This is a guide to installing and running Tableau Desktop on your personal computer. Please note that all workstations in the Digital Studio (on the second floor of O'Neill Library) already have Tableau Desktop installed.

Tableau has versions for both Windows and Mac. Detailed system requirements for Tableau here: https://public.tableau.com/en-us/s/download.

Tableau Desktop is a visualization software used to create data visualizations and interactive dashboards. If you are a student, instructor, or researcher, you can request a free, renewable, one-year license for Tableau Desktop through Tableau Academic Program. For instructor and researcher, the individual license is valid for one year and can be renewed each year if you are teaching Tableau in the classroom or conducting non-commercial academic research; The student license expires after one year; you can request a new license each year as a full-time student.

If you are a member of the public, please consider using Tableau Public instead, which is the free version of Tableau Desktop.

Here are the steps for students: (Installation process for instructors and researchers is similar. Just follow the instructions on the screen.)

Step 1: Go to https://www.tableau.com/academic/students (Here is the link for instructors.)

Tableau Student

Step 2: Click on Get Tableau for Free.

Step 3: A web form will pop up. Complete all of the requested information, using your official BC email address when you fill out the form.

Step 4: Next, click on Verify Student Status.

Step 5: You will receive an email with a product key and link to download the software.

Step 6: Click on Download Tableau Desktop from your email and copy the product key.

Step 7: Follow the installation instructions to install Tableau to your computer.

Step 8: Activate your Tableau with your license key.

For instructor and researcher, click on Request Individual License on the screen.

The pop up request form is similar to the student one described above, but additionally asks "I plan to use Tableau Desktop for..." Under that popup, you can select "Teaching only," "Noncommercial academic research only," or both. Select the option that fits your needs best. You do not need to be an instructor to get a Tableau copy.

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Tableau Public

Following are the general steps to download Tableau Public:

1. Go to Tableau Public Download Page: public.tableau.com ​

2. Enter your email address and click "Download the App".

3. Once the installation file has been downloaded to your computer, run it and follow the prompts to install Tableau on your Mac or PC.

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​Tableau Community​

Join the Tableau Community Forums to find solutions for what you need to accomplish. Ask questions to receive help and feedback.

​Tableau Visual Gallery​

Get inspired by the many interactive visualizations in the Visual Gallery. Download the workbooks to play with on Tableau Desktop

Tableau training: How-to Videos​

​Lynda.com --Lynda.com has a great variety of training videos about Tableau.

Note: Lynda.com can be accessed with a Boston Public Library Card. Anyone residing in the state of Massachusetts can apply for a free e-library card. Once you have a Boston Public Library account, you can use your credentials to log in.

More reading about data visualization:

• The Big Book of Dashboards

• Visual Reporting and Analysis: Seeing is Knowing Whitepaper

• Visual Analysis Best Practices: A Guidebook Whitepaper

• Data Storytelling: Using visualization to share the human impact of numbers Whitepaper

• Beautiful Evidence – Edward Tufte

• Information Dashboard Design – Stephen Few

• Information Visualization – Colin Ware

Example 1: Tableau Chart Catalog

This catalog provides a list of different chart types with links to actual visualizations built in Tableau and published on Tableau Public. This was developed as a resource for the Tableau community for inspiration and to assist in the understanding of how these chart types might be used in actual use cases. All visualizations on this page are being provided with the permission of the original author and are available for download from Tableau Public. Click on the image to open the actual visualization in a separate browser window. (Note: inclusion does not mean the chart is the best choice for the data represented. Also note that the originator of each chart may not necessarily be represented; these are simply examples).

Tableau Chart Catalog

Example 2: Napoleon’s Invasion of Russia 1812-181

The best statistical graphic ever drawn“, is how statistician Edward Tufte described this chart in his authoritative work ‘The Visual Display of Quantitative Information’. The chart above also tells the story of a war: Napoleon’s Russian campaign of 1812. It was drawn half a century afterwards by Charles Joseph Minard, a French civil engineer who worked on dams, canals and bridges. He was 80 years old and long retired when, in 1861, he called on the innovative techniques he had invented for the purpose of displaying flows of people, in order to tell the tragic tale in a single image. This visualization shows 6 type of data (Number of Solider remaining, Army's direction, Geographic information, Distance, Dates, and Temperature) in 2 dimensions.

