SD for Data Analysis Secondary indices and auto indexing Version:īit64 (≥ 4.0.0), bit (≥ 4.0.4), curl, R.utils, xts, nanotime, zoo (≥ 1.8-1), yaml, knitr, rmarkdownįinance, HighPerformanceComputing, TimeSeries, WebTechnologiesīenchmarking data.table Frequently asked questions Importing data.table Introduction to data.table Keys and fast binary search based subset Reference semantics Efficient reshaping using data.tables Using. Offers a natural and flexible syntax, for faster development. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write.

The data used to create these tables are available as a comma separated value (csv) file also available on this page.Fast aggregation of large data (e.g. All relevant outputs can be found on the National Energy Efficiency Data-Framework ( NEED) report: summary of analysis 2018 page. There are also additional detailed tables including distributions of consumption and estimates at local authority level. More information on the development of the framework, headline results and data quality are available in the publication. Data for each year from 2005 to 2016 are available.įigures provided in the latest version of the tool (June 2018) are based on data used in the June 2018 National Energy Efficiency Data-Framework ( NEED) publication. There is also a choice of fuel (electricity or gas). 2 variables can be selected to be considered at once (such as property age and property type), with mean, median or number of observations shown in the table. This tool provides users with the ability to create bespoke cross tabs and charts on consumption by property attributes and characteristics, based on the data available from NEED.

Data table creator for website