Peru Analytics
LANGUAGES
- Official Language:
- 1. Peruvian Spanish
: 29,000,000
- 2. Spanish
: 28,891,000
Mother Tongue : Peruvian Spanish
Literacy Rate (%) : 94.5
Country Capital | : | Yaren |
---|---|---|
GDP Per capita | : | 7,239 |
GDP Per Capita Rank | : | 88th/195 |
Life Expectancy | : | 72 |
Unemployment Rate | : | 6 |
Number of Internet Users | : | 24,140,000 |
Internet Users Rank | : | 36th/195 |
Area | : | 19 |
Area Rank | : | 193rd/195 |
Total Population | : | 33,715 |
Total Population Rank | : | 44th/195 |
Continent: South America
Peru Highlights
Peru is the 44th ranked country in population and 193rd ranked in area out of 195 countries in the world.Please keep the country rank in perspective, for the highlights below.
Better than World Average-
- 1. Peru is the 2nd highest ranked in Copper prod. out of 195 countries in the world. This implies that the country has a robust Electrical/Electronics industry or be a huge exporter of such products or resources.
- 2. The average Zinc prod. of 195 countries in the world is 1,007,000. Peru is the 2nd highest ranked country out of 195 countries. This implies that the country has a robust battery production industry or be a huge exporter of Zinc.
- 3. Out of the 195 countries in the world, Peru is the 3rd highest ranked in Silver prod. . This implies that the country has higher foreign earnings through Silver exports or indicate higher economic growth potential.
Worse than World Average-
- 1. Peru is the 41st worst ranked in #Dentists out of 195 countries in the world. This may indicate worse healthcare infrastructure investment by the country or may indicate lower population
- 2. The average Pharmacists (Per 10,000) of the countries in the world is 4. Peru is the 87th worst-ranked country out of 195 countries. This may indicate worse healthcare infrastructure investment by the country or may indicate lower population.
- 3. Out of the 195 countries in the world, Peru is the 91st worst ranked in Total No. of Pharmacists . This may indicate worse healthcare infrastructure investment by the country or may indicate lower population
Peru Metrics
Language Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | Ashaninka | # People | 106 | 1 | 1127 | ||
2 | Peruvian Spanish | # People | 148,717 | 1 | 1130 | ||
3 | Quechua | # People | 43,743 | 1 | 1130 | ||
4 | Ashaninka as a % of total Ashaninka speakers | % People | 0 | 1 | 1127 | ||
5 | Peruvian Spanish as a % of total Peruvian Spanish speakers | % People | 0 | 1 | 1128 | ||
6 | Quechua as a % of total Quechua speakers | % People | 0 | 1 | 1129 | ||
7 | Aymara | # People | 11,945 | 2 | 1125 | ||
8 | Aymara as a % of total Aymara speakers | % People | 0 | 2 | 1129 | ||
9 | Spanish | # People | 2,344,008 | 6 | 1130 | ||
10 | Spanish as a % of total Spanish speakers | % People | 0 | 6 | 1126 | ||
Below than World Average- |
|||||||
1 | Standard Chinese as a % of total Standard Chinese speakers | % People | 0 | 15 | 1233 | ||
2 | Standard Chinese | # People | 6,821,357 | 17 | 1233 |
Urbanization Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | 10M+ Cities Ratio ( 10M+ Cities/ # Cities> 100000) | 0 | 1 | 1129 | |||
2 | # Cities>10M | # Cities | 0 | 4 | 1130 | ||
3 | # Cities>5M | # Cities | 0 | 9 | 1125 | ||
4 | # Cities>5M | # Cities | 0 | 11 | 1130 | ||
5 | Urban Population (2021) | # People | 22,563,215 | 33 | 1127 | ||
6 | # Cities>300000 | # Cities | 7 | 34 | 1128 | ||
7 | # Cities>300000 | # Cities | 8 | 38 | 1127 | ||
