| import streamlit as st |
|
|
| st.title("📊 Data Collection & Data Understanding") |
|
|
| st.markdown(""" |
| ## 📥 Data Collection: |
| The dataset used in this project was collected from an online source containing historical flight price data for various airlines. |
| |
| ### Dataset Features: |
| - **Airline:** Name of the airline company. |
| - **Source City:** The departure city. |
| - **Departure Time:** Scheduled time of departure. |
| - **Stops:** Number of stops in the flight. |
| - **Arrival Time:** Scheduled arrival time. |
| - **Destination City:** The destination city. |
| - **Class:** Class of the flight (Economy/Business). |
| - **Duration:** Total travel duration (in hours). |
| - **Days Left:** Number of days between the booking date and the flight date. |
| - **Price:** Target variable — flight ticket price. |
| |
| --- |
| |
| ## 📚 Key Understanding: |
| - **Data Type:** Mix of categorical and numerical variables. |
| - **Data Size:** Contains several thousand records. |
| - **Target Variable:** Flight Ticket Price. |
| |
| The next step is to explore the dataset through Exploratory Data Analysis (EDA). |
| """) |
|
|
| if st.button('Next'): |
| st.switch_page('pages/3_EDA.py') |
|
|
| if st.button('Go to Problem Statement'): |
| st.switch_page('pages/1_Problem_Statement.py') |
