visual bug in pd.style.background_gradient

#### Problem description
The `pd.style.background_gradient` messes up the color order. That is it display wrongs colors that obviously don't conform the order of underlying numbers.

#### Code Sample, a copy-pastable example if possible
```python
import io
import pandas as pd
pd.read_csv(io.StringIO('''round,letter,source,findings,punctuation,see,reference
round 1,0.9853724610779391,0.9967806193222191,0.9857700345095259,0.966600495940578,0.98430677224734,0.572541233138048
round 2,0.9999946348522148,0.9995960833535309,0.994186634099717,0.987516415231207,0.9903793223872329,0.863724309623997
round 3,0.999963099705787,0.999681116612525,0.993544442544026,0.990503466426927,0.983378536954797,0.924636377166516
'''))

aucs.style.background_gradient(cmap='viridis_r').format("{:.2%}")

```

<img width="578" alt="Screen Shot 2020-02-23 at 13 09 22" src="https://user-images.githubusercontent.com/8426290/75120156-26f87680-563e-11ea-824f-1222be131eee.png">

Notice that 57% appears to be yellow, while on the left of it 98% is green (that is it suggest that it's a lower number).

#### Expected Output
This is how same table was plotted in seaborn. Find 10 differences ;)
![image](https://user-images.githubusercontent.com/8426290/75120174-4ee7da00-563e-11ea-91a5-26334d9d5f8a.png)





#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.2.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.1
numpy            : 1.16.2
pytz             : 2018.4
dateutil         : 2.7.3
pip              : 19.0.3
setuptools       : 40.8.0
Cython           : 0.29.10
pytest           : 4.3.1
hypothesis       : None
sphinx           : 1.8.5
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.4.1
html5lib         : None
pymysql          : None
psycopg2         : 2.7.5 (dt dec pq3 ext lo64)
jinja2           : 2.10
IPython          : 7.4.0
pandas_datareader: None
bs4              : 4.8.1
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.4.1
matplotlib       : 2.2.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 4.3.1
pyxlsb           : None
s3fs             : None
scipy            : 1.2.1
sqlalchemy       : 1.3.10
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : 0.46.0
</details>
