pd.get_dummies different default return type than .str.get_dummies
Let's consider this dataframe with both integer and string values in two columns
```python
import pandas as pd
df = pd.DataFrame({'col1': [0,1,1,0,1], 'col2':list('aabbc')})
```
When I want to use ```str.get_dummies``` on one column and want -1 instead of 1, I can do:
```python
print (-df.col2.str.get_dummies())
   a  b  c
0 -1  0  0
1 -1  0  0
2  0 -1  0
3  0 -1  0
4  0  0 -1
```
which is correct, but at first I tried with ```pd.get_dummies``` and I got a value of 255 instead of -1:
```python
print (-pd.get_dummies(df.col2)) #or print (-pd.get_dummies(df[['col2']])) same result
     a    b    c
0  255    0    0
1  255    0    0
2    0  255    0
3    0  255    0
4    0    0  255
```
If I used only the integer column ```col1```, I get the same behavior, but if I use both columns at once, then I get the right result:
```python
print (-pd.get_dummies(df))
   col1  col2_a  col2_b  col2_c
0     0      -1       0       0
1    -1      -1       0       0
2    -1       0      -1       0
3     0       0      -1       0
4    -1       0       0      -1
```
As explained in the [doc](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.get_dummies.html) , if you don't specify the ```columns``` parameter, then _all the columns with object or category dtype will be converted_, ```col1``` is then ignored as supposed. But if I pass both columns in the parameter, I get 255 instead of -1 again:
```python
print (-pd.get_dummies(df, columns = ['col1','col2']))
   col1_0  col1_1  col2_a  col2_b  col2_c
0     255       0     255       0       0
1       0     255     255       0       0
2       0     255       0     255       0
3     255       0       0     255       0
4       0     255       0       0     255
```
I found this with ```pd.__version__ == "0.24.2"```.
Note: if you do multiply by ```-1``` instead of just the sign ```-```, then ```print (-1*pd.get_dummies(df.col2))``` gives the expected result

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.24.2
pytest: 4.0.2
pip: 18.1
setuptools: 40.6.3
Cython: 0.29.2
numpy: 1.15.4
scipy: 1.1.0
pyarrow: 0.11.1
xarray: None
IPython: 7.2.0
sphinx: 1.8.2
patsy: 0.5.1
dateutil: 2.7.5
pytz: 2018.7
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.8
feather: None
matplotlib: 3.0.2
openpyxl: 2.5.12
xlrd: 1.2.0
xlwt: 1.3.0
xlsxwriter: 1.1.2
lxml.etree: 4.2.5
bs4: 4.6.3
html5lib: 1.0.1
sqlalchemy: 1.2.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
