Cotton fell to 66.13 USd/Lbs on July 11, 2025, down 0.06% from the previous day. Over the past month, Cotton's price has risen 1.49%, but it is still 3.81% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Cotton - values, historical data, forecasts and news - updated on July of 2025.

This dataset provides values for COTTON reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Dropping Ogallala aquifer levels and changing commodity prices and energy costs make irrigation management an important but uncertain issue to west Texas cotton producers. For example, is deficit or full irrigation more profitable under the current lint price and pumping cost conditions? Also, what is the best way to divide production into dryland and irrigated acreage with limited well capacity? To help producers answer these questions this web application estimates the effects of irrigation on the profitability of center pivot cotton production on the Southern High Plains. It's main purpose is to show the impact of irrigation on yield and the related effects on both profits per acre and profits over a center pivot area with combined dryland and irrigated production. Resources in this dataset:Resource Title: Cotton Irrigation Tool. File Name: Web Page, url: https://www.ars.usda.gov/research/software/download/?softwareid=486&modecode=30-96-05-00 download page

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Cotton Index: The Future of Textile Trade?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Cotton On-Call Report shows the quantity of call cotton bought or sold on which the price has not been fixed, together with the respective futures on which the purchase or sale is based on.

About this dataset

Context

The dataset tabulates the Cotton Plant 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 Cotton Plant 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 Cotton Plant was 499, a 1.58% decrease year-by-year from 2022. Previously, in 2022, Cotton Plant population was 507, a decline of 1.17% compared to a population of 513 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Cotton Plant decreased by 452. In this period, the peak population was 951 in the year 2000. 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 Cotton Plant is shown in this column.
• Year on Year Change: This column displays the change in Cotton Plant 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 Cotton Plant Population by Year. You can refer the same here

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Will the Cotton Index Signal a Shift in the Market?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

19336 Global export shipment records of Cotton Bales with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

This dataset tracks annual reduced-price lunch eligibility from 2003 to 2023 for Cotton Creek School vs. Illinois and Wauconda CUSD 118 School District

This dataset tracks annual reduced-price lunch eligibility from 2004 to 2023 for Cotton Boll School vs. Arizona and Peoria Unified School District (4237)

The spread of cotton leaf curl disease in China, India and Pakistan is a recent phenomenon. Analysis of available sequence data determined that there is a substantial diversity of cotton-infecting geminiviruses in Pakistan. Phylogenetic analyses indicated that recombination between two major groups of viruses, cotton leaf curl Multan virus (CLCuMuV) and cotton leaf curl Kokhran virus (CLCuKoV), led to the emergence of several new viruses. Recombination detection programs and phylogenetic analyses showed that CLCuMuV and CLCuKoV are highly recombinant viruses. Indeed, CLCuKoV appeared to be a major donor virus for the coat protein (CP) gene, while CLCuMuV donated the Rep gene in the majority of recombination events. Using recombination free nucleotide datasets the substitution rates for CP and Rep genes were determined. We inferred similar nucleotide substitution rates for the CLCuMuV-Rep gene (4.96X10-4) and CLCuKoV-CP gene (2.706X10-4), whereas relatively higher substitution rates were observed for CLCuMuV-CP and CLCuKoV-Rep genes. The combination of sequences with equal and relatively low substitution rates, seemed to result in the emergence of viral isolates that caused epidemics in Pakistan and India. Our findings also suggest that CLCuMuV is spreading at an alarming rate, which can potentially be a threat to cotton production in the Indian subcontinent.

About this dataset

Context

The dataset tabulates the Cotton County 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 Cotton County 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 Cotton County was 5,427, a 0.40% decrease year-by-year from 2022. Previously, in 2022, Cotton County population was 5,449, an increase of 0.13% compared to a population of 5,442 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Cotton County decreased by 1,191. In this period, the peak population was 6,618 in the year 2000. 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 Cotton County is shown in this column.
• Year on Year Change: This column displays the change in Cotton County 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 Cotton County Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Cotton 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 Cotton 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 Cotton township was 454, a 0% decrease year-by-year from 2022. Previously, in 2022, Cotton township population was 454, an increase of 0.22% compared to a population of 453 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Cotton township decreased by 63. In this period, the peak population was 517 in the year 2000. 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 Cotton township is shown in this column.
• Year on Year Change: This column displays the change in Cotton 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 Cotton township Population by Year. You can refer the same here