Closed
Description
When generating a multi-indexed dataframe, if the default index is renamed and the dataframe is longer than the max_rows display option. This cropped up after updating from 0.17 to 0.18.
Code Sample, a copy-pastable example if possible
>>> df = pd.DataFrame({'Vals':range(100)})
>>> df = pd.concat([df, ], keys=['Sweep'], names=['Sweep', 'Index'])
>>> df
Traceback (most recent call last):
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\indexes\range.py", line 124, in _simple_new
return RangeIndex(start, stop, step, name=name, **kwargs)
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\indexes\range.py", line 73, in __new__
start = _ensure_int(start, 'start')
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\indexes\range.py", line 59, in _ensure_int
new_value = int(value)
TypeError: only length-1 arrays can be converted to Python scalars
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\core\base.py", line 63, in __repr__
return str(self)
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\core\base.py", line 42, in __str__
return self.__unicode__()
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\core\frame.py", line 534, in __unicode__
line_width=width, show_dimensions=show_dimensions)
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\core\frame.py", line 1486, in to_string
show_dimensions=show_dimensions)
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\core\format.py", line 378, in __init__
self._chk_truncate()
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\core\format.py", line 450, in _chk_truncate
frame.iloc[-row_num:, :]))
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\tools\merge.py", line 834, in concat
copy=copy)
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\tools\merge.py", line 972, in __init__
self.new_axes = self._get_new_axes()
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\tools\merge.py", line 1059, in _get_new_axes
new_axes[self.axis] = self._get_concat_axis()
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\tools\merge.py", line 1111, in _get_concat_axis
concat_axis = _concat_indexes(indexes)
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\tools\merge.py", line 1129, in _concat_indexes
return indexes[0].append(indexes[1:])
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\indexes\multi.py", line 1029, in append
label = self.get_level_values(i)
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\indexes\multi.py", line 666, in get_level_values
tz=getattr(unique, 'tz', None))
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\indexes\range.py", line 126, in _simple_new
return Index(start, stop, step, name=name, **kwargs)
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\indexes\base.py", line 214, in __new__
return Int64Index(data, copy=copy, dtype=dtype, name=name)
File "C:\Users\User\Anaconda3\lib\site-packages\pandas\indexes\numeric.py", line 107, in __new__
not issubclass(np.dtype(dtype).type, np.integer)):
TypeError: data type "Index" not understood
Expected Output
The expected outcome is that the dataframe should print out without producing a traceback, as occurs when the length is less than that set by max_rows. I.e.
>>> df = pd.DataFrame({'Vals':range(10)})
>>> df = pd.concat([df, ], keys=['Sweep'], names=['Sweep', 'Index'])
>>> df
Vals
Sweep Index
Sweep 0 0
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
9 9
The issue only seems to be with changing the default index name, as you can change the other index name without issue:
>>> df = pd.DataFrame({'Vals':range(100)})
>>> df = pd.concat([df, ], keys=['Sweep'], names=['Sweep',])
>>> df
Vals
Sweep
Sweep 0 0
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
9 9
10 10
11 11
12 12
13 13
14 14
15 15
16 16
17 17
18 18
19 19
20 20
21 21
22 22
23 23
24 24
25 25
26 26
27 27
28 28
29 29
... ...
70 70
71 71
72 72
73 73
74 74
75 75
76 76
77 77
78 78
79 79
80 80
81 81
82 82
83 83
84 84
85 85
86 86
87 87
88 88
89 89
90 90
91 91
92 92
93 93
94 94
95 95
96 96
97 97
98 98
99 99
[100 rows x 1 columns]
output of pd.show_versions()
>>> pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
pandas: 0.18.0
nose: 1.3.7
pip: 8.1.0
setuptools: 20.2.2
Cython: 0.23.4
numpy: 1.10.4
scipy: 0.17.0
statsmodels: 0.6.1
xarray: None
IPython: 4.0.3
sphinx: 1.3.1
patsy: 0.4.0
dateutil: 2.4.2
pytz: 2015.7
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.4.6
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.5.0
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.11
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.39.0
Discussed in more detail here