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| title: "6. Data Analysis" | |
| original_url: "https://tds.s-anand.net/#/data-analysis?id=data-analysis" | |
| downloaded_at: "2025-06-08T23:26:37.046522" | |
| [Data analysis](#/data-analysis?id=data-analysis) | |
| ================================================= | |
| [Data Analysis: Introduction Podcast](https://drive.google.com/file/d/1isjtxFa43CLIFlLpo8mwwQfBog9VlXYl/view) by [NotebookLM](https://notebooklm.google.com/) | |
| Once you’ve prepared the data, your next task is to analyze it to get insights that are not immediately obvious. | |
| In this module, you’ll learn: | |
| * **Statistical analysis**: Calculate correlations, regressions, forecasts, and outliers using **spreadsheets** | |
| * **Data summarization**: Aggregate and pivot data using **Python** and **databases**. | |
| * **Geo-data Collection & Processing**: Gather and process geospatial data using tools like Python (GeoPandas) and QGIS. | |
| * **Geo-visualization**: Create and visualize geospatial data on maps using Excel, QGIS, and Python libraries such as Folium. | |
| * **Network & Proximity Analysis**: Analyze geospatial relationships and perform network analysis to understand data distribution and clustering. | |
| * **Storytelling & Decision Making**: Develop narratives and make informed decisions based on geospatial data insights. | |
| [](https://youtu.be/CRSljunxjnk) | |
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| Correlation with Excel](#/correlation-with-excel) |