def test_keep_latest_csv():
# test latest
df = file_to_dataframe(data_dir / "instr1_primaryall.csv")
result = df.mac.group_by_keep_one(group_by_col="pidn",
date_col_name="dcdate",
keep="latest")
expected_result = file_to_dataframe(data_dir / "instr1_primarylatest.csv")
assert_dfs_equal(result,
expected_result,
cols_ignore=cols_ignore,
output_dir=output_dir)
def test_keepone(cli_keepone_big):
G = ExecutableGraph()
prim_filepath = data_dir / "instr1_primaryall.csv"
primary = LavaDataset.from_file(prim_filepath)
G.add_node(
primary,
operation=partial(
group_by_keep_one,
group_by_col=primary.id2_col_name,
date_col_name=primary.date_col_name,
keep="earliest",
drop_duplicates=False,
),
)
G.execute()
nodes_with_operations = G.get_all_node_data("operation")
result = nodes_with_operations[0]["operation_result"]
expected_result = file_to_dataframe(cli_keepone_big)
assert_dfs_equal(result,
expected_result,
cols_ignore_pat=cols_ignore_pat,
output_dir=output_dir)
def test_keep_earliest_csv():
# test earliest
df = file_to_dataframe(data_dir / "instr1_primaryall.csv")
result = df.mac.group_by_keep_one(group_by_col="pidn",
date_col_name="dcdate",
keep="earliest")
assert get_option("column.system.duplicates") in result.columns
expected_result = file_to_dataframe(data_dir /
"instr1_primaryearliest.csv")
assert_dfs_equal(result,
expected_result,
cols_ignore=cols_ignore,
output_dir=output_dir)
def test_dupes():
primary = file_to_dataframe(current_dir / "primary.xlsx")
secondary = file_to_dataframe(current_dir / "secondary.xlsx")
dupes_result = primary.mac.date_proximity(
secondary,
id_on='pidn',
date_on='dcdate',
get='closest',
when='earlier_or_later',
days=90,
left_link_id='instrid',
merge='full',
duplicates_indicator=True
)
# dupes_result.to_excel(current_dir / "dupes_result.xlsx", index=False)
dupes_expected_result = file_to_dataframe(current_dir / "dupes_expected_result.xlsx")
assert_dfs_equal(dupes_result, dupes_expected_result, cols_ignore=cols_ignore, output_dir=output_dir)
def test_merge_partial():
# partial merge
merge_partial_result = primary.mac.date_proximity(
secondary,
id_on='pidn',
date_on='dcdate',
get='closest',
when='earlier_or_later',
days=90,
left_link_id='instrid',
merge='partial'
)
# merge_partial_result.to_excel(current_dir / "merge_partial_result.xlsx", index=False)
merge_partial_expected_result = file_to_dataframe(current_dir / "merge_partial_expected_result.xlsx")
assert_dfs_equal(merge_partial_result,
merge_partial_expected_result,
cols_ignore=cols_ignore,
output_dir=output_dir)
# test that results are same when using equivalent id and date params
test_id_on_params = primary.mac.date_proximity(
secondary,
id_left_on='pidn',
id_right_on='pidn',
date_on='dcdate',
get='closest',
when='earlier_or_later',
days=90,
left_link_id='instrid',
merge='partial'
)
test_date_on_params = primary.mac.date_proximity(
secondary,
id_on='pidn',
date_left_on='dcdate',
date_right_on='dcdate',
get='closest',
when='earlier_or_later',
days=90,
left_link_id='instrid',
merge='partial'
)
# test using id_left_on and id_right_on params
assert merge_partial_result.equals(test_id_on_params)
# test using date_left_on and date_right_on params
assert merge_partial_result.equals(test_date_on_params)
def test_filter_by_id():
df = file_to_dataframe(current_dir / "basic.xlsx")
