add apply function which returns empty list if pd.series is empty

.gitignore

@@ -102,3 +102,6 @@ venv.bak/
 
 # mypy
 .mypy_cache/
+
+# pycharm
+.idea

.travis.yml

@@ -0,0 +1,11 @@
+language: python
+python: 3.6.7
+env:
+- BOTO_CONFIG=/dev/null
+install:
+- pip install --upgrade pip
+- pip install coverage
+script:
+- coverage run --include=kuma setup.py test
+after_success:
+- coveralls

kuma/__init__.py

@@ -0,0 +1,2 @@
+from kuma.kuma import SeriesAccessor
+from kuma.kuma_pandas import kuma_pandas as pandas

kuma/kuma.py

@@ -0,0 +1,10 @@
+import pandas as pd
+
+
+@pd.api.extensions.register_series_accessor('kuma')
+class SeriesAccessor(object):
+    def __init__(self, pandas_obj: pd.Series) -> None:
+        self._obj = pandas_obj
+
+    def apply(self, func, **kwargs):
+        return self._obj.apply(func=func, **kwargs) if not self._obj.empty else []

kuma/kuma_pandas.py

@@ -0,0 +1,13 @@
+import pandas as pd
+
+
+class KumaSeries(object):
+    """To make IDE intellisense work well, functions are defined as staticmethod and named with `kuma_` prefix.
+    """
+    @staticmethod
+    def kuma_apply(data: pd.Series, func, **kwargs):
+        return data.apply(func=func, **kwargs) if not data.empty else []
+
+
+def kuma_pandas():
+    pd.Series.kuma_apply = KumaSeries.kuma_apply

setup.py

@@ -0,0 +1,28 @@
+from setuptools import setup, find_packages
+from codecs import open
+from os import path
+
+with open(path.join(path.abspath(path.dirname(__file__)), 'README.md'), encoding='utf-8') as f:
+    long_description = f.read()
+
+
+install_requires = [
+    'pandas',
+]
+
+setup(
+    name='kuma',
+    use_scm_version=True,
+    setup_requires=['setuptools_scm'],
+    description='A package which adds new functions to a pandas dataframe or series.',
+    long_description=long_description,
+    long_description_content_type="text/markdown",
+    author='M3, inc.',
+    url='https://github.com/m3dev/kuma',
+    license='MIT License',
+    packages=find_packages(),
+    install_requires=install_requires,
+    tests_require=[],
+    test_suite='test',
+    classifiers=['Programming Language :: Python :: 3.6'],
+)

test/test_kuma_apply.py

@@ -0,0 +1,20 @@
+import unittest
+
+import pandas as pd
+
+import kuma
+
+kuma.pandas()
+
+
+class TestKumaApply(unittest.TestCase):
+    def test_with_empty(self):
+        df = pd.DataFrame(columns=['input'])
+        df['result'] = df['input'].kuma_apply(lambda x: x + 1)
+        self.assertEqual(len(df['result']), 0)
+
+    def test_with_not_empty(self):
+        df = pd.DataFrame(dict(input=[0, 1]))
+        df['result'] = df['input'].kuma_apply(lambda x: x + 1)
+        self.assertEqual(len(df['result']), 2)
+

test/test_series_accessor.py

@@ -0,0 +1,15 @@
+import unittest
+import pandas as pd
+import kuma
+
+
+class TestSeriesAccessor(unittest.TestCase):
+    def test_apply_with(self):
+        df = pd.DataFrame(dict(input=[0, 1]))
+        df['result'] = df['input'].kuma.apply(lambda x: x + 1)
+        self.assertListEqual(df['result'].tolist(), [1, 2])
+
+    def test_apply_with_empty_df(self):
+        df = pd.DataFrame(columns=['input'])
+        df['result'] = df['input'].kuma.apply(lambda x: x + 1)
+        self.assertEqual(len(df['result']), 0)

yapf.ini

@@ -0,0 +1,3 @@
+[style]
+based_on_style = pep8
+column_limit = 120