## Connect Tableau to An Excel File

I have just enrolled in a Data Science course on Udemy  and I learned good stuff.

Now that you downloaded the dataset in Excel file format, we’ll use Tableau to analyze this.

We’ll connect to the dataset using the « Excel » option.

Now that you downloaded the dataset which is in Excel format, we will use Tableau to analyze this.

We will connect the the dataset using the « Excel » option.

Select the dataset in Excel file you downloaded and click on the « Open » button.

And as you can see, there is only one tab.

There is only one tab because in the Excel file there is only one tab. If in the Excel file there were several tabs, they would all have been listed here.

It’s necessary to check that all data is « OK ». Scroll the lines and columns to see that. Everything is good, there are 10 000 lines as in the Excel file.

Excellent, we connected our Excel source file to Tableau.

Now, click on the « Sheet1 » tab to access the Worksheet.

We’ll have a little fun.

For example, let’s look at what we have with « Geography »

« Geography » is the dimension that gives us the country, so we’ll make a map to see where the clients from the bank come from.

Move « Geography » on this area.

Ah, it’s odd, nothing happens ?!? Why ? Look, when you look at « Geography », it’s not recognized by Tableau as a geographic dimension. Here,, you can see that Tableau recognized « Geography » as a dimension of type text with the label « ABC »

Don’t worry, we can fix it quickly. Click on the arrow of « Geography ».

Selects « Geography Roles » and « Country Region » so that the « Geography » dimension become geography’s type.

Now you remove « Geography » made a table with a click-and-drag.

Look, we have a globe next to « Geography ». This means that Tableau recognize that « Geography » is a geographic dimension.

Since « Geography » is a dimension of geography type, there are 2 new measures that have appeared : Latitude (generated) and Longitude (generated).

Put « Geography » in this space with a click and drag.

Look, this time there is a map.

You have the possibility of zooming with these buttons.

The map is fine but we’ll remove the blue dots and modify the map so that it’s easier to read.

We’ll color the countries and display the clients number that has in each country.

We know that in the dataset each line corresponds to a client. What we can do is use the « number Of Record », it means the total of number of observations. In this way, we can visualize the number of lines attended to each country and the number of lines attended to each country is the number of client per country.

Then, take the « number Of Record » and move it to « Colors ».

Boom ! Each country has a color.

Look at the color contrasts. France has a darker color which indicates that it is the country with the most clients. Germany and Spain have almost the same colors which indicates that they have almost the same clients number.

But we want to know the clients number per country without have the cursor on the country.

To do this we’ll add a label. Take « number Of Record » and moves it to « Label ».

We’ll increase the text’s size and put in bold. Click on « Label », click on « Font » and select « 12 » and bold.

It’s cool, we can see the clients number per country. You have the possibility to zoom on a region. Click on « Zoom area » and drag and drag to select the region on the map.

Now we can see that the majority of clients are in France, this represents almost half of the total clients number of the dataset. Germany and Spain have almost the same number of clients.

-Steph

## Dataset For Data Mining

I have just enrolled in a Data Science course on Udemy  and I learned good stuff.

To have the dataset to do Data Mining, you need to go to the superdatascience website . In « Part.1 Visualization », you see the section « How to use Tableau for Data Mining ». Click on « Churn Modeling » to download the file.

Once you have downloaded the file, move the file to the directory you created for the course. In this directory, create a new directory (unless you already do it) named « 2.Chunk investigation ».

Open this fiel with Excel or with other spreadsheet software.

Know that we use this dataset for the visualization part but we will also use this dataset for the modeling part.

Let’s analyze the data of this dataset.

This dataset is quite large because it contains 10 000 lines and a few columns. This is the list of a bank’s client. The client information is :

• Surname (last name)

• Credit score ( is the measure that indicates the client’s ability to borrow)

• Geography (client’s country)

• Gender (male or female)

• Age

• Tenure -(the number of years the client is in the bank)

• Balance (balance of the client’s bank account)

• NumOfProduct (number of product that the client has in the bank – credit card, contract, account)

• HasCrCard (does the client have a credit card ?)

• IsActiveMember (did the client use his/her credit card during the last month ?)

• EstimatedSalary (the bank’s estimate of the client’s annual salary)

• Exited (did the client leave the bank ?)

