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Title:
TST: add validation checks on levels keyword from pd.concat · Issue #46653 · pandas-dev/pandas
Description:
Pandas version checks I have checked that this issue has not already been reported. I have confirmed this bug exists on the latest version of pandas. I have confirmed this bug exists on the main branch of pandas. Reproducible Example >>>...
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Keywords {🔍}
pandas, levels, pddataframea, issue, sign, checks, bug, indexx, indexy, pdconcatdf, levelsx, keys, projects, tst, add, validation, keyword, pdconcat, closed, gyhhaha, added, navigation, pull, requests, actions, security, description, version, confirmed, exists, keysx, raise, infering, valueerror, triage, reviewed, team, member, reshaping, concat, mergejoin, stackunstack, explode, error, reporting, incorrect, improved, errors, jreback, milestone,
Topics {✒️}
pandas reshaping concat add validation checks personal information tst comment metadata assignees 1 issue description mentions infering levels latest version projects milestone 1 bug exists type projects triage issue explode type pandas main branch level values tst stack/unstack improved errors 5 closed 100% complete relationships issue infering keys merge/join levels keyword levels duplicated levels supported github concat [df1 'y' pd join levels=[[ levels df2] sign keys=[ keys skip jump checked reported confirmed reproducible dataframe index=[ raise unreasonable doc valueerror
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DiscussionForumPosting:
context:https://schema.org
headline:TST: add validation checks on levels keyword from pd.concat
articleBody:### Pandas version checks
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the main branch of pandas.
### Reproducible Example
```python
>>> df1 = pd.DataFrame({"A": [1]}, index=["x"])
>>> df2 = pd.DataFrame({"A": [1]}, index=["y"])
>>> pd.concat([df1, df2], keys=["x", "y"], levels=[["x", "y", "y"]])
A
x x 1
y y 1
```python
>>> df1 = pd.DataFrame({"A": [1]}, index=["x"])
>>> df2 = pd.DataFrame({"A": [1]}, index=["y"])
>>> pd.concat([df1, df2], levels=[["x", "y"]])
A
x 1
y 1
```
### Issue Description
First, we should raise when levels duplicated. Second, when levels specified and keys not given, then we should also raise since this is unreasonable. (DOC only mentions infering levels from keys but not infering keys from levels)
### Expected Behavior
```python
>>> df1 = pd.DataFrame({"A": [1]}, index=["x"])
>>> df2 = pd.DataFrame({"A": [1]}, index=["y"])
>>> pd.concat([df1, df2], keys=["x", "y"], levels=[["x", "y", "y"]])
ValueError: Level values not unique: ['x', 'y', 'y']
```
```python
>>> df1 = pd.DataFrame({"A": [1]}, index=["x"])
>>> df2 = pd.DataFrame({"A": [1]}, index=["y"])
>>> pd.concat([df1, df2], levels=[["x", "y"]])
ValueError: levels supported only when keys not None
```
### Installed Versions
<details>
1.4.1
</details>
author:
url:https://github.com/GYHHAHA
type:Person
name:GYHHAHA
datePublished:2022-04-06T04:12:45.000Z
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url:https://github.com/46653/pandas/issues/46653
context:https://schema.org
headline:TST: add validation checks on levels keyword from pd.concat
articleBody:### Pandas version checks
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the main branch of pandas.
### Reproducible Example
```python
>>> df1 = pd.DataFrame({"A": [1]}, index=["x"])
>>> df2 = pd.DataFrame({"A": [1]}, index=["y"])
>>> pd.concat([df1, df2], keys=["x", "y"], levels=[["x", "y", "y"]])
A
x x 1
y y 1
```python
>>> df1 = pd.DataFrame({"A": [1]}, index=["x"])
>>> df2 = pd.DataFrame({"A": [1]}, index=["y"])
>>> pd.concat([df1, df2], levels=[["x", "y"]])
A
x 1
y 1
```
### Issue Description
First, we should raise when levels duplicated. Second, when levels specified and keys not given, then we should also raise since this is unreasonable. (DOC only mentions infering levels from keys but not infering keys from levels)
### Expected Behavior
```python
>>> df1 = pd.DataFrame({"A": [1]}, index=["x"])
>>> df2 = pd.DataFrame({"A": [1]}, index=["y"])
>>> pd.concat([df1, df2], keys=["x", "y"], levels=[["x", "y", "y"]])
ValueError: Level values not unique: ['x', 'y', 'y']
```
```python
>>> df1 = pd.DataFrame({"A": [1]}, index=["x"])
>>> df2 = pd.DataFrame({"A": [1]}, index=["y"])
>>> pd.concat([df1, df2], levels=[["x", "y"]])
ValueError: levels supported only when keys not None
```
### Installed Versions
<details>
1.4.1
</details>
author:
url:https://github.com/GYHHAHA
type:Person
name:GYHHAHA
datePublished:2022-04-06T04:12:45.000Z
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