python

7 Things I Should’ve Learnt Much Earlier For Python Functions Free Code: https://www.clcoding.com/2024/08/7-things-i-shouldve-learnt-much-earlier.html

4 Practical Python Programs for Working with Excel using the openpyxl Library Free 365 Days Python Challenge https://bit.ly/3Rr3OrM

Why F-Strings Are Python’s Superpower — 8 Cool Examples

Monitor and analyze the impact of small business loans with this Excel dashboard template. Visualize financial data, track repayments, and assess loan performance easily. Download this template to manage your business finances effectively

This SaaS sales dashboard in Excel is designed to simplify business planning with clear data visualization. Track recurring revenue, churn, and customer growth to evaluate performance effectively. Compare key SaaS metrics, monitor expenses, and assess profitability trends. Use interactive charts to gain insights into subscription plans, optimize decision-making, and create a scalable strategy for sustainable growth.

7 Lesser-Known Python Techniques about Lists Free Code: https://bit.ly/3AGA9bq

The append() method in Python adds a new element to the end of a list, allowing you to grow the list dynamically as your program runs. #PythonLists #AppendMethod #LearnPython

Bar Chart using Pygal in Python

10 Essential Use Cases of Python's zip() Function with Examples Free Code: https://www.clcoding.com/2024/08/10-essential-use-cases-of-pythons-zip.html

Choosing the right bank can make or break your small business growth. This interactive Excel dashboard helps you analyze and compare loan scenarios from different banks, showing how each option impacts your profit margins and risk. Model various financing strategies and understand the trade-offs between growth potential and financial stability — all in one easy-to-use tool. ✅ Compare banking products side-by-side ✅ Visualize loan effects on profitability and risk ✅ Essential for smart...

Convert CSV to JSON using Python

𝗪𝗵𝘆 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝟵𝟬% 𝗼𝗳 𝗔𝗜 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗳𝗮𝗶𝗹 𝗯𝗲𝗳𝗼𝗿𝗲 𝘁𝗵𝗲𝘆 𝗿𝗲𝗮𝗰𝗵 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 It's not the models. It's not the data. It's the architecture. Across the industry, brilliant engineers build AI prototypes that work perfectly in Jupyter notebooks... then spend 6 months trying to productionize them. 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗽𝗿𝗼𝗯𝗹𝗲𝗺? Most AI projects start as experiments and never graduate to engineered systems. Here's what separates successful AI implementations from failures: 𝟭. 𝗖𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻 𝗛𝗲𝗹𝗹 When API keys, model...

In Python, *args lets you pass a variable number of positional arguments, while **kwargs lets you pass a variable number of keyword arguments to a function. They make functions flexible and dynamic. 💡https://www.pybeginners.com #PythonTips #argskwargs #PythonBeginners