Comprehensive dataset of 36 Data entry services in Spain as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 1 Data entry services in Sverdlovsk Oblast, Russia as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

description: The dataset is known as Border Crossing/Entry Data. The Bureau of Transportation Statistics (BTS) Border Crossing/Entry Data provides summary statistics to the public for incoming crossings at the U.S.-Canadian and the U.S.-Mexican border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians. Data fields are numeric counts and textual sequences. These data are collected by U.S. Customs and Border Protection (CBP) at individual ports of entry, then compiled and tabulated by staff of CBP's Office of Field Operations. CBP uses a mixture of manual and automated procedures to collect the data. The data reflect the number of vehicles, containers, passengers or pedestrians entering the United States. U.S. Customs and Border Protection does not collect comparable data on outbound crossings.; abstract: The dataset is known as Border Crossing/Entry Data. The Bureau of Transportation Statistics (BTS) Border Crossing/Entry Data provides summary statistics to the public for incoming crossings at the U.S.-Canadian and the U.S.-Mexican border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians. Data fields are numeric counts and textual sequences. These data are collected by U.S. Customs and Border Protection (CBP) at individual ports of entry, then compiled and tabulated by staff of CBP's Office of Field Operations. CBP uses a mixture of manual and automated procedures to collect the data. The data reflect the number of vehicles, containers, passengers or pedestrians entering the United States. U.S. Customs and Border Protection does not collect comparable data on outbound crossings.

Python Code Instruction

Training Data with Instruction, Input, Output, and Prompt Columns

By Tarun Bisht (From Huggingface) [source]

About this dataset

The python_code_instructions_18k_alpaca dataset is a comprehensive training dataset specifically curated for researchers and developers involved in the analysis and comprehension of Python code instructions. It contains a vast collection of Python code snippets along with their corresponding instruction, input, output, and prompt information. By utilizing this dataset, users can gain valuable insights into various Python programming concepts and techniques.

The dataset is organized into columns to facilitate easy access to the required information. The instruction column holds the specific task or instruction that the Python code snippet is designed to perform. This allows users to understand the purpose or requirement of each code snippet at a glance.

The input column contains all necessary input data or parameters that are required for executing the Python code snippet accurately. These inputs provide context and enable users to comprehend how different variables or values impact the overall functioning of each code snippet.

Likewise, the output column presents expected results or outcomes that should be produced when executing each Python code snippet with its specified input values. This allows for validation and verification purposes, ensuring that each code snippet performs as intended.

In addition to instruction, input, and output details, this dataset also includes prompts. The prompt column provides additional context or information intended to assist users in better understanding the purpose or requirements of each particular Python code snippet.

By leveraging this comprehensive python_code_instructions_18k_alpaca training dataset, researchers and developers can delve into numerous real-world examples of Python programming challenges - helping them enhance their coding skills while gaining invaluable knowledge about effective implementation techniques across various domains

Research Ideas

• Code Instruction Analysis: This dataset can be used to analyze different types of Python code instructions and identify patterns or common practices. Researchers or developers can use this dataset to gain insights into effective ways of writing code instructions.
• Code Output Prediction: With the given input and instruction, this dataset can be used to train models for predicting the expected output of a Python code snippet. This can be useful in automating the testing process or verifying the correctness of the code.
• Prompt Generation: Developers often struggle with providing clear and concise prompts for their code snippets. This dataset can serve as a resource for generating prompts by analyzing existing examples and extracting key information or requirements from them

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: train.csv | Column name | Description | |:----------------|:------------------------------------------------------------------------------------------------------------------| | instruction | Specific tasks or instructions assigned to each Python code snippet. (Text) | | input | The input data or parameters required for executing the code instruction. (Text) | | output | The expected result or output that should be produced when executing the code instruction. (Text) | | prompt | Additional information or context to help understand the purpose or requirements of each code instruction. (Text) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Tarun Bisht (From Huggingface).

decadals are a group of experiments of the CMIP5 - Coupled Model Intercomparison Project Phase 5 ( https://pcmdi.llnl.gov/mips/cmip5 ). CMIP5 is meant to provide a framework for coordinated climate change experiments for the next five years and thus includes simulations for assessment in the AR5 as well as others that extend beyond the AR5.

1.5 decadal (1.5 decadal hindcast/forecast utilizing alternative initializations.) - Version 1: Decadal hindcast/prediction. Comparison of initialization strategies - for example, a repeat of experiment 1.1 using an alternate initialization strategy or alternate initial data. Individual decadal experiments are named decadalXXXX with starting year XXXX.

