columna dividida de pandas en múltiples columnas por delimitador
df[['A', 'B']] = df['AB'].str.split(' ', 1, expand=True)
Scary Swan
df[['A', 'B']] = df['AB'].str.split(' ', 1, expand=True)
import pandas as pd
df = pd.DataFrame(["STD, City State",
"33, Kolkata West Bengal",
"44, Chennai Tamil Nadu",
"40, Hyderabad Telengana",
"80, Bangalore Karnataka"], columns=['row'])
out = pd.DataFrame(df.row.str.split(' ',2).tolist(),columns=['STD','City','State'])
out.drop(index=0,inplace=True)df %>%
separate(mainColumn,c('c1','c2'),'_',extra ='merge')df.Name.str.split(expand=True,)
0 1
0 Steve Smith
1 Joe Nadal
2 Roger Federer
d = [pd.DataFrame(df[col].tolist()).add_prefix(col) for col in df.columns]
df = pd.concat(d, axis=1)
id0 id1 id2 value0 value1 value2
0 10 10 NaN apple orange None
1 15 67 NaN banana orange None
2 12 34 45.0 apple banana orangeDECLARE @tt TABLE(i INT IDENTITY,x VARCHAR(8000));
INSERT INTO @tt(x)VALUES('-9;-9;-1;-9;-9;-9;-9;-9;-1;-9;-9;-9;-9;-9;-9;-9;-9;-9;-1;-9;-9;-9;-9;-9;-9;-9;-9;-9;-1;-9;-1;-9;-9;-9;-1;-9;-9;-9;-9;-9;-9;-1;-1;-1;-1;-9;-1;-1;-9;-9;-9;-9;-1;-9;-1;-9;-9;-9;-1;-9;-1;-9;-1;-9;-9;-9;-9;-1;-9;-9;-1;-1;-9;-1;-1;0000;FFF8;-9;-9;-9;-1;-9;-1;-9;FFF6;-9;-1;-9;-1;-9;-1;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9;-9');
SELECT
i,
val1=n.v.value('/e[1]','VARCHAR(16)'),
val2=n.v.value('/e[2]','VARCHAR(16)'),
val3=n.v.value('/e[3]','VARCHAR(16)'),
-- ... repeat for val4 .. val114
val115=n.v.value('/e[115]','VARCHAR(16)')
FROM
@tt
CROSS APPLY (
SELECT
CAST('<e>'+REPLACE(x,';','</e><e>')+'</e>' AS XML) AS itm
) AS i
CROSS APPLY i.itm.nodes('/') AS n(v);