Consumer Price Index CPI in the United States increased to 320.80 points in April from 319.80 points in March of 2025. This dataset provides the latest reported value for - United States Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Three-View Cloud Particle Imager (3V-CPI) is a combination of three imaging instruments. Two of them comprise a 2D-S instrument, in which two 2D probes image particles as they pass through beams that are oriented orthogonally to each other and the airflow. If particles also lie in the intersection of the sensitive areas of the two beams, they are seen by both 2D probes. In that case, the CPI is triggered to take a high-resolution picture, via a briefly illuminated high-resolution imaging array, to provide a third image at high resolution. The probe is particularly suited to imaging ice crystals, but also provide good detection of other hydrometeors including large cloud droplets, drizzle and small rain drops, and precipitation particles. The 3V-CPI measures the size, shape and concentration of water drops and ice particles in clouds in the size range of 15-250 µm. This dataset contains 2D-S imagery collected by the 3V-CPI aboard the NSF/NCAR C130 N130AR during the ICE-T project. The 2DS puts all flight data into 3 files, and the size of these files depends on the amount of time in clouds.

Consumer Price Index CPI in Thailand increased to 100.40 points in May from 100.14 points in April of 2025. This dataset provides the latest reported value for - Thailand Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The dataset represents the joint dynamics of Financial Stress Index (FSI), Consumer Price Index (CPI) calculated and provided by the National Bank of Ukraine (NBU) and Gross Domestic Product (GDP) provided by SSSU for Ukraine.

The monthly dataset range is Feb 2004-Feb 2022, the effective balanced range is Jan 2011-Dec 2021.

The daily FSI data is aggregated into monthly series as a period average. The CPI series are monthly. The quarterly GDP data is seasonally adjusted and interpolated into monthly data with the use of ARIMA model and cubic spline method accordingly, converted into year-over-year series (dGDP).

Context

The Corruption Perceptions Index (CPI)(link is external) was established in 1995 by Transparency International as a composite indicator used to measure perceptions of corruption in the public sector in different countries around the world. During the past 20 years, both the sources used to compile the index and the methodology has been adjusted and refined. The most recent review process took place in 2012 , and some important changes were made to the methodology in 2012(link is external). The method that was used up until 2012 to aggregate different data sources has been simplified and now includes just one year’s data from each data source. Crucially, this method now allows us to compare scores over time, which was not methodologically possible prior to 2012. The methodology follows 4 basic steps: selection of source data, rescaling source data, aggregating the rescaled data and then reporting a measure for uncertainty. Given the changes in the 2012 methodology, this dataset contains two indicators (CPI score and country ranking) for both the old methodology (up to 2011) and the new one (from 2012 onwards), totalling the following four indicators:

1. Corruption Perception Index - Score - New Method (from 2012 onwards - scale from 0 to 100, where 0 re presents very high levels of perceived corruption)
2. CPI score - Old methodology (from 1995 to 2011 - scale from 0 to 10, where 0 represents very high levels of perceived corruption)
3. CPI country ranking - New methodology (from 2012 onwards)
4. CPI country ranking - Old methodology (from 1995 to 2011)

What do the numbers indicate?

The indicator ranges from 0 (Very high level of perceived corruption) to 100 (very low level of perceived corruption.

Original Data

Acknowlegement

Foto von Elimende Inagella auf Unsplash

Monthly indexes and percentage changes for all components and special aggregates of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the corresponding month of the previous year, the previous month and the current month. The base year for the index is 2002=100.

Graph and download economic data for Inflation, consumer prices for the United States (FPCPITOTLZGUSA) from 1960 to 2024 about consumer, CPI, inflation, price index, indexes, price, and USA.

Inflation Rate in India decreased to 3.16 percent in April from 3.34 percent in March of 2025. This dataset provides - India Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

