将Python列表解析为Pandas DataFrame

Question

I have an array that has values separated by '|'. I would like to parse it to a pandas data frame.

import pandas as pd    
arr = ['19345360853|5264654|100530|2017-01-07', '19345360853|13518371|100530|2018-10-08']
pd.DataFrame([{'Id': item.split('|')[0] ,'Code_A': item.split('|')[1] , 'Code_B': item.split('|')[2],'Reg_Date': item.split('|')[3]} for item in arr ])

I would like the pandas dataframe to be in the following schema,

'Id' string 'Code_A' string 'Code_B' string 'Reg_Date' date

So the resulting Pandas dataframe would be similar to this. result dataframe

Any help is appreciated.

Answer 1

First, convert to two dimensional list

arr = [a.split("|") for a in arr]

Second, convert to pandas dataframe

data = pd.DataFrame(arr,columns=['Id','Code_A','Code_B','Reg_Date'])

            Id    Code_A  Code_B    Reg_Date
0  19345360853   5264654  100530  2017-01-07
1  19345360853  13518371  100530  2018-10-08

Convert column Reg_Date using astype (Ref: astype )

a =pd.DataFrame(arr,columns=['Id','Code_A','Code_B','Reg_Date'])
a['Reg_Date'] = a['Reg_Date'].astype('datetime64[ns]')