def test_groupby_to_series_to_frame_2(self):
df = pd.DataFrame({'a': [6, 2, 2], 'b': [4, 5, 6]})
labels = ['g1', 'g1', 'g2']
benchmark = df.groupby(labels).apply(frame_to_series)
result = pandas_easy.groupby_to_series_to_frame(
df, frame_to_series, 1, use_apply=False, by=labels)
assert_frame_equal(result, benchmark)
def user_appCategory():
user_app_category = get_userID_appID()
user_app_category = user_app_category[:1000][:]
app_category_series = user_app_category['appCategory'].unique()
columns_name = [
'user_category_count_' + str(i) for i in app_category_series.tolist()
]
func = partial(count_user_appCategory, app_category_series)
user_app_cateogry_dataframe = pandas_easy.groupby_to_series_to_frame(
user_app_category,
func,
n_jobs=mp.cpu_count() - 1,
use_apply=True,
by='userID')
'''
user_app_category_groupby_user = user_app_category.groupby('userID',as_index = False)
user_app_cateogry_list = papply(user_app_category_groupby_user,count_user_appCategory,app_category_series)
#user_app_cateogry_list = user_app_category_groupby_user.apply(lambda x:count_user_appCategory(x,app_category_series))
user_app_cateogry_dataframe = pd.DataFrame(list(user_app_cateogry_list),
columns=['userID'] + columns_name)
'''
#print(user_app_cateogry_dataframe)
split_point = len(user_app_cateogry_dataframe) // 4
data1 = user_app_cateogry_dataframe[:split_point][:]
data2 = user_app_cateogry_dataframe[split_point:split_point * 2]
data3 = user_app_cateogry_dataframe[split_point * 2:split_point * 3]
data4 = user_app_cateogry_dataframe[split_point * 3:][:]
pickle.dump(data1, open(user_category_path1, 'wb'), protocol=4)
pickle.dump(data2, open(user_category_path2, 'wb'), protocol=4)
pickle.dump(data3, open(user_category_path3, 'wb'), protocol=4)
pickle.dump(data4, open(user_category_path4, 'wb'), protocol=4)
def test_groupby_to_series_to_frame_3(self):
df = pd.DataFrame({'a': [6, 2, 2], 'b': [4, 5, 6]})
benchmark = df.groupby('a').apply(max)
result = pandas_easy.groupby_to_series_to_frame(df, max, 1, by='a')
assert_frame_equal(result, benchmark)
