def test_get_team_result_on_date_nominal(self):
"""
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
date = datetime.datetime(day=25, month=10, year=2019)
res = Api.get_team_result_on_date('Los Angeles Lakers', date, df)
self.assertEqual('95-86', res)
def test_filter_df_on_team_names_nominal(self):
"""
The function `filter_df_on_team_names` shall filter the given data frame only where the box score data is from
one of the given team names.
"""
my_csv = 'small_data_set.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
team_df = Api.filter_df_on_team_names(df, ['Los Angeles Lakers'])
self.assertEqual(team_df.shape[0], 3)
team_df = Api.filter_df_on_team_names(
df, ['Los Angeles Lakers', 'Chicago Bulls'])
self.assertEqual(team_df.shape[0], 4)
def test_create_scatter_plot_with_trend_line_svg_save(self):
"""
The function `create_scatter_plot_with_trend_line` shall create and save a scatter plot.
"""
my_csv = 'small_data_set.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, _, _ = Api.create_scatter_plot_with_trend_line(
x_key='minutes_played',
y_key='points',
df=df,
save_path='svg_buffer')
self.assertEqual(41174, len(plot_path))
def test_create_scatter_plot_with_trend_line_nominal(self):
"""
The function `create_scatter_plot_with_trend_line` shall create and save a scatter plot.
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, _, _ = Api.create_scatter_plot_with_trend_line(
x_key='minutes_played',
y_key='points',
df=df,
save_path=self.logs_dir)
self.assertTrue(os.path.exists('%s.png' % plot_path))
def test_create_date_plot_invalid_grid(self):
"""
The function `create_date_plot` shall create and save a date plot with a default grid when provided
with nominal data and grid is not one of the following: both, x, or y.
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, _, _ = Api.create_date_plot(player='Anthony Davis',
y_key='points',
df=df,
save_path=self.logs_dir,
grid='BAD')
self.assertTrue(os.path.exists('%s.png' % plot_path))
def test_create_date_plot_nominal(self):
"""
The function `create_date_plot` shall create and save a date plot when provided nominal data.
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, outlier_df, _ = Api.create_date_plot(
player='Anthony Davis',
y_key='points',
df=df,
save_path=self.logs_dir)
self.assertTrue(os.path.exists('%s.png' % plot_path))
self.assertEqual(5, outlier_df.shape[0])
def test_create_date_plot_player_substring(self):
"""
The function `create_date_plot` shall return a plot path of invalid player name when given a substring of a
player name that exists in the pandas.DataFrame object provided.
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, _, _ = Api.create_date_plot(player='Anthony',
y_key='points',
df=df,
save_path=self.logs_dir,
grid='both')
self.assertEqual(plot_path, 'Invalid player name of Anthony')
def test_create_scatter_plot_with_trend_line_save_path(self):
"""
The function `create_scatter_plot_with_trend_line` shall create and save a scatter plot if given a
specific path.
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
save_path = os.path.join(self.logs_dir, 'test.png')
plot_path, _, _ = Api.create_scatter_plot_with_trend_line(
x_key='minutes_played', y_key='points', df=df, save_path=save_path)
self.assertTrue(os.path.exists(plot_path))
self.assertTrue(os.path.exists(save_path))
self.assertEqual(plot_path, save_path)
def test_create_date_plot_invalid_max_seconds(self):
"""
The function `create_date_plot` shall create and save a plot with default max and min seconds when provided
an invalid max seconds value.
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, _, _ = Api.create_date_plot(player='Anthony Davis',
y_key='points',
df=df,
save_path=self.logs_dir,
max_seconds='a')
self.assertTrue('Max/Min seconds incorrect type' in plot_path)
def test_create_date_plot_y_grid(self):
"""
The function `create_date_plot` shall create and save a date plot with a y axis grid only when provided
with nominal data and grid = 'y'.
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, _, _ = Api.create_date_plot(player='Anthony Davis',
y_key='points',
df=df,
save_path=self.logs_dir,
grid='y')
self.assertTrue(os.path.exists('%s.png' % plot_path))
def test_create_bar_plot_one_column(self):
"""
The function `create_bar_plot` shall create and save a bar plot when only one column is provided.
"""
my_csv = 'small_data_set.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path = Api.create_bar_plot(df, ['points'],
save_path=self.logs_dir,
team=Team.LOS_ANGELES_LAKERS.name,
date=datetime.datetime(day=22,
month=10,
year=2019))
self.assertTrue(os.path.exists('%s.png' % plot_path))
def test_create_scatter_plot_with_trend_line_filter_teams(self):
"""
The function `create_scatter_plot_with_trend_line` shall create and save a scatter plot with a filtered data
frame based on team name.
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, _, _ = Api.create_scatter_plot_with_trend_line(
x_key='minutes_played',
y_key='points',
df=df,
teams=['Los Angeles Lakers'],
save_path=self.logs_dir)
self.assertTrue(os.path.exists('%s.png' % plot_path))
def test_get_team_date_nominal(self):
"""
The function `get_team_date` shall retrieve a pandas.DataFrame object containing the player box score
information of a given day and team.
"""
my_csv = 'small_data_set.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
team_df = Api.get_team_date_df(
df, 'CHICAGO_BULLS', datetime.datetime(day=23, month=10,
year=1996))
self.assertEqual(team_df.shape[0], 0)
team_df = Api.get_team_date_df(
df, 'CHICAGO_BULLS', datetime.datetime(day=22, month=10,
year=1996))
self.assertEqual(team_df.shape[0], 1)
def test_create_date_plot_outlier_count(self):
"""
The function `create_date_plot` shall create and save a plot at the desired location and create a
pandas.DataFrame object holding the desired number of outlier points.
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, outlier_df, _ = Api.create_date_plot(
player='Anthony Davis',
y_key='points',
df=df,
num_outliers=8,
save_path=self.logs_dir)
self.assertTrue(os.path.exists('%s.png' % plot_path))
self.assertEqual(8, outlier_df.shape[0])
def test_create_scatter_plot_with_trend_line_minutes_filter(self):
"""
The function `create_scatter_plot_with_trend_line` shall create and save a scatter plot when provided with
a minimum and maximum minutes value.
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, _, _ = Api.create_scatter_plot_with_trend_line(
x_key='minutes_played',
y_key='points',
df=df,
min_seconds=10,
max_seconds=30,
save_path=self.logs_dir)
self.assertTrue(os.path.exists('%s.png' % plot_path))
def test_create_scatter_plot_with_trend_line_data_frames(self):
"""
The function `create_scatter_plot_with_trend_line` shall create and save a scatter plot, return
the outlier DataFrame object, and return the total filtered DataFrame object.
"""
my_csv = 'small_data_set.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, outlier_df, total_df = Api.create_scatter_plot_with_trend_line(
x_key='minutes_played',
y_key='points',
df=df,
save_path=self.logs_dir)
self.assertTrue(os.path.exists('%s.png' % plot_path))
self.assertEqual(outlier_df.shape[0], 5)
self.assertEqual(total_df.shape[0], 55)
def test_create_date_plot_nominal_params(self):
"""
The function `create_date_plot` shall create and save a date plot when provided nominal data and optional
**kwarg arguments.
"""
my_csv = 'player_box_scores.csv'
df = Api.get_existing_data_frame(my_csv, logger=self.logger)
plot_path, _, _ = Api.create_date_plot(player='Anthony Davis',
y_key='points',
df=df,
save_path=self.logs_dir,
min_seconds=300,
max_seconds=2200,
num_outliers=7,
grid='x',
mean_line=False)
self.assertTrue(os.path.exists('%s.png' % plot_path))