Excel Data Processing for Startup Performance Tracking

Small businesses and startups often struggle with tracking their financial and operational performance. They may have Excel sheets with data but lack the tools to analyze trends, profitability, or customer growth efficiently.

A Python script that:

Reads an Excel file containing performance data

Cleans and processes the data

Computes key business metrics (e.g., profit, customer retention rate)

Generates summary reports and visualizes trends

import pandas as pd

import matplotlib.pyplot as plt

# Load Excel data

def load_data(file_path):

try:

df = pd.read_excel(file_path)

return df

except Exception as e:

print("Error loading file:", e)

return None

# Process data

def process_data(df):

df['Profit'] = df['Revenue'] - df['Expenses']

df['Customer Growth Rate'] = df['New Customers'] / df['Total Customers'] * 100

return df

# Generate summary statistics

def generate_summary(df):

summary = {

"Total Revenue": df['Revenue'].sum(),

"Total Expenses": df['Expenses'].sum(),

"Total Profit": df['Profit'].sum(),

"Average Customer Growth Rate": df['Customer Growth Rate'].mean()

}

return summary

# Visualize trends

def plot_trends(df):

plt.figure(figsize=(10,5))

plt.plot(df['Month'], df['Revenue'], label='Revenue', marker='o')

plt.plot(df['Month'], df['Expenses'], label='Expenses', marker='o')

plt.plot(df['Month'], df['Profit'], label='Profit', marker='o')

plt.xlabel('Month')

plt.ylabel('Amount')

plt.title('Startup Financial Performance')

plt.legend()

plt.grid(True)

plt.show()

# Main function

def main():

file_path = 'startup_data.xlsx' # Update with actual file path

df = load_data(file_path)

if df is not None:

df = process_data(df)

summary = generate_summary(df)

print("Summary Report:", summary)

plot_trends(df)

if name == "__main__":

main()

Reads Data: Loads an Excel file with columns like Month, Revenue, Expenses, New Customers, and Total Customers.

Processes Data:

Generates Summary: Aggregates total revenue, expenses, profit, and average customer growth.

Visualizes Trends: Plots Revenue, Expenses, and Profit over time.

Create a sample startup_data.xlsx file with test data.

Enhance with more KPIs like retention rate or CAC (Customer Acquisition Cost).

Automate sending reports via email.