The typical statewide or county-wide red/blue map (shown at left) depicts presidential voting results on a winner-take-all basis, so they award an entire geographical area to the Republican or Democratic candidate no matter how close the actual vote tally The large map in the attachment factors in both the percentage of the popular vote won by each candidate as well as the population density of each county. So, the sparsely populated Great Plains and Rocky Mountain West are shown in a much lighter color than the Eastern Seaboard, and the map as a whole is more purple than either red or blue. Perhaps the United States is less divided than some maps would lead us to believe.

Florida was admitted to the union in 1845, and has taken part in 43 U.S. presidential elections since this time. In these 43 elections, Florida has voted for the overall winner thirty times, giving a success rate of seventy percent. Since 1928, Florida has voted for the winning candidate in 21 out of 24 elections, and is considered a key battleground state in modern elections. Florida has voted for a major party nominee in every election, backing the Republican nominee 17 times, Democrat 25 times, and the only time it did not vote Republican or Democrat was in 1848 when it voted for the Whig Party's Zachary Taylor. Florida did not take part in the 1864 election due to its secession from the Union in the American Civil War, and like most other southern states it primarily voted Democrat until the mid-twentieth century, when it then started leaning more Republican. No U.S. President has ever been born in Florida, or resided there when taking office; although Donald Trump declared himself a resident of Florida in 2019, therefore making it his official home state during the 2020 election. The 2020 election in Florida proved to be a surprise for many, as Donald Trump won the popular vote by a 3.4 percent margin; most polls had favored Biden going into election day, however intensive campaigning and increased Republican support among Cuban Americans has been cited as the reason for Trump's victory in Florida.

Florida's importance

In 1920, Florida's population was fewer than one million people; however it has grown drastically in the past century to almost 22 million people, making Florida the third most populous state in the country. With this population boom, Florida's allocation of electoral votes has surged, from just six in the 1920s, to 29 in recent elections (this is expected to increase to 31 votes in the 2024 election). Unlike the other most populous states, such as California and New York, which are considered safe Democratic states, or Texas, which is considered a safe Republican state, presidential elections in Florida are much more unpredictable. Florida is a southern state, and its majority-white, rural and suburban districts tend to vote in favor of the Republican Party (Republicans have also dominated state elections in recent decades), although, Florida is also home to substantial Hispanic population, and is a popular destination for young workers in the tourism sector and retirees from across the U.S., with these groups considered more likely to vote Democrat. However, the discrepancy between voters of Cuban (58 percent voted Republican) and Puerto Rican (66 percent voted Democrat) origin in the 2020 election shows that these traditional attitudes towards Hispanic voters may need to be re-evaluated.

2000 controversy The 2000 U.S. presidential election is one of the most famous and controversial elections in U.S. history, due to the results from Florida. The election was contested by the Republican Party's George W. Bush and the Democratic Party's Al Gore; by the end of election day, it became clear that Florida's 25 electoral votes would decide the outcome, as neither candidate had surpassed the 270 vote margin needed to win nationwide. While Florida's early results showed Bush in the lead, Gore's share of the results in urban areas then brought their totals close enough to trigger a recount; after a month of recounts and legal proceedings, Bush was eventually declared the winner of Florida by a margin of 537 popular votes (or 0.009 percent). Although Gore did win a plurality of the votes nationwide, Bush had won 271 electoral votes overall, and was named the 43rd President of the United States; this was just one of five elections where the candidate with the most popular votes did not win the election. In the six most recent U.S. presidential elections in Florida, the difference in the share of popular votes between the Republican and Democratic candidates has been just two percent on average.

Presidential elections in the United States have been dominated by two parties throughout most of their history. The Democratic Party became the most powerful political party with Andrew Jackson's victory in the 1828 election, and the Republican Party emerged as their main opponents following Abraham Lincoln's victory in 1860. Since these years, Democratic candidates have won 23 U.S. presidential elections, while Republicans have won 24. The longest winning streaks of ether party came between 1860 and 1880, where Republican candidates won six elections in a row, while the Democrats won five in a row between 1932 and 1948 (four of which were won by Franklin D. Roosevelt).

Longest streaks

Although the nation's longest streak is just six elections in a row, the longest streaks of any individual state lasted for 27 consecutive elections. These belonged to Vermont, who voted Republican in all elections between 1856 and 1960, and Georgia, who voted Democrat in all elections between 1852 and 1960 (except in 1864, when it had seceded from the union). The longest current streak belongs to the District of Columbia, which has voted for the Democratic candidate in all 15 presidential elections in which it has taken part. Illinois and West Virginia are the only states with streaks for both the Democratic and Republican parties, while Kentucky's longest streaks are for both the Democratic-Republican and Democratic parties respectively.

