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Ulrich Djounda

@UlrichDjounda

I am deeply passionate about data analytics. I find it incredibly fascinating how data can provide insights into the most complex of problem

Buea , South-west Cameroon

Public Apps

boilerplate-sea-level-predictor2 years ago
predictions based on data visualization
boilerplate-page-view-time-series-visualizer2 years ago
boilerplate-medical-data-visualizer (2)2 years ago
this repl basically visualize data using seaborn
boilerplate-medical-data-visualizer (1)2 years ago
boilerplate-demographic-data-analyzer (2)2 years ago
Given a csv file , this repl compute and display : the number of each races , the average age of men , the percentage of people with bachelors degrees ... In one word , it analyse the data base on specific quetions .
boilerplate-mean-variance-standard-deviation-calculator3 years ago
Given a list of nine digits , this repl compute : the mean , the variance , the standard deviation and other statistical operations. But this is not done randomly , i therefor invite you to come and discover , the beauty of this program .
boilerplate-demographic-data-analyzer3 years ago
LopsidedLawfulProgrammer3 years ago
firstrepl3 years ago
a function named calculate() uses Numpy to output the mean, variance, standard deviation, max, min, and sum of the rows, columns, and elements in a 3 x 3 matrix. The input of the function is a list containing 9 digits. The function convert the list into a 3 x 3 Numpy array, and then return a dictionary containing the mean, variance, standard deviation, max, min, and sum along both axes and for the flattened matrix.