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/pull/2073#issuecomment-383364259,https://api.github.com/repos/pydata/xarray/issues/2073,383364259,MDEyOklzc3VlQ29tbWVudDM4MzM2NDI1OQ==,16351486,2018-04-22T08:21:20Z,2018-04-22T08:21:20Z,NONE,"When I am a novice, I want to convert multidimensional data of ```pd.Dataframe``` into ```xr.Dataset```. The 'Multi-dimensional data' section is found from the 'Working with pandas' chapter. Then, I skipping the other to this section. this example showed that Xarray is not good at Multi-dimensional data until i discovered ```xr.Dataset.from_dataframe```


i know the mean of the leading paragraph, but it may be obstacles in this the 'Multi-dimensional data' section for novices.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,316540429
https://github.com/pydata/xarray/pull/2073#issuecomment-383350237,https://api.github.com/repos/pydata/xarray/issues/2073,383350237,MDEyOklzc3VlQ29tbWVudDM4MzM1MDIzNw==,16351486,2018-04-22T02:24:17Z,2018-04-22T02:58:49Z,NONE,"
No, these should not

An example
---
```python
# creat dataframe
index = pd.MultiIndex.from_arrays([['a', 'a', 'b'], [0, 1, 2]],
                                   names=['one', 'two'])
df = pd.DataFrame({'x': 1, 'y': 2}, index=index)
# display
df
```

<div>
<table border=""1"" class=""dataframe"">
  <thead>
    <tr style=""text-align: right;"">
      <th></th>
      <th></th>
      <th>x</th>
      <th>y</th>
    </tr>
    <tr>
      <th>one</th>
      <th>two</th>
      <th></th>
      <th></th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th rowspan=""2"" valign=""top"">a</th>
      <th>0</th>
      <td>1</td>
      <td>2</td>
    </tr>
    <tr>
      <th>1</th>
      <td>1</td>
      <td>2</td>
    </tr>
    <tr>
      <th>b</th>
      <th>2</th>
      <td>1</td>
      <td>2</td>
    </tr>
  </tbody>
</table>
</div>

---
```python
# use xr.Dataset transform
xr.Dataset(df)
```




    <xarray.Dataset>
    Dimensions:  (dim_0: 3)
    Coordinates:
      * dim_0    (dim_0) MultiIndex
      - one      (dim_0) object 'a' 'a' 'b'
      - two      (dim_0) int64 0 1 2
    Data variables:
        x        (dim_0) int64 1 1 1
        y        (dim_0) int64 2 2 2

---
```python
# use xr.Dataset.from_dataframe transform
xr.Dataset.from_dataframe(df)
```




    <xarray.Dataset>
    Dimensions:  (one: 2, two: 3)
    Coordinates:
      * one      (one) object 'a' 'b'
      * two      (two) int64 0 1 2
    Data variables:
        x        (one, two) float64 1.0 1.0 nan nan nan 1.0
        y        (one, two) float64 2.0 2.0 nan nan nan 2.0

---



From the above example,```xr.Dataset.from_dataframe``` is a better representation of the coordinate than ```xr.Dataset```from pandas.dataframe
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,316540429