Setup

Overview

Time: min

Objectives

• Install and authenticate Tableau subscription

• Install and setup Zoom if needed

• Download data files for this workshop

Software setup

Install the videoconferencing client

If you haven't used Zoom before, go to the official website to download and install the Zoom client for your computer.

Set up your workspace

Like other Carpentries workshops, you will be learning by "coding along" with the Instructors. To do this, you will need to have both the window for the tool you will be learning about (a terminal, RStudio, your web browser, etc..) and the window for the Zoom video conference client open. In order to see both at once, we recommend using one of the following set up options:

• Two monitors: If you have two monitors, plan to have the tool you are learning up on one monitor and the video conferencing software on the other.
• Two devices: If you don't have two monitors, do you have another device (tablet, smartphone) with a medium to large sized screen? If so, try using the smaller device as your video conference connection and your larger device (laptop or desktop) to follow along with the tool you will be learning about.
• Divide your screen: If you only have one device and one screen, practice having two windows (the video conference program and one of the tools you will be using at the workshop) open together. How can you best fit both on your screen? Will it work better for you to toggle between them using a keyboard shortcut? Try it out in advance to decide what will work best for you.

Data files:

Please download the following file(s) to particpate in the workshop:

Link to Data Set: https://uofi.box.com/s/6q4p6u601z28b5iacmmydbuw3p6r0ezm

Link to Tableau File: https://uofi.box.com/s/fxios6tbtzg5r3xsr4uzl5ykwsop96ce

About the Data Used in this Workshop:

The dataset used is a sample dataset from Tabelau. It is a basic data collection of US supermarkets.

Let us understand the attributes of this data set:

• ‘Row ID’ - This is nothing but Serial No.
• ‘Order ID’ - ID created when a product order is placed.
• ‘Order Date’ - Date on which a customer places his/her order.
• ‘Ship Date’ - Date on which the order is shipped.
• ‘Ship Mode’ - Mode of shipment of each order.
• ‘Customer ID’ - ID assigned to each customer who places an order.
• ‘Customer Name’ - Name of Customer.
• ‘Segment’ - Section from where the order is placed.
• ‘Country’ - Country details of this data set. We are looking only for US store data.
• ‘City’ - Cities of US are listed here.
• ‘State’ - States of US are listed here.
• ‘Postal Code’ - pin code
• ‘Region’ - grouped into region wise
• ‘Product ID’ - Product ID of each product
• ‘Category’ - Category to which each product belongs to.
• ‘Sub-Category’ - Sub-Category of each Category
• ‘Product Name’ - Name of products.
• ‘Sales’ - Selling Price of each product.
• ‘Quantity’ - number of quantity available for a particular product.
• ‘Discount’ - Discount available on each product.
• ‘Profit’ - Profit gained on each product.

Key Points

Data Visualization Basics

Overview

Time: 15 min

Objectives

• To get a fundamental grasp of data visualization.

• The audience will be introduced to the tableau platform in general, as well as basic charts and visualizations in tableau.

1. What is Data Visualization?

• Data visualization is a way of representing the data in the form of graphs, maps or charts. Pictorial representation of data helps in identifying trends or patterns in data as well as outliers in the data.
• What makes data visualization so special is that it squeezes a large amount of data in just one graph.

1. Why Data Visualization?

Data Visualization helps in data interpretation in the most efficient way possible. The history of data visualization goes back to the 17th century where maps and graphs were used to understand the data better. One notable example of it is the map of Napoleon’s invasion of Russia. The map depicted the size of the army as well as the path of Napoleon’s retreat from Moscow – and tied that information to temperature and time scales for a more in-depth understanding of the event.

Advantages of using Data Visualization –

• Human brain is a powerful processor and vision dominates our memory. Hence data visualization helps the audience retain the information for a long time.
• A picture is worth a thousand words. With massive amount of data being generated every day, Data visualization helps to tell stories by curating data into a form which is easier to understand.
• Identifying trends in data seems like an obvious use of data visualization, but it is kind of an important one. To make predictions, we need data from past and present. Trends over time tell us how a firm is doing and how a firm can potentially go.
• Not only does it help in predicting future occurrences,it also helps in identifying current areas that need attention/improvements.

3.Good / Bad Visualizations

• There are many ways in which data visualization can go wrong. A good visualization is the one where you can find the insights just in a glance.

• It should be simple, easy on the eyes and informative and should avoid visual clutter. Any unnecessary ink on the chart, too much information in one chart, a lot of colors and shapes they all cause visual clutter. Here are some examples of good / bad visualizations –

• Bad Visualizations: a. The pie chart below adds up to a total of 193% which is wrong

b. Too much information in one graph

c. The x-axis scale is not consistent

Good Visualizations: Simple, easy on the eyes and informative graphs

Key Points

• Introduction to Tableau Desktop, Tableau Basics explained in subsequent lessons.

