def test_encode_chunk_with_floats():
"""Test that floats in a dataframe are encoded with at most 17 significant
figures.
See: https://github.com/pydata/pandas-gbq/issues/192 and
https://github.com/pydata/pandas-gbq/issues/326
"""
input_csv = textwrap.dedent("""01/01/17 23:00,0.14285714285714285,4
01/02/17 22:00,1.05148,3
01/03/17 21:00,1.05153,2
01/04/17 20:00,3.141592653589793,1
01/05/17 19:00,2.0988936657440586e+43,0
""")
input_df = pandas.read_csv(StringIO(input_csv),
header=None,
float_precision="round_trip")
csv_buffer = load.encode_chunk(input_df)
round_trip = pandas.read_csv(csv_buffer,
header=None,
float_precision="round_trip")
pandas.testing.assert_frame_equal(
round_trip,
input_df,
check_exact=True,
)
def test_encode_chunk_with_newlines():
"""See: https://github.com/pydata/pandas-gbq/issues/180"""
df = pandas.DataFrame({"s": ["abcd", "ef\ngh", "ij\r\nkl"]})
csv_buffer = load.encode_chunk(df)
csv_bytes = csv_buffer.read()
csv_string = csv_bytes.decode("utf-8")
assert "abcd" in csv_string
assert '"ef\ngh"' in csv_string
assert '"ij\r\nkl"' in csv_string
def test_encode_chunk_with_floats():
"""Test that floats in a dataframe are encoded with at most 15 significant
figures.
See: https://github.com/pydata/pandas-gbq/issues/192
"""
input_csv = StringIO(u"01/01/17 23:00,1.05148,1.05153,1.05148,1.05153,4")
df = pandas.read_csv(input_csv, header=None)
csv_buffer = load.encode_chunk(df)
csv_bytes = csv_buffer.read()
csv_string = csv_bytes.decode("utf-8")
assert "1.05153" in csv_string
def test_encode_chunk_with_unicode():
"""Test that a dataframe containing unicode can be encoded as a file.
See: https://github.com/pydata/pandas-gbq/issues/106
"""
df = pandas.DataFrame(numpy.random.randn(6, 4),
index=range(6),
columns=list("ABCD"))
df["s"] = "信用卡"
csv_buffer = load.encode_chunk(df)
csv_bytes = csv_buffer.read()
csv_string = csv_bytes.decode("utf-8")
assert "信用卡" in csv_string