How would you like to present your data analytics work better?
When starting your data analytics projects, one of the critical considerations is how to present your results quickly and understandably?
Undoubtedly this is true if you are only going to look at the results yourself.
If the work you do is a repeatable process, a more robust longer-term solution needs to be applied, this is where Tkinter can help, which is a python graphical user interface.
When you are importing tkinter, some of the functionality that can be used include:
Use them to build calculators.
They can show graphs and bar charts.
Show graphics on a screen.
Validate user input, through building entry widgets.
Where this all fits in with data analytics?
While going through a set of data and getting some meaning to it can be challenging, using the python graphical user interface tutorial below can help build the screens that will allow a repeatable process to display in a meaningful way.
Using the tkinter widget could help achieve the following:
Build a screen that shows data analytics errors in a data set, e.g. The number of blank column values in a dataset.
Another application is to run your analytics to show the results on a screen that can be printed or exported.
Similarly, you could also have a screen where a user selects several parameters that are fed into the data analytics code and produces information for the user to analyse.
There are many more ways that you could do this, but one of the most important things is that data analytics can be built into a windows environment using Tkinter.
These GUI applications are what the user would be used to currently seeing. As a result, this could help to distribute a solution across an enterprise to lots of different users.
Also, another benefit is that they will work on many different operating systems.
The only thing that needs to happen is that the requirements the user needs are defined, and the developer then builds on those, with the data analytics code run in the background of this program with Tkinter and output into a user-friendly screen for review.
It will demonstrate how a Combobox can be used to select values and then validate the entry chosen.
Using a Combobox in the computer programming world has been around for some time.
It is a useful way to select from a choice and could in many ways in data analytics help as the following examples show:
Select a date to filter a data set down to values that are in the dataset.
Using matplotlib to plot data points in charts, you could have dynamic values that change the diagram based on values chosen from the Combobox.
Utilizing data analytics reports that the user accesses, the Combobox could be used to change the data shown dynamically to allow comparisons.
When looking to fix data quality issues, use the Combobox to select values for a date that needs to be fixed, apply the fixes on screen, and then save back to the database.
Developing a Tkinter GUI and the possibilities it brings
In this video, we use ttk, written to help split the behavior of code from the code implementing its appearance.
You can see plenty more on it here ttk information. This is a handy piece of functionality as styling an object can interfere with how it works.
We also have a function that helps with the validation. In the below, it accomplishes the following:
Allows the combobox value selected to be retrieved.
Validates the entry chosen in the combobox using an if statement.
def checkifireland ():
x = combolist.get() # asssigns the value inside the combobox to x so it can be processed
if x == "Ireland":
messagebox.showinfo("Correct answer", "You will love it in Ireland")
messagebox.showinfo("Incorrect answer", "You should visit Ireland first!")
The effectiveness is especially handy as it helps to ensure that the code returned from the Combobox to the function is correct
The below video will take through this step by step and explain the concepts discussed above.
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