Category: Vizualization

Qlik Sense: A first Impression

On By Ben Larson Ph.D.In Qlik, VizualizationLeave a comment

So I am trying out Qlik Sense as a possible BI option for work. I have some limited experience (through grad school) working with another one of their products Qlik View. I will say right from the get go, Qlik Sense is much more user friendly.

Opening it up, I get the following splash screen

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Qlik then asks if I would like to Create a New App.qlikSense1.jpg

I click Create A New APP and I get a window to name it.

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It says New app created, and asks if I want to open my app

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Now I am brought to a page to add my data. I have two options, one a more GUI driven method, and the other that will allow me to create my data model using Qlik’s script (very similar to SQL).

I am going to go with the GUI method for now.

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I choose Excel files

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Next I select a file QlikTEst.xlsx that I put together for this test drive.

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My file appears in preview mode. Notice I am able to select both sheets to load and unselect columns I don’t want.

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I click Prepare Data at the bottom and I am brought to this screen. Notice the red triangle warning on the bottom of the screen. It says I have possible associations.

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I click the warning and I now have a recommendation for an association to make between sheets. My Equipmentkey column matches up(53%) on both sheets.

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Just double click the Recommendations box and your pages are now joined

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Now hit Load data

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Qlik now brings you to a work sheet.

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I want to create a bar chart, so I drag one in from the menu column.

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Now I pick my Month as my dimension

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And I choose WorkOrderNo as my measure

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Now I choose an Aggregate of Count()

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And I have a bar chart.

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Now, let’s add a filter – drag it in from the menu column

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Select FacilityCode as my dimension

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I can adjust the filter size by clicking on these points

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Now hit done at the top of the screen

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And I now have a live interactive bar chart.

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My Thoughts on Qlik Sense

Qlik Sense is insanely easy to get up an running. You really don’t need to know much more than how to drag and drop. However, if you are like me and enjoy getting under the hood, Qlik does allow you custom code your data models and formulas.

My only complaint, and this could be because I am new and don’t know a work around, is having to hit Done to leave the edit screen before I can test the interactivity of my charts.

 

Python: Line Graph

On By Ben Larson Ph.D.In Python, VizualizationLeave a comment

Let’s build on what we learned in : Python: Intro to Graphs

First, import pyplot from matplotlib

Remember %matplotlib inline let’s you see your graphs in the jupyter notebooks

pythonLine

Line 1

Note I am using a list comprehension to fill the x axis.

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Now, let us do some formatting:

  • ‘r:’    –   red dotted line
  • label = ‘up’   –  adds label to the line
  • py.legend(loc=9)  – adds a legend to the chart

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Line 2

For line 2, I want to create a reverse curve:

  • d = u  – list u is copied to d
  • d.reverse() – reverses values in d

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Plot the line.

  • ‘g-.’ – green dashed line

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Combine the two lines

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Line 3

Here I use another list comprehension  and zip to make our last like. This adds each element of list u and d in order.

  • ‘b-‘ – blue solid line

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If you enjoyed this lesson, click LIKE below, or even better, leave me a COMMENT. 

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Python: Intro to Graphs

On By Ben Larson Ph.D.In Python, Vizualization2 Comments

Visualizations are big part of analytics. You will need to produce visually engaging graphics for presentations, reports, and dashboards. You will also make graphs for your own use in data discovery and analysis. As bonus, unlike data cleaning, data viz can be pretty fun.

Matplotlab and Pyplot

Matplotlab is a module you can import into Python that will help you to build some basic graphs and charts. Pyplot is part of Matplotlab and the part we will be using in the following example.

**If you are using the Anaconda Python distribution, Matplotlab is already installed. If not, you may need to download it from another source.

