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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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RDBMS Vs NOSQL awesome differences to read now

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NoSQL and RDBMS or SQL are different from each other. You may ask what is the difference. Below explained in a way that you can understand quickly.

rdbms vs no sql

💡Traditional Database

  • A schema is required. All traditional data warehouses using RDBMS to store datamarts.
  • Databases understand SQL language. It has a specific format and rules to interact with traditional databases.
  • Less scalable. It has certain limitations. 
  • Expensive to make the databases as scalable
  • Data should be in a certain format.
  • Data stored in row format.

NoSQL database

The growing internet usage and involving a number of devices caused to invent databases that have the capability to store any kind of data.

NoSQL Special Features
  • The schema is not required. Ability to handle multiple data types. This is the power of NoSQL.
  • NoSQL is much suitable for analytical databases. Since those should be flexible, scalable, and able to store any formatted data.
  • The increased usage of web applications, the availability of broadband for the common man, caused the generating of a variety of data. So NoSQL is absolutely needed for the new generation businesses.
  • Data stored in column format. In the form of key-value pairs.
  • Python, Ruby, PHP, and Java are top languages you need to interact with NoSQL databases.

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