Yes Data @yesdata_

Data-driven visuals and statistics focused on economics, health or human resources. Tools in posts, all visuals are original. 📊🗺️📸 buymeacoffee.com/yesdata_ France Joined July 2023

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Yes Data @yesdata_

9 months ago

🐔 Series: Chicken Density (No. 3) - Indonesia Indonesia has a massive chicken population, supporting its huge poultry industry. 🔧 Tools: Python (Rasterio, Geopandas, Shapely)

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Yes Data @yesdata_

9 months ago

🚗 Series: Roads (No. 6) - India India's 6.3 million km road network, the world's second largest, connects cities and villages, driving economic growth. 🔧 Tools: Python (Pandas, Geopandas, Matplotlib)

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Simon Kuestenmacher @simongerman600

9 months ago

This map by @yesdata_ shows the population density across North America.

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🗺️ Series: Population Density (No. 12) - North America North America's population density averages about 22 people per square kilometer, with significant regional variations. 🔧 Tools: Python (Rasterio, Geopandas, Shapely)

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Yes Data @yesdata_

9 months ago

🚗 Series: Roads (No. 5) - Thailand Thailand's road network connects Bangkok to regional centers with major highways, while rural roads vary in quality. 🔧 Tools: Python (Pandas, Geopandas, Matplotlib)

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Yes Data @yesdata_

10 months ago

🗺️ Series: Population Density (No. 11) - South America South America's population density is starkly uneven, clustering in cities while thinning out in rural and wilderness areas. 🔧 Tools: Python (Rasterio, Geopandas, Shapely)

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Yes Data @yesdata_

10 months ago

🐮 Series: Cattle Density (No. 5) - India India has one of the highest cattle densities globally due to its large bovine population and limited agricultural land. 🔧 Tools: Python (Rasterio, Geopandas, Shapely)

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Yes Data @yesdata_

10 months ago

🗺️ Series: UNESCO World Heritage Sites (No. 4) - North America North America hosts UNESCO World Heritage Sites like Yellowstone and Chichen Itza, valued for their natural and cultural significance. 🔧 Tools: Python (Geopandas, Shapely, Contextily)

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Yes Data @yesdata_

10 months ago

👨‍🌾 Series: HDI (No. 6) - North America The Human Development Index assesses development via health, education, and living standards. The dataset contains anomalies. Values are estimates. 🔧 Tools: Python (Rasterio, Rioxarray, Shapely)

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Yes Data @yesdata_

10 months ago

🧯 Series: Fires (No. 4) - Japan NASA uses its satellites to detect sources of heat on Earth. This map shows 2023 signals. It only shows 'type 0' heat sources (presumed vegetation fire) with confidence 'h' (high). 🔧 Tools: Python (Geopandas, Shapely, Contextily)

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Yes Data @yesdata_

11 months ago

💧 Series: Rivers (No. 5) - Germany Germany's river system, including major rivers like the Rhine, Danube, and Elbe, plays a vital role in transportation, trade, and supporting diverse ecosystems across the country. 🔧 Tools: Python (Pandas, Geopandas, Shapely)

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Yes Data @yesdata_

11 months ago

☔️ Series: Rainfall (No. 5) - Africa Africa's precipitation varies widely, with tropical regions like Central Africa receiving heavy rainfall, while vast deserts like the Sahara experience minimal precipitation. 🔧 Tools: Python (Rasterio, Rioxarray, Geopandas)

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Yes Data @yesdata_

11 months ago

💧 Series: Rivers (No. 4) - Türkiye Türkiye's river system includes major rivers like the Euphrates, Tigris, and Kızılırmak, which flow through diverse landscapes, supporting agriculture, hydropower, and ecosystems. 🔧 Tools: Python (Pandas, Geopandas, Shapely)

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Yes Data @yesdata_

11 months ago

🗺️ Series: UNESCO World Heritage Sites (No. 3) - D.R. Congo The D.R. Congo is home to five UNESCO World Heritage Sites, including Virunga National Park, known for its diverse ecosystems and endangered mountain gorillas. 🔧 Tools: Python (Geopandas, Shapely, Contextily)

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Yes Data @yesdata_

12 months ago

💧 Series: Rivers (No. 3) - Nigeria Nigeria's Niger and Benue rivers form a vital confluence at Lokoja, driving ecosystems and culture. 🔧 Tools: Python (Pandas, Geopandas, Shapely)

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Yes Data @yesdata_

12 months ago

👨‍🌾 Series: HDI (No. 5) - Brazil The Human Development Index assesses development via health, education, and living standards. The dataset contains anomalies. Values are estimates. 🔧 Tools: Python (Rasterio, Rioxarray, Shapely)

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Yes Data @yesdata_

a year ago

🚗 Series: Roads (No. 4) - Czechia Czechia's road network is extensive and well-maintained, with a radial structure centered around Prague and ongoing modernization efforts. 🔧 Tools: Python (Pandas, Geopandas, Matplotlib)

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Simon Kuestenmacher @simongerman600

a year ago

Holy cow! South Asia’s cattle density really is highest in India. HT @yesdata_ (give them a follow)

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Simon Kuestenmacher @simongerman600

a year ago

Wonderfully detailed map shows the Human Development Index across Europe. Concentration of development in Central Europe generally and within the big cities within each individual country. HT @yesdata_