Added price prediction model #46
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This model is made by collecting official data from government websites and based on rainfall and temperature it will predict the future price of commodities.
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@yashasvini121 Can you please review this and suggest me some improvements if required? |
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First of all, nice idea!! Your code seems great, but I believe, a few changes would make it better.
To implement the suggested changes, please follow these steps:
- Sync your fork and pull the branch accordingly.
- To update your code, you need to make the necessary modifications directly in your current working branch.
- Apply the changes as discussed in the reviews, following all the 🔴 Steps.
- Once you've made the changes and committed them, the pull request will automatically reflect the updates you've made.
According to me, these reviews should work and not give you any bugs. Let me know if you still get any errors while correcting the project structure.
| st.sidebar.markdown("<h2 style='color: #0056b3;'>User Inputs</h2>", unsafe_allow_html=True) | ||
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| with st.sidebar.expander("Select Parameters", expanded=True): | ||
| state = st.selectbox("Select State", ["Mumbai"], |
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🔴 Step 6:
Only a single state is available, see If you have any unused files, or options. Or maybe you plan on working on them later on.
Make the changes accordingly.
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🔴 Step 2:
This file is not being utilized anywhere, according to me. Please verify whether it should be removed.
Similarly check for the Mumbai_moong.py and Mumbai_urad.py files.
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This file is not being utilized anywhere. Please verify whether it should be removed.
There was a problem hiding this comment.
This file is not being utilized anywhere. Please verify whether it should be removed.
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🔴 Step 1:
- Please check if this file is being utilized anywhere in the project.
- Convert this file to CSV format because it is generally more efficient for data storage and compatibility with various data processing tools, and can be viewed by the developer easily.
- Update the relevant code in the project, where you are using
pd.read_excel()function.
This review is for all the files in data/
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🔴 Step 5:
To align the application with the project structure, please follow these steps:
- Change the file name from
app.pytoMumbai_Agriculture_Price_Prediction.py. - Transfer the renamed file to the
pages/folder. - Adjust the file paths for data files to reflect their new locations.
- Modify any module import paths as necessary to ensure they align with the new file structure.
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| # Load data | ||
| @st.cache_data | ||
| def load_data(file_path): |
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🔴 Step 3:
- Please move the specified code to a separate file within the existing folder to enhance modularity and maintainability in the codebase.
- Then update the module paths in
App.pyaccordingly to reflect the changes.
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| # Prediction logic | ||
| def predict_prices(df, commodity, days_to_predict, rainfall, temperature): |
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🔴 Step 4:
- Please move this code to a separate file within the existing folder to enhance modularity and maintainability in the codebase.
- Then update the module paths in
App.pyaccordingly to reflect the changes.
| @import url('https://fonts.googleapis.com/css2?family=Roboto:wght@400;500;700&display=swap'); | ||
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| .main { | ||
| background-image: url("https://wallpapercave.com/wp/wp9212753.jpg"); |
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🔴 Step 7:
See if the image is working out. If not then remove it.
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@StunningShield4504, updates? |
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@yashasvini121 Its done ill push it by tomorrow |
This model is made by collecting official data from government websites and based on rainfall and temperature it will predict the future price of commodities.Just we have to add it on the main page that ill do it in one or two days.