html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/2547#issuecomment-460600719,https://api.github.com/repos/pydata/xarray/issues/2547,460600719,MDEyOklzc3VlQ29tbWVudDQ2MDYwMDcxOQ==,21049064,2019-02-05T11:15:49Z,2019-02-05T11:15:49Z,NONE,But the original question was answered so thank you very much!,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-460600500,https://api.github.com/repos/pydata/xarray/issues/2547,460600500,MDEyOklzc3VlQ29tbWVudDQ2MDYwMDUwMA==,21049064,2019-02-05T11:15:01Z,2019-02-05T11:15:01Z,NONE,"Sorry for the silence! I got pulled away to another project. Unfortunately I wasn't able to finish completing the task in xarray but I found that the easiest way around the problem was to use a combination of two functions:
```python
def change_missing_vals_to_9999f(ds, variable):
"""""" Change the missing values from np.nan to -9999.0f""""""
arr = ds[variable].values
# set the values to -9999
arr[np.isnan(arr)] = -9999
# reassign the values back to the array
ds[variable] = (ds[variable].dims, arr)
return ds
def change_missing_data_values(filename):
"""""" change the values INSIDE the .nc file to -9999.0f """"""
assert (
filename.split(""."")[-1] == ""nc""
), ""This function only works with .nc files. Filename: {}"".format(filename)
print(""** Processing {} **"").format(filename)
# ONLY OPEN THE DATASET ONCE
ds = xr.open_dataset(filename)
variables = ds.data_vars.keys()
for variable in variables:
print(""** Working on variable {} **"".format(variable))
ds = change_missing_vals_to_9999f(ds, variable)
# ds.map(change_missing_vals_to_9999f, variable)
# rewrite to netcdf file
ds.to_netcdf(filename)
print(""** Written variables {} to filename {} **"").format(variables, filename)
return
```
and then another function using the `NCO` command:
```
def change_nc_FillValue(filename):
"""""" use the NCO command to change the fillvalue metadata in the .nc files""""""
command = ""ncatted -a _FillValue,,m,f,-9999.0 {}"".format(filename)
os.system(command)
print(""** _FillValue changed on {} file **"".format(filename))
return
```
RUN HERE:
```
@click.command()
@click.argument(""filename"", type=str)
def main(filename):
"""""" Run the two commands
a) change the Values INSIDE the .nc file [python, numpy, xarray]
b) change the associated METADATA for the .nc file headers [nco]
""""""
change_missing_data_values(filename)
change_nc_FillValue(filename)
print(""**** PROCESS DONE FOR {} ****"").format(filename)
return
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-460020696,https://api.github.com/repos/pydata/xarray/issues/2547,460020696,MDEyOklzc3VlQ29tbWVudDQ2MDAyMDY5Ng==,2443309,2019-02-03T03:50:47Z,2019-02-03T03:50:47Z,MEMBER,"@tommylees112 - this issue has sat for a bit of time now. Did you end up with a solution here? If so, is okay with you if we close this out?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-436695050,https://api.github.com/repos/pydata/xarray/issues/2547,436695050,MDEyOklzc3VlQ29tbWVudDQzNjY5NTA1MA==,6628425,2018-11-07T16:53:14Z,2018-11-07T16:53:14Z,MEMBER,"The `_FillValue` encoding seems to be preserved with your desired value in my example:
```
$ ncdump -h result.nc
netcdf result {
dimensions:
time = 366 ;
y = 200 ;
x = 200 ;
variables:
int64 time(time) ;
time:units = ""days since 2000-01-01 00:00:00"" ;
time:calendar = ""proleptic_gregorian"" ;
short Rg(time, y, x) ;
Rg:_FillValue = -1s ;
Rg:long_name = ""HWSD sub sum content"" ;
Rg:units = ""percent wt"" ;
Rg:valid_range = 97., 103. ;
double latitude(y, x) ;
latitude:_FillValue = -99999. ;
double longitude(y, x) ;
longitude:_FillValue = -99999. ;
// global attributes:
:Conventions = ""CF-1.0"" ;
:content = ""HARMONIZED WORLD SOIL DATABASE; first it was aggregated to one global file; then the missing areas were filled with interpolated data; then separate tiles were extracted"" ;
:scaling_factor = ""20"" ;
```
Is the time encoding important for your land surface model? That does change in my example (see the units attribute); you might need some special logic to handle that.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-436688702,https://api.github.com/repos/pydata/xarray/issues/2547,436688702,MDEyOklzc3VlQ29tbWVudDQzNjY4ODcwMg==,21049064,2018-11-07T16:36:09Z,2018-11-07T16:46:01Z,NONE,"@spencerkclark Thanks very much that is awesome!
