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
st.set_page_config(layout="wide",
initial_sidebar_state="expanded",
page_icon="⚡",
page_title='Deja Vu Stores Dashboard'
)
# Load the available data and overview
path = os.path.dirname(__file__)
path = os.path.join(path, "dataonline.csv")
@st.cache_data
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.
else:
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')
st.dataframe(df.head())
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")
plt.xlabel("Month")
plt.ylabel("Revenue")
st.pyplot(plt)
# 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.xlabel("Month")
plt.ylabel("Items Sold")
st.pyplot(plt)
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.xlabel("Month")
plt.ylabel("Active Users")
st.pyplot(plt)
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 ")
plt.xlabel("Month")
plt.ylabel("Revenue")
st.pyplot(plt)
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")
plt.ylabel("Customers")
plt.xlabel("Months")
st.pyplot(plt)
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.xlabel("Month")
plt.ylabel("Revenue (In millions)")
plt.legend(loc="lower left")
plt.xlim([0, 12])
st.pyplot(plt)
elif selection == 'Analysis':
st.subheader('Display data')
st.write(df.head(5))
# 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 ")
st.write(df.describe())
# 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>
<div class="col l3 s12">
<h5 class="white-text">Connect With Us</h5>
<ul>
<a href="https://www.facebook.com/kerzuah/" target="_blank" class="white-text">
<i class="fab fa-facebook fa-4x"></i>
</a>
<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>
<a href="https://www.youtube.com/watch?v=ZRdlQwNTJ7o" target="_blank" class="white-text">
<i class="fab fa-youtube-square fa-4x"></i>
</a>
<a href="https://github.com/lkerzuah" target="_blank" class="white-text">
<i class="fab fa-github-square fa-4x"></i>
</a>
</ul>
</div>
</div>
</div>
<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>
</div>
</div>
</footer>
"""
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
This topic was automatically closed 2 days after the last reply. New replies are no longer allowed.
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