In 2023, the District of Columbia had the highest reported violent crime rate in the United States, with 1,150.9 violent crimes per 100,000 of the population. Maine had the lowest reported violent crime rate, with 102.5 offenses per 100,000 of the population. Life in the District The District of Columbia has seen a fluctuating population over the past few decades. Its population decreased throughout the 1990s, when its crime rate was at its peak, but has been steadily recovering since then. While unemployment in the District has also been falling, it still has had a high poverty rate in recent years. The gentrification of certain areas within Washington, D.C. over the past few years has made the contrast between rich and poor even greater and is also pushing crime out into the Maryland and Virginia suburbs around the District. Law enforcement in the U.S. Crime in the U.S. is trending downwards compared to years past, despite Americans feeling that crime is a problem in their country. In addition, the number of full-time law enforcement officers in the U.S. has increased recently, who, in keeping with the lower rate of crime, have also made fewer arrests than in years past.

An interactive public crime mapping application providing DC residents and visitors easy-to-understand data visualizations of crime locations, types and trends across all eight wards. Crime Cards was created by the DC Metropolitan Police Department (MPD) and Office of the Chief Technology Officer (OCTO). Special thanks to the community members who participated in reviews with MPD Officers and IT staff, and those who joined us for the #SaferStrongerSmarterDC roundtable design review. All statistics presented in Crime Cards are based on preliminary DC Index crime data reported from 2009 to midnight of today’s date. They are compiled based on the date the offense was reported (Report Date) to MPD. The application displays two main crime categories: Violent Crime and Property Crime. Violent Crimes include homicide, sex abuse, assault with a dangerous weapon (ADW), and robbery. Violent crimes can be further searched by the weapon used. Property Crimes include burglary, motor vehicle theft, theft from vehicle, theft (other), and arson. CrimeCards collaboration between the Metropolitan Police Department (MPD) and the Office of the Chief Technology Officer (OCTO).

Abstract: The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.Purpose: On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments. This change was not applied to datasets pre-2020.Supplemental Information: All statistics presented in Crime Cards are based on preliminary DC criminal code offense definitions. The data do not represent official statistics submitted to the FBI under the Uniform Crime Reporting program (UCR) or National Incident Based Reporting System (NIBRS). All preliminary offenses are coded based on DC criminal code and not the FBI offense classifications. Please understand that any comparisons between MPD preliminary data as published on this website and the official crime statistics published by the FBI under the Uniform Crime Reporting Program (UCR) are inaccurate and misleading. The MPD does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information. The MPD will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. Please note that changes to MPD's PSA and police district boundaries occasionally occur. The statistics provided through DC Crime Mapping Application are based on current police boundaries as of January 3, 2017. Sex Assault Data Availability: In an effort to provide more clear information about the most serious sex assaults that are most closely aligned with the public's perception of rape and attempted rape, the most serious sex abuse categories are included in the reports of DC Code Index Violent Crimes: Sex Assault. The figures reported in this category include First Degree Sex Abuse, Second Degree Sex Abuse, Attempted First Degree Sex Abuse and Assault with Intent to Commit First Degree Sex Abuse against adults. Data in this format is available online from 2011. Similar to the other offense data, the sex assault statistics are subject to change due to a variety of reasons, such as a change in classification, the determination that certain offense reports were unfounded, or late reporting. Please understand that any comparisons between MPD preliminary data as published on this website and the official crime statistics published by the FBI under the Uniform Crime Reporting Program (UCR) are inaccurate and misleading. Please also be aware that on Sunday, August 23, 2015, the MPD implemented a new records management system called Cobalt. The offense categories presented within this application have remained the same; however, all statistics are subject to change due to a variety of reasons, such as a change in classification, the determination that certain offense reports were unfounded, or late reporting. All statistics presented in Crime Cards are based on preliminary DC Index crime data reported from 2009 up to a second before midnight today (that's 11:59:59 pm yesterday) . They are compiled based on the date the offense was reported ( Report Date) to the police department. The date and time window of the crime’s occurrence is provided in the See a det

The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit https://crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.