One final Q: How do I set the `fill_value` not to `nan` but to `-1` (this is what I need for the Land Surface Model)?
### The current output of `ncdump -h Rg_dummy.nc` is:
```
...
variables:
double time(time) ;
time:_FillValue = NaN ;
time:standard_name = ""time"" ;
time:units = ""day as %Y%m%d.%f"" ;
time:calendar = ""proleptic_gregorian"" ;
short Rg(time, y, x) ;
Rg:_FillValue = NaN ;
Rg:long_name = ""HWSD sub sum content"" ;
Rg:units = ""percent wt"" ;
Rg:valid_range = 97., 103. ;
double latitude(y, x) ;
latitude:_FillValue = -99999. ;
double longitude(y, x) ;
longitude:_FillValue = -99999. ;
```
### What I want is:
`ncdump -h Rg_dummy.nc`
```
...
variables:
double time(time) ;
time:_FillValue = -1s ;
time:standard_name = ""time"" ;
time:units = ""day as %Y%m%d.%f"" ;
time:calendar = ""proleptic_gregorian"" ;
short Rg(time, y, x) ;
Rg:_FillValue = -1s ;
Rg:long_name = ""HWSD sub sum content"" ;
Rg:units = ""percent wt"" ;
Rg:valid_range = 97., 103. ;
double latitude(y, x) ;
latitude:_FillValue = -99999. ;
double longitude(y, x) ;
longitude:_FillValue = -99999. ;
```
I want to do something like:
```
ds2.to_netcdf(filename, set_fill_value=-1)
```
I saw these:
[Issue #1598](https://github.com/pydata/xarray/issues/1598)
[Issue #1865](https://github.com/pydata/xarray/issues/1865)
But failed to understand where/how to use them
Thank you so much for helping me out with xarray. It's crazy powerful. It's also just very big!","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-436679811,https://api.github.com/repos/pydata/xarray/issues/2547,436679811,MDEyOklzc3VlQ29tbWVudDQzNjY3OTgxMQ==,6628425,2018-11-07T16:14:27Z,2018-11-07T16:14:27Z,MEMBER,"Thanks @tommylees112 -- note that the `reindex` and `ffill` methods do not operate in-place, so you'll need to assign the results of them to new variables. You can also do them all in one step:
```
In [1]: import xarray as xr; import pandas as pd; import numpy as np
In [2]: ds = xr.open_dataset('Rg_dummy.nc')
In [3]: times = pd.date_range(""2000-01-01"", ""2000-12-31"", name=""time"")
In [4]: ds['time'] = np.array([times[0]])
In [5]: ds2 = ds.reindex(time=times, method='ffill')
In [6]: ds2.to_netcdf('result.nc')
```
Regarding the issue saving to files -- I can reproduce that issue with older xarray versions. It is related to
#2512 and was fixed in #2513 (i.e. it works with the master version of xarray). The good news is this bug only applies to saving `ds` in my example, not `ds2`, so you should be able to do this with your current setup just fine.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-436668695,https://api.github.com/repos/pydata/xarray/issues/2547,436668695,MDEyOklzc3VlQ29tbWVudDQzNjY2ODY5NQ==,21049064,2018-11-07T15:45:22Z,2018-11-07T15:46:15Z,NONE,"That all worked great until I tried to write out to a .nc file.
```python
data_dir = ""./""
filename = ""Rg_dummy.nc""
# get the datetime range
times = pd.date_range(""2000-01-01"", ""2000-12-31"", name=""time"")
var = ""Rg""
copyfile(data_dir + filename, ""temp.nc"")
ds = xr.open_dataset(""temp.nc"")
print(""Temporary Data read to Python"")
# FORWARD FILL FROM THE ORIGINAL DATA to new timesteps
ds['time'] = np.array([times[0]])
ds.reindex({""time"":times})
ds.ffill(""time"")
ds.to_netcdf(filename, format=""NETCDF3_CLASSIC"")
print(filename, ""Written!"")