Changing ideologies When looking at streaks that took place over 15 or more elections, most states were voting for the party that is not the most dominant there today. For example, from around the time of the American Civil War until after the Second World War, many southern states voted exclusively for the Democratic Party's nominee, whereas many northern states voted Republican between 1856 and 1908; in contrast, most of these states have voted for the opposite party's candidate in the past six or more elections. Historically, the Democratic Party was the more conservative of the two major parties, but gradually became more fiscally liberal during Franklin D. Roosevelt's administration, while it became more socially liberal following the Second World War. In doing this, the Democratic Party grew more appealing to voters in urban centers and in the northeast, however this transition alienated many conservative voters in the south, who became disenfranchised by the party's policies regarding civil rights. Because of this, the Republican Party then launched its "Southern strategy" during the 1960s, moving further to the right and capitalizing on racial polarization in the south by proposing policies that enforced segregation and protected Jim Crow laws. Since this time, the Republican Party has generally been the strongest in the south, although growing Hispanic and (sub)urban populations are weakening their dominance (such as in Georgia in 2020).

Since 1852, the U.S. presidential election has been contested in California 44 times, with Californians successfully voting for the winning candidate on 35 occasions, giving an overall success rate of 80 percent. California has awarded the majority of its electoral votes to the Republican Party in 23 elections, the Democratic Party in 20 elections, and the only year when a third-party candidate won a majority was in 1912, where Theodore Roosevelt won the state while campaigning as the Progressive Party's nominee. Between 1952 and 1988, there was only one election that was not won by the Republican candidate, while all elections since 1992 have been won by the Democratic nominee. In the 2024 election, Oakland-born Vice President Kamala Harris ran as the Democratic nominee, and comfortably won her home state but lost the nationwide vote. Californian under-representation? California was admitted to the union in 1850, and was granted just four electoral votes in its first three presidential elections. In the past two centuries, California's population has grown rapidly, largely due to a positive net migration rate from within the U.S. and abroad. Today, it has the highest population of any state in the U.S, with almost forty million people, and has therefore been designated 54 electoral votes; the most of any state. Although California has been allocated around ten percent of the total electoral votes on offer nationwide, The Golden State is home to roughly twelve percent of the total U.S. population, therefore a number closer to 62 electoral votes would be more proportional to the U.S. population distribution. Despite this, California's total allocation was reduced to 54 in the 2024 election. Native Californians As of 2020, Richard Nixon is the only native Californian to have been elected to the presidency, having won the election in 1968 and 1972. California also voted for Nixon in the 1960 election, although John F. Kennedy was the overall winner. Two other U.S. Presidents had declared California as their home state; they were Herbert Hoover, who won the 1928 election, and Ronald Reagan, who won in 1980 and 1984 respectively. While states generally support candidates who were born or reside there, Californian candidates have failed to carry their home state or state of birth in four U.S. presidential elections, these were; John C. Frémont in 1854 (who actually came third in California), Herbert Hoover in 1932, and Adlai Stevenson in both the 1952 and 1956 elections.

About this dataset

Context

The dataset tabulates the Blue Ridge population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Blue Ridge across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Blue Ridge was 1,200, a 0% decrease year-by-year from 2022. Previously, in 2022, Blue Ridge population was 1,200, an increase of 1.10% compared to a population of 1,187 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Blue Ridge increased by 460. In this period, the peak population was 1,200 in the year 2022. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Blue Ridge is shown in this column.
• Year on Year Change: This column displays the change in Blue Ridge population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Blue Ridge Population by Year. You can refer the same here

Pennsylvania has taken part in every U.S. presidential election, correctly voting for the nationwide winner in 47 out of 59 elections, giving a success rate of eighty percent. Since 1828, Pennsylvania has voted for the Democratic nominee in twenty elections, and the Republican Party's nominee in 26 elections (including all but one elections from 1860 to 1932). The only time where Pennsylvania did not vote for a major party candidate was in 1912, where it granted its 38 electoral votes to Theodore Roosevelt, who was running as the candidate of the newly-formed Progressive Party. After voting Democrat in all elections between 1992 and 2012, Pennsylvania voted red in 2016, as Donald Trump defeated Hillary Clinton by less than one percent of the popular vote. In 2020, Joe Biden flipped Pennsylvania blue again by 1.2 percent of the popular vote. Pennsylvania proved to be the decisive state in the week following the 2020 election, as the returns of mail in ballots gradually swung the result in Biden's favor, following a strong early showing from Donald Trump; the development of these results eventually signaled that Joe Biden had (provisionally) obtained the 270 electoral votes needed to win the election, leading all major news outlets to declare him the winner.

