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/2139#issuecomment-708594913,https://api.github.com/repos/pydata/xarray/issues/2139,708594913,MDEyOklzc3VlQ29tbWVudDcwODU5NDkxMw==,145117,2020-10-14T18:52:38Z,2020-10-14T18:52:38Z,CONTRIBUTOR,"The issue is that if you pass in `names = ['a','b','c']` to `pd.read_csv` and there are more columns than names, it takes all the columns without a name and creates a multi-index. That was a bug in my code that I had more columns than names, didn't want a multi-index, and didn't make use of `usecols`.

This multi-index came from a small 12 MB file - 5000 rows and 40 variables. When I then did `df.to_xarray()` it filled up my RAM. If I ran the code I provided above, it worked.

Now that I've figured all this out, I don't think that any bugs exist in `xarray` or `pandas`, just my code. As usual :). But if the fact that I can fill ram with `df.to_xarray()` but not with the 3 lines shown above sounds like an issue you want to explore, I'm happy to provide an MWE on a new ticket and tag you there. Let me know...","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,323703742
https://github.com/pydata/xarray/issues/2139#issuecomment-708513119,https://api.github.com/repos/pydata/xarray/issues/2139,708513119,MDEyOklzc3VlQ29tbWVudDcwODUxMzExOQ==,145117,2020-10-14T16:23:36Z,2020-10-14T16:23:36Z,CONTRIBUTOR,"@max-sixty Sorry for posting this here. This memory blow-up was a byproduct of another bug that it took me a few more hours to track down. This other bug is in Pandas, not xarray.","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 1, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,323703742
https://github.com/pydata/xarray/issues/2139#issuecomment-708339519,https://api.github.com/repos/pydata/xarray/issues/2139,708339519,MDEyOklzc3VlQ29tbWVudDcwODMzOTUxOQ==,145117,2020-10-14T11:25:03Z,2020-10-14T11:25:03Z,CONTRIBUTOR,"Late reply, but if anyone else finds this issue, I was filling memory with: `ds = df.to_xarray()`, but if I build the dataset more manually, I have no memory issues:

```python
ds = xr.Dataset({df.columns[0]: xr.DataArray(data=df[df.columns[0]], dims=['index'], coords={'index':df.index})})
for c in df.columns[1:]:
    ds[c] = (('index'), df[c])
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,323703742