Here are some examples from Chapter 15. The examples are related to the General Social Survey from NORC at the Unversity of Chicago.
library(tidyverse)
library(forcats)
gss_cat
gss_cat %>%
count(race)
Factor variables are used to make bar charts. The geom_bar() counts the observations in each level of the factor.
ggplot(gss_cat, aes(race)) +
geom_bar()
![](data:image/png;base64,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)
Forcing NAs.
ggplot(gss_cat, aes(race)) +
geom_bar() +
scale_x_discrete(drop = FALSE)
![](data:image/png;base64,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)
Modifying the order of a factor.
Examine tv watch time by religion.
relig_summary <- gss_cat %>%
group_by(relig) %>%
summarise(
age = mean(age, na.rm = TRUE),
tvhours = mean(tvhours, na.rm = TRUE),
n = n()
)
relig_summary %>% ggplot(aes(tvhours, relig)) + geom_point()
![](data:image/png;base64,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)
relig_summary %>% ggplot(aes(tvhours, fct_reorder(relig, tvhours))) +
geom_point()
![](data:image/png;base64,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)
The fct_reorder() functon should be used in a mutate statement.
Same as the last code.
relig_summary %>%
mutate(relig = fct_reorder(relig, tvhours)) %>%
ggplot(aes(tvhours, relig)) +
geom_point()
![](data:image/png;base64,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)
Now tv watch time by average age.
rincome_summary <- gss_cat %>%
group_by(rincome) %>%
summarise(
age = mean(age, na.rm = TRUE),
tvhours = mean(tvhours, na.rm = TRUE),
n = n()
)
rincome_summary %>% ggplot(aes(age, fct_reorder(rincome, age))) +
geom_point()
![](data:image/png;base64,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)
Does this make sense? What is wrong with this plot?
rincome_summary %>%ggplot(aes(age, fct_relevel(rincome, "Not applicable"))) +
geom_point()
![](data:image/png;base64,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)
Using mutate()
gss_cat %>% ggplot(aes(marital)) +
geom_bar()
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAArwAAAGwCAMAAAB8TkaXAAACrFBMVEUAAAACAgIDAwMGBgYHBwcICAgJCQkKCgoLCwsMDAwODg4PDw8RERESEhITExMVFRUWFhYXFxcZGRkbGxseHh4gICAhISEjIyMkJCQlJSUnJycoKCgpKSktLS0vLy8xMTEyMjIzMzM1NTU2NjY3Nzc4ODg5OTk6Ojo7Ozs9PT0+Pj4/Pz9AQEBBQUFCQkJFRUVGRkZHR0dISEhJSUlLS0tNTU1OTk5PT09QUFBRUVFSUlJTU1NUVFRVVVVWVlZXV1dYWFhZWVlaWlpbW1tcXFxdXV1eXl5fX19gYGBhYWFiYmJjY2NkZGRlZWVmZmZnZ2doaGhpaWlqampra2ttbW1ubm5vb29wcHBxcXFycnJzc3N0dHR1dXV2dnZ3d3d4eHh5eXl6enp7e3t8fHx9fX1+fn5/f3+AgICBgYGCgoKDg4OEhISFhYWGhoaHh4eIiIiJiYmKioqLi4uMjIyNjY2Ojo6Pj4+QkJCRkZGSkpKTk5OUlJSVlZWWlpaXl5eYmJiZmZmampqbm5ucnJydnZ2enp6fn5+goKChoaGioqKjo6OkpKSmpqanp6eoqKipqamqqqqrq6usrKytra2urq6vr6+wsLCysrKzs7O0tLS1tbW2tra3t7e4uLi5ubm6urq7u7u8vLy9vb2+vr6/v7/AwMDBwcHCwsLDw8PExMTFxcXGxsbHx8fJycnKysrLy8vMzMzNzc3Ozs7Pz8/Q0NDR0dHS0tLT09PU1NTV1dXW1tbX19fY2NjZ2dna2trb29vc3Nzd3d3e3t7f39/g4ODh4eHi4uLj4+Pk5OTl5eXm5ubn5+fo6Ojp6enq6urr6+vs7Ozt7e3u7u7v7+/w8PDx8fHy8vLz8/P09PT19fX29vb39/f4+Pj5+fn6+vr7+/v8/Pz9/f3+/v7///8FUd+EAAAACXBIWXMAAA7DAAAOwwHHb6hkAAAXxElEQVR4nO3di59U5XnA8S21adPWaG9Jes+2SWua2iZpVlG8sRfiihI2IBLceAM32ESiaFXuElGJGBPjglZqSnF1kyhW1Bobi7iKuoobYe/D7uzMnucf6ZnzzuxlBjPPey7vnsHf7/OBwXXPeTjP+y0MpMnWCVGNVjfXPwGisIGXajbwUs0GXqrZwEs1G3ipZosF73D4xscjXKwtO+ZgSO5E8jNGc6PJD8nkRpIfcmIiytVx4v0gfOMTES7Wlh9zMERGkp8xIIPJDxmWY8kPyUxGuRq8MQdem8CrDbw2gVcbeG0Crwm8MQdem8CrDbw2gVcbeG0Crwm8MQdem8CrDbw2gVcbeG0Crwm8MQdem8CrDbw2gVcbeG0Crwm8MQdem8CrDbw2gVcbeG0Crwm8MQdem5LHm7ti1P/+hbaWzbkPeQHvVOBdmFxlkxR497Y3+HgzjYeyHXtO/gLe6cCbKrwvPzvfx9vdIXKw/eQvIvne3t6h/vBlcxEu1pYfdzBEMsnPGJLh5IeMykC4CxPEO3vQcc3bBjnfx9u5RaS39eQvIkfr6+s3/Np70EelBPHOHpQtvirwbvWdXnryF/8+Bw4ceHswfBO5CBdrm8w6GCInkp8xIqPJD8nIULgLE8Q7e9CAGm/3WpEXrz75S7EIb7B4z2sT73lNaryZpl5v3e6Tv4B3OvCmEK8cXLZkU+5DXsA7FXhThldZhE2B1ybwmsAbc+AFbxKB1ybwagOvTeA1gTfmwAveJAKvTeDVBl6bwGsCb8yBF7xJBF6bwKsNvDaB1wTemAMveJMIvDaBVxt4bQKvCbwxB17wJhF4bQKvNvDaBF4TeGMOvOBNIvDaBF5t4LUJvCbwxhx4wZtE4LUJvNrAaxN4TeCNOfCCN4nAaxN4tYHXJvCawBtz4AVvEoHXJvBqA69N4DWBN+bAC94kAq9N4NUGXpvAawJvzIEXvEkEXpvAqw28NoHXBN6YAy94kwi8NoFXG3htAq8pTrzHwpediHCxtvyYgyEymvyMARlKfsiIHA93YYJ4yybFiXc8fJOTES7W5uUdDJFc8jOyMpH8kAnJhrswQbyzB43GiTfC71G8bbCJtw0m8MYceMGbROC1CbzawGsTeE3gjTnwgjeJwGsTeLWB1ybwmsAbc+AFbxKB1ybwagOvTeA1gTfmwAveJAKvTeDVBl6bwGsCb8yBF7xJBF6bwKsNvDaB1wTemAMveJMIvDaBVxt4bQKvCbwxB17wJhF4bQKvNvDaBF4TeGMOvOBNIvDaBF5t4LUJvCbwxhx4wZtE4LUJvNrAaxN4TeCNOfCCN4nAaxN4tYHXJvCawBtz4AVvEoHXJvBqA69N4DWBN+bAC94kAq9N4NUGXpvAawJvzIE3hXgfbig0ICv977eJvNDWsjk39QLeqcCbQrz5bDZ74E6RhUPZbF4yjYeyHXtKL+CdDrwpxOs3tmZMRpqDH3Z3iBxsL72AdzrwphPvjmdEDjctv3jNUencItLbWnoROd7W1rZ7InyTXoSLtXmTDoZIPvkZOcklPyQvIS9MEO/sQRkLvO+t9ESO7Boe3dkunVt9tZeWXkQGrrnmmr0RvlYoX77VJr58a5DNl299cK//nb846V/gda8VefFqKb7wtmE63jYkiLdskh6v97UB//v9KwbHHuqQTFOvt2536QW804E3jXgPtQWEdzY3rev3/5i2bMmm3NQLeKcCbxrxVi/CpsBrE3hN4I058II3icBrE3i1gdcm8JrAG3PgBW8Sgdcm8GoDr03gNYE35sAL3iQCr03g1QZem8BrAm/MgRe8SQRem8CrDbw2gdcE3pgDL3iTCLw2gVcbeG0Crwm8MQde8CYReG0Crzbw2gReE3hjDrzgTSLw2gRebeC1Cbwm8MYceMGbROC1CbzawGsTeE3gjTnwgjeJwGsTeLWB1ybwmsAbc+AFbxKB1ybwagOvTeA1gTfmwAveJAKvTeDVBl6bwGsCb8yBF7xJBF6bwKsNvDaB1wTemANvbeKN8OUW+QqYNvEVMINsvgJm1Y6FLzsR4WJt+TEHQ2Q0+RkDMpT8kBE5Hu7CBPGWTYoTb4Tfo3jbYBNvG0zgjTnwgjeJwGsTeLWB1ybwmsAbc+AFbxKB1ybwagOvTeA1gTfmwAveJAKvTeDVBl6bwGsCb8yBF7xJBF6bwKsNvDaB1wTemAMveJMIvDaBVxt4bQKvCbwxB17wJhF4bQKvNvDaBF4TeGMOvOBNIvDaBF5t4LUJvKZKvF8Kvu8/H7yhAu/c4V2/vm59oaWngzdU4J07vGedVXdWoc/vAG+owDt3eEXq7dWCdzrwziVeOXG4UA94QwXeucT7w9PqCn2sJvC6W5