# ids list with invalid integer should raise ValueError
ids = [1, 2, "hello"]
with pytest.raises(ValueError):
df.mac.filter_by_id("pidn", ids)
# number of rows of filtered result should match number of ids
ids = [2, 3, "4"]
result = df.mac.filter_by_id("pidn", ids)
# result.to_excel(Path("tests/pandas/operators/filter_by_id/result.xlsx"), index=False)
assert result.mac.row_count() == 4
def test_merge_full():
# full merge
merge_full_result = primary.mac.date_proximity(
secondary,
id_on='pidn',
date_on='dcdate',
get='closest',
when='earlier_or_later',
days=90,
left_link_id='instrid',
merge='full'
)
# merge_full_result.to_excel(current_dir / "merge_full_result.xlsx", index=False)
merge_full_expected_result = file_to_dataframe(current_dir / "merge_full_expected_result.xlsx")
assert_dfs_equal(merge_full_result, merge_full_expected_result, cols_ignore=cols_ignore, output_dir=output_dir)
def test_left_link_id_blank_merge_partial():
# partial merge
result = primary.mac.date_proximity(secondary,
id_on='pidn',
date_on='dcdate',
get='closest',
when='earlier_or_later',
days=90,
merge='partial')
# result.to_excel(current_dir / "left_link_id_blank_merge_partial_result.xlsx", index=False)
expected_result = file_to_dataframe(
current_dir / "left_link_id_blank_merge_partial_expected_result.xlsx")
assert_dfs_equal(result,
expected_result,
cols_ignore=cols_ignore,
output_dir=output_dir)
def test_secondary_instr1():
secondary_instr1 = file_to_dataframe(data_dir / "instr1_all.csv")
# test closest; earlier_or_later; 90 days
instr1_result = primary.mac.date_proximity(
secondary_instr1,
id_on='pidn',
date_on='dcdate',
get='closest',
when='earlier_or_later',
days=90,
left_link_id='instrid',
duplicates_indicator=True
)
# instr1_result.to_excel(current_dir / "instr1_result.xlsx", index=False)
instr1_expected_result = dfs_dict['INSTR1_linked']
assert_dfs_equal(instr1_result,
instr1_expected_result,
cols_ignore=cols_ignore,
cols_ignore_pat=cols_ignore_pat)
from pathlib import Path
from macpie.pandas import file_to_dataframe
from macpie.testing import assert_dfs_equal
current_dir = Path(__file__).parent.absolute()
# output_dir = current_dir
output_dir = None
primary = file_to_dataframe(current_dir / "primary.xlsx")
secondary = file_to_dataframe(current_dir / "secondary.xlsx")
cols_ignore = []
def test_merge_partial():
# partial merge
merge_partial_result = primary.mac.date_proximity(
secondary,
id_on='pidn',
date_on='dcdate',
get='closest',
when='earlier_or_later',
days=90,
left_link_id='instrid',
merge='partial'
)
def test_instr1():
dfs_dict = pd.read_excel(data_dir / "instr1.xlsx",
sheet_name=[
'primary', 'closest_earlier_or_later_90',
'closest_later_90', 'closest_earlier_90',
'all_earlier_or_later_90', 'all_later_90',
'all_earlier_90'
])
primary = dfs_dict['primary']
secondary = file_to_dataframe(data_dir / "instr1_all.csv")
# test closest; earlier_or_later; 90 days
closest_earlier_or_later_90_result = primary.mac.date_proximity(
secondary,
id_on='pidn',
date_on='dcdate',
get='closest',
when='earlier_or_later',
days=90)
# closest_earlier_or_later_90_result.to_excel(current_dir / "closest_earlier_or_later_90_result.xlsx", index=False)
closest_earlier_or_later_90_expected_result = dfs_dict[
'closest_earlier_or_later_90']
assert_dfs_equal(closest_earlier_or_later_90_result,
closest_earlier_or_later_90_expected_result,
