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This gist shows how to download and wrangle YouTube meta data in R

Background

You’ll need to setup YouTube OAuth Authentication (with an application id and password). If you have questions check out the package documentation or the tutorial on Storybench.

# Load packages below
library(magrittr) # Pipes %>%, %T>% and equals(), extract().
library(tidyverse) # all tidyverse packages
library(hrbrthemes) # themes for graphs
library(tuber) # youtube API

Accessing YouTube data

Great! Now that you have your YouTube authentication all set up, we’ll download some data into RStudio. Be sure to check out the reference page and the YouTube API reference docs on how to access various meta data from YouTube videos.

An example data set

We’re basing this documentation off of a previous project implemented in Python, and want to create two data sets identical to the .csv’s we import in the code chunk below:

amy_destfile <- paste0("data/", 
       base::noquote(lubridate::today()), 
       "-amy.csv")

kap_destfile <- paste0("data/", 
       base::noquote(lubridate::today()), 
       "-kap.csv")

download.file(url = "https://raw.githubusercontent.com/richardcornish/sketch-comedy-data/master/csvs/amy.csv", 
              destfile = amy_destfile)
download.file(url = "https://raw.githubusercontent.com/richardcornish/sketch-comedy-data/master/csvs/kap.csv", 
              destfile = kap_destfile)

trying URL 'https://raw.githubusercontent.com/richardcornish/sketch-comedy-data/master/csvs/amy.csv'
Content type 'text/plain; charset=utf-8' length 19693 bytes (19 KB)
==================================================
downloaded 19 KB

trying URL 'https://raw.githubusercontent.com/richardcornish/sketch-comedy-data/master/csvs/kap.csv'
Content type 'text/plain; charset=utf-8' length 30913 bytes (30 KB)
==================================================
downloaded 30 KB

Import the datasets.

KeyAndPeeleRaw <- readr::read_csv(kap_destfile)
AmyRaw <- readr::read_csv(kap_destfile)

Parsed with column specification:
cols(
  publishedAt = col_datetime(format = ""),
  dislikeCount = col_double(),
  url = col_character(),
  id = col_character(),
  commentCount = col_double(),
  title = col_character(),
  viewCount = col_double(),
  likeCount = col_double()
)
Parsed with column specification:
cols(
  publishedAt = col_datetime(format = ""),
  dislikeCount = col_double(),
  url = col_character(),
  id = col_character(),
  commentCount = col_double(),
  title = col_character(),
  viewCount = col_double(),
  likeCount = col_double()
)

Take a look at variables in both datasets to see what I’ll need.

# more elaborate than needed, but wanted to see how well this works
intersect(x = names(KeyAndPeeleRaw), 
                     y = names(AmyRaw))

[1] "publishedAt"  "dislikeCount" "url"          "id"           "commentCount" "title"        "viewCount"    "likeCount"   

After doing a little reading in the YouTube API documentation, we discover we will have to adapt the tuber package functions to get us these columns. We’ll use the Drunk History playlist from Comedy Central’s YouTube Channel as case study.

Step 1) Extracting playlist data

We will be using the playlist id from the url to access the content from the videos. Be sure to check the documentation on the available playlist data from the YouTube API.

playlistId = The playlistId parameter specifies the unique ID of the playlist for which you want to retrieve playlist items. Note that even though this is an optional parameter, every request to retrieve playlist items must specify a value for either the id parameter or the playlistId parameter.

Let’s split the url for this playlist and get the playlistId and store it in drunk_history_playlist_id.

drunk_history_playlist_id <- stringr::str_split(
    string = "https://www.youtube.com/playlist?list=PLD7nPL1U-R5pSwKIcVaIQrG5BnGMbHI5H", 
    pattern = "=", 
    n = 2,
    simplify = TRUE)[ , 2]
drunk_history_playlist_id

[1] "PLD7nPL1U-R5pSwKIcVaIQrG5BnGMbHI5H"

Step 2) Getting the playlist items

We now take the playlistId object (stored in a vector drunk_history_playlist_id), and pass it over to the tuber::get_playlist_items() function, but add part and max_results arguments. The documentation for the tuber::get_playlist_items() from tuber has the following description & arguments:

Description: Get Playlist Items.

