monkstools 0.10

Tools for the Monks advertising platform

monkstools

monkstools for team

begin to work. by Xiaowen kang. 2023.8.24. check . well done. by xiaowen kang. 2023.8.24 prepare for pypi package. by xiaowen kang. 2023.8.24.

README.md

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monkstools: Advertising Delivery ROI Analysis Framework

monkstools is a Python module designed to analyze and visualize the Return on Investment (ROI) of product advertising across different platforms. It provides insights into which platform might yield the highest returns for advertising a particular product. While this framework is provided for demonstration purposes, the actual results in a production setting would be based on in-depth model training and real-world data.

Overview

The primary goal of monkstools is to serve as a platform for programmers and data analysts to discuss, share, and collaborate on analyzing the ROI of advertising delivery. It's a template to kick-start discussions and exchange ideas on the intricacies of advertising dynamics across different platforms for various products.

Key Components

1. ProductPreference Class

• Purpose: Retrieve product preference values for specified products and customer types.
• Primary Method: get_preference(product_name, customer_type, verbose=False)

2. TransmissionCost Class

• Purpose: Fetch transmission cost values for designated platforms and customer types.
• Primary Method: get_cost(platform_name, customer_type, verbose=False)

3. ROICalculator Class

• Purpose: Compute and visualize ROIs.
• Primary Methods:
  • calculate(product_name, platform_name, verbose=False): Computes the ROI for a given product and platform.
  • display_roi_matrix(roi_calculator, products, platforms): Visualizes the ROI matrix.

Usage Guide

1. Initialization

First, you need to initialize the ROICalculator object, which, in turn, initializes the ProductPreference and TransmissionCost objects.

preference_file = 'path_to_preference_file.csv'
cost_file = 'path_to_cost_file.csv'
roi_calculator = ROICalculator(preference_file, cost_file)

2. Setting Up Products and Platforms

Define the list of products and platforms you're interested in analyzing.

products = ['Example Product 1', ...]  
platforms = ['Example Platform 1', ...] 

3. Displaying the ROI Matrix

Use the display_roi_matrix method of the ROICalculator class to compute and showcase the ROI matrix.

ROICalculator.display_roi_matrix(roi_calculator, products, platforms)

4. Debugging and Logging

Set verbose=True when calling methods to print additional debugging and logging information.

Note

This framework is intended for team discussions and sharing. The specific functions and data here are examples, and in a real-world scenario, deeper model training would be necessary. The final outcome is contingent on actual data and post-deep-training results. This is merely a conceptual framework and thought process to facilitate programmers' exchange of ideas.

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To leverage this library, ensure monkstools is installed and data provided matches expected formats.

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xiaowen kang. 2023.8.23