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fix to issue #94#95
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now all text will inferred as string and the user can change it to their desired data type.
| _cols.remove('text') | ||
| for col in _cols: | ||
| _df[col] = _df[col].astype(int) | ||
| res['data'] = _df |
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Can you try the following code:
_data = pytesseract.image_to_data(img_content, lang=self.lang, **self.configs)df = pd.read_csv( io.StringIO(_data), quoting=csv.QUOTE_NONE, encoding="utf-8", sep="\t")df['text'] = df['text'].astype('str')res["data"] = dfThere was a problem hiding this comment.
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@lolipopshock sorry it does not, I have tried this
and ya i get it, the for loop and all that stuff looks ugly :)
here's the screenshot
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I see -- it's the issue from floating point numbers.0 right?
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Yes
lolipopshock commentedFeb 2, 2022 • edited
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edited
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I think the new solution can solve your issue -- see example below: Let's say we have a csv file And if we read it via: We have
(There's no |
Fixes ##94 (comment)
#94
The issue was, all digit sequences were inferred as float, with this fix all text (numeric + non-numeric) will be inferred as string and the user can change it to their desired data type.
But with this fix, the user will be required to change the numeric data type columns.
i could not find any better solution other than this.