# ds1000 / 822

- 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

```
# 822: DS-1000 Task

## Prompt
Problem:

I'd like to do some operations to my df. And there is an example below.
df

Col1   Col2         Col3
 C      33     [Apple, Orange, Banana]
 A      2.5    [Apple, Grape]
 B      42     [Banana]
after the operations, the df is converted into

df

Col1   Col2   Apple   Orange   Banana   Grape
 C      33     1        1        1       0
 A      2.5    1        0        0       1
 B      42     0        0        1       0
Generally, I want this pandas column which consisting of a list of String names broken down into as many columns as the unique names.
Maybe it's like one-hot-encode them (note that value 1 representing a given name existing in a row and then 0 is absence).
Could any one give me any suggestion of pandas or sklearn methods? thanks!

A:

<code>
import pandas as pd
import numpy as np
import sklearn
df = load_data()
</code>
df_out = ... # 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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