Apple Card owners in the United States in 2023 were typically Millennials (** percent of respondents) who tended to have a relatively high income. This is according to a survey held among Americans who either owned or did not own Apple's credit card. The source adds this demographic was in line with other surveys they held for other Apple products. Statista's Consumer Insights also noted that U.S. Apple iOS users are typically high income. The source of this particular survey, however, does not state how many of its 4,000 respondents owned an Apple Card. All statistics on Apple Pay - and services that rely on it, such as Apple Card and Apple Cash - are estimates, typically based on survey information. Apple Inc. does not share figures on individual services, whereas financial providers who offer Apple Pay, Apple Card, etc. are contractually forbidden to share such information.

About this dataset

Context

The dataset tabulates the population of Pine Apple by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Pine Apple across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 50.32% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Pine Apple is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Pine Apple total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Pine Apple Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Pine Apple by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Pine Apple. The dataset can be utilized to understand the population distribution of Pine Apple by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Pine Apple. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Pine Apple.

Key observations

Largest age group (population): Male # 75-79 years (29) | Female # 70-74 years (19). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Pine Apple population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Pine Apple is shown in the following column.
• Population (Female): The female population in the Pine Apple is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Pine Apple for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Pine Apple Population by Gender. You can refer the same here

According to a survey conducted in the United States in November 2022, 20 percent of respondents watched Apple TV Plus at all during the month prior to the survey, while daily use stood at five percent. Men are more likely to use the streaming service than women.

Apple TV+ is a subscription video-on-demand (SVOD) service owned by Apple which features Apple original series, movies, and TV shows.

This statistic gives information on the share of Apple Music in the United States as of February 2018, by gender. During this month, 56 percent of Apple Music users were female.

About this dataset

Context

The dataset tabulates the population of Apple River town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Apple River town. The dataset can be utilized to understand the population distribution of Apple River town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Apple River town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Apple River town.

Key observations

Largest age group (population): Male # 15-19 years (87) | Female # 65-69 years (86). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Apple River town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Apple River town is shown in the following column.
• Population (Female): The female population in the Apple River town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Apple River town for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Apple River town Population by Gender. You can refer the same here

Apple Pay users in the United States made up ** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in the United States was that they were between ********* years old, and fell in the ******* quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in the United States was equally used in online shopping as it was in offline POS.

About this dataset

Context

The dataset tabulates the population of Apple River by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Apple River across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of female population, with 53.77% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Apple River is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Apple River total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Apple River Population by Race & Ethnicity. You can refer the same here

Apple Pay users in Poland made up ** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in Poland was that they were ******, were ******** years old, and fell in the ******* quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in Poland was used more in online shopping than it was in offline POS.

About this dataset

Context

The dataset tabulates the population of Apple Valley by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Apple Valley. The dataset can be utilized to understand the population distribution of Apple Valley by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Apple Valley. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Apple Valley.

Key observations

Largest age group (population): Male # 10-14 years (2,133) | Female # 5-9 years (2,672). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Apple Valley population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Apple Valley is shown in the following column.
• Population (Female): The female population in the Apple Valley is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Apple Valley for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Apple Valley Population by Gender. You can refer the same here

Apple Pay users in Mexico made up **** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in Mexico was that they were ****, were ******** years old or ********************, and fell in the ******* quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in Mexico was used more in online shopping than it was in offline POS.

Apple Pay users in Brazil made up **** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in Brazil was that they were ****, were ******** years old, and fell in the ******* quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in Brazil was used less in online shopping than it was in offline POS.

Apple Pay users in Finland made up ** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in Finland was that they were ****, were ******** years old, and fell in the ******* quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in Finland was used more in online shopping than it was in offline POS.

Apple Pay users in China made up ** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in China was that they were ******** years old, and fell in the ******* quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in China was used more in online shopping than it was in offline POS.

Apple Pay users in Germany made up ** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in Germany was that they were ****, were ******** years old, and fell in the ******* quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in Germany was used more in online shopping than it was in offline POS.

About this dataset

Context

The dataset tabulates the population of Apple Valley by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Apple Valley across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 52.47% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Apple Valley is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Apple Valley total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Apple Valley Population by Race & Ethnicity. You can refer the same here

Apple Pay users in Italy made up **** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in Italy was that they were ******** years old, and fell in the ******* quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in Italy was used more in online shopping than it was in offline POS.

Apple Pay users in France made up ** percent of respondents in 2025, and were likely to come from a ****** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in France was that they were ******** years old, and fell in the ****** quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in France was used less in online shopping than it was in offline POS.

Apple Pay users in the Netherlands made up ** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in the Netherlands was that they were ****, were ******** years old, and fell in the ******* quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in the Netherlands was used more in online shopping than it was in offline POS.

Apple Pay users in Austria made up ** percent of respondents in 2025, and were likely to come from a **** income. This is according to questions asked in Statista's Consumer Insights, focusing on what payment services consumers used in the past 12 months. The typical user profile of an Apple Pay user in Austria was that they were ******, were ******** years old, and fell in the ******* quantile in terms of income. According to Statista surveys, in 2024, Apple Pay in Austria was used more in online shopping than it was in offline POS.