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https://github.com/pxaris/expenditure-analyzer


https://github.com/pxaris/expenditure-analyzer

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README 

        

# Expenditure Data Analysis



This repository contains scripts to analyze expenditure data, generating categorized reports and visualizations of financial transactions over time. The analysis outputs a summary report and visualizations for easy data interpretation.



## Docker Installation and Usage



You can use Docker to run the analysis script without needing to install dependencies directly on your machine.



Clone the repository:

   ```bash

   git clone https://github.com/pxaris/expenditure-analyzer.git

   cd expenditure-analyzer

   ```



### Step 1: Build the Docker Image



In the root directory of this repository, build the Docker image:



```bash

docker build -t expenditure-analyzer .

```



### Step 2: Run the Analysis with Docker



To analyze expenditure data, place your CSV file in the `data/` directory, then specify the `--data_filename` with the following Docker command:

```bash

docker run --rm -v $(pwd)/data:/app/data -v $(pwd)/report:/app/report expenditure-analyzer --data_filename 'sample_data.csv'

```



This command:



- Mounts the `data` directory to `/app/data` in the container, so it can access the specified at `--data_filename` CSV file.

- Mounts the `report` directory to `/app/report` in the container, where it will save the generated reports and figures.



### Step 3: View the Results



After the analysis completes, you can find the output in the `report/` directory:



- **Report**: The `report.txt` file provides a summary of the analyzed expenditure data, including the total and average expenditures, breakdowns by category, and insights by month.

- **Figures**: The generated figures, including bar charts of monthly expenditures and pie charts showing expenditure distribution by category, are also saved in the `report/` directory.



These outputs offer a comprehensive view of your spending patterns, making it easier to understand and interpret your financial data over time.



---



## Manual Installation and Usage



To get started, install the required Python packages. It's recommended to use a virtual environment.



### Requirements Installation



1. Clone the repository:

   ```bash

   git clone https://github.com/pxaris/expenditure-analyzer.git

   cd expenditure-analyzer

   ```



2. Install the required packages:

   ```bash

   pip install -r requirements.txt

   ```



### Usage



To analyze expenditure data, follow these steps:



#### Step 1: Configure Default Variables



Open the `config.py` file and set the following default configuration variables if needed:



- `DATA_FILENAME`: Name of the default CSV file containing transaction data, e.g., `'sample_data.csv'`.

- `N_SKIPROWS`: Number of rows to skip at the beginning of the CSV file, typically for headers or additional info, e.g., `6`.

- `CSV_DELIMITER`: The delimiter used in the CSV file, e.g., `';'`.

- `DATE_COLUMN`: Name of the column in the CSV file containing transaction dates, e.g., `'Ημ/νία συναλλαγής'`.

- `EXPENDITURE_COLUMN`: Name of the column with expenditure amounts, e.g., `'Ποσό (EUR)'`.

- `EXPENDITURE_CATEGORY_COLUMN`: Name of the column categorizing expenditures, e.g., `'Κατηγορία δαπάνης'`.

- `CURRENCY`: Currency symbol to display in the report, e.g., `'€'`.



#### Step 2: Run the Analysis



You can override the default `DATA_FILENAME` and `REPORT_DIR` values directly from the command line.



##### Basic Usage

To use the default values specified in `config.py`, simply run:

```bash

python analyze.py

```



##### Custom Usage

To specify a different data file or report directory, use the following arguments:

```bash

python analyze.py --data_filename 'custom_data.csv' --report_dir 'custom_report_dir'

```



This will process the specified input data, perform analysis, and generate reports and visualizations in the designated report directory.



#### Step 3: View the Results



After the analysis completes, the **Report** and the **Figures** will be located in the `report/` directory (or the directory specified in `--report_dir`).



---



## Additional Information



- **Sample Data**: A sample CSV file is included to demonstrate the format required for analysis. It follows the rationale of an exported data file from a Greek bank and the respective analysis can be found in the `sample_report/` directory.

- **Customization**: Modify `config.py` and adjust the `analyze.py` and `utils.py` scripts as needed to fit different datasets or specific analysis requirements.



Enjoy analyzing your expenditure data!