Data Science Utilities

Data Science utilities in python.

• Free software: MIT license
• Documentation: http://data-science-utilities-python.readthedocs.io.

Features

Missing Data Statistic

from data_science_utilities import data_science_utilities

# make statistic
missing_data = data_science_utilities.missing_data_stats(df)

# display statistic
missing_data

Read CSV files from path

from data_science_utilities import data_science_utilities

train_path = '../data/raw/train.csv'
test_path = '../data/raw/test.csv'

X_train, X_test = data_science_utilities.read_csv_files(train_path, test_path)

Plotting distribution normal

from data_science_utilities import data_science_utilities

data_science_utilities.plot_dist_norm(dist, 'distribution normal')

Plotting correlation matrix

from data_science_utilities import data_science_utilities

data_science_utilities.plot_corelation_matrix(data)

Plotting top attributes correlation matrix

from data_science_utilities import data_science_utilities

data_science_utilities.plot_top_corelation_matrix(data, target, k=10, cmap='YlGnBu')

Plotting attributes by scatter chart

from data_science_utilities import data_science_utilities

data_science_utilities.plot_scatter(data, column_name, target)

Plotting attributes by box bar

from data_science_utilities import data_science_utilities

data_science_utilities.plot_box(data, column_name, target)

Plotting category by box bar

from data_science_utilities import data_science_utilities

data_science_utilities.plot_category_columns(data, limit_bars=10)

Generate a simple plot of the test and traning learning curve

from data_science_utilities import data_science_utilities

data_science_utilities.plot_learning_curve(estimator, title, X, y, ylim=None,
                    cv=None, train_sizes=np.linspace(.1, 1.0, 5))

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.