Minimum Wages in Angola remained unchanged at 32181.15 AOA/Month in 2025 from 32181.15 AOA/Month in 2024. This dataset provides - Angola Minimum Wages- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Angola AO: Law Mandates Equal Remuneration for Females & Males for Work of Equal Value: 1=Yes; 0=No data was reported at 1.000 NA in 2018. This stayed constant from the previous number of 1.000 NA for 2017. Angola AO: Law Mandates Equal Remuneration for Females & Males for Work of Equal Value: 1=Yes; 0=No data is updated yearly, averaging 1.000 NA from Dec 2009 (Median) to 2018, with 10 observations. The data reached an all-time high of 1.000 NA in 2018 and a record low of 1.000 NA in 2018. Angola AO: Law Mandates Equal Remuneration for Females & Males for Work of Equal Value: 1=Yes; 0=No data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Angola – Table AO.World Bank.WDI: Governance: Policy and Institutions. Law mandates equal remuneration for females and males for work of equal value is whether there is a law that obligates employers to pay equal remuneration to male and female employees who do work of equal value.“Remuneration” refers to the ordinary, basic or minimum wage or salary and any additional emoluments payable directly or indirectly, whether in cash or in kind, by the employer to the worker and arising out of the worker’s employment. “Work of equal value” refers not only to the same or similar jobs but also to different jobs of the same value.; ; World Bank: Women, Business and the Law.; ;

Angola AO: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 22.800 % in 2018. This records an increase from the previous number of 17.200 % for 2008. Angola AO: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 22.800 % from Dec 2000 (Median) to 2018, with 3 observations. The data reached an all-time high of 23.500 % in 2000 and a record low of 17.200 % in 2008. Angola AO: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Angola – Table AO.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

This is a very small project that focus on yearly sales (real data that went through slightly modifications)of a company's two different stores. This stores are located in different areas of the city (Huambo, Angola) where one is in the main shopping center and the other one 13 miles from the city center. In this table you will find the mobiles brand, name, colour, battery in mAh, prices, sales per store and other features.

Although Angola is one of the most expensive countries to live in, the minimum wage is very low at about 35,000kz which is 54USD roughly.

The objective of this project is to calculate and compare how much each store sold in total, by brand and how much the company made in that year. By managing the data itself, conclusions can be drawn and assumptions can be made. However, test yourself and do Machine Learning to predict the future sales considering factores like minimum country wage, phone upgrades resulting in new phones and lower prices for the existing models, the location of the store, etc.