Parse Python List to 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.

Python does not have arrays, python has lists. That said, why not just split the strings by | separator — Jab
– Jab, Commented Jan 29, 2019 at 21:04

ignacio.saravia · Accepted Answer · 2019-01-29 21:16:22Z

5

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]')

edited Jan 29, 2019 at 21:16

answered Jan 29, 2019 at 21:08

ignacio.saravia

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3 Comments

Keerikkattu Chellappan Over a year ago

How to get the Reg_Date column as date?

ignacio.saravia Over a year ago

@KeerikkattuChellappan using astype, i edit the answer

Jab Over a year ago

Just to note, you can make the [a.split("|") for a in arr] into a generator comprehension and it won't take up as much space in memory.

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