Columns and DataType Not Explicitly Set on line 466 of sequential_minimum_optimization.py

[CodeSmileBot]

Hello!

I found an AI-Specific Code smell in your project.
The smell is called: Columns and DataType Not Explicitly Set

You can find more information about it in this paper: https://dl.acm.org/doi/abs/10.1145/3522664.3528620.

According to the paper, the smell is described as follows:

Problem	If the columns are not selected explicitly, it is not easy for developers to know what to expect in the downstream data schema. If the datatype is not set explicitly, it may silently continue the next step even though the input is unexpected, which may cause errors later. The same applies to other data importing scenarios.
Solution	It is recommended to set the columns and DataType explicitly in data processing.
Impact	Readability

Example:

### Pandas Column Selection
import pandas as pd
df = pd.read_csv('data.csv')
+ df = df[['col1', 'col2', 'col3']]

### Pandas Set DataType
import pandas as pd
- df = pd.read_csv('data.csv')
+ df = pd.read_csv('data.csv', dtype={'col1': 'str', 'col2': 'int', 'col3': 'float'})

You can find the code related to this smell in this link:

Python/machine_learning/sequential_minimum_optimization.py

Lines 456 to 476 in 5180533

	if not os.path.exists(r"cancel_data.csv"):
	request = urllib.request.Request( # noqa: S310
	CANCER_DATASET_URL,
	headers={"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)"},
	)
	response = urllib.request.urlopen(request) # noqa: S310
	content = response.read().decode("utf-8")
	with open(r"cancel_data.csv", "w") as f:
	f.write(content)
	data = pd.read_csv(r"cancel_data.csv", header=None)
	# 1: pre-processing data
	del data[data.columns.tolist()[0]]
	data = data.dropna(axis=0)
	data = data.replace({"M": np.float64(1), "B": np.float64(-1)})
	samples = np.array(data)[:, :]
	# 2: dividing data into train_data data and test_data data
	train_data, test_data = samples[:328, :], samples[328:, :]
	test_tags, test_samples = test_data[:, 0], test_data[:, 1:]

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I also found instances of this smell in other files, such as:

.

I hope this information is helpful!