  • filter = string; Required. named vector of length 1 potential names of the entry in the vector: item_id: comma-separated list of one or more unique playlist item IDs. playlist_id: YouTube playlist ID.
  • video_id = Comma separated list of IDs of the videos for which details are requested. Required.
  • part = Required. Comma separated string including one or more of the following: contentDetails, id, snippet, status. Default: contentDetails
  • max_results = Maximum number of items that should be returned. Integer. Optional. Default is 50. If over 50, all the results are returned.
  • simplify = returns a data.frame rather than a list.

We’ll set the part to "snippet", the max_result to the number of videos in the playlist, and simplify to true. We’ll throw all this into a data.frame named DrunkHistRawSnippets.

DrunkHistRawSnippets <- tuber::get_playlist_items(filter = c(playlist_id = drunk_history_playlist_id), 
                                              # get snippets
                                              part = "snippet",
                                              # set this to the number of videos
                                              max_results = 150,
                                              # return a data frame
                                              simplify = TRUE) 
DrunkHistRawSnippets %>% dplyr::glimpse(78)

Observations: 110
Variables: 28
$ .id                                <chr> "items1", "items2", "items3", "i…
$ kind                               <fct> youtube#playlistItem, youtube#pl…
$ etag                               <fct> "p4VTdlkQv3HQeTEaXgvLePAydmU/Jjk…
$ id                                 <fct> UExEN25QTDFVLVI1cFN3S0ljVmFJUXJH…
$ snippet.publishedAt                <fct> 2019-09-26T18:34:54.000Z, 2019-0…
$ snippet.channelId                  <fct> UCUsN5ZwHx2kILm84-jPDeXw, UCUsN5…
$ snippet.title                      <fct> "Alexander Hamilton’s Salacious …
$ snippet.description                <fct> "Alexander Hamilton is mired in …
$ snippet.thumbnails.default.url     <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet.thumbnails.default.width   <int> 120, 120, 120, 120, 120, 120, 12…
$ snippet.thumbnails.default.height  <int> 90, 90, 90, 90, 90, 90, 90, 90, …
$ snippet.thumbnails.medium.url      <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet.thumbnails.medium.width    <int> 320, 320, 320, 320, 320, 320, 32…
$ snippet.thumbnails.medium.height   <int> 180, 180, 180, 180, 180, 180, 18…
$ snippet.thumbnails.high.url        <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet.thumbnails.high.width      <int> 480, 480, 480, 480, 480, 480, 48…
$ snippet.thumbnails.high.height     <int> 360, 360, 360, 360, 360, 360, 36…
$ snippet.thumbnails.standard.url    <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet.thumbnails.standard.width  <int> 640, 640, 640, 640, 640, 640, 64…
$ snippet.thumbnails.standard.height <int> 480, 480, 480, 480, 480, 480, 48…
$ snippet.thumbnails.maxres.url      <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet.thumbnails.maxres.width    <int> 1280, 1280, 1280, 1280, 1280, 12…
$ snippet.thumbnails.maxres.height   <int> 720, 720, 720, 720, 720, 720, 72…
$ snippet.channelTitle               <fct> Comedy Central, Comedy Central, …
$ snippet.playlistId                 <fct> PLD7nPL1U-R5pSwKIcVaIQrG5BnGMbHI…
$ snippet.position                   <int> 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10…
$ snippet.resourceId.kind            <fct> youtube#video, youtube#video, yo…
$ snippet.resourceId.videoId         <fct> 3yi0FNwOYiI, agsiFcRGAQo, 4iRwHL…

We can see the columns here aren’t exactly what I wanted, but I’m getting closer! I can use the contentDetails.videoId variable to get the statistics for each video (likeCount, dislikeCount, viewCount) etc.

First I put the id into a vector and call it drunk_hist_videoIds.

# Get the ids
drunk_hist_videoIds <- as.vector(DrunkHistRawSnippets$snippet.resourceId.videoId)
dplyr::glimpse(drunk_hist_videoIds)

chr [1:110] "3yi0FNwOYiI" "agsiFcRGAQo" "4iRwHLRS8Qw" "fD_zMzwa3VE" ...

