gistfile1.txt

# Read the csv and convert it into a list of dictionaries
with open(file_to_load) as financial_data:
    reader = csv.reader(financial_data)

    # Read the header row
    header = next(reader)

    # Extract first row to avoid appending to net_change_list
    first_row = next(reader)
    total_months = total_months + 1
    total_net = total_net + int(first_row[1])
    prev_net = int(first_row[1])

    for row in reader:

        # Track the total
        total_months = total_months + 1
        total_net = total_net + int(row[1])

        # Track the net change
        net_change = int(row[1]) - prev_net
        prev_net = int(row[1])
        net_change_list = net_change_list + [net_change]
        month_of_change = month_of_change + [row[0]]

        # Calculate the greatest increase
        if net_change > greatest_increase[1]:
            greatest_increase[0] = row[0]
            greatest_increase[1] = net_change

        # Calculate the greatest decrease
        if net_change < greatest_decrease[1]:
            greatest_decrease[0] = row[0]
            greatest_decrease[1] = net_change
# Calculate the Average Net Change
net_monthly_avg = round(sum(net_change_list) / len(net_change_list),2)


# Export the results to text file
with open(file_to_output, "w") as txt_file:
    txt_file.write(f"Financial Analysis\n")
    txt_file.write(f"----------------------------\n")
    txt_file.write(f"Total Months: {total_months}\n")
    txt_file.write(f"Total: ${total_net}\n")
    txt_file.write(f"Average  Change: ${net_monthly_avg}\n")
    txt_file.write(f"Greatest Increase in Profits: {greatest_increase[0]} (${greatest_increase[1]})\n")
    txt_file.write(f"Greatest Decrease in Profits: {greatest_decrease[0]} (${greatest_decrease[1]})\n")