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Columns and DataType Not Explicitly Set on line 25 of download_data.py #194

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CodeSmileBot opened this issue Nov 9, 2023 · 0 comments

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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:

local_file = "sample_et_al.tar"
# Download the data.
urllib.request.urlretrieve("https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE114002&format=file", local_file)
with tarfile.open(local_file, "r") as archive:
contents = archive.extractfile("GSM3130435_egfp_unmod_1.csv.gz").read()
contents = gzip.decompress(contents).decode("utf-8")
os.remove(local_file)
# Format data.
df = pandas.read_csv(io.StringIO(contents), sep=",", index_col=0)
df = df[["utr", "total_reads", target_column]]
df.sort_values("total_reads", inplace=True, ascending=False)
df.reset_index(inplace=True, drop=True)
# Split into train/validation/test.
df = df.iloc[:280000]
datasets = dict(test=df.iloc[:20000])
df = df.iloc[20000:]
df = df.sample(frac=1.)
datasets["validate"] = df.iloc[:20000]
.

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

.

I hope this information is helpful!

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