About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in London, KY, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 8,406, while the mean income for the highest quintile (20% of households with the highest income) is 144,994. This indicates that the top earners earn 17 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 249,623, which is 172.16% higher compared to the highest quintile, and 2969.58% higher compared to the lowest quintile.

https://i.neilsberg.com/ch/london-ky-mean-household-income-by-quintiles.jpeg" alt="Mean household income by quintiles in London, KY (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.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

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 London median household income. You can refer the same here

In 2024, the there were more private renters in London, England, than owner-occupiers with a mortgage. Approximately *** million households occupied a privately rented home, compared to less than a million that were buying a home with a mortgage. Additionally, approximately ******* households owned their home without a mortgage. Although buying a house in London is far from affordable, it is still cheaper than renting.

Energy consumption readings for a sample of 5,567 London Households that took part in the UK Power Networks led Low Carbon London project between November 2011 and February 2014.

Readings were taken at half hourly intervals. The customers in the trial were recruited as a balanced sample representative of the Greater London population.

The dataset contains energy consumption, in kWh (per half hour), unique household identifier, date and time. The CSV file is around 10GB when unzipped and contains around 167million rows.

Within the data set are two groups of customers. The first is a sub-group, of approximately 1100 customers, who were subjected to Dynamic Time of Use (dToU) energy prices throughout the 2013 calendar year period. The tariff prices were given a day ahead via the Smart Meter IHD (In Home Display) or text message to mobile phone. Customers were issued High (67.20p/kWh), Low (3.99p/kWh) or normal (11.76p/kWh) price signals and the times of day these applied. The dates/times and the price signal schedule is availaible as part of this dataset. All non-Time of Use customers were on a flat rate tariff of 14.228pence/kWh.

The signals given were designed to be representative of the types of signal that may be used in the future to manage both high renewable generation (supply following) operation and also test the potential to use high price signals to reduce stress on local distribution grids during periods of stress.

The remaining sample of approximately 4500 customers energy consumption readings were not subject to the dToU tariff.

More information can be found on the Low Carbon London webpage

Some analysis of this data can be seen here.

The average household size in London was 2.51 people per household in 2024, compared with the UK average of 2.35 people per household.

This statistics shows the sources of income for working London households as a share of theirgross weekly household income. For working households in London, ** percent of income came from wages and salaries, with ** percent coming from self employment.

About this dataset

Context

The dataset presents median household incomes for various household sizes in London, OH, 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, all of the household sizes were found in London. Across the different household sizes in London the mean income is $83,188, and the standard deviation is $27,435. The coefficient of variation (CV) is 32.98%. 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 $41,819. It then further increased to $114,420 for 7-person households, the largest household size for which the bureau reported a median household income.

https://i.neilsberg.com/ch/london-oh-median-household-income-by-household-size.jpeg" alt="London, OH 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 London median household income. You can refer the same here

In 2023/24 London had the highest average weekly household income before housing costs were considered in the United Kingdom, at *** British pounds a week, compared with the UK average of *** pounds a week.

Graph and download economic data for Estimate of Median Household Income for New London County, CT (MHICT09011A052NCEN) from 1989 to 2021 about New London County, CT; Norwich; CT; households; median; income; and USA.

FOCUSONLONDON2010:INCOMEANDSPENDINGATHOME Household income in London far exceeds that of any other region in the UK. At £900 per week, London’s gross weekly household income is 15 per cent higher than the next highest region. Despite this, the costs to each household are also higher in the capital. Londoners pay a greater amount of their income in tax and national insurance than the UK average as well as footing a higher bill for housing and everyday necessities. All of which leaves London households less well off than the headline figures suggest. This chapter, authored by Richard Walker in the GLA Intelligence Unit, begins with an analysis of income at both individual and household level, before discussing the distribution and sources of income. This is followed by a look at wealth and borrowing and finally, focuses on expenditure including an insight to the cost of housing in London, compared with other regions in the UK. See other reports from this Focus on London series. PRESENTATION: This interactive presentation finds the answer to the question, who really is better off, an average London or UK household? This analysis takes into account available data from all types of income and expenditure. Click on the link to access.

