diff --git a/README.md b/README.md
index d2231c0f4..271f13032 100644
--- a/README.md
+++ b/README.md
@@ -59,7 +59,8 @@ pip install validmind
 - **Install with R support (requires R to be installed)**
 
     ```bash
-    pip install validmind[r-support]
+    pip install validmind
+    pip install rpy2
     ```
 
 ## How to contribute
@@ -102,7 +103,8 @@ brew install r
 Once you have R installed, install the `r-support` extra to install the necessary dependencies for R by running:
 
 ```bash
-poetry install --extras r-support
+poetry install
+pip install rpy2
 ```
 
 ### Versioning
diff --git a/README.pypi.md b/README.pypi.md
index e376eb60e..b1553674d 100644
--- a/README.pypi.md
+++ b/README.pypi.md
@@ -68,5 +68,6 @@ The ValidMind Library has optional dependencies that can be installed separately
 - **R Models**: To use R models with the ValidMind Library, install the `r` extra:
 
     ```bash
-    pip install validmind[r-support]
+    pip install validmind
+    pip install rpy2
     ```
diff --git a/poetry.lock b/poetry.lock
index d1d3eb383..b352501d2 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -466,34 +466,6 @@ files = [
 docs = ["furo", "jaraco.packaging (>=9.3)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 testing = ["jaraco.test", "pytest (!=8.0.*)", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)"]
 
-[[package]]
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-version = "0.2.1"
-description = "Backport of the standard library zoneinfo module"
-optional = true
-python-versions = ">=3.6"
-files = [
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-]
-
-[package.extras]
-tzdata = ["tzdata"]
-
 [[package]]
 name = "beautifulsoup4"
 version = "4.12.3"
@@ -985,13 +957,13 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [[package]]
 name = "cloudpickle"
-version = "3.1.0"
+version = "3.1.1"
 description = "Pickler class to extend the standard pickle.Pickler functionality"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -1282,37 +1254,37 @@ vision = ["Pillow (>=9.4.0)"]
 
 [[package]]
 name = "debugpy"
-version = "1.8.11"
+version = "1.8.12"
 description = "An implementation of the Debug Adapter Protocol for Python"
 optional = false
 python-versions = ">=3.8"
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 ]
 
 [[package]]
@@ -1379,11 +1351,8 @@ name = "docutils"
 version = "0.18.1"
 description = "Docutils -- Python Documentation Utilities"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
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-]
+python-versions = "*"
+files = []
 
 [[package]]
 name = "entrypoints"
@@ -1507,61 +1476,61 @@ pyflakes = ">=2.4.0,<2.5.0"
 
 [[package]]
 name = "fonttools"
-version = "4.55.3"
+version = "4.55.4"
 description = "Tools to manipulate font files"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
@@ -4167,86 +4136,90 @@ realtime = ["websockets (>=13,<15)"]
 
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 ]
 
 [[package]]
@@ -4308,8 +4281,8 @@ files = [
 [package.dependencies]
 numpy = [
     {version = ">=1.20.3", markers = "python_version < \"3.10\""},
-    {version = ">=1.21.0", markers = "python_version >= \"3.10\" and python_version < \"3.11\""},
     {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
+    {version = ">=1.21.0", markers = "python_version >= \"3.10\" and python_version < \"3.11\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -4768,13 +4741,13 @@ twisted = ["twisted"]
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.48"
+version = "3.0.50"
 description = "Library for building powerful interactive command lines in Python"
 optional = false
-python-versions = ">=3.7.0"
+python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -5260,13 +5233,13 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "pydash"
-version = "8.0.4"
+version = "8.0.5"
 description = "The kitchen sink of Python utility libraries for doing \"stuff\" in a functional way. Based on the Lo-Dash Javascript library."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -6038,32 +6011,6 @@ files = [
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 ]
 
