<h4 dir="auto">Code Sample, a copy-pastable example if possible</h4>
<p dir="auto"><strong>BEFORE</strong></p>
<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="df_india.groupby('sector').id.count().sort_values().plot.bar();"><pre class="notranslate"><span class="pl-s1">df_india</span>.<span class="pl-en">groupby</span>(<span class="pl-s">'sector'</span>).<span class="pl-s1">id</span>.<span class="pl-en">count</span>().<span class="pl-en">sort_values</span>().<span class="pl-s1">plot</span>.<span class="pl-en">bar</span>();</pre></div>
<p dir="auto">would result in a bar plot with all bars having the same color</p>
<p dir="auto"><strong>AFTER</strong> version 0.20</p>
<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="df_india.groupby('sector').id.count().sort_values().plot.bar(color='cornflowerblue');"><pre class="notranslate"><span class="pl-s1">df_india</span>.<span class="pl-en">groupby</span>(<span class="pl-s">'sector'</span>).<span class="pl-s1">id</span>.<span class="pl-en">count</span>().<span class="pl-en">sort_values</span>().<span class="pl-s1">plot</span>.<span class="pl-en">bar</span>(<span class="pl-s1">color</span><span class="pl-c1">=</span><span class="pl-s">'cornflowerblue'</span>);</pre></div>
<p dir="auto">I need to explicitly provide a color, else each bar is colored differently</p>
<p dir="auto">Minimal reproducible code:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="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()"><pre class="notranslate"><code class="notranslate">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()
</code></pre></div>
<p dir="auto">Output:</p>
<p dir="auto"><a target="_blank" rel="noopener noreferrer nofollow" href="https://user-images.githubusercontent.com/3866405/38206924-d34dffcc-36c9-11e8-866c-57364f90042b.png"><img src="https://user-images.githubusercontent.com/3866405/38206924-d34dffcc-36c9-11e8-866c-57364f90042b.png" alt="download" style="max-width: 100%;"></a></p>
<h4 dir="auto">Problem description</h4>
<p dir="auto">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.</p>
<p dir="auto">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.</p>
<p dir="auto">Reference for visual appeal and the use of colors: <a href="http://www.perceptualedge.com/articles/visual_business_intelligence/rules_for_using_color.pdf" rel="nofollow">http://www.perceptualedge.com/articles/visual_business_intelligence/rules_for_using_color.pdf</a></p>
<p dir="auto">Would it be possible to revert to the pre-0.20 behavior?</p>
<h4 dir="auto">Output of <code class="notranslate">pd.show_versions()</code></h4>
<details>
<p dir="auto">[paste the output of <code class="notranslate">pd.show_versions()</code> here below this line]</p>
<h2 dir="auto">INSTALLED VERSIONS</h2>
<p dir="auto">commit: None<br>
python: 3.6.4.final.0<br>
python-bits: 64<br>
OS: Linux<br>
OS-release: 4.9.0-5-amd64<br>
machine: x86_64<br>
processor:<br>
byteorder: little<br>
LC_ALL: C.UTF-8<br>
LANG: C.UTF-8<br>
LOCALE: en_US.UTF-8</p>
<p dir="auto">pandas: 0.22.0<br>
pytest: 3.2.1<br>
pip: 9.0.1<br>
setuptools: 38.5.2<br>
Cython: 0.26.1<br>
numpy: 1.14.2<br>
scipy: 1.0.0<br>
pyarrow: 0.8.0<br>
xarray: 0.10.1<br>
IPython: 6.1.0<br>
sphinx: 1.6.3<br>
patsy: 0.4.1<br>
dateutil: 2.6.0<br>
pytz: 2018.3<br>
blosc: None<br>
bottleneck: 1.2.1<br>
tables: 3.4.2<br>
numexpr: 2.6.2<br>
feather: 0.4.0<br>
matplotlib: 2.1.0<br>
openpyxl: 2.4.8<br>
xlrd: 1.1.0<br>
xlwt: 1.3.0<br>
xlsxwriter: 1.0.2<br>
