DataSet

Exploring, filtering and shaping web-based public data using Data Explorer Excel add-in:

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Data Explorer let’s you “Explore” (search) for web-based public data. This is a great way to combine data that you may have in your data-sources with public data sources for data analysis purposes. Sometimes your data might not tell you the reason behind the observed trends, so when that happens – you can try to see if a public data-set might give you the much-needed context. Let me give you an Example before we start hands-on w/ data explorer so that you have better understanding of importance of public datasets. Here’s a sample that I found here. So, Here’s a demo:

An auto company is seeing sales trends of Hybrid cars and SUV’s from the sales data-sources. But what is the reason behind that? company data does not show that. Someone hypothesizes that it might be because of gas prices. So they test out the hypothesis by combining gas prices information available via public data. And turns out gas prices might be the driving force of sales trends! SEE:

if the gas prices increase, then the sale of SUV go down and the sale of Hybrids go up:

data analysis combine data with public datasets

You know that public data can be helpful! So how can you search for public data-sets? Well, You can manually search online, ask someone, browse through public data repositories like azure data market (and other data markets), there’s also a public data search engine! OR you can directly search for them via Data Explorer.

Here are the steps:

1) Excel 2010/2013 > Data Explorer Tab > Online Search > type “Tallest Buildings”

excel public data search data explorer2) I selected one of the data-sets that said “Tallest completed building…. ”

excel data from internet

3) Now let’s do some filtering and shaping. Here are the requirements:

– Hide columns: Image, notes & key

– clean columns that has heights data

– Show only city name in location

OK, let’s get to this one by one!

4) Hiding Columns:

Click on Filter & Shape button from the Query Settings:

excel data shaping cleaning

Select Image Column > Right Click > Hide:

excel hide remove columns

Repeat the steps for notes & key column.

Click on DONE

5) clean column that has heights data.

Click on Filter & Shape to open the query editor

A) let’s rename it. Select column > Right Click > Rename to Height > press ENTER

B) let’s remove the values in brackets. Select Column > right click > split column > By delimiter > At each occurrence of the delimiter > Custom and enter “(” > OK

excel split a columnThis should transform the data like this:

excel data explorer split a column

Hide height.2 and rename the height.1 to height

Click on DONE

6) Let’s just have city names in the location column

click on Filter & shape to load query editor:

A) select location > right click > split column > by delimiter > Custom – Enter: ° in the text box like this:

an excel split by delimiter dataclick on OK

Hide Location.2, Location.3, Location.4 & Location.5

Select Location.1 > Right Click > Split Column > by Number of characters > Number of characters: 2 > Once, as far right as possible > OK

cleaning data in excel shaping filtering

Hide Location.1.2 and rename Location.1.1 to Location

One last thing! making sure that the data type of height is numbers.

Select height > change type > number

Also,

Select floors > change type > number

click on DONE. Here’s our filtered and shaped data!

filter data excel shape clean

7) LET”S VISUALIZE IT!

For the purpose of visualization I copied first 20 rows to a separate excel sheet and created a chart:

z excel data visualization

That’s about it for this post. Here are some related Posts on Data Explorer:
Unpivoting data using the data explorer preview for Excel 2010/2013
Merging/Joining datasets in Excel using Data Explorer add-in
Remove Duplicates in Excel Tables using Data Explorer Add-in
Web Scraping Tables using Excel add-in Data Explorer preview:

Your comments are very welcome!

How conditionally formatting your data in Excel can help you save time in answering business questions?

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Visual analytics is amazing – it helps “data enthusiasts” save time in answering questions using Data. Let’s see one such example. For the purpose of the blog post, I am going to show how to do it in Excel 2010:

Problem:

Here’s the Business Question: What was sales of Tea in North Region in 2012 Q1

Here’s the data:

SALES DATA(2012 Q1) EastWestCentralNorthSouth
Coffee $  7,348.00 $  7,238.00 $  1,543.00 $  9,837.00 $    1,823.00
Tea $  9,572.00 $  8,235.00 $  3,057.00 $  8,934.00 $  13,814.00
Herbal Tea $  5,782.00 $  8,941.00 $  9,235.00 $     392.00 $    1,268.00
Espresso $  9,012.00 $  2,590.00 $  4,289.00 $  7,848.00 $       340.00

So it’s easy to give out answer using the data: $8934

But let me CHANGE the business question:

WHICH Products in WHAT regions are doing the best?

