geeksales 0.1.1

A PySpark utility package for sales data analysis and visualization

GeekSales

A powerful PySpark utility package for sales data analysis and visualization.

Features

• Create and configure Spark sessions with optimized settings
• Calculate sales metrics and aggregations
• Generate comprehensive sales dashboards
• Create various sales visualizations:
  • Sales by region
  • Customer order distribution
  • Sales trends over time
  • Top products by sales

Installation

pip install geeksales

Usage

from geeksales import spark_utils

# Create a Spark session
spark = spark_utils.create_spark_session("Sales Analysis")

# Load your sales data
df = spark.read.csv("sales_data.csv", header=True, inferSchema=True)

# Add sales metrics
df_with_metrics = spark_utils.add_sales_metrics(df)

# Generate sales summary
summary = spark_utils.get_sales_summary(df_with_metrics)

# Create visualizations
spark_utils.plot_sales_by_region(df_with_metrics)
spark_utils.plot_customer_order_distribution(df_with_metrics)
spark_utils.plot_sales_trend(df_with_metrics)
spark_utils.plot_product_sales(df_with_metrics)

# Create a complete dashboard
dashboard = spark_utils.create_sales_dashboard(df_with_metrics)

Requirements

• Python 3.7 or higher
• PySpark 3.0 or higher
• Matplotlib 3.0 or higher
• Seaborn 0.11 or higher
• Pandas 1.0 or higher

License

This project is licensed under the MIT License - see the LICENSE file for details.