Pennsylvanians in office Prior to the 2020 election, James Buchanan is the only U.S. president to have been born in the Keystone State. Several other major party nominees have been born in Pennsylvania, including three of the losing candidates who ran between 1864 and 1884. Although he is more commonly associated with Delaware, Joe Biden's victory in 2020 made him the the second U.S. president to have been born in Pennsylvania, having spent the first ten years of his life in Scranton. Biden will, most likely, want to be remembered more favorably than Buchanan, who is consistently ranked as the worst U.S. president in history. Weakening influence From 1804 until 1964, Pennsylvania had the second-highest allocation of electoral votes in every U.S. presidential election (usually behind New York), with the number peaking at 38 electoral votes between 1912 and 1928. Since then, Pennsylvania's allocation of electoral votes has fallen gradually, and is expected to be just 19 votes in the 2024 election; half of what it was one century previously. The reason for this drop in electoral votes is due Pennsylvanians migrating to other parts of the country, while growing populations across the border and Midwestern states has seen a shift in population distribution across the country. Nonetheless, with 19 electoral votes, Pennsylvania is likely to remain one of the most valuable battleground states in future elections.

About this dataset

Context

The dataset tabulates the Blue Springs population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Blue Springs across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Blue Springs was 439, a 0% decrease year-by-year from 2022. Previously, in 2022, Blue Springs population was 439, an increase of 0.46% compared to a population of 437 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Blue Springs increased by 297. In this period, the peak population was 439 in the year 2022. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Blue Springs is shown in this column.
• Year on Year Change: This column displays the change in Blue Springs population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Blue Springs Population by Year. You can refer the same here

The state of Virginia has taken part in all U.S. elections since 1789, except for the 1864 and 1868 elections due to its status during and after the American Civil War; of the 57 elections in which it participated, Virginians sided with the nationwide winner 38 times, giving a success rate of 67 percent. In its early years, Virginia sided with the Democratic-Republican nominee, before voting for the Democratic nominee in most elections between 1828 and 1948. The only time where Virginia voted for a third party candidate was in 1860, where it backed the Constitutional Union's John Bell in the lead up to the Civil War. Like most southern states, Virginia was a reliably Republican state from the 1950s onwards, and the only time where a Democrat won the Old Dominion between 1952 and 2004 was in Lyndon B. Johnson's landslide victory in 1964. Unlike most southern states, however, Virginia has transitioned into a blue state in recent years, with Hillary Clinton winning the popular vote with a 5.4 percent margin in 2016; this transition has been attributed to a growing Hispanic population and the extension of the Washington D.C. metropolitan area in the north of the state, making it one of the most ethnically diverse regions of the country. In the 2020 election, Democratic nominee Joe Biden won Virginia by a comfortable, ten percent margin. "Mother of Presidents" Virginia has the unofficial nickname of "Mother of Presidents", as eight of the 45 men who have served as president were born here (officially 46 (incl. Biden) as Grover Cleveland is counted twice). Four of the U.S.' first five presidents were born in Virginia; these were George Washington, Thomas Jefferson, James Madison and James Monroe. The most recent Virginian to ascend to the presidency was Woodrow Wilson, who was born in 1856 and served between 1913 and 1921 (although Wilson is more commonly associated with New Jersey). Since Wilson, no major party candidate has ever been born in or resided in Virginia when seeking office, although Virginian Senator Harry F. Byrd received 15 electoral votes in the 1960 election, as a protest against John F. Kennedy's liberal attitudes towards civil rights. Electoral votes In the first six U.S. presidential elections, Virginia was allocated the highest number of electoral votes of any state, and this number peaked at 25 electoral votes between the 1812 and 1820 elections. From this point until the civil war, the number of votes gradually decreased to 15, as population growth in other states was much faster than that of Virginia. During the civil war, the region of West Virginia became a separate state, and since the 1872 election, Virginia's allocation of electoral votes has remained constant, fluctuating between 11 and 13 votes.

Graph and download economic data for Estimated Percent of People of All Ages in Poverty for Blue Earth County, MN (PPAAMN27013A156NCEN) from 1989 to 2023 about Blue Earth County, MN; Mankato; MN; percent; child; poverty; and USA.

The state of Washington has taken part in all 33 U.S. presidential elections since 1892, voting for the nationwide winner in 23 elections, giving a success rate of seventy percent. Washington voted for the Republican Party's nominee in 14 elections, and the Democratic nominee in 18; while Washington did not have a strong party affiliation throughout most of its history, it has grown to be a solid blue state in the past few decades, voting for the Democratic nominee in all elections since 1988. The only election where Washington did not vote for a major party nominee was in the 1912 election, where it voted for former-President Theodore Roosevelt, who ran as a third-party candidate for the Progressive Party. In the 2020 election, Washington proved to be a comfortable victory for the Democratic nominee, Joe Biden, who won by an almost twenty percent margin in the popular vote.

Electoral votes Washington's influence has steadily grown throughout U.S. election history, with its allocation of electoral votes gradually increasing from four votes in at the turn of the twentieth century, to twelve votes since 2012. This is largely due to Washington state's high population growth, which has consistently grown at a faster rate than the national average since the 1940s; Seattle, Washington's largest city, has consistently been the fastest growing city in the U.S. in the past decade, due to the booming tech industry and high standard of living. As of the 2020 election, no U.S. president or major party nominee was born in Washington, or resided there when taking office.

