Tableau is a powerful data visualization and business intelligence tool that helps users to quickly analyze and visualize data from a variety of sources. It allows users to create interactive dashboards, charts, and graphs that are easy to understand, even for non-technical users. Tableau's drag-and-drop interface makes it easy to connect to data, create visualizations, and share insights with others. With its robust features, Tableau is widely used by businesses, analysts, and data scientists to make informed decisions based on data. In fact, there is even a Tableau visualization that demonstrates its purpose, showcasing its capabilities in analyzing data and creating dynamic visualizations.
The Tableau data visualization for flights in San Francisco in March 2020 provides an insightful look into the air traffic trends in the region. The graph showcasing flights per day highlights a steady increase in the number of flights during the first half of the month, with a peak on March 11th. This is followed by a sharp drop towards the end of the month, corresponding to the period when the COVID-19 pandemic began to intensify in the United States. The graph effectively portrays the impact of the pandemic on air travel in the region.
Another useful visualization in the dashboard is the route map that shows the destinations of flights originating from San Francisco. The map is color-coded to highlight the frequency of flights to each destination, with darker shades indicating higher frequency. The most frequent destinations are Los Angeles, New York, Seattle, and Las Vegas. Additionally, the graph depicting the distance between San Francisco and other destinations highlights that the majority of destinations are within a 2,000-mile range. This information can be useful for travelers and travel companies in determining the most popular routes and planning for future travel. Overall, the Tableau data visualization provides valuable insights into air travel trends in San Francisco in March 2020.
Power BI is a powerful business analytics tool developed by Microsoft that enables users to connect to a wide range of data sources, create interactive visualizations and reports, and share insights with others. With Power BI, users can easily transform raw data into visually appealing and insightful reports, charts, and graphs, allowing them to make data-driven decisions. The software's intuitive drag-and-drop interface and extensive library of pre-built visualizations make it easy for users to create customized and interactive dashboards. Moreover, Power BI allows users to collaborate with others by sharing reports and insights securely. In fact, there is even a Power BI visualization that demonstrates its purpose, showcasing its capabilities in analyzing data, creating interactive reports, and sharing insights with others.
Fortnightly Exchange
Sum of Aggregate Deposits by Year:
The graph on Sum of Aggregate Deposits by Year in India from 2017 to 2022 shows a steady increase in the amount of deposits made by individuals and institutions in Indian banks. The graph depicts that the total deposits in banks have increased from 122 trillion Indian rupees in 2017 to over 155 trillion Indian rupees in 2022. This upward trend indicates a growing confidence in the Indian banking sector, reflecting a positive outlook on the country's economic growth.
Sum of Bank Credit by Year:
The graph on Sum of Bank Credit by Year in India from 2017 to 2022 displays the amount of credit extended by Indian banks to individuals and businesses. The graph depicts a significant increase in bank credit over the years, reflecting a growing demand for credit in the country's expanding economy. From 2017 to 2022, bank credit increased from 68 trillion Indian rupees to over 100 trillion Indian rupees. This trend demonstrates a significant growth opportunity for Indian businesses and entrepreneurs, as access to credit has become more accessible.
Sum of Investment:
The graph on Sum of Investment in India from 2017 to 2022 provides insight into the country's investment trends over the years. The graph depicts a gradual increase in the amount of investments made in the Indian economy, reflecting a growing confidence among investors. The total investment has increased from 33 trillion Indian rupees in 2017 to over 47 trillion Indian rupees in 2022, indicating a positive sentiment towards India's economic growth prospects.
Graph on M3:
The graph on M3 in India from 2017 to 2022 shows the trend in the country's money supply over the years. M3 is a measure of the total money supply in an economy, including currency in circulation, deposits, and other liquid assets. The graph depicts a steady increase in M3 in India from 2017 to 2022, reflecting a growing economy and an increase in money circulation. This trend is indicative of a positive outlook on India's economic growth, as a growing money supply provides greater opportunities for investment and growth.