Context

The dataset featured below was created by aggregating hourly energy consumption data from individual London homes provided by UK Power Networks. The dataset keeps track of the energy consumption of 5,567 randomly selected households in London from November 2011 to February 2014.

-> This energy dataset is a great addition to this London Weather Dataset. You can join both datasets on the 'date' attribute, after some preprocessing, and perform some interesting data analytics regarding how energy consumption was impacted by the weather in London.

Content

The size for the file featured within this Kaggle dataset is shown below — along with a list of attributes and their description summaries: - london_energy.csv - 3510433 observations x 3 attributes

1. LCLid - individual household unique identifier - (str)
2. Date - date of recorded measurement - (date)
3. KWH - energy consumption measurement in kWh - (float)

Source

Energy Data - https://data.london.gov.uk/dataset/smartmeter-energy-use-data-in-london-households

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

FOCUSONLONDON2010:INCOMEANDSPENDINGATHOME

Household income in London far exceeds that of any other region in the UK. At £900 per week, London’s gross weekly household income is 15 per cent higher than the next highest region. Despite this, the costs to each household are also higher in the capital. Londoners pay a greater amount of their income in tax and national insurance than the UK average as well as footing a higher bill for housing and everyday necessities. All of which leaves London households less well off than the headline figures suggest.

This chapter, authored by Richard Walker in the GLA Intelligence Unit, begins with an analysis of income at both individual and household level, before discussing the distribution and sources of income. This is followed by a look at wealth and borrowing and finally, focuses on expenditure including an insight to the cost of housing in London, compared with other regions in the UK.

See other reports from this Focus on London series.

PRESENTATION:

This interactive presentation finds the answer to the question, who really is better off, an average London or UK household? This analysis takes into account available data from all types of income and expenditure. Click on the link to access.

PREZI

FACTS:

Some interesting facts from the data…

• Five boroughs with the highest median gross weekly pay per person in 2009:
• 1. Kensington & Chelsea - £809
• 2. City of London - £767
• 3. Westminster - £675
• 4. Wandsworth - £636
• 5. Richmond - £623
• ...
• 32. Brent - £439
• 33. Newham - £422
• Five boroughs with the highest median weekly rent for a 2 bedroom property in October 2010:
• 1. Kensington & Chelsea - £550
• 2. Westminster - £500
• 3. City of London - £450
• 4. Camden - £375
• 5. Islington - £360
• ...
• 32. Havering - £183
• 33. Bexley - £173
• Five boroughs with the highest percentage of households that own their home outright in 2009:
• 1. Bexley – 38 per cent
• 2. Havering – 36 per cent
• 3. Richmond – 32 per cent
• 4. Bromley – 31 per cent
• 5. Barnet – 28 per cent
• ...
• 31. Tower Hamlets – 9 per cent
• 32. Southwark – 9 per cent

The volume of regular household waste collections in London, England was approximately 1.6 million metric tons for the year ended March 2023. The amount of household waste from regular household collections in London has decreased notably over the past two decades.

This dataset is a cleaned up version of the London dataset. This dataset was create to do forecasting on

In 2023, the net number of housing units added to the stock in London was lower than the household formation. That was a bad sign for the housing shortage, as it is necessary to have more new dwellings than households moving in to the city to ensure that there is housing for everyone.

Estimate of Median Household Income for New London County, CT was 78552.00000 $ in January of 2021, according to the United States Federal Reserve. Historically, Estimate of Median Household Income for New London County, CT reached a record high of 78552.00000 in January of 2021 and a record low of 36422.00000 in January of 1989. Trading Economics provides the current actual value, an historical data chart and related indicators for Estimate of Median Household Income for New London County, CT - last updated from the United States Federal Reserve on December of 2025.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F10373355%2F54284ab1fa129bca103b985046a162fb%2FInfographic-1024x576.png?generation=1763876426981513&alt=media" alt="">

🔧 How I Processed the 168 Smart-Meter CSV Files (A Smarter, Faster Approach)

The original Low Carbon London smart-meter dataset is amazing, but working with it is a nightmare:

• 167+ separate daily CSV files

• 170 million rows

• Mixed Std/ToU tariffs

• Timestamps in string format (with microseconds)

• Massive memory load if you try to load everything at once

To handle this efficiently, I used a lightweight Python-based database layer using SQLite3, no heavy external database required, allowing fast loading, indexing, querying, and grouping.