Step 3) Create custom function for video stats

Now that I have the Drunk History playlist video ids in a character vector (drunk_hist_videoIds), we can create a function that extracts the statistics for each video.

# Function to scrape stats for all vids
get_all_stats <- function(id) {
  tuber::get_stats(video_id = id)
} 

Step 4) Use purrr:map_df() to get all statistics for videos

Now I can apply the function get_all_stats to the vector of video ids (drunk_hist_videoIds)

# Get stats and convert results to data frame 
DrunkHistAllStatsRaw <- purrr::map_df(.x = drunk_hist_videoIds, 
                                      .f = get_all_stats)
DrunkHistAllStatsRaw %>% dplyr::glimpse(78)

Observations: 109
Variables: 6
$ id            <chr> "3yi0FNwOYiI", "agsiFcRGAQo", "4iRwHLRS8Qw", "fD_zMzw…
$ viewCount     <chr> "374141", "152978", "182906", "110198", "106631", "15…
$ likeCount     <chr> "13935", "2951", "3738", "1985", "3875", "3241", "145…
$ dislikeCount  <chr> "127", "81", "138", "269", "59", "63", "332", "179", …
$ favoriteCount <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0"…
$ commentCount  <chr> "602", "222", "249", "240", "291", "157", "679", "537…

The purrr::map_df() function “maps” the function over all video ids in the vector and returns a data.frame we call DrunkHistAllStatsRaw. But now we notice we don’t have the name of the video.

Well, I can join the new DrunkHistAllStatsRaw back to the DrunkHistRawSnippets data.frame using the snippet.resourceId.videoId column and the id column from DrunkHistAllStatsRaw.

DrunkHistRawStatsSnips <- DrunkHistAllStatsRaw %>% 
    inner_join(x = ., 
               DrunkHistRawSnippets, 
               by = c("id" = "snippet.resourceId.videoId"))
DrunkHistRawStatsSnips %>% dplyr::glimpse(78)

Observations: 111
Variables: 33
$ id                                 <chr> "3yi0FNwOYiI", "agsiFcRGAQo", "4…
$ viewCount                          <chr> "392821", "155224", "183979", "1…
$ likeCount                          <chr> "14912", "3010", "3769", "1993",…
$ dislikeCount                       <chr> "142", "82", "140", "269", "59",…
$ favoriteCount                      <chr> "0", "0", "0", "0", "0", "0", "0…
$ commentCount                       <chr> "637", "224", "249", "240", "292…
$ .id                                <chr> "items1", "items2", "items3", "i…
$ kind                               <fct> youtube#playlistItem, youtube#pl…
$ etag                               <fct> "p4VTdlkQv3HQeTEaXgvLePAydmU/Jjk…
$ id.y                               <fct> UExEN25QTDFVLVI1cFN3S0ljVmFJUXJH…
$ snippet.publishedAt                <fct> 2019-09-26T18:34:54.000Z, 2019-0…
$ snippet.channelId                  <fct> UCUsN5ZwHx2kILm84-jPDeXw, UCUsN5…
$ snippet.title                      <fct> "Alexander Hamilton’s Salacious …
$ snippet.description                <fct> "Alexander Hamilton is mired in …
$ snippet.thumbnails.default.url     <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet.thumbnails.default.width   <int> 120, 120, 120, 120, 120, 120, 12…
$ snippet.thumbnails.default.height  <int> 90, 90, 90, 90, 90, 90, 90, 90, …
$ snippet.thumbnails.medium.url      <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet.thumbnails.medium.width    <int> 320, 320, 320, 320, 320, 320, 32…
$ snippet.thumbnails.medium.height   <int> 180, 180, 180, 180, 180, 180, 18…
$ snippet.thumbnails.high.url        <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet.thumbnails.high.width      <int> 480, 480, 480, 480, 480, 480, 48…
$ snippet.thumbnails.high.height     <int> 360, 360, 360, 360, 360, 360, 36…
$ snippet.thumbnails.standard.url    <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet.thumbnails.standard.width  <int> 640, 640, 640, 640, 640, 640, 64…
$ snippet.thumbnails.standard.height <int> 480, 480, 480, 480, 480, 480, 48…
$ snippet.thumbnails.maxres.url      <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet.thumbnails.maxres.width    <int> 1280, 1280, 1280, 1280, 1280, 12…
$ snippet.thumbnails.maxres.height   <int> 720, 720, 720, 720, 720, 720, 72…
$ snippet.channelTitle               <fct> Comedy Central, Comedy Central, …
$ snippet.playlistId                 <fct> PLD7nPL1U-R5pSwKIcVaIQrG5BnGMbHI…
$ snippet.position                   <int> 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10…
$ snippet.resourceId.kind            <fct> youtube#video, youtube#video, yo…

