R-Workspace containing two customized functions for plotting,

- grid_arrange_shared_legend taken from: https://github.com/tidyverse/ggplot2/wiki/Share-a-legend-between-two-ggplot2-graphs

- multiplot taken from: http://www.cookbook-r.com/Graphs/Multiple_graphs_on_one_page_%28ggplot2%29/

#

and three data.frames:

- mdat: Raw data of mothers, includimng founder generation (N = 15961, extracted from the Krummhörn pedigree containing 74639 individuals)

- mdat0: Study sample including only mothers with minimum pedigree depth of 4 (N = 6447)

- mdat1: Data set of mothers for which all grandparents of them and their partner(s) are known (N = 2321)

with the variables:

$ momid : num ID of mother

$ incl : num 1 if included in data set of known mothers, otherwise 0

$ SES : Factor for socioeconomic status (4 levels: "Unknown", "Landless", "small to medium scale farmers", "large scale farmers")

$ minByear : num Birth year of 1st born child

$ maxByear : num Birth year of last born child

$ minDepth : num Pedigree depth as the generation number of known ancestors

$ Fmean : num Inbreeding coefficient F (as calculated by pedigree::calcInbreeding())

$ cons : num 1 if consanguineous (i.e. F>=0.0156), otherwise 0

$ cousMarr : num 1 if in 1st cousin marriage (i.e. F~0.0625), otherwise 0

$ consanguinity : Factor for consanguinity (3 levels: "low (<0.0156)", "medium (>=0.0156)", "high (1st cousins)")

$ docGrasenMean : num Mean number of grasen within a mother's founded families

$ eltnrfGrasenMean : num Number of grasen within the mother's family-of-origin

$ eltnrmGrasenMean : num Mean number of grasen within the mother's partner(s)' family/ies-of-origin

$ mlocal : chr Code of the Kirchspiel, in which the mother was first married

$ decade : Factor fot the decade in which the mother's first marriage occured (28 levels)

$ cross : num 1 if identified as cross-cousin marriage, otherwise 0

$ paral : num 1 if identified as parallel cousin marriage, otherwise 0

Comprehensive dataset of 2 Mobile money agents in Cuenca, Spain as of August, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 2 Mobile money agents in Czech Republic as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 2 Money transfer services in สระบุรี, Thailand as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 2 Money transfer services in Cork, Ireland as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 2 Money order services in Province of Ancona, Italy as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset containing 3 verified Mobile money agent businesses in Metropolitan City of Florence, Italy with complete contact information, ratings, reviews, and location data.

this graphs is ourdataworld :

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F00b0f9cc2bd8326c60fd0ea3b5dbe4b7%2Finequality.png?generation=1710013947537354&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F1978511abe249d3081a3a95bae2ef7d5%2Fincome-share-top-1-before-tax-wid-extrapolations.png?generation=1710013977201099&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F2a5a54725f65801ba75b6ab07bc5cb9f%2Fincome-share-top-1-before-tax-wid-extrapolations%20(1).png?generation=1710013994341360&alt=media" alt="">

How are incomes and wealth distributed between people? Both within countries and across the world as a whole?

On this page, you can find all our data, visualizations, and writing relating to economic inequality.

This evidence demonstrates that inequality in many countries is substantial and, in numerous instances, has been escalating. Global economic inequality is extensive and exacerbated by intersecting disparities in health, education, and various other dimensions.

However, economic inequality is not uniformly increasing. In many countries, it has declined or remained steady. Furthermore, global inequality – following two centuries of ascent – is presently decreasing as well.

The significant variations observed across countries and over time are pivotal. They indicate that high and rising inequality is not inevitable and that the current extent of inequality is subject to change.

About this data This data explorer offers various inequality indicators measured according to two distinct definitions of income sourced from different outlets.

Data from the World Inequality Database pertains to inequality prior to taxes and benefits. Data from the World Bank pertains to either income post taxes and benefits or consumption, contingent on the country and year. For additional details regarding the definitions and methodologies underlying this data, refer to the accompanying article below, where you can also delve into and juxtapose a broader spectrum of indicators from various sources.