Here is the interactive version of this visualization on Tableau public:

https://public.tableau.com/en-us/gallery/recreating-charles-minards-napoleons-march

Example 3: Diagram of the causes of mortality in the army

Example 4: A Pie Chart Redesign in Tableau

Explore this visualization: link

Example 5: Information Wanted

Here is an example that I created in Tableau:

More about his project:

Example 6: Bubble Art with Tableau

Source: https://www.flerlagetwins.com/2017/12/geometric-art-in-tableau_17.html

Import CSV & Excel files from local directory

Import csv files from local directory pandas tutorial: pandas.read_csv

#Uplocad csv file from your local directory
from google.colab import files
uploaded = files.upload()

import pandas as pd
df = pd.read_csv('FILENAME.csv')  #The filename of the uplpaded csv file
#df.shape
df.head()

Import Excel files pandas tutorial: pandas.read_excel

#Uplocad Excel file from your local directory
from google.colab import files
uploaded = files.upload()

import pandas as pd
df = pd.read_excel('FILENAME.xlsx')  #The filename of the uplpaded csv file
#df.shape
df.head()

Import data from URL

#Example: NYT Github COVID-19 data
#https://raw.githubusercontent.com/nytimes/covid-19-data/master/live/us-counties.csv
url = 'The URL of data'
df = pd.read_csv(url)
#df.shape
df.head()

Google Drive Import

Read data by Google Sheets Name

#gspread setup
!pip install --upgrade gspread

#Authenticate access to your Google Drive
from google.colab import auth
auth.authenticate_user()

import gspread
from oauth2client.client import GoogleCredentials
gc = gspread.authorize(GoogleCredentials.get_application_default())


import pandas as pd
worksheet = gc.open('Google Sheets NAME').sheet1   
rows = worksheet.get_all_values()    # get_all_values gives a list of rows.
df = pd.DataFrame.from_records(rows)  # Convert to a DataFrame and render.
df.head()

Read data by Google Sheets ID

#gspread setup
!pip install --upgrade gspread

#Authenticate access to your Google Drive
from google.colab import auth
auth.authenticate_user()

import gspread
from oauth2client.client import GoogleCredentials
gc = gspread.authorize(GoogleCredentials.get_application_default())


worksheet = gc.open_by_key('Google Sheets ID').worksheet('NAME OF A SHEET TAB')    #Call by Sheet ID & Name
rows = worksheet.get_all_values()    # get_all_values gives a list of rows.
df = pd.DataFrame.from_records(rows[1:], columns=rows[0])   # Convert to a DataFrame and render. 1st Row as Headers
df.head()

Read CSV file from Google Drive - by sharing link

!pip install -U -q PyDrive 

from pydrive.auth import GoogleAuth 
from pydrive.drive import GoogleDrive 
from google.colab import auth 
from oauth2client.client import GoogleCredentials 


# Authenticate and create the PyDrive client. 
auth.authenticate_user() 
gauth = GoogleAuth() 
gauth.credentials = GoogleCredentials.get_application_default() 
drive = GoogleDrive(gauth)   #Copy and paste Google Authentication code

link = 'SHARING LINK'  #The sharing link of the data file stored on your Google Drive
id = link.split("/")[-2]
#print(id)
downloaded = drive.CreateFile({'id':id})  
downloaded.GetContentFile('covid_county.csv')   
df = pd.read_csv('covid_county.csv') 
df.head()

Read CSV file from Google Drive - by mounting Google Drive

#Mount Google Drive
from google.colab import drive
drive.mount('/content/drive')  

path = '/content/drive/PATH TO THE FILE'
df = pd.read_csv(path)
df.head()

Starter Kit for Text Analysis

Search for “Digital Humanities” in Tableau Public

3 Easy Steps to Make Graphs

Add Image of Google Maps and OpenStreetMap as Background Images in Tableau

U.S. Census Bureau Vizzes

In this tutorial, we will look at a few advanced graphs that go beyond the show me feature in Tableau.

Tableau is a great tool for data analysis and visualization. It has some powerful tools to make the visualizations appealing and interactive. The Show Me feature can be used to apply a required view to the existing data in the worksheet. Those views can be a pie chart, a line graph, a scatter plot, or a simple map. Whenever a worksheet with data is created, it is available in the top right corner as shown in the following figure. Some of the view options will be greyed out depending on the nature of selection in the data pane.

One such awesome feature is animated data visualization.

The contains resources to help people visualize and analyze the most recent data on the coronavirus outbreak.