Monthly Exchange
Sum of GDP at Market Prices:
The graph on the Sum of GDP at Market Prices in India from 2017 to 2022 provides an overview of the country's economic growth over the years. The graph shows a steady increase in GDP from 124.9 trillion Indian rupees in 2017 to over 204 trillion Indian rupees in 2022. This upward trend is indicative of a growing economy with an increasing GDP, and is a positive indicator for investors and businesses operating in the Indian market.
Sum of Overall Balance of Payment Net:
The graph on the Sum of Overall Balance of Payment Net in India from 2017 to 2022 shows the country's overall balance of payments position. The balance of payments is a measure of all economic transactions between a country and the rest of the world, including imports and exports of goods and services, and capital flows. The graph indicates that India has maintained a positive balance of payments position over the years, indicating that the country's exports are greater than its imports. This trend is an indication of a growing and competitive economy.
Sum of International Investment Position:
The graph on the Sum of International Investment Position in India from 2017 to 2022 provides an overview of the country's international investment position over the years. The graph shows a steady increase in the country's international investment position from -34.8 trillion Indian rupees in 2017 to over 18.2 trillion Indian rupees in 2022. This upward trend is indicative of an increase in foreign investment in India and highlights the country's potential as an investment destination.
Sum of GDP at Market Prices:
The graph on the Sum of GDP at Market Prices in India from 2017 to 2022 provides insight into the country's economic growth over the years. The graph depicts a steady increase in GDP from 124.9 trillion Indian rupees in 2017 to over 204 trillion Indian rupees in 2022. This upward trend indicates a growing economy with an increasing GDP, which is a positive indicator for businesses and investors operating in India. The graph highlights the country's potential for sustained economic growth and its potential as an attractive investment destination.
Quarterly Exchange
Sum of Exchange rate between INR and USD by Foreign Direct Investment:
The graph on the Sum of Exchange rate between INR and USD by Foreign Direct Investment in India from 2017 to 2022 provides insight into the country's foreign direct investment trends over the years. The graph depicts a steady increase in the exchange rate between INR and USD as a result of foreign direct investment. This trend is indicative of a growing confidence among foreign investors in the Indian economy and highlights the country's potential as an attractive investment destination.
Sum of Exchange rate between INR and USD by NET Foreign Direct Investment:
The graph on the Sum of Exchange rate between INR and USD by NET Foreign Direct Investment in India from 2017 to 2022 provides an overview of the country's foreign direct investment trends over the years. The graph shows a steady increase in the exchange rate between INR and USD due to the net inflow of foreign direct investment. This trend is indicative of an increase in foreign investments and highlights the country's potential as a hub for foreign direct investment.
Sum of Exchange rate between INR and USD by Foreign Trade Exports Total:
The graph on the Sum of Exchange rate between INR and USD by Foreign Trade Exports Total in India from 2017 to 2022 provides insight into the country's foreign trade and export trends over the years. The graph depicts a steady increase in the exchange rate between INR and USD due to the total value of foreign trade exports. This trend is indicative of an increase in foreign trade and highlights the country's potential as a hub for international trade.
Sum of Exchange rate between INR and USD by Total Investment Flows:
The graph on the Sum of Exchange rate between INR and USD by Total Investment Flows in India from 2017 to 2022 provides an overview of the country's investment trends over the years. The graph shows a steady increase in the exchange rate between INR and USD due to total investment flows. This trend is indicative of an increase in overall investment in the Indian economy and highlights the country's potential as an attractive investment destination.
Weekly Exchange
The graphs on the Sum of bank rates and exchange reserves in India from 2017 to 2022 provide insights into the country's monetary policy and foreign exchange reserves. The graph on the Sum of bank rates depicts the trend of the bank rates over the years, which can be useful for assessing the impact of monetary policy on the economy. The graph on the Sum of exchange reserves provides an overview of the country's foreign exchange reserves, which is an important indicator of the country's ability to meet its external obligations. Together, these graphs can provide a comprehensive understanding of the country's monetary policy and its ability to manage external financial risks.
