Site: Add new sample datasets (#46)

_posts/2023-06-07-oaxaca.md → _posts/2023-06-07-Oaxaca-Development.md

@@ -4,7 +4,7 @@ title: 'Oaxaca Development'
 date: 2023-06-07 11:32:16
 image: /assets/img/
 description:
-main-class: 'development'
+main-class: 'textbook'
 color:
 tags:
   - development

_posts/2023-10-11-Ceara-Zika.md

@@ -0,0 +1,73 @@
+---
+layout: post
+title: 'Ceará Zika, municipalities in the State of Ceará, Brazil'
+date: 2023-10-11 11:46:00
+image: /assets/img/
+description:
+main-class: 'textbook'
+color:
+tags:
+  - polygons
+  - <500
+  - textbook
+  - ESDA
+  - open data
+categories:
+twitter_text:
+introduction: 'Zika and Microcephaly infections and socio-economic profiles for 2013-2016'
+---
+<div id="root" data-geojson="../data/ceara.geojson"></div>
+
+<br>
+
+[DOWNLOAD DATA](../data/ceara.zip)
+
+Zika and Microcephaly infections and socio-economic profiles for 2013-2016 in Ceará Zika, municipalities in the State of Ceará, Brazil.
+
+Source: Amaral et al (2019). Geospatial modeling of microcephaly and zika virus spread patterns in Brazil, PLoS ONE 14(9), doi 10.1371/journal.pone.0222668
+
+- Observations = 184
+- Variables = 35
+- Years = 2013-2016
+
+**Overview of data**
+
+|**Variable**|**Description**|
+|---|---|
+|code7|municipality's code with 7 digits|
+|mun_name|municipality's name|
+|state_init|state's initials|
+|area_km2|municipality's area in km2|
+|state_code|state's code|
+|micro_code|Microregion's code (microregion = group of municipalities defined by IBGE. No administrative use at all, just for statistics)|
+|micro_name|Microregion's name (microregion = group of municipalities defined by IBGE. No administrative use at all, just for statistics)|
+|inc_mic_4q|microcephaly incidence in the 4th quarter|
+|inc_zik_3q|zika incidence in the 3rd quarter|
+|inc_zik_2q|zika incidence in the 2nd quarter|
+|inc_zik_1q|zika incidence in the 1st quarter|
+|prim_care|population with primary care coverage|
+|ln_gdp|Log of GDP|
+|ln_pop|Log of population|
+|mobility|Mobility index|
+|environ|Environment index|
+|housing|Housing index|
+|sanitation|Sanitation index|
+|infra|Infrastructure index|
+|acu_zik_1q|Cumulative case count Zika up to 1st quarter|
+|acu_zik_2q|Cumulative case count Zika up to 2nd quarter|
+|acu_zik_3q|Cumulative case count Zika up to 3rd quarter|
+|pop_zikav|Population Zika relevant|
+|acu_mic_4q|Case count microcephaly 4th quarter (missing values)|
+|pop_micro|Microregion population (microregion = group of municipalities defined by IBGE. No administrative use at all, just for statistics)|
+|lngdpcap|Log of GDP per capita|
+|gdp|GDP|
+|pop|Population total|
+|gdpcap|GCP per capita|
+|popdens|Population density|
+|zik_1q|Zika case count quarter 1 only|
+|zik_2q|Zika case count quarter 2 only|
+|zik_3q|Zika case count quarter 3 only|
+|zika_d|Zika cases indicator (1=cases, 0=no cases)|
+|mic_d|Microcephaly cases indicator (1=cases, 0=no cases)|
+
+Prepared by ([Center for Spatial Data Science](https://spatial.uchicago.edu/)). Last updated Oct 11, 2023. Data provided "as is," no warranties.

_posts/2023-10-11-Chi-CCA.md

@@ -0,0 +1,38 @@
+---
+layout: post
+title: 'Chicago Community Areas'
+date: 2023-10-11 12:46:00
+image: /assets/img/
+description:
+main-class: 'textbook'
+color:
+tags:
+  - polygons
+  - <500
+  - textbook
+  - ESDA
+  - open data
+categories:
+twitter_text:
+introduction: 'Socio-economic snapshot for Chicago Community Areas in 2020'
+---
+<div id="root" data-geojson="../data/Chicago_2020.geojson"></div>
+
+<br>
+
+[DOWNLOAD DATA](../data/Chi-CCA.zip)
+
+Socio-economic snapshot for Chicago Community Areas in 2020 in Chicago, IL.
+
+Source: American Community Survey from the Chicago Metropolitan Agency for Planning - CMAP - data portal
+
+- Observations = 77
+- Variables = 291
+- Years = 2020
+
+**Overview of data**
+
+Embed the pdf here
+<embed src="../data/CDSFieldDescriptions202106.pdf" width="100%" height="500px" type="application/pdf">
+
+Prepared by ([Center for Spatial Data Science](https://spatial.uchicago.edu/)). Last updated Oct 11, 2023. Data provided "as is," no warranties.

