Showing posts with the label analysis

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The Quick and Easy Way to Analyze Numpy Arrays

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

2 Top Tableau Unique Features

Tableau is one of the most popular tools in data analysis. Learning the Tableau gives you so many options in data analysis career. You can download Tableau Software free version here . Get a complete understanding document on how Tableau works here . Read this post for advancing in your Tableau Career. Unique functionality in Tableau Tableau Software was founded on the idea that analysis and visualization should not be isolated activities but must be synergistically integrated into a visual analysis process. Visual analysis means specifically: 1). Data Exploration Visual analysis is designed to support analytical reasoning. The goal of the visual analysis is to answer important questions using data and facts. In order to support analysis, it is not enough to only access and report on the data. Analysis requires computational support throughout the process. Typical steps in the analysis include such operations as filtering to focus on items of interest sorting to rank