Money Supply M0 in the United States decreased to 5740300 USD Million in July from 5748800 USD Million in June of 2025. This dataset provides - United States Money Supply M0 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Money Supply M2 in the United States increased to 21942 USD Billion in May from 21862.40 USD Billion in April of 2025. This dataset provides - United States Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Money Supply M0 in Canada decreased to 214637 CAD Million in June from 220343 CAD Million in May of 2025. This dataset provides - Canada Money Supply M0 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset illustrates the median household income in Money Creek township, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for Money Creek township increased by $3,940 (4.55%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 6 years and declined for 7 years.

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 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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 Money Creek township median household income. You can refer the same here

Money Supply M0 in the United Kingdom increased to 99678 GBP Million in June from 99403 GBP Million in May of 2025. This dataset provides - United Kingdom Money Supply M0 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Money Creek township. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Money Creek township. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Money Creek township, the median household income stands at $95,500 for householders within the 25 to 44 years age group, followed by $93,958 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $76,875.

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.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific 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 Money Creek township median household income by age. You can refer the same here

Context

There is a lack of public available datasets on financial services and specially in the emerging mobile money transactions domain. Financial datasets are important to many researchers and in particular to us performing research in the domain of fraud detection. Part of the problem is the intrinsically private nature of financial transactions, that leads to no publicly available datasets.

We present a synthetic dataset generated using the simulator called PaySim as an approach to such a problem. PaySim uses aggregated data from the private dataset to generate a synthetic dataset that resembles the normal operation of transactions and injects malicious behaviour to later evaluate the performance of fraud detection methods.

Content

PaySim simulates mobile money transactions based on a sample of real transactions extracted from one month of financial logs from a mobile money service implemented in an African country. The original logs were provided by a multinational company, who is the provider of the mobile financial service which is currently running in more than 14 countries all around the world.

This synthetic dataset is scaled down 1/4 of the original dataset and it is created just for Kaggle.

Headers

This is a sample of 1 row with headers explanation:

1,PAYMENT,1060.31,C429214117,1089.0,28.69,M1591654462,0.0,0.0,0,0

step - maps a unit of time in the real world. In this case 1 step is 1 hour of time. Total steps 744 (30 days simulation).

type - CASH-IN, CASH-OUT, DEBIT, PAYMENT and TRANSFER.

amount - amount of the transaction in local currency.

nameOrig - customer who started the transaction

oldbalanceOrg - initial balance before the transaction

newbalanceOrig - new balance after the transaction

nameDest - customer who is the recipient of the transaction

oldbalanceDest - initial balance recipient before the transaction. Note that there is not information for customers that start with M (Merchants).

newbalanceDest - new balance recipient after the transaction. Note that there is not information for customers that start with M (Merchants).

isFraud - This is the transactions made by the fraudulent agents inside the simulation. In this specific dataset the fraudulent behavior of the agents aims to profit by taking control or customers accounts and try to empty the funds by transferring to another account and then cashing out of the system.

isFlaggedFraud - The business model aims to control massive transfers from one account to another and flags illegal attempts. An illegal attempt in this dataset is an attempt to transfer more than 200.000 in a single transaction.

Past Research

There are 5 similar files that contain the run of 5 different scenarios. These files are better explained at my PhD thesis chapter 7 (PhD Thesis Available here http://urn.kb.se/resolve?urn=urn:nbn:se:bth-12932).

We ran PaySim several times using random seeds for 744 steps, representing each hour of one month of real time, which matches the original logs. Each run took around 45 minutes on an i7 intel processor with 16GB of RAM. The final result of a run contains approximately 24 million of financial records divided into the 5 types of categories: CASH-IN, CASH-OUT, DEBIT, PAYMENT and TRANSFER.

Acknowledgements

This work is part of the research project ”Scalable resource-efficient systems for big data analytics” funded by the Knowledge Foundation (grant: 20140032) in Sweden.

Please refer to this dataset using the following citations:

PaySim first paper of the simulator:

E. A. Lopez-Rojas , A. Elmir, and S. Axelsson. "PaySim: A financial mobile money simulator for fraud detection". In: The 28th European Modeling and Simulation Symposium-EMSS, Larnaca, Cyprus. 2016

Description of the Dataset: A Comprehensive Record of Personal Savings Account Transactions

This dataset provides a detailed record of an individual's savings bank account transactions spanning the years 2022 and 2023. It encompasses a total of 10 columns, consisting of 6 primary columns and 4 secondary columns.

