123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167 |
- import numpy as np
- import pytest
- import pandas as pd
- import pandas._testing as tm
- from pandas.io.sas.sasreader import read_sas
- # CSV versions of test xpt files were obtained using the R foreign library
- # Numbers in a SAS xport file are always float64, so need to convert
- # before making comparisons.
- def numeric_as_float(data):
- for v in data.columns:
- if data[v].dtype is np.dtype("int64"):
- data[v] = data[v].astype(np.float64)
- class TestXport:
- @pytest.fixture
- def file01(self, datapath):
- return datapath("io", "sas", "data", "DEMO_G.xpt")
- @pytest.fixture
- def file02(self, datapath):
- return datapath("io", "sas", "data", "SSHSV1_A.xpt")
- @pytest.fixture
- def file03(self, datapath):
- return datapath("io", "sas", "data", "DRXFCD_G.xpt")
- @pytest.fixture
- def file04(self, datapath):
- return datapath("io", "sas", "data", "paxraw_d_short.xpt")
- @pytest.fixture
- def file05(self, datapath):
- return datapath("io", "sas", "data", "DEMO_PUF.cpt")
- @pytest.mark.slow
- def test1_basic(self, file01):
- # Tests with DEMO_G.xpt (all numeric file)
- # Compare to this
- data_csv = pd.read_csv(file01.replace(".xpt", ".csv"))
- numeric_as_float(data_csv)
- # Read full file
- data = read_sas(file01, format="xport")
- tm.assert_frame_equal(data, data_csv)
- num_rows = data.shape[0]
- # Test reading beyond end of file
- with read_sas(file01, format="xport", iterator=True) as reader:
- data = reader.read(num_rows + 100)
- assert data.shape[0] == num_rows
- # Test incremental read with `read` method.
- with read_sas(file01, format="xport", iterator=True) as reader:
- data = reader.read(10)
- tm.assert_frame_equal(data, data_csv.iloc[0:10, :])
- # Test incremental read with `get_chunk` method.
- with read_sas(file01, format="xport", chunksize=10) as reader:
- data = reader.get_chunk()
- tm.assert_frame_equal(data, data_csv.iloc[0:10, :])
- # Test read in loop
- m = 0
- with read_sas(file01, format="xport", chunksize=100) as reader:
- for x in reader:
- m += x.shape[0]
- assert m == num_rows
- # Read full file with `read_sas` method
- data = read_sas(file01)
- tm.assert_frame_equal(data, data_csv)
- def test1_index(self, file01):
- # Tests with DEMO_G.xpt using index (all numeric file)
- # Compare to this
- data_csv = pd.read_csv(file01.replace(".xpt", ".csv"))
- data_csv = data_csv.set_index("SEQN")
- numeric_as_float(data_csv)
- # Read full file
- data = read_sas(file01, index="SEQN", format="xport")
- tm.assert_frame_equal(data, data_csv, check_index_type=False)
- # Test incremental read with `read` method.
- with read_sas(file01, index="SEQN", format="xport", iterator=True) as reader:
- data = reader.read(10)
- tm.assert_frame_equal(data, data_csv.iloc[0:10, :], check_index_type=False)
- # Test incremental read with `get_chunk` method.
- with read_sas(file01, index="SEQN", format="xport", chunksize=10) as reader:
- data = reader.get_chunk()
- tm.assert_frame_equal(data, data_csv.iloc[0:10, :], check_index_type=False)
- def test1_incremental(self, file01):
- # Test with DEMO_G.xpt, reading full file incrementally
- data_csv = pd.read_csv(file01.replace(".xpt", ".csv"))
- data_csv = data_csv.set_index("SEQN")
- numeric_as_float(data_csv)
- with read_sas(file01, index="SEQN", chunksize=1000) as reader:
- all_data = list(reader)
- data = pd.concat(all_data, axis=0)
- tm.assert_frame_equal(data, data_csv, check_index_type=False)
- def test2(self, file02):
- # Test with SSHSV1_A.xpt
- # Compare to this
- data_csv = pd.read_csv(file02.replace(".xpt", ".csv"))
- numeric_as_float(data_csv)
- data = read_sas(file02)
- tm.assert_frame_equal(data, data_csv)
- def test2_binary(self, file02):
- # Test with SSHSV1_A.xpt, read as a binary file
- # Compare to this
- data_csv = pd.read_csv(file02.replace(".xpt", ".csv"))
- numeric_as_float(data_csv)
- with open(file02, "rb") as fd:
- # GH#35693 ensure that if we pass an open file, we
- # dont incorrectly close it in read_sas
- data = read_sas(fd, format="xport")
- tm.assert_frame_equal(data, data_csv)
- def test_multiple_types(self, file03):
- # Test with DRXFCD_G.xpt (contains text and numeric variables)
- # Compare to this
- data_csv = pd.read_csv(file03.replace(".xpt", ".csv"))
- data = read_sas(file03, encoding="utf-8")
- tm.assert_frame_equal(data, data_csv)
- def test_truncated_float_support(self, file04):
- # Test with paxraw_d_short.xpt, a shortened version of:
- # http://wwwn.cdc.gov/Nchs/Nhanes/2005-2006/PAXRAW_D.ZIP
- # This file has truncated floats (5 bytes in this case).
- # GH 11713
- data_csv = pd.read_csv(file04.replace(".xpt", ".csv"))
- data = read_sas(file04, format="xport")
- tm.assert_frame_equal(data.astype("int64"), data_csv)
- def test_cport_header_found_raises(self, file05):
- # Test with DEMO_PUF.cpt, the beginning of puf2019_1_fall.xpt
- # from https://www.cms.gov/files/zip/puf2019.zip
- # (despite the extension, it's a cpt file)
- msg = "Header record indicates a CPORT file, which is not readable."
- with pytest.raises(ValueError, match=msg):
- read_sas(file05, format="xport")
|