Creating new DataFrame from dict automatically orders columns
#### Code Sample, a copy-pastable example if possible
data = {'C':[1], 'B':[2],'A':[3]}
df = pd.DataFrame(data)

Out[4]: 
   A  B  C
0  3  2  1
```
#### Problem description

Creating a new DataFrame from a dict, I would expect pd.DataFrame() to respect the order in which the columns are put in. It does not. 

If this is a behavior that we want, then I would expect to have the option to turn it off. 

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#### Expected Output
Out[4]: 
   C  B  A
0  1  2  3

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

Out[4]: 
   A  B  C
0  3  2  1

[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.2.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.22.0
pytest: 3.2.0
pip: 19.1.1
setuptools: 41.0.1
Cython: 0.26
numpy: 1.16.0
scipy: 0.19.1
pyarrow: 0.5.0
xarray: 0.9.6
IPython: 6.1.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.7.2
pytz: 2018.9
blosc: 1.5.1
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: 0.3.1
matplotlib: 3.0.3
openpyxl: None
xlrd: 1.0.0
xlwt: None
xlsxwriter: 0.9.8
lxml: None
bs4: 4.6.0
html5lib: 0.9999999
sqlalchemy: 1.1.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: 0.1.2
fastparquet: 0.1.1
pandas_gbq: None
pandas_datareader: 0.5.0
