大きなcsvファイルを扱う時はPythonのpickleが超便利. python panadas のデータフレームはかなり便利で、. pythonでcsvファイルを扱う時、pandasで読み込むわけですが、. csvファイルのサイズが大きくなってくると読み込むだけでかなり時間がかかるようになってきます. The code itself is the exact same for both Pandas and Modin. To measure the speed, I imported the time module and put a time.time () before and after the read_csv (). As a result, Pandas took 8.38 seconds to load the data from CSV to memory while Modin took 3.22 seconds. That's a speedup of 2.6X. To retrieve pickled data, the steps are quite simple. You have to use pickle.load() function to do that. The primary argument of pickle load function is the file object that you get by opening the file in read-binary (rb) mode. Simple! Isn't it. Let's write the code to retrieve data we pickled using the pickle dump code. CSV Explorer is a tool for opening, searching, aggregating, and plotting big CSV files. Behind the scenes, it uses a combination of Python and SQL to open big CSVs. If playback doesn't begin shortly, try restarting your device. Videos you watch may be added to the TV's watch history and influence TV recommendations.