import os
import numpy as np
import pytest
import pandas as pd
import pandas.util.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(object):
@pytest.fixture(autouse=True)
def setup_method(self, datapath):
self.dirpath = datapath("io", "sas", "data")
self.file01 = os.path.join(self.dirpath, "DEMO_G.xpt")
self.file02 = os.path.join(self.dirpath, "SSHSV1_A.xpt")
self.file03 = os.path.join(self.dirpath, "DRXFCD_G.xpt")
self.file04 = os.path.join(self.dirpath, "paxraw_d_short.xpt")
def test1_basic(self):
# Tests with DEMO_G.xpt (all numeric file)
# Compare to this
data_csv = pd.read_csv(self.file01.replace(".xpt", ".csv"))
numeric_as_float(data_csv)
# Read full file
data = read_sas(self.file01, format="xport")
tm.assert_frame_equal(data, data_csv)
num_rows = data.shape[0]
# Test reading beyond end of file
reader = read_sas(self.file01, format="xport", iterator=True)
data = reader.read(num_rows + 100)
assert data.shape[0] == num_rows
reader.close()
# Test incremental read with `read` method.
reader = read_sas(self.file01, format="xport", iterator=True)
data = reader.read(10)
reader.close()
tm.assert_frame_equal(data, data_csv.iloc[0:10, :])
# Test incremental read with `get_chunk` method.
reader = read_sas(self.file01, format="xport", chunksize=10)
data = reader.get_chunk()
reader.close()
tm.assert_frame_equal(data, data_csv.iloc[0:10, :])
# Test read in loop
m = 0
reader = read_sas(self.file01, format="xport", chunksize=100)
for x in reader:
m += x.shape[0]
reader.close()
assert m == num_rows
# Read full file with `read_sas` method
data = read_sas(self.file01)
tm.assert_frame_equal(data, data_csv)
def test1_index(self):
# Tests with DEMO_G.xpt using index (all numeric file)
# Compare to this
data_csv = pd.read_csv(self.file01.replace(".xpt", ".csv"))
data_csv = data_csv.set_index("SEQN")
numeric_as_float(data_csv)
# Read full file
data = read_sas(self.file01, index="SEQN", format="xport")
tm.assert_frame_equal(data, data_csv, check_index_type=False)
# Test incremental read with `read` method.
reader = read_sas(self.file01, index="SEQN", format="xport",
iterator=True)
data = reader.read(10)
reader.close()
tm.assert_frame_equal(data, data_csv.iloc[0:10, :],
check_index_type=False)
# Test incremental read with `get_chunk` method.
reader = read_sas(self.file01, index="SEQN", format="xport",
chunksize=10)
data = reader.get_chunk()
reader.close()
tm.assert_frame_equal(data, data_csv.iloc[0:10, :],
check_index_type=False)
def test1_incremental(self):
# Test with DEMO_G.xpt, reading full file incrementally
data_csv = pd.read_csv(self.file01.replace(".xpt", ".csv"))
data_csv = data_csv.set_index("SEQN")
numeric_as_float(data_csv)
reader = read_sas(self.file01, index="SEQN", chunksize=1000)
all_data = [x for x in reader]
data = pd.concat(all_data, axis=0)
tm.assert_frame_equal(data, data_csv, check_index_type=False)
def test2(self):
# Test with SSHSV1_A.xpt
# Compare to this
data_csv = pd.read_csv(self.file02.replace(".xpt", ".csv"))
numeric_as_float(data_csv)
data = read_sas(self.file02)
tm.assert_frame_equal(data, data_csv)
def test_multiple_types(self):
# Test with DRXFCD_G.xpt (contains text and numeric variables)
# Compare to this
data_csv = pd.read_csv(self.file03.replace(".xpt", ".csv"))
data = read_sas(self.file03, encoding="utf-8")
tm.assert_frame_equal(data, data_csv)
def test_truncated_float_support(self):
# 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(self.file04.replace(".xpt", ".csv"))
data = read_sas(self.file04, format="xport")
tm.assert_frame_equal(data.astype('int64'), data_csv)