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Update population data to Mid 2024
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population/README.md

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</tr>
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<td>Dataset description</td>
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<td>Estimates of the usual resident population in Trafford during mid-2020</td>
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<td>Estimates of the usual resident population in Trafford during mid-2024</td>
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<td>Source</td>
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<td>Office for National Statistics</td>
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<td>Publisher</td>
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<td><a href="https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/bulletins/annualmidyearpopulationestimates/mid2020">Office for National Statistics</a></a></td>
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<td><a href="https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/censusoutputareapopulationestimatessupportinginformation">Office for National Statistics</a></a></td>
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<td>Geography</td>
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<td>Temporal coverage</td>
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<td>Mid-2020</td>
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<td>Mid-2024</td>
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<td>Update frequency</td>
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<td>Last updated</td>
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<td>2021-09-17</td>
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<td>2026-03-04</td>
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</tr>
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</table>

population/mid_year_2024/index.Rmd

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---
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pagetitle: "Mid-2024 population estimates"
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lang: "en-GB"
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output:
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html_document:
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css: ../../guidance/template/styles.css
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self_contained: TRUE
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---
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```{r setup, include=FALSE}
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knitr::opts_chunk$set(echo = FALSE, message = FALSE, warning = FALSE)
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library(tidyverse) ; library(htmltools) ; library(DT)
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df <- read_csv("mid-year_2024_population_estimates_ward.csv") %>%
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rename_all(. %>% str_to_title() %>% str_replace_all("_", " ")) %>%
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mutate(`Area name` = factor(`Area name`)) %>%
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rename_all(. %>% str_to_title())
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```
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<header>
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<span id="a11yNav"><a href="#downloads" class="themeBlockDark">Skip to downloads</a></span>
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<a href="https://www.trafforddatalab.io/data.html"><img src="https://www.trafforddatalab.io/assets/logo/trafforddatalab_logo.svg" alt="Trafford Data Lab" aria-label="Return to Trafford Data Lab data page" width="100" class="traffordDataLabLogo"/></a>
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<h1>Mid-2024 population estimates</h1>
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*Estimates of the usual resident population in Trafford during mid-2024.*
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</header>
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<main>
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<h2>Metadata</h2>
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<table id="metadata" class="table table-condensed">
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<thead>
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<tr class="header">
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<th>Source</th>
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<th>Publisher</th>
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<th>Time period</th>
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<th>Geography</th>
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<th>Licence</th>
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<th>Attribution</th>
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<th>Last updated</th>
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</tr>
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</thead>
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<tr>
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<td>Office for National Statistics</td>
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<td><a href="https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/estimatesofthepopulationforenglandandwales" target="_blank">Office for National Statistics</a></td>
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<td><time datetime="2024-06-30">2024-06-30</time></td>
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<td>Local authority, electoral wards, MSOAs, LSOAs and OAs</td>
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<td><a href="http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/" target="_blank">OGL v3.0</a></td>
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<td>Contains public sector information licensed under the Open Government Licence v3.0</td>
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<td><time datetime="2026-03-04">2026-03-04</time></td>
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</tr>
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</table>
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<h2>Preview</h2>
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Sort, filter and export a selection of the data using the table.
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<div id = "renderDT">
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```{r preview}
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datatable(df,
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class = 'cell-border stripe',
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rownames = FALSE,
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extensions = c('Scroller', 'Buttons', 'KeyTable'),
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options = list(
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keys = TRUE,
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search = list(regex = TRUE),
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searchHighlight = TRUE,
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dom = 'ftB',
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buttons = list(
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list(extend = "csv",
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text = "Download selection")),
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deferRender = TRUE,
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scrollX = TRUE,
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scrollY = 300,
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scroller = TRUE,
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columnDefs = list(
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list(className = 'dt-left', targets = "_all")
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)))
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```
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</div>
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<div id="tableFooterTitle">Mid-2024 population estimates for Trafford's wards</div>
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<h2>Data</h2>
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<span id ="downloads">Download the complete dataset using the following links:</span>
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|File name |Format |
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|---|---|
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|[mid-year_2024_population_estimates_all_geographies.csv](mid-year_2024_population_estimates_all_geographies.csv) |CSV |
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|[mid-year_2024_population_estimates_local_authority.csv](mid-year_2024_population_estimates_local_authority.csv) |CSV |
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|[mid-year_2024_population_estimates_ward.csv](mid-year_2024_population_estimates_ward.csv) |CSV |
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|[mid-year_2024_population_estimates_msoa.csv](mid-year_2024_population_estimates_msoa.csv) |CSV |
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|[mid-year_2024_population_estimates_lsoa.csv](mid-year_2024_population_estimates_lsoa.csv) |CSV |
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|[mid-year_2024_population_estimates_oa.csv](mid-year_2024_population_estimates_oa.csv) |CSV |
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<h2>Pre-processing</h2>
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[The R script used to process the data](pre-processing.R) can be adapted to other areas. For information about R visit the <a href="https://cran.r-project.org" target="_blank">CRAN website</a>.
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</main>
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<script>
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// Fixes to dynamic elements created by DataTables to improve accessibility
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var removeElFn = setInterval(removeElement, 1000);
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function removeElement() {
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try {
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var el = document.getElementsByClassName("dataTables_scrollBody")[0].childNodes[0];
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el.removeChild(el.childNodes[0]); // Remove unwanted hidden text element from table - causing accessibility alert as it has no label
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el.parentNode.setAttribute('tabindex', '0'); // add attribute allowing keyboard users to access scrollable area
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clearInterval(removeElFn); // cancel any further calls to this function as we have completed all actions
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}
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catch(e) {
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// form element 'el' doesn't exist yet so setInterval will call the function again until it does
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}
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}
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</script>

population/mid_year_2024/index.html

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