Code source de ensae_teaching_cs.automation.modules_documentation

"""
Customize a Windows Setup for these teachings


:githublink:`%|py|5`
"""

import pandas
from pyquickhelper.pandashelper import df2rst


[docs]def rst_table_modules(classifier=False): """ Produces a table with some modules useful to do machine learning. :param classifier: keep classifiers? :return: string :githublink:`%|py|17` """ try: from pymyinstall.packaged import small_set, classifiers2string except KeyError: from pyquickhelper.pycode.pip_helper import fix_pip_902 fix_pip_902() from pymyinstall.packaged import small_set, classifiers2string mod = small_set() mod.sort() df = pandas.DataFrame(_.as_dict(rst_link=True) for _ in mod) if classifier: df = df[["usage", "rst_link", "kind", "version", "license", "purpose", "classifier"]] df["classifier"] = df.apply( lambda row: classifiers2string(row["classifier"]), axis=1) df.columns = ["usage", "name", "kind", "version", "license", "purpose", "classifier"] else: df = df[["usage", "rst_link", "kind", "version", "license", "purpose"]] df.columns = ["usage", "name", "kind", "version", "license", "purpose"] df["lname"] = df["name"].apply(lambda s: s.lower()) df = df.sort_values("lname").drop("lname", axis=1) df = df.reset_index(drop=True).reset_index(drop=False) return df2rst(df)