Programming
def process_batch(data: pd.DataFrame) -> None:
# Optimize memory footprint
for col in data.select_dtypes(include=["float64"]).columns:
data[col] = pd.to_numeric(data[col], downcast="float")
return apply_transform(data)
Oct 12, 20245 min read
Pandas Memory Optimization Techniques
Stop hitting OutOfMemory errors. Practical tips for downcasting, chunking, and lazy evaluation in Python data workflows.