pandas2ri.ri2py_dataframe(r_dataframe) returns floating point numbers instead of ISO-8601 (YYYY-MM-DD) formatted dates
#### Code Sample, a copy-pastable example if possible

```python
# First, convert the input dataframe to an R dataframe to be used by our R function:
input_dataframe_r = pandas2ri.py2ri(input_dataframe)
output_dataframe_r = r_generate_notifications(input_dataframe_r, metric_name, lookback, moving_average, sigmas)

# And convert it back to a Pandas dataframe:
output_dataframe_py = pandas2ri.ri2py_dataframe(output_dataframe_r)

print('output dataframe r:', output_dataframe_r)
print('\n')
print('output dataframe py:', output_dataframe_py)
print('\n')

```
#### Problem description

I have a Pandas dataframe in Python that I want to do some R maths on. So I take in a parameter of `input_dataframe` which is a Pandas dataframe, do some stuff (in this case it's an R function called `r_generate_notifications()`), then convert back to a Python Pandas dataframe using `output_dataframe_py = pandas2ri.ri2py_dataframe(output_dataframe_r)`. 

The problem is that the R code returns some dates using `ymd()` and when I convert to a Pandas dataframe, these all convert to floating point numbers. I'm not sure if this is an error or bug in the code or if it's user error. I'll be posting this on StackOverflow as well to see if I get some hits.

#### Expected Output
```python
output dataframe r:    notify_day daily_value is_high_value time_period_length time_period_value
1  2017-05-09    11033.79             1                  7          30938.45
2  2017-05-18     1613.64             1                  7          25669.63
3  2017-05-19     2121.38             1                  7          28048.14
4  2017-05-26     1774.44             1                  7          28185.27
5  2017-06-12      693.24             1                  7          26170.57
6  2017-06-24     2275.77             1                  7          36550.32
7  2017-06-29     5336.76             1                  7          32748.46
8  2017-06-30     8921.38             1                  7          43366.39
9  2017-07-11     4007.84             0                  7          28986.47
10 2017-07-20     5766.12             0                  7          24627.51
11 2017-08-01     4150.32             1                  7          24760.60
12 2017-08-04      734.40             0                  7          20645.43
13 2017-08-12        0.00             1                  7           9898.20
14 2017-12-29     5000.00             1                  7          12467.02
15 2018-01-28        0.00             1                  7          12538.81
16 2018-02-14        0.00             1                  7          14351.24
17 2018-02-20    10628.82             1                  7          20905.00
18 2018-03-16      237.44             1                  7          24400.76
19 2018-03-21      917.96             1                  7          26485.20
20 2018-03-24     1272.85             1                  7          39287.70
21 2018-03-26     3231.26             1                  7          41543.95
22 2018-03-29     9493.31             1                  7          43060.81
23 2018-03-30    21696.04             0                  7          34854.90
24 2018-03-31     1403.33             0                  7          13158.86
25 2018-04-06        0.00             0                  7          15240.38
26 2018-04-08      453.68             0                  7          18004.12
27 2018-04-18     4666.36             1                  7          27038.60
28 2018-04-21        0.00             0                  7          24620.15
29 2018-04-23     4306.88             1                  7          27470.00
   time_period_start time_period_end comparison_days_ago comparison_value
1         2017-05-03      2017-05-09                  28         19056.30
2         2017-05-12      2017-05-18                  14         21610.99
3         2017-05-13      2017-05-19                  28         24321.11
4         2017-05-20      2017-05-26                  28         14530.01
5         2017-06-06      2017-06-12                  28         20087.97
6         2017-06-18      2017-06-24                  28         30796.60
7         2017-06-23      2017-06-29                  14         28394.23
8         2017-06-24      2017-06-30                  28         22758.57
9         2017-07-05      2017-07-11                  14         36122.77
10        2017-07-14      2017-07-20                  28         29509.53
11        2017-07-26      2017-08-01                   7         19662.71
12        2017-07-29      2017-08-04                  28         30518.06
13        2017-08-06      2017-08-12                   1          4487.40
14        2017-12-23      2017-12-29                  28             0.00
15        2018-01-22      2018-01-28                  28         10393.82
16        2018-02-08      2018-02-14                  28          2177.36
17        2018-02-14      2018-02-20                  28           602.64
18        2018-03-10      2018-03-16                  28         19042.76
19        2018-03-15      2018-03-21                  28         14042.68
20        2018-03-18      2018-03-24                  28          9351.16
21        2018-03-20      2018-03-26                  28          7909.36
22        2018-03-23      2018-03-29                  28           464.28
23        2018-03-24      2018-03-30                   1         43060.81
24        2018-03-25      2018-03-31                  14         24163.32
25        2018-03-31      2018-04-06                  14         17591.66
26        2018-04-02      2018-04-08                  14         39418.18
27        2018-04-12      2018-04-18                  14         12906.06
28        2018-04-15      2018-04-21                  28         39287.70
29        2018-04-17      2018-04-23                  14         18153.08
   comparison_period_start comparison_period_end
1               2017-04-05            2017-04-11
2               2017-04-28            2017-05-04
3               2017-04-15            2017-04-21
4               2017-04-22            2017-04-28
5               2017-05-09            2017-05-15
6               2017-05-21            2017-05-27
7               2017-06-09            2017-06-15
8               2017-05-27            2017-06-02
9               2017-06-21            2017-06-27
10              2017-06-16            2017-06-22
11              2017-07-19            2017-07-25
12              2017-07-01            2017-07-07
13              2017-08-05            2017-08-11
14              2017-11-25            2017-12-01
15              2017-12-25            2017-12-31
16              2018-01-11            2018-01-17
17              2018-01-17            2018-01-23
18              2018-02-10            2018-02-16
19              2018-02-15            2018-02-21
20              2018-02-18            2018-02-24
21              2018-02-20            2018-02-26
22              2018-02-23            2018-03-01
23              2018-03-23            2018-03-29
24              2018-03-11            2018-03-17
25              2018-03-17            2018-03-23
26              2018-03-19            2018-03-25
27              2018-03-29            2018-04-04
28              2018-03-18            2018-03-24
29              2018-04-03            2018-04-09
```