Q28Lo7k0q8n1zz1sx/A167wOvuTCrx/knOni14pwKvuzOpxHvBG+A9yaK0gdfdmVTi/fkXNu3/qR94QwVed2dSiXdeMfCGCrzuzqQSb/gibAq8NoHXVIl3wDQM3lCB192ZVOKtM30WvKECr7szqcT7qt8L2//qFfCGCrzuzqQSr+mJs8EbKvC6O5MPw/uLj5d/ZGVDQ8M2kRfaWjbnyl/AOxV43Z1JJd5fFOr+lz8vx7twKJvNS6bxULZjT9kLeKcDr7szqcRr/rx2xhNldkeag5fuDpGD7WUvImP79u07PBy+XD7cdQkuKuSTyFjICy0alUzyQ8ZkJNyFzs5ksBLvSJBX/gvv4ablF685Kp1bRHpby15EjtbX128ov8RBCS5qDp7m1MjZmWSLrzPf8052bd24f7L8p3Rk1/Doznbp3OpzvbTsxb9maGhoPMLXCg375VsTXFTIJ+HLt7o7k0q8fZ/5jU9+al59Xxnecd95/wKve63Ii1fL7JdiEd5g8Z7XJt7zmirxXvK5IyJvfa6xDO/+FYNjD3VIpqnXW7e77AW804HX3ZlU4j3zqcL33X9Qhtfb2dy0rt//89myJZty5S/gnQq87s6kEu8ZBu+Z5W96qxdhU+C1CbymSryXfPYtkXf+LsSftiNsCrw2gddUibevft6nPj3vr8v/wAZeXeB1dyaVeGXyyc2b/qvir8rAqwu87s6kEu/4Dc0i/7ziBHhDBV53Z1KJd/kZW0V2/fEK8IYKvO7OpBLvmQ8Uvv/xH4I3VOB1dyaVeE//eeH7A78P3lCB192ZVOJd8OUBkeGGc8EbKvC6O5NKvEf/8nf+9u9/99NvgzdU4HV3JpV4Jf/oupsezp5MJ3irB153Z3ISvKGLsCnw2gReE3iVi9IGXndnAl7lorSB192ZgFe5KG3gdXcm4FUuSht43Z0JeJWL0gZed2cCXuWitIHX3ZmAV7kobeB1dybgVS5KG3jdnQl4lYvSBl53ZwJe5aK0gdfdmYBXuSht4HV3JuBVLkobeN2dCXiVi9IGXndnAl7lorSB192ZgFe5KG3gdXcm4FUuSht43Z0JeJWL0gZed2cCXuWitIHX3ZmAV7kobeB1dybgVS5KG3jdnQl4lYvSBl53ZwJe5aK0gdfdmYBXuSht4HV3JuBVLkobeN2dCXiVi9IGXndnEifewfBN5MJdl+CiQj6JnAh5oUUjMpr8kIwMhbvQ2ZkMxIl3NHy5fLjrElxUyCeRbMgLLTohY8kPGZdMuAudnclwnHgj/B7F2wabeNtgAq9yUdrA6+5MwKtclDbwujsT8CoXpQ287s4EvMpFaQOvuzMBr3JR2sDr7kzAq1yUNvC6OxPwKhelDbzuzgS8ykVpA6+7MwGvclHawOvuTMCrXJQ28Lo7E/AqF6UNvO7OBLzKRWkLizd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOcUnj3XdF441GRlQ0NDdtEXmhr2ZybegHvVOB19yRqvL0L3h3fcZ3IwqFsNi+ZxkPZjj2lF/BOB153T6LG+/xmkbdbZKQ5+KfuDpGD7aUX8E4HXndPosbrN3HrNjnctPziNUelc4v/a3Fr6UWk7+yzz77bC59IuOsSXFTYJwl5HU9i/STjerzez5bel5cju4ZHd7ZL51Zf7aWlF5HR+++///kIXyuUL9+auic5lb58q3fXtb3+y3hWpH+B171W5MWrpfjC24bpeNvg7knUeA+snMjn87J/xeDYQx2Saer11u0uvYB3OvC6exI13nsb/BrF29nctK7f/2PasiWbclMv4J0KvO6eRI1XUbhnDQJv6p4EvNrAm7onAa828KbuScCrDbypexLwagNv6p4EvNrAm7onAa828KbuScCrDbypexLwagNv6p4EvNrAm7onAa828KbuScCrDbypexLwagNv6p4EvNrAm7onAa828KbuScCrDbypexLwagNv6p4EvNrAm7onAa828KbuScCrDbxOnuTUGWJ2DV7dorSB18kQs2vw6halDbxOhphdg1e3KG3gdTLE7Bq8ukVpA6+TIWbX4NUtSht4nQwxuwavblHawOtkiNk1eHWL0gZeJ0PMrsGrW5Q28DoZYnYNXt2itIHXyRCza/DqFqUNvE6GmF2DV7cobeB1MsTsGry6RWkDr5MhZtfg1S1KG3idDDG7Bq9uUdrA62SI2TV4dYvSBl4nQ8yuwatblDbwOhlidg1e3aK0gdfJELNr8OoWpQ28ToaYXceIdyJ8k1646xJcVMgnkXyKn+TUGVIoEyfecL/kBPErr5MnOXWGmF2DV7cobeB1MsTsGry6RWkDr5MhZtfg1S1KG3idDDG7Bq9uUdrA62SI2TV4dYvSBl4nQ8yuwatblDbwOhlidg1e3aK0gdfJELNr8OoWpQ28ToaYXYNXtyht4HUyxOwavLpFaQOvkyFm1+DVLUobeJ0MMbsGr25R2sDrZIjZNXh1i9IGXidDzK7Bq1uUNvA6GWJ2DV7dorSB18kQs2vw6halDbxOhphdg7fqohiSviFB4K2+KIakb0gQeKsviiHpGxIE3uqLYkj6hgSBt/qiGJK+IUHgrb4ohqRvSBB4qy+KIekbEgTe6otiSPqGBIG3+qIYkr4hQeCtviiGpG9IEHirL4oh6RsSBN7qi2JI+oYEgbf6ohiSviFB4K2+KIakb