def test_across_dataframe_single_column_with_lambda():
convert_date = lambda x: x.strftime('%b %-d, %Y') if not x is pd.NaT else x
df = generate_periods(delta_range=(1, 10), rows=20)
df = make_null_dates(df, null_values_percent=.2)
exp = df.copy(deep=True)
exp.effective = exp.effective.apply(convert_date)
got = across(df, columns='effective', function=convert_date)
assert exp.equals(got) == True
def test_across_raise_function_parm_none_ValueError():
convert_date = lambda x: pd.to_datetime(
x, dayfirst=True, format='%d%m%Y', errors='coerce')
test = [30112019, 2942019, 3022019, 2822019, 2019430]
got = pd.DataFrame(test, columns=['dates'])
# Convert expected values to datetime format
exp = ['30/11/2019', '29/4/2019', pd.NaT, '28/2/2019', pd.NaT]
exp = pd.DataFrame(exp, columns=['dates'])
exp.dates = exp.dates.astype('datetime64[ns]')
with pytest.raises(ValueError):
got = across(got, columns='dates', function=None)
def test_across_dataframe_multiple_columns_raise_invalid_column():
convert_date = lambda x: x.strftime('%b %-d, %Y') if not x is pd.NaT else x
df = generate_periods(delta_range=(1, 10), rows=20)
df = make_null_dates(df, null_values_percent=.2)
exp = df.copy(deep=True)
exp.effective = exp.effective.apply(convert_date)
exp.expired = exp.expired.apply(convert_date)
with pytest.raises(ValueError):
got = across(df,
columns=['effective', 'invalid'],
function=convert_date)
def test_across_str_date_single_col_lambda():
''' '''
convert_date = lambda x: pd.to_datetime(
x, dayfirst=True, format='%d%m%Y', errors='coerce')
test = [30112019, 2942019, 3022019, 2822019, 2019430]
got = pd.DataFrame(test, columns=['dates'])
# Convert expected values to datetime format
exp = ['30/11/2019', '29/4/2019', pd.NaT, '28/2/2019', pd.NaT]
exp = pd.DataFrame(exp, columns=['dates'])
exp.dates = exp.dates.astype('datetime64[ns]')
got = across(got, 'dates', convert_date)
assert exp.equals(got) == True
def test_across_str_date_single_col_pd_to_datetime():
''' '''
test = ['30/11/2019', '29/4/2019', '30/2/2019', '28/2/2019', '2019/4/30']
got = pd.DataFrame(test, columns=['dates'])
# Convert expected values to datetime format
exp = ['30/11/2019', '29/4/2019', pd.NaT, '28/2/2019', pd.NaT]
exp = pd.DataFrame(exp, columns=['dates'])
exp.dates = exp.dates.astype('datetime64[ns]')
got = across(got,
'dates',
pd.to_datetime,
format='%d/%m/%Y',
errors='coerce')
assert exp.equals(got) == True
