网络信息分化表格:
library(tidyverse)## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --## v ggplot2 3.3.5 v purrr 0.3.4
## v tibble 3.1.4 v dplyr 1.0.7
## v tidyr 1.1.3 v stringr 1.4.0
## v readr 2.0.1 v forcats 0.5.1## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(readstata13)
library(haven)
css2019 <- read.dta13("E:/data/CSS/CSS2019/css2019.dta")## Warning in read.dta13("E:/data/CSS/CSS2019/css2019.dta"):
## Missing factor labels for variables
##
## d4b3_4
##
## No labels have beend assigned.
## Set option 'generate.factors=TRUE' to generate labels.css2019 <- css2019 %>% mutate(age = 2019-a1_1_a)
#css2019$age
css2019<-
css2019 %>%
mutate(agegroup = case_when(
age <= 40 ~ "40岁以下",
age >40 & age <= 60 ~ "40-60",
age > 60 ~ "60以上"
))
cssk <-
css2019 %>% select(
agegroup,
是否上网=d4a,
上网浏览时政信息=d4b1_1,
网上娱乐=d4b1_2,
上网聊天交友=d4b1_3,
网上商务或者工作=d4b1_4,
网上学习教育=d4b1_5,
网上购物与生活服务=d4b1_6,
网上投资理财=d4b1_7,
)
names(cssk)## [1] "agegroup" "是否上网" "上网浏览时政信息"
## [4] "网上娱乐" "上网聊天交友" "网上商务或者工作"
## [7] "网上学习教育" "网上购物与生活服务" "网上投资理财"cssk1<-cssk %>%drop_na(agegroup,是否上网)%>% replace(is.na(.), "从不")
cssk1$agegroup<-as.factor(cssk1$agegroup)
cssk1$agegroup<-factor(cssk1$agegroup, levels = c("40岁以下", "40-60", "60以上") )
library(gtsummary)## #Uighurtbl_summary(cssk1)| Characteristic | N = 10,2801 |
|---|---|
| agegroup | |
| 40岁以下 | 3,506 (34%) |
| 40-60 | 4,675 (45%) |
| 60以上 | 2,099 (20%) |
| 是否上网 | |
| 1.上 | 6,737 (66%) |
| 2.不上 | 3,543 (34%) |
| 上网浏览时政信息 | |
| 几乎每天 | 3,028 (29%) |
| 一周多次 | 1,141 (11%) |
| 一周至少一次 | 927 (9.0%) |
| 一月至少一次 | 333 (3.2%) |
| 一年几次 | 315 (3.1%) |
| 从不 | 4,536 (44%) |
| 网上娱乐 | |
| 几乎每天 | 3,030 (29%) |
| 一周多次 | 1,528 (15%) |
| 一周至少一次 | 791 (7.7%) |
| 一月至少一次 | 278 (2.7%) |
| 一年几次 | 206 (2.0%) |
| 从不 | 4,447 (43%) |
| 上网聊天交友 | |
| 几乎每天 | 3,663 (36%) |
| 一周多次 | 1,305 (13%) |
| 一周至少一次 | 755 (7.3%) |
| 一月至少一次 | 265 (2.6%) |
| 一年几次 | 176 (1.7%) |
| 从不 | 4,116 (40%) |
| 网上商务或者工作 | |
| 几乎每天 | 1,716 (17%) |
| 一周多次 | 722 (7.0%) |
| 一周至少一次 | 338 (3.3%) |
| 一月至少一次 | 230 (2.2%) |
| 一年几次 | 263 (2.6%) |
| 从不 | 7,011 (68%) |
| 网上学习教育 | |
| 几乎每天 | 1,297 (13%) |
| 一周多次 | 1,148 (11%) |
| 一周至少一次 | 692 (6.7%) |
| 一月至少一次 | 408 (4.0%) |
| 一年几次 | 405 (3.9%) |
| 从不 | 6,330 (62%) |
| 网上购物与生活服务 | |
| 几乎每天 | 439 (4.3%) |
| 一周多次 | 903 (8.8%) |
| 一周至少一次 | 834 (8.1%) |
| 一月至少一次 | 1,536 (15%) |
| 一年几次 | 938 (9.1%) |
| 从不 | 5,630 (55%) |
| 网上投资理财 | |
| 几乎每天 | 144 (1.4%) |
| 一周多次 | 93 (0.9%) |
| 一周至少一次 | 109 (1.1%) |
| 一月至少一次 | 158 (1.5%) |
| 一年几次 | 488 (4.7%) |
| 从不 | 9,288 (90%) |
|
1
n (%)
|
|
cssk1 %>% tbl_summary(
by = agegroup, missing = "no",
) %>%
#add_n() %>% # add column with total number of non-missing observations
add_p() %>% # test for a difference between groups
