Delete data_processor.py

data_processor.py

@@ -1,62 +0,0 @@
-import pandas as pd
-import numpy as np
-import plotly.express as px
-import plotly.graph_objects as go
-import streamlit as st
-from typing import Dict, List, Any
-
-
-class DataProcessor:
-    def __init__(self):
-        self.data = None
-        self.numeric_columns = []
-        self.categorical_columns = []
-        self.date_columns = []
-    
-    def load_data(self, file) -> bool:
-        try:
-            self.data = pd.read_csv(file)
-            self._classify_columns()
-            return True
-        except Exception as e:
-            st.error(f"Error loading data: {str(e)}")
-            return False
-    
-    def _classify_columns(self):
-        for col in self.data.columns:
-            if pd.api.types.is_numeric_dtype(self.data[col]):
-                self.numeric_columns.append(col)
-            elif pd.api.types.is_datetime64_any_dtype(self.data[col]):
-                self.date_columns.append(col)
-            else:
-                try:
-                    pd.to_datetime(self.data[col])
-                    self.date_columns.append(col)
-                except:
-                    self.categorical_columns.append(col)
-
-    def get_basic_stats(self) -> Dict[str, Any]:
-        if self.data is None:
-            return {}
-        
-        stats = {
-            'summary': self.data[self.numeric_columns].describe(),
-            'missing_values': self.data.isnull().sum(),
-            'row_count': len(self.data),
-            'column_count': len(self.data.columns)
-        }
-        return stats
-
-    def create_visualization(self, chart_type: str, x_col: str, y_col: str, color_col: str = None) -> go.Figure:
-        if chart_type == "Line Plot":
-            fig = px.line(self.data, x=x_col, y=y_col, color=color_col)
-        elif chart_type == "Bar Plot":
-            fig = px.bar(self.data, x=x_col, y=y_col, color=color_col)
-        elif chart_type == "Scatter Plot":
-            fig = px.scatter(self.data, x=x_col, y=y_col, color=color_col)
-        elif chart_type == "Box Plot":
-            fig = px.box(self.data, x=x_col, y=y_col, color=color_col)
-        else:
-            fig = px.histogram(self.data, x=x_col, color=color_col)
-        
-        return fig