Experiment design: https://pcmdi.llnl.gov/mips/cmip5/experiment_design.html
List of output variables: https://pcmdi.llnl.gov/mips/cmip5/datadescription.html
Output: time series per variable in model grid spatial resolution in netCDF format Earth System model and the simulation information: CIM repository

Entry name/title of data are specified according to the Data Reference Syntax ( https://pcmdi.llnl.gov/mips/cmip5/docs/cmip5_data_reference_syntax.pdf ) as activity/product/institute/model/experiment/frequency/modeling realm/MIP table/ensemble member/version number/variable name/CMOR filename.nc .

This record is an overview entry for biological data collected on Soela cruise SO 6/85. This cruise took place in the Coral Sea off northeastern Queensland during 14 November - 28 November 1985, …Show full descriptionThis record is an overview entry for biological data collected on Soela cruise SO 6/85. This cruise took place in the Coral Sea off northeastern Queensland during 14 November - 28 November 1985, under the leadership of Trevor Ward. Biological data collected on this cruise include samples of crustaceans and fish from more than 80 trawls. 20 new species of crustaceans and about 40 new species of fish were obtained. Sediment samples, photography of bottom types and photography of the common species of crustaceans were also obtained.(derived from the cruise report) - Biological Field Data Sheets recorded during this voyage have been scanned to PDF, and are available (to CSIRO Staff) on-line. See the details link under "Stored Media List" (below).

Comprehensive dataset of 1 Data entry services in State of Pernambuco, Brazil as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

[ Derived from parent entry - See data hierarchy tab ]

historicalExt is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 ( https://pcmdi.llnl.gov/mips/cmip5 ). CMIP5 is meant to provide a framework for coordinated climate change experiments for the next five years and thus includes simulations for assessment in the AR5 as well as others that extend beyond the AR5.

7.4 historicalExt (7.4 Historical Extension) - Version 1: Extend the CMIP5 historical runs to the near-present (as we have for AMIP), rather than ending them in 2005. Simulations extended to at least the end of 2012 using some estimate of recent and future forcing. Groups are free to use whatever concentrations, solar forcing, SO2 emissions etc. they want to use in extending these runs. It is recommended that if an ensemble of "all-forcings" historical simulations have been run, then each member of the ensemble should be carried to the end of 2012. If some other forcing is used or if the run is an RCP run that is truncated after a few years, then the run should be considered a "historical extension" experiment with its output placed in a directory named historicalExt. For these historicalExt experiments, the ensemble member (designated by the "rip" value appearing in the filename and recorded as netCDF global attributes) will be identical to the historical run it extends.

List of output variables: https://pcmdi.llnl.gov/mips/cmip5/datadescription.html Output: time series per variable in model grid spatial resolution in netCDF format Earth System model and the simulation information: CIM repository

Entry name/title of data are specified according to the Data Reference Syntax ( https://pcmdi.llnl.gov/mips/cmip5/docs/cmip5_data_reference_syntax.pdf ) as activity/product/institute/model/experiment/frequency/modeling realm/MIP table/ensemble member/version number/variable name/CMOR filename.nc .

CN: Input-Output: Intermediate Use: Intermediate Input: Information Transmission, Software and Information Technology Service: Wholesale, Retail, Transport, Storage & Post data was reported at 296.532 RMB bn in 2020. This records an increase from the previous number of 166.685 RMB bn for 2017. CN: Input-Output: Intermediate Use: Intermediate Input: Information Transmission, Software and Information Technology Service: Wholesale, Retail, Transport, Storage & Post data is updated yearly, averaging 231.609 RMB bn from Dec 2017 (Median) to 2020, with 2 observations. The data reached an all-time high of 296.532 RMB bn in 2020 and a record low of 166.685 RMB bn in 2017. CN: Input-Output: Intermediate Use: Intermediate Input: Information Transmission, Software and Information Technology Service: Wholesale, Retail, Transport, Storage & Post data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AG: Input-Output Table: Intermediate Use: Input/Output: Information Transmission, Software and Information Technology Service.