modify_header(label = "**年龄分布与网络使用**") %>% # update the column header
bold_labels() | 年龄分布与网络使用 | 40岁以下, N = 3,5061 | 40-60, N = 4,6751 | 60以上, N = 2,0991 | p-value2 |
|---|---|---|---|---|
| 是否上网 | <0.001 | |||
| 1.上 | 3,314 (95%) | 2,865 (61%) | 558 (27%) | |
| 2.不上 | 192 (5.5%) | 1,810 (39%) | 1,541 (73%) | |
| 上网浏览时政信息 | <0.001 | |||
| 几乎每天 | 1,340 (38%) | 1,359 (29%) | 329 (16%) | |
| 一周多次 | 678 (19%) | 397 (8.5%) | 66 (3.1%) | |
| 一周至少一次 | 544 (16%) | 348 (7.4%) | 35 (1.7%) | |
| 一月至少一次 | 205 (5.8%) | 116 (2.5%) | 12 (0.6%) | |
| 一年几次 | 201 (5.7%) | 104 (2.2%) | 10 (0.5%) | |
| 从不 | 538 (15%) | 2,351 (50%) | 1,647 (78%) | |
| 网上娱乐 | <0.001 | |||
| 几乎每天 | 1,728 (49%) | 1,066 (23%) | 236 (11%) | |
| 一周多次 | 834 (24%) | 599 (13%) | 95 (4.5%) | |
| 一周至少一次 | 362 (10%) | 372 (8.0%) | 57 (2.7%) | |
| 一月至少一次 | 126 (3.6%) | 138 (3.0%) | 14 (0.7%) | |
| 一年几次 | 83 (2.4%) | 102 (2.2%) | 21 (1.0%) | |
| 从不 | 373 (11%) | 2,398 (51%) | 1,676 (80%) | |
| 上网聊天交友 | <0.001 | |||
| 几乎每天 | 2,117 (60%) | 1,315 (28%) | 231 (11%) | |
| 一周多次 | 640 (18%) | 579 (12%) | 86 (4.1%) | |
| 一周至少一次 | 263 (7.5%) | 405 (8.7%) | 87 (4.1%) | |
| 一月至少一次 | 89 (2.5%) | 144 (3.1%) | 32 (1.5%) | |
| 一年几次 | 74 (2.1%) | 90 (1.9%) | 12 (0.6%) | |
| 从不 | 323 (9.2%) | 2,142 (46%) | 1,651 (79%) | |
| 网上商务或者工作 | <0.001 | |||
| 几乎每天 | 1,140 (33%) | 556 (12%) | 20 (1.0%) | |
| 一周多次 | 503 (14%) | 207 (4.4%) | 12 (0.6%) | |
| 一周至少一次 | 211 (6.0%) | 119 (2.5%) | 8 (0.4%) | |
| 一月至少一次 | 133 (3.8%) | 88 (1.9%) | 9 (0.4%) | |
| 一年几次 | 161 (4.6%) | 95 (2.0%) | 7 (0.3%) | |
| 从不 | 1,358 (39%) | 3,610 (77%) | 2,043 (97%) | |
| 网上学习教育 | <0.001 | |||
| 几乎每天 | 798 (23%) | 441 (9.4%) | 58 (2.8%) | |
| 一周多次 | 826 (24%) | 285 (6.1%) | 37 (1.8%) | |
| 一周至少一次 | 439 (13%) | 221 (4.7%) | 32 (1.5%) | |
| 一月至少一次 | 246 (7.0%) | 148 (3.2%) | 14 (0.7%) | |
| 一年几次 | 236 (6.7%) | 145 (3.1%) | 24 (1.1%) | |
| 从不 | 961 (27%) | 3,435 (73%) | 1,934 (92%) | |
| 网上购物与生活服务 | <0.001 | |||
| 几乎每天 | 340 (9.7%) | 92 (2.0%) | 7 (0.3%) | |
| 一周多次 | 704 (20%) | 179 (3.8%) | 20 (1.0%) | |
| 一周至少一次 | 611 (17%) | 190 (4.1%) | 33 (1.6%) | |
| 一月至少一次 | 950 (27%) | 543 (12%) | 43 (2.0%) | |
| 一年几次 | 410 (12%) | 472 (10%) | 56 (2.7%) | |
| 从不 | 491 (14%) | 3,199 (68%) | 1,940 (92%) | |
| 网上投资理财 | <0.001 | |||
| 几乎每天 | 108 (3.1%) | 31 (0.7%) | 5 (0.2%) | |
| 一周多次 | 65 (1.9%) | 27 (0.6%) | 1 (<0.1%) | |
| 一周至少一次 | 79 (2.3%) | 25 (0.5%) | 5 (0.2%) | |
| 一月至少一次 | 120 (3.4%) | 33 (0.7%) | 5 (0.2%) | |
| 一年几次 | 327 (9.3%) | 141 (3.0%) | 20 (1.0%) | |
| 从不 | 2,807 (80%) | 4,418 (95%) | 2,063 (98%) | |
|
1
n (%)
2
Pearson's Chi-squared test
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