Search Results for "numerical python 1.7.1"

...Shows how a target value (e.g. "Survived" in the Titanic dataset) relates to other features. Sweetviz integrates associations for numerical (Pearson's correlation), categorical (uncertainty coefficient) and categorical-numerical (correlation ratio) datatypes seamlessly, to provide maximum information for all data types. Automatically detects numerical, categorical and text features, with optional manual overrides. min/max/range, quartiles, mean, mode, standard deviation, sum, median absolute deviation, coefficient of variation, kurtosis, skewness.

Data Preprocessing Automation is a Python-based GUI application designed to simplify and automate data preprocessing tasks. It allows users to upload Excel files, automatically handle missing values, remove duplicates, and detect and remove outliers using statistical methods. The application provides data visualization tools, including box plots for distribution analysis and scatter plots for exploring relationships between variables. Users can download the processed data for further...

DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify...

Python(x,y) is a free scientific and engineering development software for numerical computations, data analysis and data visualization based on Python programming language, Qt graphical user interfaces and Spyder interactive scientific development environment.

There are functions for numerical integration of the standard normal probability distribution. They can be used to find probabilities, find z-alpha values, calculate confidence interval, etc. New functionality I wish to add are hypothesis testing and calculation of p-value, type I & II errors, etc. These functions would come in handy to anyone taking introductory or intermediate-level courses in probability, statistics and data analysis. There are several numerical integration techniques...