diff --git a/CHANGELOG.md b/CHANGELOG.md
index cbe40823b..485cc4c96 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -7,10 +7,20 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 ### Added
+- RelevanceTable returns rank ([#268](https://github.com/tinkoff-ai/etna-ts/pull/268/))
+
+### Changed
+
+### Fixed
+
+## [1.3.1] - 2021-11-12
+### Changed
+- Delete restriction on version of pandas ([#274](https://github.com/tinkoff-ai/etna-ts/pull/274))
+
+## [1.3.0] - 2021-11-12
+### Added
 - Backtest cli ([#223](https://github.com/tinkoff-ai/etna-ts/pull/223), [#259](https://github.com/tinkoff-ai/etna-ts/pull/259))
 - TreeFeatureSelectionTransform ([#229](https://github.com/tinkoff-ai/etna-ts/pull/229))
-- MRMRFeatureSelectionTransform ([#251](https://github.com/tinkoff-ai/etna-ts/pull/251))
-- Feature relevance table calculation ([#227](https://github.com/tinkoff-ai/etna-ts/pull/227), [#249](https://github.com/tinkoff-ai/etna-ts/pull/249))
 - Feature relevance table calculation using tsfresh ([#227](https://github.com/tinkoff-ai/etna-ts/pull/227), [#249](https://github.com/tinkoff-ai/etna-ts/pull/249))
 - Method to_flatten to TSDataset ([#241](https://github.com/tinkoff-ai/etna-ts/pull/241)
 - Out_column parameter to not inplace transforms([#211](https://github.com/tinkoff-ai/etna-ts/pull/211))
diff --git a/etna/analysis/feature_relevance/relevance.py b/etna/analysis/feature_relevance/relevance.py
index eceaa9421..61844a39a 100644
--- a/etna/analysis/feature_relevance/relevance.py
+++ b/etna/analysis/feature_relevance/relevance.py
@@ -2,6 +2,7 @@
 from abc import abstractmethod
 
 import pandas as pd
+import scipy.stats
 
 from etna.analysis.feature_relevance.relevance_table import get_model_relevance_table
 from etna.analysis.feature_relevance.relevance_table import get_statistics_relevance_table
@@ -21,8 +22,15 @@ def __init__(self, greater_is_better: bool):
         """
         self.greater_is_better = greater_is_better
 
+    def _get_ranks(self, table: pd.DataFrame) -> pd.DataFrame:
+        """Compute rank relevance table from relevance table."""
+        if self.greater_is_better:
+            table *= -1
+        rank_table = pd.DataFrame(scipy.stats.rankdata(table, axis=1), columns=table.columns, index=table.index)
+        return rank_table.astype(int)
+
     @abstractmethod
-    def __call__(self, df: pd.DataFrame, df_exog: pd.DataFrame, **kwargs) -> pd.DataFrame:
+    def __call__(self, df: pd.DataFrame, df_exog: pd.DataFrame, return_ranks: bool = False, **kwargs) -> pd.DataFrame:
         """Compute relevance table.
         For each series in df compute relevance of corresponding series in df_exog.
 
@@ -32,6 +40,8 @@ def __call__(self, df: pd.DataFrame, df_exog: pd.DataFrame, **kwargs) -> pd.Data
             dataframe with series that will be used as target
         df_exog:
             dataframe with series to compute relevance for df
+        return_ranks:
+            if False return relevance values else return ranks of relevance values
 
         Returns
         -------
@@ -47,9 +57,11 @@ class StatisticsRelevanceTable(RelevanceTable):
     def __init__(self):
         super().__init__(greater_is_better=False)
 
-    def __call__(self, df: pd.DataFrame, df_exog: pd.DataFrame, **kwargs) -> pd.DataFrame:
+    def __call__(self, df: pd.DataFrame, df_exog: pd.DataFrame, return_ranks: bool = False, **kwargs) -> pd.DataFrame:
         """Compute feature relevance table with etna.analysis.get_statistics_relevance_table method."""
         table = get_statistics_relevance_table(df=df, df_exog=df_exog)
+        if return_ranks:
+            return self._get_ranks(table)
         return table
 
 
@@ -59,7 +71,9 @@ class ModelRelevanceTable(RelevanceTable):
     def __init__(self):
         super().__init__(greater_is_better=True)
 
-    def __call__(self, df: pd.DataFrame, df_exog: pd.DataFrame, **kwargs) -> pd.DataFrame:
+    def __call__(self, df: pd.DataFrame, df_exog: pd.DataFrame, return_ranks: bool = False, **kwargs) -> pd.DataFrame:
         """Compute feature relevance table with etna.analysis.get_model_relevance_table method."""
         table = get_model_relevance_table(df=df, df_exog=df_exog, **kwargs)
+        if return_ranks:
+            return self._get_ranks(table)
         return table
diff --git a/etna/transforms/__init__.py b/etna/transforms/__init__.py
index bc8fd262c..40e2f4952 100644
--- a/etna/transforms/__init__.py
+++ b/etna/transforms/__init__.py
@@ -6,7 +6,6 @@
 from etna.transforms.datetime_flags import TimeFlagsTransform
 from etna.transforms.detrend import LinearTrendTransform
 from etna.transforms.detrend import TheilSenTrendTransform
-from etna.transforms.feature_importance import MRMRFeatureSelectionTransform
 from etna.transforms.feature_importance import TreeFeatureSelectionTransform
 from etna.transforms.filter import FilterFeaturesTransform
 from etna.transforms.imputation import TimeSeriesImputerTransform
diff --git a/etna/transforms/feature_importance.py b/etna/transforms/feature_importance.py
index bf1b55173..e05e164d4 100644
--- a/etna/transforms/feature_importance.py
+++ b/etna/transforms/feature_importance.py
@@ -8,16 +8,12 @@
 import numpy as np
 import pandas as pd
 from catboost import CatBoostRegressor
-from mrmr import mrmr_classif
 from sklearn.ensemble import ExtraTreesRegressor
 from sklearn.ensemble import GradientBoostingRegressor
 from sklearn.ensemble import RandomForestRegressor
 from sklearn.tree import DecisionTreeRegressor
 from sklearn.tree import ExtraTreeRegressor
 
