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A package containing the necessary functions to smoothly run the analysis in DSCI-310-Group-1

Project description

grouponefunctions

A package containing the necessary functions to smoothly run the analysis in DSCI-310-Group-1.

Installation

Note: The installation is not likely to proceed for Python version lower than 3.9.10. Please check your Python version the code below.

python --version

Then you can install the package by the command below.

pip install grouponefunctions

Usage

grouponefunctions is primarily used for analysis of Predicting students’ grades using multi-variable regression, but contains three general use functions. To implement the functions, import our package grouponefunctions as a module. The package has three functions: splitxy, listfun, and plotsquaredata.

split_xy

split_xy can be used to split data into predictor feature and target variables as follows:

from grouponefunctions.grouponefunctions import split_xy

X_train, y_train = split_xy(train_df, ["feature1", "feature2", "feature3"], target)
X_test, y_test = split_xy(test_df, ["feature1", "feature2", "feature3"], target) 

plot_square_data

This function is capable at creating plots to display in a grid configuration.

from grouponefunctions.grouponefunction import plot_square_data

plot_square_data(X_train, y_train, ["feature1", "feature2", "feature3"], ["title1", "title2", "title3], "This is Plot 1")
plot_square_data(dependent, independednts, ["income"], ["retirement_age"], "Income and Retirement Age Relation")

list_abs

This function is the abstract function for list, used in Results part in the analysis.

from grouponefunctions.grouponefunction import list_abs

list_abs(preprocessor, "pipeline-2", "onehotencoder", categorical_features)

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

grouponefunctions was created by Andres Zepeda Perez, Daniel Hou, Zizhen Guo, Timothy Zhou. It is licensed under the terms of the MIT license.

Credits

grouponefunctions was created with cookiecutter and the py-pkgs-cookiecutter template.

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