In this tutorial, we will learn:

1. How to connect data to Tableau

2. How to create worksheets

3. How to create an interactive dashboard

4. How to save and publish your visualization

Download the Data

In this tutorial, we will work the COVID-19 data from the European Centre for Disease Prevention and Control website.

Data preview in Excel:

The data fields are described below:

Connect to Data Source

Startup Tableau desktop, you will get the start page showing various data sources. Under the “Connect” on the left side of the screen, you have options to connect to a file or server data source. Under to a File, choose Text file. Then navigate to the CSV file you just download from the last step:

Creating Views and Analysis

At the bottom of the Tableau desktop, click on a sheet (sheet 1) and you will see the following screen:

Tableau automatically separates the data into Dimensions and Measures. Dimensions are the categorical fields. Measures are the quantitative fields, such as death count, positive cases count

We will create a bar chart tracking number of new positive cases per day. Drag “People Positive New Cases” from Measures and drop it into the “Rows” section. Drag" Report Date" from Dimensions to "Columns". Select “Days” from the shortcut menu.

Note that it defaults to YEAR(Date). To format how the date is displayed, right-click on YEAR(Date) and select Day, specifically the option that has the example "8th May, 2015".

We can also add some filters to the bar chart so that a user could filter to see a certain country or date range. From Dimensions, drag Country Short Name to the Filters shelf. Click on All and then OK.

Next, right-click on the Country Short Name on the Filters shelf and select Show Filter. Now you will see a list of countries on the right.

Double click on Sheet 1, rename the worksheet title to "New Positive Cases"

Next, we will create a map. First, open a new workbook, double click "Country Short Name", Tableau has placed the longitude and latitude coordinates in the columns and rows, respectively, a point map will show on the design canvas.

Drag and drop "People Positive Cases Count" to Size under Marks.

Double click on Sheet 2, rename the worksheet title to "New Positive Cases by Country"

Now we will create the third worksheet, open a new worksheet.

We’ll create a vertical bar chart tracking confirmed case per country.

Drag “People Positive Cases Count” from measures and drop it into the “Columns” section. Drag Country Short Name from Dimensions to "Measures".

Go to the bottom of the chart and click on the sorting icon. Sort the number of positive cases in descending order.

Go to Marks, you customize the chart color by using the color pilates.

Name the worksheet “Positive Cases by Country.”

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Create an interactive dashboard

Let’s create a dashboard to pull all of these visualizations together. The dashboard will combine our three visuals we have made in the previous steps. Click on the new dashboard icon at the bottom of the page to create a new dashboard.

Our three worksheets are on the left. Drag “worksheet 1" into the drop area on the right.

Combine 3 worksheets:

In this tutorial, you will learn how to install Google Colab in your Google Drive, and use Colab to perform a number of data tasks including:

Exemplar data: COVID-19 case and death data (date: 202012006)

Bar Chart

Tutorial:

Line Chart

Scatter Plot Chart

Simple calculation using Pandas

Descriptive statistics

Extract a subset by columns and rows

Data aggregation

Google Colab Installation

Step 1: Go to your Google Workspace Marketplace and search for "colab"

Step 2: Locate "Colaboratory" and click add to drive

Step 3: Access Colab as using a regular Google doc

Basic Layout in Google Colab

Export data to csv file to local directory

from google.colab import files
df.to_csv('FILENAME.csv') 
files.download('FILENAME.csv')  #Download winder pops out

Export data to CSV file to Google Drive

from google.colab import drive
drive.mount('/content/drive')  #Copy and paste Google Authentication code
df.to_csv('/content/drive/PATH TO Google Drive FOLDER')

Export plot image to local directory

#Export bar chart
bar_image = bar_2.get_figure().savefig('bar_image.png')
from google.colab import files
files.download('bar_image.png')  #Download window pops out

#Export line chart
line_image = line_1.get_figure().savefig('line_image.png')
from google.colab import files
files.download('line_image.png')  #Download window pops out

#Export scatter plot chart
scat_image = scatter.get_figure().savefig('scatter_image.png')
from google.colab import files
files.download('scatter_image.png')  #Download window pops out

Step 1: Navigate to https://datastudio.google.com/overview

Step 2: Click on "use it for free button

Step 3: Sign in with your Google account and password. You should now see the home page of the Data Studio

Step 4: click on 'Create' button on the top left:

Step 5: Click on 'data source'

Step 6: Find and Click on Google sheet connector

Step 7: Find and Click on the Google sheet

Step 8: Once you select the worksheet, there are still some decisions to make. You have three options:

1. Use the first row as headers. Selected by default. Does what it says on the tin.

2. Include hidden and filtered cells. Selected by default. If you want to keep data out of Data Studio by hiding its columns in Google Sheets, deselect this.

