def test_convert_null(self):
result = render(
pd.DataFrame({"A": [1, np.nan]}),
{"colnames": ["A"]},
input_columns={"A": RenderColumn("A", "number", "{:,d}")},
)
assert_frame_equal(result, pd.DataFrame({"A": ["1", np.nan]}))
def test_convert_str(self):
result = render(
pd.DataFrame({"A": ["a"]}),
{"colnames": ["A"]},
input_columns={"A": RenderColumn("A", "text", None)},
)
assert_frame_equal(result, pd.DataFrame({"A": ["a"]}))
def test_convert_numbers_all_null(self):
result = render(
pd.DataFrame({"A": [np.nan, np.nan]}, dtype=np.float64),
{"colnames": ["A"]},
input_columns={"A": RenderColumn("A", "number", "{:d}")},
)
assert_frame_equal(result,
pd.DataFrame({"A": [np.nan, np.nan]}, dtype=object))
def test_NOP(self):
# should NOP when first applied
result = render(
pd.DataFrame({"A": [0.006]}),
{"colnames": []},
input_columns={"A": RenderColumn("A", "number", "{:.2f}")},
)
assert_frame_equal(result, pd.DataFrame({"A": [0.006]}))
def test_convert_datetime(self):
result = render(
pd.DataFrame({
"A":
[np.datetime64("2018-01-01"),
np.datetime64("2019-02-13")]
}),
{"colnames": ["A"]},
input_columns={"A": RenderColumn("A", "datetime", None)},
)
assert_frame_equal(result,
pd.DataFrame({"A": ["2018-01-01", "2019-02-13"]}))
def test_convert_float(self):
result = render(
pd.DataFrame({
"A": [1.111],
"B": [2.6]
}),
{"colnames": ["A", "B"]},
input_columns={
"A": RenderColumn("A", "number", "{:.2f}"),
"B": RenderColumn("B", "number", "{:d}"),
},
)
assert_frame_equal(result, pd.DataFrame({"A": ["1.11"], "B": ["2"]}))