Producer Prices in India increased to 154.80 points in February from 154.70 points in January of 2025. This dataset provides the latest reported value for - India Producer Prices - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

United States Producer Price Index data was reported at 259.726 1982=100 in Feb 2025. This records an increase from the previous number of 257.202 1982=100 for Jan 2025. United States Producer Price Index data is updated monthly, averaging 34.900 1982=100 from Jan 1913 (Median) to Feb 2025, with 1346 observations. The data reached an all-time high of 280.251 1982=100 in Jun 2022 and a record low of 10.300 1982=100 in Feb 1933. United States Producer Price Index data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.I060: Producer Price Index: by Commodities. [COVID-19-IMPACT]

Producer Price Indices (PPIs) are a series of economic indicators that measure the price movement of goods bought and sold by UK manufacturers.

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

A comprehensive selection of data on input and output indices. Contains producer price indices of materials and fuels purchased and output of manufacturing industry by broad sector.

This table contains figures on the average price development of the selling prices, the import prices and the domestic consumption of industrial products with a base year of 2021=100. This data is available for both domestic and foreign sales. The products are classified based on the goods classification PRODCOM (PRODuction COMmunautaire).

Data available from: January 2018

Status of the figures: The figures in this table are provisional during five months.

Changes as of February 28th 2025 Figures of January 2025 have been added.

When will new figures be published? New figures will be published not later than 30 days after the period under review.

Producer Prices in Ghana increased 27.60 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Ghana Producer Prices Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This table contains figures on the average price development of the selling prices, the import prices and the domestic consumption of industrial products with a base year of 2015=100. This data is available for both domestic and foreign sales. The products are classified based on the goods classification PRODCOM (PRODuction COMmunautaire).

Data available from January 2012 up to and including December 2023.

Status of the figures: The data for August 2023 up to and including December 2023 and the 2023 annual rate are provisional. Since this table has been stopped, the data is no longer made definitive.

Changes as of March 6th 2024 None, this table is stopped.

When will new figures be published? The results in this series are based on 2015=100. Due to the base shift this table is stopped. Figures based on 2021=100 are published in table Producer Price Index (PPI), output and importprices by product, 2021=100. Further information, see Base Year Revision Industrial Producer Price Index, 2021=100 in paragraph 3.

Producer Prices in China decreased 2.20 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - China Producer Prices Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Producer Prices In the Euro Area increased 1.80 percent in January of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Euro Area Producer Prices Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Please refer to the original data article for further data description: Jan Luxemburk et al. CESNET-QUIC22: A large one-month QUIC network traffic dataset from backbone lines, Data in Brief, 2023, 108888, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2023.108888. We recommend using the CESNET DataZoo python library, which facilitates the work with large network traffic datasets. More information about the DataZoo project can be found in the GitHub repository https://github.com/CESNET/cesnet-datazoo. The QUIC (Quick UDP Internet Connection) protocol has the potential to replace TLS over TCP, which is the standard choice for reliable and secure Internet communication. Due to its design that makes the inspection of QUIC handshakes challenging and its usage in HTTP/3, there is an increasing demand for research in QUIC traffic analysis. This dataset contains one month of QUIC traffic collected in an ISP backbone network, which connects 500 large institutions and serves around half a million people. The data are delivered as enriched flows that can be useful for various network monitoring tasks. The provided server names and packet-level information allow research in the encrypted traffic classification area. Moreover, included QUIC versions and user agents (smartphone, web browser, and operating system identifiers) provide information for large-scale QUIC deployment studies. Data capture The data was captured in the flow monitoring infrastructure of the CESNET2 network. The capturing was done for four weeks between 31.10.2022 and 27.11.2022. The following list provides per-week flow count, capture period, and uncompressed size:

W-2022-44

Uncompressed Size: 19 GB Capture Period: 31.10.2022 - 6.11.2022 Number of flows: 32.6M W-2022-45

Uncompressed Size: 25 GB Capture Period: 7.11.2022 - 13.11.2022 Number of flows: 42.6M W-2022-46

Uncompressed Size: 20 GB Capture Period: 14.11.2022 - 20.11.2022 Number of flows: 33.7M W-2022-47

Uncompressed Size: 25 GB Capture Period: 21.11.2022 - 27.11.2022 Number of flows: 44.1M CESNET-QUIC22

Uncompressed Size: 89 GB Capture Period: 31.10.2022 - 27.11.2022 Number of flows: 153M

