I have a dataset like this

import pandas as pd 
df = pd.read_csv("music.csv") 
df

This table is not in 1NF. I would like to convert in the form of pd.DataFrame, that satiesfy 1NF.

How can I do that?

I did this, but seems not work

import pandas as pd
import numpy as np
 
df = pd.read_csv("music.csv") 
 
lens = list(map(len, df['singer','language].values))
 
res = pd.DataFrame({'name': np.repeat(
    df['name'], lens), 'singer': np.concatenate(df['singer'].values),'language': np.concatenate(df['language'].values)})
 
print(res)

It should satisfy only 1NF not 3NF and so on.

CodePudding user response：

Split language and singer by values and use pd.explode:

df['language']=df['language'].str.split(';')
df['singer']=df['singer'].str.split(";")
df.explode(['language','singer'])