Category : valueerror

I am taking multiple different different sorting algos and benchmarking their times based on different sizes of arrays and different sorting of arrays. IE sorted, random, and reverse arrays ranging from 10^0 to 10^8. I am getting an error whenever I try to use a random_swap function within the main benchmarking function, and I cannot ..

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I’m writing a script for a deck of card in an OO way as shown below. class Deck: def __init__(self): self.card_list = self.build() def build(self): suit = ["S", "H", "D", "C"] val = ["ace", "two", "thr", "fou", "fiv", "six", "sev", "eig", "nin", "ten", "jac", "que", "kin"] return list(itertools.product(suit, val)) def deal(self): cards = random.choices(population=self.card_list, k=3) ..

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I downloaded a zipped file from S3 and unzipped it: with zipfile.ZipFile(‘/tmp/DataPump_10000838.zip’, ‘r’) as zip_ref: testList = [] for i in zip_ref.namelist(): if (i.startswith("__MACOSX/") == False): val = ‘/tmp/’+i testList.append(val) Now, I have a few unzipped files in my /tmp folder. I want to open those files, gzip and move them to an S3 bucket. ..

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I’m trying to do cross validation to select the maximum degree of polynomial to add to my features in a Logistic regression. But I get the following error ValueError: could not broadcast input array from shape (928,2) into shape (928,0), which I understand means elements in my input array must be equal to elements of ..

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I have Data Frame in Python Pandas like below with str values: NR ——– 910517196 921122192 020612567 And I try to calculate age based on values in column "NR" using below code: ABT_DATE = pd.Timestamp(year=2021, month=6, day=30) df[‘age’] = (ABT_DATE – pd.to_datetime(df.NR.str[:6], format = ‘%y%m%d’)) / np.timedelta64(1, ‘Y’) df["age"] = df.age.astype("int") Logic of above code ..

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