Description
Code Sample, a copy-pastable example if possible
In [2]: import numpy as np
In [3]: df = pd.DataFrame(np.random.random((1000, 4)))
In [4]: percentiles = np.linspace(0, 0.99, 10)
In [5]: df.describe(percentiles=percentiles)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-5-83616b318eba> in <module>()
----> 1 df.describe(percentiles=percentiles)
C:\Users\pbreach\Anaconda3\lib\site-packages\pandas\core\generic.py in describe(self, percentiles, include, exclude)
5194 # median should always be included
5195 if 0.5 not in percentiles:
-> 5196 percentiles.append(0.5)
5197 percentiles = np.asarray(percentiles)
5198 else:
AttributeError: 'numpy.ndarray' object has no attribute 'append'
Problem description
In the documentation the kwarg percentiles is expecting an array-like input, however when passing in a numpy array, an attribute error is thrown as if it were expecting a list. If a list is being expected in the case that the median is not found should there be an explicit conversion to list before the median is appended?
Expected Output
In [6]: df.describe(percentiles=list(percentiles))
Out[6]:
0 1 2 3
count 1000.000000 1000.000000 1000.000000 1000.000000
mean 0.500730 0.501185 0.498594 0.498648
std 0.289616 0.286023 0.290509 0.292264
min 0.001290 0.000822 0.000459 0.001975
0% 0.001290 0.000822 0.000459 0.001975
11% 0.119319 0.124990 0.107683 0.114136
22% 0.211321 0.232740 0.209913 0.227046
33% 0.331405 0.325820 0.336409 0.311294
44% 0.439314 0.446085 0.443036 0.431923
50% 0.500374 0.505759 0.499125 0.491579
55.0% 0.553634 0.552899 0.552896 0.544990
66% 0.666159 0.647926 0.661797 0.661387
77% 0.777984 0.774892 0.776067 0.773342
88% 0.883761 0.874293 0.872860 0.884350
99% 0.985795 0.989234 0.991083 0.993646
max 0.998623 0.999924 0.999723 0.999185
Output of pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.19.1
nose: 1.3.7
pip: 9.0.1
setuptools: 23.0.0
Cython: 0.24
numpy: 1.11.2
scipy: 0.18.1
statsmodels: 0.6.1
xarray: 0.8.2
IPython: 4.2.0
sphinx: 1.3.1
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.4
blosc: None
bottleneck: 1.1.0
tables: 3.2.2
numexpr: 2.6.0
matplotlib: 1.5.3
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.2
lxml: 3.6.0
bs4: 4.4.1
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.40.0
pandas_datareader: None