The 6 Primary Columns Are: 1. Date: This column records the date of each transaction. 2. Debit or Credit: It signifies whether each transaction involves a debit (money withdrawn) or a credit (money deposited). 3. Amount: This column documents the monetary value associated with each transaction. 4. Balance: It records the account balance after each transaction. 5. Method of Transaction: This column specifies the method or channel through which the transaction was executed. 6. Name of Person: It identifies the person involved in the transaction.

In addition to these primary columns, there is an essential secondary column: i.e., Tday (Transaction Day): This column is designed to highlight specific days with multiple transactions. It indicates the occurrence of multiple transactions on the same date, providing valuable information about account activity.

This dataset comprises a total of 509 transactions, and within these transactions, there are 313 unique transaction dates. This unique date count underscores that the dataset includes days with multiple transactions, and the 'Tday' column is utilized to distinguish and track such instances.

Refer the data for more insights. You will also be able to see Pareto distribution (Find it out!!)

Context

This dataset was created from the online retail dataset found here https://www.kaggle.com/roshansharma/online-retail. This has had some processing for customer segmentation so it can be used for nice visualisation of the data.

Content

The following variables are used: | Variable | Description | | --- | --- | |**CustomerID**| This is the same CustomerID field as in the online retail dataset found in the link above and can be linked to this dataset.| |**Frequency**|This is how many times a customer purchased.| |**Recency**|This is how many days ago a customer made a purchase. This is adjusted to reference a point in time.| |**Monetary** |This is how much a customer spent in total. Their total Lifetime monetary value.| |**rankF**|This is the Frequency value divided into different ranges from 1 to 5 using the cut function in R. (5 = lots of visits, 1 = very low visits)| |**rankR**|This is the Recency value divided into different ranges from 1 to 5 using the cut function in R and then flipped. (5 = very Recent, 1 = ages ago) | |**rankM**|This is the Monetary value divided into different ranges from 1 to 5 using the cut function in R. (5 = High spender, 1 = low spender) | |**groupRFM**| The group RFM is a value combining the rankR, rankF and rankM. This uses 1 digit per rank (ie 1 rankR, 2 rankF, 5 rankM would be 125 Group)| |**Country**|This is the customer delivery country from the original online retail dataset.| |**Customer_Segment**| A customer segment is added to give a more human description of the customer and therefore can be treated differently. These segments are listed below.|

Customer Segments

The customer segments below detail the description of the customers from their details processed in the RFM analysis. | Customer Segment | Segment Description | | --- | --- | |**Champions** | Bought recently buy often and spend the most | |**Loyal Customers**|Spend good money Responsive to promotions| |**Potential Loyalist**|Recent customers spent good amount, bought more than once| |**Recent High Spender**|Recent customers not frequent but spend some| |**New Customers**|Bought more recently but not often| |**Promising**|Recent shoppers but haven’t spent much| |**Need Attention**|Above average recency frequency & monetary values| |**About To Sleep**|Below average recency frequency & monetary values| |**At Risk**|Spent big money purchased often but long time ago| |**Can’t Lose Them**|Made big purchases and often but long time ago| |**Hibernating**|Low spenders low frequency purchased long time ago| |**Lost**|Lowestrecency frequency & monetary scores|

Acknowledgements

Thank you to the owners of the online retail dataset. https://www.kaggle.com/roshansharma

Inspiration

The online retail dataset is a great set for finding anomalies and doing some interesting reports, however RFM analysis allows you to treat clusters of data in the same way which is suitable for marketing teams etc.

RFM analysis is a straight forward analytical process that can be achieved by clustering but a more manual process is good as you can adjust these figures to get more even groups. I will post my R code for this and link shortly.| | | | | --- | --- | | | | | | | --- | --- | | | |

About this dataset

Context

The dataset illustrates the median household income in Money Creek township, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2021, the median household income for Money Creek township decreased by $6,986 (8.39%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.

Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 4 years and declined for 7 years.

https://i.neilsberg.com/ch/money-creek-township-mn-median-household-income-trend.jpeg" alt="Money Creek Township, Minnesota median household income trend (2010-2021, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2021
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2022 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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 Money Creek township median household income. You can refer the same here

Money Supply M1 in the United States increased to 18861.10 USD Billion in July from 18803.40 USD Billion in June of 2025. This dataset provides - United States Money Supply M1 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Total outstanding debt of the U.S. government reported daily. Includes a breakout of intragovernmental holdings (federal debt held by U.S. government) and debt held by the public (federal debt held by entities outside the U.S. government).

Description This submission is categorized under "LGF/A US", but also applies to "LGF/B US", increasing $ ADV and borrow. RECOMMENDATION: SHORT Lions Gate with 40-70% upside driven by 1) untenable leverage, 2) 25%+ misses on OIBDA (EBITDA equivalent), and 3) a failed spin process. DESCRIPTION: LGF consists of two businesses: (i) Studio (~2/3 of revenue) that produces, distributes, and licenses movies and TV shows and (ii) Starz (~1/3 of revenue), which is an on-demand TV offering that caters to niche audiences. short interest api stock value calculator Black Scholes Calculator THESIS 1: LGF has an untenable ~5-6x OIBDA leverage, a content library that doesn’t generate enough cash to de-lever, and accounting that disincents debt paydown. Investors will become frustrated by high and rising leverage, falling reported FCF, and a rising cost of debt LGF’s studio content has soured and new releases have underperformed (last 2 Rambos lost money, Saw is 2 movies past “Saw the Final Chapter”, the last Hunger Games was released 8 years ago and the newly released prequel is underperforming HSX.com expectations, the last Expendables underperformed, etc.). LGF’s new releases are financed with production loans that LGF now cannot afford to repay and have therefore ballooned to all-time highs (~300% above long-term median). While production loans are non-recourse, management will admit that LGF cannot default on its production loans (and never has) given LGF’s new releases / survival are reliant upon new production loan issuances. Moreover, LGF’s accounting disincents production loan repayment given production loan paydown is treated as a use of FCF, meaning repayment leads to reporting troubling negative FCF for a highly overlevered business. Additionally, LGF has sizable term loan + bond balances from overpaying for Starz and other poor managerial decisions. Therefore, LGF is stuck in a precarious situation in which they have elevated leverage, no path for repayment, and a deteriorating content slate, which will prove increasingly troubling for investors. THESIS 2: LGF will miss on OIBDA by 25%+, leading to a de-rating Desperate to lower leverage and show growth, management gave an overly aggressive guide for LTM 1Q23-LTM 1Q24. To hit the guide, LGF released titles across all of its remaining functional franchises including (i) John Wick, (ii) a John Wick spin TV show, (iii) Expendables, (iv) Saw, and (v) Hunger Games. A box office unit economics analysis indicates that new content releases alone will not be enough to hit the Studio guide. Therefore, to temporarily hit numbers, management was forced to aggressively license content by signing longer-term deals (revenue derived from licensing is recognized immediately irrespective of contract length, so signing a 5-year deal allows more revenue to be pulled forward and recognized than a 2-year deal). This pull-forward led LGF to print revenue / OIBDA numbers that cannot be sustained. Despite LGF’s unsustainable release slate and licensing, St is projecting MSD % revenue and mid-teens % OIBDA growth off the elevated LTM 1Q24 figures, setting LGF up for 20-30% OIBDA misses. As LGF misses, investors will become disappointed and leverage levels will rise, exacerbating investor frustration. THESIS 3: desperate for a permanent solution to its overleverage and declining content slate, management is attempting a spin that will asset strip at bondholders’ expense. Bondholders have picked up on this, formed a bond group to block the spin, and are succeeding. A failed spin will disappoint bulls, leading to a SoTP valuation that implies 40-60% downside Nancy Pelosi Stock Trades Tracker Congress Stock Trades Tracker To address overleverage and a declining content slate, management is turning to corporate actions to find a permanent solution. Management is attempting to strip the assets of value (the Studio) from LGF, leaving bondholders behind with only the low-quality assets (Starz). This will allow management to pursue a sale of the de-levered Studio post-spin and more value to be captured by Studio equity holders. However, this contemplated spin trips a change in control provision that states the bonds must be refi’d out if “all or substantially all” of the assets change hands given the Studio represents just about all or substantially all of LGF’s FMV. Management is attempting to argue that “all or substantially all” of the BOOK VALUE is not changing hands and so the change in control provision is not triggered, but this argument is a stretch. A bond group has formed to fight management on this and there are data points to indicate that they are winning (management has alluded to concessions, bonds are being repurchased in the pubic markets, the spin has been delayed 3x, etc.). If the bonds have to be refi’d out, the spin destroys shareholder value given the cost of debt for the bonds rises 3x+ from the current 5.5% coupon closer to the bonds’ current mid- to high-teens...