Now this questions is not as easy as the previous one? WHY? because you’ll have to manually go through each number in a linear fashion to answer the question. Now imagine a bigger data-set. It’ll take even more time.

Solution

What can Excel Power users and Data Enthusiasts do to answer the new business question in an efficient way? Well, let’s see what conditional formatting can do it:

Excel Visual Analytics Conditional formatting

Now with the Data Bars, it’s easier to just glance at the report and see best performing products and regions. For instance, it’s very easy to spot that Tea is performing best in South among all products and region.

So how do you create data bars?

1. Select the data

2. Home > Conditional Formatting > Data Bars

Excel Visual Analytics Conditional formatting 2

3.Done! you’ll see this:

Excel Visual Analytics Conditional formatting

4. You can play with other options here to see what suits the best for your needs. But I just wanted to point out that there is a way for you to highlight the data in a way that helps you save time in answering business questions using data

Conclusion:

Visual analytics is a great way to quickly analyze data. In most cases, Human brain is much faster at interpreting the visual results as oppose to text/numbers – so why not use it to your advantage. And tools like Excel have inbuilt functionality to help you do that!

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Unpivoting data using the data explorer preview for Excel 2010/2013:

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Introduction:

Data Explorer add-in is amazing! It’s helps you: combine, find and re-shape your data in Excel 2010/2013. I’ve blogged about: 1) How to merge Table Data and 2) How to clean duplicate data and now in this blog post, I want to share a step-by-step on Unpivoting data using the Data Explorer add-in.

Before we begin, If you haven’t downloaded and installed the data explorer add-in for Excel 2010 & 2013, you can find Information about it here: http://office.microsoft.com/en-us/excel/download-data-explorer-for-excel-FX104018616.aspx 

Problem:

What is un-pivoting? I hear you ask. Instead of explaining it, let me share an Image:

data explorer unpivot excel

BTW, the above data is from my Facebook Page Insights.

So our problem statement is (please refer to above Image): we are given table blue and we need to output table green. In other words, we need to Unpivot the data.

Solution:

Here are the steps:

1) Open Excel, Open Data Explorer add-in. And Connect to your data. Wait when you see the Query Editor.

2) (Optional) In the Query Editor, Rename the query. I renamed it to “Unpivot Data”. And this how my query editor looks:

data explorer unpivot excel 2

3) Now, Select the columns that need to be unpivoted > Right Click > Unpivot Column

Note that I’ve selected all columns that I want to UnPivot:

data explorer unpivot excel 3

4) You’ll see the updated results in the query editor window. I renamed the columns “Attribute” to “Age and Gender” and “value” to “reach”. If you want to rename the columns, select the column > Right click > rename.

data explorer unpivot excel 4

If everything looks OK, click on Done in the bottom right corner

5) There you have it, Unpivoted data in Excel 2010/2013 using Data Explorer add-in!

And then its super easy to create charts, Here’s one I created after I had unpivoted the data:

data explorer unpivot excel 5

Insight: For my blog, my Target Audience seems to Male between the age of 18-24 and then 25-34.

FYI: The Date Range of the Data Set of 1st Jan 2013 – 25th Apr 2013.

That’s about it for this post, Here are some Related articles:

Your comments are very welcome!

 

Merging/Joining datasets in Excel using Data Explorer add-in

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Problem:

Merging/Joining/Combining data-sets in Excel has not been an easy task. There are third-party add-ins that makes it easy but out of the box, excel didn’t have an easy way to merge/join table data. But now with the Data Explorer add-in, we have an add-in that let’s us merge/join data in excel w/ few clicks.

