Pandas count results per unique server

Question

I am very new to both pandas and python. I did find this

Pandas Count Unique Occurances by Month

on stackoverflow that is similar to my question, but I can't seem to manipulate the answer to address my problem so here goes:

I have a list of servers, and each server has a number of patches that apply to that server. The excel looks a bit like this:

Server Name - Missing Patch
Server 1 ---- file
Server 1 ---- reg
Server 1 ---- file
Server 2 ---- reg
Server 2 ---- file
Server 2 ---- file
Server 2 ---- file
Server 3 ---- reg
Server 3 ---- reg
Server 3 ---- file
Server 3 ---- reg
Server 3 ---- unicorns

I would like to make a dataframe that has one column of unique servers and one column counting how many missing patches there are for each server. It should look like this:

Server Name - Missing Patch Count
Server 1 ---- 3
Server 2 ---- 4
Server 3 ---- 5

I can't seem to make nunique work, and value_counts returns a series, which isn't quite what I want. I managed to get df.drop_duplicates('Server Name') to work to only display unique instances of server names, but I can't get it to sort the column by that data.

I realise there have been a lot of similar questions on here, but I am new to pandas and can't seem to apply the right syntax to my problem using the documentation - can anyone help?

Answer 1

You can groupby 'Server Name', call count and then reset_index to restore the server name column:

In [330]:

df.groupby('Server Name').count().reset_index()
Out[330]:
  Server Name  Missing Patch
0    Server 1              3
1    Server 2              4
2    Server 3              5