-[[package]]
-name = "rpy2"
-version = "3.5.17"
-description = "Python interface to the R language (embedded R)"
-optional = true
-python-versions = ">=3.7"
-files = [
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-
-[package.dependencies]
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-cffi = ">=1.15.1"
-jinja2 = "*"
-packaging = {version = "*", markers = "platform_system == \"Windows\""}
-tzlocal = "*"
-
-[package.extras]
-all = ["ipython", "numpy (<1.26)", "numpy (>=1.26)", "pandas", "pandas (>=1.3.5)", "pytest"]
-doc = ["ipykernel", "jupytext", "multipledispatch", "nbconvert", "numpy", "pandas", "pygraphviz", "sphinx"]
-numpy = ["numpy (<1.26)", "numpy (>=1.26)"]
-pandas = ["numpy (<1.26)", "numpy (>=1.26)", "pandas", "pandas (>=1.3.5)"]
-test = ["ipython", "numpy (<1.26)", "numpy (>=1.26)", "pandas", "pandas (>=1.3.5)", "pytest"]
-test-minimal = ["coverage", "pytest (>=8)", "pytest-cov"]
-types = ["mypy", "types-tzlocal"]
-
 [[package]]
 name = "safetensors"
 version = "0.5.2"
@@ -7475,24 +7422,6 @@ files = [
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 ]
 
-[[package]]
-name = "tzlocal"
-version = "5.2"
-description = "tzinfo object for the local timezone"
-optional = true
-python-versions = ">=3.8"
-files = [
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-
-[package.dependencies]
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-tzdata = {version = "*", markers = "platform_system == \"Windows\""}
-
-[package.extras]
-devenv = ["check-manifest", "pytest (>=4.3)", "pytest-cov", "pytest-mock (>=3.3)", "zest.releaser"]
-
 [[package]]
 name = "unify"
 version = "0.5"
@@ -7549,13 +7478,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.28.1"
+version = "20.29.1"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "virtualenv-20.29.1.tar.gz", hash = "sha256:b8b8970138d32fb606192cb97f6cd4bb644fa486be9308fb9b63f81091b5dc35"},
 ]
 
 [package.dependencies]
@@ -8049,13 +7978,13 @@ propcache = ">=0.2.0"
 
 [[package]]
 name = "ydata-profiling"
-version = "4.12.1"
+version = "4.12.2"
 description = "Generate profile report for pandas DataFrame"
 optional = false
 python-versions = "<3.13,>=3.7"
 files = [
-    {file = "ydata-profiling-4.12.1.tar.gz", hash = "sha256:341b23bbf220a03639a0e2a4b58c4c663cb0a8d73dd27b6f93fa86406cd16cc1"},
-    {file = "ydata_profiling-4.12.1-py2.py3-none-any.whl", hash = "sha256:c14e148dfc779540203acd17b2298171a72c8098c7e2481f8030f50d6f0dc4b5"},
+    {file = "ydata-profiling-4.12.2.tar.gz", hash = "sha256:af9a6dcadf1a8cc73aa9e59c1d1f5f02c798bf5510817bf33e735ebf7c838c02"},
+    {file = "ydata_profiling-4.12.2-py2.py3-none-any.whl", hash = "sha256:b3d2df646a9694dab221d52548ca4d5af0462d5f05996e215fdee35f1e45b391"},
 ]
 
 [package.dependencies]
@@ -8063,36 +7992,36 @@ dacite = ">=1.8"
 htmlmin = "0.1.12"
 imagehash = "4.3.1"
 jinja2 = ">=2.11.1,<3.2"
-matplotlib = ">=3.5,<3.10"
+matplotlib = ">=3.5"
 multimethod = ">=1.4,<2"
-numba = ">=0.56.0,<1"
 numpy = ">=1.16.0,<2.2"
 pandas = ">1.1,<1.4.0 || >1.4.0,<3"
 phik = ">=0.11.1,<0.13"
 pydantic = ">=2"
 PyYAML = ">=5.0.0,<6.1"
 requests = ">=2.24.0,<3"
-scipy = ">=1.4.1,<1.14"
+scipy = ">=1.4.1,<1.16"
 seaborn = ">=0.10.1,<0.14"
 statsmodels = ">=0.13.2,<1"
 tqdm = ">=4.48.2,<5"
 typeguard = ">=3,<5"
-visions = {version = ">=0.7.5,<0.7.7", extras = ["type-image-path"]}
+visions = {version = ">=0.7.5,<0.8.0", extras = ["type-image-path"]}
 wordcloud = ">=1.9.3"
 
