Let’s consider two options and what happens in both cases: chunksize is None(default value): pandas passes query to database database executes query pandas checks and sees that chunksize is None pandas tells database that it wants to receive all rows of the result table at once database returns all rows of the result table pandas … Read more
Here is another way: var chunks = []; int chunkSize = 2; for (var i = 0; i < letters.length; i += chunkSize) { chunks.add(letters.sublist(i, i+chunkSize > letters.length ? letters.length : i + chunkSize)); } return chunks; Run it on dartpad
Is it possible? Yes it is! git checkout -p stash@{0} Where you can replace the 0 in stash@{0} with the index of the stash you want to apply. Use git stash list and git show -p stash@{n} if unsure which n is the stash you want to apply. Don’t forget to git stash drop stash@{n} … Read more
You can write it fairly simply as a list generator: def split(a, n): k, m = divmod(len(a), n) return (a[i*k+min(i, m):(i+1)*k+min(i+1, m)] for i in range(n)) Example: >>> list(split(range(11), 3)) [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10]]
The error shows that the machine does not have enough memory to read the entire CSV into a DataFrame at one time. Assuming you do not need the entire dataset in memory all at one time, one way to avoid the problem would be to process the CSV in chunks (by specifying the chunksize parameter): … Read more
def chunker(seq, size): return (seq[pos:pos + size] for pos in range(0, len(seq), size)) Works with any sequence: text = “I am a very, very helpful text” for group in chunker(text, 7): print(repr(group),) # ‘I am a ‘ ‘very, v’ ‘ery hel’ ‘pful te’ ‘xt’ print(‘|’.join(chunker(text, 10))) # I am a ver|y, very he|lpful text animals … Read more
Here’s a generator that yields evenly-sized chunks: def chunks(lst, n): “””Yield successive n-sized chunks from lst.””” for i in range(0, len(lst), n): yield lst[i:i + n] import pprint pprint.pprint(list(chunks(range(10, 75), 10))) [[10, 11, 12, 13, 14, 15, 16, 17, 18, 19], [20, 21, 22, 23, 24, 25, 26, 27, 28, 29], [30, 31, 32, 33, … Read more