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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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How to Identify Data Relevant for Data Science Analytics

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Your government, your web server, your business partners, even your body. While we aren’t drowning in a sea of data, we’re finding that almost everything can (or has) been instrumented. We frequently combine publishing industry data from Nielsen Book Scan with our own sales data, publicly available Amazon data, and even job data to see what’s happening in the publishing industry. Data is everywhere Sites like Infochimps and Factual provide access to many large datasets, including climate data, MySpace activity streams, and game logs from sporting events. Factual enlists users to update and improve its datasets, which cover topics as diverse as endocrinologists to hiking trails. How the data is growing Much of the data we currently work with is the direct consequence of Web 2.0, and of Moore’s Law applied to data. The Web has people spending more time online and leaving a trail of data wherever they go. Mobile applications leave an even richer data trail since many of them a
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Real Opportunities to Get a Job in Data Analytics

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In my recent analysis, I have found that a lot of jobs will be created in big data analysis area. I have listed the real opportunities here. I have collected a few of the things, and I am sharing with you. Opportunities ahead to get a job  The huge volume of data created by users from multiple devices in a variety of formats.  Need specialized skills to analyze the data, and to get predictive results. The tools developed by SAP, IBM, and Oracle provide multiple opportunities to start a career in data analytics.   Video on job opportunities
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