summerofgeorge

#Optimal production quantities for products A and B
import pandas as pd
from scipy.optimize import linprog

# Coefficients for the objective function (negative for maximization)
c = [-40, -30]
# Coefficients for the inequality constraints
A = [
    [2, 4],   # Labor constraint
    [3, 2]    # Material constraint

summerofgeorge

A supplier must ship goods from two warehouses (W1 and W2) to three retail stores (S1, S2, and S3).

Shipping cost per unit:
W1 → S1 costs 4
W1 → S2 costs 6
W1 → S3 costs 8
W2 → S1 costs 5
W2 → S2 costs 4
W2 → S3 costs 7

summerofgeorge

A factory produces three products: A, B, and C.

Profit per unit:
A earns 25 profit.
B earns 40 profit.
C earns 35 profit.

Resource usage per unit:
Each unit of A uses 1 labor hour and 4 units of material.
Each unit of B uses 3 labor hours and 3 units of material.

summerofgeorge

A company produces two products, A and B.

Profit per unit of A is 40.
Profit per unit of B is 30.

Each unit of A uses 2 labor hours and 3 units of material.
Each unit of B uses 4 labor hours and 2 units of material.

The company has 100 total labor hours available.
The company has 90 total material units available.

summerofgeorge

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      "text": "Car Fuel Efficiency Summary",
      "weight": "Bolder",
      "size": "Medium"
    },

summerofgeorge

You are an AI data analyst. Summarize insights from the following dataset about car fuel efficiency:  
autompg.autompg
 



The dataset includes the following columns: mpg, cylinders, displacement, horsepower, weight, acceleration, model.year, and origin.

summerofgeorge

You are an AI data analyst. Summarize insights from the dataset autompg.autompg, which contains information about car fuel efficiency.

The dataset includes the following columns: mpg, cylinders, displacement, horsepower, weight, acceleration, model year, and origin.

Analyze the data and describe:

• The overall average miles per gallon (mpg).
• How mpg has changed over time.
• The relationship between vehicle weight and mpg (for example, whether it’s positive, negative, or none).
• Differences in fuel efficiency across cylinder counts.
• Differences in efficiency by vehicle origin.

summerofgeorge

function main(workbook: ExcelScript.Workbook) {
    // Get the 'sales' table
    const table = workbook.getTable("sales");
    const dataRows = table.getRangeBetweenHeaderAndTotal().getValues();
    const headers = table.getHeaderRowRange().getValues()[0] as string[];

    // Identify column positions
    const colRegion = headers.indexOf("Region");
    const colUnits = headers.indexOf("Units Sold");
    const colPrice = headers.indexOf("Unit Price");

summerofgeorge

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  "body": [
    {
      "type": "TextBlock",
      "text": "📊 **Excel KPI Summary**",
      "wrap": true,
      "size": "Large",

summerofgeorge

You are an AI data analyst. Analyze the following sales data and write a concise, professional summary for posting in Microsoft Teams. Focus on key trends and performance insights.

Sales data columns: Date | Region | Salesperson | Product Category | Units Sold | Unit Price | Customer Type | Channel

Tasks:

1. Calculate total revenue by multiplying Units Sold * Unit Price.
2. Identify which region and salesperson had the highest total revenue.
3. Highlight the top-performing product category.
4. Note any differences in performance between Corporate vs. Individual customers.