 [package.extras]
 notebook = ["ipywidgets (>=7.5.1)", "jupyter (>=1.0.0)"]
+numba = ["numba (>=0.56.0,<1)"]
 unicode = ["tangled-up-in-unicode (==0.2.0)"]
 
 [[package]]
 name = "yfinance"
-version = "0.2.51"
+version = "0.2.52"
 description = "Download market data from Yahoo! Finance API"
 optional = false
 python-versions = "*"
 files = [
-    {file = "yfinance-0.2.51-py2.py3-none-any.whl", hash = "sha256:d5cc7a970bb4bb43e4deee853514cbaa3c2b070a0dee6b2861c1ab5076f21dc1"},
-    {file = "yfinance-0.2.51.tar.gz", hash = "sha256:7902cc9b23699a51efa50f1cc7a965220a56beccc00d189f929b4c7c5c189a60"},
+    {file = "yfinance-0.2.52-py2.py3-none-any.whl", hash = "sha256:3ca150da85f56b999687e13b72304338499a417d5bad6af9da2aa13821992bd7"},
+    {file = "yfinance-0.2.52.tar.gz", hash = "sha256:d2c2ed9bc935596934cba99fca0f05beaa8384648f78105c77754e92f11bf72f"},
 ]
 
 [package.dependencies]
@@ -8132,13 +8061,12 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools",
 type = ["pytest-mypy"]
 
 [extras]
-all = ["langchain-openai", "pycocoevalcap", "ragas", "rpy2", "sentencepiece", "torch", "transformers"]
+all = ["langchain-openai", "pycocoevalcap", "ragas", "sentencepiece", "torch", "transformers"]
 huggingface = ["sentencepiece", "transformers"]
 llm = ["langchain-openai", "pycocoevalcap", "ragas", "sentencepiece", "torch", "transformers"]
 pytorch = ["torch"]
-r-support = ["rpy2"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<3.12"
-content-hash = "dcf7a178278fe9d98b68e3848c39b537d5e088edeb93c53e29a9968ad9346d76"
+content-hash = "6c3c40ab7dbfe990a6c1b02c4c23a558e49230daaba554fd5571b337c8e0c033"
diff --git a/pyproject.toml b/pyproject.toml
index 424285bc7..78a15fd62 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -40,7 +40,6 @@ python = ">=3.8.1,<3.12"
 python-dotenv = "*"
 ragas = {version = ">=0.2.3", optional = true}
 rouge = ">=1"
-rpy2 = {version = "^3.5.10", optional = true}
 scikit-learn = "*,<1.6.0"
 scipy = "*"
 scorecardpy = "^0.1.9.6"
@@ -76,7 +75,6 @@ twine = "^4.0.2"
 
 [tool.poetry.extras]
 all = [
-  "rpy2",
   "torch",
   "transformers",
   "pycocoevalcap",
@@ -94,7 +92,6 @@ llm = [
   "langchain-openai",
 ]
 pytorch = ["torch"]
-r-support = ["rpy2"]
 
 [build-system]
 build-backend = "poetry.core.masonry.api"
diff --git a/validmind/__init__.py b/validmind/__init__.py
index 3cf200e25..99a3d0d2c 100644
--- a/validmind/__init__.py
+++ b/validmind/__init__.py
@@ -55,26 +55,32 @@
 