The Office of Gun Violence Prevention (OGVP) shares real-time gun violence data to increase government transparency, improve the public's awareness, and support community-based gun violence prevention and reduction partners. All District crime data is available through Crime Cards. The dashboards below focus on gun violence only. The data in these dashboards is updated daily at 7:40AM with the incidents from the day before. View data covering 7-Day Look-back of Gun Violence and Year-to-date Gun Violence.All statistics presented here are based on preliminary DC criminal code offense definitions. The data do not represent official statistics submitted to the FBI under the Uniform Crime Reporting program (UCR) or National Incident Based Reporting System (NIBRS). All preliminary offenses are coded based on DC criminal code and not the FBI offense classifications. Please understand that any comparisons between MPD preliminary data as published on this website and the official crime statistics published by the FBI under the Uniform Crime Reporting Program (UCR) are inaccurate and misleading. The MPD does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information. The MPD will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. Read complete data notes at buildingblocks.dc.gov/data.

About this dataset

Context

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

Key observations

There is a slight majority of female population, with 52.39% 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 Washington is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Washington 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 Washington Population by Race & Ethnicity. You can refer the same here

In 2023, the government and government enterprises industry added the most real value to the gross domestic product (GDP) of the District of Columbia, amounting to around 44.91 billion U.S. dollars. Comparatively, the information industry contributed around 12.89 billion U.S. dollars to the district's real GDP.

Comprehensive demographic dataset for Downtown Washington, Washington, DC, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Washington. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Washington, the median income for all workers aged 15 years and older, regardless of work hours, was $77,818 for males and $64,201 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 17% between the median incomes of males and females in Washington. With women, regardless of work hours, earning 83 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Washington.

- Full-time workers, aged 15 years and older: In Washington, among full-time, year-round workers aged 15 years and older, males earned a median income of $110,582, while females earned $95,422, resulting in a 14% gender pay gap among full-time workers. This illustrates that women earn 86 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the city of Washington.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Washington.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Washington median household income by race. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Washington by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Washington. The dataset can be utilized to understand the population distribution of Washington by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Washington. 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 Washington.

Key observations

Largest age group (population): Male # 30-34 years (37,060) | Female # 25-29 years (40,335). 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 Washington population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Washington is shown in the following column.
• Population (Female): The female population in the Washington 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 Washington 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 Washington Population by Gender. You can refer the same here

Dashboard featuring statistics regarding residents' place of birth in Washington, DC. Data derived from ACS Place of Birth Variables - Boundaries, which is a layer by Esri and is available on Living Atlas.

Comprehensive demographic dataset for University Heights, Washington, DC, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Dashboard featuring statistics regarding age and percentage of population by gender in Washington, DC. Data derived from ACS Population Variables - Boundaries and ACS Median Age Variables - Boundaries, which are layers by Esri and are available on Living Atlas.

Comprehensive demographic dataset for West End Washington, Washington, DC, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Comprehensive demographic dataset for Southeast Washington, Washington, DC, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

This statistic shows a forecast of Washington D.C.'s share of the total U.S. legal cannabis market from 2016 to 2025. Washington D.C.'s market share in legal cannabis is predicted to rise from **** percent in 2016 to *** percent in 2025.

The S&P Case Shiller Washington DC Home Price Index has increased steadily in recent years. The index measures changes in the prices of existing single-family homes. The index value was equal to 100 as of January 2000, so if the index value is equal to *** in a given month, for example, it means that the house prices have increased by ** percent since 2000. The value of the S&P Case Shiller Washington DC Home Price Index amounted to ****** in August 2024. That was slightly higher than the national average.

Comprehensive demographic dataset for H Street Washington, Washington, DC, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

This study provides statistical information on how prosecutors and the courts disposed of criminal cases involving adults arrested for felony crimes in two individual urban jurisdictions, Portland, Oregon and Washington, D.C. Cases in the data files were initiated or filed in 1982. Both the Washington, D.C. file and the Portland file contain information on all felony arrests (which include arrests declined as well as those filed), cases filed, and cases indicted. Sentencing information is provided in the Portland file but is not available for Washington D.C.

The graph shows the share of adults who are fans of DC Comics in the United States as of April 2019. The data reveals that ** percent of respondents said that they were fans of DC Comics, however ** percent said that they were not.