This dataset represents CLIGEN input parameters for locations in 68 countries. CLIGEN is a point-scale stochastic weather generator that produces long-term weather simulations with daily output. The input parameters are essentially monthly climate statistics that also serve as climate benchmarks. Three unique input parameter sets are differentiated by having been produced from 30-year, 20-year and 10-year minimum record lengths that correspond to 7673, 2336, and 2694 stations, respectively. The primary source of data is the NOAA GHCN-Daily dataset, and due to data gaps, records longer than the three minimum record lengths were often queried to produce the needed number of complete monthly records. The vast majority of stations used at least some data from the 2000's, and temporal coverages are shown in the Excel table for each station. CLIGEN has various applications including being used to force soil erosion models. This dataset may reduce the effort needed in preparing climate inputs for such applications. Revised input files added on 11/16/20. These files were revised from the original dataset. Fixed metadata issues with the headings of each file. Fixed inconsistencies with MX.5P and transition probability values for extremely dry climates and/or months. Second revision input files added on 2/12/20. A formatting error was fixed that affected transition probabilities for 238 stations with zero recorded precipitation for one or more months. The affected stations were predominantly in Australia and Mexico. Resources in this dataset:Resource Title: 30-year input files. File Name: 30-year.zipResource Description: CLIGEN .par input files based on 30-year minimum record lengths. May be viewed with text editor.Resource Software Recommended: CLIGEN v5.3,url: https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/ Resource Title: 20-year input files. File Name: 20-year.zipResource Description: CLIGEN .par input files based on 20-year minimum record lengths. May be viewed with text editor.Resource Software Recommended: CLIGEN v5.3,url: https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/ Resource Title: 10-year input files. File Name: 10-year.zipResource Description: CLIGEN .par input files based on 10-year minimum record lengths. May be viewed with text editor.Resource Software Recommended: CLIGEN v5.3,url: https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/ Resource Title: Map Layer. File Name: MapLayer.kmzResource Description: Map Layer showing locations of the new CLIGEN stations. This layer may be imported into Google Earth and used to find the station closest to an area of interest.Resource Software Recommended: Google Earth,url: https://www.google.com/earth/ Resource Title: Temporal Ranges of Years Queried. File Name: GHCN-Daily Year Ranges.xlsxResource Description: Excel tables of the first and last years queried from GHCN-Daily when searching for complete monthly records (with no gaps in data). Any ranges in excess of 30 years, 20 years and 10 years, for respective datasets, are due to data gaps.Resource Title: 30-year input files (revised). File Name: 30-year revised.zipResource Description: CLIGEN .par input files based on 30-year minimum record lengths. May be viewed with text editor. Revised from the original dataset. Fixed metadata issues with the headings of each file. Fixed inconsistencies with MX.5P and transition probability values for extremely dry climates and/or months.Resource Software Recommended: CLIGEN v5.3,url: https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/ Resource Title: 20-year input files (revised). File Name: 20-year revised.zipResource Description: CLIGEN .par input files based on 20-year minimum record lengths. May be viewed with text editor. Revised from the original dataset. Fixed metadata issues with the headings of each file. Fixed inconsistencies with MX.5P and transition probability values for extremely dry climates and/or months.Resource Software Recommended: Cligen v5.3,url: https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/ Resource Title: 10-year input files (revised). File Name: 10-year revised.zipResource Description: CLIGEN .par input files based on 10-year minimum record lengths. May be viewed with text editor. Revised from the original dataset. Fixed metadata issues with the headings of each file. Fixed inconsistencies with MX.5P and transition probability values for extremely dry climates and/or months.Resource Software Recommended: Cligen v5.3,url: https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/ Resource Title: 30-year input files (revised 2). File Name: 30-year revised 2.zipResource Description: CLIGEN .par input files based on 30-year minimum record lengths. May be viewed with text editor. Fixed formatting issue for 238 stations that affected transition probabilities.Resource Software Recommended: Cligen v5.3,url: https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/ Resource Title: 20-year input files (revised 2). File Name: 20-year revised 2.zipResource Description: CLIGEN .par input files based on 20-year minimum record lengths. May be viewed with text editor. Fixed formatting issue for 238 stations that affected transition probabilities.Resource Software Recommended: Cligen v5.3,url: https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/ Resource Title: 10-year input files (revised 2). File Name: 10-year revised 2.zipResource Description: CLIGEN *.par input files based on 10-year minimum record lengths. May be viewed with text editor. Fixed formatting issue for 238 stations that affected transition probabilities.Resource Software Recommended: Cligen v5.3,url: https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/

China Input-Output: Intermediate Use: Value Added: Transport, Storage, Post, Information Transmission, Computer Services & Software data was reported at 4,883.472 RMB bn in 2015. This records an increase from the previous number of 3,473.422 RMB bn for 2012. China Input-Output: Intermediate Use: Value Added: Transport, Storage, Post, Information Transmission, Computer Services & Software data is updated yearly, averaging 702.589 RMB bn from Dec 1990 (Median) to 2015, with 11 observations. The data reached an all-time high of 4,883.472 RMB bn in 2015 and a record low of 91.789 RMB bn in 1990. China Input-Output: Intermediate Use: Value Added: Transport, Storage, Post, Information Transmission, Computer Services & Software data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AG: Input-Output Table: Intermediate Use: Input/Output: Transport, Storage, Post, Information Transmission, Computer Services and Software.

China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Real Estate, Leasing and Commercial Service data was reported at 454.682 RMB bn in 2015. This records an increase from the previous number of 268.675 RMB bn for 2012. China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Real Estate, Leasing and Commercial Service data is updated yearly, averaging 134.620 RMB bn from Dec 2002 (Median) to 2015, with 6 observations. The data reached an all-time high of 454.682 RMB bn in 2015 and a record low of 30.462 RMB bn in 2002. China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Real Estate, Leasing and Commercial Service data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AG: Input-Output Table: Intermediate Use: Input/Output: Transport, Storage, Post, Information Transmission, Computer Services and Software.

