Scraping tables from website returns only empty table

Question

I try to scrap tables from link: https://archive.twitter-trending.com/united-states/16-11-2023. My goal is to get all tables from this link. I use following code:

library(rvest)
library(dplyr)
link <- 'https://archive.twitter-trending.com/united-states/16-11-2023'
tt = read_html(link)

my_tables <- html_nodes(tt, "table")

for (table in my_tables) {
  print(table %>% html_table())
}

And the output I got is:

# A tibble: 1 x 4
  X1    X2    X3                                        X4                                       
  <lgl> <lgl> <chr>                                     <chr>                                    
1 NA    NA    United States Twitter Trends (16/11/2023) United States Twitter Trends (16/11/2023)

Why can`t I access tables?

Answer 1

It's a dynamic javascript-driven site, those tables are built by your browser. If you are fine with using Chrome, chromote and up to date rvest (>= 1.0.4), you could try read_html_live():

library(rvest)
library(purrr)
library(dplyr)
library(stringr)

link <- 'https://archive.twitter-trending.com/united-states/16-11-2023'
sess <- read_html_live(link)
# currently there doesn't seem to be a proper interface for waiting for 
# chromote / LiveHTML events, but evaluating JS takes some time; 
# so we'll just sleep for a moment
Sys.sleep(.5)

# check the first table
html_element(sess, "table.tablo611") |> 
  html_table()
#> # A tibble: 15 × 2
#>    X1           X2                  
#>    <chr>        <chr>               
#>  1 1)           Blinken             
#>  2 36.000 tweet <NA>                
#>  3 2)           HELLUVATOOZ         
#>  4 6.832 tweet  <NA>                
#>  5 3)           Wray                
#>  6 4)           Reed Richards       
#>  7 5)           Keke                
#>  8 6)           First Person Shooter
#>  9 9.879 tweet  <NA>                
#> 10 7)           Madame Web          
#> 11 8)           Camilla             
#> 12 9.218 tweet  <NA>                
#> 13 9)           559Q-RXGN4-JZPP     
#> 14 5.962 tweet  <NA>                
#> 15 10)          King Kilo

# create a helper to clean it up a bit ..
parse_tbl <- \(t_) t_ |>
  html_table() |>
  mutate(n = if_else(str_detect(X1, "tweet"), X1, NA) |> str_remove_all("[^\\d]") |> as.integer() |> lead()) |>
  select(topic = X2, n) |> 
  filter(!is.na(topic))

# .. test ..
html_element(sess, "table.tablo611") |> 
  parse_tbl()
#> # A tibble: 10 × 2
#>    topic                    n
#>    <chr>                <int>
#>  1 Blinken              36000
#>  2 HELLUVATOOZ           6832
#>  3 Wray                    NA
#>  4 Reed Richards           NA
#>  5 Keke                    NA
#>  6 First Person Shooter  9879
#>  7 Madame Web              NA
#>  8 Camilla               9218
#>  9 559Q-RXGN4-JZPP       5962
#> 10 King Kilo               NA

# .. collect all div.tek_tablo elemnts to collect table captions to be used as list names and
# apply parse_tbl() to all "div.tek_tablo > table.tablo611" elements
html_elements(sess, "div.tek_tablo") %>% 
  set_names(html_element(., ".trend_baslik611") |> html_text()) |>
  map(\(tek_tablo) html_element(tek_tablo, "table.tablo611") |> parse_tbl())

Result:

#> $`00:00`
#> # A tibble: 10 × 2
#>    topic                    n
#>    <chr>                <int>
#>  1 Blinken              36000
#>  2 HELLUVATOOZ           6832
#>  3 Wray                    NA
#>  4 Reed Richards           NA
#>  5 Keke                    NA
#>  6 First Person Shooter  9879
#>  7 Madame Web              NA
#>  8 Camilla               9218
#>  9 559Q-RXGN4-JZPP       5962
#> 10 King Kilo               NA
#> 
#> $`00:30`
#> # A tibble: 10 × 2
#>    topic                    n
#>    <chr>                <int>
#>  1 Pedro Pascal            NA
#>  2 Blinken              37400
#>  3 Wray                    NA
#>  4 Keke                 40599
#>  5 First Person Shooter 12000
#>  6 Chip Roy                NA
#>  7 Usher                34400
#>  8 King Kilo               NA
#>  9 John Krasinski          NA
#> 10 Camilla                 NA
#> 
#> $`01:00`
#> # A tibble: 10 × 2
#>    topic                    n
#>    <chr>                <int>
#>  1 Pedro Pascal            NA
#>  2 Blinken              39599
#>  3 John Krasinski        1047
#>  4 HELLUVATOOZ           9206
#>  5 Wray                    NA
#>  6 First Person Shooter 14399
#>  7 Candace              31600
#>  8 Keke                 42400
#>  9 Chip Roy             11000
#> 10 King Kilo               NA
#> 
#> $`01:30`
#> # A tibble: 10 × 2
#>    topic                    n
#>    <chr>                <int>
#>  1 Pedro Pascal            NA
#>  2 Candace                 NA
#>  3 Blinken              40400
#>  4 John Krasinski        1383
#>  5 HELLUVATOOZ          10200
#>  6 Wray                 72199
#>  7 First Person Shooter 15200
#>  8 Keke                    NA
#>  9 Shadow and Bone       2598
#> 10 Vin Diesel            1192
#> 
#> $`02:00`
#> # A tibble: 10 × 2
#>    topic                    n
#>    <chr>                <int>
#>  1 Pedro Pascal            NA
#>  2 Candace                 NA
#>  3 Cy Young                NA
#>  4 Gerrit Cole           3265
#>  5 #AaveHack             5223
#>  6 Blinken              41800
#>  7 John Krasinski        1732
#>  8 HELLUVATOOZ          11200
#>  9 Wray                 76600
#> 10 First Person Shooter 16799
#> 
#> $`02:30`
#> # A tibble: 10 × 2
#>    topic                    n
#>    <chr>                <int>
#>  1 #CashAppPlays         1606
#>  2 Candace                 NA
#>  3 Pedro Pascal            NA
#>  4 #AaveHack            20000
#>  5 Blinken              42000
#>  6 HELLUVATOOZ          12800
#>  7 Wray                 81400
#>  8 Shadow and Bone         NA
#>  9 Ospreay               1902
#> 10 First Person Shooter 17600
#> 
#> $`03:00`
#> # A tibble: 10 × 2
#>    topic               n
#>    <chr>           <int>
#>  1 Candace            NA
#>  2 Pedro Pascal       NA
#>  3 Blinken         43800
#>  4 Doris Burke        NA
#>  5 Shadow and Bone    NA
#>  6 Ospreay          2221
#>  7 Wray            86000
#>  8 HELLUVATOOZ     13200
#>  9 The Rock        99600
#> 10 Chris Martin    25799
#> 
#> $`03:30`
#> # A tibble: 10 × 2
#>    topic                n
#>    <chr>            <int>
#>  1 #AEWDynamite        NA
#>  2 Candace             NA
#>  3 #Survivor45       1737
#>  4 Cy Young            NA
#>  5 #TheMaskedSinger    NA
#>  6 Doris Burke         NA