Line Graph

Syntax

  • %matplotlib inline – this code allows you to view your graphs inside jupyter notebooks
  • from matplotlib import pyplot as plt – here we import pyplot from matplotlib into our program (note, we only want pyplot not all the functions in matplotlib).Adding “as plt” gives us a shorter alias to work with
  • age and height lines – fill our lists with age and height information for an individual
  • plt.plot(age, height, color = ‘blue’) – here we tell Python to plot age against height and to color our line blue
  • plt.show() – prints out our graph

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Bar Chart

For this example, we will make a bar charting showing ages of 4 people.

Syntax

  • You should understand the first few lines from the first example
  • count_names = [i for i,_ in enumerate(name)]  – since the name list is a list of strings, we cannot really graph that onto a chart. We need a way to convert these strings into numbers.

Wait? What does for i,_ mean? Let’s jump to the next code sample

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While you don’t see it when making the list, a Python list is technically a list of tuples (index number, element). So if instead of i,_ we asked for both elements in the tuple, (i,j) we would get the following.

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So by iterating by for i,_ we only return the first element in the tuple (the index)

** notice we are using a list comprehension. If you are unfamiliar with list comprehensions, check out my earlier post: Python: List Comprehension

Let’s clean up our bar chart a little now.

  • plt.ylabel(‘Age’) – label the y-axis Age
  • plt.title(‘Age of People’) – give the graph a title
  • plt.xticks([i+0.5 for i,_ in enumerate(name)], name) – this label function is using a list comprehension to first chose the position on the X-axis, and name provides the person’s name for the label.

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Intro to Tableau: Line Chart: 3 or More Measures

On By Ben Larson Ph.D.In Tableau, VizualizationLeave a comment

 Note:

If you do not currently have Tableau, you can download a free version at: https://public.tableau.com/s/

Downloads:

Download Practice Excel File Here: School Lunch

 

Line Chart: 3 or More Measures

This lesson is a continuation of an earlier lesson. If you are already familiar with Tableau, feel free to continue on. Otherwise, check out my first Tableau lesson: Line and Bar Charts

If you want to add 3 or more measures to a line chart, you need to take a different approach than in regular charts.

Import the Data

Select Excel from the Connect menu and select the school lunch excel file you have downloaded.

If you are continuing on from the Line and Bar Charts lesson, you can skip this step, your data is already loaded.

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Create a New Worksheet

Click the New Worksheet icon found on the bottom of your screen.

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Drag Year to Columns and Measure Values to Rows

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  1. Get rid of Sum(Number of Records) by dragging it back into Measures
  2. While holding down Ctrl drag Measure Names from the Dimensions slot to Color

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And there you have it. 3 Measures in one chart.

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Intro to Tableau: Dual Axis Charts

On By Ben Larson Ph.D.In Tableau, VizualizationLeave a comment

 Note:

If you do not currently have Tableau, you can download a free version at: https://public.tableau.com/s/

Downloads:

Download Practice Excel File Here: School Lunch

 

Dual Axis Charts

This lesson is a continuation of an earlier lesson. If you are already familiar with Tableau, feel free to continue on. Otherwise, check out my first Tableau lesson: Line and Bar Charts

Import the Data

Select Excel from the Connect menu and select the school lunch excel file you have downloaded.

If you are continuing on from the Line and Bar Charts lesson, you can skip this step, your data is already loaded.

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Create a New Worksheet

Click the New Worksheet icon found on the bottom of your screen.

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Drag Year from Dimensions and Free from Measures into Columns and Rows respectively. You should now have a line chart. (if not, refer to Lesson 1 for troubleshooting tips)

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Now, drag Full Price into Rows. You should now notice you have two graphs. Free up top and Full Price on the bottom.

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Now you could just stop there. You do have both Measures graphed. But this really isn’t the best way analyze this data. It is hard to do a good comparison this way.

Dual Axis

For better analysis, we are going to create a Dual Axis Chart.

Right click on the Y Axis of the bottom chart and select Dual axis

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Now you have both measures on one graph.

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If you look closely at the Left and Right Y-Axis’s, you will notice they are not the same. This could skew how someone would interpret this data.

