If youโve spent time in Python for data analysis, you know the magic of Pandas. A few lines of code, and you can filter, aggregate, and transform data like a wizard. But when your dataset starts hitting millions of rows or you want to run computations across a cluster, Pandas starts to sweat โ thatโs... Continue Reading →
Pandas DataFrame vs. Spark DataFrame: Which One Should You Use & When?
Ever felt like your laptopโs about to take off while processing that โinnocentโ CSV file with 1 million rows? ๐Yep. Youโre probably using Pandas, and itโs starting to sweat. Thatโs where Spark DataFrames come in โ but wait, donโt ditch Pandas just yet!Letโs break it down. Think of it like this: Pandas is your reliable... Continue Reading →