# ds1000 / 921

- 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

```
# 921: DS-1000 Task

## Prompt
Problem:

I have a data which include dates in sorted order.

I would like to split the given data to train and test set. However, I must to split the data in a way that the test have to be newer than the train set.

Please look at the given example:

Let's assume that we have data by dates:

1, 2, 3, ..., n.

The numbers from 1 to n represents the days.

I would like to split it to 20% from the data to be train set and 80% of the data to be test set.

Good results:

1) train set = 1, 2, 3, ..., 20

   test set = 21, ..., 100


2) train set = 101, 102, ... 120

    test set = 121, ... 200
My code:

train_size = 0.2
train_dataframe, test_dataframe = cross_validation.train_test_split(features_dataframe, train_size=train_size)

train_dataframe = train_dataframe.sort(["date"])
test_dataframe = test_dataframe.sort(["date"])
Does not work for me!

Any suggestions?

A:

<code>
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
features_dataframe = load_data()
</code>
train_dataframe, test_dataframe = ... # put solution in these variables
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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