The "Hamilton Electors" In the 2016 election, four of Washington's electors made headlines by not voting for Hillary Clinton, who was the statewide winner of the popular vote. Instead, three electors voted for Colin Powell, while one voted for Faith Spotted Eagle; respectively making them the first African-American Republican and Native American to receive electoral votes for president. This was part of the "Hamilton Electors" movement, which began shortly after the popular vote results were announced. Its aim it was to have 35 electors cast faithless ballots, reduce Donald Trump's electoral vote majority below 270, and bring the election before the House of Representatives. Ultimately, only seven electors cast faithless ballots (only two of which were for Trump), and the four faithless electors from Washington were fined one thousand dollars each. Following a series of subsequent legal challenges, in July 2020, the Supreme Court unanimously ruled that states may oblige electors to vote for their pledged candidate in future elections, therefore giving all states the power to invalidate faithless ballots in future presidential elections.

About this dataset

Context

The dataset tabulates the Blue Hill township population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Blue Hill township across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Blue Hill township was 2,600, a 0.39% increase year-by-year from 2022. Previously, in 2022, Blue Hill township population was 2,590, an increase of 1.17% compared to a population of 2,560 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Blue Hill township increased by 1,796. In this period, the peak population was 2,600 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Blue Hill township is shown in this column.
• Year on Year Change: This column displays the change in Blue Hill township population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Blue Hill township Population by Year. You can refer the same here

The state of Michigan has taken part in 47 U.S. presidential elections, correctly voting for the nationwide winner in 37 of these, giving a success rate of 79 percent. Throughout most of the nineteenth century, Michigan generally voted for the Republican Party's nominee, although it has regularly swung between the two major parties since the 1930s. The only time when the Wolverine State voted for a third party candidate was in the 1912 election, when former President Theodore Roosevelt carried Michigan while running as the Progressive Party's nominee. While born in Nebraska, Gerald R. Ford was raised, studied and represented Michigan in Congress, before he became the only Michiganian to ascend to the presidency following Richard Nixon's resignation in 1974.

Swing state After voting for the Democratic candidate in all elections from 1992 until 2012, the Republican nominee Donald Trump carried the state in the 2016 election, with just a 0.23 percent larger share of the popular votes than Hillary Clinton. Trump's victory has been attributed to a large number of working class voters who traditionally voted Democrat, but had become disenfranchised with the party during the Obama presidency. In the 2020 election, however, increased turnout among black voters and stronger appeal to unionized workers saw Joe Biden swing Michigan blue again, with a seven percent margin in the popular vote.

Michigan demographics Michigan was designated three electoral votes in the 1836 election (despite not being admitted to the union until 1837), and over the next 130 years its allocation grew to 21 votes. This came as a result of Michigan's significant population growth and positive net migration rate in mid-1900s, which was largely due to the expansion of the automotive industry in the Detroit area. Since the 1970s, job automation and increased competition have substantially weakened the industry's employment opportunities; therefore Michigan's population growth has slowed significantly, and its number of electoral votes has also decreased to just 16. This number is expected to drop to 15 in the 2024 election.

About this dataset

Context

The dataset tabulates the Blue Mounds population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Blue Mounds across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Blue Mounds was 924, a 1.70% decrease year-by-year from 2021. Previously, in 2021, Blue Mounds population was 940, a decline of 0.74% compared to a population of 947 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Blue Mounds increased by 215. In this period, the peak population was 990 in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Blue Mounds is shown in this column.
• Year on Year Change: This column displays the change in Blue Mounds population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Blue Mounds Population by Year. You can refer the same here