8 | # Cities>100000 | # Cities | 21 | 39 | 1125 | ||
9 | Urban Population / Total Population % . | % People | 59 | 50 | 1129 | ||
10 | Pop. with access to Electricity (%) | % People | 85 | 125 | 1129 | ||
Below than World Average- |
|||||||
1 | Rural Pop. /Total Pop. % | % People | 41 | 148 | 1230 | ||
2 | # Cities>1M | # Cities | 2 | 46 | 1234 | ||
3 | 1M+ Cities per 100000 ( 1M+ Cities/ Tot Pop.)* 100000 | 0 | 95 | 1230 | |||
4 | 1M+ Cities Ratio ( 1M+ Cities/ # Cities> 100000) | 0 | 94 | 1235 | |||
5 | # Cities>1M | # Cities | 1 | 39 | 1235 | ||
6 | Rural Pop. | # People | 18,013,759 | 70 | 1233 | ||
7 | # Cities>500000 | # Cities | 5 | 38 | 1231 | ||
8 | # Cities>500000 | # Cities | 4 | 36 | 1232 | ||
9 | # Cities>100000 | # Cities | 23 | 39 | 1231 |
Wealth Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | Corporate Tax Rates in % | Rate | 23 | 2 | 1128 | ||
2 | Import Ban(Number of products) | Count | 12 | 23 | 1130 | ||
3 | FDI (millions USD) | Amount | 7,895 | 33 | 1127 | ||
4 | FDI / Total FDI of the World %. | 0 | 33 | 1130 | |||
Below than World Average- |
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1 | Imports /Total GDP of the Country %. | 52 | 123 | 1232 | |||
2 | Exports/Total GDP of the Country %. | 45 | 106 | 1234 | |||
3 | GDP Per Capita (USD) | $ | 18,253 | 88 | 1233 | ||
4 | Import of Goods and Services (in Million $) | Amount | 182,282 | 54 | 1234 | ||
5 | Imports/Total Imports of the World %. | 0 | 54 | 1234 | |||
6 | GDP (Billions USD) 2022 | $ Billions | 531 | 49 | 1235 | ||
7 | Export of Goods and Services (in Million $) | Amount | 184,833 | 49 | 1230 | ||
8 | GDP as a % of Total GDP | Percent | 0 | 49 | 1235 | ||
9 | Exports /Total Exports of the World %. | 0 | 48 | 1231 | |||
10 | No. of Companies Listed in NYSE | Count | 65 | 24 | 1234 |
Nature Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | Copper prod. | Weight | 1,350 | 2 | 1127 | ||
2 | Zinc prod. | Weight | 1,007,000 | 2 | 1129 | ||
3 | Copper Produced /Total Copper Produced % | Weight | 9 | 2 | 1127 | ||
4 | Zinc Produced/Total Zinc Produced %. | Weight | 9 | 2 | 1128 | ||
5 | Silver prod. | Weight | 1,980 | 3 | 1126 | ||
6 | Silver Produced/Total Silver Produced % | Weight | 9 | 3 | 1125 | ||
7 | Forest Area. | Area | 21,142,892 | 9 | 1129 | ||
8 | Country forest area / Global Forest area % | 0 | 9 | 1130 | |||
9 | Number of Trees | Count | 15,642,617,148 | 13 | 1126 | ||
10 | Potatoes Produced /Total Potatoes Produced % | Weight | 0 | 13 | 1129 | ||
11 | Potatoes prod. | Weight | 2,516,782 | 14 | 1128 | ||
12 | Tree density . | Density | 828 | 26 | 1125 | ||
13 | Tree density. | Density | 22,685 | 57 | 1130 | ||
Below than World Average- |
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1 | Soyabean prod. | Weight | 3,628,152 | 79 | 1232 | ||
2 | Wheat prod. | Weight | 6,681,335 | 73 | 1230 | ||
3 | Wheat Produced /Total Wheat Produced. %. | Weight | 0 | 68 | 1230 | ||
4 | Honey Produced /Total Honey Produced % | Weight | 0 | 67 | 1234 | ||
5 | Honey prod. | Weight | 14,821 | 67 | 1231 | ||
6 | Oil Prod. | 4,369,531 | 52 | 1235 | |||
7 | Oil Prodcuced/Total Oil Produced % | 5 | 52 | 1232 | |||
8 | Barley prod. | Weight | 1,558,004 | 48 | 1231 | ||
9 | Barley Produced/Total Barley Produced.% | Weight | 1 | 47 | 1232 | ||
10 | Natural Gas Prod. | Mass | 216,389 | 38 | 1232 | ||
11 | Natural Gas Produced/Total Natural Gas Produced % | Mass | 5 | 38 | 1232 | ||
12 | Sweet Potatoes prod. | Weight | 833,178 | 29 | 1230 | ||