#>  7 Banton              NA
#>  8 John Krasinski    2867
#>  9 Wray             91400
#> 10 Ospreay             NA
#> 
#> $`04:00`
#> # A tibble: 10 × 2
#>    topic             n
#>    <chr>         <int>
#>  1 #AEWDynamite     NA
#>  2 Candace          NA
#>  3 #CashAppPlays    NA
#>  4 Hangman          NA
#>  5 Cy Young         NA
#>  6 Vin Diesel     2454
#>  7 Skye Blue      1302
#>  8 Blinken       46000
#>  9 Prince Nana      NA
#> 10 Springer       8019
#> 
#> $`04:30`
#> # A tibble: 10 × 2
#>    topic              n
#>    <chr>          <int>
#>  1 #AEWDynamite      NA
#>  2 #RHOBH            NA
#>  3 #RHOM             NA
#>  4 Kellie          4704
#>  5 Doris Burke       NA
#>  6 Bin Laden         NA
#>  7 Blinken        46800
#>  8 Skye Blue         NA
#>  9 Banton          1912
#> 10 Christ is King 11800
#> 
#> $`05:00`
#> # A tibble: 10 × 2
#>    topic             n
#>    <chr>         <int>
#>  1 #AEWDynamite     NA
#>  2 #Survivor45      NA
#>  3 Al Horford       NA
#>  4 Derrick White  2766
#>  5 #SistasOnBET     NA
#>  6 #RHOM            NA
#>  7 Doris Burke    2037
#>  8 Embiid        12399
#>  9 Bin Laden        NA
#> 10 Reed Richards    NA
#> 
#> $`05:30`
#> # A tibble: 10 × 2
#>    topic            n
#>    <chr>        <int>
#>  1 #AEWDynamite    NA
#>  2 #Survivor45     NA
#>  3 Candace         NA
#>  4 #SistasOnBET    NA
#>  5 #RHOBH          NA
#>  6 #RHOM           NA
#>  7 Eubanks       1814
#>  8 Brunson       4147
#>  9 Bin Laden       NA
#> 10 Doris Burke   2138
#> 
#> $`06:00`
#> # A tibble: 10 × 2
#>    topic                n
#>    <chr>            <int>
#>  1 #AEWDynamite        NA
#>  2 Candace             NA
#>  3 #RHOBH              NA
#>  4 Al Horford          NA
#>  5 #SistasOnBET        NA
#>  6 #RHOM               NA
#>  7 Bin Laden           NA
#>  8 Eubanks           2633
#>  9 Patrick Williams    NA
#> 10 Brunson             NA
#> 
#> $`06:30`
#> # A tibble: 10 × 2
#>    topic            n
#>    <chr>        <int>
#>  1 #AEWDynamite    NA
#>  2 Sabonis       5662
#>  3 Candace         NA
#>  4 #RHOBH          NA
#>  5 Al Horford      NA
#>  6 #SistasOnBET    NA
#>  7 #FluffyFunko  2311
#>  8 Bin Laden       NA
#>  9 Vin Diesel    3509
#> 10 Insurrection 33400
#> 
#> $`07:00`
#> # A tibble: 10 × 2
#>    topic             n
#>    <chr>         <int>
#>  1 #AEWDynamite     NA
#>  2 Sabonis        6574
#>  3 Anthony Davis 12000
#>  4 Candace          NA
#>  5 #RHOBH           NA
#>  6 Bin Laden        NA
#>  7 #FluffyFunko   2508
#>  8 #SistasOnBET     NA
#>  9 Al Horford       NA
#> 10 Insurrection  36599
#> 
#> $`07:30`
#> # A tibble: 10 × 2
#>    topic             n
#>    <chr>         <int>
#>  1 Sabonis        7604
#>  2 Anthony Davis 11600
#>  3 #AEWDynamite     NA
#>  4 #Survivor45      NA
#>  5 Candace          NA
#>  6 #RHOBH           NA
#>  7 Bin Laden        NA
#>  8 #FluffyFunko   2627
#>  9 #SistasOnBET     NA
#> 10 Al Horford       NA
#> 
#> $`08:00`
#> # A tibble: 10 × 2
#>    topic              n
#>    <chr>          <int>
#>  1 Sabonis         9072
#>  2 Anthony Davis  12600
#>  3 #AEWDynamite      NA
#>  4 #Survivor45       NA
#>  5 Candace           NA
#>  6 Bin Laden         NA
#>  7 #RHOBH            NA
#>  8 #FluffyFunko    2744