# remove temporary file
os.remove(data_dir+""temp.nc"")
print(""Temporary Data Removed"")
del ds
```
I get the following Error message:
```
Temporary Data read to Python
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-228-e3d645224353> in <module>()
15 ds.ffill(""time"")
16
---> 17 ds.to_netcdf(filename, format=""NETCDF3_CLASSIC"")
18 print(filename, ""Written!"")
19
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/core/dataset.pyc in to_netcdf(self, path, mode, format, group, engine, encoding, unlimited_dims, compute)
1148 engine=engine, encoding=encoding,
1149 unlimited_dims=unlimited_dims,
-> 1150 compute=compute)
1151
1152 def to_zarr(self, store=None, mode='w-', synchronizer=None, group=None,
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/api.pyc in to_netcdf(dataset, path_or_file, mode, format, group, engine, writer, encoding, unlimited_dims, compute)
721 try:
722 dataset.dump_to_store(store, sync=sync, encoding=encoding,
--> 723 unlimited_dims=unlimited_dims, compute=compute)
724 if path_or_file is None:
725 return target.getvalue()
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/core/dataset.pyc in dump_to_store(self, store, encoder, sync, encoding, unlimited_dims, compute)
1073
1074 store.store(variables, attrs, check_encoding,
-> 1075 unlimited_dims=unlimited_dims)
1076 if sync:
1077 store.sync(compute=compute)
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/common.pyc in store(self, variables, attributes, check_encoding_set, unlimited_dims)
366 self.set_dimensions(variables, unlimited_dims=unlimited_dims)
367 self.set_variables(variables, check_encoding_set,
--> 368 unlimited_dims=unlimited_dims)
369
370 def set_attributes(self, attributes):
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/netCDF4_.pyc in set_variables(self, *args, **kwargs)
405 def set_variables(self, *args, **kwargs):
406 with self.ensure_open(autoclose=False):
--> 407 super(NetCDF4DataStore, self).set_variables(*args, **kwargs)
408
409 def encode_variable(self, variable):
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/common.pyc in set_variables(self, variables, check_encoding_set, unlimited_dims)
403 check = vn in check_encoding_set
404 target, source = self.prepare_variable(
--> 405 name, v, check, unlimited_dims=unlimited_dims)
406
407 self.writer.add(source, target)
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/netCDF4_.pyc in prepare_variable(self, name, variable, check_encoding, unlimited_dims)
451 least_significant_digit=encoding.get(
452 'least_significant_digit'),
--> 453 fill_value=fill_value)
454 _disable_auto_decode_variable(nc4_var)
455
netCDF4/_netCDF4.pyx in netCDF4._netCDF4.Dataset.createVariable()
netCDF4/_netCDF4.pyx in netCDF4._netCDF4.Variable.__init__()
TypeError: illegal primitive data type, must be one of ['i8', 'f4', 'f8', 'S1', 'i2', 'i4', 'u8', 'u4', 'u1', 'u2', 'i1'], got datetime64[ns]
```
and if I try with the default netcdf writing options
```python
ds.to_netcdf(filename)
print(filename, ""Written!"")
```
I get this error message:
```
Temporary Data read to Python
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-229-453d5f074d33> in <module>()
15 ds.ffill(""time"")
16
---> 17 ds.to_netcdf(filename)
18 print(filename, ""Written!"")
