def testExampleMultipleCSVGeneration(ref):
"""
This test uses generate_dataframe() from dataframes.py to
generate two simple Pandas dataframe, and then saves each to a CSV
file.
The test checks the generated CSV files are as expected, in terms of
both data content (the values) and metadata (the types, order, etc)
of the columns.
"""
df1 = generate_dataframe(nrows=10)
df2 = generate_dataframe(nrows=20)
outpath1 = os.path.join(ref.tmp_dir, 'csv_result1.csv')
outpath2 = os.path.join(ref.tmp_dir, 'csv_result2.csv')
df1.to_csv(outpath1, index=False)
df2.to_csv(outpath2, index=False)
columns = ref.all_fields_except(['random'])
ref.assertCSVFilesCorrect([outpath1, outpath2],
['dataframe_result.csv', 'dataframe_result2.csv'],
check_data=columns)
def testExampleMultipleCSVGeneration(ref):
"""
This test uses generate_dataframe() from dataframes.py to
generate two simple Pandas dataframe, and then saves each to a CSV
file.
The test checks the generated CSV files are as expected, in terms of
both data content (the values) and metadata (the types, order, etc)
of the columns.
"""
df1 = generate_dataframe(nrows=10)
df2 = generate_dataframe(nrows=20)
outpath1 = os.path.join(ref.tmp_dir, 'csv_result1.csv')
outpath2 = os.path.join(ref.tmp_dir, 'csv_result2.csv')
df1.to_csv(outpath1, index=False)
df2.to_csv(outpath2, index=False)
columns = ref.all_fields_except(['random'])
ref.assertCSVFilesCorrect(
[outpath1, outpath2],
['dataframe_result.csv', 'dataframe_result2.csv'],
check_data=columns)
def testExampleDataFrameGeneration(self):
"""
This test uses generate_dataframe() from dataframes.py to
generate a simple Pandas DataFrame.
The test checks the DataFrame is as expected, in terms of both
data content (the values) and metadata (the types, order, etc)
of the columns.
"""
df = generate_dataframe()
columns = self.all_fields_except(['random'])
self.assertDataFrameCorrect(df, 'dataframe_result.csv',
check_data=columns, check_types=columns)
def testExampleDataFrameGeneration(self):
"""
This test uses generate_dataframe() from dataframes.py to
generate a simple Pandas DataFrame.
The test checks the DataFrame is as expected, in terms of both
data content (the values) and metadata (the types, order, etc)
of the columns.
"""
df = generate_dataframe()
columns = self.all_fields_except(['random'])
self.assertDataFrameCorrect(df, 'dataframe_result.csv',
check_data=columns, check_types=columns)
def testExampleCSVGeneration(self):
"""
This test uses generate_dataframe() from dataframes.py to
generate a simple Pandas dataframe, and then saves it to a CSV file.
The test checks the generated CSV file is as expected, in terms of both
data content (the values) and metadata (the types, order, etc)
of the columns.
"""
df = generate_dataframe(nrows=10, precision=3)
outpath = os.path.join(self.tmp_dir, 'csv_result.csv')
columns = self.all_fields_except(['random'])
self.assertCSVFileCorrect(outpath, 'dataframe_result.csv',
check_data=columns, check_types=columns)
def testExampleCSVGeneration(self):
"""
This test uses generate_dataframe() from dataframes.py to
generate a simple Pandas dataframe, and then saves it to a CSV file.
The test checks the generated CSV file is as expected, in terms of both
data content (the values) and metadata (the types, order, etc)
of the columns.
"""
outpath = os.path.join(self.tmp_dir, 'csv_result.csv')
df = generate_dataframe()
df.to_csv(outpath, index=False)
columns = self.all_fields_except(['random'])
self.assertCSVFileCorrect(outpath, 'dataframe_result.csv',
check_data=columns, check_types=columns)
