Issue 1:
Code Sample, a copy-pastable example if possible

BEFORE

df_india.groupby('sector').id.count().sort_values().plot.bar();

would result in a bar plot with all bars having the same color

AFTER version 0.20

df_india.groupby('sector').id.count().sort_values().plot.bar(color='cornflowerblue');

I need to explicitly provide a color, else each bar is colored differently

Minimal reproducible code:

import pandas as pd
df = pd.DataFrame({'account-start': ['2017-02-03', '2017-03-03', '2017-01-01'],
'client': ['Alice Anders', 'Bob Baker', 'Charlie Chaplin'],
'balance': [-1432.32, 10.43, 30000.00],
'db-id': [1234, 2424, 251],
'proxy-id': [525, 1525, 2542],
'rank': [52, 525, 32],
})
df.client.value_counts().plot.bar()

Output:

Problem description

Why was the behavior of Series.plot.bar changed to plot bars with different color? Visually these colors add nothing to the plot as different colors should only be used when they correspond to differences of meaning in the data.

Why is the default behavior to provide an unnecessarily visually overwhelming graph? It took me some time to realize why my bars suddenly started acting strangely. Now, I pass color='cornflowerblue' to get all my bars the same pleasant hue.

Reference for visual appeal and the use of colors: http://www.perceptualedge.com/articles/visual_business_intelligence/rules_for_using_color.pdf

Would it be possible to revert to the pre-0.20 behavior?

Output of pd.show_versions()

[paste the output of pd.show_versions() here below this line]

INSTALLED VERSIONS

commit: None

python: 3.6.4.final.0

python-bits: 64

OS: Linux

OS-release: 4.9.0-5-amd64

machine: x86_64

processor:

byteorder: little

LC_ALL: C.UTF-8

LANG: C.UTF-8

LOCALE: en_US.UTF-8

pandas: 0.22.0

pytest: 3.2.1

pip: 9.0.1

setuptools: 38.5.2

Cython: 0.26.1

numpy: 1.14.2

scipy: 1.0.0

pyarrow: 0.8.0

xarray: 0.10.1

IPython: 6.1.0

sphinx: 1.6.3

patsy: 0.4.1

dateutil: 2.6.0

pytz: 2018.3

blosc: None

bottleneck: 1.2.1

tables: 3.4.2

numexpr: 2.6.2

feather: 0.4.0

matplotlib: 2.1.0

openpyxl: 2.4.8

xlrd: 1.1.0

xlwt: 1.3.0

xlsxwriter: 1.0.2

lxml: 4.1.0

bs4: 4.6.0

html5lib: 0.9999999

sqlalchemy: 1.1.13

pymysql: None

psycopg2: None

jinja2: 2.9.6

s3fs: None

fastparquet: None

pandas_gbq: None

pandas_datareader: 0.6.0

Issue 2:
Code Sample

Series([10**x for x in range(5)]).plot.bar()
Series([10**x for x in range(5)]).plot.bar(logy=True)

Problem description

The behavior changed from last version, 0.20. In last version, Series.plot.bar uses one color for bars. In the new version, it uses different colors for bars even for a single series. When using logy argument, the bars cannot be seen. It seems the fill color is same as the background color.

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None

python: 3.6.3.final.0

python-bits: 64

OS: Windows

OS-release: 10

machine: AMD64

processor: Intel64 Family 6 Model 94 Stepping 3, GenuineIntel

byteorder: little

LC_ALL: None

LANG: None

LOCALE: None.None

pandas: 0.21.0

pytest: 3.2.1

pip: 9.0.1

setuptools: 36.5.0.post20170921

Cython: 0.26.1

numpy: 1.13.3

scipy: 1.0.0

pyarrow: 0.7.0

xarray: None

IPython: 6.1.0

sphinx: 1.6.3

patsy: 0.4.1

dateutil: 2.6.1

pytz: 2017.2

blosc: None

bottleneck: 1.2.1

tables: 3.4.2

numexpr: 2.6.2

feather: 0.4.0

matplotlib: 2.1.0

openpyxl: 2.4.8

xlrd: 1.1.0

xlwt: 1.3.0

xlsxwriter: 1.0.2

lxml: 4.1.0

bs4: 4.6.0

html5lib: 0.999999999

sqlalchemy: 1.1.13

pymysql: 0.7.11.None

psycopg2: None

jinja2: 2.9.6

s3fs: None

fastparquet: None

pandas_gbq: None

pandas_datareader: 0.5.0]