19
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/core/dataset.pyc in to_netcdf(self, path, mode, format, group, engine, encoding, unlimited_dims, compute)
1148 engine=engine, encoding=encoding,
1149 unlimited_dims=unlimited_dims,
-> 1150 compute=compute)
1151
1152 def to_zarr(self, store=None, mode='w-', synchronizer=None, group=None,
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/api.pyc in to_netcdf(dataset, path_or_file, mode, format, group, engine, writer, encoding, unlimited_dims, compute)
721 try:
722 dataset.dump_to_store(store, sync=sync, encoding=encoding,
--> 723 unlimited_dims=unlimited_dims, compute=compute)
724 if path_or_file is None:
725 return target.getvalue()
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/core/dataset.pyc in dump_to_store(self, store, encoder, sync, encoding, unlimited_dims, compute)
1073
1074 store.store(variables, attrs, check_encoding,
-> 1075 unlimited_dims=unlimited_dims)
1076 if sync:
1077 store.sync(compute=compute)
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/common.pyc in store(self, variables, attributes, check_encoding_set, unlimited_dims)
366 self.set_dimensions(variables, unlimited_dims=unlimited_dims)
367 self.set_variables(variables, check_encoding_set,
--> 368 unlimited_dims=unlimited_dims)
369
370 def set_attributes(self, attributes):
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/netCDF4_.pyc in set_variables(self, *args, **kwargs)
405 def set_variables(self, *args, **kwargs):
406 with self.ensure_open(autoclose=False):
--> 407 super(NetCDF4DataStore, self).set_variables(*args, **kwargs)
408
409 def encode_variable(self, variable):
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/common.pyc in set_variables(self, variables, check_encoding_set, unlimited_dims)
403 check = vn in check_encoding_set
404 target, source = self.prepare_variable(
--> 405 name, v, check, unlimited_dims=unlimited_dims)
406
407 self.writer.add(source, target)
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/netCDF4_.pyc in prepare_variable(self, name, variable, check_encoding, unlimited_dims)
418 unlimited_dims=None):
419 datatype = _get_datatype(variable, self.format,
--> 420 raise_on_invalid_encoding=check_encoding)
421 attrs = variable.attrs.copy()
422
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/netCDF4_.pyc in _get_datatype(var, nc_format, raise_on_invalid_encoding)
99 def _get_datatype(var, nc_format='NETCDF4', raise_on_invalid_encoding=False):
100 if nc_format == 'NETCDF4':
--> 101 datatype = _nc4_dtype(var)
102 else:
103 if 'dtype' in var.encoding:
/home/mpim/m300690/miniconda3/envs/holaps/lib/python2.7/site-packages/xarray/backends/netCDF4_.pyc in _nc4_dtype(var)
122 else:
123 raise ValueError('unsupported dtype for netCDF4 variable: {}'
--> 124 .format(var.dtype))
125 return dtype
126
ValueError: unsupported dtype for netCDF4 variable: datetime64[ns]
```
### Version information
If this is useful:
```
In [230]: xr.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.15.final.0
python-bits: 64
OS: Linux
OS-release: 2.6.32-696.18.7.el6.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None
xarray: 0.10.7
pandas: 0.23.0
numpy: 1.11.3
scipy: 1.1.0
netCDF4: 1.4.0
h5netcdf: None
h5py: None
Nio: None
zarr: None
bottleneck: 1.2.1
cyordereddict: None
dask: None
distributed: None
matplotlib: 1.5.1
cartopy: None
seaborn: None
setuptools: 39.1.0
pip: 18.1
conda: None
pytest: None
IPython: 5.7.0
sphinx: None
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-436638944,https://api.github.com/repos/pydata/xarray/issues/2547,436638944,MDEyOklzc3VlQ29tbWVudDQzNjYzODk0NA==,6628425,2018-11-07T14:23:42Z,2018-11-07T14:23:42Z,MEMBER,"@tommylees112 I had a look at your dataset and noticed that the time coordinate was not encoded in a way that allows xarray to automatically decode the time values into datetimes. Specifically, the units attribute is not in the format of some unit of time (e.g. 'seconds') since a given reference date.
```
$ ncdump -h Rg_dummy.nc
netcdf Rg_dummy {
dimensions:
time = 1 ;
y = 200 ;
x = 200 ;
variables:
double time(time) ;
time:_FillValue = NaN ;
time:standard_name = ""time"" ;
time:units = ""day as %Y%m%d.%f"" ;
time:calendar = ""proleptic_gregorian"" ;
short Rg(time, y, x) ;
Rg:_FillValue = -1s ;
Rg:long_name = ""HWSD sub sum content"" ;
Rg:units = ""percent wt"" ;
Rg:valid_range = 97., 103. ;
double latitude(y, x) ;
latitude:_FillValue = -99999. ;
double longitude(y, x) ;
longitude:_FillValue = -99999. ;
// global attributes:
:Conventions = ""CF-1.0"" ;
:content = ""HARMONIZED WORLD SOIL DATABASE; first it was aggregated to one global file; then the missing areas were filled with interpolated data; then separate tiles were extracted"" ;
:scaling_factor = ""20"" ;
}
```
This is why `ds.time` is an array of floats when you load the file in. We could discuss how to address that, but depending on your broader needs here that might not be a major concern.
