英文:
Replace characters and extract substrings from pandas dataframe
问题
I can help you modify the regex to include the ''' character for removal in the mentioned rows. Here's the modified regex pattern:
df[['label', 'id']] = df['name'].str.extract(r'(?:\[?\??\|?[[{]?(.*?)[]}]?\]|(.*?))\s+\(\d+\)')
This updated pattern should capture both cases where the ''' character is present within square brackets and where it is not.
英文:
I have following pandas dataframe. I would like to replace some characters and extract substrings (there exists more rows in the original dataframe).
I am using following regex but I am unable to replace '?' from some rows like row 6, 7, 8.
df[['label', 'id']] = df['name'].str.extract(r'\{?\??\|?[[{]?(.*?)[]}]?(?:,\s+(\d{3,100}))?\s+\(\d+\)')
You-Hoover-Fong syndrome, 616954 (3)Yuan-Harel-Lupski syndrome (4)Zaki syndrome, 619648 (3)Zimmermann-Laband syndrome 2, 616455 (3)Zimmermann-Laband syndrome 3, 618658 (3)[?Birbeck granule deficiency], 613393 (3)[?Homosexuality, male] (2)[?Phosphohydroxylysinuria], 615011 (3)[Acetylation, slow], 243400 (3)
The expected output is:
You-Hoover-Fong syndrome 616954Yuan-Harel-Lupski syndromeZaki syndrome 619648Zimmermann-Laband syndrome 2 616455Zimmermann-Laband syndrome 3 618658Birbeck granule deficiency 613393Homosexuality, malePhosphohydroxylysinuria 615011Acetylation, slow 243400
How can I modify the current regex to include the '?' to remove from the mentioned rows?
答案1
得分: 1
text number0 You-Hoover-Fong syndrome 6169541 Yuan-Harel-Lupski syndrome2 Zaki syndrome 6196483 Zimmermann-Laband syndrome 2 6164554 Zimmermann-Laband syndrome 3 6186585 Birbeck granule deficiency 6133936 Homosexuality, male7 Phosphohydroxylysinuria 6150118 Acetylation, slow 243400
英文:
Try:
df['number'] = df['text'].str.extract(r'(\d{6})').fillna('')df['text'] = df['text'].str.extract(r'^[^a-zA-Z]*(.*?(?:\s*(?<!\()\d{,2}))[^a-zA-Z]*$')df['text'] = df['text'].str.strip()print(df)
Prints:
text number0 You-Hoover-Fong syndrome 6169541 Yuan-Harel-Lupski syndrome2 Zaki syndrome 6196483 Zimmermann-Laband syndrome 2 6164554 Zimmermann-Laband syndrome 3 6186585 Birbeck granule deficiency 6133936 Homosexuality, male7 Phosphohydroxylysinuria 6150118 Acetylation, slow 243400
Initial dataframe:
text0 You-Hoover-Fong syndrome, 616954 (3)1 Yuan-Harel-Lupski syndrome (4)2 Zaki syndrome, 619648 (3)3 Zimmermann-Laband syndrome 2, 616455 (3)4 Zimmermann-Laband syndrome 3, 618658 (3)5 [?Birbeck granule deficiency], 613393 (3)6 [?Homosexuality, male] (2)7 [?Phosphohydroxylysinuria], 615011 (3)8 [Acetylation, slow], 243400 (3)
答案2
得分: 1
你可以只更改正则表达式的第一部分，以匹配任意数量的 `[`, `{`, `|` 或 `?` 字符：```regex[[{?|]*(.*?)[]}]?(?:,\s+(\d{3,100}))?\s+\(\d+\)
在Python中
df[['label', 'id']] = df['name'].str.extract(r'[[{?|]*(.*?)[]}]?(?:,\s+(\d{3,100}))?\s+\(\d+\)').fillna('')
输出：
name label id0 You-Hoover-Fong syndrome, 616954 (3) You-Hoover-Fong syndrome 6169541 Yuan-Harel-Lupski syndrome (4) Yuan-Harel-Lupski syndrome2 Zaki syndrome, 619648 (3) Zaki syndrome 6196483 Zimmermann-Laband syndrome 2, 616455 (3) Zimmermann-Laband syndrome 2 6164554 Zimmermann-Laband syndrome 3, 618658 (3) Zimmermann-Laband syndrome 3 6186585 [?Birbeck granule deficiency], 613393 (3) Birbeck granule deficiency 6133936 [?Homosexuality, male] (2) Homosexuality, male7 [?Phosphohydroxylysinuria], 615011 (3) Phosphohydroxylysinuria 6150118 [Acetylation, slow], 243400 (3) Acetylation, slow 243400
<details><summary>英文:</summary>You could just change the first part of your regex to match any number of `[`, `{`, `|` or `?` characters:```regex[[{?|]*(.*?)[]}]?(?:,\s+(\d{3,100}))?\s+\(\d+\)
In python
df[['label', 'id']] = df['name'].str.extract(r'[[{?|]*(.*?)[]}]?(?:,\s+(\d{3,100}))?\s+\(\d+\)').fillna('')
Output:
name label id0 You-Hoover-Fong syndrome, 616954 (3) You-Hoover-Fong syndrome 6169541 Yuan-Harel-Lupski syndrome (4) Yuan-Harel-Lupski syndrome2 Zaki syndrome, 619648 (3) Zaki syndrome 6196483 Zimmermann-Laband syndrome 2, 616455 (3) Zimmermann-Laband syndrome 2 6164554 Zimmermann-Laband syndrome 3, 618658 (3) Zimmermann-Laband syndrome 3 6186585 [?Birbeck granule deficiency], 613393 (3) Birbeck granule deficiency 6133936 [?Homosexuality, male] (2) Homosexuality, male7 [?Phosphohydroxylysinuria], 615011 (3) Phosphohydroxylysinuria 6150118 [Acetylation, slow], 243400 (3) Acetylation, slow 243400
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