Measure and Map Access to Grocery StoresFrom the perspective of the people living in each neighborhood How do people in your city get to the grocery store? The answer to that question depends on the person and where they live. This web map helps answer the question in this app. Some live in cities and stop by a grocery store within a short walk or bike ride of home or work. Others live in areas where car ownership is more prevalent, and so they drive to a store. Some do not own a vehicle, and rely on a friend or public transit. Others rely on grocery delivery for their needs. And, many live in rural areas far from town, so a trip to a grocery store is an infrequent event involving a long drive.This map from Esri shows which areas are within a ten minute walk or ten minute drive of a grocery store in the United States and Puerto Rico. Darker color indicates access to more stores. The chart shows how many people can walk to a grocery store if they wanted to or needed to.It is estimated that 20% of U.S. population live within a 10 minute walk of a grocery store, and 92% of the population live within a 10 minute drive of a grocery store. Look up your city to see how the numbers change as you move around the map. Or, draw a neighborhood boundary on the map to get numbers for that area.Every census block is scored with a count of walkable and drivable stores nearby, making this a map suitable for a dashboard for any city, or any of the 50 states, DC and Puerto Rico. Two colorful layers visualize this definition of access, one for walkable access (suitable for looking at a city neighborhood by neighborhood) and one for drivable access (suitable for looking across a city, county, region or state). On the walkable layer, shades of green define areas within a ten minute walk of one or more grocery stores. The colors become more intense and trend to a blue-green color for the busiest neighborhoods, such as downtown San Francisco. As you zoom in, a layer of Census block points visualizes the local population with or without walkable access. As you zoom out to see the entire city, the map adds a light blue - to dark blue layer, showing which parts of the region fall within ten minutes' drive of one or more grocery stores. As a result, the map is useful at all scales, from national to regional, state and local levels. It becomes easier to spot grocery stores that sit within a highly populated area, and grocery stores that sit in a shopping center far away from populated areas. This view of a city begins to hint at the question: how many people have each type of access to grocery stores? And, what if they are unable to walk a mile regularly, or don't own a car? How to Use This MapUse this map to introduce the concepts of access to grocery stores in your city or town. This is the kind of map where people will want to look up their home or work address to validate what the map is saying. The map was built with that use in mind. Many maps of access use straight-line, as-the-crow-flies distance, which ignores real-world barriers to walkability like rivers, lakes, interstates and other characteristics of the built environment. Block analysis using a network data set and Origin-Destination analysis factors these barriers in, resulting in a more realistic depiction of access. There is data behind the map, which can be summarized to show how many people have walkable access to local grocery stores. The map includes a feature layer of population in Census block points, which are visible when you zoom in far enough. This feature layer can be plugged into an app like this one that summarizes the population with/without walkable or drivable access. Lastly, this map can serve as backdrop to other community resources, like food banks, farmers markets (example), and transit (example). Add a transit layer to immediately gauge its impact on the population's grocery access. You can also use this map to see how it relates to communities of concern. Add a layer of any block group or tract demographics, such as Percent Senior Population (examples), or Percent of Households with Access to 0 Vehicles (examples). The map is a useful visual and analytic resource for helping community leaders, business and government leaders see their town from the perspective of its residents, and begin asking questions about how their community could be improved. Data sourcesPopulation data is from the 2010 U.S. Census blocks. Each census block has a count of stores within a 10 minute walk, and a count of stores within a ten minute drive. Census blocks known to be unpopulated are given a score of 0. The layer is available as a hosted feature layer. Grocery store locations are from SafeGraph, reflecting what was in the data as of October 2020. Access to the layer was obtained from the SafeGraph offering in ArcGIS Marketplace. For this project, ArcGIS StreetMap Premium was used for the street network in the origin-destination analysis work, because it already has the necessary attributes on each street segment to identify which streets are considered walkable, and supports a wide variety of driving parameters. The walkable access layer and drivable access layers are rasters, whose colors were chosen to allow the drivable access layer to serve as backdrop to the walkable access layer. Data PreparationArcGIS Network Analyst was used to set up a network street layer for analysis. ArcGIS StreetMap Premium was installed to a local hard drive and selected in the Origin-Destination workflow as the network data source. This allows the origins (Census block centroids) and destinations (SafeGraph grocery stores) to be connected to that network, to allow origin-destination analysis. The Census blocks layer contains the centroid of each Census block. The data allows a simple popup to be created. This layer's block figures can be summarized further, to tract, county and state levels. The SafeGraph grocery store locations were created by querying the SafeGraph source layer based on primary NAICS code. After connecting to the layer in ArcGIS Pro, a definition query was set to only show records with NAICS code 445110 as an initial screening. The layer was exported to a local disk drive for further definition query refinement, to eliminate any records that were obviously not grocery stores. The final layer used in the analysis had approximately 53,600 records. In this map, this layer is included as a vector tile layer. MethodologyEvery census block in the U.S. was assigned two access scores, whose numbers are simply how many grocery stores are within a 10 minute walk and a 10 minute drive of that census block. Every census block has a score of 0 (no stores), 1, 2 or more stores. The count of accessible stores was determined using Origin-Destination Analysis in ArcGIS Network Analyst, in ArcGIS Pro. A set of Tools in this ArcGIS Pro package allow a similar analysis to be conducted for any city or other area. The Tools step through the data prep and analysis steps. Download the Pro package, open it and substitute your own layers for Origins and Destinations. Parcel centroids are a suggested option for Origins, for example. Origin-Destination analysis was configured, using ArcGIS StreetMap Premium as the network data source. Census block centroids with population greater than zero were used as the Origins, and grocery store locations were used as the Destinations. A cutoff of 10 minutes was used with the Walk Time option. Only one restriction was applied to the street network: Walkable, which means Interstates and other non-walkable street segments were treated appropriately. You see the results in the map: wherever freeway overpasses and underpasses are present near a grocery store, the walkable area extends across/through that pass, but not along the freeway. A cutoff of 10 minutes was used with the Drive Time option. The default restrictions were applied to the street network, which means a typical vehicle's access to all types of roads was factored in. The results for each analysis were captured in the Lines layer, which shows which origins are within the cutoff of each destination over the street network, given the assumptions about that network (walking, or driving a vehicle). The Lines layer was then summarized by census block ID to capture the Maximum value of the Destination_Rank field. A census block within 10 minutes of 3 stores would have 3 records in the Lines layer, but only one value in the summarized table, with a MAX_Destination_Rank field value of 3. This is the number of stores accessible to that census block in the 10 minutes measured, for walking and driving. These data were joined to the block centroids layer and given unique names. At this point, all blocks with zero population or null values in the MAX_Destination_Rank fields were given a store count of 0, to help the next step. Walkable and Drivable areas are calculated into a raster layer, using Nearest Neighbor geoprocessing tool on the count of stores within a 10 minute walk, and a count of stores within a ten minute drive, respectively. This tool uses a 200 meter grid and interpolates the values between each census block. A census tracts layer containing all water polygons "erased" from the census tract boundaries was used as an environment setting, to help constrain interpolation into/across bodies of water. The same layer use used to "shoreline" the Nearest Neighbor results, to eliminate any interpolation into the ocean or Great Lakes. This helped but was not perfect. Notes and LimitationsThe map provides a baseline for discussing access to grocery stores in a city. It does not presume local population has the desire or means to walk or drive to obtain groceries. It does not take elevation gain or loss into account. It does not factor time of day nor weather, seasons, or other variables that affect a person's commute choices. Walking and driving are just two ways people get to a grocery

