Get my Key” or “Authorize”.

6. Once you have your API Key, you simply copy and paste it into the WP to Twitter config page and you’re done! Tweet away…

 

 

How to Analyze Data Using Microsoft Excel

For any profession, the ability to analyze data using Microsoft Excel is essential.

In this post I’ll show you how I was able to look at the Olympic Gold Medal winners (by country), but rank them according to their population or GDP. You’ll be surprised to see the new angle of this.

Now I’ll outline exactly how I did this, because this type of analysis is not beyond the average Excel user.

First I had to accumulate my data sources. Wikipedia is always a good place to start. I did a simple Google search for ‘country medals 2012’, ‘country population’ and ‘country gdp’. Pretty simple, huh? For more difficult searching, check out this article on how to optimize your Google searching. 

I found my 3 lists, with the country names (highlighted in red) being the common denominator across each list. Simply copy paste into Excel, with one list next to the other. This will help me consolidate into a single list later on. This is also why I find Wikipedia useful – because most of their lists follow a similar format and thus you don’t have to tweak the data as much.

 

The next step is to create a single list, although before we get there we need to make sure our common denominator (country) is identical across each list. It’s difficult to tell in this frame, but each country in the Population and GDP list has a space before the country. This simple thing would prevent your lists from consolidating correctly.

To fix it, we’ll use a formula to delete the first character of these cells. Before that, let’s create a bunch of new columns so that we’re all set to build out our analysis.

Notice I expanded the first list to include 2 columns – one for population and one for GDP. Later we’ll use a vlookup formula to pull in the values from the other lists.

To delete the first character in the country cells (for the Population and GDP lists), we’ll use the MID formula, which returns the characters from the middle of a text string, given a starting position and length. We’ll also include the LEN formula, which returns the number of characters in a text string. Enter this in J3:

=MID(L3,2,LEN(L3))

L3 is in the Population list, and it’s the first country listed (” China”). By declaring L3 and then the number 2, we are telling the formula to start in L3, and within L3 to look at the number 2 character. In this case the number 1 character is the blank space, so it will start at “C”. The third part of the MID formula is for the number of characters you want to return (starting at the 2nd character, how many MORE do you want to return). By using LEN, we are telling the formula to return however many characters are actually in the text string ” China”, starting at the 2nd character (“C”). Try this out for the GDP countries as well, and drag the formulas down.

Now that we have a common denominator of country names across all 3 lists, we’ll use vlookup to pull in values for Population and GDP into the first list. Enter this in G3:

=VLOOKUP(B3, $J3:$P244, 4, 0)

What vlookup does is use a lookup value (in this case, B3, which is “United States”) to scan through other lists (Population or GDP lists) and then return a corresponding value (actual population or actual GDP). So what we are asking Excel to do here is look up B3 (“United States”) in the table array $J3:$P244 (entire list for Population). Note here that the first column of your table array (J) needs to be the column that contains your common denominator (country name “United States”). Also note the dollar signs in the array – this is simply to refer to a static table array, rather than shifting the table downwards as you drag your formula down.

Once it finds it (happens to be in J5), we have told the formula to retrieve the 4th column value (which, starting at column J, is returning column M “Population”). The last part of vlookup is rarely used and so I won’t bother to explain. Just put in the number zero. Now, in G3 you should hopefully return this value: 314,168,000. Drag it down and now try to apply the same formula to column H for GDP.

Here’s a snapshot of where we’re at now:

Hopefully you noticed some errors in columns G and H, in the form of “#N/A”. This is common in data analysis, and requires a little manual intervention. If you look at H4, you’ll see this error for the GDP value for China. This is explained by the fact that China is listed as ‘China, People’s Republic’ in the GDP list. Again, this is normal when doing analysis, and there’s no easy way around it for some situations. So what we need to do is filter columns G and H for the “#N/A” values and identify where the issue comes from. Most should be explanatory (another example is G5 and H5 for “Great Britain”, which is listed as “United Kingdom” the other lists).

To further our analysis, we want to compare our 3 lists to one another by using our extended list. We’ll create 4 additional columns.

