pandas data frame from python lists in more efficient way

Question

I have 3 lists in python. Using these 3 lists I want to create a pandas data frame. I have done like below.

import pandas as pd
import numpy as np

mysql_list = ['id', 'date', 'name']
oracle_list = ['id', 'date-1', 'name_1']
sql_list = ['id', 'date', 'name-1']

mysql_name='test_123'
oracle_name='test-123'
sql_name='test123'


pd_df = pd.DataFrame(columns = ['mysql_name', 'mysql_cols', 'oracle_name', 'oracle_cols', 'sql_name', 'sql_cols'])
pd_df = pd.DataFrame(index = [np.arange(len(mysql_list))],columns = ['mysql_name', 'mysql_cols', 'oracle_name', 'oracle_cols', 'sql_name', 'sql_cols'])

pd_df.loc[:,'mysql_name'] = mysql_name
pd_df.loc[:,'mysql_cols'] = mysql_list

pd_df.loc[:,'sql_name'] = sql_name
pd_df.loc[:,'sql_cols'] = sql_list

pd_df.loc[:,'oracle_name'] = oracle_name
pd_df.loc[:,'oracle_cols'] = oracle_list

pd_df

  mysql_name mysql_cols oracle_name oracle_cols sql_name sql_cols
0   test_123         id    test-123          id  test123       id
1   test_123       date    test-123      date-1  test123     date
2   test_123       name    test-123      name_1  test123   name-1

I am able to achieve my requirement. Is there a simple way we can do this with less number of lines of code.

I believe there is but I don't know how I can do it

MaxU - stand with Ukraine · Accepted Answer · 2017-11-21 18:59:00Z

3

In [16]: (pd.DataFrame({'mysql_cols':mysql_list, 'oracle_cols':oracle_list,
    ...:                        'sql_cols':sql_list})
    ...:            .assign(mysql_name=mysql_name,oracle_name=oracle_name, sql_name=sql_name)
    ...:            .sort_index(axis=1))
    ...:
Out[16]:
  mysql_cols mysql_name oracle_cols oracle_name sql_cols sql_name
0         id   test_123          id    test-123       id  test123
1       date   test_123      date-1    test-123     date  test123
2       name   test_123      name_1    test-123   name-1  test123

answered Nov 21, 2017 at 18:59

MaxU - stand with Ukraine

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BENY · Accepted Answer · 2017-11-21 19:02:24Z

3

You can using dict with assign

d={'mysql_name':'test_123','oracle_name':'test-123','sql_name':'test123'}
pd.DataFrame({'mysql_cols':mysql_list, 'oracle_cols':oracle_list,
                       'sql_cols':sql_list}).assign(**d)

Out[312]: 
  mysql_cols oracle_cols sql_cols mysql_name oracle_name sql_name
0         id          id       id   test_123    test-123  test123
1       date      date-1     date   test_123    test-123  test123
2       name      name_1   name-1   test_123    test-123  test123

answered Nov 21, 2017 at 19:02

BENY

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