The Application

This application allows comparison of the proposed California 2020 Public Use Microdata Areas (PUMAs) with the 2010 PUMAs. The boundaries for these PUMAs were delineated based on population counts for California counties and tracts from the 2020 Census. The Demographic Research Unit worked with California State Data Center affiliates and regional organizations to ensure that the PUMAs reflect local communities.

For more information, go to the Census Bureau's 2020 Census PUMA program web page.

PUMAs

Public Use Microdata Areas (PUMAs) are non-overlapping, statistical geographic areas that partition each state or equivalent entity into geographic areas containing no fewer than 100,000 people each. They cover the entirety of the United States. The Census Bureau defines PUMAs for the tabulation and dissemination of decennial census and American Community Survey (ACS) Public Use Microdata Sample (PUMS) data. The delineation of new PUMAs occurs after the completion of the decennial census as part of a program involving the State Data Centers (SDCs). The Census Bureau's PUMA web page contains more details about these areas.

Note that the 2020 and 2010 PUMAs may not overlap exactly as 2020 census tracts were changed from the 2010 census.

Source:

California Department of Finance, Demographic Research Unit.

The U.S. presidential election has been held in North Carolina on 57 occasions; this was every election except the first, in 1789, and the 1864 election, when North Carolina was a member of the Confederate States of America. North Carolina has awarded all (or at least a majority) of its electoral votes to the nationwide winning candidate in 38 elections, giving a success rate of 67 percent. The "Tar Heel State" has voted for the Democratic nominee in thirty elections, and the Republican nominee in 15; although eleven of these have come in the past 14 elections. Despite North Carolina voting red in most elections since 1968, it has often been seen as a battleground state, with the four most recent popular votes split by fewer than four points. In the 2020 election, North Carolina was on of the closest results nationwide, with Donald Trump winning the popular vote by a one percent margin. North Carolinians in office Two U.S. presidents were born in North Carolina; the first was James K. Polk, who spent the first seven years of his life in the Waxhaws region, and the second was Andrew Johnson, who was born and raised in Raleigh. Coincidentally, both these men would move to Tennessee, where they would establish political careers before ascending to the presidency. Polk also failed to win the election in his state of birth, while Johnson's election (as Abraham Lincoln's vice presidential nominee) was not contested there. Electoral votes Between 1812 and 1840, North Carolina had 15 electoral votes, however this then decreased to just nine votes by the Reconstruction era, as higher net migration rates in other states saw the saw North Carolina's population grow more slowly than the national average. The allocation then rose to 13 votes in the 1930s, and remained at 13 or 14 until 2004, when it then returned to 15. Historically, the majority of North Carolinians have lived in rural areas, although recent decades have seen the population shift to be come more urban or suburban, and grow due to an influx of migrants from Latin America and South or Southeast Asia. In the 2024 election, North Carolina is expected to gain another electoral vote as its population grows faster than the national average, and higher birth rates among urban and foreign-born populations is likely to increase the Democratic Party's voter base in the state.