13 | Sweet Potatoes Produced/Total Sweet Potatoes Produced % | Weight | 0 | 29 | 1231 | ||
14 | Rice Produced/Total Rice Produced.% | Weight | 0 | 20 | 1234 | ||
15 | Rice prod. | Weight | 6,871,329 | 20 | 1233 | ||
16 | Gold Prod. | Weight | 125 | 9 | 1233 | ||
17 | Gold Produced/Total Gold Produced %. | 4 | 9 | 1233 | |||
18 | Mercury prod. | Weight | 564 | 4 | 1232 | ||
19 | Tin prod. | Weight | 23,069 | 4 | 1232 | ||
20 | Mercury Produced/Total Mercury Produced % | Weight | 14 | 4 | 1230 | ||
21 | Tin Produced/Total Tin Produced in 2019 | Weight | 7 | 4 | 1235 |
--- Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | Christian Pop./Total Pop.% | % People | 42 | 15 | 1127 | ||
2 | Christian Pop./Total Christian Pop.% | % People | 0 | 22 | 1126 |
Internet Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | FB Users / Total Int. Users %. | % People | 76 | 16 | 1128 | ||
2 | LinkedIn users | # People | 5,792,754 | 22 | 1129 | ||
3 | LinkedIn Users as a % of Total LinkedIn Users | # People | 0 | 22 | 1128 | ||
4 | Facebook users | # People | 17,943,893 | 28 | 1130 | ||
5 | FB Users / Total Pop. %. | % People | 60 | 32 | 1125 | ||
6 | LinkedIn Users as a % of Total Internet Users | # People | 34 | 50 | 1128 | ||
7 | Int. Users / Total Pop.% | % People | 66 | 106 | 1125 | ||
Below than World Average- |
|||||||
1 | Twitter Users as a % of Total Internet Users | # People | 16 | 96 | 1235 | ||
2 | Twitter Users as a % of Total Population | # People | 14 | 94 | 1235 | ||
3 | LinkedIn Users as a % of Total Population | # People | 29 | 60 | 1234 | ||
4 | Internet Users | # People | 25,030,008 | 36 | 1234 | ||
5 | Twitter users | # People | 3,240,046 | 34 | 1235 | ||
6 | Twitter Users as a % of Total Twitter Users | # People | 0 | 34 | 1232 |
Health Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | HIV Infections (Per 1000) | People Per 1,000 | 0 | 18 | 1129 | ||
2 | Life Expectancy at Birth, both sexes | Age | 71 | 91 | 1128 | ||
3 | No. of people HIV infected/Total pop. | # People | 11,349 | 14 | 1130 | ||
Below than World Average- |
|||||||
1 | Dentist (per 10,000) | People per 10000 | 31 | 166 | 1230 | ||
2 | #Dentists | # People | 13,328 | 155 | 1233 | ||
3 | Pharmacists (Per 10,000) | People Per 10,000 | 4 | 108 | 1230 | ||
4 | Nurses to doctor ratio | Ratio | 2 | 106 | 1230 | ||
5 | Total No. of Pharmacists | # People | 14,339 | 105 | 1230 | ||
6 | Nurses(per 10000) | People per 10000 | 44 | 98 | 1233 | ||
7 | Doctors (Per 10,000) | People Per 10,000 | 20 | 96 | 1230 | ||
8 | Total Nursing | # People | 163,061 | 46 | 1232 | ||
9 | Total No. of Doctors | # People | 73,975 | 38 | 1235 |
Culture Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | Christian Population | # People | 11,763,461 | 22 | 1129 | ||
2 | World Heritage Sites | Count | 7 | 24 | 1127 | ||
Below than World Average- |
|||||||
1 | Islamic Population | # People | 9,744,062 | 166 | 1233 | ||
2 | # Olympic Medals | Count | 126 | 87 | 1234 | ||
3 | Total Medals | Count | 12 | 68 | 1231 | ||
4 | Bronze Medal | Count | 4 | 49 | 1234 |
Work Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | Labour Force Participation | # People | 11,624,528 | 24 | 1126 | ||
2 | Total Labour Force/Total Pop. | % People | 43 | 27 | 1126 | ||
3 | Employment in Services | # People | 9,747,273 | 36 | 1130 | ||
4 | Employment in Agriculture /Total Pop. %. | % People | 9 | 49 | 1130 | ||
5 | Employment in Services /Total pop.%. | % People | 24 | 67 | 1127 | ||
6 | Employment in Agri. / Total Labour Force % . | % People | 24 | 68 | 1127 | ||
