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Finance Visualizer

A robust and flexible Command Line Interface (CLI) tool designed to automate the generation of charts from CSV data. It scans directories for CSV files based on configurable patterns, aggregates data, and generates Line or Bar charts using matplotlib.

🚀 Features

  • Recursive File Scanning: Uses glob patterns (e.g., data/**/*.csv) to find files in nested directories.
  • Flexible Aggregation:
    • Group data by specific columns (e.g., Year, Category).
    • sum specific columns or calculated totals of multiple columns.
  • Chart Types: Supports Line and Bar charts.
  • Batch Processing: Define multiple configuration sets in a single JSON file to process different datasets simultaneously.
  • Automatic Output: Saves generated charts as .png files directly alongside the source CSVs.

📦 Installation & Requirements

  1. Clone the repository (or download the source code).
  2. Install dependencies: 
    pip install -r requirement.txt

Required dependencies:

  • Python 3.x
  • pandas
  • matplotlib

🛠️ Usage

Run the tool from the command line by providing the path to your configuration JSON file:

python main.py --config config.json

Configuration

The tool is driven by a JSON configuration file. The file should contain a list of configuration objects.

Configuration Options

Key Type Description
directory string The glob pattern to search for CSV files. Supports ** for recursive search.
columns string or list The column name(s) to plot on the Y-axis. If a list is provided, the tool sums the values of these columns for the plot.
groupby string or list The column name(s) to group data by (X-axis).
chart_type string The type of chart to generate. Options: "line" or "bar".
chart_label string (Optional) Custom label for the chart legend/Y-axis.

Example config.json

[
  {
    "directory": "data/finance/**/*.csv",
    "columns": ["Income", "Dividends"],
    "groupby": "Year",
    "chart_type": "bar",
    "chart_label": "Total Revenue"
  },
  {
    "directory": "data/expenses/*.csv",
    "columns": "Amount",
    "groupby": "Category",
    "chart_type": "line"
  }
]

Example Scenario

Input File: data/2023_financials.csv

Year Category Salary Bonus
2023 Tech 50000 5000
2023 Tech 52000 6000
2024 HR 48000 4000

Config:

{
  "directory": "data/*.csv",
  "columns": ["Salary", "Bonus"],
  "groupby": "Year",
  "chart_type": "bar",
  "chart_label": "Total Compensation"
}

Result: The tool will:

  1. Read data/2023_financials.csv.
  2. Sum Salary + Bonus into a calculated total.
  3. Group by Year (summing the totals for 2023).
  4. Generate a Bar chart named 2023_financials_Year_bar.png in the data/ folder.