df.plot.bar not showing colors as expected as compared to matplotlib

[rajgupt]

pandas/pandas/plotting/_core.py

Lines 2649 to 2666 in 3a7f956

	def bar(self, x=None, y=None, **kwds):
	"""
	Vertical bar plot
	.. versionadded:: 0.17.0
	Parameters
	----------
	x, y : label or position, optional
	Coordinates for each point.
	**kwds : optional
	Keyword arguments to pass on to :py:meth:`pandas.DataFrame.plot`.
	Returns
	-------
	axes : matplotlib.AxesSubplot or np.array of them
	"""
	return self(kind='bar', x=x, y=y, **kwds)

import pandas as pd
import numpy as np
import matplotlib
get_ipython().magic(u'pylab inline')

# In[17]:
df = pd.DataFrame({'id': range(1,11), 'normcolor': np.random.rand(10), 'count': np.random.randint(0,100,(10))})

# In[21]:
colors = matplotlib.cm.hsv(df['normcolor'])
df.plot.bar('id','count', color=colors) # return plot with not color variation


# In[22]:
plt.bar(df['id'], df['count'], color=colors) # returns plot as expected

Current Output

Correct Output

[rajgupt]

import pandas as pd
pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 2.7.12.final.0
python-bits: 32
OS: Windows
OS-release: 10
machine: x86
processor: x86 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.20.3
pytest: 2.8.5
pip: 9.0.1
setuptools: 23.0.0
Cython: 0.23.4
numpy: 1.13.1
scipy: 0.19.1
xarray: None
IPython: 4.2.0
sphinx: 1.3.5
patsy: 0.4.0
dateutil: 2.4.2
pytz: 2015.7
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.6.2
feather: None
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
sqlalchemy: 1.0.11
pymysql: None
psycopg2: None
jinja2: 2.8
s3fs: None
pandas_gbq: None
pandas_datareader: None
None

[chris-b1]

duplicate of #16822, PR to fix welcome! From that issue, df.plot.bar('id','count', color=[colors]) is apparently a workaround.