I am getting in deploying my app


ModuleNotFoundError: This app has encountered an error. The original error message is redacted to prevent data leaks. Full error details have been recorded in the logs (if you’re on Streamlit Cloud, click on ‘Manage app’ in the lower right of your app).

File "/home/adminuser/venv/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 552, in _run_script
    exec(code, module.__dict__)File "/mount/src/class-projects/Dashboard/App.py", line 3, in <module>

Unfortunately, you did not provide any useful information, therefore we can only guess.
Probably the requirements.txt file is missing.

import streamlit as st
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import streamlit.components.v1 as components
import os

                   page_title='Deja Vu Stores Dashboard'

# Load the available data and overview
path = os.path.dirname(__file__)
path = os.path.join(path, "dataonline.csv")

def load_data(data_path):
    dataframe = pd.read_csv(data_path, encoding="ISO-8859-1", low_memory=False)
    dataframe["Revenue"] = dataframe["UnitPrice"] * dataframe["Quantity"]
    dataframe["InvoiceDate"] = pd.to_datetime(dataframe["InvoiceDate"])
    dataframe["InvoiceMonth"] = pd.DatetimeIndex(dataframe["InvoiceDate"]).month
    dataframe["InvoiceYear"] = pd.DatetimeIndex(dataframe["InvoiceDate"]).year
    return dataframe

st.sidebar.header('Deja Vu Stores')
data = st.sidebar.file_uploader("Upload Dataset", type=['csv', 'txt', 'xlsx'])
# Check for uploaded dataset.
if data is not None:
    df = load_data(data)
# Default Dataset if none is uploaded.
    df = load_data(path)

# Add select boxes for different commands and functionalities.
menu = ['Business Snapshot', 'Analysis', 'About']
selection = st.sidebar.selectbox("Key Performance Indicator (KPI) ", menu)

st.sidebar.write('''Retail analytics is the process of providing analytical data on inventory levels, 
supply chain movement, consumer demand, sales, etc. ... The analytics on demand and supply data can be 
used for maintaining procurement level and also inform marketing strategies.''')

if selection == 'Business Snapshot':
    # Use the full page instead of a narrow central column
    # st.set_page_config(layout="wide")
    st.subheader('Display Data')

    col1, col2 = st.columns(2)
    # Column1
    with col1:
        # Monthly revenue
        st.subheader("Monthly Revenue Overview")
        df_revenue = df.groupby(["InvoiceMonth", "InvoiceYear"])["Revenue"].sum().reset_index()
        plt.figure(figsize=(15, 10))
        sns.barplot(x="InvoiceMonth", y="Revenue", hue="InvoiceYear", data=df_revenue)
        plt.title("Monthly Revenue")

        # Column2
        with col2:
            # Monthly Items Sold Overview
            st.subheader("Monthly Items Sold Overview")
            df_quantity = df.groupby(["InvoiceMonth", "InvoiceYear"])["Quantity"].sum().reset_index()
            plt.figure(figsize=(15, 10))
            sns.barplot(x="InvoiceMonth", y="Quantity", data=df_quantity)
            plt.title("Monthly Items Sold")
            plt.ylabel("Items Sold")

    col3, col4 = st.columns(2)
    with col3:
        st.subheader("Monthly Active Customers")
        # Monthly Active Customers
        df_active = df.groupby(["InvoiceMonth", "InvoiceYear"])["CustomerID"].nunique().reset_index()
        plt.figure(figsize=(15, 10))
        sns.barplot(x="InvoiceMonth", y="CustomerID", hue="InvoiceYear", data=df_active)
        plt.title("Monthly Active Users")
        plt.ylabel("Active Users")

    with col4:
        # Monthly Items Sold Overview
        st.subheader("Average Revenue per Month")
        df_revenue_avg = df.groupby(["InvoiceMonth", "InvoiceYear"])["Revenue"].mean().reset_index()
        plt.figure(figsize=(15, 10))
        sns.barplot(x="InvoiceMonth", y="Revenue", data=df_revenue)
        plt.title("Monthly Average Revenue ")

