id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
712217045,MDU6SXNzdWU3MTIyMTcwNDU=,4476,Reimplement GroupBy.argmax,1200058,open,0,,,5,2020-09-30T19:25:22Z,2023-03-03T06:59:40Z,,NONE,,,,"Please implement

**Is your feature request related to a problem? Please describe.**
Observed:
```python
da.groupby(""g"").argmax(dim=""t"")
```
```python
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-84-15c199b0f7d4> in <module>
----> 1 da.groupby(""g"").argmax(dim=""t"")

AttributeError: 'DataArrayGroupBy' object has no attribute 'argmax'
```

**Describe the solution you'd like**
Expected: Vector of length `len(unique(g))` containing the indices of `da[""t""]` where the value was maximum.

**Workaround:**
```python
da.groupby(""g"").apply(lambda c: c.argmax(dim=""t""))
```
```
<xarray.DataArray 'da' (st: 11, g: 1)>
array([[ 7],
       [ 0],
       [14],
       [14],
       [ 0],
       [ 0],
       [ 7],
       [ 0],
       [14],
       [ 0],
       [ 7]])
Coordinates:
  * st      (st) object 'a' ... 'z'
  * g       (g) object 'E'
```

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528060435,MDU6SXNzdWU1MjgwNjA0MzU=,3570,fillna on dataset converts all variables to float,1200058,open,0,,,5,2019-11-25T12:39:49Z,2020-09-15T15:35:04Z,,NONE,,,,"#### MCVE Code Sample
```python
xr.Dataset(
     {
         ""A"": (""x"", [np.nan, 2, np.nan, 0]),
         ""B"": (""x"", [3, 4, np.nan, 1]),
         ""C"": (""x"", [True, True, False, False]),
         ""D"": (""x"", [np.nan, 3, np.nan, 4])
     },
     coords={""x"": [0, 1, 2, 3]}
).fillna(value={""A"": 0})
```
```
<xarray.Dataset>
Dimensions:  (x: 4)
Coordinates:
  * x        (x) int64 0 1 2 3
Data variables:
    A        (x) float64 0.0 2.0 0.0 0.0
    B        (x) float64 3.0 4.0 nan 1.0
    C        (x) float64 1.0 1.0 0.0 0.0
    D        (x) float64 nan 3.0 nan 4.0
```

#### Expected Output
```
<xarray.Dataset>
Dimensions:  (x: 4)
Coordinates:
  * x        (x) int64 0 1 2 3
Data variables:
    A        (x) float64 0.0 2.0 0.0 0.0
    B        (x) float64 3.0 4.0 nan 1.0
    C        (x) bool True True False False
    D        (x) float64 nan 3.0 nan 4.0
```

#### Problem Description
I'd like to use `fillna` to replace NaN's in some of a `Dataset`'s variables.
However, `fillna` unexpectably converts all variables to float, even if they are boolean or integers.

Would it be possible to apply `fillna` only on float / object types and consider the `value` argument, if I only want to apply `fillna` to a subset of the dataset?


#### Output of ``xr.show_versions()``
<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.4 (default, Aug 13 2019, 20:35:49) 
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-957.27.2.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.4
libnetcdf: 4.6.1

xarray: 0.14.0
pandas: 0.25.1
numpy: 1.17.2
scipy: 1.3.1
netCDF4: 1.4.2
pydap: None
h5netcdf: 0.7.4
h5py: 2.9.0
Nio: None
zarr: 2.3.2
cftime: 1.0.3.4
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2.5.2
distributed: 2.5.2
matplotlib: 3.1.1
cartopy: None
seaborn: 0.9.0
numbagg: None
setuptools: 41.4.0
pip: 19.2.3
conda: None
pytest: 5.0.1
IPython: 7.8.0
sphinx: None


</details>
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