-from etna.analysis import RelevanceTable
-from etna.clustering import EuclideanClustering
-from etna.clustering import HierarchicalClustering
 from etna.datasets import TSDataset
 from etna.transforms.base import Transform
 
@@ -134,108 +130,3 @@ def transform(self, df: pd.DataFrame) -> pd.DataFrame:
         )
         result = result.loc[:, pd.IndexSlice[:, selected_columns]]
         return result
-
-
-class MRMRFeatureSelectionTransform(Transform):
-    """Transform that selects regressors according to mRMR variable selection method."""
-
-    def __init__(
-        self,
-        relevance_method: RelevanceTable,
-        top_k: int,
-        clustering_method: HierarchicalClustering = EuclideanClustering(),
-        n_clusters: int = 10,
-        linkage: str = "average",
-        **relevance_params,
-    ):
-        """
-        Init MRMRFeatureSelectionTransform.
-
-        Parameters
-        ----------
-        relevance_method:
-            method to calculate relevance table
-        top_k:
-            num of regressors to select; if there are not enough regressors, then all will be selected
-        clustering_method:
-            method of time series clustering
-        n_clusters:
-            number of clusters
-        linkage:
-            rule for distance computation for new clusters, allowed "ward", "single", "average", "maximum", "complete"
-        """
-        if not isinstance(top_k, int) or top_k < 0:
-            raise ValueError("Parameter top_k should be positive integer")
-
-        if not isinstance(n_clusters, int) or n_clusters < 2:
-            raise ValueError("Parameter n_clusters should be integer and greater than 1")
-
-        self.relevance_method = relevance_method
-        self.clustering = clustering_method
-        self.n_clusters = n_clusters
-        self.linkage = linkage
-        self.top_k = top_k
-        self.relevance_params = relevance_params
-        self.selected_regressors: Optional[List[str]] = None
-
-    @staticmethod
-    def _get_regressors(df: pd.DataFrame) -> List[str]:
-        """Get list of regressors in the dataframe."""
-        result = set()
-        for column in df.columns.get_level_values("feature"):
-            if column.startswith("regressor_"):
-                result.add(column)
-        return sorted(list(result))
-
-    def fit(self, df: pd.DataFrame) -> "MRMRFeatureSelectionTransform":
-        """
-        Fit the method and remember features to select.
-
-        Parameters
-        ----------
-        df:
-            dataframe with all segments data
-
-        Returns
-        -------
-        result: MRMRFeatureSelectionTransform
-            instance after fitting
-        """
-        if len(self._get_regressors(df)) <= self.n_clusters:
-            raise ValueError("The number of clusters must be strictly less than the number of regressors")
-
-        ts = TSDataset(df=df, freq=pd.infer_freq(df.index))
-        self.clustering.build_distance_matrix(ts=ts)
-        self.clustering.build_clustering_algo(n_clusters=self.n_clusters, linkage=self.linkage)
-        s2c = self.clustering.fit_predict()
-        relevance_table = self.relevance_method(ts[:, :, "target"], ts[:, :, ts.regressors], **self.relevance_params)
-        y = np.empty(len(relevance_table))
-        for k, cluster in enumerate(relevance_table.index):
-            y[k] = s2c[cluster]
-        self.selected_regressors = mrmr_classif(relevance_table, y, K=self.top_k)
-        return self
-
-    def transform(self, df: pd.DataFrame) -> pd.DataFrame:
-        """
-        Select top_k regressors.
-
-        Parameters
-        ----------
-        df:
-            dataframe with all segments data
-
-        Returns
-        -------
-        result: pd.DataFrame
-            Dataframe with with only selected regressors
-        """
-        result = df.copy()
-        selected_columns = sorted(
-            [
-                column
-                for column in df.columns.get_level_values("feature").unique()
-                if not column.startswith("regressor_") or column in self.selected_regressors
-            ]
-        )
-        result = result.loc[:, pd.IndexSlice[:, selected_columns]]
-        return result
diff --git a/poetry.lock b/poetry.lock
index 61668e67a..4765ada9e 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,10 +1,10 @@
 [[package]]
 name = "absl-py"
-version = "0.15.0"
+version = "1.0.0"
 description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
 category = "main"
 optional = true
-python-versions = "*"
+python-versions = ">=3.6"
 
 [package.dependencies]
 six = "*"
@@ -22,23 +22,37 @@ contextvars = {version = "2.4", markers = "python_version < \"3.7\""}
 
 [[package]]
 name = "aiohttp"
-version = "3.7.4.post0"
+version = "3.8.0"
 description = "Async http client/server framework (asyncio)"
 category = "main"
 optional = true
 python-versions = ">=3.6"
 