IntroductionClimate Central’s Surging Seas: Risk Zone map shows areas vulnerable to near-term flooding from different combinations of sea level rise, storm surge, tides, and tsunamis, or to permanent submersion by long-term sea level rise. Within the U.S., it incorporates the latest, high-resolution, high-accuracy lidar elevation data supplied by NOAA (exceptions: see Sources), displays points of interest, and contains layers displaying social vulnerability, population density, and property value. Outside the U.S., it utilizes satellite-based elevation data from NASA in some locations, and Climate Central’s more accurate CoastalDEM in others (see Methods and Qualifiers). It provides the ability to search by location name or postal code.The accompanying Risk Finder is an interactive data toolkit available for some countries that provides local projections and assessments of exposure to sea level rise and coastal flooding tabulated for many sub-national districts, down to cities and postal codes in the U.S. Exposure assessments always include land and population, and in the U.S. extend to over 100 demographic, economic, infrastructure and environmental variables using data drawn mainly from federal sources, including NOAA, USGS, FEMA, DOT, DOE, DOI, EPA, FCC and the Census.This web tool was highlighted at the launch of The White House's Climate Data Initiative in March 2014. Climate Central's original Surging Seas was featured on NBC, CBS, and PBS U.S. national news, the cover of The New York Times, in hundreds of other stories, and in testimony for the U.S. Senate. The Atlantic Cities named it the most important map of 2012. Both the Risk Zone map and the Risk Finder are grounded in peer-reviewed science.Back to topMethods and QualifiersThis map is based on analysis of digital elevation models mosaicked together for near-total coverage of the global coast. Details and sources for U.S. and international data are below. Elevations are transformed so they are expressed relative to local high tide lines (Mean Higher High Water, or MHHW). A simple elevation threshold-based “bathtub method” is then applied to determine areas below different water levels, relative to MHHW. Within the U.S., areas below the selected water level but apparently not connected to the ocean at that level are shown in a stippled green (as opposed to solid blue) on the map. Outside the U.S., due to data quality issues and data limitations, all areas below the selected level are shown as solid blue, unless separated from the ocean by a ridge at least 20 meters (66 feet) above MHHW, in which case they are shown as not affected (no blue).Areas using lidar-based elevation data: U.S. coastal states except AlaskaElevation data used for parts of this map within the U.S. come almost entirely from ~5-meter horizontal resolution digital elevation models curated and distributed by NOAA in its Coastal Lidar collection, derived from high-accuracy laser-rangefinding measurements. The same data are used in NOAA’s Sea Level Rise Viewer. (High-resolution elevation data for Louisiana, southeast Virginia, and limited other areas comes from the U.S. Geological Survey (USGS)). Areas using CoastalDEM™ elevation data: Antigua and Barbuda, Barbados, Corn Island (Nicaragua), Dominica, Dominican Republic, Grenada, Guyana, Haiti, Jamaica, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, San Blas (Panama), Suriname, The Bahamas, Trinidad and Tobago. CoastalDEM™ is a proprietary high-accuracy bare earth elevation dataset developed especially for low-lying coastal areas by Climate Central. Use our contact form to request more information.Warning for areas using other elevation data (all other areas)Areas of this map not listed above use elevation data on a roughly 90-meter horizontal resolution grid derived from NASA’s Shuttle Radar Topography Mission (SRTM). SRTM provides surface elevations, not bare earth elevations, causing it to commonly overestimate elevations, especially in areas with dense and tall buildings or vegetation. Therefore, the map under-portrays areas that could be submerged at each water level, and exposure is greater than shown (Kulp and Strauss, 2016). However, SRTM includes error in both directions, so some areas showing exposure may not be at risk.SRTM data do not cover latitudes farther north than 60 degrees or farther south than 56 degrees, meaning that sparsely populated parts of Arctic Circle nations are not mapped here, and may show visual artifacts.Areas of this map in Alaska use elevation data on a roughly 60-meter horizontal resolution grid supplied by the U.S. Geological Survey (USGS). This data is referenced to a vertical reference frame from 1929, based on historic sea levels, and with no established conversion to modern reference frames. The data also do not take into account subsequent land uplift and subsidence, widespread in the state. As a consequence, low confidence should be placed in Alaska map portions.Flood control structures (U.S.)Levees, walls, dams or other features may protect some areas, especially at lower elevations. Levees and other flood control structures are included in this map within but not outside of the U.S., due to poor and missing data. Within the U.S., data limitations, such as an incomplete inventory of levees, and a lack of levee height data, still make assessing protection difficult. For this map, levees are assumed high and strong enough for flood protection. However, it is important to note that only 8% of monitored levees in the U.S. are rated in “Acceptable” condition (ASCE). Also note that the map implicitly includes unmapped levees and their heights, if broad enough to be effectively captured directly by the elevation data.For more information on how Surging Seas incorporates levees and elevation data in Louisiana, view our Louisiana levees and DEMs methods PDF. For more information on how Surging Seas incorporates dams in Massachusetts, view the Surging Seas column of the web tools comparison matrix for Massachusetts.ErrorErrors or omissions in elevation or levee data may lead to areas being misclassified. Furthermore, this analysis does not account for future erosion, marsh migration, or construction. As is general best practice, local detail should be verified with a site visit. Sites located in zones below a given water level may or may not be subject to flooding at that level, and sites shown as isolated may or may not be be so. Areas may be connected to water via porous bedrock geology, and also may also be connected via channels, holes, or passages for drainage that the elevation data fails to or cannot pick up. In addition, sea level rise may cause problems even in isolated low zones during rainstorms by inhibiting drainage.ConnectivityAt any water height, there will be isolated, low-lying areas whose elevation falls below the water level, but are protected from coastal flooding by either man-made flood control structures (such as levees), or the natural topography of the surrounding land. In areas using lidar-based elevation data or CoastalDEM (see above), elevation data is accurate enough that non-connected areas can be clearly identified and treated separately in analysis (these areas are colored green on the map). In the U.S., levee data are complete enough to factor levees into determining connectivity as well.However, in other areas, elevation data is much less accurate, and noisy error often produces “speckled” artifacts in the flood maps, commonly in areas that should show complete inundation. Removing non-connected areas in these places could greatly underestimate the potential for flood exposure. For this reason, in these regions, the only areas removed from the map and excluded from analysis are separated from the ocean by a ridge of at least 20 meters (66 feet) above the local high tide line, according to the data, so coastal flooding would almost certainly be impossible (e.g., the Caspian Sea region).Back to topData LayersWater Level | Projections | Legend | Social Vulnerability | Population | Ethnicity | Income | Property | LandmarksWater LevelWater level means feet or meters above the local high tide line (“Mean Higher High Water”) instead of standard elevation. Methods described above explain how each map is generated based on a selected water level. Water can reach different levels in different time frames through combinations of sea level rise, tide and storm surge. Tide gauges shown on the map show related projections (see just below).The highest water levels on this map (10, 20 and 30 meters) provide reference points for possible flood risk from tsunamis, in regions prone to them.