description: A coastal change potential (CPI) was used to map the relative change potential of the coast to sea-level change within Kenai Fjords National Park in Alaska. The CPI ranks the following in terms of their physical contribution to sea-level rise-related coastal change: geomorphology, regional coastal slope, rate of relative sea-level change, historical shoreline change rates, mean tidal range and mean significant wave height. The rankings for each input variable were combined and an index value calculated for 1-minute grid cells covering the park. The CPI highlights those regions where the physical effects of sea-level rise might be the greatest. This approach combines the coastal system's susceptibility to change with its natural ability to adapt to changing environmental conditions, yielding a quantitative, although relative, measure of the park's natural change potential to the effects of sea-level change. The CPI and the data contained within this dataset provide an objective technique for evaluation and long-term planning by scientists and park managers.; abstract: A coastal change potential (CPI) was used to map the relative change potential of the coast to sea-level change within Kenai Fjords National Park in Alaska. The CPI ranks the following in terms of their physical contribution to sea-level rise-related coastal change: geomorphology, regional coastal slope, rate of relative sea-level change, historical shoreline change rates, mean tidal range and mean significant wave height. The rankings for each input variable were combined and an index value calculated for 1-minute grid cells covering the park. The CPI highlights those regions where the physical effects of sea-level rise might be the greatest. This approach combines the coastal system's susceptibility to change with its natural ability to adapt to changing environmental conditions, yielding a quantitative, although relative, measure of the park's natural change potential to the effects of sea-level change. The CPI and the data contained within this dataset provide an objective technique for evaluation and long-term planning by scientists and park managers.

****Dataset Overview**** This dataset contains historical macroeconomic data, featuring key economic indicators in the United States. It includes important metrics such as the Consumer Price Index (CPI), Retail Sales, Unemployment Rate, Industrial Production, Money Supply (M2), and more. The dataset spans from 1993 to the present and includes monthly data on various economic indicators, processed to show their rate of change (either percentage or absolute difference, depending on the indicator).

provenance

The data in this dataset is sourced from the Federal Reserve Economic Data (FRED) database, hosted by the Federal Reserve Bank of St. Louis. FRED provides access to a wide range of economic data, including key macroeconomic indicators for the United States. My work involved calculating the rate of change (ROC) for each indicator and reorganizing the data into a more usable format for analysis. For more information and access to the full database, visit FRED's website.

Purpose and Use for the Kaggle Community:

This dataset is a valuable resource for data scientists, economists, and analysts interested in understanding macroeconomic trends, performing time series analysis, or building predictive models. With the rate of change included, users can quickly assess the growth or contraction in these indicators month-over-month. This dataset can be used for:

• Exploratory Data Analysis (EDA): Understanding historical economic trends. -Time Series Forecasting: Building models to predict future economic conditions. -Macroeconomic Analysis: Analyzing the relationship between various economic indicators. -Machine Learning Projects: Using the data as features to predict financial or economic outcomes. -By utilizing this dataset, users can perform in-depth analysis on the impact of macroeconomic changes, compare the historical performance of various indicators, and experiment with different time series forecasting techniques.

****Column Descriptions****

Year: The year of the observation.

Month: The month of the observation (1-12).

Industrial Production: Monthly data on the total output of US factories, mines, and utilities.

Manufacturers' New Orders: Durable Goods: Measures the value of new orders placed with manufacturers for durable goods, indicating future production activity.

Consumer Price Index (CPIAUCSL): A measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services.

Unemployment Rate: The percentage of the total labor force that is unemployed but actively seeking employment.

Retail Sales: The total receipts of retail stores, indicating consumer spending and economic activity.

Producer Price Index: Measures the average change over time in the selling prices received by domestic producers for their output.

Personal Consumption Expenditures (PCE): A measure of the prices paid by consumers for goods and services, used in calculating inflation.

National Home Price Index: A measure of changes in residential real estate prices across the country.

All Employees, Total Nonfarm: The number of nonfarm payroll employees, an important indicator of the labor market.

Labor Force Participation Rate: The percentage of the working-age population that is either employed or actively looking for work.

Federal Funds Effective Rate: The interest rate at which depository institutions lend reserve balances to other depository institutions overnight.

Building Permits: The number of building permits issued for residential and non-residential buildings, a leading indicator of construction activity.

Money Supply (M2): The total money supply, including cash, checking deposits, and easily convertible near money.

Personal Income: The total income received by individuals from all sources, including wages, investments, and government transfers.

Trade Balance: The difference between a country's imports and exports, indicating the net trade flow.

Consumer Sentiment: The index reflecting consumer sentiment and expectations for the future economic outlook.

Consumer Confidence: A measure of how optimistic or pessimistic consumers are regarding their expected financial situation and the economy.

Notes on Interest Rates Please note that for the Federal Funds Effective Rate (FEDFUNDS), the dataset includes the absolute change in basis points (bps), not the rate of change. This means that the dataset reflects the direct change in the interest rate rather than the percentage change month-over-month. The change is represented in basis points, where 1 basis point equals 0.01%.

