Python Pandas Expand a Column of List of Lists to Two New Column

You can .apply(pd.Series) twice to get what you need as an intermediate step, then merge back to the original dataframe.

import pandas as pd

df = pd.DataFrame({
    'name': ['john', 'smith'],
    'id': [1, 2],
    'apps': [[['app1', 'v1'], ['app2', 'v2'], ['app3','v3']], 
             [['app1', 'v1'], ['app4', 'v4']]]
})

dftmp = df.apps.apply(pd.Series).T.melt().dropna()
dfapp = (dftmp.value
              .apply(pd.Series)
              .set_index(dftmp.variable)
              .rename(columns={0:'app_name', 1:'app_version'})
        )

df[['name', 'id']].merge(dfapp, left_index=True, right_index=True)
# returns:
    name  id app_name app_version
0   john   1     app1          v1
0   john   1     app2          v2
0   john   1     app3          v3
1  smith   2     app1          v1
1  smith   2     app4          v4

Another approach would be (should be quite fast too):

#Repeat the columns without the list by the str length of the list
m=df.drop('apps',1).loc[df.index.repeat(df.apps.str.len())].reset_index(drop=True)
#creating a df exploding the list to 2 columns
n=pd.DataFrame(np.concatenate(df.apps.values),columns=['app_name','app_version'])
#concat them together
df_new=pd.concat([m,n],axis=1)

---

    name id app_name app_version
0   john  1     app1          v1
1   john  1     app2          v2
2   john  1     app3          v3
3  smith  2     app1          v1
4  smith  2     app4          v4

You can always have a brute force solution. Something like:

name, id, app_name, app_version = [], [], [], []
for i in range(len(df)):
    for v in df.loc[i,'apps']:
        app_name.append(v[0])
        app_version.append(v[1])
        name.append(df.loc[i, 'name'])
        id.append(df.loc[i, 'id'])
df = pd.DataFrame({'name': name, 'id': id, 'app_name': app_name, 'app_version': app_version})

will do the work.

Note that I assumed df['apps'] is lists of strings if df['apps'] is strings then you need: eval(df.loc[i,'apps']) instead of df.loc[i,'apps']