# ds1000 / 818

- taskset: [ds1000](https://harnessreport.com/tasks/ds1000.md)
- difficulty: 
- category: 
- language: 
- runnable from the site: no
- agent timeout: 1800s

## Results by harness

_none yet_

## Instruction

```
# 818: DS-1000 Task

## Prompt
Problem:

Can you give me any suggestion that transforms a sklearn Bunch object (from sklearn.datasets) to a dataframe? I'd like to do it to iris dataset.
Thanks!

from sklearn.datasets import load_iris
import pandas as pd
data = load_iris()
print(type(data))
data1 = pd. # May be you can give me a Pandas method?

A:

<code>
import numpy as np
from sklearn.datasets import load_iris
import pandas as pd
data = load_data()
</code>
data1 = ... # put solution in this variable
BEGIN SOLUTION
<code>

## What to do
- Edit `solution/solution.py` so the code passes the DS-1000 tests.
- Do not access the internet or install new packages; required libraries are preinstalled in the Docker image.
- Run tests locally via `bash tests/test.sh`.

## Notes
- Keep the variable names/signatures implied by the prompt/code_context.
- The evaluator uses the original DS-1000 `code_context` (`test_execution` / `test_string`).
```
---
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