_posts/2023-10-11-Chi-Carjackings.md

@@ -0,0 +1,53 @@
+---
+layout: post
+title: 'Chicago Carjackings'
+date: 2023-10-11 12:29:00
+image: /assets/img/
+description:
+main-class: 'textbook'
+color:
+tags:
+  - points
+  - <500
+  - textbook
+  - ESDA
+  - open data
+categories:
+twitter_text:
+introduction: 'Point locations of carjackings in 2020 Chicago'
+---
+<div id="root" data-geojson="../data/Chi_Carjackings.geojson"></div>
+
+<br>
+
+[DOWNLOAD DATA](../data/Chi_Carjackings.zip)
+
+Point locations of carjackings in 2020 in Chicago, IL.
+
+Source: Chicago Open Data Portal 
+
+- Observations = 1412
+- Variables = 15
+- Years = 2020
+
+**Overview of data**
+
+|**Variable**|**Description**|
+|---|---|
+|ID|unique identifier|
+|Case_mber|case number|
+|Date|date of incident|
+|IUCR|Illinois Uniform Crime Reporting code|
+|Descr_tion|incident description|
+|Locat_tionion|type of location (e.g., street, gas station)|
+|Beat|Police beat code|
+|District|Police district code|
+|Ward|Ward code|
+|Commu_Area|Community area code|
+|FBI Code|FBI uniform crime reporting code|
+|X Coo_nate|X coordinates (projected UTM Zone 16N, ESPG=32616)|
+|Y Coo_nate|Y coordinates (projected UTM Zone 16N, ESPG=32616)|
+|Latitude|Latitude in decimal degrees|
+|Longitude|Longitude in decimal degrees|
+
+Prepared by ([Center for Spatial Data Science](https://spatial.uchicago.edu/)). Last updated Oct 11, 2023. Data provided "as is," no warranties.

_posts/2023-10-11-Chi-SDOH.md

@@ -0,0 +1,89 @@
+---
+layout: post
+title: 'Chicago SDOH, census Tracts'
+date: 2023-10-11 12:19:00
+image: /assets/img/
+description:
+main-class: 'textbook'
+color:
+tags:
+  - polygons
+  - <500
+  - textbook
+  - ESDA
+  - open data
+categories:
+twitter_text:
+introduction: 'Socio-economic determinants of health in 2014 Chicago'
+---
+<div id="root" data-geojson="../data/Chi-SDOH.geojson"></div>
+
+<br>
+
+[DOWNLOAD DATA](../data/Chi-SDOH.zip)
+
+Socio-economic determinants of health in 2014 (a subset of the data used in Kolak et al. 2020) for census tracts in Chicago, IL.
+
+Source: Kolak, Marynia, Jay Bhatt, Yoon Hong Park, Norma A. Padrón, and Ayrin Molefe. 2020. “Quantification of Neighborhood-Level Social Determinants of Health in the Continental United States.” JAMA Network Open 3 (1): e1919928–28. https://doi.org/10.1001/jamanetworkopen.2019.19928.
+
+- Observations = 791
+- Variables = 51
+- Years = 2014
+
+**Overview of data**
+
+|**Variable**|**Description**|
+|---|---|
+|OBJECTID|unique census tract identifier|
+|Shape_Leng|perimeter|
+|Shape_Area|area|
+|TRACTCE10|tract FIPS code|
+|geoid10|complete GEO ID code|
+|commarea|community area code|
+|ChildPvt14|percent children in poverty (2014)|
+|EP_CROWD|percent crowded housing (2014)|
+|EP_UNINSUR|percent uninsured (2014)|
+|EP_MINRTY|percent minority (2014)|
+|Ovr6514P|percent population over 65 (2014)|
+|EP_AGE17|percent children and youth < 18 (2014)|
+|EP_DISABL|percent with disability (2014)|
+|EP_NOHSDP|percent without high school (2014)|
+|EP_LIMENG|percent with limited English proficiency (2014)|
+|EP_SNGPNT|percent single parent households (2014)|
+|Pov14|percent living in poverty (2014)|
+|EP_PCI|per capita income (2014)|
+|Unemp14|unemployment rate (2014)|
+|EP_NOVEH|percent households without a vehicle (2014)|
+|FORCLRISK|foreclosure risk (2011)|
+|HealthLit|health literacy index (2014)|
+|CarC14P|percent commuting by car (2014)|
+|CAR|indicator variable more than 50 percent car commute|
+|NOCAR|indicator variable less than 50 percent car commute|
+|CTA14P|percent public transit commuter (2014)|
+|CTA|indicator variable more than 50 percent public transit commute|
+|CmTm14|average commute time (in minutes, 2014)|
+|Undr514P|percent young children (under 5, 2014)|
+|Wht14P|percent white (2014)|
+|WHT50PCT|original white indicator variable|
+|Wht|new white indicator variable (>= 50 percent)|
+|Blk14P|percent black (2014)|
+|BLCK50PCT|original black indicator variable|
+|Blk|new black indicator variable (>=50 percent)|
+|Hisp14P|percent hispanic (2014)|
+|HISP50PCT|original hispanic indicator variable|
+|Hisp|new hispanic indicator variable (>= 50 percent)|
+|Pop2014|population count (2014)|
+|PDENS14|population density (2014)|
+|MEANMI_07|supermarket cost distance in miles (2007)|
+|MEANMI_11|supermarket cost distance in miles (2011)|
+|MEANMI_14|supermarket cost distance in miles (2014)|
+|FACHANGE|change in distance 2014-07 (positive is closer)|
+|PCCRIMERT15|property crime rate (2015)|
+|VCRIMERT15|violent crime rate (2015)|
+|ForclRt|foreclosure rate (2014)|
+|EP_MUNIT|percent multi-unit housing (2014)|
+|EP_GROUPQ|institutionalized population (2014)|
+|SchHP_MI|distance to high performance school (2012)|
+|BrownF_MI|distance to nearest brownfield I(2012)|
+
+Prepared by ([Center for Spatial Data Science](https://spatial.uchicago.edu/)). Last updated Oct 11, 2023. Data provided "as is," no warranties.