Data description The dataset consists of network flows describing encrypted QUIC communications. Flows were created using ipfixprobe flow exporter and are extended with packet metadata sequences, packet histograms, and with fields extracted from the QUIC Initial Packet, which is the first packet of the QUIC connection handshake. The extracted handshake fields are the Server Name Indication (SNI) domain, the used version of the QUIC protocol, and the user agent string that is available in a subset of QUIC communications. Packet Sequences Flows in the dataset are extended with sequences of packet sizes, directions, and inter-packet times. For the packet sizes, we consider payload size after transport headers (UDP headers for the QUIC case). Packet directions are encoded as ±1, +1 meaning a packet sent from client to server, and -1 a packet from server to client. Inter-packet times depend on the location of communicating hosts, their distance, and on the network conditions on the path. However, it is still possible to extract relevant information that correlates with user interactions and, for example, with the time required for an API/server/database to process the received data and generate the response to be sent in the next packet. Packet metadata sequences have a length of 30, which is the default setting of the used flow exporter. We also derive three fields from each packet sequence: its length, time duration, and the number of roundtrips. The roundtrips are counted as the number of changes in the communication direction (from packet directions data); in other words, each client request and server response pair counts as one roundtrip. Flow statistics Flows also include standard flow statistics, which represent aggregated information about the entire bidirectional flow. The fields are: the number of transmitted bytes and packets in both directions, the duration of flow, and packet histograms. Packet histograms include binned counts of packet sizes and inter-packet times of the entire flow in both directions (more information in the PHISTS plugin documentation There are eight bins with a logarithmic scale; the intervals are 0-15, 16-31, 32-63, 64-127, 128-255, 256-511, 512-1024, >1024 [ms or B]. The units are milliseconds for inter-packet times and bytes for packet sizes. Moreover, each flow has its end reason - either it was idle, reached the active timeout, or ended due to other reasons. This corresponds with the official IANA IPFIX-specified values. The FLOW_ENDREASON_OTHER field represents the forced end and lack of resources reasons. The end of flow detected reason is not considered because it is not relevant for UDP connections. Dataset structure The dataset flows are delivered in compressed CSV files. CSV files contain one flow per row; data columns are summarized in the provided list below. For each flow data file, there is a JSON file with the number of saved and seen (before sampling) flows per service and total counts of all received (observed on the CESNET2 network), service (belonging to one of the dataset's services), and saved (provided in the dataset) flows. There is also the stats-week.json file aggregating flow counts of a whole week and the stats-dataset.json file aggregating flow counts for the entire dataset. Flow counts before sampling can be used to compute sampling ratios of individual services and to resample the dataset back to the original service distribution. Moreover, various dataset statistics, such as feature distributions and value counts of QUIC versions and user agents, are provided in the dataset-statistics folder. The mapping between services and service providers is provided in the servicemap.csv file, which also includes SNI domains used for ground truth labeling. The following list describes flow data fields in CSV files:

ID: Unique identifier SRC_IP: Source IP address DST_IP: Destination IP address DST_ASN: Destination Autonomous System number SRC_PORT: Source port DST_PORT: Destination port PROTOCOL: Transport protocol QUIC_VERSION QUIC: protocol version QUIC_SNI: Server Name Indication domain QUIC_USER_AGENT: User agent string, if available in the QUIC Initial Packet TIME_FIRST: Timestamp of the first packet in format YYYY-MM-DDTHH-MM-SS.ffffff TIME_LAST: Timestamp of the last packet in format YYYY-MM-DDTHH-MM-SS.ffffff DURATION: Duration of the flow in seconds BYTES: Number of transmitted bytes from client to server BYTES_REV: Number of transmitted bytes from server to client PACKETS: Number of packets transmitted from client to server PACKETS_REV: Number of packets transmitted from server to client PPI: Packet metadata sequence in the format: [[inter-packet times], [packet directions], [packet sizes]] PPI_LEN: Number of packets in the PPI sequence PPI_DURATION: Duration of the PPI sequence in seconds PPI_ROUNDTRIPS: Number of roundtrips in the PPI sequence PHIST_SRC_SIZES: Histogram of packet sizes from client to server PHIST_DST_SIZES: Histogram of packet sizes from server to client PHIST_SRC_IPT: Histogram of inter-packet times from client to server PHIST_DST_IPT: Histogram of inter-packet times from server to client APP: Web service label CATEGORY: Service category FLOW_ENDREASON_IDLE: Flow was terminated because it was idle FLOW_ENDREASON_ACTIVE: Flow was terminated because it reached the active timeout FLOW_ENDREASON_OTHER: Flow was terminated for other reasons

