itholic opened a new pull request #34931:
URL: https://github.com/apache/spark/pull/34931
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### What changes were proposed in this pull request?
This PR proposes to support string and timestamp type columns for
`(Series|DataFrame).describe()` API.
Now `(Series|DataFrame).describe()` API only supports the numeric type
column, so we should support other types.
The initial issue is reported from Koalas user in legacy Koalas repo
(https://github.com/databricks/koalas/issues/1888).
### Why are the changes needed?
We should match the latest pandas' behavior as much as possible.
### Does this PR introduce _any_ user-facing change?
Users can apply the `(Series|DataFrame).describe()` API to the string and
timestamp type columns which is unavailable before this fix.
**Before**
```python
>>> df = ps.DataFrame({'a': ["a", "b", "c"]})
>>> df.describe()
Traceback (most recent call last):
...
ValueError: Cannot describe a DataFrame without columns
```
**After**
```python
>>> df = ps.DataFrame({'a': ["a", "b", "c"]})
>>> df.describe()
a
count 3
unique 3
top a
freq 1
```
### How was this patch tested?
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Added unittests.
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