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Developed a Streamlit application for analyzing transactions and user data from the Pulse dataset. Explored data insights on states, years, quarters, districts, transaction types, and brands through EDA. Visualized trends and patterns using plots and charts to optimize decision-making in the Fintech industry.
Problem Statement: The Phonepe pulse Github repository contains a large amount of data related to various metrics and statistics. The goal is to extract this data and process it to obtain insights and information that can be visualized in a user-friendly manner.
We introduce an open-source web platform we have developed to enable users to view and compare the radial profiles of land artificialization for 785 major European cities in 2018.
This public repository contains a fully functional AtlasCine template. You will also find all documentation related to Atlascine's use and deployment in this repository's wiki.
Utilized R to analyze data from Chicago, focusing on healthcare infrastructure and socioeconomic factors. Geo-visualized city metrics to reveal areas with shared socioeconomic attributes. Identified spatial patterns linking health outcomes with socioeconomic conditions, offering a comprehensive view of community health across the city.
[ Phonepe Pulse Data Visualization dependence on given specifications. ] | ( Disclaimer: Transaction and user analysis of Phonepe app in INDIA 2018 - 2022 only ) | Clone | Python | Pandas | Numpy | MySQL | Streamlit | Plotly | Geo visualization |
[ Phonepe Pulse Data Visualization dependence on given specifications. ] | ( Disclaimer: Transaction and user analysis of Phonepe app in INDIA 2018 - 2022 only ) | Clone | Python | Pandas | Numpy | MySQL | Streamlit | Plotly | Geo visualization |
[ Phonepe Pulse Data Visualization dependence on given specifications. ] | ( Disclaimer: Transaction and user analysis of Phonepe app in INDIA 2018 - 2022 only ) | Clone | Python | Pandas | Numpy | MySQL | Streamlit | Plotly | Geo visualization |