Python
Python is a versatile programming language used for automation, data analysis, and web development.
Python is more than just a general-purpose programming language — it’s the backbone of most of my automation and data work. Its clear syntax makes it easy to write and maintain, while its huge ecosystem of libraries (packages) means there’s almost always a tool available for the task at hand.
How I use Python in practice
Automation & Workflows
Python can interact with files, emails, APIs, and databases to remove repetitive manual work. Libraries like pandas and openpyxl make it possible to read, clean, and restructure large Excel files in seconds instead of hours.
Data Analysis & Reporting
With pandas for data manipulation and matplotlib/seaborn for visualization, Python turns raw datasets into insights. This helps identify trends, errors, and opportunities hidden in day-to-day reporting.
Dashboards & Web Apps
Using frameworks like Streamlit or Dash, Python scripts can be transformed into interactive dashboards that non-technical users can explore in a browser.
Machine Learning & AI
Libraries such as scikit-learn, TensorFlow, and PyTorch let Python handle predictive modeling and advanced analytics. This ranges from simple forecasting to building models that recognize patterns in customer or financial data.
Versatility Across Projects
Whether it’s scraping websites for structured data, automating file delivery schedules, or running statistical tests, Python’s ecosystem has a package for nearly everything a business might need.
Because of this flexibility, Python acts as a “glue” language in my projects — bridging together different systems, files, and tools into one seamless process.