# monotonic1

Load the Yandex dataset with monotonic constraints. This dataset contains categorical features.

This dataset can be used for regression.

It contains several numerical and categorical features.

The contents of columns depends on the name or on the pattern of the name of the corresponding column:

• Target (the first column) — Target values.

• Cat* — Categorical features.

• Num* — Numerical features.

• MonotonicNeg* — Numerical features, for which monotonic constraints must hold.

If values of such features decrease, then the prediction value must not decrease. Thus, if there are two objects $x_{1}$ and $x_{2}$ with all features being equal except for a monotonic negative feature M, such that $x_{1}[M] > x_{2}[M]$, then the following inequality must be met for predictions:

$f(x_{1}) \leq f(x_{2})$

## Method call format

monotonic1()


## Type of return value

A two pandas.DataFrame tuple (for train and validation datasets).

## Usage examples

from catboost.datasets import monotonic1
monotonic1_train, monotonic1_test = monotonic1()


     Target      Num0                              Cat0                              Cat1                              Cat2                              Cat3  ... MonotonicNeg10     Num24     Num25     Num26     Num27     Num28