[FIXED] How to divide a column into groups and loop across the groups

Issue

I have a column with IDs and I divide the column into groups using pd.cut like this:

ID	Group
3645390	1
3678122	1
3615370	2
3371122	2
3645590	2
3778682	3
3125140	3
3578772	3

After that, how do I loop across the 'Group' column and pick out the IDs and assign them to an array.

array_1 = [3645390,3678122]
array_2 = [3615370,3371122,3645590]
.
so on..

Solution

It is often a bad practice to generate variables, the ideal is to use a container (dictionaries are ideal).

You could use groupby and transform the output into dictionary of lists:

out = df.groupby('Group')['ID'].apply(list).to_dict()

Then access your lists by group key:

>>> out
{1: [3645390, 3678122],
 2: [3615370, 3371122, 3645590],
 3: [3778682, 3125140, 3578772]}

>>> out[1]  ## group #1
[3645390, 3678122]

If you really want array_x as keys:

(df.assign(Group='array_'+df['Group'].astype(str))
   .groupby('Group')['ID'].apply(list).to_dict()
)

output:

{'array_1': [3645390, 3678122],
 'array_2': [3615370, 3371122, 3645590],
 'array_3': [3778682, 3125140, 3578772]}

Answered By - mozway