Omdena Kano Nigeria Chapter Food Prices Analysis and Prediction

This project leverages Machine Learning techniques and Python programming language to analyze historical food prices data in Nigeria, predict future prices, and offer valuable insights for consumers, policymakers, and stakeholders.

Getting Started

Prerequisites

• Python (3.6 or later)

Installation

1. Clone the repository:

   git clone https://dagshub.com/Omdena/KanoNigeriaChapter_FoodPrices.git
   
   
   

2. To install the required dependencies, run the following command in your terminal:

   pip install streamlit
   
   
   
   

Running the Application

Ensure you are in the project directory, then execute the following command to run the Streamlit application:

streamlit run 1 (after typing 1 press 'Tab' button on keyboard to auto-fill the name of file as it uses emoji in the filename)

Customizing Themes and CSS

If you want to customize the theme or apply custom CSS:

1. Open the .streamlit/config.toml file.

2. Modify the theme settings and add custom CSS:

   [theme]
   base="dark"
   primaryColor="#f1df10"
   backgroundColor="#014803"
   secondaryBackgroundColor="#318100"
   textColor="#ffffff"
   font="serif"
   
   

3. To apply additional CSS, you can inject it directly into your Streamlit Python script using the st.markdown function:

   st.markdown("""
       <style>
           /* Your custom CSS styles here */
       </style>
   """, unsafe_allow_html=True)

Explore the Application

Open your web browser and go to http://localhost:8501 to explore the different sections of the app. This web address works after you run the file using "streamlit run file_name.py"