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DS-1000 / 923 / I have a data which include dates in sorted order.

Problem

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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()
def solve(features_dataframe):
    # return the solution in this function
    # train_dataframe, test_dataframe = solve(features_dataframe)
    ### BEGIN SOLUTION

library

Sklearn

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Source and history

upstream_id / Original problem ID
923
task_id
6cce081d-84e1-5b5c-9910-a9e12c02bd10
task_key
default--test--923
task_revision_id
1
config / split
default / test

Official source

initial import