 [package.dependencies]
-async-timeout = ">=3.0,<4.0"
+aiosignal = ">=1.1.2"
+async-timeout = ">=4.0.0a3,<5.0"
+asynctest = {version = "0.13.0", markers = "python_version < \"3.8\""}
 attrs = ">=17.3.0"
-chardet = ">=2.0,<5.0"
+charset-normalizer = ">=2.0,<3.0"
+frozenlist = ">=1.1.1"
 idna-ssl = {version = ">=1.0", markers = "python_version < \"3.7\""}
 multidict = ">=4.5,<7.0"
-typing-extensions = ">=3.6.5"
+typing-extensions = {version = ">=3.7.4", markers = "python_version < \"3.8\""}
 yarl = ">=1.0,<2.0"
 
 [package.extras]
-speedups = ["aiodns", "brotlipy", "cchardet"]
+speedups = ["aiodns", "brotli", "cchardet"]
+
+[[package]]
+name = "aiosignal"
+version = "1.2.0"
+description = "aiosignal: a list of registered asynchronous callbacks"
+category = "main"
+optional = true
+python-versions = ">=3.6"
+
+[package.dependencies]
+frozenlist = ">=1.1.0"
 
 [[package]]
 name = "alabaster"
@@ -50,7 +64,7 @@ python-versions = "*"
 
 [[package]]
 name = "alembic"
-version = "1.7.4"
+version = "1.7.5"
 description = "A database migration tool for SQLAlchemy."
 category = "main"
 optional = true
@@ -107,11 +121,22 @@ python-versions = ">=3.5"
 
 [[package]]
 name = "async-timeout"
-version = "3.0.1"
+version = "4.0.1"
 description = "Timeout context manager for asyncio programs"
 category = "main"
 optional = true
-python-versions = ">=3.5.3"
+python-versions = ">=3.6"
+
+[package.dependencies]
+typing-extensions = ">=3.6.5"
+
+[[package]]
+name = "asynctest"
+version = "0.13.0"
+description = "Enhance the standard unittest package with features for testing asyncio libraries"
+category = "main"
+optional = true
+python-versions = ">=3.5"
 
 [[package]]
 name = "atomicwrites"
@@ -261,14 +286,6 @@ python-versions = "*"
 [package.dependencies]
 pycparser = "*"
 
-[[package]]
-name = "chardet"
-version = "4.0.0"
-description = "Universal encoding detector for Python 2 and 3"
-category = "main"
-optional = true
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
-
 [[package]]
 name = "charset-normalizer"
 version = "2.0.7"
@@ -322,7 +339,7 @@ numpy = "*"
 
 [[package]]
 name = "cmd2"
-version = "2.2.0"
+version = "2.3.0"
 description = "cmd2 - quickly build feature-rich and user-friendly interactive command line applications in Python"
 category = "main"
 optional = true
@@ -330,7 +347,6 @@ python-versions = ">=3.6"
 
 [package.dependencies]
 attrs = ">=16.3.0"
-colorama = ">=0.3.7"
 importlib-metadata = {version = ">=1.6.0", markers = "python_version < \"3.8\""}
 pyperclip = ">=1.6"
 pyreadline = {version = "*", markers = "sys_platform == \"win32\" and python_version < \"3.8\""}
@@ -383,7 +399,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 
 [[package]]
 name = "colorlog"
-version = "6.5.0"
+version = "6.6.0"
 description = "Add colours to the output of Python's logging module."
 category = "main"
 optional = true
@@ -397,15 +413,15 @@ development = ["black", "flake8", "mypy", "pytest", "types-colorama"]
 
 [[package]]
 name = "configparser"
-version = "5.0.2"
+version = "5.1.0"
 description = "Updated configparser from Python 3.8 for Python 2.6+."
 category = "main"
 optional = true
 python-versions = ">=3.6"
 
 [package.extras]
-docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"]
-testing = ["pytest (>=4.6)", "pytest-checkdocs (>=1.2.3)", "pytest-flake8", "pytest-cov", "pytest-enabler", "pytest-black (>=0.3.7)", "pytest-mypy"]
+docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)", "jaraco.tidelift (>=1.4)"]
+testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "pytest-black (>=0.3.7)", "pytest-mypy"]
 
 [[package]]
 name = "contextvars"
@@ -447,14 +463,11 @@ toml = ["toml"]
 
 [[package]]
 name = "cycler"
-version = "0.10.0"
+version = "0.11.0"
 description = "Composable style cycles"
 category = "main"
 optional = false
-python-versions = "*"
-
-[package.dependencies]
-six = "*"
+python-versions = ">=3.6"
 
 [[package]]
 name = "cython"
@@ -571,9 +584,17 @@ python-versions = "*"
 [package.dependencies]
 flake8 = "*"
 
+[[package]]
+name = "frozenlist"
+version = "1.2.0"
+description = "A list-like structure which implements collections.abc.MutableSequence"
+category = "main"
+optional = true
+python-versions = ">=3.6"
+
 [[package]]
 name = "fsspec"
-version = "2021.10.1"
+version = "2021.11.0"
 description = "File-system specification"
 category = "main"
 optional = true
@@ -638,7 +659,7 @@ typing-extensions = {version = ">=3.7.4.3", markers = "python_version < \"3.10\"
 
 [[package]]
 name = "google-auth"
-version = "2.3.2"
+version = "2.3.3"
 description = "Google Authentication Library"
 category = "main"
 optional = true
@@ -672,7 +693,7 @@ tool = ["click (>=6.0.0)"]
 
 [[package]]
 name = "graphviz"
-version = "0.17"
+version = "0.18"
 description = "Simple Python interface for Graphviz"
 category = "main"
 optional = false
@@ -681,7 +702,7 @@ python-versions = ">=3.6"
 [package.extras]
 dev = ["tox (>=3)", "flake8", "pep8-naming", "wheel", "twine"]
 docs = ["sphinx (>=1.8)", "sphinx-autodoc-typehints", "sphinx-rtd-theme"]
-test = ["mock (>=3)", "pytest (>=5.2)", "pytest-mock (>=2)", "pytest-cov"]
+test = ["pytest (>=6)", "pytest-mock (>=2)", "mock (>=3)", "pytest-cov"]
 