0gQeKsviiHpGxIE3uqLYkj6hgSBt/qiGJK+IUHgrb4ohqRvSBB4qy+KIekbEgTe6otiSPqGBIG3+qIYkr4hQeCtviiGpG9IUES8L7S1bM6BlyE1iDfTeCjbsQe8DKlBvN0dIgfb/R8Mb9iw4ecnwpefDHddgotiSJqHFBqOhrdzi0hvq/+DX51zzjk78+HzvAgXaxMnQyaTnzHpZkjyM/JelCFjEfFu9fFeWvqncL/zB4V922BVfszBkLD/c082Dchg8kOG5VjyQzKTUa6Ohrd7rciLV4N3RuC1aS7xZpp6vXW7wTsj8No0l3jl4LIlm+byr8qsAq9Npz7eWUX4aYDXJvCawBtz4LUJvNrAaxN4tYHXJvCawBtz4LUJvNrAaxN4tYHXJvCawBtz4LUJvNrAaxN4tYHXJvCawBtz4LUJvNrAa9NHDG+EHu90MOSBp5KfMbnh5eSHHNvwbvJDDm0Yq/5JUXt2Rww3mWu87V9zMGTBLcnPmKx/OPkhr9UfTH7IE/WDyQ/Z8sUYbgLemAKvVeDVBl6bwKvt+AfVPydy7w84GNI7mvyMid5s8kMyvZPJDxl6L4abzDVeotCBl2o2J3g/aHjS/75zW5rvfGSl6rNWNy66vfqbkPz59rcu6/zzzr/ohrd0nxtqgPybv7XehudF9rRr7hNuSKG+huDvxa5t/PWfZj/ADd5zW0ZCEPP6I975w25Q+LjX/9ysZapWl2/99xPj277zYf96al4cePsk89jCoecqTvwkDxXO1X/6V+1d4Lu6dWdxSlJ4F1zhiQxeNONRQp/ArNzgbdy4NSC2/4pFd5wIPvRIyyXX9UvPjQ/e9PXXJH9nU/OjcuXLct9i8ZrfOrjssjtHpOdbN31Tf2dzzfVdItu/L7NucOT6Hdfc+MwtrXunhvofL3z7nwYpfqb38KIluzSre/+8nP9njY2l67o23dK+um/mfYs//NeGb9jeujwfr8/qB/5PsvhQZnfBkH1XNG33og6Qd88dl3X3LRdZ/Lw/pXQfM6bsLMIPKdTX8s3XRX7y3cYYTmBWjvAONb/mE3u7+Z3cLTsLH+m7sC/73YelZ/6r8vCt8tTVY2/NH/veQ3Ldhf1Hm/sveTO/8U7pOe+x6v9JT+nOxWseXS/e5W/MvsGRhne8q270Xrl8aqj/8eDbKil+5sHL+kZXaVbnXfbtlwv/hf/idV3zj8juNTPvW/yh/yuv7a3LC/Du+47/kzQPVdxdYcibrR/0L30u6gDxFr3iNQ8uHBg8J+NPKd6nOKbsLMIPKdTXsuf7ImufbozhBGblCK/8ZOVk57ZH/N/ee9oKH8n2y+jt90vPEpEX18qTS3v831cOdOQvu+2ZJ2994mb/iiXS0+rp71y8pq8xf+Rr3uwbHFkqcsdeGWmZGup/PPi2SoqfueXHIj9TrW5wx9ILbzlauq5rtf8k8ydm3Lf4Qx+v9a3LCvA+t8r/SZqHKu6uMGTXAyL/1xN1gMgtj/RcJTc/fWBFYRXF+xTHlJ1FhCFSwNvX5p1o7WuM4wRm5gqvt2pv57Yd/k9x6OLCR/K7rly56v7Cz15eWiu5HzZdvtcbbXz9W4/ft+WJB1uuvPLKVV7PNyzuXLxGlr/6owdk9g0Kb6Xu6JLRlqmh/seDb6tKn3lzt8hr2tUd3XjhUPG6rtv9f248PuO+xR/6eMPcembTv/KahyrurjDkrv8ofELUASKP39x5r+y96/vbC6so3qc4puwsIgyRAl656u3uTf5ZxXMCU7nCKz2N92575G6RN5YWPtK18rg8MoX32GD+pUsPy8ptP+i5dvl7j28RmTga/Dv1nYvX+L8orXpTZt9gGu+MocVvxc/c9ojIs5rVPe3/OuH/dvu/xeu6rhPJzM/PuG/xhz5e21uXF+C97cHCTYOHKu6u8M87f+Cf9C+jDvA3s6jjeXn3stXPFO5avE/piGafRYQhEuD90UO3HvTPKvoJzMoZXrl7gf+e92h+ffDXJp3rvF+tuLuE96HVE5mlL8m9FxzMNy323l/0bv6e2/V4C3cuXiOHF7d5MvsG03hnDC1+K37mS4s/GLtWs7pjjV3Zof3No8Xrus55efJ735l53+IP8+dO2t66PB/v2N6Fg4WbBg9V3F3hn1+9vH/0qqejDvD/r7DxghPiLZ4/WLhr8T6lI5p9FhGGSID3na+35vyzin4Cs3KHN9MS/G3D7ZnCRwbbW6/tWna48ASv7JXhNQtb7vXk+YYRueEO/83P0uabhizwFu5srhGvdZeU3aCEd8vMoaVv5jO9H311yROq//+HX157cePq10rXdX1rdfPqYzPvW/yhd2Ob9a3LOn/BhRddfyT4SZqHMrsLHuqxxS3bvagD/L5d+AvejW3BKkr3KR7R7LOIMiTAK1+/rXBWMZzAzPhP2CLUtWGufwYf7cAbIfDObeClmg28VLOBl2o28FLNBl6q2cCbrnJ1/z3XP4XaCbxz3Jt1W+Ws9VP/CF6LwDunjff0X/MseEMGXkedtvfLZ/7jO1f+2RkbRV794u99/B9eEpn36Ce+IvN+Wl9X96XSx8BrEXgdddo/DRz/i4/tmVw/b0Q+84V9+z//Nz7eP73nDR9v8Ctv8WPgtQi8jjrthyLf8MG+V3d48ruvizzwCR/vrf6/MHhLHwOvReB11GldIjd8RWSg7rBkn97w1TMKeH8iJbylj4HXIvA6agbe0c99atWeez4RuC3hLX0MvBaB11Ez8D7222Mi22fjLX0MvBaB11Ez8D5Vt+v17X/0my9N4f380v7Sx8BrEXgdNYX3t3q8G888fcHhc78yhfee088rfQy8FoGXajbwUs0GXqrZwEs1G3ipZgMv1WzgpZoNvFSzgZdqNvBSzQZeqtn+H0bll+CQXobCAAAAAElFTkSuQmCC)