Regarding assigning a new value to the time coordinate, the following should work:
```python
ds['time'] = np.array([times[0]])
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-436606451,https://api.github.com/repos/pydata/xarray/issues/2547,436606451,MDEyOklzc3VlQ29tbWVudDQzNjYwNjQ1MQ==,21049064,2018-11-07T12:24:36Z,2018-11-07T12:25:02Z,NONE,"The ds.time[0] won't let me set it's value to a datetime. Instead it returns a float:
```python
In [19]: ds.time[0].item()
Out[19]: 10509.0
```
And none of the following work:
```python
# doesn't change the time value
ds.time[0].values = times[0]
# returns an error because I can't assign to a function call
ds.time[0].item() = times[0]
# returns ValueError: replacement data must match the Variable's shape
ds['time'].values = np.array(times[0])
```
Thanks for your help!","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-436422432,https://api.github.com/repos/pydata/xarray/issues/2547,436422432,MDEyOklzc3VlQ29tbWVudDQzNjQyMjQzMg==,5635139,2018-11-06T21:54:18Z,2018-11-06T21:54:18Z,MEMBER,Can you ensure `times[0].item() == ds.time[0].item()` prior to the reindex? Otherwise the reindex won't find the original index value and will fill with NaNs...,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-436400765,https://api.github.com/repos/pydata/xarray/issues/2547,436400765,MDEyOklzc3VlQ29tbWVudDQzNjQwMDc2NQ==,21049064,2018-11-06T20:40:20Z,2018-11-06T20:41:25Z,NONE,"Data:
[netcdf_files.zip](https://github.com/pydata/xarray/files/2554979/netcdf_files.zip)
Code below:
```python
import numpy as np
import pandas as pd
import xarray as xr
from shutil import copyfile
import os
data_dir = ""./""
filename = ""Rg_dummy.nc""
# get the datetime range
times = pd.date_range(""2000-01-01"", ""2000-12-31"", name=""time"")
var = ""Rg""
copyfile(filename, ""temp.nc"")
ds = xr.open_dataset(""temp.nc"")
print(""Temporary Data read to Python"")
# FORWARD FILL FROM THE ORIGINAL DATA to new timesteps
ds.reindex({""time"":times})
ds.ffill(""time"")
# ds.to_netcdf(filename, format=""NETCDF3_CLASSIC"")
# print(filename, ""Written!"")
# remove temporary file
os.remove(data_dir+""temp.nc"")
print(""Temporary Data Removed"")
del ds
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-436390574,https://api.github.com/repos/pydata/xarray/issues/2547,436390574,MDEyOklzc3VlQ29tbWVudDQzNjM5MDU3NA==,5635139,2018-11-06T20:06:54Z,2018-11-06T20:06:54Z,MEMBER,"Your original value needs to be in the time index in order to remain there after the reindex. Currently it looks like a float value:
```
Coordinates:
* time (time) float64 9.505e+17
```
If you have a repro example (link in issue template) it's easier to offer help on the whole issue ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-436383962,https://api.github.com/repos/pydata/xarray/issues/2547,436383962,MDEyOklzc3VlQ29tbWVudDQzNjM4Mzk2Mg==,21049064,2018-11-06T19:45:46Z,2018-11-06T19:50:00Z,NONE,"Thanks for your help! you definitely understood me correctly!
This doesn't seem to work as it fills my`Rg` arrays with nan values.
```python
ds = ds.reindex({""time"":pd.date_range(""2000-01-01"",""2000-12-31"")})
ds = ds.ffill(""time"")
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810
https://github.com/pydata/xarray/issues/2547#issuecomment-436336253,https://api.github.com/repos/pydata/xarray/issues/2547,436336253,MDEyOklzc3VlQ29tbWVudDQzNjMzNjI1Mw==,5635139,2018-11-06T17:23:28Z,2018-11-06T17:23:28Z,MEMBER,"IIUC, this is actually much easier - reindex on your enlarged `times` index, and then use `ffill`. No need for the `for` loop etc","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,377947810