 [[package]]
 name = "greenlet"
@@ -759,7 +780,7 @@ idna = ">=2.0"
 
 [[package]]
 name = "imagesize"
-version = "1.2.0"
+version = "1.3.0"
 description = "Getting image size from png/jpeg/jpeg2000/gif file"
 category = "main"
 optional = true
@@ -781,7 +802,7 @@ test = ["flake8 (>=3.8.4,<3.9.0)", "pycodestyle (>=2.6.0,<2.7.0)", "mypy (>=0.91
 
 [[package]]
 name = "importlib-metadata"
-version = "4.8.1"
+version = "4.8.2"
 description = "Read metadata from Python packages"
 category = "main"
 optional = false
@@ -794,11 +815,11 @@ zipp = ">=0.5"
 [package.extras]
 docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"]
 perf = ["ipython"]
-testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "packaging", "pep517", "pyfakefs", "flufl.flake8", "pytest-perf (>=0.9.2)", "pytest-black (>=0.3.7)", "pytest-mypy", "importlib-resources (>=1.3)"]
+testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "packaging", "pep517", "pyfakefs", "flufl.flake8", "pytest-perf (>=0.9.2)", "pytest-black (>=0.3.7)", "pytest-mypy", "importlib-resources (>=1.3)"]
 
 [[package]]
 name = "importlib-resources"
-version = "5.3.0"
+version = "5.4.0"
 description = "Read resources from Python packages"
 category = "main"
 optional = true
@@ -899,7 +920,7 @@ test = ["pytest (>=3.6.0)", "pytest-cov", "mock"]
 
 [[package]]
 name = "isort"
-version = "5.9.3"
+version = "5.10.1"
 description = "A Python utility / library to sort Python imports."
 category = "main"
 optional = true
@@ -928,7 +949,7 @@ testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<6.0.0)"]
 
 [[package]]
 name = "jinja2"
-version = "3.0.2"
+version = "3.0.3"
 description = "A very fast and expressive template engine."
 category = "main"
 optional = true
@@ -1214,7 +1235,7 @@ name = "mrmr"
 version = "0.1"
 description = ""
 category = "main"
-optional = true
+optional = false
 python-versions = "*"
 develop = false
 
@@ -1224,13 +1245,12 @@ joblib = "*"
 numpy = ">=1.18.1"
 pandas = ">=1.0.3"
 sklearn = "*"
-tqdm = "*"
 
 [package.source]
 type = "git"
 url = "https://github.com/smazzanti/mrmr.git"
-reference = "main"
-resolved_reference = "74987fc32319edb838a2f864b16c509dc351ea9a"
+reference = "96ad224"
+resolved_reference = "96ad224f4668737593c69920c8d0d668ac0a31ab"
 
 [[package]]
 name = "multidict"
@@ -1290,7 +1310,7 @@ testing = ["beautifulsoup4", "coverage", "docutils (>=0.17.0,<0.18.0)", "pytest
 
 [[package]]
 name = "nbclient"
-version = "0.5.4"
+version = "0.5.8"
 description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
 category = "main"
 optional = true
@@ -1304,9 +1324,9 @@ nest-asyncio = "*"
 traitlets = ">=4.2"
 
 [package.extras]
-dev = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "bumpversion", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"]
+dev = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"]
 sphinx = ["Sphinx (>=1.7)", "sphinx-book-theme", "mock", "moto", "myst-parser"]
-test = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "bumpversion", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"]
+test = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"]
 
 [[package]]
 name = "nbconvert"
@@ -1504,14 +1524,14 @@ tests = ["fakeredis", "pytest"]
 
 [[package]]
 name = "packaging"
-version = "21.0"
+version = "21.2"
 description = "Core utilities for Python packages"
 category = "main"
 optional = false
 python-versions = ">=3.6"
 
 [package.dependencies]
-pyparsing = ">=2.0.2"
+pyparsing = ">=2.0.2,<3"
 
 [[package]]
 name = "pandas"
@@ -1582,7 +1602,7 @@ test = ["pytest", "pytest-cov", "scipy"]
 
 [[package]]
 name = "pbr"
-version = "5.6.0"
+version = "5.7.0"
 description = "Python Build Reasonableness"
 category = "main"
 optional = true
@@ -1668,7 +1688,7 @@ testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
 name = "prettytable"
-version = "2.2.1"
+version = "2.4.0"
 description = "A simple Python library for easily displaying tabular data in a visually appealing ASCII table format"
 category = "main"
 optional = true
@@ -1679,11 +1699,11 @@ importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 wcwidth = "*"
 
 [package.extras]
-tests = ["pytest", "pytest-cov"]
+tests = ["pytest", "pytest-cov", "pytest-lazy-fixture"]
 
 [[package]]
 name = "prometheus-client"
-version = "0.11.0"
+version = "0.12.0"
 description = "Python client for the Prometheus monitoring system."
 category = "main"
 optional = true
@@ -1708,7 +1728,7 @@ test = ["pytest (>=2.7.3)", "pytest-cov", "coveralls", "futures", "pytest-benchm
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.21"
+version = "3.0.22"
 description = "Library for building powerful interactive command lines in Python"
 category = "main"
 optional = true
@@ -1741,7 +1761,7 @@ tqdm = ">=4.36.1"
 
