Remove Duplicate Items from a Python List

#Remove duplicate item from Python List old_list = ['k','l','k','m','m','n','o'] new_list =[] for element in old_list: if element not in new_list: new_list.append(element) #print(new_list) #['k', 'l', 'm', 'n', 'o'] #2nd Approach: old_list = ['k','l','k','m','m','n','o'] #new_list = dict.fromkeys(old_list) #{'k': None, 'l': None, 'm': None, 'n': None, 'o': None} new_list = dict.fromkeys(old_list).keys() #dict_keys(['k', 'l', 'm', 'n', 'o']) new_list = list( dict.fromkeys(old_list).keys() ) print(new_list) #['k', 'l', 'm', 'n', 'o']

Functional Programming and OOP Comparison Table

 

Basis For Comparison	Functional Programming	OOP
Definition	Functional programming emphasizes an evaluation of functions.	Object-oriented programming is based on the concept of objects.
Data	Functional programming uses immutable data.	Object-oriented uses mutable data.
Model	Functional programming does follow a declarative programming model.	Object-oriented programming does follow an imperative programming model.
Support	Functional Programming supports parallel programming.	Object-oriented programming does not support parallel programming.
Execution	In Functional programming, the statements can be executed in any order.	In OOPs, the statements should be executed in a particular order.
Iteration	In Functional programming, recursion is used for iterative data.	People use loops for iterative data in OOP.
Element	The basic elements of functional programming are Variables and Functions.	The essential elements of object-oriented programming are objects and methods.
Use	People use functional programming only when they have few things with more operations.	People use object-oriented programming when they have many things with few operations.

Dense_Rank with Group function

 Source_Path: "E:\source_files\CUSTOMER_CGI.CSV"

sdate,custid,pname,region,pcategory,price 01-01-2019,111,pen,NY,stationary,10.00 01-01-2019,111,pencil,NY,stationary,40.00 01-01-2019,222,pen,NY,stationary,10.00 01-01-2019,333,pen,NY,stationary,10.00 01-01-2019,444,book,CT,stationary,55.00 01-01-2019,222,pen,NY,stationary,10.00 01-02-2019,333,pen,NY,stationary,10.00 01-02-2019,333,pen,NY,stationary,10.00 01-02-2019,111,slate,NY,stationary,40.00 01-02-2019,111,slate,NY,stationary,40.00 01-02-2019,555,bag,NY,stationary,100.00 01-03-2019,444,pen,CT,stationary,10.00 01-03-2019,444,pencil,CT,stationary,15.00 01-03-2019,444,pencil,CT,stationary,15.00 01-03-2019,444,pen,CT,stationary,10.00 01-03-2019,111,pen,NY,stationary,10.00 01-03-2019,111,pen,NY,stationary,10.00 01-04-2019,111,pen,NY,stationary,10.00 01-04-2019,222,pen(,NY,stationary,10.00 01-04-2019,333,pen,NY,stationary,10.00 01-04-2019,444,choco,CT,stationary,50.00 01-04-2019,444,choco,CT,stationary,50.00 SET LINES 100 ALTER SESSION SET NLS_DATE_FORMAT = 'DD-MM-YYYY'; select * from CUSTOMER_CGI ORDER BY SDATE ; SDATE CUSTID PNAME REGION PCATEGORY PRICE ---------- ---------- ---------- ---------- ---------- ---------- 01-01-2019 333 pen NY stationary 10 01-01-2019 222 pen NY stationary 10 01-01-2019 111 pencil NY stationary 40 01-01-2019 111 pen NY stationary 10 01-01-2019 444 book CT stationary 55 01-01-2019 222 pen NY stationary 10 01-02-2019 111 slate NY stationary 40 01-02-2019 111 slate NY stationary 40 01-02-2019 333 pen NY stationary 10 01-02-2019 333 pen NY stationary 10 01-02-2019 555 bag NY stationary 100 01-03-2019 444 pen CT stationary 10 01-03-2019 444 pencil CT stationary 15 01-03-2019 444 pencil CT stationary 15 01-03-2019 444 pen CT stationary 10 01-03-2019 111 pen NY stationary 10 01-03-2019 111 pen NY stationary 10 01-04-2019 111 pen NY stationary 10 01-04-2019 222 pen NY stationary 10 01-04-2019 333 pen NY stationary 10 01-04-2019 444 choco CT stationary 50 01-04-2019 444 choco CT stationary 50 By SQL Method : Q1: --Get the custer detail who has done highest sales per day (datewise highest sales) SELECT * FROM ( SELECT custid, sdate, SUM (price) AS total_price, DENSE_RANK () OVER (PARTITION BY sdate ORDER BY SUM (price) desc) AS rnk --desc if u want maximum , asc if u want minimum FROM CUSTOMER_CGI GROUP BY sdate, custid ) tt WHERE tt.rnk = 1 ; Q2: --Get the custer detail along with date where the total sales price is/are the highest . SELECT * FROM ( SELECT custid, sdate, SUM (price) AS total_price, DENSE_RANK () OVER (ORDER BY SUM (price) desc) AS rnk --desc if u want maximum , asc if u want minimum FROM CUSTOMER_CGI GROUP BY sdate, custid ) tt WHERE tt.rnk = 1 By Dataframe Method: