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main (1).py

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+import streamlit as st
+import pandas as pd
+import matplotlib.pyplot as plt
+
+# Load data
+data = pd.read_csv('customers.csv')
+
+
+# Function to display basic data information
+def display_data_info(data):
+    st.write("### Data Information")
+    st.write(data.info())
+    st.write("### Data Description")
+    st.write(data.describe())
+
+
+# Function to plot data
+def plot_data(data, column, chart_type):
+    if column == 'Net Sale':
+        data[column] = data[column].replace('[\$,]', '', regex=True).str.strip()
+        data[column] = pd.to_numeric(data[column], errors='coerce')
+    elif column == 'Cost':
+        data[column] = data[column].replace('[\$,]', '', regex=True).str.strip()
+        data[column] = pd.to_numeric(data[column], errors='coerce')
+    elif column == 'Gross Profit':
+        data[column] = data[column].replace('[\$,]', '', regex=True).str.strip()
+        data[column] = pd.to_numeric(data[column], errors='coerce')
+    elif column == ' AVG Inv. ':
+        data[column] = data[column].replace('[\$,]', '', regex=True).str.strip()
+        data[column] = pd.to_numeric(data[column], errors='coerce')
+
+    grouped_data = data.groupby('Mail ZIP')[column].sum()
+
+    plt.figure(figsize=(10, 6))
+    if chart_type == 'Bar Chart':
+        grouped_data.plot(kind='bar', color='skyblue')
+    elif chart_type == 'Scatter Plot':
+        plt.scatter(grouped_data.index, grouped_data.values, color='skyblue')
+    elif chart_type == 'Line Chart':
+        grouped_data.plot(kind='line', color='skyblue')
+    plt.title(f'{column} by ZIP Code')
+    plt.xlabel('ZIP Code')
+    plt.ylabel(column)
+    plt.xticks(rotation=45)
+    st.pyplot(plt)
+
+
+# Function to plot gross margin by ZIP Code
+def gross_margin_by_zip_code(data, chart_type):
+    margin_by_zip = data.groupby('Mail ZIP')['Gross Margin'].mean()
+    plt.figure(figsize=(10, 6))
+    if chart_type == 'Bar Chart':
+        margin_by_zip.plot(kind='bar', color='orange')
+    elif chart_type == 'Scatter Plot':
+        plt.scatter(margin_by_zip.index, margin_by_zip.values, color='orange')
+    elif chart_type == 'Line Chart':
+        margin_by_zip.plot(kind='line', color='orange')
+    plt.title('Gross Margin by ZIP Code')
+    plt.xlabel('ZIP Code')
+    plt.ylabel('Gross Margin (%)')
+    plt.xticks(rotation=45)
+    st.pyplot(plt)
+
+
+# Streamlit App
+def main():
+    st.title("Sales and Cost Dashboard")
+
+    # Sidebar options
+    st.sidebar.title("Options")
+    options = st.sidebar.radio(
+        "Select a Report", [
+                    'Data Information',
+                    'Net Sales by ZIP Code',
+                    'Cost by ZIP Code',
+                    'Gross Profit by ZIP Code',
+                    'Gross Margin by ZIP Code',
+                    'Average Invoice by ZIP Code'
+                    ]
+        )
+
+    chart_type = st.sidebar.selectbox("Select Chart Type", ['Bar Chart', 'Scatter Plot', 'Line Chart'])
+
+    if options == 'Data Information':
+        display_data_info(data)
+    elif options == 'Net Sales by ZIP Code':
+        plot_data(data, 'Net Sale', chart_type)
+    elif options == 'Cost by ZIP Code':
+        plot_data(data, 'Cost', chart_type)
+    elif options == 'Gross Profit by ZIP Code':
+        plot_data(data, 'Gross Profit', chart_type)
+    elif options == 'Gross Margin by ZIP Code':
+        gross_margin_by_zip_code(data, chart_type)
+    elif options == 'Average Invoice by ZIP Code':
+        plot_data(data, ' AVG Inv. ', chart_type)
+
+
+if __name__ == '__main__':
+    main()

requirements.txt

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+streamlit
+pandas
+matplotlib