This project is named as Global Inflation Analyzer (GIA). It is a python library, and written to give a comprehensive analysis of inflation rate. The library can be used to perform analysis based on a given dataset with the classification standard of classification of individual consumption by purpose (COICOP 2-5-digit hierarchy).
With the dataset contained data about consumer price index for group of products and services, the library will analyze the following main questions or features:
1. How much has inflation changed during the given range of years?
2. In what amount, inflation recorded after or before specific year (e.g. COVID-19 or UKRAIN WAR)?
3. Which group of products or services is highly affected after specific year?
4. In which year was high inflation recorded?
5. What is the inflation rate of a specific products or services globally?
6. What is the inflation rate of a specific products or services group (specific Country)?
Install Global_Inflation_Analyser and go to root folder:
git clone https://gitup.uni-potsdam.de/kar/global_inflation_analyser
cd global_inflation_analyser
After you downloaded our repository, make sure you have Python installed and all the dependencies needed for the project.
Make sure you are in the folder containing the software. Check it running pwd in terminal. it should end in global_inflation_analyser
If you are using conda, you can download all the dependencies, while being in the root folder, with the following command:
conda install -e .
Otherwhise, for installing it with pip, run:
pip install -e .
After you have moved yourself in the repository where you saved the project. You will notice that you have three classes provided to you: preprocessor, analysis and the plotter class. With the Preprocessor class the provided data will be cleaned and filtered to your User needs. The Analysis class calculates the Inflation rate of the given data set and merge all products inflation rate of a given country for specific period of time. The plotter class provides plots with the previous analysed data. Generally if you want to use the Project we would recommend to use the provided Jupyter Notebook and to run all the cells in their given order. While running the cells you will notice you need to choose your data set and the years you want. After you executed the plotting part, your results will be saved in the results directory where you can look up all the plots.
The second option that you have is to run the separate python files one after another. It means you would run the preprocessor.py. Please be aware you need to be in the directory where the code actually is. So if you are for example in global_inflation_analyser:
# Moving to the Directory
cd global_inflation_analyser
# Displaying the help
python preprocessor.py -h
# Example: Specify product name
python preprocessor.py -p Education
# Example: Specify product name and list of countries
python preprocessor.py -p Education -c Germany France Italy
# Example: Specify product name, list of countries, and time period
python preprocessor.py -p Education -c Germany France Italy -t Jan_2010 Dec_2012
After that you would run the analysis.py.
# Displaying the help
python analysis.py -h
# Example:
python analysis.py -p Education -c Germany France Italy -t Jan_2023 Dec_2023
And in the End the plotter.py.
# Displaing the help
python plotter.py
# Example:
python plotter.py -p "productname" -c "country1" "country2" -t "Jan_2021" "Dec_2022" -a "product"
After that you should be again able to look up the plots in the results directory.
- Comparison Table
- Line Plot Diagramm
- Bar Plot Diagramm
- Boxplot Diagramm
- Dataset can be adjusted
- Years adjustable
- Product adjustable
Please see Global Inflation Analyzer documentation for more information.
Our code of conduct can be found in the code of CONDUCT.md file in the global_inflation_analyser repository.
Contributions are always welcome, if you want to find out how to contribute to the Project read the CONTRIBUTING.md.
Distributed under the GNU GENERAL PUBLIC LICENSE. See LICENSE.txt for more information.
If you have any question regarding this library, please feel free to get in touch with us:
We would like to thank the whole Group and the University of Potsdam for the Opportunity to work on such a project and give us the needed knowledge in order to make such a project.