  1. Gold Medals per Capita
  2. Total Medals per Capita
  3. Price per Gold Medal
  4. Price per Medal

The formulas for these columns will be simple: either Population divided by Gold/Total Medals, or GDP divided by Gold/Total Medals.

Your values should look like this:

If we highlight our country column, and highlight the Gold Medals per Capita column, we can create a helpful scatter plot to illustrate some data analysis. Once you’ve highlighted, go to Insert > Scatter. At this point you should have a graph like the one below, which shows how some countries (ie: Lithuania), although small, performed extremely well considering their actual population. You can create a similar graph for the other columns we created, but for purposes of this post I only explain this one.

To crunch a few numbers, Lithuania secured a gold medal for about every 2 million people who live there. If the USA had that type of efficiency, it’d take home over 150 golds as opposed to 46. China by comparison would take home 637 golds!

Please contact me for specific questions or comments about this.

GoDaddy Coupon Codes

I wanted to write a quick post about something that’s helped me a lot in my internet endeavors. So if you’re like me, you purchase domain names. And if you’re like me, you use GoDaddy, despite their awful commercials. Regardless, there are a couple sites out there with pretty legit GoDaddy coupon codes. Here’s my list of the best:

  1. GoDaddy Coupon Codes
    — OK, so not the most aesthetically pleasing blogs. Shit, it ain’t Selfware. But, notwithstanding their sloppy design and upkeep, they do seem to stay very well updated on the latest GoDaddy Coupon Codes.
  2. GoDaddy Coupon Codes
    — A little more professional, more intuitive. Neat stats like average discount and also pretty decent social functions. Though, nothing quite says you’re cheap like a Facebook status of “JUST SAVED $0.30 on a 6.99 domain name!!! LOLZ”
  3. GoDaddy Coupon Codes
    — This site is if there’s a nuclear holocaust and all servers are down except this one. Still has some relatively updated codes, but use the first two if you’re serious about saving.

How to Enter GoDaddy Coupon Codes

Once you’ve browsed GoDaddy’s site and have found the domain you want. Simply click “Register” to begin the process. There should be about 4-5 steps, most all of them horse-pucky up-selling. If you manage to make it to the final checkout page, hold on for a second. You should see this in the middle-right of the page:
GoDaddy Coupon Code Checkout
Make sure you click “Enter Promo or Source Code” before you checkout. Simply copy/paste, and hit apply. You’ve officially saved marginal money.

“Is there an American male left who still goes to GoDaddy.com expecting to see a half-naked Danica Patrick? In a world filled with so much free Internet porn, why should we even care?” –Courtesy of San Francisco Chronicle

How to Setup Google Analytics

To setup Google Analytics, you first need your web site up and running. Check our quick guide for this, and also make sure you’ve got the Google Analytics for WordPress plugin installed.

Courtesy of Google Analytics

Also, if you haven’t signed up for a Google Account, do this now. There are too many weapons Google provides you, and they’re all for free and have a plethora of user documentation and tips.

Assuming you’ve logged into the homepage for Google Analytics, click on the Admin tab at the top right of your screen, which should take you to the Account Administration screen.

From here, click ‘+ New Account’ and proceed to enter basic details like the Name (nickname) for your account, and the URL. Once you click ‘Create Account’ you’ll be dropped off on a screen that has your Google Analytics ID (GAID), and some instructions on how to install it. At this point the ‘Tracking Status’ should say ‘Tracking Not Installed‘.

Yoast – our top recommendation for SEO plugins

Our suggestion is to use the Google Analytics for WordPress (by Yoast) plugin for your site to do this. Pull your GAID and then proceed into your WP Admin site and install the plugin if you don’t already have it. Once you install you’ll be asked to ‘select which Analytics profile to track’. Click ‘click here to authenticate with Google‘ and choose the correct email address.

Now you can select a drop down value for the correct profile (this is the Nickname you created in Google Analytics), and the corresponding GAID will populate in the next dropdown.

Or you can select a Manual entry and copy paste the GAID.

It takes up to 24 hours for Google to begin collecting data for your site, and it’s usually quicker. Let the analysis begin!

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