 [[package]]
 name = "protobuf"
-version = "3.19.0"
+version = "3.19.1"
 description = "Protocol Buffers"
 category = "main"
 optional = true
@@ -1768,11 +1788,11 @@ python-versions = "*"
 
 [[package]]
 name = "py"
-version = "1.10.0"
+version = "1.11.0"
 description = "library with cross-python path, ini-parsing, io, code, log facilities"
 category = "main"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 
 [[package]]
 name = "pyasn1"
@@ -1803,7 +1823,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 
 [[package]]
 name = "pycparser"
-version = "2.20"
+version = "2.21"
 description = "C parser in Python"
 category = "main"
 optional = true
@@ -1857,14 +1877,11 @@ python-versions = "*"
 
 [[package]]
 name = "pyparsing"
-version = "3.0.3"
+version = "2.4.7"
 description = "Python parsing module"
 category = "main"
 optional = false
-python-versions = ">=3.6"
-
-[package.extras]
-diagrams = ["jinja2", "railroad-diagrams"]
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
 
 [[package]]
 name = "pyperclip"
@@ -1982,7 +1999,7 @@ github-actions = ["pytest-github-actions-annotate-failures"]
 
 [[package]]
 name = "pytorch-lightning"
-version = "1.4.9"
+version = "1.5.1"
 description = "PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate."
 category = "main"
 optional = true
@@ -1997,19 +2014,19 @@ pyDeprecate = "0.3.1"
 PyYAML = ">=5.1"
 tensorboard = ">=2.2.0"
 torch = ">=1.6"
-torchmetrics = ">=0.4.0"
+torchmetrics = ">=0.4.1"
 tqdm = ">=4.41.0"
 typing-extensions = "*"
 
 [package.extras]
-all = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "omegaconf (>=2.0.1)", "torchtext (>=0.7)", "onnx (>=1.7.0)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)", "jsonargparse[signatures] (>=3.17.0)", "gcsfs (>=2021.5.0)", "neptune-client (>=0.4.109)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)", "coverage (>5.2.0)", "codecov (>=2.1)", "pytest (>=6.0)", "check-manifest", "twine (==3.2)", "mypy (>=0.900)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "scikit-learn (>0.22.1)", "scikit-image (>0.17.1)", "nltk (>=3.3)", "pandas", "torchvision (>=0.7)", "gym (>=0.17.0)", "ipython"]
-cpu = ["matplotlib (>3.1)", "omegaconf (>=2.0.1)", "torchtext (>=0.7)", "onnx (>=1.7.0)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)", "jsonargparse[signatures] (>=3.17.0)", "gcsfs (>=2021.5.0)", "neptune-client (>=0.4.109)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)", "coverage (>5.2.0)", "codecov (>=2.1)", "pytest (>=6.0)", "check-manifest", "twine (==3.2)", "mypy (>=0.900)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "scikit-learn (>0.22.1)", "scikit-image (>0.17.1)", "nltk (>=3.3)", "pandas", "torchvision (>=0.7)", "gym (>=0.17.0)", "ipython"]
-cpu-extra = ["matplotlib (>3.1)", "omegaconf (>=2.0.1)", "torchtext (>=0.7)", "onnx (>=1.7.0)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)", "jsonargparse[signatures] (>=3.17.0)", "gcsfs (>=2021.5.0)"]
-dev = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "omegaconf (>=2.0.1)", "torchtext (>=0.7)", "onnx (>=1.7.0)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)", "jsonargparse[signatures] (>=3.17.0)", "gcsfs (>=2021.5.0)", "neptune-client (>=0.4.109)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)", "coverage (>5.2.0)", "codecov (>=2.1)", "pytest (>=6.0)", "check-manifest", "twine (==3.2)", "mypy (>=0.900)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "scikit-learn (>0.22.1)", "scikit-image (>0.17.1)", "nltk (>=3.3)", "pandas"]
+all = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "torchtext (>=0.7)", "omegaconf (>=2.0.5)", "hydra-core (>=1.0.5)", "jsonargparse[signatures] (>=3.19.3)", "gcsfs (>=2021.5.0)", "rich (>=10.2.2)", "neptune-client (>=0.10.0)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)", "coverage (>5.2.0)", "codecov (>=2.1)", "pytest (>=6.0)", "pytest-rerunfailures (>=10.2)", "check-manifest", "twine (==3.2)", "mypy (>=0.900)", "flake8 (>=3.9.2)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "scikit-learn (>0.22.1)", "onnxruntime", "pandas", "torchvision (>=0.7)", "gym (>=0.17.0)", "ipython"]
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+cpu-extra = ["matplotlib (>3.1)", "torchtext (>=0.7)", "omegaconf (>=2.0.5)", "hydra-core (>=1.0.5)", "jsonargparse[signatures] (>=3.19.3)", "gcsfs (>=2021.5.0)", "rich (>=10.2.2)"]
+dev = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "torchtext (>=0.7)", "omegaconf (>=2.0.5)", "hydra-core (>=1.0.5)", "jsonargparse[signatures] (>=3.19.3)", "gcsfs (>=2021.5.0)", "rich (>=10.2.2)", "neptune-client (>=0.10.0)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)", "coverage (>5.2.0)", "codecov (>=2.1)", "pytest (>=6.0)", "pytest-rerunfailures (>=10.2)", "check-manifest", "twine (==3.2)", "mypy (>=0.900)", "flake8 (>=3.9.2)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "scikit-learn (>0.22.1)", "onnxruntime", "pandas"]
 examples = ["torchvision (>=0.7)", "gym (>=0.17.0)", "ipython"]
-extra = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "omegaconf (>=2.0.1)", "torchtext (>=0.7)", "onnx (>=1.7.0)", "onnxruntime (>=1.3.0)", "hydra-core (>=1.0)", "jsonargparse[signatures] (>=3.17.0)", "gcsfs (>=2021.5.0)"]
-loggers = ["neptune-client (>=0.4.109)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)"]
-test = ["coverage (>5.2.0)", "codecov (>=2.1)", "pytest (>=6.0)", "check-manifest", "twine (==3.2)", "mypy (>=0.900)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "scikit-learn (>0.22.1)", "scikit-image (>0.17.1)", "nltk (>=3.3)", "pandas"]
+extra = ["matplotlib (>3.1)", "horovod (>=0.21.2)", "torchtext (>=0.7)", "omegaconf (>=2.0.5)", "hydra-core (>=1.0.5)", "jsonargparse[signatures] (>=3.19.3)", "gcsfs (>=2021.5.0)", "rich (>=10.2.2)"]
+loggers = ["neptune-client (>=0.10.0)", "comet-ml (>=3.1.12)", "mlflow (>=1.0.0)", "test-tube (>=0.7.5)", "wandb (>=0.8.21)"]
+test = ["coverage (>5.2.0)", "codecov (>=2.1)", "pytest (>=6.0)", "pytest-rerunfailures (>=10.2)", "check-manifest", "twine (==3.2)", "mypy (>=0.900)", "flake8 (>=3.9.2)", "pre-commit (>=1.0)", "cloudpickle (>=1.3)", "scikit-learn (>0.22.1)", "onnxruntime", "pandas"]
 
