pybeepop 0.1.3

Assessing the Influence of Pesticide Usage, Parasitic Factors, and Climate on Honey Bee Populations in the United States (2015-2019)

pybeepop

Assessing the Influence of Pesticide Usage, Parasitic Factors, and Climate on Honey Bee Populations in the United States (2015-2019)

Installation

$ pip install pybeepop

Usage

The pybeepop has 4 modules ("analysis", "clean_data", "eda", and "to_ddl"), with the goal of analyzing the bee population project.

from pybeepop.analysis import *
from pybeepop.clean_data import *
from pybeepop.eda import *
from pybeepop.to_ddl import *

# read the raw data

data1_path_origin = '../tests/data/original/average_monthly_temperature_by_state_1950-2022.parquet'
data2_path_origin = '../tests/data/original/epest_county_estimates.parquet'
data3_path_origin = '../tests/data/original/save_the_bees.parquet'
data4_path_origin = '../tests/data/original/pollution_2000_2021.parquet'

data1, data2, data3, data4 = read_data(data1_path_origin, data2_path_origin, data3_path_origin, data4_path_origin)

# Write the sql file and load it to database

sql_path = "../tests/scripts/output.sql"
temperature_data_path = "../tests/data/processed/average_monthly_temperature_by_state_1950-2022.csv"

init_tables(sql_path)
create_sql_MonitorStation(temperature_data_path, sql_path)
connection = connect_to_db(3307, 'localhost')
load_sql_to_db(connection, sql_path)

# fetch data from the database and return it as a dataframe

query_monitor_station = """
    SELECT *
    FROM MonitorStation
"""
columns_monitor_station = ['CentroidLongitude', 'CentroidLatitude', 'Year', 'AverageTemperature']
monitor_station_df = query_transform_dataframe(connection, query_monitor_station, columns_monitor_station)

# combine plots into 2 x 2 scale

concat_plots(Illinois_plot_1, Massachusetts_plot_1, Kansas_plot_1, Georgia_plot_1, loss_disease_parasite_path)

# check variance inflation factor (VIF)

vif_path = "../tests/data/processed/vif.csv"
check_vif(data)

# check and generate correlation matrix

correlation_path = "../tests/images/correlation_matrix.png"
correlation(data, correlation_path)

# run linear and non-linear models

linear_model_path = "../tests/models/linear_model.pkl"
shap_train_path = "../tests/images/shap_train.png"
shap_overall_path = "../tests/images/shap_overall.png"
X, y, model = linear_model(data, linear_model_path)
non_linear_model(X, y, shap_train_path, shap_overall_path)

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

pybeepop was created by Hanlin Zhao. It is licensed under the terms of the MIT license.

Credits

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