The Three-View Cloud Particle Imager (3V-CPI) is a combination of three imaging instruments. Two of them comprise a 2D-S instrument, in which two 2D probes image particles as they pass through beams that are oriented orthogonally to each other and the airflow. If particles also lie in the intersection of the sensitive areas of the two beams, they are seen by both 2D probes. In that case, the CPI is triggered to take a high-resolution picture, via a briefly illuminated high-resolution imaging array, to provide a third image at high resolution. The probe is particularly suited to imaging ice crystals, but also provide good detection of other hydrometeors including large cloud droplets, drizzle and small rain drops, and precipitation particles. The 3V-CPI measures the size, shape and concentration of water drops and ice particles in clouds in the size range of 15-250 micrometers. This dataset contains 2D-S imagery collected by the 3V-CPI aboard the NSF/NCAR C-130 during the ARISTO2016 project. The 2DS puts all flight data into 3 files, and the size of these files depends on the amount of time in clouds.

Inflation Rate in Brazil increased to 5.53 percent in April from 5.48 percent in March of 2025. This dataset provides - Brazil Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Inflation Rate in Argentina decreased to 47.30 percent in April from 55.90 percent in March of 2025. This dataset provides the latest reported value for - Argentina Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Core consumer prices in the United States increased 2.80 percent in April of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The WC food CPI decreased to 9,5% in July, 0,6 percentage points lower than South Africa’s 10,1%. Load shedding and the weakening exchange rate remains key drivers to upward pressure. The continuous hikes in the repo rate have assisted in the headline CPI decreasing to below 6%, falling within the target range.

Inflation Rate in Indonesia decreased to 1.60 percent in May from 1.95 percent in April of 2025. This dataset provides - Indonesia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Consumer Price Index CPI in Mexico increased to 139.62 points in April from 139.16 points in March of 2025. This dataset provides - Mexico Consumer Price Index (CPI) - actual values, historical data, forecast, chart, statistics, economic calendar and news.

BackgroundThe identification of compound-protein interactions (CPIs) is crucial for drug discovery and understanding mechanisms of action. Accurate CPI prediction can elucidate drug-target-disease interactions, aiding in the discovery of candidate compounds and effective synergistic drugs, particularly from traditional Chinese medicine (TCM). Existing in silico methods face challenges in prediction accuracy and generalization due to compound and target diversity and the lack of largescale interaction datasets and negative datasets for model learning.MethodsTo address these issues, we developed a computational model for CPI prediction by integrating the constructed large-scale bioactivity benchmark dataset with a deep learning (DL) algorithm. To verify the accuracy of our CPI model, we applied it to predict the targets of compounds in TCM. An herb pair of Astragalus membranaceus and Hedyotis diffusaas was used as a model, and the active compounds in this herb pair were collected from various public databases and the literature. The complete targets of these active compounds were predicted by the CPI model, resulting in an expanded target dataset. This dataset was next used for the prediction of synergistic antitumor compound combinations. The predicted multi-compound combinations were subsequently examined through in vitro cellular experiments.ResultsOur CPI model demonstrated superior performance over other machine learning models, achieving an area under the Receiver Operating Characteristic curve (AUROC) of 0.98, an area under the precision-recall curve (AUPR) of 0.98, and an accuracy (ACC) of 93.31% on the test set. The model’s generalization capability and applicability were further confirmed using external databases. Utilizing this model, we predicted the targets of compounds in the herb pair of Astragalus membranaceus and Hedyotis diffusaas, yielding an expanded target dataset. Then, we integrated this expanded target dataset to predict effective drug combinations using our drug synergy prediction model DeepMDS. Experimental assay on breast cancer cell line MDA-MB-231 proved the efficacy of the best predicted multi-compound combinations: Combination I (Epicatechin, Ursolic acid, Quercetin, Aesculetin and Astragaloside IV) exhibited a half-maximal inhibitory concentration (IC50) value of 19.41 μM, and a combination index (CI) value of 0.682; and Combination II (Epicatechin, Ursolic acid, Quercetin, Vanillic acid and Astragaloside IV) displayed a IC50 value of 23.83 μM and a CI value of 0.805. These results validated the ability of our model to make accurate predictions for novel CPI data outside the training dataset and evaluated the reliability of the predictions, showing good applicability potential in drug discovery and in the elucidation of the bioactive compounds in TCM.ConclusionOur CPI prediction model can serve as a useful tool for accurately identifying potential CPI for a wide range of proteins, and is expected to facilitate drug research, repurposing and support the understanding of TCM.

Consumer Price Index CPI in Italy remained unchanged at 122.60 points in May. This dataset provides the latest reported value for - Italy Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Consumer Price Index CPI in Ireland increased to 102.60 points in April from 102.20 points in March of 2025. This dataset provides the latest reported value for - Ireland Consumer Price Index (cpi) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.