Intro to Tableau Desktop

Overview

Time: min

Objectives

• Demo of Tableau Desktop. Connecting to dataset and working with Sheets.

• This is how the tableau desktop looks. On the left hand-side you have options to connect to files and servers. -On the right hand-side you have resources and training material available. To connect to a data source, you can either connect from local device i.e your computer or you can connect via a server.

• This the page that appears when you import data into Tableau. You can see all the sheets in the data source under the Sheets column in the left corner.
• You can drag the sheets you want to work with in the upper part of the page which says, ‘Drag tables here’. You can see the preview of the sheet that you are working with on the bottom part of the page.
• You can view all the fields and data types of the fields as well. You can also perform join operations and join multiple sheets. After you have connected to the desired data source, you can then see a sheet layout.

• This sheet is your working space for your tableau project. On the top you can see rows and columns shelves where you place the items or features you want to visualize. The columns shelf creates columns of the table while rows creates rows of table. You can place any number of fields on these shelves.

• The left corner has a list of measures and dimensions. The variables (or the columns) from the dataset are divided into dimensions and measures. The simplest way to know the difference between them is that all dimensions are categorical/discrete variables and all measures are quantitative/continuous variables. To make it even simpler, measures are the ones on which we can perform arithmetic operations.

• The most powerful element is tableau is the marks card. With the marks cards, you can encode your data with color, size, shape, text and detail. The filter shelf allows you to specify which data to include/exclude.

• You can use measures or dimensions or both at the same time. The page shelf helps you view the visualization into series of pages so you can analyze how a specific field affects the rest of the data. The ‘show me’ on the right corner is like a cheat sheet and it tells you about the variety of charts you can create and what number of dimensions and measures you will require to make that chart.

Key Points

Tableau Basics

Overview

Time: min

Objectives

• Introduction to Data Types, and Types of Charts in Tableau.

Data Types in Tableau

• All the variables in the dataset have a data type. It tells us the kind of information stored in that field. Tableau has specific data type icons which tell you about the data type.

Sometimes, tableau might interpret the data type wrong. For example, it might consider the date type as integers as it has numbers in it. You can always change the data type of the field.

• There are several methods to do so. The easiest is to go on the data type icon and click. You will see a list of data types. Select the one you want and it will be changed.

• Choosing the right chart type This is one of the most important skill to have while dealing with data visualization. The points that you need to consider while making a visualization are what questions you are answering and what insights you are getting. With experience you will be able to assess what chart type you want to create. Here are some examples –

• a. Magnitude Charts – It shows the relative size/value of two or more discrete items. For example, if you are comparing sales of different regions you want to compare the magnitudes. They include bar charts, line charts, packed bubble chart.
• b. Ranking Charts – Sometimes you want to depict the relative ranking of all the members of your dimension. For example, showing the top 10 sales people. Ranking charts include bar graphs with rank calculations.
• c. Distribution Charts – They are helpful in plotting the frequency of an event within a population. For example, frequency of incoming calls by day. Distribution charts include histograms, population pyramids and box plots.
• d. Deviation Charts – Deviation charts show how the values deviate from a baseline value. That baseline value could be the average or the median. For example, if an item has unusually high or low profits you use deviation charts. They include bullet charts, bar charts and combination charts.
• e. Change over time Charts- To observe change in a variable over time we use these visualization. The charts include line charts, slope charts, highlight tables.
• f. Part-to-Whole Charts – To observe how much of a whole an individual part takes up you need part-to-whole charts. For example, how much a region contributes to overall sales. The charts may be pie charts, area charts, treemaps and stacked bar charts.
• g. Spatial Charts – These are the charts that display the precise locations and geographical patterns in your data. For example, map of all sales across the country. They include filled maps, point distribution maps, symbol maps and density maps.
• h. Flow Charts – They include path over time and path between origin and destination charts. For example, identifying the longest shipping route.

Key Points

Basic Charts

Overview

Time: min

Objectives

• Introduction to Profit mix, bar and Trend Charts.

Basic Charts

a. Sales and Profit mix

• To create the sales and profit chart, you first need to drag the sub-category field from dimensions and drop it in the columns shelf. Next drag the sales from measures and drop it in the rows shelf.
• This chart shows the sales across subcategory. To add profits, you drag the profits from measures and drop it on the color marks card. Now, its common that we relate green color with progress and red color with loss/danger.

• To change the color theme, you click on the color marks card and select edit color. From the drop down select the appropriate color palette and click on OK.

b. Sales Trend

• To plot the sales trend, first drag the order date on columns shelf and click on the plus sign. By doing so, you get order dates in quarterly and monthly pattern.
• For this visualization you need order date by month. You can go ahead and remove other options from column shelf.

• Next, select sales from measures and drop on the rows shelf. This gives you the monthly sales. To see yearly sales add order date (yearly) to the color marks card. This visualization shows yearly sales trends

Key Points