China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Other Service data was reported at 267.319 RMB bn in 2015. This records an increase from the previous number of 201.895 RMB bn for 2012. China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Other Service data is updated yearly, averaging 32.743 RMB bn from Dec 1992 (Median) to 2015, with 10 observations. The data reached an all-time high of 267.319 RMB bn in 2015 and a record low of 3.327 RMB bn in 1995. China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Other Service data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AG: Input-Output Table: Intermediate Use: Input/Output: Transport, Storage, Post, Information Transmission, Computer Services and Software.

China Input-Output: Intermediate Use: Total Input: Transport, Storage, Post, Information Transmission, Computer Services & Software data was reported at 11,931.916 RMB bn in 2015. This records an increase from the previous number of 8,705.175 RMB bn for 2012. China Input-Output: Intermediate Use: Total Input: Transport, Storage, Post, Information Transmission, Computer Services & Software data is updated yearly, averaging 1,460.643 RMB bn from Dec 1990 (Median) to 2015, with 11 observations. The data reached an all-time high of 11,931.916 RMB bn in 2015 and a record low of 153.500 RMB bn in 1990. China Input-Output: Intermediate Use: Total Input: Transport, Storage, Post, Information Transmission, Computer Services & Software data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AG: Input-Output Table: Intermediate Use: Input/Output: Transport, Storage, Post, Information Transmission, Computer Services and Software.

This record is an overview entry for biological data collected on Diamantina cruise Dm 2/62. This cruise took place in the south-east Indian Ocean during 16 July to 25 August 1962, under the leadership of B. Hamon. Biological data collected on this cruise include primary production rates; pigment samples; and zooplankton biomass. Please note: This metadata record is a preliminary entry derived from information in the cruise report. Individual data types - which may span several cruises - will be indexed separately within this metadata system in due course.

This record is an overview entry for biological data collected on Southern Surveyor cruise SS 04/95. This cruise took place in the north-western Coral Sea during 9-26 May 1995, under the leadership of Roland Pitcher. Biological data collected on this cruise include phyllosoma and puerulus larvae samples, video photography of live captured larvae in ship-board aquaria and gut content samples for subsequent analysis. Please note: This metadata record is a preliminary entry derived from information in the cruise plan. The biological data collected on this cruise will be updated when cruise report is available. Individual data types - which may span several cruises - will be indexed separately within this metadata system in due course.

China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Metal Product Mfg data was reported at 37.238 RMB bn in 2015. This records a decrease from the previous number of 44.152 RMB bn for 2012. China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Metal Product Mfg data is updated yearly, averaging 24.394 RMB bn from Dec 1995 (Median) to 2015, with 9 observations. The data reached an all-time high of 54.954 RMB bn in 2010 and a record low of 4.278 RMB bn in 1997. China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Metal Product Mfg data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AG: Input-Output Table: Intermediate Use: Input/Output: Transport, Storage, Post, Information Transmission, Computer Services and Software.

China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Banking and Insurance data was reported at 853.553 RMB bn in 2015. This records an increase from the previous number of 614.925 RMB bn for 2012. China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Banking and Insurance data is updated yearly, averaging 100.185 RMB bn from Dec 1995 (Median) to 2015, with 9 observations. The data reached an all-time high of 853.553 RMB bn in 2015 and a record low of 4.918 RMB bn in 1995. China Input-Output: Intermediate Use: Intermediate Input: Transport, Storage, Post, Information Transmission, Computer Services & Software: Banking and Insurance data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AG: Input-Output Table: Intermediate Use: Input/Output: Transport, Storage, Post, Information Transmission, Computer Services and Software.

China Input-Output: Intermediate Use: Value Added: Transport, Storage, Post, Information Transmission, Computer Services & Software: Operating Surplus data was reported at 1,073.337 RMB bn in 2015. This records a decrease from the previous number of 1,078.336 RMB bn for 2012. China Input-Output: Intermediate Use: Value Added: Transport, Storage, Post, Information Transmission, Computer Services & Software: Operating Surplus data is updated yearly, averaging 401.658 RMB bn from Dec 1992 (Median) to 2015, with 10 observations. The data reached an all-time high of 1,078.336 RMB bn in 2012 and a record low of 40.799 RMB bn in 1995. China Input-Output: Intermediate Use: Value Added: Transport, Storage, Post, Information Transmission, Computer Services & Software: Operating Surplus data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AG: Input-Output Table: Intermediate Use: Input/Output: Transport, Storage, Post, Information Transmission, Computer Services and Software.