Pandas dataframe 列包含字符串和列表

Question

I have a data frame that contains a column with both strings and lists.

import pandas as pd    
data = {'lanes': ['1',['2','4'],'2','3',['1','2','3']]}
df = pd.DataFrame(data,columns=['lanes'])
df

original dat frame

I need to convert the strings to ints and replace the lists with means of the list elements. So, the output should look like this:

data2 = {'lanes': [1,3,2,3,2]}
df2 = pd.DataFrame(data2,columns=['lanes']) 
df2  

desired data frame

Can anyone give me some direction on how to do this, if you have done something like this before?

Answer 1

Use Series.explode , convert values to integers and then count mean per duplicated index by mean :

df['lanes'] = df['lanes'].explode().astype(int).mean(level=0)
print (df)
   lanes
0      1
1      3
2      2
3      3
4      2

If data are not lists, but strings repr of lists use:

data = {'lanes': ['1',"['2','4']",'2','3',"['1','2','3']"]}
df = pd.DataFrame(data,columns=['lanes'])

import ast

df['lanes'] = df['lanes'].apply(ast.literal_eval).explode().astype(int).mean(level=0)
print (df)
   lanes
0      1
1      3
2      2
3      3
4      2

Answer 2

You can try below snippet as well. It uses list comprehension to get the result

import pandas as pd
data = {'lanes': ['1',['2','4'],'2','3',['1','2','3']]}


def mean(lst):
    return sum(lst) / len(lst)

data2 = dict()
data2['lanes']= [int(mean(i)) for i in [[int(x) for x in list] for list in data['lanes']]]
df2 = pd.DataFrame(data2,columns=['lanes'])