pandas.Dataframe.interpolate() does not extrapolate even if it is asked to, depending on interpolation method
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import numpy as np

a = pd.Series([0, 1, np.nan, 3, 4, np.nan, np.nan, np.nan, np.nan])
a_int=a.interpolate(method='cubic', limit_area=None)

```
#### Problem description

Some of the offered methods (it seems all of them that are provided by interp1d) are unable to extrapolate over np.nan. However, the limit_area switch for df.interpolate() indicates you can force extrapolation. A combination of limit_area=None and an incompatible method should raise a warning.

There used to be a similar issue where extrapolation over trailing NaN was done unintentionally, so maybe the fix for that overdid it. https://github.com/pandas-dev/pandas/issues/8000

#### Expected Output

Extrapolation over the NaNs in the array is expected. Using a different method, such as pchip achieves this.

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.2.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 63 Stepping 2, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : en
LOCALE           : None.None

pandas           : 0.25.3 (also tested with 1.0.0)
numpy            : 1.15.4
pytz             : 2018.9
dateutil         : 2.7.5
pip              : 20.0.2
setuptools       : 41.0.1
Cython           : 0.29.15
pytest           : None
hypothesis       : None
sphinx           : 1.8.3
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.3.3
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10
IPython          : 7.5.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.3.3
matplotlib       : 3.0.3
numexpr          : None
odfpy            : None
openpyxl         : 2.5.12
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : 1.2.1
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : None
</details>