#>  9 LIGHT THE BEAM  1119
#> 10 #SACvsLAL         NA
#> 
#> $`08:30`
#> # A tibble: 10 × 2
#>    topic              n
#>    <chr>          <int>
#>  1 Sabonis         9781
#>  2 Anthony Davis  11800
#>  3 #AEWDynamite      NA
#>  4 #Survivor45       NA
#>  5 Bin Laden         NA
#>  6 Candace           NA
#>  7 #RHOBH            NA
#>  8 #FluffyFunko    2842
#>  9 LIGHT THE BEAM  1236
#> 10 Christ is King    NA
#> 
#> $`09:00`
#> # A tibble: 10 × 2
#>    topic              n
#>    <chr>          <int>
#>  1 Sabonis           NA
#>  2 #Survivor45    12800
#>  3 #AEWDynamite      NA
#>  4 Bin Laden         NA
#>  5 Candace           NA
#>  6 #FluffyFunko    2911
#>  7 #RHOBH            NA
#>  8 LIGHT THE BEAM  1322
#>  9 Christ is King    NA
#> 10 Vin Diesel      3922
#> 
#> $`09:30`
#> # A tibble: 10 × 2
#>    topic              n
#>    <chr>          <int>
#>  1 Sabonis           NA
#>  2 Anthony Davis  11800
#>  3 #Survivor45    12800
#>  4 Bin Laden         NA
#>  5 #AEWDynamite      NA
#>  6 Candace           NA
#>  7 #FluffyFunko    2976
#>  8 #RHOBH            NA
#>  9 Christ is King    NA
#> 10 LIGHT THE BEAM  1337
#> 
#> $`10:00`
#> # A tibble: 10 × 2
#>    topic                       n
#>    <chr>                   <int>
#>  1 Sabonis                    NA
#>  2 Bin Laden                  NA
#>  3 #Survivor45                NA
#>  4 #AEWDynamite            55400
#>  5 Candace                    NA
#>  6 #FluffyFunko             3044
#>  7 #BorutoTwoBlueVortexCh4  1483
#>  8 #RHOBH                     NA
#>  9 Christ is King             NA
#> 10 LIGHT THE BEAM           1380
#> 
#> $`10:30`
#> # A tibble: 10 × 2
#>    topic                       n
#>    <chr>                   <int>
#>  1 Scary Hours 3            1934
#>  2 Sabonis                    NA
#>  3 Bin Laden                  NA
#>  4 #Survivor45                NA
#>  5 Candace                    NA
#>  6 #AEWDynamite               NA
#>  7 #BorutoTwoBlueVortexCh4  2040
#>  8 #FluffyFunko             3100
#>  9 Christ is King             NA
#> 10 #RHOBH                     NA
#> 
#> $`11:00`
#> # A tibble: 10 × 2
#>    topic                       n
#>    <chr>                   <int>
#>  1 Scary Hours 3            4755
#>  2 Sabonis                    NA
#>  3 Bin Laden                  NA
#>  4 Anthony Davis           12399
#>  5 #Survivor45             14399
#>  6 #BorutoTwoBlueVortexCh4  2520
#>  7 Candace                    NA
#>  8 #FluffyFunko             3155
#>  9 #AEWDynamite               NA
#> 10 Zack                    56800
#> 
#> $`11:30`
#> # A tibble: 10 × 2
#>    topic                       n
#>    <chr>                   <int>
#>  1 Bin Laden                  NA
#>  2 Sabonis                    NA
#>  3 #BorutoTwoBlueVortexCh4  3067
#>  4 #Survivor45                NA
#>  5 Candace                    NA
#>  6 #FluffyFunko             3199
#>  7 mcountdown              93600
#>  8 Zack                    58000
#>  9 Christ is King             NA
#> 10 #AEWDynamite               NA
#> 
#> $`12:00`
#> # A tibble: 10 × 2
#>    topic                       n
#>    <chr>                   <int>
#>  1 Bin Laden                  NA
#>  2 #BorutoTwoBlueVortexCh4  3594
#>  3 Sabonis                    NA