 __all__ = [  # noqa
     "__version__",
-    # Python Library API
-    "datasets",
-    "errors",
-    "get_test_suite",
+    # main library API
     "init",
+    "reload",
     "init_dataset",
     "init_model",
     "init_r_model",
     "preview_template",
-    "print_env",
-    "RawData",
-    "reload",
     "run_documentation_tests",
+    # log metric function (for direct/bulk/retroactive logging of metrics)
+    "log_metric",
+    # test suite functions (less common)
+    "get_test_suite",
     "run_test_suite",
+    # helper functions (for troubleshooting)
+    "print_env",
+    # decorators (for building tests
     "tags",
     "tasks",
     "test",
-    "tests",
-    "test_suites",
+    # raw data (for post-processing test results and building tests)
+    "RawData",
+    # submodules
+    "datasets",
+    "errors",
     "vm_models",
+    "tests",
     "unit_metrics",
-    "log_metric",
+    "test_suites",
 ]
diff --git a/validmind/errors.py b/validmind/errors.py
index 76c497691..a7db65c49 100644
--- a/validmind/errors.py
+++ b/validmind/errors.py
@@ -228,7 +228,7 @@ class MissingRExtrasError(BaseError):
     def description(self, *args, **kwargs):
         return (
             self.message
-            or "ValidMind r-support needs to be installed: `pip install validmind[r-support]`"
+            or "`rpy2` is required to use R models. Please install it with `pip install rpy2`"
         )
 
 
diff --git a/validmind/models/r_model.py b/validmind/models/r_model.py
index 6277c4109..d26a17092 100644
--- a/validmind/models/r_model.py
+++ b/validmind/models/r_model.py
@@ -5,6 +5,7 @@
 import numpy as np
 import pandas as pd
 
+from validmind.errors import MissingRExtrasError
 from validmind.logging import get_logger
 from validmind.vm_models.model import VMModel
 
@@ -125,7 +126,10 @@ def predict(self, new_data, return_probs=False):
         """
         Converts the predicted probabilities to classes
         """
-        from rpy2.robjects import pandas2ri
+        try:
+            from rpy2.robjects import pandas2ri
+        except ImportError:
+            raise MissingRExtrasError()
 
         # Activate the pandas conversion for rpy2
         pandas2ri.activate()
diff --git a/validmind/tests/data_validation/FeatureTargetCorrelationPlot.py b/validmind/tests/data_validation/FeatureTargetCorrelationPlot.py
index 43e2d7dd7..5fb06c998 100644
--- a/validmind/tests/data_validation/FeatureTargetCorrelationPlot.py
+++ b/validmind/tests/data_validation/FeatureTargetCorrelationPlot.py
@@ -52,16 +52,10 @@ def FeatureTargetCorrelationPlot(dataset, fig_height=600):
     - Not apt for models that employ complex feature interactions, like Decision Trees or Neural Networks, as the test
     may not accurately reflect their importance.
     """
-
-    # Filter DataFrame based on features and target_column
     df = dataset.df[dataset.feature_columns + [dataset.target_column]]
 
-    fig = _visualize_feature_target_correlation(df, dataset.target_column, fig_height)
-
-    correlations = (
-        df.corr(numeric_only=True)[dataset.target_column]
-        .drop(dataset.target_column)
-        .to_frame()
+    fig, correlations = _visualize_feature_target_correlation(
+        df, dataset.target_column, fig_height
     )
 
     return fig, RawData(correlation_data=correlations)
@@ -100,4 +94,5 @@ def _visualize_feature_target_correlation(df, target_column, fig_height):
         yaxis_title="",
         height=fig_height,  # Adjust the height value as needed
     )
-    return fig
+
+    return fig, correlations
diff --git a/validmind/tests/model_validation/ContextualRecall.py b/validmind/tests/model_validation/ContextualRecall.py
index ad6df9a3e..6bff63856 100644
--- a/validmind/tests/model_validation/ContextualRecall.py
+++ b/validmind/tests/model_validation/ContextualRecall.py
@@ -118,4 +118,4 @@ def ContextualRecall(dataset, model):
     # Create a DataFrame from all collected statistics
     result_df = pd.DataFrame(stats_df).reset_index().rename(columns={"index": "Metric"})
 
