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A PySpark utility package for sales data analysis and visualization

Project description

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.

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