https://github.com/ndomah1/learning-tableau
This repo offers a comprehensive tutorial on Tableau, guiding users through installation, dataset connection, visualization creation, join techniques, and the use of calculated fields and bins for effective data analysis.
https://github.com/ndomah1/learning-tableau
bins business-intelligence calculated-fields data-analysis data-visualization data-viz join tableau
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This repo offers a comprehensive tutorial on Tableau, guiding users through installation, dataset connection, visualization creation, join techniques, and the use of calculated fields and bins for effective data analysis.
- Host: GitHub
- URL: https://github.com/ndomah1/learning-tableau
- Owner: ndomah1
- Created: 2025-03-20T22:29:11.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2025-03-20T22:56:47.000Z (about 1 month ago)
- Last Synced: 2025-03-20T23:28:36.446Z (about 1 month ago)
- Topics: bins, business-intelligence, calculated-fields, data-analysis, data-visualization, data-viz, join, tableau
- Homepage:
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- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Learning Tableau
## Table of Contents
- [Installing Tableau and Creating Your First Visualization](#installing-tableau-and-creating-your-first-visualization)
- [Installing Tableau Public](#installing-tableau-public)
- [Connecting to a Dataset](#connecting-to-a-dataset)
- [Creating Basic Visualizations](#creating-basic-visualizations)
- [Using Joins in Tableau](#using-joins-in-tableau)
- [Understanding Joins vs. Relationships](#understanding-joins-vs-relationships)
- [Types of Joins in Tableau](#types-of-joins-in-tableau)
- [Creating Visualizations](#creating-visualizations)
- [Common Charts in Tableau](#common-charts-in-tableau)
- [Using Calculated Fields and Bins](#using-calculated-fields-and-bins)
- [Bins](#bins)
- [Calculated Fields](#calculated-fields)
- [Summary](#summary)
## Installing Tableau and Creating Your First Visualization
### Installing Tableau Public
- Tableau Public is a free version of Tableau with limited features but ideal for learning and portfolio building.
- Steps to install:
1. Download from Tableau Public's official website: https://www.tableau.com/products/public
2. Provide an email and install the application.
3. Open Tableau Public and navigate the interface.
### Connecting to a Dataset
- Use the **Video Game Sales** dataset from Kaggle for practice: https://www.kaggle.com/datasets/gregorut/videogamesales
- Load the dataset by selecting **Text File** in Tableau.
- Tableau automatically categorizes data types (numeric, text, date).
### Creating Basic Visualizations
- **Line Chart:**
- Import the video game sales CSV into Tableau Public and open a new worksheet.
- Drag the `Global Sales` measure onto the Rows shelf and the `Year` dimension onto the Columns shelf to create a basic line graph.
- Add the `Genre` dimension to the Marks card under Color to visually differentiate each game genre.
- Include labels for min and max values along the lines to provide additional context.
- **Genre Sales Chart:**
- Open another worksheet to focus on overall sales by game genre.
- Set `Genre` as your primary dimension and `Global Sales` as the measure.
- Use the sorting feature to organize the data and assign distinct colors to each genre for clarity.
- Finally, combine these worksheets into a dashboard for a comprehensive view.
## Using Joins in Tableau
Download excel file: https://github.com/AlexTheAnalyst/PortfolioProjects/blob/main/Tableau%20Joins%20File.xlsx
### Understanding Joins vs. Relationships
- Tableau uses **Relationships** by default, which dynamically infer joins based on data.
- **Joins** allow more control over how tables merge.
### Types of Joins in Tableau
- **Inner Join:** Includes only matching records between tables.
- **Left Join:** Includes all records from the left table and matches from the right.
- **Right Join:** Includes all records from the right table and matches from the left.
- **Full Outer Join:** Includes all records from both tables.
## Creating Visualizations
Download this dataset: https://www.kaggle.com/datasets/starbucks/store-locations
### Common Charts in Tableau
- **Bar and Line Graphs:** Combine bars and lines for comparative sales analysis.
- **Maps:** Use geographic data (longitude/latitude) to create density or filled maps.
- Import **Starbucks store locations** dataset.
- Drag `Latitude` and `Longitude` into **Columns** and **Rows**.
- Use **State** or **Postal Code** as a level of detail.
Store location density by zipcode.
- **Scatter Plots:** Compare two numeric fields to analyze correlations.
## Using Calculated Fields and Bins
### **Bins**
- Bins group numeric data into defined ranges (e.g., 1990–1994, 1995–1999).
- To create bins, right-click a numeric field (such as `Year`) and select **Create → Bins**, then choose a bin size (e.g., 5).
- Bins turn continuous numeric values into categories, making it easier to compare grouped data (for instance, total sales per 5-year range).
- You can exclude null or unwanted values from the view if needed (e.g., by right-clicking on null bars and selecting **Exclude**).
### **Calculated Fields**
- Calculated fields let you build new measures or dimensions from existing data (e.g., `[Global Sales] - [EU Sales]`).
- To create one, click the dropdown next to a field, choose **Create → Calculated Field**, then enter your formula.
- Quick table calculations (like “Percent of Total”) are built-in options, and you can drag them into the data pane to save them as custom fields.
- Use calculated fields to perform basic arithmetic, combine fields, or handle more complex logic, depending on your analysis needs.
## Summary
These tutorials provide a foundational understanding of Tableau, covering installation, joins, visualization types, and calculations. For a deeper understanding, practicing with real-world datasets and different chart types is recommended.