Featured Post

Python map() and lambda() Use Cases and Examples

-
Image
 In Python, map() and lambda functions are often used together for functional programming. Here are some examples to illustrate how they work. Python map and lambda top use cases 1. Using map() with lambda The map() function applies a given function to all items in an iterable (like a list) and returns a map object (which can be converted to a list). Example: Doubling Numbers numbers = [ 1 , 2 , 3 , 4 , 5 ] doubled = list ( map ( lambda x: x * 2 , numbers)) print (doubled) # Output: [2, 4, 6, 8, 10] 2. Using map() to Convert Data Types Example: Converting Strings to Integers string_numbers = [ "1" , "2" , "3" , "4" , "5" ] integers = list ( map ( lambda x: int (x), string_numbers)) print (integers) # Output: [1, 2, 3, 4, 5] 3. Using map() with Multiple Iterables You can also use map() with more than one iterable. The lambda function can take multiple arguments. Example: Adding Two Lists Element-wise list1 = [ 1 , 2 , 3 ]
Post a Comment

SAS- Get the Right Training, Go get the Job

-
sas career options

sas career options
Many people think analytics is about gathering data using software tools and creating dashboards and reports. However, analytics is much more. Analytics goes beyond data; its primary goal is to enable business decisions based on that data. This involves working with stakeholders to understand the gaps in the business and using this knowledge as a guide to manipulate data, derive useful insights, and make recommendations – all key actions to increase revenue and lower costs.
Wherever you sit in your organization, what’s most important is the bottom line. And so whether you lead business or IT units or are in the trenches, the analytics profession has likely crossed your mind. What does it entail? Who are true analysts? How does one become an analyst?
Those of you specifically in a data management, data warehousing or business intelligence role may wonder how to further develop your analytics career. On the surface, an “analytics career” can be quite broadly defined, and the transition to it can seem very confusing. However, the structured approach we describe in this article will make it easy to choose your path – and give managers and leaders an appreciation for the developmental steps to success.

Don’t expect to learn analytics from blogs and social chatter. There is a lot of information published online. Do your own due diligence.
Don’t view conferences as a solution for training

Analytics is hot field- many jobs available. To land a great analytics job, consider networking via LinkedIn. Use LinkedIn Jobs as well as LinkedIn analytics groups and highlight your analytics skills using tags. Also consider key job portals, such as Craigslist, icrunchdata, Indeed, Dice and Monster.

Read more...

Comments

Post a Comment

Thanks for your message. We will get back you.

Popular posts from this blog

How to Fix datetime Import Error in Python Quickly

-
Image
Here's a quick resolution for import datetime Python error . The reason is your .py python script name and datetime  are the same. I'll show you how this error happens and its resolution.   Here's the Resolution for ImportError I've created a script called 'datetime.py.' to check whether the minute value is 'odd' or not. During the import of my python script, I got the import error cannot import name datetime. My Script: datetime.py My script's intention is to find whether the minute value is odd or not. Python Logic from datetime import datetime odds = [ 1 , 3 , 5 , 7 , 9 , 11 , 13 , 15 , 17 , 19 , 21 , 23 , 25 , 27 , 29 , 31 , 33 , 35 , 37 , 39 , 41 , 43 , 45 , 47 , 49 , 51 , 53 , 55 , 57 , 59 ] right_this_minute = datetime.today().minute if right_this_minute in odds: print ( "This minute seems a little odd." ) else : print ( "Not an odd minute." ) ImportError I have imported my datetime.py from Linux. It gives an error
Read more

SQL Query: 3 Methods for Calculating Cumulative SUM

-
Image
SQL provides various constructs for calculating cumulative sums, offering flexibility and efficiency in data analysis. In this article, we explore three distinct SQL queries that facilitate the computation of cumulative sums. Each query leverages different SQL constructs to achieve the desired outcome, catering to diverse analytical needs and preferences. Using Window Functions (e.g., PostgreSQL, SQL Server, Oracle) SELECT id, value, SUM(value) OVER (ORDER BY id) AS cumulative_sum  FROM your_table; This query uses the SUM() window function with the OVER clause to calculate the cumulative sum of the value column ordered by the id column. Using Subqueries (e.g., MySQL, SQLite): SELECT t1.id, t1.value, SUM(t2.value) AS cumulative_sum FROM your_table t1 JOIN your_table t2 ON t1.id >= t2.id GROUP BY t1.id, t1.value ORDER BY t1.id; This query uses a self-join to calculate the cumulative sum. It joins the table with itself, matching rows where the id in the first table is greater than or
Read more

Python placeholder '_' Perfect Way to Use it

-
Image
What is placeholder in Python? The purpose of it is to mask the variable that you don't want to use in a function. In python, y ou can call the underscore ( _ ) operator placeholder. Below, you'll find how to use single and double placeholders in a function. What is placeholder in python The purpose of placeholder in Python is to mask variables that you don't want to use in a function. So that your code will be readable. Moreover, in future, if you want to use those variables you can replace the placeholders with the names you want. In This Page You'll know in three steps how to use placeholder correctly. Creating a function Logic to use single placeholder Logic to use two placeholders 1. Creating a function. def function_that_returns_multiple_values(x):        return x*2, x*3, x+1        for i in range(0,5):             square, cube, added_one = function_that_returns_multiple_values(i)             print(square, cube) Here, in print, it returns two variables. I will s
Read more