From 0f5c1e7d411c94ae6476c4921431b091f4a93ea0 Mon Sep 17 00:00:00 2001 From: diego Date: Wed, 3 Feb 2021 07:47:29 -0600 Subject: [PATCH] Update github readme [SKIP CI] --- .gitignore | 1 + README.Rmd | 22 +++---- README.md | 56 +++++++++--------- README_files/figure-gfm/unnamed-chunk-1-1.png | Bin 0 -> 57326 bytes README_files/figure-gfm/unnamed-chunk-3-1.png | Bin 0 -> 130250 bytes 5 files changed, 40 insertions(+), 39 deletions(-) create mode 100644 README_files/figure-gfm/unnamed-chunk-1-1.png create mode 100644 README_files/figure-gfm/unnamed-chunk-3-1.png diff --git a/.gitignore b/.gitignore index f15e9bb..89ace9f 100644 --- a/.gitignore +++ b/.gitignore @@ -6,5 +6,6 @@ R/saveshps.R docs/* /index.html /index.md +/index_files data-raw/simpl/ AGEEML_20211271312276.csv.xz diff --git a/README.Rmd b/README.Rmd index 8294ef1..8a6f1f1 100644 --- a/README.Rmd +++ b/README.Rmd @@ -44,9 +44,9 @@ devtools::install_github('diegovalle/mxmaps') ```{r} library(mxmaps) -data("df_mxstate") -df_mxstate$value <- df_mxstate$pop -mxstate_choropleth(df_mxstate, +data("df_mxstate_2020") +df_mxstate_2020$value <- df_mxstate_2020$pop +mxstate_choropleth(df_mxstate_2020, title = "Total population, by state") ``` @@ -55,10 +55,10 @@ mxstate_choropleth(df_mxstate, The data.frame that you provide to the plotting functions must have one column named "region" and one column named "value". The entries for "region" must match the INEGI codes for states ("01", "02", etc) and municipios ("01001", "01002", etc) either as a string with or without a leading "0" or as numerics. The functions `str_mxstate` and `str_mxmunicipio` are provided to easily format codes to the INEGI specification. Also, two example data.frames, `df_mxstate` and `df_mxmunicipio`, are provided with demographic variables from the Encuesta Intercensal 2015. ```{r} -data("df_mxstate") -knitr::kable(head(df_mxstate)) -data("df_mxmunicipio") -knitr::kable(head(df_mxmunicipio)) +data("df_mxstate_2020") +knitr::kable(head(df_mxstate_2020)) +data("df_mxmunicipio_2020") +knitr::kable(head(df_mxmunicipio_2020)) ``` ## Municipios @@ -66,9 +66,9 @@ knitr::kable(head(df_mxmunicipio)) Here's another example showing Mexican municipios (similar to counties): ```{r} -data("df_mxmunicipio") -df_mxmunicipio$value <- df_mxmunicipio$indigenous / df_mxmunicipio$pop -mxmunicipio_choropleth(df_mxmunicipio, num_colors = 1, - title = "Percentage of the population that self-identifies as indigenous") +data("df_mxmunicipio_2020") +df_mxmunicipio_2020$value <- df_mxmunicipio_2020$indigenous_language / df_mxmunicipio_2020$pop +mxmunicipio_choropleth(df_mxmunicipio_2020, num_colors = 1, + title = "Percentage of the population that identifies as indigenous") ``` diff --git a/README.md b/README.md index ad76772..0da4571 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ Mexico Choropleths ================ Diego Valle-Jones -November 05, 2020 +February 03, 2021 - [What does it do?](#what-does-it-do) - [Installation](#installation) @@ -48,9 +48,9 @@ devtools::install_github('diegovalle/mxmaps') ``` r library(mxmaps) -data("df_mxstate") -df_mxstate$value <- df_mxstate$pop -mxstate_choropleth(df_mxstate, +data("df_mxstate_2020") +df_mxstate_2020$value <- df_mxstate_2020$pop +mxstate_choropleth(df_mxstate_2020, title = "Total population, by state") ``` @@ -69,42 +69,42 @@ specification. Also, two example data.frames, `df_mxstate` and Encuesta Intercensal 2015. ``` r -data("df_mxstate") -knitr::kable(head(df_mxstate)) +data("df_mxstate_2020") +knitr::kable(head(df_mxstate_2020)) ``` -| region | state\_name | state\_name\_official | state\_abbr | state\_abbr\_official | pop | pop\_male | pop\_female | afromexican | part\_afromexican | indigenous | part\_indigenous | -| :----- | :------------------ | :-------------------- | :---------- | :-------------------- | ------: | --------: | ----------: | ----------: | ----------------: | ---------: | ---------------: | -| 01 | Aguascalientes | Aguascalientes | AGS | Ags. | 1312544 | 640091 | 672453 | 653 | 4559 | 153395 | 18716 | -| 02 | Baja California | Baja California | BC | BC | 3315766 | 1650341 | 1665425 | 7445 | 10432 | 283055 | 38391 | -| 03 | Baja California Sur | Baja California Sur | BCS | BCS | 712029 | 359137 | 352892 | 11032 | 5132 | 103034 | 11728 | -| 04 | Campeche | Campeche | CAMP | Camp. | 899931 | 441276 | 458655 | 3554 | 6833 | 400811 | 13140 | -| 05 | Coahuila | Coahuila de Zaragoza | COAH | Coah. | 2954915 | 1462612 | 1492303 | 2761 | 8137 | 204890 | 28588 | -| 06 | Colima | Colima | COL | Col. | 711235 | 350791 | 360444 | 762 | 3314 | 145297 | 12373 | +| region | state\_name | state\_name\_official | state\_abbr | state\_abbr\_official | year | pop | pop\_male | pop\_female | afromexican | indigenous\_language | +| :----- | :------------------ | :-------------------- | :---------- | :-------------------- | ---: | ------: | --------: | ----------: | ----------: | -------------------: | +| 01 | Aguascalientes | Aguascalientes | AGS | Ags. | 2020 | 1425607 | 696683 | 728924 | 22425 | 2539 | +| 02 | Baja California | Baja California | BC | BC | 2020 | 3769020 | 1900589 | 1868431 | 64362 | 49130 | +| 03 | Baja California Sur | Baja California Sur | BCS | BCS | 2020 | 798447 | 405879 | 392568 | 26330 | 13581 | +| 04 | Campeche | Campeche | CAMP | Camp. | 2020 | 928363 | 456939 | 471424 | 19319 | 91801 | +| 05 | Coahuila | Coahuila de Zaragoza | COAH | Coah. | 2020 | 3146771 | 1563669 | 1583102 | 45976 | 5527 | +| 06 | Colima | Colima | COL | Col. | 2020 | 731391 | 360622 | 370769 | 13574 | 5210 | ``` r -data("df_mxmunicipio") -knitr::kable(head(df_mxmunicipio)) +data("df_mxmunicipio_2020") +knitr::kable(head(df_mxmunicipio_2020)) ``` -| state\_code | municipio\_code | region | state\_name | state\_name\_official | state\_abbr | state\_abbr\_official | municipio\_name | pop | pop\_male | pop\_female | afromexican | part\_afromexican | indigenous | part\_indigenous | metro\_area | long | lat | -| :---------- | :-------------- | :----- | :------------- | :-------------------- | :---------- | :-------------------- | :------------------ | -----: | --------: | ----------: | ----------: | ----------------: | ---------: | ---------------: | :------------- | ---------: | -------: | -| 01 | 001 | 01001 | Aguascalientes | Aguascalientes | AGS | Ags. | Aguascalientes | 877190 | 425731 | 451459 | 532 | 2791 | 104125 | 14209 | Aguascalientes | \-102.2960 | 21.87982 | -| 01 | 002 | 01002 | Aguascalientes | Aguascalientes | AGS | Ags. | Asientos | 46464 | 22745 | 23719 | 3 | 130 | 1691 | 92 | NA | \-102.0893 | 22.23832 | -| 01 | 003 | 01003 | Aguascalientes | Aguascalientes | AGS | Ags. | Calvillo | 56048 | 27298 | 28750 | 10 | 167 | 7358 | 2223 | NA | \-102.7188 | 21.84691 | -| 01 | 004 | 01004 | Aguascalientes | Aguascalientes | AGS | Ags. | Cosío | 15577 | 7552 | 8025 | 0 | 67 | 2213 | 191 | NA | \-102.3000 | 22.36641 | -| 01 | 005 | 01005 | Aguascalientes | Aguascalientes | AGS | Ags. | Jesús María | 120405 | 60135 | 60270 | 32 | 219 | 8679 | 649 | Aguascalientes | \-102.3434 | 21.96127 | -| 01 | 006 | 01006 | Aguascalientes | Aguascalientes | AGS | Ags. | Pabellón de Arteaga | 46473 | 22490 | 23983 | 3 | 74 | 6232 | 251 | NA | \-102.2765 | 22.14920 | +| state\_code | municipio\_code | region | state\_name | state\_name\_official | state\_abbr | state\_abbr\_official | municipio\_name | year | pop | pop\_male | pop\_female | afromexican | indigenous\_language | metro\_area | long | lat | +| :---------- | :-------------- | :----- | :------------- | :-------------------- | :---------- | :-------------------- | :------------------ | ---: | -----: | --------: | ----------: | ----------: | -------------------: | :------------- | ---------: | -------: | +| 01 | 001 | 01001 | Aguascalientes | Aguascalientes | AGS | Ags. | Aguascalientes | 2020 | 948990 | 462073 | 486917 | 15170 | 1839 | Aguascalientes | \-102.2960 | 21.87982 | +| 01 | 002 | 01002 | Aguascalientes | Aguascalientes | AGS | Ags. | Asientos | 2020 | 51536 | 25261 | 26275 | 225 | 22 | NA | \-102.0893 | 22.23832 | +| 01 | 003 | 01003 | Aguascalientes | Aguascalientes | AGS | Ags. | Calvillo | 2020 | 58250 | 28563 | 29687 | 266 | 76 | NA | \-102.7188 | 21.84691 | +| 01 | 004 | 01004 | Aguascalientes | Aguascalientes | AGS | Ags. | Cosío | 2020 | 17000 | 8292 | 8708 | 2155 | 7 | NA | \-102.3000 | 22.36641 | +| 01 | 005 | 01005 | Aguascalientes | Aguascalientes | AGS | Ags. | Jesús María | 2020 | 129929 | 64219 | 65710 | 2543 | 158 | Aguascalientes | \-102.3434 | 21.96127 | +| 01 | 006 | 01006 | Aguascalientes | Aguascalientes | AGS | Ags. | Pabellón de Arteaga | 2020 | 47646 | 23377 | 24269 | 482 | 52 | NA | \-102.2765 | 22.14920 | ## Municipios Here’s another example showing Mexican municipios (similar to counties): ``` r -data("df_mxmunicipio") -df_mxmunicipio$value <- df_mxmunicipio$indigenous / df_mxmunicipio$pop -mxmunicipio_choropleth(df_mxmunicipio, num_colors = 1, - title = "Percentage of the population that self-identifies as indigenous") +data("df_mxmunicipio_2020") +df_mxmunicipio_2020$value <- df_mxmunicipio_2020$indigenous_language / df_mxmunicipio_2020$pop +mxmunicipio_choropleth(df_mxmunicipio_2020, num_colors = 1, + title = "Percentage of the population that identifies as indigenous") ``` ![](README_files/figure-gfm/unnamed-chunk-3-1.png) 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