import io
import os
import numpy as np
import pytest
from pandas.compat import PY2
from pandas.errors import EmptyDataError
import pandas.util._test_decorators as td
import pandas as pd
import pandas.util.testing as tm
# https://github.com/cython/cython/issues/1720
@pytest.mark.filterwarnings("ignore:can't resolve package:ImportWarning")
class TestSAS7BDAT(object):
@pytest.fixture(autouse=True)
def setup_method(self, datapath):
self.dirpath = datapath("io", "sas", "data")
self.data = []
self.test_ix = [list(range(1, 16)), [16]]
for j in 1, 2:
fname = os.path.join(
self.dirpath, "test_sas7bdat_{j}.csv".format(j=j))
df = pd.read_csv(fname)
epoch = pd.datetime(1960, 1, 1)
t1 = pd.to_timedelta(df["Column4"], unit='d')
df["Column4"] = epoch + t1
t2 = pd.to_timedelta(df["Column12"], unit='d')
df["Column12"] = epoch + t2
for k in range(df.shape[1]):
col = df.iloc[:, k]
if col.dtype == np.int64:
df.iloc[:, k] = df.iloc[:, k].astype(np.float64)
elif col.dtype == np.dtype('O'):
if PY2:
f = lambda x: (x.decode('utf-8') if
isinstance(x, str) else x)
df.iloc[:, k] = df.iloc[:, k].apply(f)
self.data.append(df)
def test_from_file(self):
for j in 0, 1:
df0 = self.data[j]
for k in self.test_ix[j]:
fname = os.path.join(
self.dirpath, "test{k}.sas7bdat".format(k=k))
df = pd.read_sas(fname, encoding='utf-8')
tm.assert_frame_equal(df, df0)
def test_from_buffer(self):
for j in 0, 1:
df0 = self.data[j]
for k in self.test_ix[j]:
fname = os.path.join(
self.dirpath, "test{k}.sas7bdat".format(k=k))
with open(fname, 'rb') as f:
byts = f.read()
buf = io.BytesIO(byts)
rdr = pd.read_sas(buf, format="sas7bdat",
iterator=True, encoding='utf-8')
df = rdr.read()
tm.assert_frame_equal(df, df0, check_exact=False)
rdr.close()
def test_from_iterator(self):
for j in 0, 1:
df0 = self.data[j]
for k in self.test_ix[j]:
fname = os.path.join(
self.dirpath, "test{k}.sas7bdat".format(k=k))
rdr = pd.read_sas(fname, iterator=True, encoding='utf-8')
df = rdr.read(2)
tm.assert_frame_equal(df, df0.iloc[0:2, :])
df = rdr.read(3)
tm.assert_frame_equal(df, df0.iloc[2:5, :])
rdr.close()
@td.skip_if_no('pathlib')
def test_path_pathlib(self):
from pathlib import Path
for j in 0, 1:
df0 = self.data[j]
for k in self.test_ix[j]:
fname = Path(os.path.join(
self.dirpath, "test{k}.sas7bdat".format(k=k)))
df = pd.read_sas(fname, encoding='utf-8')
tm.assert_frame_equal(df, df0)
@td.skip_if_no('py.path')
def test_path_localpath(self):
from py.path import local as LocalPath
for j in 0, 1:
df0 = self.data[j]
for k in self.test_ix[j]:
fname = LocalPath(os.path.join(
self.dirpath, "test{k}.sas7bdat".format(k=k)))
df = pd.read_sas(fname, encoding='utf-8')
tm.assert_frame_equal(df, df0)
def test_iterator_loop(self):
# github #13654
for j in 0, 1:
for k in self.test_ix[j]:
for chunksize in 3, 5, 10, 11:
fname = os.path.join(
self.dirpath, "test{k}.sas7bdat".format(k=k))
rdr = pd.read_sas(fname, chunksize=10, encoding='utf-8')
y = 0
for x in rdr:
y += x.shape[0]
assert y == rdr.row_count
rdr.close()
def test_iterator_read_too_much(self):
# github #14734
k = self.test_ix[0][0]
fname = os.path.join(self.dirpath, "test{k}.sas7bdat".format(k=k))
rdr = pd.read_sas(fname, format="sas7bdat",
iterator=True, encoding='utf-8')
d1 = rdr.read(rdr.row_count + 20)
rdr.close()
