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Hi there I am trying to accomplish something similar to the mid function in excel with a column in a pandas dataframe in python. I have a column with medication names + strengths, etc of variable length. I just want to pull out the first "part" of the name and place the result into another column in the dataframe.

Example:

Dataframe column

MEDICATION_NAME
acetaminophen 325 mg
a-hydrocort 100 mg/2 ml

Desired Result

MEDICATION_NAME               GENERIC_NAME
acetaminophen 325 mg          acetaminophen     
a-hydrocort 100 mg/2 ml       a-hydrocort

What I have tried

df['GENERIC_NAME'] = df['MEDICATION_NAME'].str[:df['MEDICATION_NAME'].apply(lambda x: x.find(' '))]

Basically I want to apply the row specific result of 

df['GENERIC_NAME'] = df['MEDICATION_NAME'].apply(lambda x: x.find(' '))

to the 

 str[:]
function?

Thanks

Nexxsys
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    Can you provide more examples? Is the name always followed by a space and numbers then mg? Are there some Generic names with spaces? – ALollz Nov 09 '18 at 20:55

4 Answers4

3

You can use str.partition [pandas-doc] here:

df['GENERIC_NAME'] = df['MEDICATION_NAME'].str.partition(' ')[0]

For the given column this gives:

>>> g.str.partition(' ')[0]
0    acetaminophen
1      a-hydrocort
Name: 0, dtype: object

partition itself creates from a series a dataframe with three columns: before, match, and after :

>>> df['MEDICATION_NAME'].str.partition(' ')
               0  1            2
0  acetaminophen          325 mg
1    a-hydrocort     100 mg/2 ml
Sai Kumar
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Willem Van Onsem
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2

DO with str.split 

df['MEDICATION_NAME'].str.split(n=1).str[0]
Out[345]: 
0    acetaminophen
1      a-hydrocort
Name: MEDICATION_NAME, dtype: object
#df['GENERIC_NAME']=df['MEDICATION_NAME'].str.split(n=1).str[0]
BENY
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1

Use str.extract to use full regex features:

df["GENERIC_NAME"] = df["MEDICATION_NAME"].str.extract(r'([^\s]+)')

This capture the first word bounded by space. So will protect against instances where there are a space first.

Rocky Li
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1

Try this:

df['GENERIC_NAME'] = df['MEDICATION_NAME'].str.split(" ")[0]
petezurich
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