#### Actual Output

```python
output dataframe py:     notify_day  daily_value  is_high_value  time_period_length  \
0      17295.0     11033.79            1.0                   7   
1      17304.0      1613.64            1.0                   7   
2      17305.0      2121.38            1.0                   7   
3      17312.0      1774.44            1.0                   7   
4      17329.0       693.24            1.0                   7   
5      17341.0      2275.77            1.0                   7   
6      17346.0      5336.76            1.0                   7   
7      17347.0      8921.38            1.0                   7   
8      17358.0      4007.84            0.0                   7   
9      17367.0      5766.12            0.0                   7   
10     17379.0      4150.32            1.0                   7   
11     17382.0       734.40            0.0                   7   
12     17390.0         0.00            1.0                   7   
13     17529.0      5000.00            1.0                   7   
14     17559.0         0.00            1.0                   7   
15     17576.0         0.00            1.0                   7   
16     17582.0     10628.82            1.0                   7   
17     17606.0       237.44            1.0                   7   
18     17611.0       917.96            1.0                   7   
19     17614.0      1272.85            1.0                   7   
20     17616.0      3231.26            1.0                   7   
21     17619.0      9493.31            1.0                   7   
22     17620.0     21696.04            0.0                   7   
23     17621.0      1403.33            0.0                   7   
24     17627.0         0.00            0.0                   7   
25     17629.0       453.68            0.0                   7   
26     17639.0      4666.36            1.0                   7   
27     17642.0         0.00            0.0                   7   
28     17644.0      4306.88            1.0                   7   

    time_period_value  time_period_start  time_period_end  \
0            30938.45            17289.0          17295.0   
1            25669.63            17298.0          17304.0   
2            28048.14            17299.0          17305.0   
3            28185.27            17306.0          17312.0   
4            26170.57            17323.0          17329.0   
5            36550.32            17335.0          17341.0   
6            32748.46            17340.0          17346.0   
7            43366.39            17341.0          17347.0   
8            28986.47            17352.0          17358.0   
9            24627.51            17361.0          17367.0   
10           24760.60            17373.0          17379.0   
11           20645.43            17376.0          17382.0   
12            9898.20            17384.0          17390.0   
13           12467.02            17523.0          17529.0   
14           12538.81            17553.0          17559.0   
15           14351.24            17570.0          17576.0   
16           20905.00            17576.0          17582.0   
17           24400.76            17600.0          17606.0   
18           26485.20            17605.0          17611.0   
19           39287.70            17608.0          17614.0   
20           41543.95            17610.0          17616.0   
21           43060.81            17613.0          17619.0   
22           34854.90            17614.0          17620.0   
23           13158.86            17615.0          17621.0   
24           15240.38            17621.0          17627.0   
25           18004.12            17623.0          17629.0   
26           27038.60            17633.0          17639.0   
27           24620.15            17636.0          17642.0   
28           27470.00            17638.0          17644.0   

    comparison_days_ago  comparison_value  comparison_period_start  \
0                  28.0          19056.30                  17261.0   
1                  14.0          21610.99                  17284.0   
2                  28.0          24321.11                  17271.0   
3                  28.0          14530.01                  17278.0   
4                  28.0          20087.97                  17295.0   
5                  28.0          30796.60                  17307.0   
6                  14.0          28394.23                  17326.0   
7                  28.0          22758.57                  17313.0   
8                  14.0          36122.77                  17338.0   
9                  28.0          29509.53                  17333.0   
10                  7.0          19662.71                  17366.0   
11                 28.0          30518.06                  17348.0   
12                  1.0           4487.40                  17383.0   
13                 28.0              0.00                  17495.0   
14                 28.0          10393.82                  17525.0   
15                 28.0           2177.36                  17542.0   
16                 28.0            602.64                  17548.0   
17                 28.0          19042.76                  17572.0   
18                 28.0          14042.68                  17577.0   
19                 28.0           9351.16                  17580.0   
20                 28.0           7909.36                  17582.0   
21                 28.0            464.28                  17585.0   
22                  1.0          43060.81                  17613.0   
23                 14.0          24163.32                  17601.0   
24                 14.0          17591.66                  17607.0   
25                 14.0          39418.18                  17609.0   
26                 14.0          12906.06                  17619.0   
27                 28.0          39287.70                  17608.0   
28                 14.0          18153.08                  17624.0   

    comparison_period_end  
0                 17267.0  
1                 17290.0  
2                 17277.0  
3                 17284.0  
4                 17301.0  
5                 17313.0  
6                 17332.0  
7                 17319.0  
8                 17344.0  
9                 17339.0  
10                17372.0  
11                17354.0  
12                17389.0  
13                17501.0  
14                17531.0  
15                17548.0  
16                17554.0  
17                17578.0  
18                17583.0  
19                17586.0  
20                17588.0  
21                17591.0  
22                17619.0  
23                17607.0  
24                17613.0  
25                17615.0  
26                17625.0  
27                17614.0  
28                17630.0  
```
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-122-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
pytest: None
pip: 10.0.1
setuptools: 39.1.0
Cython: None
numpy: 1.14.3
scipy: None
pyarrow: None
xarray: None
IPython: 6.4.0
sphinx: None
patsy: None
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
