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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
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5 Top features of MongoDB

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The most important of the philosophies that underpin MongoDB is the notion that one size does not fit all. For many years, traditional SQL databases (MongoDB is a document-orientated database) have been used for storing content of all types. It didn't matter whether the data was a good fit for the relational model (which is used in all RDBMS databases, such as MySQL, PostgresSQL, SQLite, Oracle, MS SQL Server, and so on). The data was stuffed in there, anyway. Purpose Part of the reason for this is that, generally speaking, i t's much easier (and more secure) to read and write to a database than it is to write to a file system. If you pick up any book that teaches PHP (such as PHP for Absolute Beginners (Apress, 2009)) by Jason Lengstorf, you'll probably find that almost right away the database is used to store information, not the file system.  It's just so much easier to do things that way. And while using a database as a storage bin works, developers always
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MongoDB Basics Tutorial top Resources

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Mongo DB has rapidly grown to become a popular database for web applications and is a perfect fit for Node.JS applications, letting you write Javascript for the client, backend and database layer. Its schemaless nature is a better match to our constantly evolving data structures in web applications, and the integrated support for location queries is a bonus that’s hard to ignore. Throw in Replica Sets for scaling, and we’re looking at really nice platform to grow your storage needs now and in the future. Now to shamelessly plug my driver. It can be downloaded via npm, or fetched from the github repository. To install via npm, do the following: npm   install   mongodb or go fetch it from github at  https://github.com/mongodb/node-mongodb-native Once this business is taken care of, let’s move through the types available for the driver and then how to connect to your Mongo DB instance before facing the usage of some CRUD operations. Tutorial on MongoDB Mongo DB data type
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