https://github.com/kisaa-fatima/data-visualization-with-tableauleu
Conducted Exploratory Data Analysis (EDA) on the Berkeley Earth Dataset (large scale dataset), which features high-resolution land and ocean time series data. Created interactive dashboards using Tableau to effectively visualize and highlight trends and patterns within the data.
https://github.com/kisaa-fatima/data-visualization-with-tableauleu
data-analysis data-science exploratory-data-analysis insights python tableau visualizations
Last synced: about 2 months ago
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Conducted Exploratory Data Analysis (EDA) on the Berkeley Earth Dataset (large scale dataset), which features high-resolution land and ocean time series data. Created interactive dashboards using Tableau to effectively visualize and highlight trends and patterns within the data.
- Host: GitHub
- URL: https://github.com/kisaa-fatima/data-visualization-with-tableauleu
- Owner: Kisaa-Fatima
- Created: 2024-01-23T16:02:25.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-02-04T17:56:47.000Z (over 1 year ago)
- Last Synced: 2025-02-17T16:41:32.023Z (over 1 year ago)
- Topics: data-analysis, data-science, exploratory-data-analysis, insights, python, tableau, visualizations
- Language: Jupyter Notebook
- Homepage:
- Size: 10.9 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
Introduction:
Exploratory Data Analysis (EDA) is a crucial step in the data analysis process, aimed at understanding and deriving insights from datasets. In this assignment, you will work with the Berkeley Earth dataset, which provides high-resolution land and ocean time series data and gridded temperature data. This dataset offers a comprehensive collection of temperature observations and is essential for understanding climate trends.
Dataset Description:
The Berkeley Earth dataset offers global, national/regional, and local-level temperature and climate data. It includes temperature observations, often with better coverage than other products, and spans from 1850, with some land-only areas reported back to 1750. The dataset also incorporates machine learning techniques to improve spatial resolution.
Tasks to Perform:
Performed exploratory data analysis (EDA) on the Berkeley Earth dataset, focusing on a specific region ie US. In addition to the Berkeley Earth dataset, download two more time series datasets related to your chosen region. These additional datasets can cover a wide range of topics such as economics, forex data, bike usage, taxi data, or any other relevant area. I have uploaded additional datasets as well.
1. Region Selection: Choose a specific region (e.g., a country or city) as your focus area for analysis.
2. Data
Download: Download the Berkeley Earth dataset and two additional time series datasets related to your chosen region. Clearly state
the sources of these datasets.
3. Exploratory Data Analysis: Perform EDA on the Berkeley Earth dataset to understand climate trends over time. Analyze temperature patterns, seasonal variations, and long-term trends. Additionally, conduct inter-dataset EDA between the Berkeley Earth dataset and the other two datasets to explore correlations and patterns.
4. Dashboard Creation: Create a minimum of TWO Tableau stories, with each story containing multiple dashboards. Each story should address specific research questions and insights derived from your analysis.
5. Beautiful Dashboard Designs: Emphasize creating aesthetically pleasing dashboards with thoughtful design elements.
6. Compelling and Insightful Visual Storytelling : Use Tableau's storytelling feature to create compelling visual stories for each research question. These visual stories should guide the user through your analysis process, highlight key insights, and provide explanations for the visualizations.
7. Documentation: Create a PDF document that outlines the questions you addressed, the rationale behind your analysis, and your overall analytical process. Clearly reference the datasets used.
Short steps: use Tableau
1. Data download
2. Quality of exploratory data analysis
3. Beautiful dashboard designs
4. Compelling and insightful visual storytelling
5. Documentation