7 | Employment in Agriculture/Total Labour force %. | % People | 24 | 68 | 1125 | ||
Below than World Average- |
|||||||
1 | Wage & Salaried Workers / Total Labour Force % | % People | 58 | 119 | 1230 | ||
2 | Non-Agri Labour force/Total Labour force %. | % People | 75 | 111 | 1231 | ||
3 | Employment in Services / Total Labour Force %. | % People | 55 | 98 | 1230 | ||
4 | Employment in services/Total Labour force %. | % People | 55 | 98 | 1235 | ||
5 | Unemployment Rate. | % People | 13 | 78 | 1234 | ||
6 | Teachers in primary edu. | # People | 357,113 | 47 | 1232 | ||
7 | Formal Jobs | # People | 10,227,722 | 36 | 1234 | ||
8 | Non-Agricultural Labour Force | # People | 14,402,736 | 36 | 1234 | ||
9 | Total Labour Force (2021) | # People | 19,636,200 | 35 | 1233 | ||
10 | Employment in Agriculture | # People | 5,233,463 | 31 | 1234 | ||
11 | Unemployed Labour Force. | # People | 1,648,234 | 31 | 1232 |
Media Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | Theaters/Total Theaters %. | Percent | 0 | 26 | 1127 | ||
2 | # Phone Numbers /Total Pop. % | Percent | 101 | 60 | 1130 | ||
Below than World Average- |
|||||||
1 | Theaters per 100000 | Ratio | 1 | 43 | 1234 | ||
2 | # Mobile phone numbers | Count | 40,393,496 | 37 | 1232 | ||
3 | # Theaters | Count | 310 | 26 | 1233 |
Demography Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | Population Growth Rate (%) | % People | 1 | 81 | 1128 | ||
2 | Female % of Total Pop. | % People | 49 | 81 | 1126 | ||
3 | Gender Ratio | Ratio of female per male, Country total female/ Country total male | 0 | 81 | 1129 | ||
Below than World Average- |
|||||||
1 | Density ( Pop/Land Area Ratio) | Density | 342 | 155 | 1230 | ||
2 | Male % of Total Pop. | % People | 50 | 114 | 1230 | ||
3 | Births | # People (In Thousands) | 688 | 52 | 1234 | ||
4 | Male Population | # People (In Thousands) | 20,393 | 45 | 1231 | ||
5 | Total Population (2021) | # People (In Thousands) | 40,345 | 44 | 1232 | ||
6 | Female Population | # People (In Thousands) | 20,160 | 43 | 1233 |
Education Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Above than World Average- |
|||||||
1 | Literacy Rate (%) | % People | 86 | 105 | 1130 | ||
Below than World Average- |
|||||||
1 | # Students per teacher in secondary edu. | Ratio | 57 | 100 | 1232 | ||
2 | Teachers as a % of Enrolment | % People | 41 | 85 | 1234 | ||
3 | Enrolment in Secondary Edu./Total Literate Pop. | % People | 28 | 84 | 1235 | ||
4 | Enrolment in Primary Edu./ Total Literate Pop %. | % People | 36 | 81 | 1235 | ||
5 | Enrolment in Primary Edu./Total Pop %. | % People | 27 | 77 | 1235 | ||
6 | Enrolment in Secondary Edu./Total Pop %. | % People | 23 | 70 | 1232 | ||
7 | # Students per teacher in Primary edu. | Ratio | 260 | 53 | 1231 | ||
8 | Enrolment in primary edu. | # People | 9,629,078 | 43 | 1232 | ||
9 | Total Literate Pop. | # People | 34,125,548 | 41 | 1230 | ||
10 | # Students per teacher in tertiary edu. | Ratio | 58 | 41 | 1230 | ||
11 | Enrolment in secondary edu. | # People | 9,727,510 | 38 | 1235 | ||
12 | # Total Students (Primary+Secondary+Tertiary) | # People | 38,831,325 | 35 | 1234 | ||
13 | Teachers in secondary edu. | # People | 659,923 | 32 | 1230 | ||
14 | # Total Teachers (Primary+Secondary+Tertiary) | # People | 2,895,876 | 31 | 1234 | ||
15 | Enrolment in tertiary edu.(all programmes) | # People | 4,618,191 | 24 | 1235 | ||
16 | Teachers in tertiary edu. | # People | 297,976 | 20 | 1231 | ||
17 | Enrolment in Tertiary Edu./ Total Pop. %. | % People | 9 | 8 | 1235 | ||