About this dataset

Context

The dataset presents median household incomes for various household sizes in Money Creek Township, Minnesota, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

Key observations

• Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Money Creek township did not include 5, 6, or 7-person households. Across the different household sizes in Money Creek township the mean income is $99,257, and the standard deviation is $53,799. The coefficient of variation (CV) is 54.20%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
• In the most recent year, 2021, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $60,594. It then further increased to $177,675 for 4-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/money-creek-township-mn-median-household-income-by-household-size.jpeg" alt="Money Creek Township, Minnesota median household income, by household size (in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Household Sizes:

• 1-person households
• 2-person households
• 3-person households
• 4-person households
• 5-person households
• 6-person households
• 7-or-more-person households

Variables / Data Columns

• Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific household size.

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 Money Creek township median household income. You can refer the same here

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 Money Creek township. 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 Money Creek township, the median income for all workers aged 15 years and older, regardless of work hours, was $42,604 for males and $39,643 for females.

Based on these incomes, we observe a gender gap percentage of approximately 7%, indicating a significant disparity between the median incomes of males and females in Money Creek township. Women, regardless of work hours, still earn 93 cents to each dollar earned by men, highlighting an ongoing gender-based wage gap.

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.08 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

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 Money Creek township median household income by race. You can refer the same here

Money Supply M2 in China decreased to 329940 CNY Billion in July from 330332.50 CNY Billion in June of 2025. This dataset provides - China Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Context

I am fascinated by statistics and even more by Football, that's why I always wanted to have data available to analyze and draw conclusions. So I decided to put together a table with data obtained from different sources.

Content

The dataset contains statistical summary data by the end of each season from 2014 for the five big Leagues of Europe:

• La Liga
• English Premier League
• BundesLiga
• Serie A
• Ligue 1

The dataset is organized in 5 files:

Football_Data.csv contains data about each game. Transfer_team.csv - contains data with the information about transfers of each team. stats_per_game.csv - contains information for every team match. metric.txt - contains the textual description of each variable

Acknowledgements

Huge thanks for the team of understat.com for collecting this data and to Sergi Lehyki for scraped it!

Inspiration

Football data allows Data Scientist explore and learn by thousands of different questions. Let you feel free to analyse the data and try to discover new features or to confirm some hypothesis, like:

• First position teams tend to have more ball pressure.
• Last position teams always have less points than expected.
• Which League expend more money on transfers?.
• Who was the best champion since 2014 from all leagues?.
• Who was the team that had the most games in a row before the first draw?

And many more..

Contribute

If you notice a mistake or the results are being updated fast enough for your liking, you can fix that by submitting a pull request.

Money Supply M2 in India increased to 71905.21 INR Billion in May from 67821.12 INR Billion in April of 2025. This dataset provides - India Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Money Creek Township, Minnesota, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Money Creek Township, Minnesota reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Money Creek township households based on income levels.

Key observations

• For Family Households: In Money Creek township, the majority of family households, representing 28.48%, earn $60,000 to $74,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $10,000 to $14,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Money Creek township, the majority of non-family households, accounting for 33.33%, have income Less than $10,000, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $10,000 to $14,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

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

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Money Creek Township, Minnesota (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Money Creek Township, Minnesota
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Money Creek Township, Minnesota
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Money Creek Township, Minnesota

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 Money Creek township median household income. You can refer the same here

Money Supply M2 In the Euro Area decreased to 15710290 EUR Million in June from 15736686 EUR Million in May of 2025. This dataset provides the latest reported value for - Euro Area Money Supply M2 - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.