[Python] How to process CSV exports from an expense tool for visualization in a custom...

I’m currently using an Indonesian expense management tool (Mekari expense) that provides a solid built-in dashboard and allows exporting detailed expense reports as CSV files. However, I need more customized analytics and unique visualizations tailored to our specific business metrics and integration with other internal data sources.

How do I import and process these CSV files into my custom dashboard built with Python and React? Also, how to automate the import, validate the data, and keep the dashboard updated in realtime?

I initially tried to use Python’s built-in csv module to read the CSV export and then visualize the data using matplotlib. Here’s a simplified version of the code I wrote:

import csv
import matplotlib.pyplot as plt

dates = []
amounts = []

with open('expenses.csv', newline='') as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
dates.append(row['date'])
amounts.append(float(row['amount']))

plt.plot(dates, amounts)
plt.title('Expenses Over Time')
plt.xlabel('Date')
plt.ylabel('Amount')
plt.show()



The plot didn’t look right because the dates were treated as plain text, making the chart messy and out of order. I also had to manually convert the dates, which made the code longer and more error-prone. Plus, it was hard to group or categorize expenses for more detailed visualizations. What I wanted was a clean, properly ordered time series chart and an easier way to analyze and group the data by categories or dates.

Continue reading...