BUG: pd.DataFrame.astype for SparseDtype with different fill_value results in data loss
- [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.

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

---

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

```python
import pandas as pd
df = pd.DataFrame([[1,1,1,1,0,1]]).T
sdf1 = df.astype(pd.SparseDtype(int, fill_value=1))
sdf2 = sdf1.astype(pd.SparseDtype(int, fill_value=0))
sdf3 = sdf1.astype('Sparse[int]')
print(sdf1)
print(sdf2)
print(sdf3)
```

Output:
```python
>>> print(sdf1)
   0
0  1
1  1
2  1
3  1
4  0
5  1
>>> print(sdf2)
   0
0  0
1  0
2  0
3  0
4  0
5  0
>>> print(sdf3)
   0
0  0
1  0
2  0
3  0
4  0
5  0
```

#### Expected Output
```python
>>> print(sdf1)
   0
0  1
1  1
2  1
3  1
4  0
5  1
>>> print(sdf2)
   0
0  1
1  1
2  1
3  1
4  0
5  1
>>> print(sdf3)
   0
0  1
1  1
2  1
3  1
4  0
5  1
```

#### Problem description

Performing `astype` operation should not change the data in the dataframe. Currently doing `astype` on a dataframe containing sparse columns to a `SparseDtype` with a different `fill_value` results in data loss, e.g. everything becomes 0 for sparse ints. I believe similar phenomenon might exist for other sparse dtypes but have not tested that. 

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

<details>

INSTALLED VERSIONS
------------------
commit           : d9fff2792bf16178d4e450fe7384244e50635733
python           : 3.7.4.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.4.0-179-generic
Version          : #209-Ubuntu SMP Fri Apr 24 17:48:44 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.0
numpy            : 1.18.2
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.2.2
setuptools       : 46.1.3
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : 2.8.4 (dt dec pq3 ext lo64)
jinja2           : 2.11.1
IPython          : 7.13.0
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.2.1
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.15
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : None
xlrd             : 1.2.0
xlwt             : None
numba            : 0.49.1

</details>
