From b3bfca6cb679320493e39c9a5fe7c74343e59b44 Mon Sep 17 00:00:00 2001 From: SahitiSarva <55742994+SahitiSarva@users.noreply.github.com> Date: Tue, 20 Feb 2024 18:43:44 -0500 Subject: [PATCH] minor formatting edits (#21) --- .../relative-wealth-index.ipynb | 31 +++++++++++++++---- 1 file changed, 25 insertions(+), 6 deletions(-) diff --git a/notebooks/relative-wealth/relative-wealth-index.ipynb b/notebooks/relative-wealth/relative-wealth-index.ipynb index bcd34f2..7d91d2e 100644 --- a/notebooks/relative-wealth/relative-wealth-index.ipynb +++ b/notebooks/relative-wealth/relative-wealth-index.ipynb @@ -54,9 +54,7 @@ "metadata": {}, "source": [ " # Demographics of Myanmar\n", - "\n", - " ## Assignment\n", - "\n", + " \n", "To overcome gaps in official demographic statistics, the team has turned to private sector data sources. The Data Lab used algorithmically generated data such as that released by [Meta](https://dataforgood.facebook.com/dfg/docs/methodology-high-resolution-population-density-maps). \n", "\n", "Additionally, the team also extracted the [Relative Wealth Index](https://dataforgood.facebook.com/dfg/tools/relative-wealth-index) data from Meta which helps identify differences in standard of living in the population. \n", @@ -86,6 +84,13 @@ "The data extracted from Meta was then aggregated to different admin levels using the shapefiles available on [Myanmar information Management Unit](https://themimu.info/news/updated-shapefiles). These datasets are made available on [SharePoint](https://worldbankgroup.sharepoint.com.mcas.ms/teams/DevelopmentDataPartnershipCommunity-WBGroup/Shared%20Documents/Forms/AllItems.aspx?csf=1&web=1&e=Yvwh8r&cid=fccdf23e%2D94d5%2D48bf%2Db75d%2D0af291138bde&FolderCTID=0x012000CFAB9FF0F938A64EBB297E7E16BDFCFD&id=%2Fteams%2FDevelopmentDataPartnershipCommunity%2DWBGroup%2FShared%20Documents%2FProjects%2FData%20Lab%2FMyanmar%20Economic%20Monitor%2FData&viewid=80cdadb3%2D8bb3%2D47ae%2D8b18%2Dc1dd89c373c5). " ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Findings" + ] + }, { "cell_type": "code", "execution_count": 9, @@ -242,6 +247,13 @@ "hrsl_adm3.to_file('../../data/population/myanmar_adm3_hrsl.shp', format = 'ESRI Shapefile')" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Popultion Estimates" + ] + }, { "cell_type": "code", "execution_count": 88, @@ -306,7 +318,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Observations and Limitations\n", + "#### Observations and Limitations\n", "\n", "* The data is from 2019. Myanmar has seen a lot of conflict and political unrest, aside from a pandemic since then. The numbers shown here do not reflect any of the recent changes in population movement. \n", "* The regions close to the Bangladesh border (Cox's Bazar) and the regions close to the Chinese border are less populated compared to regions close to the Thailand border.\n", @@ -354,6 +366,13 @@ "lowest_rwi = myanmar_rwi_adm3.sort_values(by='rwi', ascending = True).iloc[0]" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Relative Wealth Distribution" + ] + }, { "cell_type": "code", "execution_count": 86, @@ -407,7 +426,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Observations and Limitations\n", + "#### Observations and Limitations\n", "\n", "* The algorithm Meta used uses input data collected before [2018](https://www.pnas.org/doi/10.1073/pnas.2113658119). This means that any recent changes in wealth are not reflected in the figures.\n", "* The most populous district (Bago) is not the richest one. The SEZ Yangon (West) is wealthier. " @@ -417,7 +436,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Comparing Relative Wealth in the Twonships in Bago District and Yangon (West)" + "### Comparing Relative Wealth in the Townships in Bago District and Yangon (West)" ] }, {