def test_dataframe_to_string():
with set_options(formatting={'nrows': 5, 'ncols': 8}):
# Test basic
df = DataFrame([('a', [1, 2, 3, 4, 5, 6]),
('b', [11, 12, 13, 14, 15, 16])])
string = str(df)
print(string)
assert string.splitlines()[-1] == '[1 more rows]'
# Test skipped columns
df = DataFrame([('a', [1, 2, 3, 4, 5, 6]),
('b', [11, 12, 13, 14, 15, 16]),
('c', [11, 12, 13, 14, 15, 16]),
('d', [11, 12, 13, 14, 15, 16])])
string = df.to_string(ncols=3)
print(string)
assert string.splitlines()[-2] == '[1 more rows]'
assert string.splitlines()[-1] == '[1 more columns]'
# Test masked
df = DataFrame([('a', [1, 2, 3, 4, 5, 6]),
('b', [11, 12, 13, 14, 15, 16])])
data = np.arange(6)
mask = np.zeros(1, dtype=np.uint8)
mask[0] = 0b00101101
masked = Series.from_masked_array(data, mask)
assert masked.null_count == 2
df['c'] = masked
# check data
values = list(masked)
validids = [0, 2, 3, 5]
densearray = masked.to_array()
np.testing.assert_equal(data[validids], densearray)
# valid position is corret
for i in validids:
assert data[i] == values[i]
# null position is correct
for i in range(len(values)):
if i not in validids:
assert values[i] is None
got = df.to_string(nrows=None)
print(got)
expect = '''
a b c
0 1 11 0
1 2 12
2 3 13 2
3 4 14 3
4 5 15
5 6 16 5
'''
# values should match despite whitespace difference
assert got.split() == expect.split()
def test_dataframe_to_string_wide():
# Test basic
df = DataFrame()
for i in range(100):
df['a{}'.format(i)] = list(range(3))
got = df.to_string(ncols=8)
print(got)
expect = '''
a0 a1 a2 a3 a4 a5 a6 ... a99
0 0 0 0 0 0 0 0 ... 0
1 1 1 1 1 1 1 1 ... 1
2 2 2 2 2 2 2 2 ... 2
[92 more columns]
'''
# values should match despite whitespace difference
assert got.split() == expect.split()
