How to use ChatGPT for Business Insight and Analytics Manager Job Role

python

import matplotlib.pyplot as plt
import pandas as pd

# Sample data
categories = ['Product A', 'Product B', 'Product C']
sales = [15000, 23000, 18000]

# Create a bar chart
plt.bar(categories, sales, color=['blue', 'orange', 'green'])
plt.title('Sales by Product')
plt.xlabel('Product')
plt.ylabel('Sales ($)')
plt.show()

python

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error

# Load the dataset
data = pd.read_csv('sales_data.csv')

# Define features and target variable
X = data[['feature1', 'feature2', 'feature3']]  # Replace with actual feature names
Y = data['sales']

# Split the data into training and testing sets
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2, random_state=42)

# Create and train the model
model = LinearRegression()
model.fit(X_train, Y_train)

# Make predictions
predictions = model.predict(X_test)

# Evaluate the model
mse = mean_squared_error(Y_test, predictions)
print(f'Mean Squared Error: {mse}')