Merging (in Table R) data published on https://www.data.gouv.fr/fr/datasets/ventes-de-pesticides-par-departement/, and joining two other sources of information associated with MAs: — uses: https://www.data.gouv.fr/fr/datasets/usages-des-produits-phytosanitaires/ — information on the “Biocontrol” status of the product, from document DGAL/SDQSPV/2020-784 published on 18/12/2020 at https://agriculture.gouv.fr/quest-ce-que-le-biocontrole

All the initial files (.csv transformed into.txt), the R code used to merge data and different output files are collected in a zip. enter image description here NB: 1) “YASCUB” for {year,AMM,Substance_active,Classification,Usage,Statut_“BioConttrol”}, substances not on the DGAL/SDQSPV list being coded NA. 2) The file of biocontrol products shall be cleaned from the duplicates generated by the marketing authorisations leading to several trade names.
3) The BNVD_BioC_DY3 table and the output file BNVD_BioC_DY3.txt contain the fields {Code_Region,Region,Dept,Code_Dept,Anne,Usage,Classification,Type_BioC,Quantite_substance)}

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

Abstract \r

\r The Galilee Basin Operators' Forum (GBOF) is a group of petroleum companies exploring the Galilee\r \r Basin for commercial quantities of hydrocarbons. Exploration activities include the search for\r \r conventional hydrocarbons, and increasingly non-conventional hydrocarbon sources such as coal\r \r seam gas (CSG). The CSG target is the Permian coal measures as shown in Figure 1.1.\r \r Understanding and protecting groundwater is a key issue and community concern. As part of the\r \r early exploration activities in the Galilee Basin, the GBOF companies have initiated this study to\r \r assist in developing a regional and consistent subsurface description, and to document the existing\r \r data for the groundwater systems in the Galilee Basin study area. RPS, as an independent company,\r \r was contracted to perform the study and prepare a report.\r \r This initial study should not be confused with a "baseline assessment" or "underground water impact\r \r report" which are specific requirements under the Water Act 2000, triggered once production testing is\r \r underway or production has commenced. This study gathers and assembles all the base historical\r \r data which may be used in further studies. For the Galilee Basin study area, this investigation is\r \r specifically designed to:\r \r  Review stratigraphy and identify possible aquifers beneath the GBOF member company\r \r tenures;\r \r  Delineate aquifers that warrant further monitoring; and\r \r  Obtain and tabulate current Department of Environment and Resource Management\r \r Groundwater Database (DERM GWDB)( now the Department of Environment and Heritage\r \r EHP)registered bore data including;\r \r » Water bore location and summary statistics;\r \r » Groundwater levels and artesian flow data; and\r \r » Groundwater quality.\r \r Data sources for this report include:\r \r  Groundwater data available in the DERM GWDB;\r \r  Petroleum exploration wells recorded in Queensland Petroleum Exploration Data (QPED);\r \r  DERM groundwater data logger/tipping bucket rain gauge program;\r \r  Springs of Queensland Dataset (version 4.0) held by DERM;\r \r  PressurePlot Version 2 developed by CSIRO and linked to a Pressure-Hydrodynamics\r \r database; and\r \r  Direct communication with GBOF members.\r \r Data was sourced in January 2011. Since then there has been considerable additional drilling by\r \r GBOF members, which is not incorporated in this report. All data has been used by RPS as provided\r \r without independent investigations to validate the data. It is recognised that historical data may be\r \r subject to inaccuracies, however, as work progresses in the region, an improvement in data integrity\r \r should be realised.\r \r

Dataset History \r

\r Tables as taken from Appendix B to F of the - Galilee Basin: Report on the Hydrogelogical Investigations, Prepared by RPS Australia PTY LTD for RLMS. PR102603-1: Rev 1 / December 2012.\r \r \r \r Spatial datasets created for each appendix table using supplied coordinate values (MGA Zone 54, MGA Zone 55, GDA94 Geographics) where available, or spatially referencing (spatial join) the NGIS QLD core - bores dataset, via the unique DERM Registered Bore Numbers attribute field.\r \r

Dataset Citation \r

\r Geoscience Australia (XXXX) RPS Galilee Basin: Report on the Hydrogeological Investigations - Appendix tables B to F (Spatial). Bioregional Assessment Derived Dataset. Viewed 16 November 2016, http://data.bioregionalassessments.gov.au/dataset/d3d92616-c0b8-4cfb-9eb5-4031915e5e41.\r \r

Dataset Ancestors \r

\r * Derived From National Groundwater Information System, Queensland Core dataset (superseded)\r \r * Derived From RPS Galilee Hydrogeological Investigations - Appendix tables B to F (original)\r \r

Table 2 | Extrapolated tree species hyperdominance results for African, Amazonian, Southeast Asian tropical forests at the regional scale Number of hyperdominantsTotal speciesHyperdominant percentageAfrica104 [101,107]4,638 [4,511,4,764]2.23Amazonia299 [295,304]13,826 [13,615,14,036]2.16Southeast Asia278 [268,289]11,963 [11,451,12,475]2.32Total a681 [664,700]30,427 [29,577,31,275]2.24 a Calculated as the sum of the number of hyperdominants and total species across the three major tropical forest regions with hyperdominance percentage derived therefrom.Prediction intervals (in brackets) combine uncertainty from the standard error of predicted means and the residual s.d. of the regression of the bias correction fit.