Course Template
Data Science Toolbox – Climate Data & City Analysis
Analysis and Visualization of Climate Data with Python Libraries such as pandas, numpy, and matplotlib.
Didactic Objective
This course template introduces structured steps for data analysis with Python. The focus is on Importing and Structuring Data Sets, Statistical Evaluation of Climate Data, and their graphical interpretation. The individual modules represent the typical workflow of modern data analysis – from data preparation to analysis, visualization, and simple predictive models. This supports competency development in data-based modeling and analysis within the field of data handling.
Competency Focus
- Importing and Structuring Climate Data from CSV Files with pandas
- Calculating statistical measures such as mean, median, standard deviation, and range using numpy
- Visualizing time series and data distributions with matplotlib
- Transformation of Data Sets into JSON Structures and Storage via REST APIs
- Analysis of Database Data by Converting JSON to pandas DataFrames
- Investigation of Connections and Subsets of Data Sets through Filtering and Comparison Analyses
- Creation of Simple Forecast Models with Linear Regression for Analyzing Long-Term Temperature Trends
Structure of Modules
Visualizing Climate Data from CSV
Introduction to Loading Climate Data Sets from CSV Files, Their Statistical Evaluation, and Visualization of Temperature Time Series with matplotlib.
Analyzing Temperature Statistics with NumPy
Statistical Analysis of Temperature Data through Calculation of Central Values and Comparison of Dispersion between Multiple Cities.
Storing Climate Data in User-DB
Building a Simple Data Pipeline by Converting CSV Data to JSON and Storing the Data Sets via a REST API in a Database.
Analyzing Climate Data from User-DB
Stored climate data retrieval via REST interface, conversion to DataFrames, and statistical analysis with subsequent visualization.
Enhanced climate data visualization
Analysis and graphical representation of climate data with various diagram types to investigate time series and relationships.
Temperature trend with Linear Regression
Introduction to machine learning fundamentals through training a linear regression model for analyzing long-term temperature trends.
The clearly structured modules enable a step-by-step introduction to data analysis, statistical evaluation, and visualization and can be flexibly integrated into lesson series.
Use the demo access to test the template and adapt individual analysis or visualization steps to your learning group.