Update app.py

app.py

@@ -2,6 +2,16 @@ import streamlit as st
 import pandas as pd
 import numpy as np
 import plotly.express as px
+from scipy import stats
+import plotly.colors as pc
+import joblib
+from io import StringIO
+import requests
+import asyncio
+from io import BytesIO
+import base64
+import mimetypes
+import matplotlib.pyplot as plt
 from sklearn.model_selection import train_test_split, GridSearchCV, cross_val_score, learning_curve
 from sklearn.linear_model import LinearRegression, LogisticRegression
 from sklearn.tree import DecisionTreeRegressor, DecisionTreeClassifier
@@ -11,7 +21,6 @@ from sklearn.feature_selection import SelectKBest
 from sklearn.experimental import enable_iterative_imputer
 from sklearn.impute import IterativeImputer
 from sklearn.neural_network import MLPRegressor
-import joblib
 from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_error, accuracy_score, precision_score, recall_score, f1_score
 from sklearn.impute import KNNImputer, SimpleImputer
 from sklearn.preprocessing import RobustScaler, StandardScaler, OneHotEncoder, LabelEncoder
@@ -19,13 +28,7 @@ from sklearn.compose import ColumnTransformer
 from sklearn.pipeline import Pipeline
 from ydata_profiling import ProfileReport
 from streamlit_pandas_profiling import st_profile_report
-from io import StringIO
-import requests
-import asyncio
-from io import BytesIO
-import base64
-import mimetypes
-import matplotlib.pyplot as plt
+
 
 # Enhanced configuration
 st.set_page_config(
@@ -602,10 +605,13 @@ elif app_mode == "Advanced EDA":
         config = st.session_state.eda_config
 
         if config['plot_type'] == "Histogram":
+            color_palette = config['color_palette']
+            colors = getattr(pc.sequential, color_palette)
             fig = px.histogram(
                 df, x=config['x_col'], y=config['y_col'],
                 nbins=30, template="plotly_dark",
-                color_discrete_sequence=[config['color_palette']]
+                color=config['x_col'],
+                color_discrete_sequence = [colors[0]]
             )
 
         elif config['plot_type'] == "Scatter Plot":
@@ -730,7 +736,7 @@ elif app_mode == "Advanced EDA":
             with st.spinner("Generating report..."):
                 pr = ProfileReport(df, explorative=True)
                 st_profile_report(pr)
-
+                
 # Model Training Section
 elif app_mode == "Model Training":
     st.title("🚂 Model Training Studio")