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To visually explore and analyze PhonePe Pulse data, aiming to understand trends and patterns easily, facilitating better decision-making and strategic planning.

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ChemoshTony/Phonepe-Pulse-Data-Visualization-and-Exploration

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Phonepe_Pulse_DataVisualization_and_Exploration

Phonepe Pulse Data Visualization and Exploration: A User-Friendly Tool Using Streamlit and Plotly DATA SOURCE - https://github.com/PhonePe/pulse.git

  1. Data extraction: Clone the Github using scripting to fetch the data from the Phonepe pulse Github repository and store it in a suitable format such as CSV or JSON.

  2. Data transformation: Use a scripting language such as Python, along with libraries such as Pandas, to manipulate and pre-process the data. This may include cleaning the data, handling missing values, and transforming the data into a format suitable for analysis and visualization.

  3. Database insertion: Use the "mysql-connector-python" library in Python to connect to a MySQL database and insert the transformed data using SQL commands.

  4. Dashboard creation: Use the Streamlit and Plotly libraries in Python to create an interactive and visually appealing dashboard. Plotly's built-in geo map functions can be used to display the data on a map and Streamlit can be used to create a user-friendly interface with multiple

  5. Data retrieval: Use the "mysql-connector-python" library to connect to the MySQL database and fetch the data into a Pandas dataframe. Use the data in the dataframe to update the dashboard dynamically.

  6. Deployment: Ensure the solution is secure, efficient, and user-friendly. Test the solution thoroughly and deploy the dashboard publicly, making it accessible to users.

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To visually explore and analyze PhonePe Pulse data, aiming to understand trends and patterns easily, facilitating better decision-making and strategic planning.

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