How can I handle large files in Python efficiently?
You can use libraries like pandas
for data manipulation or dask
for parallel processing. What type of files are you working with?
I'm working with CSV files that are several gigabytes in size.
For large CSV files, consider using pandas.read_csv()
with the chunksize
parameter to read the file in smaller chunks.
Can you give me an example of how to do that?
Sure! Here's a simple example:
import pandas as pd
chunk_size = 10000 # Number of rows per chunk
for chunk in pd.read_csv('large_file.csv', chunksize=chunk_size):
process(chunk) # Replace with your processing function
Get this answer and more from ChatGPT in Telegram, try it for free!
Get Started For FreePowered by advanced language models trained on billions of online words and conversations, MagicBuddy delivers friendly and helpful chat on demand.
Ask questions and get answers. Crack jokes and get laughs. Or even get writing ideas and study help. MagicBuddy's conversational intelligence allows for a truly unique and useful chat experience.
Curious? Try these prompts:
MagicBuddy is incredibly easy to use and the responses are lightning fast! 🥇
Impressive! MagicBuddy is my go-to AI assistant. It’s quick, accurate, and user-friendly.
Sending voice messages makes it easier to use in the middle of the day and the answers are super fast.
Love it! A friend of mine told me about it and it has made my life so much easier. It’s like having a helpful friend in my pocket!
I use 2 months already, simply amazing! MagicBuddy delivers answers in a snap. It’s a must-have tool for staying informed!
Game-changer! MagicBuddy’s speed and accuracy are unmatched. It’s my secret weapon for productivity
Say Hello to Your New Telegram BFF - Try MagicBuddy Free!
Get Started For Free