# Step 1: Importing Libraries

import pandas as pd from prophet import Prophet

import matplotlib.pyplot as plt from openpyxl

import Workbook from openpyxl.drawing.image

import Image

# Step 2: Loading Sales Data
file_path = ‘/content/sales_data_2018_to_2022.xlsx’ # Replace with your file path
sales_data = pd.read_excel(file_path)

# Step 3: Preparing Data for Prophet
sales_data.rename(columns={‘Date’: ‘ds’, ‘Sales’: ‘y’}, inplace=True)

# Step 4: Initializing and Fitting the Model
model = Prophet()
model.fit(sales_data)

# Step 5: Creating Future Dates for Prediction
future_dates = model.make_future_dataframe(periods=365)
future_dates = future_dates[future_dates[‘ds’].dt.year == 2023]

# Step 6: Forecast sales for 2023
forecast = model.predict(future_dates)

# Step 7: Visualize and Save the Forecast
fig = model.plot(forecast, xlabel=’Date’, ylabel=’Sales’)
plt.title(‘Sales Forecast for 2023 using Prophet’)

# Save the plot as an image BEFORE calling show
plt.savefig(‘forecast_plot.png’)

# Now display the plot
plt.show()

# Insert the Image into an Excel File
wb = Workbook()
ws = wb.active

# Ensure the path is correct when loading the image
img = Image(‘forecast_plot.png’)
ws.add_image(img)

# Save the workbook with the image
wb.save(‘forecast_in_excel.xlsx’)