This is a successful submission to the INSIGHT data engineering challenge for the session starting on April 16, 2018
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Updated
Feb 13, 2018 - Python
This is a successful submission to the INSIGHT data engineering challenge for the session starting on April 16, 2018
1-Outlier detection and removal of the outlier by Using IQR The Data points consider outliers if it's below the first quartile or above the third quartile 2-Remove the Outliers by using the percentile 3-Remove the outliers by using zscore and standard deviation
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calculate root mean square, variance, standard deviation, skewness, percentile covariance, pearson product-moment correlation coefficient, spearman correlation coefficient, kendall correlation coefficient, determination coefficient, slope, equation and plot of linear and polynomial regression degree 2 and 3 in various way using python library ma…
Conversion from Grading System to Percent. This is an approximate assumption as the grade system ranges the percent of an individual.
A library to compute histograms on distributed environments, on streaming data
A simple standalone script to plot HdrHistograms directly from the output of wrk load testing tool
Group values from a Pandas Series according to given intervals and represent them graphically with Plotly
t-Digest data structure in Python. Useful for percentiles and quantiles, including distributed enviroments like PySpark
Calculate Percentiles from raw Prometheus Blackbox exporter logs
Query and analyze percentiles of player levels on Steam.
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