#>  4 Anthony Davis           12399
#>  5 MCOUNTDOWN              88600
#>  6 Candace                    NA
#>  7 Zack                    61000
#>  8 #FluffyFunko             3242
#>  9 #Survivor45             15399
#> 10 #holoARMIS              20799
#> 
#> $`12:30`
#> # A tibble: 10 × 2
#>    topic               n
#>    <chr>           <int>
#>  1 Draymond Green     NA
#>  2 Candace            NA
#>  3 China          436000
#>  4 #AEWDynamite       NA
#>  5 Scary Hours 3      NA
#>  6 Madame Web      79199
#>  7 Thanksgiving    94199
#>  8 Klay            34200
#>  9 #Survivor45        NA
#> 10 Reed Richards   51400
#> 
#> $`13:00`
#> # A tibble: 10 × 2
#>    topic                         n
#>    <chr>                     <int>
#>  1 Draymond                     NA
#>  2 Candace                      NA
#>  3 China                    444000
#>  4 #StandingNextToYou2ndWin  33599
#>  5 #AEWDynamite                 NA
#>  6 Madame Web                79000
#>  7 Thanksgiving              95199
#>  8 Scary Hours 3                NA
#>  9 #Survivor45                  NA
#> 10 JUNGKOOK                 794000
#> 
#> $`13:30`
#> # A tibble: 10 × 2
#>    topic                         n
#>    <chr>                     <int>
#>  1 Draymond                     NA
#>  2 Candace                      NA
#>  3 China                    441000
#>  4 #StandingNextToYou2ndWin     NA
#>  5 #AEWDynamite                 NA
#>  6 Madame Web                79199
#>  7 Thanksgiving              95600
#>  8 #Survivor45               15399
#>  9 Reed Richards             52000
#> 10 Usher                        NA
#> 
#> $`14:00`
#> # A tibble: 10 × 2
#>    topic                         n
#>    <chr>                     <int>
#>  1 Draymond                     NA
#>  2 Candace                      NA
#>  3 China                    451000
#>  4 #AEWDynamite              58000
#>  5 #StandingNextToYou2ndWin     NA
#>  6 #thursdaymorning           4032
#>  7 Madame Web                80000
#>  8 Thanksgiving              96400
#>  9 #Survivor45                  NA
#> 10 Scary Hours 3                NA
#> 
#> $`14:30`
#> # A tibble: 10 × 2
#>    topic                 n
#>    <chr>             <int>
#>  1 Draymond             NA
#>  2 Candace              NA
#>  3 China            446000
#>  4 #thursdaymorning   4405
#>  5 #AEWDynamite         NA
#>  6 #thursdayvibes     7152
#>  7 Thanksgiving      96400
#>  8 Madame Web        80199
#>  9 #Survivor45          NA
#> 10 Good Thursday     21799
#> 
#> $`15:00`
#> # A tibble: 10 × 2
#>    topic                 n
#>    <chr>             <int>
#>  1 Draymond             NA
#>  2 Candace              NA
#>  3 China            458000
#>  4 #thursdaymorning   4852
#>  5 Scary Hours 3        NA
#>  6 #AEWDynamite      59800
#>  7 #thursdayvibes     7938
#>  8 Thanksgiving      97800
#>  9 Madame Web        80199
#> 10 #Survivor45       16600
#> 
#> $`15:30`
#> # A tibble: 10 × 2
#>    topic                 n
#>    <chr>             <int>
#>  1 Draymond             NA
#>  2 Candace              NA
#>  3 China            451000
#>  4 #thursdaymorning   5329
#>  5 Scary Hours 3        NA
#>  6 #thursdayvibes     8826
#>  7 #AEWDynamite      60000
#>  8 Thanksgiving      96400
#>  9 Madame Web        80600
#> 10 Ken Squier         1758
#> 
#> $`16:00`
#> # A tibble: 10 × 2
#>    topic                 n
#>    <chr>             <int>
#>  1 #thursdaymorning   5986
#>  2 #thursdayvibes     9724
#>  3 Ken Squier         2280
#>  4 Scary Hours 3        NA
#>  5 #MyGiftToYou         NA
#>  6 Happy Friday Eve     NA
#>  7 Bin Laden            NA
#>  8 #ThursdayThoughts  7280
#>  9 Good Thursday     26600
#> 10 Zack              84800
#> 
#> $`16:30`
#> # A tibble: 10 × 2
#>    topic                 n
#>    <chr>             <int>
#>  1 #MyGiftToYou       1428
#>  2 #thursdaymorning   6597
#>  3 Ken Squier         3101
#>  4 #thursdayvibes    11200
#>  5 Bin Laden            NA
#>  6 Happy Friday Eve     NA
#>  7 Zack              88600
#>  8 #ThursdayThoughts  7795
#>  9 Revert             4944
#> 10 Good Thursday     28400
#> 
#> $`17:00`
#> # A tibble: 10 × 2
#>    topic                 n
#>    <chr>             <int>
#>  1 #MyGiftToYou       2079
#>  2 #thursdaymorning   7286
#>  3 Oakland           28400
#>  4 Bin Laden            NA
#>  5 Ken Squier         3824
#>  6 #thursdayvibes    12200
#>  7 Scary Hours 3        NA
#>  8 Frozen 3           2617
#>  9 Zack              92000
#> 10 #ThursdayThoughts  8206
#> 
#> $`17:30`
#> # A tibble: 10 × 2
#>    topic                 n
#>    <chr>             <int>
#>  1 #MyGiftToYou       2682
#>  2 #thursdaymorning   8128
#>  3 Bin Laden            NA
#>  4 Ken Squier         4557
#>  5 #thursdayvibes    13600
#>  6 Frozen 3           2955
#>  7 Drake                NA
#>  8 Zack              96400
#>  9 #ThursdayThoughts  9004
#> 10 John Fisher        1625
#> 
#> $`18:00`
#> # A tibble: 10 × 2
#>    topic                n
#>    <chr>            <int>
#>  1 Oakland          32800
#>  2 #MyGiftToYou      3165
#>  3 Bin Laden           NA
#>  4 George Santos       NA
#>  5 #thursdaymorning  8701
#>  6 #thursdayvibes   14000
#>  7 Drake               NA
#>  8 Frozen 3          3376
#>  9 Zack              8371
#> 10 John Fisher       2003
#> 
#> $`18:30`
#> # A tibble: 10 × 2
#>    topic                 n
#>    <chr>             <int>
#>  1 Oakland           33400
#>  2 #MyGiftToYou       3516
#>  3 Bin Laden            NA
#>  4 #thursdaymorning   9439
#>  5 #GiftRTX          23799
#>  6 Frozen 3           3762
#>  7 #thursdayvibes       NA
#>  8 Drake                NA
#>  9 Zack             104000
#> 10 John Fisher        2198
#> 
#> $`19:00`
#> # A tibble: 10 × 2
#>    topic                n
#>    <chr>            <int>
#>  1 George Santos       NA
#>  2 Bin Laden           NA
#>  3 #MyGiftToYou      3848
#>  4 #GiftRTX         24200
#>  5 #thursdaymorning 10399
#>  6 Frozen 3            NA
#>  7 Bay Bridge        5961
#>  8 #thursdayvibes   16400
#>  9 John Fisher         NA
#> 10 Morel             2193
#> 
#> $`19:30`
#> # A tibble: 10 × 2
#>    topic                n
#>    <chr>            <int>
#>  1 George Santos       NA
#>  2 Oakland          36000
#>  3 Bin Laden           NA
#>  4 #MyGiftToYou      4149
#>  5 #GiftRTX         23000
#>  6 Bay Bridge        9846
#>  7 Release the J6   14399
#>  8 Morel               NA
#>  9 Snoop             6981
#> 10 #thursdaymorning 11399
#> 
#> $`20:00`
#> # A tibble: 10 × 2