rdr = pd.read_sas(fname, iterator=True, encoding="utf-8")
d2 = rdr.read(rdr.row_count + 20)
tm.assert_frame_equal(d1, d2)
rdr.close()
def test_encoding_options(datapath):
fname = datapath("io", "sas", "data", "test1.sas7bdat")
df1 = pd.read_sas(fname)
df2 = pd.read_sas(fname, encoding='utf-8')
for col in df1.columns:
try:
df1[col] = df1[col].str.decode('utf-8')
except AttributeError:
pass
tm.assert_frame_equal(df1, df2)
from pandas.io.sas.sas7bdat import SAS7BDATReader
rdr = SAS7BDATReader(fname, convert_header_text=False)
df3 = rdr.read()
rdr.close()
for x, y in zip(df1.columns, df3.columns):
assert(x == y.decode())
def test_productsales(datapath):
fname = datapath("io", "sas", "data", "productsales.sas7bdat")
df = pd.read_sas(fname, encoding='utf-8')
fname = datapath("io", "sas", "data", "productsales.csv")
df0 = pd.read_csv(fname, parse_dates=['MONTH'])
vn = ["ACTUAL", "PREDICT", "QUARTER", "YEAR"]
df0[vn] = df0[vn].astype(np.float64)
tm.assert_frame_equal(df, df0)
def test_12659(datapath):
fname = datapath("io", "sas", "data", "test_12659.sas7bdat")
df = pd.read_sas(fname)
fname = datapath("io", "sas", "data", "test_12659.csv")
df0 = pd.read_csv(fname)
df0 = df0.astype(np.float64)
tm.assert_frame_equal(df, df0)
def test_airline(datapath):
fname = datapath("io", "sas", "data", "airline.sas7bdat")
df = pd.read_sas(fname)
fname = datapath("io", "sas", "data", "airline.csv")
df0 = pd.read_csv(fname)
df0 = df0.astype(np.float64)
tm.assert_frame_equal(df, df0, check_exact=False)
def test_date_time(datapath):
# Support of different SAS date/datetime formats (PR #15871)
fname = datapath("io", "sas", "data", "datetime.sas7bdat")
df = pd.read_sas(fname)
fname = datapath("io", "sas", "data", "datetime.csv")
df0 = pd.read_csv(fname, parse_dates=['Date1', 'Date2', 'DateTime',
'DateTimeHi', 'Taiw'])
# GH 19732: Timestamps imported from sas will incur floating point errors
df.iloc[:, 3] = df.iloc[:, 3].dt.round('us')
tm.assert_frame_equal(df, df0)
def test_compact_numerical_values(datapath):
# Regression test for #21616
fname = datapath("io", "sas", "data", "cars.sas7bdat")
df = pd.read_sas(fname, encoding='latin-1')
# The two columns CYL and WGT in cars.sas7bdat have column
# width < 8 and only contain integral values.
# Test that pandas doesn't corrupt the numbers by adding
# decimals.
result = df['WGT']
expected = df['WGT'].round()
tm.assert_series_equal(result, expected, check_exact=True)
result = df['CYL']
expected = df['CYL'].round()
tm.assert_series_equal(result, expected, check_exact=True)
def test_many_columns(datapath):
# Test for looking for column information in more places (PR #22628)
fname = datapath("io", "sas", "data", "many_columns.sas7bdat")
df = pd.read_sas(fname, encoding='latin-1')
fname = datapath("io", "sas", "data", "many_columns.csv")
df0 = pd.read_csv(fname, encoding='latin-1')
tm.assert_frame_equal(df, df0)
def test_inconsistent_number_of_rows(datapath):
# Regression test for issue #16615. (PR #22628)
fname = datapath("io", "sas", "data", "load_log.sas7bdat")
df = pd.read_sas(fname, encoding='latin-1')
assert len(df) == 2097
def test_zero_variables(datapath):
# Check if the SAS file has zero variables (PR #18184)
fname = datapath("io", "sas", "data", "zero_variables.sas7bdat")
with pytest.raises(EmptyDataError):
pd.read_sas(fname)