Now, I will explain the context related to this dataset. This bank has branches in several countries like Germany, Spain and France. This bank noticed that lately there were many clients who left the bank. The bank has a report called « churn rate » which is the customers rate who leave the bank and for a few months the « churn rate » is really higher than usual. It’s for this reason that the bank needs a data scientist (you) to find the problem and propose solutions.

This dataset is a small sample of clients bank. These are 10 000 randomly selected client.

The column « Exited » is a column that didn’t exist before. This column has created when the bank realized that there was an abnormal number of client who were leaving the bank.

Then the bank observed these clients for 6 months to see which client left the bank.

In the « Exited » column, the number « 1 » means that the client left the bank and the number « 0 » means that the client stayed in the bank.

To analyze this dataset, you’ll need to do A/B Tests. For exemple, a classic A/B Test is to see if women are more likely to left the bank than men. That’s means, see the number of men who left the bank, see the number of women who left the bank and then normalize by the total number of clients. It’s important to normalize the number of clients because there are not the same proportions of women as men. Next, based on the last column « Exited », you’ll find out if it’s the men or women who are likely to left the bank.

Once you have relevant results, you can show your report to the bank. And with this report you should be able to propose solutions to the bank. For example, if the report says that women leave the bank in bulk, it’s because there is a problem and it’s necessary to see whether the bank is offering women something right. Or it’s possible that another bank offers a much more attractive offer for women or something else.

You will learn how to investigate in the dataset and find answer through client information with A/B tests.

-Steph

## Fitness History – National Period in Europe (1700 – 1850) Part 6

Germany

The growth of gymnastics in Germany can be mainly attributed to the work of two physical educators : Johann Guts Muths and Friedrich Jahn. Johann Guts Muths is generally referred to as the « Grandfather of German gymnastics ». He invented several exercise programs and equipment on which they were performed. All his works and achievements are in 2 books – Gymnastics for youth and games.

Friedrich Jahn earned the title of « Father of German gymnastics » for its long-term work. It was early in the Jahn’s life that Napoleon had conquered much of Europe including Germany. With the fall of France (Napoleon), Germany was divided into two separate states. Jahn’s passion for German nationalism and independence had become the driving force behind his creations of gymnastics programs. He believed that the invasion of Germany by a foreign country could be prevented by the physical development of the German people. Soon, exercise facilities that contained devices designed for running, jumping, balancing, climbing and vaulting called Turnvereins were spread throughout Germany.

Sweden

Pehr Henrik Ling has developed and introduced its own gymnastics program in Sweden that was composed of 3 different areas: 1) educational gymnastics 2) military gymnastics 3) Medical gymnastics. Ling who had a strong medical background had recognized that exercises were necessary for all people. He maintained that exercise programs should be designed to individual differences. Ling also believed that physical educators must possess knowledge of the effects of exercise on the human body. Ling was using science and physiology for a better understanding of the importance of fitness.

That’s all for today. Soon the rest of the fitness history

-Steph

## Fitness History – Renaissance (1400 – 1600) Part 5

After the dark ages and the Middle Ages, there was a rebirth of cultural knowledge. Inspired by ancient Greek and Roman civilization, it created the Renaissance. During this period the interest in the human body was the thing. Remember, the ancient Greek glorified the human body.

Martin Luther (religious leader), John Locke (philosopher), Vittorino da Feltre, John Comenius and Richard Mulcaster (physical educators) had a high level of fitness to improve their intellectual learning.

Civilizations that recognized the importance of fitness need to convey it to people. Fitness and physical education have a common bond. So, physical education was the solution to spread the values and benefits of fitness. Before, school programs in ancient Greek already included physical education. The appreciation of human life during the Renaissance helped to develop physical education. As a result, physical education transmitted throughout Europe.

National Period in Europe (1700 – 1850)

Europe suffered several cultural changes after the Renaissance. Despite that fitness stayed high and continued. Physical education programs extend in the emerging country in Europe. The feeling of nationalism and independence has created the first modern fitness movement. These were gymnastics programs. They were popular in Germany, Denmark, Sweden, and Great Britain.

That’s all for today. Soon the rest of the fitness history

-Steph