About this dataset

Context

The dataset tabulates the Blue Lake population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Blue Lake across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Blue Lake was 1,183, a 1.09% decrease year-by-year from 2021. Previously, in 2021, Blue Lake population was 1,196, a decline of 0.33% compared to a population of 1,200 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Blue Lake increased by 83. In this period, the peak population was 1,265 in the year 2016. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Blue Lake is shown in this column.
• Year on Year Change: This column displays the change in Blue Lake population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Blue Lake Population by Year. You can refer the same here

Missouri has taken part in all 51 U.S. presidential elections since 1820, voting for the winning candidate on 37 occasions, giving a success rate of 73 percent. Missouri was a staunchly Democrat state for most of the nineteenth century, only voting Republican during the Civil War and Reconstruction. Throughout the twentieth century, Missouri was the epitomic bellwether state; siding with the winning candidate in 23 out of 25 elections, only failing to vote for the nationwide winner in 1900 and 1956. The Show-Me State has voted for the Republican Party's nominee in the past six elections, with Donald Trump winning the 2016 election in Missouri by the largest margin in over three decades; the state's status has changed from being a battleground state to a safe red state, and in the 2020 election, Donald Trump won the state again, with the same share of the popular vote. Missouri's President As of 2020, President Harry S. Truman is the only Missouri native to have ascended to the presidency. Truman was born and raised in Missouri, and then represented his home state in the senate, before winning the vice presidency in the 1944 election, and ascending to the presidency less than four months after taking office. No other president has been born in or resided in Missouri when taking office, nor has any major party candidate (although Benjamin G. Brown did receive some electoral votes in the 1872*** election). Electoral votes Since its admission to the union in 1821****, Missouri's allocation of electoral votes grew from just three to eighteen throughout the nineteenth century. It then plateaued at this number from 1904 to 1928, but has fallen to just ten votes since 2012. For the past century, Missouri's population growth in each decade has been below ten percent, and growing at a much lower rate than the national average; it is estimated that Missouri's population growth in the 2010s was just 2.5 percent, which is its lowest growth rate of any decade since records began.

The state of Indiana has taken part in all U.S. presidential elections since 1816, and correctly voted for the winning candidate in 38 out of 52 elections, giving a success rate of 73 percent. Indiana's electors have always voted for a major party nominee; voting for the Whig nominee twice, the Democratic-Republican nominee three times, the Democratic Party's nominee 14 times, and the Republican Party's nominee 33 times. Since 1940, Indiana has voted for the Republican candidate in all but two elections, which were in 1964 and 2008; in the 2020 election, Republican nominee Donald Trump won the popular vote in Indiana by a margin of 16 percent.. Indiana natives Indiana has been home to one U.S. president, as Benjamin Harrison moved there in his twenties before becoming a lawyer and entering the world of politics. No U.S. president has ever been born in Indiana, Vice President Mike Pence was born and raised in the Hoosier State, and was Governor before becoming vice president. FDR's opponent in the 1940 election, Wendell Wilkie, was also born there. Indiana native Pete Buttigieg made history in the 2020 election cycle, by becoming the first openly gay person to launch a major presidential campaign and win a presidential primary or caucus; although he later dropped out of the race. Electoral votes Indiana was allocated just three electoral votes in its first few presidential elections; an influx of migrants saw the population grow rapidly in the next five decades, and the state had 15 electoral votes in elections between 1872 and 1928. Since the 1920s, Indiana's allocation of electoral votes has gradually decreased, falling to eleven in the four most recent elections, and it is expected to remain at eleven until the 2024 election.