 [[package]]
 name = "pytz"
@@ -2029,7 +2046,7 @@ python-versions = "*"
 
 [[package]]
 name = "pywinpty"
-version = "1.1.4"
+version = "1.1.5"
 description = "Pseudo terminal support for Windows from Python."
 category = "main"
 optional = true
@@ -2057,7 +2074,7 @@ py = {version = "*", markers = "implementation_name == \"pypy\""}
 
 [[package]]
 name = "qtconsole"
-version = "5.1.1"
+version = "5.2.0"
 description = "Jupyter Qt console"
 category = "main"
 optional = true
@@ -2087,7 +2104,7 @@ python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*"
 
 [[package]]
 name = "regex"
-version = "2021.10.23"
+version = "2021.11.10"
 description = "Alternative regular expression module, to replace re."
 category = "main"
 optional = true
@@ -2274,7 +2291,7 @@ python-versions = "*"
 
 [[package]]
 name = "shortuuid"
-version = "1.0.1"
+version = "1.0.8"
 description = "A generator library for concise, unambiguous and URL-safe UUIDs."
 category = "main"
 optional = true
@@ -2293,7 +2310,7 @@ name = "sklearn"
 version = "0.0"
 description = "A set of python modules for machine learning and data mining"
 category = "main"
-optional = true
+optional = false
 python-versions = "*"
 
 [package.dependencies]
@@ -2445,7 +2462,7 @@ test = ["pytest"]
 
 [[package]]
 name = "sqlalchemy"
-version = "1.4.26"
+version = "1.4.27"
 description = "Database Abstraction Library"
 category = "main"
 optional = true
@@ -2637,7 +2654,7 @@ typing-extensions = "*"
 
 [[package]]
 name = "torchmetrics"
-version = "0.5.1"
+version = "0.6.0"
 description = "PyTorch native Metrics"
 category = "main"
 optional = true
@@ -2649,9 +2666,14 @@ packaging = "*"
 torch = ">=1.3.1"
 
