The actual situation is like this. We have conducted a survey with 4 sections. I calculated the no response ratio for each section and then created data frames for each section. After that, I merged first and second. Then I merged third and fourth. I am giving reprex below.
library(tidyverse)
data1<-tibble::tribble(
~duration, ~enumerator, ~en_name, ~survey_date, ~child_name, ~child_age2, ~l1c1_identify_pic1, ~l1c1_identify_pic2, ~l1c1_identify_pic3, ~l1c1_identify_pic4, ~l1c1_identify_pic5, ~l1c1_identify_pic6, ~l1c1_classify_bird, ~l1c1_classify_animal, ~l1c1_identification, ~l1c1_classification, ~l1c1_total, ~l1c2_identify_col1, ~NDenom.x.x, ~No.response.ratio.x.x, ~l1el1_wr_rt, ~l1el1_total, ~l1el2_fac1, ~l1el2_fac2, ~l1el2_fac3, ~l1el2_total, ~l1el3_1sen, ~l1el3_1sen_comp, ~l1el3_2sen, ~l1el3_2sen_comp, ~NDenom.y.x, ~No.response.ratio.y.x, ~l1en1_recog_num1, ~l1en1_recog_num2, ~l1en1_recog_num3, ~l1en1_recog_num4, ~l1en1_recog_num5, ~l1en1_total, ~l1en2_recog_num1, ~l1en2_recog_num2, ~NDenom.x.y, ~No.response.ratio.x.y, ~sel_conversation_l1, ~sel_focus_l1, ~sec_total_l1, ~sel_emo1_l1, ~sel_emo2_l1, ~sel_emo3_l1, ~sel_emo4_l1, ~sel_emo5_l1, ~ser_total_l1, ~N98.y.y, ~NDenom.y.y, ~No.response.ratio.y.y,
2885L, "PEN008", "Seemakausar Nadaf", "24-09-2021 00:00", "Sharat Mangoji", 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 12L, 2L, 14L, 1L, 37L, 2.702702703, 98L, 98L, 0L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 35L, 20, 1L, 1L, 1L, 1L, 1L, 5L, 1L, 1L, 24L, 0, 2L, 3L, 5L, 1L, 1L, 1L, 1L, 1L, 5L, 0L, 10L, 0L,
2438L, "PEN006", "Jayashree H Malipatil", "24-09-2021 00:00", "Devaraj C Tallur", 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 12L, 2L, 14L, 98L, 37L, 13.51351351, 98L, 98L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 35L, 25.71428571, 1L, 0L, 0L, 0L, 1L, 2L, 98L, 98L, 24L, 20.83333333, -1L, -1L, -2L, 1L, 1L, 1L, 1L, 1L, 5L, 0L, 10L, 0L,
1686L, "PEN003", "Jyoti T Patil", "24-09-2021 00:00", "Roshan begum", 6L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 0L, 10L, 1L, 11L, 0L, 37L, 2.702702703, 98L, 98L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 35L, 5.714285714, 1L, 1L, 1L, 1L, 1L, 5L, 1L, 1L, 24L, 16.66666667, 3L, 3L, 6L, 1L, 1L, 1L, 1L, 1L, 5L, 0L, 10L, 0L,
1409L, "PEN008", "Seemakausar Nadaf", "24-09-2021 00:00", "Samrth", 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 12L, 2L, 14L, 0L, 37L, 0, 0L, 0L, 0L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 34L, 23.52941176, 1L, 0L, 0L, 1L, 0L, 2L, 98L, 98L, 24L, 41.66666667, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 5L, 0L, 10L, 0L,
1825L, "PEN004", "Viranna Potadar", "24-09-2021 00:00", "Sanjay irappa dusad", 6L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 10L, 0L, 10L, 0L, 37L, 0, 0L, 0L, 0L, 0L, 0L, 0L, 0L, NA, NA, NA, 30L, 0, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 24L, 0, 1L, 1L, 2L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 10L, 0L,
2505L, "PEN002", "Hemalata B. Bhajantri", "24-09-2021 00:00", "Mahatmappa", 6L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 12L, 0L, 12L, 0L, 37L, 0, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 35L, 0, 1L, 0L, 0L, 1L, 0L, 2L, 0L, 0L, 24L, 0, 2L, 2L, 4L, 1L, 1L, 1L, 1L, 1L, 5L, 0L, 10L, 0L,
1872L, "PEN009", "Savita Vandal", "24-09-2021 00:00", "Soubhagya", 6L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 10L, 2L, 12L, 0L, 37L, 0, 0L, 0L, 0L, 0L, 0L, 0L, 0L, NA, NA, NA, 30L, 0, 1L, 0L, 0L, 1L, 0L, 2L, 0L, 0L, 24L, 0, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 5L, 0L, 10L, 0L
)
data1_cog<-data1 %>%
select(duration:No.response.ratio.x.x)
data1_lan<-data1 %>%
select(child_name,l1el1_wr_rt:No.response.ratio.y.x)
data1_num<-data1 %>%
select(child_name,l1en1_recog_num1:No.response.ratio.x.y)
data1_sel<-data1 %>%
select(child_name,sel_conversation_l1:No.response.ratio.y.y)
combine1<-left_join(data1_cog,data1_lan,by="child_name")
combine2<-left_join(data1_num,data1_sel,by="child_name")
combine_master<-left_join(combine1,combine2,by="child_name")
combine_master
#> # A tibble: 7 x 54
#> duration enumerator en_name survey_date child_name child_age2 l1c1_identify_p~
#> <int> <chr> <chr> <chr> <chr> <int> <int>
#> 1 2885 PEN008 Seemak~ 24-09-2021~ Sharat Ma~ 6 1
#> 2 2438 PEN006 Jayash~ 24-09-2021~ Devaraj C~ 6 1
#> 3 1686 PEN003 Jyoti ~ 24-09-2021~ Roshan be~ 6 1
#> 4 1409 PEN008 Seemak~ 24-09-2021~ Samrth 6 1
#> 5 1825 PEN004 Virann~ 24-09-2021~ Sanjay ir~ 6 1
#> 6 2505 PEN002 Hemala~ 24-09-2021~ Mahatmappa 6 1
#> 7 1872 PEN009 Savita~ 24-09-2021~ Soubhagya 6 1
#> # ... with 47 more variables: l1c1_identify_pic2 <int>,
#> # l1c1_identify_pic3 <int>, l1c1_identify_pic4 <int>,
#> # l1c1_identify_pic5 <int>, l1c1_identify_pic6 <int>,
#> # l1c1_classify_bird <int>, l1c1_classify_animal <int>,
#> # l1c1_identification <int>, l1c1_classification <int>, l1c1_total <int>,
#> # l1c2_identify_col1 <int>, NDenom.x.x <int>, No.response.ratio.x.x <dbl>,
#> # l1el1_wr_rt <int>, l1el1_total <int>, l1el2_fac1 <int>, ...
Created on 2021-11-08 by the reprex package (v2.0.1)