_posts/2023-10-11-Italy-Community-Banks.md

@@ -0,0 +1,69 @@
+---
+layout: post
+title: 'Italy Community Banks'
+date: 2023-10-11 11:46:00
+image: /assets/img/
+description:
+main-class: 'textbook'
+color:
+tags:
+  - development
+  - polygons
+  - <500
+  - textbook
+  - ESDA
+  - open data
+categories:
+twitter_text:
+introduction: 'Italy community bank performance indicators for 2011-17'
+---
+<div id="root" data-geojson="../data/italy_banks.geojson"></div>
+
+<br>
+
+[DOWNLOAD DATA](../data/italy_banks.zip)
+
+Italy Banks Data Dictionary
+
+Source: Algeri et al (2022). Spatial dependence in the technical efficiency of local banks. Papers in Regional Science 101, 385-416.
+
+Italy_banks.shp – 261 points in UTM zone 32, no Sardinia or Elba
+
+- Observations = 261
+- Variables = 96
+- Years = 2011-2017
+
+**Overview of data**
+|**Variable**|**Description**|
+|---|---|
+|Idd|bank ID|
+|BankName|name of the bank|
+|City|city name|
+|latitud|latitude|
+|longitud|longitude|
+|COORD_X|coordinates from UTM|
+|XKM|coordinates in km (COORD_X/1000)|
+|COORD_Y|coordinates from UTM|
+|YKM|coordinates in km (COORD_Y/1000)|
+|ID|same ID for work purposes|
+|IDN|ID of nearest neighbor|
+|distnn|distance to nearest neighbor|
+|REGCODE|region code|
+|REGNAME|region name|
+|PROVCODE|province code|
+|PROVNAME|province name|
+|COMCODE|commune code|
+|TE_IN_11|score_input_vrs_2011 to 2017: Farrel input-based technical efficiency using VRS|
+|TE_OUT_11|score_output_vrs_2011 to 2017: Farrell output-based technical efficiency using VRS|
+|CAPRAT11|totalcapitalratio2011: (Tier 1 Capital + Tier 2 Capital) / Risk weighted assets|
+|Z_11/17|zscore12011: (ROA + Leverage)/ σ (ROA)|
+|LIQASS_11/17|liq_ta_w2011: Liquid asset/ Total asset|
+|NPLl_11/17|assetquality_w2011: Non- performing loans/ Total gross loans|
+|LLP_11/17|allow_w2011: Loan loss provisions / Customer loans|
+|INTR_11/17|inexptofunds_w2011: Interest expense/ Total funds|
+|DEPO_11/17|deposit_ta_w2011: Total deposits/ Total asset|
+|EQLN_11/17|equity_loan_w2011: Total equity/ Customer loan|
+|SERV_11/17|service_w2011: Net interest income /Total operating revenues|
+|EXPE_11/17|operexp_ta_w2011: Operating expenses / Total assets|
+
+Prepared by ([Center for Spatial Data Science](https://spatial.uchicago.edu/)). Last updated Oct 11, 2023. Data provided "as is," no warranties.