A CSV file is a “comma-separated values” file. In plain English, this is a text file that contains an unusually large amount of data. More often than not, this is used in order to create databases of ...

Since the creation of python reading in files has become much easier with each update and with each added package. To work with csv and xlsx files the easiest package is the pandas package because it ...

At Springboard, we pair mentors with learners in data science. We often get questions about whether to use Python or R – and we’ve come to a conclusion thanks to insight from our community of mentors ...

What if the tools you already use could do more than you ever imagined? Picture this: you’re working on a massive dataset in Excel, trying to make sense of endless rows and columns. It’s slow, ...

Why write SQL queries when you can get an LLM to write the code for you? Query NFL data using querychat, a new chatbot component that works with the Shiny web framework and is compatible with R and ...

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your toolkit. Python’s rich ecosystem of data science tools is a big draw for ...

Have you ever found yourself wrestling with Excel formulas, wishing for a more powerful tool to handle your data? Or maybe you’ve heard the buzz about Python in Excel and wondered if it’s truly the ...

Tired of out-of-memory errors derailing your data analysis? There's a better way to handle huge arrays in Python.