SyntaxError: invalid syntax while using elif statement

Levis_Kerzuah · September 6, 2023, 2:08pm

Hello family,
I need a help on this please. I creatiing a data Analysis App with Python. This app will be run on streamlit. As you can see in the below codes, All arguments has passed successfull until the elif argurment that is give me this error: elif selection == 'Analysis': SyntaxError: invalid syntax

Someone please help me out, I am very new to Streamlit.

import query
import selection
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)

tonykip · September 6, 2023, 3:00pm

It seems the error is related to indenting under the elif block. Should edit it to look like this;

elif selection == 'Analysis':
  st.subheader('Display data')
  st.write(df.head(5))

Levis_Kerzuah · September 6, 2023, 3:04pm

I was thinking the same way, but is not. I have re-arrage the everything as it relate to indenting.

tonykip · September 6, 2023, 3:06pm

Can you share the full error log?

Levis_Kerzuah · September 6, 2023, 3:07pm

File "C:\Users\varte\OneDrive\Desktop\Data Science Course\streamlit\Dashboard\Data\App.py", line 132
  elif selection == 'Analysis':
  ^
SyntaxError: invalid syntax

tonykip · September 6, 2023, 3:12pm

Just copied your code and pasted to my IDE and it seem your entire with sections also need indenting. I have corrected the indenting here. Try it and let me know if it is resolved, if not share the errors;

import query
import selection
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)

Levis_Kerzuah · September 6, 2023, 3:23pm

Thank! you save my day. Is okay now

system · September 8, 2023, 3:24pm

This topic was automatically closed 2 days after the last reply. New replies are no longer allowed.

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SyntaxError: invalid syntax while using elif statement

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