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So, I've an excel file and that I have already converted in pandas dataframe, I've done some analysis on it already but there's an issue that I'm facing in it, that is is of how can I separate multiple values that are given in a same row, they're differentiated using a) name1 ; b) name2

As a beginner in pandas I'm unable to work upon a logic which can frame out the multiple values that are given in the column.

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This is the dataset that I'm working on and I'm unsure how can I differentiate the multiple values that are given in the same row.

Akshat Kulshreshtha
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1 Answers1

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You can use .str.split() to split the column into two and then .str.lstrip() to remove the (a) and (b):

>>> import pandas as pd
>>> df = pd.DataFrame({"Chronic medical conditions": ["(a) BP; (b) Diabetes", "(a) Diabetes; (b) high BP"]})
>>> df
  Chronic medical conditions
0       (a) BP; (b) Diabetes
1  (a) Diabetes; (b) high BP

>>> df = df["Chronic medical conditions"].str.split(';', expand=True)
>>> df.columns = ["a", "b"]  # rename columns as neccessary
>>> df
              a              b
0        (a) BP   (b) Diabetes
1  (a) Diabetes    (b) high BP

>>> df["a"] = df["a"].str.lstrip("(a) ")
>>> df["b"] = df["b"].str.lstrip(" (b)")
>>> df
           a         b
0         BP  Diabetes
1   Diabetes   high BP
ChrisOram
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  • Thanks for the help but just 1 more query, actually few rows have more than 2 values like some have 4 values in them and some are having upto 5, so can I make this process dynamic because it is limited to 2 only, right? – Akshat Kulshreshtha Aug 17 '22 at 10:55
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    I see, to do this in a reasonable and efficient way I would assume some regex with `split` or `extract` would be required. – ChrisOram Aug 17 '22 at 11:00
  • Can you help me with that as well? I mean I'm quite new to all this stuff – Akshat Kulshreshtha Aug 17 '22 at 11:14
  • @AkshatKulshreshtha I would suggest creating another question which is more specific to this. Something like, "how to extract a variable number of string slices from columns in Pandas" and tag regex also - there are many pandas + regex wizards on StackOverflow. – ChrisOram Aug 23 '22 at 09:45