cols_ignore=cols_ignore,
cols_ignore_pat=cols_ignore_pat,
output_dir=output_dir)
# test closest; later; 90 days
closest_later_90_result = primary.mac.date_proximity(secondary,
id_on='pidn',
date_on='dcdate',
get='closest',
when='later',
days=90)
# closest_later_90_result.to_excel(current_dir / "closest_later_90_result.xlsx", index=False)
closest_later_90_expected_result = dfs_dict['closest_later_90']
assert_dfs_equal(closest_later_90_result,
closest_later_90_expected_result,
cols_ignore=cols_ignore,
cols_ignore_pat=cols_ignore_pat,
output_dir=output_dir)
# test closest; earlier; 90 days
closest_earlier_90_result = primary.mac.date_proximity(secondary,
id_on='pidn',
date_on='dcdate',
get='closest',
when='earlier',
days=90)
# closest_earlier_90_result.to_excel(current_dir / "closest_earlier_90_result.xlsx", index=False)
closest_earlier_90_expected_result = dfs_dict['closest_earlier_90']
assert_dfs_equal(closest_earlier_90_result,
closest_earlier_90_expected_result,
cols_ignore=cols_ignore,
cols_ignore_pat=cols_ignore_pat,
output_dir=output_dir)
# test all; earlier_or_later; 90 days
all_earlier_or_later_90_result = primary.mac.date_proximity(
secondary,
id_on='pidn',
date_on='dcdate',
get='all',
when='earlier_or_later',
days=90)
# all_earlier_or_later_90_result.to_excel(current_dir / "all_earlier_or_later_90_result.xlsx", index=False)
all_earlier_or_later_90_expected_result = dfs_dict[
'all_earlier_or_later_90']
assert_dfs_equal(all_earlier_or_later_90_result,
all_earlier_or_later_90_expected_result,
cols_ignore=cols_ignore,
cols_ignore_pat=cols_ignore_pat,
output_dir=output_dir)
# test all; later; 90 days
all_later_90_result = primary.mac.date_proximity(secondary,
id_on='pidn',
date_on='dcdate',
get='all',
when='later',
days=90)
# all_later_90_result.to_excel(current_dir / "all_later_90_result.xlsx", index=False)
all_later_90_expected_result = dfs_dict['all_later_90']
assert_dfs_equal(all_later_90_result,
all_later_90_expected_result,
cols_ignore=cols_ignore,
cols_ignore_pat=cols_ignore_pat,
output_dir=output_dir)
# test all; earlier; 90 days
all_earlier_90_result = primary.mac.date_proximity(secondary,
id_on='pidn',
date_on='dcdate',
get='all',
when='earlier',
days=90)
# all_earlier_90_result.to_excel(current_dir / "all_earlier_90_result.xlsx", index=False)
all_earlier_90_expected_result = dfs_dict['all_earlier_90']
assert_dfs_equal(all_earlier_90_result,
all_earlier_90_expected_result,
cols_ignore=cols_ignore,
cols_ignore_pat=cols_ignore_pat,
output_dir=output_dir)
from pathlib import Path
import pandas as pd
from macpie.pandas import file_to_dataframe
from macpie.testing import assert_dfs_equal
current_dir = Path("tests/pandas/operators/merge/basic/").resolve()
# output_dir = current_dir
output_dir = None
primary = file_to_dataframe(current_dir / "small.xlsx")
dfs_dict = pd.read_excel(
current_dir / "small.xlsx",
sheet_name=['small_anchor', 'instr2_all_linked', 'instr3_all_linked'])
small_anchor = dfs_dict['small_anchor']
instr2_all_linked = dfs_dict['instr2_all_linked']
instr3_all_linked = dfs_dict['instr3_all_linked']
def test_add_suffixes_false():
result = small_anchor.mac.merge(
instr2_all_linked,
left_on=['pidn', 'dcdate', 'instrid'],
right_on=['pidn_x', 'dcdate_x', 'instrid_x'],
merge_suffixes=('_a', '_b'),
add_suffixes=False).mac.merge(
instr3_all_linked,