-    return (result_df, *tuple(figures), RawData(contextual_recall_scores=metrics_df))
+    return (result_df, *figures, RawData(contextual_recall_scores=metrics_df))
diff --git a/validmind/tests/model_validation/MeteorScore.py b/validmind/tests/model_validation/MeteorScore.py
index 052297810..bf679eea0 100644
--- a/validmind/tests/model_validation/MeteorScore.py
+++ b/validmind/tests/model_validation/MeteorScore.py
@@ -117,4 +117,4 @@ def MeteorScore(dataset, model):
     # Create a DataFrame from all collected statistics
     result_df = pd.DataFrame(stats_df).reset_index().rename(columns={"index": "Metric"})
 
-    return (result_df, *tuple(figures), RawData(meteor_scores=metrics_df))
+    return (result_df, *figures, RawData(meteor_scores=metrics_df))
diff --git a/validmind/tests/model_validation/ToxicityScore.py b/validmind/tests/model_validation/ToxicityScore.py
index 28f641046..6f6314be5 100644
--- a/validmind/tests/model_validation/ToxicityScore.py
+++ b/validmind/tests/model_validation/ToxicityScore.py
@@ -141,7 +141,7 @@ def calculate_stats(df):
 
     return (
         result_df,
-        *tuple(figures),
+        *figures,
         RawData(
             input_toxicity_df=input_df,
             true_toxicity_df=true_df,
diff --git a/validmind/tests/model_validation/sklearn/MinimumROCAUCScore.py b/validmind/tests/model_validation/sklearn/MinimumROCAUCScore.py
index 1a754f5e6..b6ed15204 100644
--- a/validmind/tests/model_validation/sklearn/MinimumROCAUCScore.py
+++ b/validmind/tests/model_validation/sklearn/MinimumROCAUCScore.py
@@ -62,18 +62,14 @@ def MinimumROCAUCScore(dataset: VMDataset, model: VMModel, min_threshold: float
         lb = LabelBinarizer()
         lb.fit(y_true)
 
-        y_true_binarized = lb.transform(y_true)
-        y_score_binarized = lb.transform(dataset.y_pred(model))
-
         roc_auc = roc_auc_score(
-            y_true=y_true_binarized,
-            y_score=y_score_binarized,
+            y_true=lb.transform(y_true),
+            y_score=lb.transform(dataset.y_pred(model)),
             average="macro",
         )
 
     else:
-        y_score_prob = dataset.y_prob(model)
-        roc_auc = roc_auc_score(y_true=y_true, y_score=y_score_prob)
+        roc_auc = roc_auc_score(y_true=y_true, y_score=dataset.y_prob(model))
 
     return [
         {
diff --git a/validmind/tests/model_validation/statsmodels/RegressionModelSummary.py b/validmind/tests/model_validation/statsmodels/RegressionModelSummary.py
index 62f4ac258..2814810fd 100644
--- a/validmind/tests/model_validation/statsmodels/RegressionModelSummary.py
+++ b/validmind/tests/model_validation/statsmodels/RegressionModelSummary.py
@@ -45,17 +45,17 @@ def RegressionModelSummary(dataset: VMDataset, model: VMModel):
     - A high R-Squared or Adjusted R-Squared may not necessarily indicate a good model, especially in cases of
     overfitting.
     """
+    y_true = dataset.y
+    y_pred = dataset.y_pred(model)
+
     return [
         {
             "Independent Variables": dataset.feature_columns,
-            "R-Squared": r2_score(dataset.y, dataset.y_pred(model)),
+            "R-Squared": r2_score(y_true, y_pred),
             "Adjusted R-Squared": adj_r2_score(
-                dataset.y,
-                dataset.y_pred(model),
-                len(dataset.y),
-                len(dataset.feature_columns),
+                y_true, y_pred, len(y_true), len(dataset.feature_columns)
             ),
-            "MSE": mean_squared_error(dataset.y, dataset.y_pred(model), squared=True),
-            "RMSE": mean_squared_error(dataset.y, dataset.y_pred(model), squared=False),
+            "MSE": mean_squared_error(y_true, y_pred, squared=True),
+            "RMSE": mean_squared_error(y_true, y_pred, squared=False),
         }
     ]