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Turn Your Excel File Into A Web App With Python (fast & easy) | Streamlit Tutorial

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In this tutorial, I am going to show you how to convert Excel Files into a Web Application by using the Python Library Streamlit. The beauty of Streamlit is that you can create web applications directly in Python, without needing to know HTML, CSS, or JavaScript. The Web App is fully interactive and will be updated, whenever you make changes in the Excel file.

📝 Resources:

You can download all the files from the tutorial here:

Download Here

 

Deploy your Streamlit Application to Heroku for free:

Deploy Your Streamlit Web App on Heroku For Free (fast & easy)

Streamlit Documentation & App Gallery:

 

👩‍💻 Source Code:

import pandas as pd
import streamlit as st
import plotly.express as px
from PIL import Image

st.set_page_config(page_title='Survey Results')
st.header('Survey Results 2021')
st.subheader('Was the tutorial helpful?')

### --- LOAD DATAFRAME
excel_file = 'Survey_Results.xlsx'
sheet_name = 'DATA'

df = pd.read_excel(excel_file,
                   sheet_name=sheet_name,
                   usecols='B:D',
                   header=3)

df_participants = pd.read_excel(excel_file,
                                sheet_name= sheet_name,
                                usecols='F:G',
                                header=3)
df_participants.dropna(inplace=True)

# --- STREAMLIT SELECTION
department = df['Department'].unique().tolist()
ages = df['Age'].unique().tolist()

age_selection = st.slider('Age:',
                        min_value= min(ages),
                        max_value= max(ages),
                        value=(min(ages),max(ages)))

department_selection = st.multiselect('Department:',
                                    department,
                                    default=department)

# --- FILTER DATAFRAME BASED ON SELECTION
mask = (df['Age'].between(*age_selection)) & (df['Department'].isin(department_selection))
number_of_result = df[mask].shape[0]
st.markdown(f'*Available Results: {number_of_result}*')

# --- GROUP DATAFRAME AFTER SELECTION
df_grouped = df[mask].groupby(by=['Rating']).count()[['Age']]
df_grouped = df_grouped.rename(columns={'Age': 'Votes'})
df_grouped = df_grouped.reset_index()

# --- PLOT BAR CHART
bar_chart = px.bar(df_grouped,
                   x='Rating',
                   y='Votes',
                   text='Votes',
                   color_discrete_sequence = ['#F63366']*len(df_grouped),
                   template= 'plotly_white')
st.plotly_chart(bar_chart)

# --- DISPLAY IMAGE & DATAFRAME
col1, col2 = st.beta_columns(2)
image = Image.open('images/survey.jpg')
print(image)
col1.image(image,
        caption='Designed by slidesgo / Freepik',
        use_column_width=True)
col2.dataframe(df[mask])

# --- PLOT PIE CHART
pie_chart = px.pie(df_participants,
                title='Total No. of Participants',
                values='Participants',
                names='Departments')

st.plotly_chart(pie_chart)