 [package.extras]
-all = ["scipy", "torchvision", "torch-fidelity", "nltk (>=3.6)", "tqdm (>=4.41.0)"]
-image = ["scipy", "torchvision", "torch-fidelity"]
-text = ["nltk (>=3.6)", "tqdm (>=4.41.0)"]
+all = ["numpy (>=1.17.2)", "packaging", "pystoi", "pesq (>=0.0.3)", "torch (>=1.3.1)", "torchvision", "pycocotools (>=2.0.2)", "nbsphinx (>=0.8)", "sphinx (>=4.0)", "sphinx-togglebutton (>=0.2)", "sphinx-autodoc-typehints (>=1.0)", "sphinxcontrib-mockautodoc", "sphinx-copybutton (>=0.3)", "pytorch-lightning (>=1.1)", "pandoc (>=1.0)", "sphinx-paramlinks (>=0.5.1)", "docutils (>=0.16)", "sphinxcontrib-fulltoc (>=1.0)", "myst-parser", "scipy", "lpips", "torch-fidelity", "pytorch-lightning (>=1.0)", "phmdoctest (>=1.1.1)", "pytest (>=6.0)", "cloudpickle (>=1.3)", "twine (>=3.2)", "codecov (>=2.1)", "sacrebleu (>=2.0.0)", "scikit-image (>0.17.1)", "mir-eval (>=0.6)", "isort (>=5.0)", "scikit-learn (>=0.24)", "mypy (>=0.790)", "jiwer (>=2.2.0)", "check-manifest", "flake8", "transformers (>=4.0)", "bert-score (==0.3.10)", "rouge-score (>=0.0.4)", "coverage (>5.2)", "pre-commit (>=1.0)", "pytest-cov (>2.10)", "pypesq", "tqdm (>=4.41.0)", "regex (>=2021.9.24)", "nltk (>=3.6)"]
+audio = ["numpy (>=1.17.2)", "packaging", "pystoi", "pesq (>=0.0.3)", "torch (>=1.3.1)"]
+detection = ["numpy (>=1.17.2)", "packaging", "torchvision", "pycocotools (>=2.0.2)", "torch (>=1.3.1)"]
+docs = ["numpy (>=1.17.2)", "packaging", "nbsphinx (>=0.8)", "sphinx (>=4.0)", "sphinx-togglebutton (>=0.2)", "sphinx-autodoc-typehints (>=1.0)", "sphinxcontrib-mockautodoc", "sphinx-copybutton (>=0.3)", "pytorch-lightning (>=1.1)", "pandoc (>=1.0)", "sphinx-paramlinks (>=0.5.1)", "docutils (>=0.16)", "sphinxcontrib-fulltoc (>=1.0)", "torch (>=1.3.1)", "myst-parser"]
+image = ["scipy", "numpy (>=1.17.2)", "packaging", "torchvision", "lpips", "torch-fidelity", "torch (>=1.3.1)"]
+integrate = ["numpy (>=1.17.2)", "packaging", "torch (>=1.3.1)", "pytorch-lightning (>=1.0)"]
+test = ["phmdoctest (>=1.1.1)", "pytest (>=6.0)", "cloudpickle (>=1.3)", "twine (>=3.2)", "codecov (>=2.1)", "sacrebleu (>=2.0.0)", "scikit-image (>0.17.1)", "mir-eval (>=0.6)", "numpy (>=1.17.2)", "isort (>=5.0)", "scikit-learn (>=0.24)", "mypy (>=0.790)", "jiwer (>=2.2.0)", "torch (>=1.3.1)", "check-manifest", "flake8", "transformers (>=4.0)", "bert-score (==0.3.10)", "packaging", "rouge-score (>=0.0.4)", "coverage (>5.2)", "pre-commit (>=1.0)", "pytest-cov (>2.10)", "pypesq"]
+text = ["numpy (>=1.17.2)", "packaging", "tqdm (>=4.41.0)", "regex (>=2021.9.24)", "nltk (>=3.6)", "torch (>=1.3.1)"]
 
 [[package]]
 name = "tornado"
@@ -2720,7 +2742,7 @@ test = ["shellingham (>=1.3.0,<2.0.0)", "pytest (>=4.4.0,<5.4.0)", "pytest-cov (
 
 [[package]]
 name = "types-pyyaml"
-version = "6.0.0"
+version = "6.0.1"
 description = "Typing stubs for PyYAML"
 category = "main"
 optional = true
@@ -2822,7 +2844,7 @@ watchdog = ["watchdog"]
 
 [[package]]
 name = "widgetsnbextension"
-version = "3.5.1"
+version = "3.5.2"
 description = "IPython HTML widgets for Jupyter"
 category = "main"
 optional = true
@@ -2844,7 +2866,7 @@ dev = ["pytest (>=4.6.2)", "black (>=19.3b0)"]
 
 [[package]]
 name = "yarl"
-version = "1.7.0"
+version = "1.7.2"
 description = "Yet another URL library"
 category = "main"
 optional = true
@@ -2894,63 +2916,102 @@ wandb = ["wandb"]
 [metadata]
 lock-version = "1.1"
 python-versions = ">=3.6.2, <3.9.0"
-content-hash = "5f9863b2a28ed0dade32ea5fbd085d55ea12b7aa3df361cf8c3e5418cdab4404"
+content-hash = "55c465f1bb5b8d807b3cc00f8298ec0982edd7ad207b1b01de4dc1814f6d7d96"
 
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+    {file = "yarl-1.7.2.tar.gz", hash = "sha256:45399b46d60c253327a460e99856752009fcee5f5d3c80b2f7c0cae1c38d56dd"},
 ]
 yaspin = [
     {file = "yaspin-2.1.0-py3-none-any.whl", hash = "sha256:d574cbfaf0a349df466c91f7f81b22460ae5ebb15ecb8bf9411d6049923aee8d"},
diff --git a/pyproject.toml b/pyproject.toml
index 05581b9a9..54e74e218 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "etna-ts"
-version = "1.2.0"
+version = "1.3.1"
 repository = "https://github.com/tinkoff-ai/etna-ts"
 readme = "README.md"
 description = "ETNA is the first python open source framework of Tinkoff.ru AI Center. It is designed to make working with time series simple, productive, and fun."
@@ -39,7 +39,7 @@ authors = [
 [tool.poetry.dependencies]
 python = ">=3.6.2, <3.9.0"
 scikit-learn = "^0.24.1"
-pandas = "^1, <1.2"
+pandas = "^1"
 catboost = "^0.25"
 ruptures = "1.1.5"
 numba = "^0.53.1"
@@ -87,9 +87,6 @@ jupyter = {version = "*", optional = true}
 nbconvert = {version = "*", optional = true}
 omegaconf = "^2.1.1"
 