18 | Enrolment in Tertiary Edu/Total Literate Pop. %. | % People | 9 | 8 | 1233 |
Governance Metrics
Sr. | Title | Metric | World Average | Rank out of 195 | Value | ||
---|---|---|---|---|---|---|---|
Below than World Average- |
|||||||
1 | Military Force/Total Pop. % | % People | 0 | 92 | 1233 | ||
2 | Military Budget/Total World Military Budget %. | Percent | 0 | 56 | 1235 | ||
3 | Military Budget (in Billion $) | $ Billion | 15 | 57 | 1234 | ||
4 | Total Military Force | # People | 122,909 | 50 | 1233 | ||
5 | Military Force/Total World Military Force %. | % People | 0 | 50 | 1231 | ||
6 | Police Officers | # People | 138,224 | 27 | 1231 |
Peru Language Details
Sr. | Language | % of people speaking the language in country. |
---|---|---|
1 | Peruvian Spanish | 86.02 % |
2 | Spanish | 85.69 % |
3 | Quechua | 13.25 % |
4 | Aymara | 1.37 % |
5 | Standard Chinese | 0.31 % |
6 | Ashaninka | 0.06 % |
List of cities having more than 100K population in Peru
Sr. | City | Total City Population (2023) |
---|---|---|
1 | Arequipa | 944,463 |
2 | Ayacucho | 198,149 |
3 | Cajamarca | 251,211 |
4 | Chiclayo | 652,352 |
5 | Chimbote | 402,648 |
6 | Chincha Alta | 193,521 |
7 | Cuzco | 467,334 |
8 | Huancayo | 396,513 |
9 | Huánuco | 190,722 |
10 | Huaraz | 140,136 |
11 | Ica | 265,634 |
12 | Iquitos | 475,837 |
13 | Juliaca | 302,228 |
14 | Lima | 10,805,626 |
15 | Pisco | 112,905 |
16 | Piura | 479,389 |
17 | Pucallpa | 227,855 |
18 | Puno | 153,912 |
19 | Sullana | 218,491 |
20 | Tacna | 320,203 |
21 | Tarapoto | 158,541 |
22 | Trujillo | 872,673 |
23 | Tumbes | 121,408 |
Frequently Asked Questions :
Q - Does Prarang do surveys to collect data? How does Prarang have such granular Country-level details which no private or public data source offers?
A - Prarang does not conduct surveys to gather data; instead, we rely on publicly available sources such as UN Population data, the CIA World Factbook, and private surveys whose results are accessible through news media and public websites. Our data classification follows a three-fold method rooted in Indian logic (Tarkashastra): Pramana (evidence-based data collection) involves gathering data from credible sources; Anumana (estimation and inference) uses modeling to draw inferences from the collected data; and Upamana (comparison) ranks countries through relative comparison, calculating the Samana (country average) to determine whether each country ranks above or below this benchmark. All data sources and estimation modeling methods are transparently detailed and accessible, with information available for each data field by clicking the "i" icon.
Q - Does Prarang take responsibility for the absolute data fields that someone buys from it, along with the calculation of the associated ranks?
A - Prarang does not do any surveys. It does data modeling & estimations based on third-party census & surveys, already in the public domain. It also shares the source of the data it uses. Users need to make their own judgment of how and for what purpose and when they use the data that they download from this Prarang website.
Q - What is the frequency of data updates on various data fields of Prarang analytics?
A - We are continuously on the lookout for market announcements of new surveys & new data. You can expect important World survey results to be live on our website, within 30 to 45 days after appearing in press/media. We model on spreadsheets & update our SQL databases, after data validation.