pycrimeprediction 0.1.0

group 10 description

pycrimeprediction

pycrimeprediction is DSCI 301 Group 10's Python package for loading, analyzing, and saving data related to crime rates

Installation

$ pip install pycrimeprediction

Usage

pycrimeprediction can be used to analyze data related to crime rates.

Below is a usage example of two of our functions:

from pycrimeprediction.read_save_data import read_save_data
from pycrimeprediction.add_if_crime import add_if_crime_feature

input_path = "url-for-data.csv"
output_path = "saved-data-to-file.csv"

#Read data and split into examples and labels
df = read_save_data(input_path, output_path)
X = df.iloc[:, 0:-1]
y = df.iloc[:, -1]

#Print Cross-validation results for the Logistic Regression classifier
print(perform_analysis(X,y))

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

pycrimeprediction was created by Cassandra Zhang, Pragya Singhal, James He, and Ethan Kenny. It is licensed under the terms of the MIT license.

Credits

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