🧠 My Processing Pipeline (Fully Reproducible) 1. Loaded all 167 CSVs into an SQLite database

Instead of concatenating CSVs directly (which can crash memory), I imported each file as its own SQLite table.

for file in extracted_files: if file.endswith('.csv'): df = pd.read_csv(os.path.join(unzip_dir, file)) table_name = file.replace('.csv','').replace(' ','_') df.to_sql(table_name, conn, if_exists='replace', index=False)

2. Queried the database efficiently by year

SQLite allowed me to run fast, SQL-based time filters, extracting only the rows belonging to each year.

def query_by_year(year): for table in table_names: query = f""" SELECT * FROM "{table}" WHERE strftime('%Y', DateTime) = '{year}' """ dfs.append(pd.read_sql(query, conn))

This avoided loading all 170M rows at once.

3. Combined all yearly data into a single clean DataFrame df_2011 = query_by_year("2011") df_2012 = query_by_year("2012") df_2013 = query_by_year("2013") df_2014 = query_by_year("2014")

4. Stored each cleaned year in Feather format (2–3 seconds loading time) df_2011.to_feather('2011_data.feather')

Feather loads 100× faster than CSV and preserves all dtypes.

🧼 Cleaning & Feature Engineering (Full Transparency) ✔ Merged all 167 files chronologically

2011-11-01 → 2014-02-28

✔ Converted DateTime strings → datetime64[ns]

Removed microseconds (dataset inconsistency).

✔ Removed duplicates & interpolated missing 30-min readings

(Low Carbon London has rare gaps.)

✔ Encoded household IDs

LCLid → integer labels (0–5566)

✔ Engineered forecasting-ready features

Per household:

• Lag features: Lag_1, Lag_2, Lag_3

• Rolling mean + std (3 and 10 windows)

• Hour, Weekday, Month (normalized 0–1)

• Weekend flag

• Seasonal dummy variables (Season_Summer, Season_Winter)

✔ Applied Min–Max scaling individually per household

(prevents data leakage)

⚡ Final Output

Your dataset becomes:

1. Clean

2. Chronologically aligned

3. Feature-rich

4. Lightning-fast to load

5. Perfect for forecasting models

🚀 Quick Start import pandas as pd

df_2012 = pd.read_feather("df_2012.feather") df_2012.head()

Loads instantly.

📈 Example LSTM Benchmark (Proof It Works)

Using only the processed data:

Normalized RMSE = 0.0267

Normalized MAE = 0.0150

Equivalent to 65–80 Wh error per half-hour, among the best public results on this dataset.

🧩 Use Cases

This dataset is perfect for:

• LSTM / GRU / Transformer forecasting

• Multi-step prediction

• Consumption profiling & clustering

• Time-of-Use vs Standard tariff analysis

• Anomaly detection

• Energy-focused research

📜 Citation

Original Smart-Meter Dataset UK Power Networks – Low Carbon London Smart Meter Trial Open Government Licence (OGL) https://data.london.gov.uk/dataset/smartmeter-energy-consumption-data-in-london-households

❤️ Final Words

Loading 167 CSVs every time wastes hours. So I fixed it, and turned this giant dataset into a clean, fast, forecasting-ready format.

If this saved you time, please leave an upvote! 🚀 Made with love (and a lot of coffee).

Comprehensive demographic dataset for Jack London, Oakland, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in London. 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 London. 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 London, where there exist only two delineated age groups, the median household income is $42,806 for householders within the 45 to 64 years age group, compared to $36,983 for the 65 years and over age group.

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 London median household income by age. You can refer the same here

The average price of houses bought by first-time buyers was notably lower than houses purchased by repeat buyers in London in 2024. Homebuyers spent on average 480,000 British pounds when purchasing their first property in 2024. For repeat buyers, this figure amounted to 850,000 British pounds in that year. In London, the average house price was about 630,000 British pounds in 2024.