Create app.py

app.py

@@ -0,0 +1,136 @@
+import streamlit as st
+import pandas as pd
+import math
+import matplotlib.pyplot as plt
+
+# Function to read different file types
+def read_file(file):
+    file_extension = file.name.split(".")[-1]
+    if file_extension == "csv":
+        data = pd.read_csv(file)
+    elif file_extension == "xlsx":
+        data = pd.read_excel(file, engine="openpyxl")
+    else:
+        st.error("Unsupported file format. Please upload a CSV or Excel file.")
+        return None
+    return data
+
+# Function to display the uploaded data
+def display_data(data):
+    st.write("### Data Preview")
+    st.dataframe(data.head())
+
+# Function to perform mathematical calculations and store results as separate columns
+def perform_calculations(data):
+    st.write("### Calculations")
+
+    # Get column names
+    columns = data.columns
+
+    # Iterate over each column and perform calculations
+    for column in columns:
+        st.write("Calculations for column:", column)
+
+        # Example calculations: sum, mean, median
+        column_sum = data[column].sum()
+        column_mean = data[column].mean()
+        column_median = data[column].median()
+
+        # Create new column names
+        sum_column_name = f"{column}_sum"
+        mean_column_name = f"{column}_mean"
+        median_column_name = f"{column}_median"
+
+        # Add the calculated values as new columns
+        data[sum_column_name] = column_sum
+        data[mean_column_name] = column_mean
+        data[median_column_name] = column_median
+
+        # Display the calculated values
+        st.write("Sum:", column_sum)
+        st.write("Mean:", column_mean)
+        st.write("Median:", column_median)
+
+    # Display the updated data with calculated columns
+    st.write("### Updated Data")
+    st.dataframe(data)
+
+# Function to perform mathematical calculations
+def perform_math(df, selected_columns, operation):
+    result = None
+
+    if operation == "sqrt":
+        result = df[selected_columns].applymap(math.sqrt)
+    elif operation == "log":
+        result = df[selected_columns].applymap(math.log)
+    elif operation == "exp":
+        result = df[selected_columns].applymap(math.exp)
+    elif operation == "sin":
+        result = df[selected_columns].applymap(math.sin)
+    elif operation == "cos":
+        result = df[selected_columns].applymap(math.cos)
+    elif operation == "tan":
+        result = df[selected_columns].applymap(math.tan)
+    elif operation == "multiply":
+        result = df[selected_columns].prod(axis=1)
+    elif operation == "add":
+        result = df[selected_columns].sum(axis=1)
+    elif operation == "subtract":
+        result = df[selected_columns[0]] - df[selected_columns[1]]
+
+    if result is not None:
+        df[f"{operation}_result"] = result
+
+    return df
+
+def plot_graph(data, graph_type, x_variables, y_variables):
+    plt.figure(figsize=(8, 6))
+
+    for x_var in x_variables:
+        for y_var in y_variables:
+            if graph_type == "Scatter":
+                plt.scatter(data[x_var], data[y_var], label=f"{x_var} vs {y_var}")
+            elif graph_type == "Line":
+                plt.plot(data[x_var], data[y_var], label=f"{x_var} vs {y_var}")
+            elif graph_type == "Bar":
+                x = range(len(data))
+                plt.bar(x, data[y_var], label=y_var)
+
+    plt.xlabel("X Values")
+    plt.ylabel("Y Values")
+    plt.title(f"{graph_type} Plot")
+    plt.legend()
+
+    st.pyplot()
+
+def main():
+    st.title("Excel-like Data Visualization and Calculations")
+    st.write("Upload a CSV or Excel file and visualize the data")
+
+    file = st.file_uploader("Upload file", type=["csv", "xlsx"])
+
+    if file is not None:
+        data = read_file(file)
+        if data is not None:
+            display_data(data)
+            perform_calculations(data)
+
+            st.write("### Graph Visualizer")
+            st.write("Select variables for visualization:")
+
+            graph_type = st.selectbox("Graph Type", options=["Scatter", "Line", "Bar"])
+            x_variables = st.multiselect("X Variables", options=data.columns)
+            y_variables = st.multiselect("Y Variables", options=data.columns)
+
+            selected_columns = st.multiselect("Select columns:", options=data.columns)
+            operation = st.selectbox("Select an operation:", ["sqrt", "log", "exp", "sin", "cos", "tan", "multiply", "add", "subtract"])
+
+            if st.button("Calculate"):
+                data = perform_math(data, selected_columns, operation)
+                st.write(data)
+            if st.button("Plot"):
+                plot_graph(data, graph_type, x_variables, y_variables)
+
+if __name__ == "__main__":
+    st.set_page_config(page_title="My Analytics App")
+    main()