# ds1000 / 916

- 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

```
# 916: DS-1000 Task

## Prompt
Problem:

Are you able to train a DecisionTreeClassifier with string data?

When I try to use String data I get a ValueError: could not converter string to float

X = [['asdf', '1'], ['asdf', '0']]

clf = DecisionTreeClassifier()

clf.fit(X, ['2', '3'])

So how can I use this String data to train my model?

Note I need X to remain a list or numpy array.

A:

corrected, runnable code
<code>
import numpy as np
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
X = [['asdf', '1'], ['asdf', '0']]
clf = DecisionTreeClassifier()
</code>
solve this question with example variable `new_X`
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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