[FIXED] Using lambda function, how to iterate over the columns having list values in pandas data frame

Issue

import pandas as pd

mydata = {"Key" : [567, 568, 569, 570, 571, 572] , "Sprint" : ["Max1;Max2", "Max2", "DI001 2", "DI001 25", "DAS 100" , "DI001 101"]}

df = pd.DataFrame(mydata)
df ["sprintlist"]= df["Sprint"].str.split(";")
print (df)

From this dataframe, I want to extract only the numbers that appears in the last part of the string from column "Sprintlist" for each value in the list to the new list "Sprintnumb" as show below

Expected output:

In one of my previous query, I got clarity on how to extract the number when only one value present in "Sprint" column. I tried using lambda function to achieved the desired output but getting errors "str' object has no attribute 'str'"

 df["Sprint Number"] = df.Sprint.str.extract(r"(\d+)$").astype(int)

Solution

Use Series.explode with Series.str.extractall, converting to numeric and aggregate lists:

df["Sprint Number"] = (df["sprintlist"].explode()
                                       .str.extractall(r"(\d+)$")[0]
                                       .astype(int)
                                       .groupby(level=0)
                                       .agg(list))
print (df)
   Key     Sprint    sprintlist Sprint Number
0  567  Max1;Max2  [Max1, Max2]        [1, 2]
1  568       Max2        [Max2]           [2]
2  569    DI001 2     [DI001 2]           [2]
3  570   DI001 25    [DI001 25]          [25]
4  571    DAS 100     [DAS 100]         [100]
5  572  DI001 101   [DI001 101]         [101]

Or use list comprhension with regex:

df["Sprint Number"] = [[int(re.search('(\d+)$', y).group(0)) for y in x]
                        for x in df["sprintlist"]]
print (df)
   Key     Sprint    sprintlist Sprint Number
0  567  Max1;Max2  [Max1, Max2]        [1, 2]
1  568       Max2        [Max2]           [2]
2  569    DI001 2     [DI001 2]           [2]
3  570   DI001 25    [DI001 25]          [25]
4  571    DAS 100     [DAS 100]         [100]
5  572  DI001 101   [DI001 101]         [101]

If possible some string not ends with number add assign operator := with testing None:

import re

mydata = {"Key" : [567, 568, 569, 570, 571, 572] , 
          "Sprint" : ["Max1;Max", "Max2", "DI001 2", "DI001 25", "DAS 100" , "DI001 101"]}

df = pd.DataFrame(mydata)
df ["sprintlist"]= df["Sprint"].str.split(";")

df["Sprint Number"] = [[int(m.group(0)) 
                       for y in x if( m:=re.search('(\d+)$', y)) is not None] 
                       for x in df["sprintlist"]]
print (df)
   Key     Sprint   sprintlist Sprint Number
0  567   Max1;Max  [Max1, Max]           [1]
1  568       Max2       [Max2]           [2]
2  569    DI001 2    [DI001 2]           [2]
3  570   DI001 25   [DI001 25]          [25]
4  571    DAS 100    [DAS 100]         [100]
5  572  DI001 101  [DI001 101]         [101]
    

Answered By - jezrael