gss_cat %>% mutate(marital = marital) %>%
ggplot(aes(marital)) +
geom_bar()
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAArwAAAGwCAMAAAB8TkaXAAACrFBMVEUAAAACAgIDAwMGBgYHBwcICAgJCQkKCgoLCwsMDAwODg4PDw8RERESEhITExMVFRUWFhYXFxcZGRkbGxseHh4gICAhISEjIyMkJCQlJSUnJycoKCgpKSktLS0vLy8xMTEyMjIzMzM1NTU2NjY3Nzc4ODg5OTk6Ojo7Ozs9PT0+Pj4/Pz9AQEBBQUFCQkJFRUVGRkZHR0dISEhJSUlLS0tNTU1OTk5PT09QUFBRUVFSUlJTU1NUVFRVVVVWVlZXV1dYWFhZWVlaWlpbW1tcXFxdXV1eXl5fX19gYGBhYWFiYmJjY2NkZGRlZWVmZmZnZ2doaGhpaWlqampra2ttbW1ubm5vb29wcHBxcXFycnJzc3N0dHR1dXV2dnZ3d3d4eHh5eXl6enp7e3t8fHx9fX1+fn5/f3+AgICBgYGCgoKDg4OEhISFhYWGhoaHh4eIiIiJiYmKioqLi4uMjIyNjY2Ojo6Pj4+QkJCRkZGSkpKTk5OUlJSVlZWWlpaXl5eYmJiZmZmampqbm5ucnJydnZ2enp6fn5+goKChoaGioqKjo6OkpKSmpqanp6eoqKipqamqqqqrq6usrKytra2urq6vr6+wsLCysrKzs7O0tLS1tbW2tra3t7e4uLi5ubm6urq7u7u8vLy9vb2+vr6/v7/AwMDBwcHCwsLDw8PExMTFxcXGxsbHx8fJycnKysrLy8vMzMzNzc3Ozs7Pz8/Q0NDR0dHS0tLT09PU1NTV1dXW1tbX19fY2NjZ2dna2trb29vc3Nzd3d3e3t7f39/g4ODh4eHi4uLj4+Pk5OTl5eXm5ubn5+fo6Ojp6enq6urr6+vs7Ozt7e3u7u7v7+/w8PDx8fHy8vLz8/P09PT19fX29vb39/f4+Pj5+fn6+vr7+/v8/Pz9/f3+/v7///8FUd+EAAAACXBIWXMAAA7DAAAOwwHHb6hkAAAXxElEQVR4nO3di59U5XnA8S21adPWaG9Jes+2SWua2iZpVlG8sRfiihI2IBLceAM32ESiaFXuElGJGBPjglZqSnF1kyhW1Bobi7iKuoobYe/D7uzMnucf6ZnzzuxlBjPPey7vnsHf7/OBwXXPeTjP+y0MpMnWCVGNVjfXPwGisIGXajbwUs0GXqrZwEs1G3ipZosF73D4xscjXKwtO+ZgSO5E8jNGc6PJD8nkRpIfcmIiytVx4v0gfOMTES7Wlh9zMERGkp8xIIPJDxmWY8kPyUxGuRq8MQdem8CrDbw2gVcbeG0Crwm8MQdem8CrDbw2gVcbeG0Crwm8MQdem8CrDbw2gVcbeG0Crwm8MQdem8CrDbw2gVcbeG0Crwm8MQdem8CrDbw2gVcbeG0Crwm8MQdem5LHm7ti1P/+hbaWzbkPeQHvVOBdmFxlkxR497Y3+HgzjYeyHXtO/gLe6cCbKrwvPzvfx9vdIXKw/eQvIvne3t6h/vBlcxEu1pYfdzBEMsnPGJLh5IeMykC4CxPEO3vQcc3bBjnfx9u5RaS39eQvIkfr6+s3/Np70EelBPHOHpQtvirwbvWdXnryF/8+Bw4ceHswfBO5CBdrm8w6GCInkp8xIqPJD8nIULgLE8Q7e9CAGm/3WpEXrz75S7EIb7B4z2sT73lNaryZpl5v3e6Tv4B3OvCmEK8cXLZkU+5DXsA7FXhThldZhE2B1ybwmsAbc+AFbxKB1ybwagOvTeA1gTfmwAveJAKvTeDVBl6bwGsCb8yBF7xJBF6bwKsNvDaB1wTemAMveJMIvDaBVxt4bQKvCbwxB17wJhF4bQKvNvDaBF4TeGMOvOBNIvDaBF5t4LUJvCbwxhx4wZtE4LUJvNrAaxN4TeCNOfCCN4nAaxN4tYHXJvCawBtz4AVvEoHXJvBqA69N4DWBN+bAC94kAq9N4NUGXpvAawJvzIEXvEkEXpvAqw28NoHXBN6YAy94kwi8NoFXG3htAq8pTrzHwpediHCxtvyYgyEymvyMARlKfsiIHA93YYJ4yybFiXc8fJOTES7W5uUdDJFc8jOyMpH8kAnJhrswQbyzB43GiTfC71G8bbCJtw0m8MYceMGbROC1CbzawGsTeE3gjTnwgjeJwGsTeLWB1ybwmsAbc+AFbxKB1ybwagOvTeA1gTfmwAveJAKvTeDVBl6bwGsCb8yBF7xJBF6bwKsNvDaB1wTemAMveJMIvDaBVxt4bQKvCbwxB17wJhF4bQKvNvDaBF4TeGMOvOBNIvDaBF5t4LUJvCbwxhx4wZtE4LUJvNrAaxN4TeCNOfCCN4nAaxN4tYHXJvCawBtz4AVvEoHXJvBqA69N4DWBN+bAC94kAq9N4NUGXpvAawJvzIE3hXgfbig0ICv977eJvNDWsjk39QLeqcCbQrz5bDZ74E6RhUPZbF4yjYeyHXtKL+CdDrwpxOs3tmZMRpqDH3Z3iBxsL72AdzrwphPvjmdEDjctv3jNUencItLbWnoROd7W1rZ7InyTXoSLtXmTDoZIPvkZOcklPyQvIS9MEO/sQRkLvO+t9ESO7Boe3dkunVt9tZeWXkQGrrnmmr0RvlYoX77VJr58a5DNl299cK//nb846V/gda8VefFqKb7wtmE63jYkiLdskh6v97UB//v9KwbHHuqQTFOvt2536QW804E3jXgPtQWEdzY3rev3/5i2bMmm3NQLeKcCbxrxVi/CpsBrE3hN4I058II3icBrE3i1gdcm8JrAG3PgBW8Sgdcm8GoDr03gNYE35sAL3iQCr03g1QZem8BrAm/MgRe8SQRem8CrDbw2gdcE3pgDL3iTCLw2gVcbeG0Crwm8MQde8CYReG0Crzbw2gReE3hjDrzgTSLw2gRebeC1Cbwm8MYceMGbROC1CbzawGsTeE3gjTnwgjeJwGsTeLWB1ybwmsAbc+AFbxKB1ybwagOvTeA1gTfmwAveJAKvTeDVBl6bwGsCb8yBF7xJBF6bwKsNvDaB1wTemANvbeKN8OUW+QqYNvEVMINsvgJm1Y6FLzsR4WJt+TEHQ2Q0+RkDMpT8kBE5Hu7CBPGWTYoTb4Tfo3jbYBNvG0zgjTnwgjeJwGsTeLWB1ybwmsAbc+AFbxKB1ybwagOvTeA1gTfmwAveJAKvTeDVBl6bwGsCb8yBF7xJBF6bwKsNvDaB1wTemAMveJMIvDaBVxt4bQKvCbwxB17wJhF4bQKvNvDaBF4TeGMOvOBNIvDaBF5t4LUJvKZKvF8Kvu8/H7yhAu/c4V2/vm59oaWngzdU4J07vGedVXdWoc/vAG+owDt3eEXq7dWCdzrwziVeOXG4UA94QwXeucT7w9PqCn2sJvC6W5Q28Lo7k0q8n1zz1sx/A167wOvuTCrx/knOni14pwKvuzOpxHvBG+A9yaK0gdfdmVTi/fkXNu3/qR94QwVed2dSiXdeMfCGCrzuzqQSb/gibAq8NoHXVIl3wDQM3lCB192ZVOKtM30WvKECr7szqcT7qt8L2//qFfCGCrzuzqQSr+mJs8EbKvC6O5MPw/uLj5d/ZGVDQ8M2kRfaWjbnyl/AOxV43Z1JJd5fFOr+lz8vx7twKJvNS6bxULZjT9kLeKcDr7szqcRr/rx2xhNldkeag5fuDpGD7WUvImP79u07PBy+XD7cdQkuKuSTyFjICy0alUzyQ8ZkJNyFzs5ksBLvSJBX/gvv4ablF685Kp1bRHpby15EjtbX128ov8RBCS5qDp7m1MjZmWSLrzPf8052bd24f7L8p3Rk1/Doznbp3OpzvbTsxb9maGhoPMLXCg375VsTXFTIJ+HLt7o7k0q8fZ/5jU9+al59Xxnecd95/wKve63Ii1fL7JdiEd5g8Z7XJt7zmirxXvK5IyJvfa6xDO/+FYNjD3VIpqnXW7e77AW804HX3ZlU4j3zqcL33X9Qhtfb2dy0rt//89myJZty5S/gnQq87s6kEu8ZBu+Z5W96qxdhU+C1CbymSryXfPYtkXf+LsSftiNsCrw2gddUibevft6nPj3vr8v/wAZeXeB1dyaVeGXyyc2b/qvir8rAqwu87s6kEu/4Dc0i/7ziBHhDBV53Z1KJd/kZW0V2/fEK8IYKvO7OpBLvmQ8Uvv/xH4I3VOB1dyaVeE//eeH7A78P3lCB192ZVOJd8OUBkeGGc8EbKvC6O5NKvEf/8nf+9u9/99NvgzdU4HV3JpV4Jf/oupsezp5MJ3irB153Z3ISvKGLsCnw2gReE3iVi9IGXndnAl7lorSB192ZgFe5KG3gdXcm4FUuSht43Z0JeJWL0gZed2cCXuWitIHX3ZmAV7kobeB1dybgVS5KG3jdnQl4lYvSBl53ZwJe5aK0gdfdmYBXuSht4HV3JuBVLkobeN2dCXiVi9IGXndnAl7lorSB192ZgFe5KG3gdXcm4FUuSht43Z0JeJWL0gZed2cCXuWitIHX3ZmAV7kobeB1dybgVS5KG3jdnQl4lYvSBl53ZwJe5aK0gdfdmYBXuSht4HV3JuBVLkobeN2dCXiVi9IGXndnEifewfBN5MJdl+CiQj6JnAh5oUUjMpr8kIwMhbvQ2ZkMxIl3NHy5fLjrElxUyCeRbMgLLTohY8kPGZdMuAudnclwnHgj/B7F2wabeNtgAq9yUdrA6+5MwKtclDbwujsT8CoXpQ287s4EvMpFaQOvuzMBr3JR2sDr7kzAq1yUNvC6OxPwKhelDbzuzgS8ykVpA6+7MwGvclHawOvuTMCrXJQ28Lo7E/AqF6UNvO7OBLzKRWkLizd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOAVxt4U/ck4NUG3tQ9CXi1gTd1TwJebeBN3ZOcUnj3XdF441GRlQ0NDdtEXmhr2ZybegHvVOB19yRqvL0L3h3fcZ3IwqFsNi+ZxkPZjj2lF/BOB153T6LG+/xmkbdbZKQ5+KfuDpGD7aUX8E4HXndPosbrN3HrNjnctPziNUelc4v/a3Fr6UWk7+yzz77bC59IuOsSXFTYJwl5HU9i/STjerzez5bel5cju4ZHd7ZL51Zf7aWlF5HR+++///kIXyuUL9+auic5lb58q3fXtb3+y3hWpH+B171W5MWrpfjC24bpeNvg7knUeA+snMjn87J/xeDYQx2Saer11u0uvYB3OvC6exI13nsb/BrF29nctK7f/2PasiWbclMv4J0KvO6eRI1XUbhnDQJv6p4EvNrAm7onAa828KbuScCrDbypexLwagNv6p4EvNrAm7onAa828KbuScCrDbypexLwagNv6p4EvNrAm7onAa828KbuScCrDbypexLwagNv6p4EvNrAm7onAa828KbuScCrDbypexLwagNv6p4EvNrAm7onAa828KbuScCrDbxOnuTUGWJ2DV7dorSB18kQs2vw6halDbxOhphdg1e3KG3gdTLE7Bq8ukVpA6+TIWbX4NUtSht4nQwxuwavblHawOtkiNk1eHWL0gZeJ0PMrsGrW5Q28DoZYnYNXt2itIHXyRCza/DqFqUNvE6GmF2DV7cobeB1MsTsGry6RWkDr5MhZtfg1S1KG3idDDG7Bq9uUdrA62SI2TV4dYvSBl4nQ8yuwatblDbwOhlidg1e3aK0gdfJELNr8OoWpQ28ToaYXceIdyJ8k1646xJcVMgnkXyKn+TUGVIoEyfecL/kBPErr5MnOXWGmF2DV7cobeB1MsTsGry6RWkDr5MhZtfg1S1KG3idDDG7Bq9uUdrA62SI2TV4dYvSBl4nQ8yuwatblDbwOhlidg1e3aK0gdfJELNr8OoWpQ28ToaYXYNXtyht4HUyxOwavLpFaQOvkyFm1+DVLUobeJ0MMbsGr25R2sDrZIjZNXh1i9IGXidDzK7Bq1uUNvA6GWJ2DV7dorSB18kQs2vw6halDbxOhphdg7fqohiSviFB4K2+KIakb0gQeKsviiHpGxIE3uqLYkj6hgSBt/qiGJK+IUHgrb4ohqRvSBB4qy+KIekbEgTe6otiSPqGBIG3+qIYkr4hQeCtviiGpG9IEHirL4oh6RsSBN7qi2JI+oYEgbf6ohiSviFB4K2+KIakb0gQeKsviiHpGxIE3uqLYkj6hgSBt/qiGJK+IUHgrb4ohqRvSBB4qy+KIekbEgTe6otiSPqGBIG3+qIYkr4hQeCtviiGpG9IUES8L7S1bM6BlyE1iDfTeCjbsQe8DKlBvN0dIgfb/R8Mb9iw4ecnwpefDHddgotiSJqHFBqOhrdzi0hvq/+DX51zzjk78+HzvAgXaxMnQyaTnzHpZkjyM/JelCFjEfFu9fFeWvqncL/zB4V922BVfszBkLD/c082Dchg8kOG5VjyQzKTUa6Ohrd7rciLV4N3RuC1aS7xZpp6vXW7wTsj8No0l3jl4LIlm+byr8qsAq9Npz7eWUX4aYDXJvCawBtz4LUJvNrAaxN4tYHXJvCawBtz4LUJvNrAaxN4tYHXJvCawBtz4LUJvNrAaxN4tYHXJvCawBtz4LUJvNrAa9NHDG+EHu90MOSBp5KfMbnh5eSHHNvwbvJDDm0Yq/5JUXt2Rww3mWu87V9zMGTBLcnPmKx/OPkhr9UfTH7IE/WDyQ/Z8sUYbgLemAKvVeDVBl6bwKvt+AfVPydy7w84GNI7mvyMid5s8kMyvZPJDxl6L4abzDVeotCBl2o2J3g/aHjS/75zW5rvfGSl6rNWNy66vfqbkPz59rcu6/zzzr/ohrd0nxtqgPybv7XehudF9rRr7hNuSKG+huDvxa5t/PWfZj/ADd5zW0ZCEPP6I975w25Q+LjX/9ysZapWl2/99xPj277zYf96al4cePsk89jCoecqTvwkDxXO1X/6V+1d4Lu6dWdxSlJ4F1zhiQxeNONRQp/ArNzgbdy4NSC2/4pFd5wIPvRIyyXX9UvPjQ/e9PXXJH9nU/OjcuXLct9i8ZrfOrjssjtHpOdbN31Tf2dzzfVdItu/L7NucOT6Hdfc+MwtrXunhvofL3z7nwYpfqb38KIluzSre/+8nP9njY2l67o23dK+um/mfYs//NeGb9jeujwfr8/qB/5PsvhQZnfBkH1XNG33og6Qd88dl3X3LRdZ/Lw/pXQfM6bsLMIPKdTX8s3XRX7y3cYYTmBWjvAONb/mE3u7+Z3cLTsLH+m7sC/73YelZ/6r8vCt8tTVY2/NH/veQ3Ldhf1Hm/sveTO/8U7pOe+x6v9JT+nOxWseXS/e5W/MvsGRhne8q270Xrl8aqj/8eDbKil+5sHL+kZXaVbnXfbtlwv/hf/idV3zj8juNTPvW/yh/yuv7a3LC/Du+47/kzQPVdxdYcibrR/0L30u6gDxFr3iNQ8uHBg8J+NPKd6nOKbsLMIPKdTXsuf7ImufbozhBGblCK/8ZOVk57ZH/N/ee9oKH8n2y+jt90vPEpEX18qTS3v831cOdOQvu+2ZJ2994mb/iiXS0+rp71y8pq8xf+Rr3uwbHFkqcsdeGWmZGup/PPi2SoqfueXHIj9TrW5wx9ILbzlauq5rtf8k8ydm3Lf4Qx+v9a3LCvA+t8r/SZqHKu6uMGTXAyL/1xN1gMgtj/RcJTc/fWBFYRXF+xTHlJ1FhCFSwNvX5p1o7WuM4wRm5gqvt2pv57Yd/k9x6OLCR/K7rly56v7Cz15eWiu5HzZdvtcbbXz9W4/ft+WJB1uuvPLKVV7PNyzuXLxGlr/6owdk9g0Kb6Xu6JLRlqmh/seDb6tKn3lzt8hr2tUd3XjhUPG6rtv9f248PuO+xR/6eMPcembTv/KahyrurjDkrv8ofELUASKP39x5r+y96/vbC6so3qc4puwsIgyRAl656u3uTf5ZxXMCU7nCKz2N92575G6RN5YWPtK18rg8MoX32GD+pUsPy8ptP+i5dvl7j28RmTga/Dv1nYvX+L8orXpTZt9gGu+MocVvxc/c9ojIs5rVPe3/OuH/dvu/xeu6rhPJzM/PuG/xhz5e21uXF+C97cHCTYOHKu6u8M87f+Cf9C+jDvA3s6jjeXn3stXPFO5avE/piGafRYQhEuD90UO3HvTPKvoJzMoZXrl7gf+e92h+ffDXJp3rvF+tuLuE96HVE5mlL8m9FxzMNy323l/0bv6e2/V4C3cuXiOHF7d5MvsG03hnDC1+K37mS4s/GLtWs7pjjV3Zof3No8Xrus55efJ735l53+IP8+dO2t66PB/v2N6Fg4WbBg9V3F3hn1+9vH/0qqejDvD/r7DxghPiLZ4/WLhr8T6lI5p9FhGGSID3na+35vyzin4Cs3KHN9MS/G3D7ZnCRwbbW6/tWna48ASv7JXhNQtb7vXk+YYRueEO/83P0uabhizwFu5srhGvdZeU3aCEd8vMoaVv5jO9H311yROq//+HX157cePq10rXdX1rdfPqYzPvW/yhd2Ob9a3LOn/BhRddfyT4SZqHMrsLHuqxxS3bvagD/L5d+AvejW3BKkr3KR7R7LOIMiTAK1+/rXBWMZzAzPhP2CLUtWGufwYf7cAbIfDObeClmg28VLOBl2o28FLNBl6q2cCbrnJ1/z3XP4XaCbxz3Jt1W+Ws9VP/CF6LwDunjff0X/MseEMGXkedtvfLZ/7jO1f+2RkbRV794u99/B9eEpn36Ce+IvN+Wl9X96XSx8BrEXgdddo/DRz/i4/tmVw/b0Q+84V9+z//Nz7eP73nDR9v8Ctv8WPgtQi8jjrthyLf8MG+V3d48ruvizzwCR/vrf6/MHhLHwOvReB11GldIjd8RWSg7rBkn97w1TMKeH8iJbylj4HXIvA6agbe0c99atWeez4RuC3hLX0MvBaB11Ez8D7222Mi22fjLX0MvBaB11Ez8D5Vt+v17X/0my9N4f380v7Sx8BrEXgdNYX3t3q8G888fcHhc78yhfee088rfQy8FoGXajbwUs0GXqrZwEs1G3ipZgMv1WzgpZoNvFSzgZdqNvBSzQZeqtn+H0bll+CQXobCAAAAAElFTkSuQmCC)
gss_cat %>% mutate(marital = marital %>% fct_infreq()) %>%
ggplot(aes(marital)) +
geom_bar()
![](data:image/png;base64,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)
gss_cat %>% mutate(marital = marital %>% fct_infreq() %>% fct_rev()) %>%
ggplot(aes(marital)) +
geom_bar()
![](data:image/png;base64,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)
Modifying factor levels.
gss_cat %>% count(partyid)
Re-coding
gss_cat %>%
mutate(partyid = fct_recode(partyid,
"Republican, strong" = "Strong republican",
"Republican, weak" = "Not str republican",
"Independent, near rep" = "Ind,near rep",
"Independent, near dem" = "Ind,near dem",
"Democrat, weak" = "Not str democrat",
"Democrat, strong" = "Strong democrat"
)) %>%
count(partyid)
Other category
gss_cat %>%
mutate(partyid = fct_recode(partyid,
"Republican, strong" = "Strong republican",
"Republican, weak" = "Not str republican",
"Independent, near rep" = "Ind,near rep",
"Independent, near dem" = "Ind,near dem",
"Democrat, weak" = "Not str democrat",
"Democrat, strong" = "Strong democrat",
"Other" = "No answer",
"Other" = "Don't know",
"Other" = "Other party"
)) %>%
count(partyid)
Collapse a factor
gss_cat %>%
mutate(partyid = fct_collapse(partyid,
other = c("No answer", "Don't know", "Other party"),
rep = c("Strong republican", "Not str republican"),
ind = c("Ind,near rep", "Independent", "Ind,near dem"),
dem = c("Not str democrat", "Strong democrat")
)) %>%
count(partyid)
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