From c9e24bfac4ef0778b96b97adf57b581193d52c07 Mon Sep 17 00:00:00 2001
From: ThomasMeissnerDS <meissnercorporation@gmx.de>
Date: Thu, 11 Jan 2024 06:10:39 +0100
Subject: [PATCH] Fix univariate plots

---
 README.md                      |  1 -
 bluecast/eda/analyse.py        | 12 +++---------
 bluecast/tests/test_analyse.py |  3 +--
 docs/source/index.md           |  1 -
 4 files changed, 4 insertions(+), 13 deletions(-)

diff --git a/README.md b/README.md
index 64f2ff4f..138538f3 100644
--- a/README.md
+++ b/README.md
@@ -148,7 +148,6 @@ train_data = feat_type_detector.fit_transform_feature_types(train_data)
 # show univariate plots
 univariate_plots(
         train_data.loc[:, feat_type_detector.num_columns],  # here the target column EC1 is already included
-        "EC1",
     )
 
 # show bi-variate plots
diff --git a/bluecast/eda/analyse.py b/bluecast/eda/analyse.py
index 197b6761..68739cc6 100644
--- a/bluecast/eda/analyse.py
+++ b/bluecast/eda/analyse.py
@@ -12,20 +12,14 @@
 from sklearn.manifold import TSNE
 
 
-def univariate_plots(df: pd.DataFrame, target: str) -> None:
+def univariate_plots(df: pd.DataFrame) -> None:
     """
-    Plots univariate plots for all the columns in the dataframe.
-    The target column must be part of the provided DataFrame.
+    Plots univariate plots for all the columns in the dataframe. Only numerical columns are expected.
+    The target column does not need to be part of the provided DataFrame.
 
     Expects numeric columns only.
     """
-    if target not in df.columns.to_list():
-        raise ValueError("Target column must be part of the provided DataFrame")
     for col in df.columns:
-        # Check if the col is the target column (EC1 or EC2)
-        if col == target:
-            continue  # Skip target columns in univariate analysis
-
         plt.figure(figsize=(8, 4))
 
         # Histogram
diff --git a/bluecast/tests/test_analyse.py b/bluecast/tests/test_analyse.py
index b223197d..1fae9ac9 100644
--- a/bluecast/tests/test_analyse.py
+++ b/bluecast/tests/test_analyse.py
@@ -80,8 +80,7 @@ def test_univariate_plots(synthetic_train_test_data):
     univariate_plots(
         synthetic_train_test_data[0].loc[
             :, ["numerical_feature_1", "numerical_feature_2", "numerical_feature_3"]
-        ],
-        "target",
+        ]
     )
     assert True
 
diff --git a/docs/source/index.md b/docs/source/index.md
index 64f2ff4f..138538f3 100644
--- a/docs/source/index.md
+++ b/docs/source/index.md
@@ -148,7 +148,6 @@ train_data = feat_type_detector.fit_transform_feature_types(train_data)
 # show univariate plots
 univariate_plots(
         train_data.loc[:, feat_type_detector.num_columns],  # here the target column EC1 is already included
-        "EC1",
     )
 
 # show bi-variate plots