Tableau Saturday VIII, 30th March, 2024

Our sole mission is to help people see and understand data .

. — Tableau©️ 2003

Hi Everyone, I would like to thank those who made it to the Tableau©️ Saturday Colab Kaduna in person event, especially our host Sanusi Ismaila and tutor Peter Okwukogwu aka Pablo.

Peter took us on a journey through, Tableau public, Python, Geopandas.

On Tableau, you can also represent data as discrete or continuous. We looked at maps, Measures and Dimensions.

Geographic visualizations

In Tableau, the built-in geographic database recognizes geographic roles for fields such as Country, State, City, Airport, Congressional District, or Zip Code. Even if your data does not contain latitude and longitude values, you can simply use geographic fields to plot locations on a map. If your data does contain latitude and longitude fields, you may use those instead of the generated values.

We discussed the Yada financial investments.

We opened the data set from Kaggle on world population.

We talked about Tradeoffs with reference to Atomic Habits by James Clear.

We were reminded that every action and decision. reached both in our personal and cooperate life is a tradeoff for something.

Every time we learn stuffs with context we learn well, you don't learn in isolation, in learning you get boring when it’s done in isolation.

We used the Tableau Introduction to maps by Pavan Lalwani on YouTube to go over concepts on Geo Maps.

https://www.youtube.com/watch?v=X0n0s0gzcvE

We talked about Contexts. There is a context to ever content or scenario. There is a context for which Colab kaduna exists too, that why there is regular meetups (townhall meetings) to look at how the journey has gone so far and where there needs to be iterations. ( this also applies to product management).

For the geo data we picked a data set on global population from KAGGLE Website. The data connected was a CSV file.

The data had six columns and 788 rows. In Python we trade off aesthetics for control and vice versa for Tableau. It’s not so sexy when it’s on Python though. We have to work with dimensions and measures. Measures are flat numbers, Dimension’s cut the measures up.

According to the Gestalt Principle perception varies.

On a visualization bar chart, you can Sort Descending and Ascending, You can Swap rows and columns . We renamed the default sheet. The default sheet name also changed on the interface.

Using Show Me

Show Me is a powerful component of Tableau that arranges selected and active fields into the places required for the selected visualization type. The Show Me toolbar displays small thumbnail images of different types of visualizations, allowing you to create visualizations with a single click. Based on the fields you select in the Data pane and the fields that are already in view, Show Me will enable possible visualizations and highlight a recommended visualization.

It does this with visual analytics best practices built in, giving you the ability to quickly see a variety of visualizations that might answer your questions.

Explore the features of Show Me by following these steps:

1. Navigate to the Show Me sheet.
2. If the Show Me pane is not expanded, click on the Show Me button in the upper right of the toolbar
3. to expand the pane.
4. Press and hold the Ctrl key while clicking on the Postal Code, State, and Profit fields in the Data pane to select each of those fields. With those fields highlighted, Show Me should look like this:

Notice that the Show Me window has enabled certain visualization types such as text tables, heat maps, symbol maps, filled maps, and bar charts. These are the visualizations that are possible given the fields already in the view, in addition to any selected in the Data pane.

We were very keen to look at where Nigeria came to be the charts. And on the Maps. We also noticed the data on it in comparison to nations with close figures and deduced reasons for some existing figures.

We created a new sheet, along the line we noticed a blank portion of the map meaning data wasn’t provided for that location.

We need to ask questions to build capacity and capability. To stimulate the mind to ask questions is very powerful .

Everything has an abstraction. We had a practical with objects within reach.

We delved into a bit of Python we looked at the Book High Performance Python , Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottienecks and significantly speed up your code in high data volume progrars. By exploring the fundamental theory behind design choices. High Performance Python helps you gain a deeper understanding of Python’s implementation.

Get a better grasp of NumPy. Cython, and profilers

• Learn how Pythen abstracts the underlying computer architecture
• Use profiling to find bottlenecks in CPU time and memory usage
• Write efficient programs by choosing appropriate data structures
• Speed up matrix and vector computations
• Use tools to compile Python down to machine code
• Manage multiple 1/0 and computational operations concurrently
• Convert multiprocessing code to run on local or remote clusters
• Deploy code faster using tools like Docker

Do comment below on how your journey into tableau has been.

Useful links:

THE 17 GOALS | Sustainable Development

Introduction to Psychology

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