Analysis from unique values from one column naming files from another - python-3.x

Question

I have the following code that I am using to loop through unique values in my data set and it works great, but I would like to change the export name to a more appropriate unique value that I can use in a dashboard. The following is the code that I have where x in path is taken from teams unique names. However, for this part only, I'd like the name to be assigned from a list outside of the original dataframe.
team = df['RSA'].unique()
for x in team:
path2 = r'C:\Users\davidlopez\Desktop\regions\%s.csv' %x
r = HROs['RSA'] == x
Completed = HROs['Current Team Simple'].isin(['Completed'])
table = HROs[Completed & r]
top20 = table.groupby(['To Position Title']).RequestNumber.count().sort_values().nlargest(20)
top20.to_csv(path2, index=True, header=True)
Couple of ways I've tried to solve this:
1) Create a list and assign x in the path to the list instead of x.
mylist = ['HR_DASH_0034','HR_DASH_0035','HR_DASH_0036','HR_DASH_0037','HR_DASH_0038','HR_DASH_0039','HR_DASH_0040',
'HR_DASH_0041','HR_DASH_0042','HR_DASH_0043','HR_DASH_0044','HR_DASH_0045','empty']
for x in team:
path2 = r'C:\Users\davidlopez\Desktop\regions\%s.csv' %mylist
r = HROs['RSA'] == x
Completed = HROs['Current Team Simple'].isin(['Completed'])
table = HROs[Completed & r]
top20 = table.groupby(['To Position Title']).RequestNumber.count().sort_values().nlargest(20)
top20.to_csv(path2, index=True, header=True)
That doesn't work because it doesn't loop and it doesn't align the new values to the original dataframe values. Cross that off the list.
2) I thought maybe a loop inside the loop would do the trick:
team = df['RSA'].unique()
mylist = ['HR_DASH_0034','HR_DASH_0035','HR_DASH_0036','HR_DASH_0037','HR_DASH_0038','HR_DASH_0039','HR_DASH_0040',
'HR_DASH_0041','HR_DASH_0042','HR_DASH_0043','HR_DASH_0044','HR_DASH_0045','empty']
for x in team:
for name in mylist:
path2 = r'C:\Users\davidlopez\Desktop\regions\%s.csv' %name
r = HROs['RSA'] == x
Completed = HROs['Current Team Simple'].isin(['Completed'])
table = HROs[Completed & r]
top20 = table.groupby(['To Position Title']).RequestNumber.count().sort_values().nlargest(20)
top20.to_csv(path2, index=True, header=True)
That didn't work either. It just gave me the last value in mylist, but also it doesn't align the the unique values in team list appropriately.
3) Next I created a dataframe with the unique values from team and the new list.
team = df['RSA'].unique()
mylist = ['HR_DASH_0034','HR_DASH_0035','HR_DASH_0036','HR_DASH_0037','HR_DASH_0038','HR_DASH_0039','HR_DASH_0040',
'HR_DASH_0041','HR_DASH_0042','HR_DASH_0043','HR_DASH_0044','HR_DASH_0045','empty']
dict = {'RSA': team, 'DASH_ID': mylist}
newdf = pd.DataFrame(dict)
print (newdf)
RSA DASH_ID
0 Intermountain Region, R4 HR_DASH_0034
1 Pacific Southwest Region, R5 HR_DASH_0035
2 Alaska Region, R10 HR_DASH_0036
3 Pacific Northwest Region, R6 HR_DASH_0037
4 Northern Region, R1 HR_DASH_0038
5 Eastern Region, R9 HR_DASH_0039
6 Albuquerque Service Center(ASC) HR_DASH_0040
7 Rocky Mountain Region, R2 HR_DASH_0041
8 Research & Development(RES) HR_DASH_0042
9 Washington Office(WO) HR_DASH_0043
10 Southwestern Region, R3 HR_DASH_0044
11 Southern Region, R8 HR_DASH_0045
12 L2 Desc Not Available empty
However, I still don't know how to get the DASH_ID column element names to export in my path mentioned above.
So in the end, HR_DASH_0034, name should align to Intermountain Region, R4 when the file is sent out.
Any help appreciated!

Answer 1

Inside your first approach, just use:
mylist = [...] # your list definition
ml_iter = iter(mylist)
and inside the loop, replace mylist with:
path2 = r'C:\Users\davidlopez\Desktop\regions\%s.csv' %str(next(ml_iter))
More info: https://www.programiz.com/python-programming/methods/built-in/iter
Lemme know if this helps!
UPDATE: Second Solution
for x, m in zip(team, mylist):
path2 = r'C:\Users\davidlopez\Desktop\regions\%s.csv' %m
r = HROs['RSA'] == x
Completed = HROs['Current Team Simple'].isin(['Completed'])
table = HROs[Completed & r]
top20 = table.groupby(['To Position Title']).RequestNumber.count().sort_values().nlargest(20)
top20.to_csv(path2, index=True, header=True)
Let me know if this works!