3. An optional range of cells containing your data. Data Studio looks at the entire worksheet by default. If your table lies in a certain range, specify that here.

Step 9: Click “Connect” to give Data Studio access to the Sheet:

Step 10: You should now see a screen like the one below. Next we need to help Data Studio understand what kind of data you’ve given it.

All the green fields represent dimensions (fields that can be counted) and all the blue fields represent metrics, usually categorical data. See the documentation for dimensions and metrics.

Step 11: Google Data Studio doesn't always determine the correct data type for each field. so you need to make sure that each field is of the correct data type.

Step 12: Create calculated fields (optional)

Data Studio allows you to add custom fields to a data sources. So instead of adding all sorts of columns and formulas to your sheet, you can add them to your data source. That’s great because you can add calculated fields on the fly, without modifying your source data. Your new fields will be accessible in any reports that use this data source.

Step 13: Once everything looks right then click on the "create report" button, this will create an empty report with your Google Sheets data source connected to it:

Step 14: Charts in this report will use your new data source by default. Now you’ve got a data source and report to work with. The rest is up to you!

Toolbar

At the top of the page you can see a toolbar where you can find different options for creating a report.

Pages, names

First of all, your report needs a title. You can simply name it at the top left corner and the changes will be automatically saved. Then you can add multiple pages to the report which you can also name and easily switch between them.

Types of data visualization

The next part of the toolbar is the data visualization tools. You can select the graph type you want to build.

For example, a bar chart requires you to select one dimension and at least one metric. If you add multiple metrics, you will see multiple bars for each category.

Inserting text and images

You can insert text, images, rectangles, and circles to the report depending on your purpose.

Selecting layout and theme

Layout and theme give you the possibility to play with the style of your report. You can change the background, colors, text styles, and display options and create a unique style that can represent the style of your company.

Styling and controlling menu

Styling and controlling menu is a great help in the process of creating a report. You can select the chart type, experiment with metrics and dimensions, change data sources, apply a filter, etc.Now let’s switch between view and edit mode to see how our sample report looks like:

Sharing the visualization

You can do a few things with the share feature. You can collaborate on the visualization with your team or clients. Depending on their level of access, they can view or edit the reports through an invitation or a shared link.

The visualizations also can be shared by embedding them into online and offline content, from websites and blog posts to annual reports.

Create New report on Airbnb Boston reviews

To create a new report from scratch, a portion of the has been uploaded into a to be used as data source for Google Data Studio.

• the full Kaggle dataset of the Airbnb reviews in Boston is available at

• the Google Sheets, with approximately 10k reviews, to be used as data source is available at

• Spend some time to understand the data by reading their description on Kaggle and looking at the table on Google Sheets.

• The data-source table has been created by joining the “Listings” and “Reviews” original tables provided by Kaggle, and exporting the first 10k joined rows sorted by ascending “listing_id”.

Create a new report

• Go to the Data Studio home page

• Click on “Start a new report” (Blank)

• Rename the “Untitled Report” with a name of your choice by clicking on the name itself

• Create a new data source by clicking on the blue button on the bottom right, or select the Airbnb data source if it is already present in the right-pane list

Connect to the Google Sheet data source by using its URL:

• Choose the “Google Sheets” connector in the list of connectors on the left

• Choose the “URL” option in the first column

• Choose the “Reviews Query DW” worksheet in the next column

• Tick the option to “use the first row as headers” if it is not ticked yet

• Click on the “Connect” button to execute the connection to the data source

Dimensions, metrics, and transformations

• Check the type and aggregation of each field and that all the fields are correctly interpreted as either dimension or metric.

• • CONCAT(latitude, CONCAT(', ', longitude)) → to generate a (lat, long) field useful for map charts; before generating this new field, set “Aggregation=None” for latitude and longitude fields, so that they become dimensions (by default, Data Studio considers them as metrics)

After creating new fields and updating the existing ones, click on “Add to report”

Analyze the data

Analyze the data by building the following visualizations. Then, explore and create new visualizations to find interesting insights on your own.

• Analysis (1): Number of Records over time

Analysis (2):

• analyzing the number of different reviewers for each (lat, long) locationnote that the Kaggle dataset of the Airbnb reviews is in Boston, Massachusetts, US

Allow end-users to filter the data under analysis by selecting a date range and city name.