#>    topic              n
#>    <chr>          <int>
#>  1 George Santos     NA
#>  2 Oakland           NA
#>  3 Snoop          14200
#>  4 Bin Laden         NA
#>  5 Release the J6 16200
#>  6 #MyGiftToYou    4408
#>  7 Bay Bridge     14000
#>  8 Morel             NA
#>  9 Frozen 3          NA
#> 10 #thursdayvibes 18600
#> 
#> $`20:30`
#> # A tibble: 10 × 2
#>    topic              n
#>    <chr>          <int>
#>  1 Snoop          21799
#>  2 George Santos     NA
#>  3 Oakland           NA
#>  4 Bin Laden         NA
#>  5 Release the J6 17400
#>  6 Bay Bridge     18000
#>  7 #MyGiftToYou    4680
#>  8 Morel             NA
#>  9 Andre 3000     21600
#> 10 #thursdayvibes 19000
#> 
#> $`21:00`
#> # A tibble: 10 × 2
#>    topic               n
#>    <chr>           <int>
#>  1 Snoop              NA
#>  2 George Santos   67600
#>  3 Oakland         43400
#>  4 Release the J6  19000
#>  5 Bay Bridge         NA
#>  6 John Fisher      4696
#>  7 #MyGiftToYou     4909
#>  8 Andre              NA
#>  9 Morel              NA
#> 10 Zack           127000
#> 
#> $`21:30`
#> # A tibble: 10 × 2
#>    topic               n
#>    <chr>           <int>
#>  1 George Santos      NA
#>  2 Bin Laden          NA
#>  3 Release the J6  20400
#>  4 Bay Bridge      27000
#>  5 John Fisher      5863
#>  6 Andre              NA
#>  7 #MyGiftToYou     5780
#>  8 Morel              NA
#>  9 Zack           130000
#> 10 Edibles          6438
#> 
#> $`22:00`
#> # A tibble: 10 × 2
#>    topic               n
#>    <chr>           <int>
#>  1 Snoop              NA
#>  2 George Santos      NA
#>  3 Bin Laden          NA
#>  4 David DePape       NA
#>  5 Andre              NA
#>  6 Petry              NA
#>  7 Edibles          7086
#>  8 Manfred            NA
#>  9 #thursdayvibes  22400
#> 10 Zack           134000
#> 
#> $`22:30`
#> # A tibble: 10 × 2
#>    topic                               n
#>    <chr>                           <int>
#>  1 NIZA                            17600
#>  2 #FOR3VERwithAESPA                  NA
#>  3 #에스파의_드라마틱한_3주년      34400
#>  4 #GetHealthyWithBIBLE            57599
#>  5 #TeeJetsxBecky                 862000
#>  6 TEEJETS X REBECCA COVER HALLEY 845000
#>  7 #MeetingBiuIn2023               29400
#>  8 HOW I MET BUILD                 28000
#>  9 NOBODY IS OUT NOW               38000
#> 10 Cake                            95400
#> 
#> $`23:00`
#> # A tibble: 10 × 2
#>    topic                 n
#>    <chr>             <int>
#>  1 Snoop                NA
#>  2 Oakland              NA
#>  3 George Santos        NA
#>  4 Reynoso            5850
#>  5 Bin Laden            NA
#>  6 Release the J6    24400
#>  7 #LGRW              1667
#>  8 Zambrano           4596
#>  9 Charissa Thompson    NA
#> 10 Bay Bridge           NA
#> 
#> $`23:30`
#> # A tibble: 10 × 2
#>    topic                     n
#>    <chr>                 <int>
#>  1 George Santos            NA
#>  2 Reynoso                  NA
#>  3 #LGRW                  1996
#>  4 Zambrano                 NA
#>  5 soobin                19400
#>  6 #PMSLive               5597
#>  7 #WWESuperCardSeason10  2459
#>  8 David DePape             NA
#>  9 pannchoa              44200
#> 10 Andre                    NA

^{Created on 2024-03-09 with reprex v2.1.0}