Link to other CESNET datasets

https://www.liberouter.org/technology-v2/tools-services-datasets/datasets/ https://github.com/CESNET/cesnet-datazoo Please cite the original data article:

@article{CESNETQUIC22, author = {Jan Luxemburk and Karel Hynek and Tomáš Čejka and Andrej Lukačovič and Pavel Šiška}, title = {CESNET-QUIC22: a large one-month QUIC network traffic dataset from backbone lines}, journal = {Data in Brief}, pages = {108888}, year = {2023}, issn = {2352-3409}, doi = {https://doi.org/10.1016/j.dib.2023.108888}, url = {https://www.sciencedirect.com/science/article/pii/S2352340923000069} }

Producer Prices in Slovenia increased 0.50 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Slovenia Producer Prices Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The production price index (PPI) for construction materials and components in the United States decreased slightly in 2024. Up until 2020, construction prices had been rising fairly steadily. However, in the years after that construction producer prices have been very unstable. Production price index A PPI of 342 in 2022, indicates that the real-world price has risen by 242 percent in comparison to the base year - 1982 in this case. Similarly, under the same baseline, the PPI for construction machinery and equipment has also risen steadily until 2018. Like all prices, there are regional differences within the United States. The PPI acts as a measurement for the average changes in prices that domestic producers receive for their output. In the United States, the PPI is one of the oldest continuous statistical datasets published by the government. Common construction materials Some building materials are essential to construction work, and the decision on which to use is important for the life and the endurance of the building. Materials such as cement, steel, and sand are essential to many construction projects. The production of cement is tightly linked to the demand that comes from the construction industry. The durability and potency of steel gives it an advantage over wood and concrete, providing buildings with a higher resistance but a cheaper price tag. Sand is commonly used in buildings, but it is especially common in roads that require stones of various grades and granulation.

About this Dataset

The Consumer Price Index (CPI) for food is a component of the all-items CPI. The CPI measures the average change over time in the prices paid by urban consumers for a representative market basket of consumer goods and services. While the all-items CPI measures the price changes for all consumer goods and services, including food, the CPI for food measures the changes in the retail prices of food items only. ERS's monthly update is usually released on the 25th of the month; however, if the 25th falls on a weekend or a holiday, the monthly update will be published on either the 23rd or 24th. This report provides a detailed outline of ERS's forecasting methodology, along with measures to test the precision of the estimates (May 2015). At ERS, work on the CPI for food consists of several activities. ERS reports the current index level for food, examines changes in the CPI for food, and constructs forecasts of the CPI for food for the next 12-18 months. Forecasting the CPI for food has become increasingly important due to the changing structure of food and agricultural economies and the important signals the forecasts provide to farmers, processors, wholesalers, consumers, and policymakers. As a natural extension of ERS's work with the CPI for food, ERS also analyzes and models forecasts for the Producer Price Index (PPI). The PPI is similar to the CPI in that it measures price changes over time; however, instead of measuring changes in retail prices, the PPI measures the average change in prices paid to domestic producers for their output. The PPI collects data for nearly every industry in the goods-producing sector of the economy. Changes in farm-level and wholesale-level PPIs are of particular interest in forecasting food CPIs. cpi

Category

Economic

Keywords

cpi,restaurant,wholesale-food-prices

Row Count

68

Price

Free

UK price index data at manufacturing, aggregated industry and product group levels. Data supplied from individual manufacturers, importers and exporters. Monthly and annual data.

Producer Prices in Germany increased 0.70 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Germany Producer Prices Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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

"The data set records the statistical data of producer price index by use in Qinghai Province, and the data are divided by year. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains four data tables, which are: Producer Price Indices by Use 1989-2016 XLS, producer Price Indices by Use 1990-2017 XLS, 1989-2016 Producer Price Index by Use (1990-2018). XLS, Producer Price Index of Qinghai Province by Use (1990-2020). XLS. The data table structure is the same. For example, the data table from 1989 to 2016 has 11 fields: Field 1: Total index Field 2: Light industry Field 3: Heavy industry Field 4: Production data Field 5: Extractive industries Field 6: Raw material industry Field 7: Processing industry Field 8: Food category Field 9: Clothing category Field 10: General commodities Field 11: Consumer durables"

Producer Prices in Indonesia increased to 104.34 points in February from 104.20 points in January of 2025. This dataset provides - Indonesia Producer Prices - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Producer Prices in Austria decreased 0.40 percent in January of 2025 over the same month in the previous year. This dataset provides - Austria Producer Prices Change - actual values, historical data, forecast, chart, statistics, economic calendar and news.