To fix this, right click on the Right Y-Axis and select Synchronize axis

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Finally, since both of your Y-Axis match up, you don’t need them both. Right click on the Right Axis again and uncheck Show header.

Previous > Lesson 1

Next > 3 or More Measures

 

Intro to Tableau: Line and Bar Charts

On By Ben Larson Ph.D.In Tableau, VizualizationLeave a comment

 Note:

If you do not currently have Tableau, you can download a free version at: https://public.tableau.com/s/

Downloads:

Download Practice Excel File Here: School Lunch

 

Lines and Bar Charts

Start Tableau

When you start up Tableau, the first thing you need to do is select a data source.

tableauIntro1

In this case, select Excel and choose the file the you downloaded above (schoolLunch.xls)

Once loaded, the Data Source Page will open up.

a. Data Source File

b. Shows Sheets in the file (there is only one sheet in this particular file)

c. Shows data.

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The Data

In this example, we are looking at the number of kids receiving Free, Reduced Priced, and Full Price lunches at American public schools from 1971 to 2015.

Line Chart

Start by making a new sheet

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A Quick Note About Dimensions and Measures:

Notice on the new sheet that the columns from your imported Excel sheet have been placed into two boxes on the left of the screen: Dimension and Measures. Think of Dimensions as Factors or Labels. While Measures are columns you would perform calculations against (adding, averaging, etc). 

Drag Year from Dimensions and Free from Measures into Columns and Rows respectively.

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The line graph should appear automatically. If not, follow the next steps:

First, make sure your Row variable says SUM(Free) — this means we are summing up all numbers in the Free column— If it doesn’t, hover over the measure until a small downward arrow appears. Then go to Measure and select Sum.

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If you don’t have a line chart, go to Marks and select Line from the drop down menu

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Bar Chart

Now, go to Marks again and select Bar. Your chart will change over to a bar chart. Try a few of the other options like Area and Shape.

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Next Lesson: Dual Axis Charts

 

 

 

 

Tableau: CPI Food Prices 2013-2015

On By Ben Larson Ph.D.In Tableau, VizualizationLeave a comment

cpifood

This visualization (made using Tableau) shows the CPI (Consumer Price Index) for common food items. While 2014 was bad year for staples such as dairy and meat, 2015 showed a nice recovery. The main exception being eggs. Look at the massive increase in egg prices caused by the bird flu epidemic of 2015.  **note the purple dot represents the 20-Year Historical Average.

Link to Tableau workbook: Workbook

Data found at USDA website: data link

HTM: Visualizing Inspection Schedule Balancing

On By Ben Larson Ph.D.In Tableau, VizualizationLeave a comment

PM’s can be a real resource drain, especially on the heavy months. That has been one thing that has always confounded me as long as I have worked as an HTM professional (or Biomed  — the name keeps changing). I have never understood why you would have one month with over 1000 scheduled inspections and only 200 scheduled inspections in another month.

The problem is, balancing the workload is a tedious job, sifting through pages of work order lists and moving schedules around. However, if you don’t feel like going cross eyed staring at all of that small text, try giving data visualization a try.

pmSchedule

This graph above(produced using Tableau) shows the scheduled work order load for an imaginary hospital. Note that each color block represents a separate department.

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Mousing over each colored block provides a fly out showing the Department and record count. You can go here to try the interactive visualization out for yourself: Click here to interact

Looking at this visualization, it is easy to see where departments can be quickly moved around to balance the load. This visualization, if connected to your database, can also become part of a dashboard – allowing you to keep an eye on the work load and prevent it from become unbalanced as departments open and closed and equipment comes and goes.

Now the final data model I created takes more into account than simply the number of records. Using historical data, I add a timing factor to each inspection (this takes into account that the inspection of a diagnostic ultrasound machine will take more time than the inspection of an IV pump). I also add in a personnel factor (if you only have one technician qualified to work on imaging equipment vs 8 technicians for standard patient care equipment, the imaging technician’s time should be weighted to represent that).