BUG: plotting with `secondary_y` and then plotting another line results in wrong color for (right) line
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [x] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
import pandas as pd

df = pd.DataFrame({'a': [1, 1], 'b': [2, 2]})
df2 = pd.DataFrame({'d': [2.5, 2.5]})

ax = df.plot(legend=True, secondary_y='b')
df2.plot(legend=False, ax=ax);
```

#### Problem description

Here's what we get:

![image](https://user-images.githubusercontent.com/33491632/109143309-c96a9e80-7757-11eb-81e0-1fd586cd36e1.png)


#### Expected Output

The colours in the legend should be correct, i.e.:

![image](https://user-images.githubusercontent.com/33491632/109143461-f4ed8900-7757-11eb-9cdd-3c629f106bc4.png)


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

<details>

INSTALLED VERSIONS
------------------
commit           : 272435073c70b4421f72184663837f4864601f11
python           : 3.8.6.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-66-generic
Version          : #74-Ubuntu SMP Wed Jan 27 22:54:38 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_GB.UTF-8
LOCALE           : en_GB.UTF-8

pandas           : 1.3.0.dev0+841.g272435073c
numpy            : 1.19.5
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 20.3.3
setuptools       : 49.6.0.post20201009
Cython           : 0.29.21
pytest           : 6.2.2
hypothesis       : 6.2.0
sphinx           : 3.5.1
blosc            : None
feather          : None
xlsxwriter       : 1.3.7
lxml.etree       : 4.6.2
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.19.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 0.8.5
fastparquet      : 0.5.0
gcsfs            : 0.7.2
matplotlib       : 3.3.3
numexpr          : 2.7.2
odfpy            : None
openpyxl         : 3.0.6
pandas_gbq       : None
pyarrow          : 2.0.0
pyxlsb           : None
s3fs             : 0.5.2
scipy            : 1.6.0
sqlalchemy       : 1.3.23
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.16.2
xlrd             : 2.0.1
xlwt             : 1.3.0
numba            : 0.52.0

</details>
