How to change the DNS server across network interfaces?

Question

Given this code that merges three Pandas data frames:

raw_data = {
        'type': [0, 1, 1],
        'id': ['3', '4', '5'],
        'name_1': ['Alex', 'Amy', 'Allen']}
df_a = pd.DataFrame(raw_data, columns = ['type', 'id', 'name_1' ])
df_a.set_index(['type', 'id'])

raw_datab = {
        'type': [1, 1, 1, 0],
        'id': ['4', '5', '5', '7'],
        'name_2': ['Billy', 'Brian', 'Joe', 'Bryce']}
df_b = pd.DataFrame(raw_datab, columns = ['type', 'id', 'name_2'])
df_b.set_index(['type', 'id'])

raw_datac = {
        'name_3': ['School', 'White', 'Jane', 'Homer'],
        'id': ['4', '6', '5', '5'],
        'type': [1, 1, 1, 1]}
df_c = pd.DataFrame(raw_datac, columns = ['name_3', 'id', 'type' ])
df_c.set_index(['type', 'id'])

dfx = df_a.merge(df_b, how='outer').merge(df_c, how='outer')
print(dfx)

I get the following response:

   type id name_1 name_2  name_3
0     0  3   Alex    NaN     NaN
1     1  4    Amy  Billy  School
2     1  5  Allen  Brian    Jane
3     1  5  Allen  Brian   Homer
4     1  5  Allen    Joe    Jane
5     1  5  Allen    Joe   Homer
6     0  7    NaN  Bryce     NaN
7     1  6    NaN    NaN   White

What I actually need is to get, as the result, the concatenation of the columns in their original order. For example:

type    id  name_1  type_2  id_2    name_2  name_3  id_3  type_3  
0       3   Alex    0       3       NaN     NaN     3     0     
1       4   Amy     1       4       Billy   School  4     1     
1       5   Allen   1       5       Brian   Jane    5     1     
1       5   Allen   1       5       Brian   Homer   5     1     
1       5   Allen   1       5       Joe     Jane    5     1     
1       5   Allen   1       5       Joe     Homer   5     1     
0       7   NaN     0       7       Bryce   NaN     7     0     
1       6   NaN     1       6       NaN     White   6     1     

Is this possible with Pandas?

Solution

You can use resolvconf if it isn't already installed use: sudo apt-get install resolvconf.

Then edit the config file: sudo nano /etc/resolvconf/resolv.conf.d/base.
Enter your nameserves (one per line) with: nameserver xxx.xxx.xxx.xxx
Update resolvconf with sudo resolvconf -u

Changes should be permanent and for all interfaces.

Comments

[Hackerman]

When you do these steps: df_b = pd.DataFrame(raw_data, columns = ['type', 'id', 'name_2' ]) you can change the colnames after like df_a.columns = ['type_2','id_2','name_2']...with the right column names for each dataframe, you should get your desired merge result.

[ps0604]

yes, that worked

[Hackerman]

Glad to help :)

[NGRhodes]

You need to update resolvconf for the settings to be applied. sudo resolvconf -u

[Steven Roose]

What do I change to the file for adding new DNS nameservers?

[Steven Roose]

(The file is empty when I try to edit it, is that correct?)

[Pabi]

It is okay that it is empty just write: nameserver xxx.xxx.xxx.xxx.

[NGRhodes]

Pabi, might be worth updating your answer with further details added in these comments :)

[Nicolay77]

use sudo editor file so everyone can load their favourite editor.

[Scott Boston]

@petersc Using List Comprehension to set index on all three dataframes. A shortcut instead of using a for loop or writing set_index three different times.