If you haven’t downloaded and installed the data explorer add-in for Excel 2010 & 2013, you can find Information about it here: http://office.microsoft.com/en-us/excel/download-data-explorer-for-excel-FX104018616.aspx 

Situation:

Input is Table 1 & Table 2. The output we need is merged Table.

Table 1:

DateDaily New numberMonth
1/1/201201
1/2/201201
1/3/201201
1/4/201201
1/5/201201
1/6/201201
1/7/201201
1/8/201201
1/9/201201

………………………………..

Table 2:

MonthMonth Name
1January
2February
3March
4April
5May
6June
7July

Merged Table:

DateDaily New numberMonthMonth Name
1/1/201201January
1/2/201201January
1/3/201201January
1/4/201201January
1/5/201201January
1/6/201201January
1/7/201201January
1/8/201201January
1/9/201201January

………………………………

Solution:

Let’s see how data explorer can help us Join/Merge Table 1 & Table 2.

1) create query that connects to Table 1 & Table 2.

data sources explorer excel

2) Once you have queries that connect to the tables need to be merged, then click on Merge

3) Once you click on Merge, you’ll see a dialog:

Here you need to configure three things:

a) First Table

b) Second Table

c) Columns that will be used to merge/join data

In this case, this is how my merge dialog looks:

merge join excel data explorer

4) Once configured correctly, click on OK. You’ll see a dialog box where you can configure the output of the merged table. click on the new column to see the options that are available to you to configure the output of the merged table:

merge join excel data explorer 2

5) In this case, I’ve selected just one column month name that needs to be merged. You can also explore the aggregate tab in case you’ve numbers that needs merging.

merge join excel table data explorer 3

6) This is how the output looks:

merge join excel table data explorer 4

7) Rename the new column.

Select the new column > Right Click > Rename

8) Click Done if it looks OK.

9) The merged data is now available to you in Excel!

And one can analyze it!

Let’s see before and after. Note that instead of month numbers, we now have month names

merged data join table visualized excel 3

Conclusion:

In this post, we saw how to merge/join/combine data from two different sources in Excel 2010.

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Remove Duplicates in Excel Tables using Data Explorer Add-in:

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In this blog post, we’ll see how you can remove duplicated and clean data in excel tables using Data Explorer Add-in.

Problem:

Our Excel Table has following Data:

MonthMonth Name
1January
1January
1January
2February
2February
3March

And we want to remove duplicates to make the data-set look like this:

MonthMonth Name
1January
2February
3March

 

In real world data-sets, we wouldn’t have few rows but lot’s of rows and doing it manually wouldn’t be the wisest option. With that in mind, let’s look for a few-clicks solution that can help us remove duplicates.

Solution:

If you haven’t already, download the Data Explorer add-in preview available for Excel 2010 & 2013. It can do a lot more than removing duplicates – it’s a great add-in and it’ll save you lots of time especially if your job involves discovering, cleaning and combining data for analysis purposes. After you’re done installing the add-in, use the steps below to remove duplicates in an excel column:

1. Open Data in Excel. Switch to Data Explorer Tab

2. For the purpose of the demo, I am assuming that you already have the data in excel file. If not, you can connect to other sources via the add-in.

3. Data Explorer add-in > Excel Data> From Table

data explorer excel remove duplicates

4. After you’ve clicked on the From Table, a query editor will pop up:

excel data explorer query editor

5. Select both columns

(you can select both columns by: select first column > hold down the ctrl key and then click on second column)

6. Right click > Remove Duplicates

data explorer remove duplicates excel

7. click on done if you see that the duplicates have been removed correctly

data explorer excel remove duplicates 2

Conclusion:

In this blog post, we saw how to remove duplicates and clean data in Excel using the Data Explorer Preview add-in.

If you’ve not downloaded and installed the data explorer add-in for Excel 2010 & 2013, you can find Information about it here: http://office.microsoft.com/en-us/excel/download-data-explorer-for-excel-FX104018616.aspx 

Note:

1) URL to download the add-in may change in future

2) The steps that I described may also change because as of today the ad-in is in “preview” stage and things may change in future.

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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!

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