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The Quick and Easy Way to Analyze Numpy Arrays

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The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array. Sum You can find the sum of Numpy arrays using the np.sum() function.  For example:  import numpy as np  a = np.array([1,2,3,4,5])  b = np.array([6,7,8,9,10])  result = np.sum([a,b])  print(result)  # Output will be 55 Mean You can find the mean of a Numpy array using the np.mean() function. This function takes in an array as an argument and returns the mean of all the values in the array.  For example, the mean of a Numpy array of [1,2,3,4,5] would be  result = np.mean([1,2,3,4,5])  print(result)  #Output: 3.0 Standard Deviation To find the standard deviation of a Numpy array, you can use the NumPy std() function. This function takes in an array as a par

Scrum Vs Agile Methodology best explained with more details


Life cycle of scrum with more details
#Life cycle of scrum with more details:
Scrum is part of the Agile movement. Agile is a response to the failure of the dominant software development project management paradigms (including waterfall) and borrows many principles from lean manufacturing. In 2001, 17 pioneers of similar methods met at the Snowbird Ski Resort in Utah and wrote the Agile Manifesto, a declaration of four values and twelve principles. 

These values and principles stand in stark contrast to the traditional Project Manager’s Body Of Knowledge (PMBOK). The Agile Manifesto placed a new emphasis on communication and collaboration, functioning software, team self organization, and the flexibility to adapt to emerging business realities.


How Does Scrum Fit With Agile?
The Agile Manifesto doesn’t provide concrete steps. Organizations usually seek more specific methods within the Agile movement. These include Crystal Clear, Extreme Programming, Feature Driven Development, Dynamic Systems Development Method (DSDM), Scrum, and others. While I like all the Agile approaches, for my own team Scrum was the one that enabled our initial breakthroughs. Scrum’s simple definitions gave our team the autonomy we needed to do our best work while helping our boss (who became our Product Owner) get the business results he wanted. Scrum opened our door to other useful Agile practices such as test-driven development (TDD). Since then we’ve helped businesses around the world use Scrum to become more agile. A truly agile enterprise would not have a “business side” and a “technical side.” It would have teams working directly on delivering business value. We get the best results when we involve the whole business in this, so those are the types of engagements I’m personally the most interested in.

What’s The Philosophy Behind Scrum?
Scrum’s early advocates were inspired by empirical inspect and adapt feedback loops to cope with complexity and risk. Scrum emphasizes decision making from real-world results rather than speculation. Time is divided into short work cadences, known as sprints, typically one week or two weeks long. The product is kept in a potentially shippable (properly integrated and tested) state at all times. At the end of each sprint, stakeholders and team members meet to see a demonstrated potentially shippable product increment and plan its next steps.


Scrum is a simple set of roles, responsibilities, and meetings that never change. By removing unnecessary unpredictability, we’re better able to cope with the necessary unpredictability of continuous discovery and learning.

(Ref: Scrummethodology)

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