lxml: 4.1.0<br>
bs4: 4.6.0<br>
html5lib: 0.9999999<br>
sqlalchemy: 1.1.13<br>
pymysql: None<br>
psycopg2: None<br>
jinja2: 2.9.6<br>
s3fs: None<br>
fastparquet: None<br>
pandas_gbq: None<br>
pandas_datareader: 0.6.0</p>
</details>
<h4 dir="auto">Code Sample</h4>
<div class="highlight highlight-source-python notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="Series([10**x for x in range(5)]).plot.bar()
Series([10**x for x in range(5)]).plot.bar(logy=True)"><pre class="notranslate"><span class="pl-v">Series</span>([<span class="pl-c1">10</span><span class="pl-c1">**</span><span class="pl-s1">x</span> <span class="pl-k">for</span> <span class="pl-s1">x</span> <span class="pl-c1">in</span> <span class="pl-en">range</span>(<span class="pl-c1">5</span>)]).<span class="pl-s1">plot</span>.<span class="pl-en">bar</span>()
<span class="pl-v">Series</span>([<span class="pl-c1">10</span><span class="pl-c1">**</span><span class="pl-s1">x</span> <span class="pl-k">for</span> <span class="pl-s1">x</span> <span class="pl-c1">in</span> <span class="pl-en">range</span>(<span class="pl-c1">5</span>)]).<span class="pl-s1">plot</span>.<span class="pl-en">bar</span>(<span class="pl-s1">logy</span><span class="pl-c1">=</span><span class="pl-c1">True</span>)</pre></div>
<h4 dir="auto">Problem description</h4>
<p dir="auto">The behavior changed from last version, 0.20. In last version, <code class="notranslate">Series.plot.bar</code> uses one color for bars. In the new version, it uses different colors for bars even for a single series. When using <code class="notranslate">logy</code> argument, the bars cannot be seen. It seems the fill color is same as the background color.</p>
<p dir="auto"><a target="_blank" rel="noopener noreferrer nofollow" href="https://user-images.githubusercontent.com/1349042/33044244-31e3451e-ce16-11e7-9c2e-ca86ac0664ec.png"><img src="https://user-images.githubusercontent.com/1349042/33044244-31e3451e-ce16-11e7-9c2e-ca86ac0664ec.png" alt="image" style="max-width: 100%;"></a><br>
<a target="_blank" rel="noopener noreferrer nofollow" href="https://user-images.githubusercontent.com/1349042/33044250-363cfc68-ce16-11e7-9dec-1b115e399369.png"><img src="https://user-images.githubusercontent.com/1349042/33044250-363cfc68-ce16-11e7-9dec-1b115e399369.png" alt="image" style="max-width: 100%;"></a></p>
<h4 dir="auto">Output of <code class="notranslate">pd.show_versions()</code></h4>
<details>
<h2 dir="auto">INSTALLED VERSIONS</h2>
<p dir="auto">commit: None<br>
python: 3.6.3.final.0<br>
python-bits: 64<br>
OS: Windows<br>
OS-release: 10<br>
machine: AMD64<br>
processor: Intel64 Family 6 Model 94 Stepping 3, GenuineIntel<br>
byteorder: little<br>
LC_ALL: None<br>
LANG: None<br>
LOCALE: None.None</p>
<p dir="auto">pandas: 0.21.0<br>
pytest: 3.2.1<br>
pip: 9.0.1<br>
setuptools: 36.5.0.post20170921<br>
Cython: 0.26.1<br>
numpy: 1.13.3<br>
scipy: 1.0.0<br>
pyarrow: 0.7.0<br>
xarray: None<br>
IPython: 6.1.0<br>
sphinx: 1.6.3<br>
patsy: 0.4.1<br>
dateutil: 2.6.1<br>
pytz: 2017.2<br>
blosc: None<br>
bottleneck: 1.2.1<br>
tables: 3.4.2<br>
numexpr: 2.6.2<br>
feather: 0.4.0<br>
matplotlib: 2.1.0<br>
openpyxl: 2.4.8<br>
xlrd: 1.1.0<br>
xlwt: 1.3.0<br>
xlsxwriter: 1.0.2<br>
lxml: 4.1.0<br>
bs4: 4.6.0<br>
html5lib: 0.999999999<br>
sqlalchemy: 1.1.13<br>
pymysql: 0.7.11.None<br>
psycopg2: None<br>
jinja2: 2.9.6<br>
s3fs: None<br>
fastparquet: None<br>
pandas_gbq: None<br>
pandas_datareader: 0.5.0]</p>
</details>