    col5, col6 = st.columns(2)
    with col5:
        st.subheader("Customer Growth (2011)")
        df_active_2011 = df_active[df_active['InvoiceYear'] != 2010]
        plt.figure(figsize=(15, 10))
        sns.regplot(x="InvoiceMonth", y="CustomerID", data=df_active_2011)
        plt.title("Customer Growth 2011")

    with col6:
        # New vs Existing Users
        st.subheader("New vs Existing Users")
        df_first_purchase = df.groupby(["CustomerID"])["InvoiceDate"].min().reset_index()
        df_first_purchase.columns = ["CustomerID", "FirstPurchaseDate"]
        df = pd.merge(df, df_first_purchase, on="CustomerID")
        df["UserType"] = "New"
        df.loc[df["InvoiceDate"] > df["FirstPurchaseDate"], "UserType"] = "Existing"
        # New vs Existing User Revenue Analysis
        df_new_revenue = df.groupby(["InvoiceMonth", "InvoiceYear", "UserType"])["Revenue"].sum().reset_index()
        df_new_revenue["Revenue"] = df_new_revenue["Revenue"] / 1000000
        plt.figure(figsize=(15, 10))
        sns.lineplot(x="InvoiceMonth", y="Revenue", hue="UserType", data=df_new_revenue)
        plt.title("New vs Existing Customers Revenue Overview")
        plt.ylabel("Revenue (In millions)")
        plt.legend(loc="lower left")
        plt.xlim([0, 12])

elif selection == 'Analysis':
    st.subheader('Display data')
    # shape of data
    if st.checkbox("show shape "):
        st.write('Data Shape')
        st.write('{:,} rows; {:,} columns'.format(df.shape[0], df.shape[1]))

        # data description
        st.markdown("Descriptive statistics ")

# adding html  Template
footer_temp = """
<!-- CSS  -->
<link href="https://fonts.googleapis.com/icon?family=Material+Icons" rel="stylesheet">
<link href="https://cdnjs.cloudflare.com/ajax/libs/materialize/1.0.0/css/materialize.min.css" 
type="text/css" rel="stylesheet" media="screen,projection"/>
<link href="static/css/style.css" type="text/css" rel="stylesheet" media="screen,projection"/>
<link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.5.0/css/all.css" 
integrity="sha384-B4dIYHKNBt8Bc12p+WXckhzcICo0wtJAoU8YZTY5qE0Id1GSseTk6S+L3BlXeVIU" cross origin="anonymous">
<footer class="page-footer grey darken-4">
<div class="container" id="about app">
<div class="row">
<div class="col l6 s12">
<h5 class="white-text">Retail Analysis App</h5>
<h6 class="grey-text text-lighten-4">This is my second  Streamlit  project.</h6>
<p class="grey-text text-lighten-4">September 2023</p>
<div class="col l3 s12">
<h5 class="white-text">Connect With Us</h5>
<a href="https://www.facebook.com/kerzuah/" target="_blank" class="white-text">
<i class="fab fa-facebook fa-4x"></i>
<a href="https://www.linkedin.com/in/levis-v-kerzuah-7917a334/" target="_blank" class="white-text">
<i class="fab fa-linkedin fa-4x"></i>
<a href="https://www.youtube.com/watch?v=ZRdlQwNTJ7o" target="_blank" class="white-text">
<i class="fab fa-youtube-square fa-4x"></i>
<a href="https://github.com/lkerzuah" target="_blank" class="white-text">
<i class="fab fa-github-square fa-4x"></i>
<div class="footer-copyright">
<div class="container">
Made by <a class="white-text text-lighten-3" href="https://github.com/lkerzuah">Levis </a><br/>
<a class="white-text text-lighten-3" href="https://github.com/lkerzuah/"></a>

if selection == 'About':
    st.header("About App")
    components.html(footer_temp, height=500)

Apparently seaborn is not installed. Seearch the log for messages related to the installation of seaborn to figure out what went wrong.

Thanks, I resolved this already over the weekend

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