seanie5011 / streamlit_randomapps

A collection of various apps created using Streamlit, a web-app Python framework.

Streamlit_RandomApps

This project contains various web-apps created using Streamlit

This project is an umbrella containing various web-apps using Streamlit. These are mostly small apps, with only few functions. They are listed as follows:

1. ExcelDashboard
2. SalaryPrediction
3. AllStreamlitWidgets

User Instructions

ExcelDashboard

This app displays various features of a typical Sales Report Excel Spreadsheet - by collecting data using openpyxl and pandas, such as Total Sales, Average sales per transaction, etc. It uses plotly-express to display plots of Total Sales by hour, and Sales by product line. There is features to filter by city, customer-type, and gender - which is updated in real-time.

The Excel Spreadsheet used is supplied, supermarkt_sales.xlsx.

LIBRARIES USED: streamlit, plotly-express, pandas, openpyxl

SalaryPrediction

This app allows the user to predict the expected salary of a Software Developer, given inputs like the Country, Education Level, and Years of Experience. The machine-learning model was created using scikit-learn, trained on data from the Stack Overflow Software Developer Survey 2022. This is a survey collecting relevant data from over 74k participants, as such, pandas was used to help with data handling and pre-processing. Some data-visualisation of the Salary vs Other Parameters was created using Matplotlib.

This app requires the user to download the survey file from the link above, and move the survey_results_public.csv file into the directory of this project. The user will have to run the SalaryPrediction.py file using the steps below to create a .pkl file which contains the Prediction model. Finally, the user can run the app.py file as below.

LIBRARIES USED: streamlit, scikit-learn, matplotlib, pandas, numpy

AllStreamlitWidgets

This app contains all streamlit widgets (within reasonable use). It does not contain explanations of all these widgets, it is simply meant to be a display of these as a way to learn what streamlit has to offer.

Helper files are supplied which are used, the user must download these.

LIBRARIES: streamlit, pandas, numpy, altair, plotly-expressm matplotlib

User Instructions

1. Clone this project
2. Create a virtual enviroment to be used, ideally in the same folder as this project
3. Install the necessary libraries as detailed, using pip
   pip install *library*
   Note: ensure protobuf is of version 3.20.x or lower; using pip install --upgrade protobuf==3.19.0
4. Open the terminal in the directory of the desired script (CTRL + L, type cmd), or cd into it
5. Activate the Virtual Enviroment *venv*\Scripts\activate
6. Run the script using Streamlit streamlit run *file*.py
   Note: To close the app, CTRL + C on the terminal then close the browser