assert_df_equals(result, answer)
def test_upper(self):
result = df_string.str.upper('movie')
movie = np.array(['FIELD OF DREAMS', 'STAR WARS'], dtype='O')
answer = pdc.DataFrame({'movie': movie})
assert_df_equals(result, answer)
def test_zfill(self):
result = df_string.str.zfill('movie', 16)
movie = np.array(['0field of dreams', '0000000star wars'], dtype='O')
answer = pdc.DataFrame({'movie': movie})
assert_df_equals(result, answer)
df_emp = pdc.read_csv('data/employee.csv')
class TestReadCSV:
def test_columns(self):
result = df_emp.columns
answer = ['dept', 'race', 'gender', 'salary']
assert result == answer
def test_data_types(self):
df_result = df_emp.dtypes
cols = np.array(['dept', 'race', 'gender', 'salary'], dtype='O')
dtypes = np.array(['string', 'string', 'string', 'int'], dtype='O')
df_answer = pdc.DataFrame({'Column Name': cols, 'Data Type': dtypes})
assert_df_equals(df_result, df_answer)
assert_df_equals(result, answer)
def test_upper(self):
result = df_string.str.upper('movie')
movie = np.array(['FIELD OF DREAMS', 'STAR WARS'], dtype='O')
answer = pdc.DataFrame({'movie': movie})
assert_df_equals(result, answer)
def test_zfill(self):
result = df_string.str.zfill('movie', 16)
movie = np.array(['0field of dreams', '0000000star wars'], dtype='O')
answer = pdc.DataFrame({'movie': movie})
assert_df_equals(result, answer)
df_emp = pdc.read_csv('notebooks/data/employee.csv')
class TestReadCSV:
def test_columns(self):
result = df_emp.columns
answer = ['dept', 'race', 'gender', 'salary']
assert result == answer
def test_data_types(self):
df_result = df_emp.dtypes
cols = np.array(['dept', 'race', 'gender', 'salary'], dtype='O')
dtypes = np.array(['string', 'string', 'string', 'int'], dtype='O')
df_answer = pdc.DataFrame({'Column Name': cols, 'Data Type': dtypes})
assert_df_equals(df_result, df_answer)
assert_df_equals(result, answer)
def test_upper(self):
result = df_string.str.upper('movie')
movie = np.array(['FIELD OF DREAMS', 'STAR WARS'], dtype='O')
answer = pdc.DataFrame({'movie': movie})
assert_df_equals(result, answer)
def test_zfill(self):
result = df_string.str.zfill('movie', 16)
movie = np.array(['0field of dreams', '0000000star wars'], dtype='O')
answer = pdc.DataFrame({'movie': movie})
assert_df_equals(result, answer)
df_emp = pdc.read_csv('C:/Users/Korisnik/Downloads/pandas_cub-master/pandas_cub-master/data/employee.csv')
class TestReadCSV:
def test_columns(self):
result = df_emp.columns
answer = ['dept', 'race', 'gender', 'salary']
assert result == answer
def test_data_types(self):
df_result = df_emp.dtypes
cols = np.array(['dept', 'race', 'gender', 'salary'], dtype='O')
dtypes = np.array(['string', 'string', 'string', 'int'], dtype='O')
df_answer = pdc.DataFrame({'Column Name': cols,
'Data Type': dtypes})
assert_df_equals(result, answer)
def test_upper(self):
result = df_string.str.upper("movie")
movie = np.array(["FIELD OF DREAMS", "STAR WARS"], dtype="O")
answer = pdc.DataFrame({"movie": movie})
assert_df_equals(result, answer)
def test_zfill(self):
result = df_string.str.zfill("movie", 16)
movie = np.array(["0field of dreams", "0000000star wars"], dtype="O")
answer = pdc.DataFrame({"movie": movie})
assert_df_equals(result, answer)
df_emp = pdc.read_csv("data/employee.csv")
class TestReadCSV:
def test_columns(self):
result = df_emp.columns
answer = ["dept", "race", "gender", "salary"]
assert result == answer
def test_data_types(self):
df_result = df_emp.dtypes
cols = np.array(["dept", "race", "gender", "salary"], dtype="O")
dtypes = np.array(["string", "string", "string", "int"], dtype="O")
df_answer = pdc.DataFrame({"Column Name": cols, "Data Type": dtypes})
assert_df_equals(df_result, df_answer)