Gephi is an open-source network analysis and visualization software that allows users to explore, analyze, and visualize complex network data. It is widely used by researchers, data scientists, and analysts to gain insights into social networks, biological networks, and other types of complex systems. Gephi provides a range of tools and features for network analysis, including the ability to import data from various sources, analyze network structure, and apply different layouts and algorithms to visualize the network. It also supports a range of graph formats, including directed and undirected graphs, and can handle large datasets with ease.
To demonstrate the purpose of Gephi, a visualisation could be created using real-world data, such as social media interactions or website traffic. The visualisation could show the relationships between different nodes in the network, such as users or web pages, and highlight patterns and trends in the data
Nodes after calculation of Between Centrality
Betweenness centrality is a fundamental measure of network centrality in network analysis, and it is one of the many centralities that can be computed in Gephi. Betweenness centrality measures the number of times a node acts as a bridge along the shortest path between two other nodes in the network. This measure is particularly useful for identifying the most important or influential nodes in the network, as nodes with high betweenness centrality are often critical to maintaining connectivity and facilitating communication between other nodes.
In Gephi, betweenness centrality can be computed using various algorithms, including Brandes' algorithm and Newman's algorithm, and the results can be visualized using different layouts and node coloring schemes. Users can also use the betweenness centrality measure to filter or rank nodes based on their importance in the network, making it easier to identify key players or influential groups.
MODULARITY PARTITIONING
In Gephi, the modularity partitioning function can be used to identify and visualize communities in a network based on their modularity score. The function uses a range of algorithms, including the Louvain method, to optimize the modularity score and partition the network into distinct communities. Users can also adjust the resolution parameter to control the granularity of the community detection and refine the results.
GeoLayout Application
Geolayout is a layout algorithm available in Gephi that is specifically designed for visualizing geographic networks. This algorithm maps nodes in the network to geographic locations based on latitude and longitude coordinates, allowing users to create interactive and dynamic maps that display the spatial relationships between nodes.
Gephi Final Result
The final result depict the nodes placed on the Map for which the points were being separated and classified. Overall, Overall, the geolayout function is a powerful tool for creating dynamic and interactive geographic network visualizations, and it can be a valuable addition to any network analysis toolkit.
A choropleth map is a type of map that uses color to represent different values of a given variable across a geographic area. In D3.js, a popular JavaScript library for data visualization, choropleth maps can be created using geoJSON data and SVG elements.
(Hover over the countries to see their status)
A choropleth map can be a powerful tool for visualizing and comparing data across geographic regions. In the above visualisation, a choropleth map can be used to show the level of economic development across different countries or regions of the world. In this type of map, countries or regions are grouped into categories such as developed, developing, and underdeveloped based on a set of criteria. Each category is assigned a different color on the map, allowing viewers to easily see the distribution of economic development across the world. The map can also be interactive, allowing users to zoom in on specific regions or hover over countries to see more detailed information.
Global GDP and CO2 emissions are two interconnected aspects of the global economy that have significant effects and consequences on the environment. The growth of global GDP has been a driving force behind the increase in carbon emissions, which in turn have had severe consequences for the environment, including global warming, climate change, and environmental degradation. This essay will explore the correlation between global GDP and CO2 emissions, the effects and consequences of high CO2 emissions, and the measures that can be taken to mitigate these effects.
The correlation between global GDP and CO2 emissions is clear. As countries become more industrialized and their economies grow, the demand for energy increases, leading to an increase in carbon emissions. According to the World Bank, the global GDP has increased from $42.2 trillion in 1990 to $87.7 trillion in 2019. This significant increase in the global GDP has led to an increase in carbon emissions, which have risen from 22.9 billion metric tons in 1990 to 36.4 billion metric tons in 2019.