-mrmr = {git = "https://github.com/smazzanti/mrmr.git", rev = "96ad224"} 
-category-encoders = "^2.3.0"
-
 [tool.poetry.extras]
 # optional deps
 prophet = ["prophet"]
diff --git a/tests/test_analysis/test_feature_relevance/test_relevance.py b/tests/test_analysis/test_feature_relevance/test_relevance.py
index 0fa11b9cc..100be660d 100644
--- a/tests/test_analysis/test_feature_relevance/test_relevance.py
+++ b/tests/test_analysis/test_feature_relevance/test_relevance.py
@@ -1,3 +1,4 @@
+import pytest
 from sklearn.tree import DecisionTreeRegressor
 
 from etna.analysis.feature_relevance import ModelRelevanceTable
@@ -8,11 +9,26 @@ def test_statistics_relevance_table(simple_df_relevance):
     rt = StatisticsRelevanceTable()
     assert not rt.greater_is_better
     df, df_exog = simple_df_relevance
-    assert rt(df=df, df_exog=df_exog).shape == (2, 2)
+    assert rt(df=df, df_exog=df_exog, return_ranks=False).shape == (2, 2)
 
 
 def test_model_relevance_table(simple_df_relevance):
     rt = ModelRelevanceTable()
     assert rt.greater_is_better
     df, df_exog = simple_df_relevance
-    assert rt(df=df, df_exog=df_exog, model=DecisionTreeRegressor()).shape == (2, 2)
+    assert rt(df=df, df_exog=df_exog, return_ranks=False, model=DecisionTreeRegressor()).shape == (2, 2)
+
+
+@pytest.mark.parametrize(
+    "greater_is_better,answer",
+    ((True, [1, 2, 2, 1]), (False, [2, 1, 1, 2])),
+)
+def test_relevance_table_ranks(greater_is_better, answer, simple_df_relevance):
+    rt = ModelRelevanceTable()
+    rt.greater_is_better = greater_is_better
+    df, df_exog = simple_df_relevance
+    table = rt(df=df, df_exog=df_exog, return_ranks=True, model=DecisionTreeRegressor())
+    assert table["regressor_1"]["1"] == answer[0]
+    assert table["regressor_2"]["1"] == answer[1]
+    assert table["regressor_1"]["2"] == answer[2]
+    assert table["regressor_2"]["2"] == answer[3]
diff --git a/tests/test_transforms/test_feature_importance_transform.py b/tests/test_transforms/test_feature_importance_transform.py
index 9f8d08003..f79b1e5f2 100644
--- a/tests/test_transforms/test_feature_importance_transform.py
+++ b/tests/test_transforms/test_feature_importance_transform.py
@@ -9,15 +9,11 @@
 from sklearn.tree import DecisionTreeRegressor
 from sklearn.tree import ExtraTreeRegressor
 
-from etna.analysis import StatisticsRelevanceTable
-from etna.clustering import DTWClustering
-from etna.clustering import EuclideanClustering
 from etna.datasets import TSDataset
 from etna.datasets import generate_ar_df
 from etna.models import LinearPerSegmentModel
 from etna.pipeline import Pipeline
 from etna.transforms import SegmentEncoderTransform
-from etna.transforms.feature_importance import MRMRFeatureSelectionTransform
 from etna.transforms.feature_importance import TreeFeatureSelectionTransform
 
 
@@ -62,61 +58,6 @@ def ts_with_regressors():
     return TSDataset(df=TSDataset.to_dataset(df), df_exog=TSDataset.to_dataset(df_exog_all_segments), freq="D")
 
 
-@pytest.mark.parametrize(
-    "relevance_method, clustering_method",
-    [
-        [StatisticsRelevanceTable(), EuclideanClustering()],
-        [StatisticsRelevanceTable(), DTWClustering()],
-    ],
-)
-@pytest.mark.parametrize("top_k", [0, 1, 5, 15, 50])
-def test_mrmr_right_len(relevance_method, clustering_method, top_k, ts_with_regressors):
-    """Check that transform selects exactly top_k regressors."""
-    df = ts_with_regressors.to_pandas()
-    mrmr = MRMRFeatureSelectionTransform(relevance_method, top_k, clustering_method, n_clusters=2)
-    df_selected = mrmr.fit_transform(df)
-    all_regressors = ts_with_regressors.regressors
-    selected_regressors = set()
-    for column in df_selected.columns.get_level_values("feature"):
-        if column.startswith("regressor"):
-            selected_regressors.add(column)
-
-    assert len(selected_regressors) == min(len(all_regressors), top_k)
-
-
-@pytest.mark.parametrize(
-    "relevance_method, clustering_method",
-    [
-        [StatisticsRelevanceTable(), EuclideanClustering()],
-    ],
-)
-def test_mrmr_right_regressors(relevance_method, clustering_method, ts_with_regressors):
-    """Check that transform selects right top_k regressors."""
-    df = ts_with_regressors.to_pandas()
-    mrmr = MRMRFeatureSelectionTransform(relevance_method, 3, clustering_method, n_clusters=2)
-    df_selected = mrmr.fit_transform(df)
-    selected_regressors = set()
-    for column in df_selected.columns.get_level_values("feature"):
-        if column.startswith("regressor"):
-            selected_regressors.add(column)
-    assert set(selected_regressors) == set(["regressor_useful_1", "regressor_useful_2", "regressor_useless_9"])
-
-
-def test_mrmr_fails_negative_parameters():
-    """Check that transform doesn't allow you to set top_k to negative values and n_clusters >= 2."""
-    with pytest.raises(ValueError, match="positive integer"):
-        MRMRFeatureSelectionTransform(StatisticsRelevanceTable(), top_k=-1)
-    with pytest.raises(ValueError, match="greater than"):
-        MRMRFeatureSelectionTransform(StatisticsRelevanceTable(), top_k=1, n_clusters=1)
-
-
-def test_mrmr_fails(ts_with_regressors):
-    """Check that transform doesn't allow you to set n_clusters greater than number of regressors."""
-    mrmr = MRMRFeatureSelectionTransform(StatisticsRelevanceTable(), top_k=4, freq="D", n_clusters=25)
-    with pytest.raises(ValueError, match="strictly less than"):
-        mrmr.fit_transform(ts_with_regressors.to_pandas())
-
-
 @pytest.mark.parametrize(
     "model",
     [