Beautiful! We have all the columns we originally needed (and more!), but we should also address the formatting on the column names.

Step 5) Clean variable names

The janitor package let’s us standardize the column names using clean_names() and case = "snake".

DrunkHistRawStatsSnips <- DrunkHistRawStatsSnips %>% 
    janitor::clean_names(dat = ., case = "snake") 
DrunkHistRawStatsSnips %>% glimpse(78)

Observations: 111
Variables: 33
$ id                                 <chr> "3yi0FNwOYiI", "agsiFcRGAQo", "4…
$ view_count                         <chr> "392821", "155224", "183979", "1…
$ like_count                         <chr> "14912", "3010", "3769", "1993",…
$ dislike_count                      <chr> "142", "82", "140", "269", "59",…
$ favorite_count                     <chr> "0", "0", "0", "0", "0", "0", "0…
$ comment_count                      <chr> "637", "224", "249", "240", "292…
$ id_2                               <chr> "items1", "items2", "items3", "i…
$ kind                               <fct> youtube#playlistItem, youtube#pl…
$ etag                               <fct> "p4VTdlkQv3HQeTEaXgvLePAydmU/Jjk…
$ id_y                               <fct> UExEN25QTDFVLVI1cFN3S0ljVmFJUXJH…
$ snippet_published_at               <fct> 2019-09-26T18:34:54.000Z, 2019-0…
$ snippet_channel_id                 <fct> UCUsN5ZwHx2kILm84-jPDeXw, UCUsN5…
$ snippet_title                      <fct> "Alexander Hamilton’s Salacious …
$ snippet_description                <fct> "Alexander Hamilton is mired in …
$ snippet_thumbnails_default_url     <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet_thumbnails_default_width   <int> 120, 120, 120, 120, 120, 120, 12…
$ snippet_thumbnails_default_height  <int> 90, 90, 90, 90, 90, 90, 90, 90, …
$ snippet_thumbnails_medium_url      <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet_thumbnails_medium_width    <int> 320, 320, 320, 320, 320, 320, 32…
$ snippet_thumbnails_medium_height   <int> 180, 180, 180, 180, 180, 180, 18…
$ snippet_thumbnails_high_url        <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet_thumbnails_high_width      <int> 480, 480, 480, 480, 480, 480, 48…
$ snippet_thumbnails_high_height     <int> 360, 360, 360, 360, 360, 360, 36…
$ snippet_thumbnails_standard_url    <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet_thumbnails_standard_width  <int> 640, 640, 640, 640, 640, 640, 64…
$ snippet_thumbnails_standard_height <int> 480, 480, 480, 480, 480, 480, 48…
$ snippet_thumbnails_maxres_url      <fct> https://i.ytimg.com/vi/3yi0FNwOY…
$ snippet_thumbnails_maxres_width    <int> 1280, 1280, 1280, 1280, 1280, 12…
$ snippet_thumbnails_maxres_height   <int> 720, 720, 720, 720, 720, 720, 72…
$ snippet_channel_title              <fct> Comedy Central, Comedy Central, …
$ snippet_playlist_id                <fct> PLD7nPL1U-R5pSwKIcVaIQrG5BnGMbHI…
$ snippet_position                   <int> 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10…
$ snippet_resource_id_kind           <fct> youtube#video, youtube#video, yo…

This looks much better–no more periods or capitol letters in the variable names.

Turn everything into a function

Ok–I was able to create a data.frame with the same columns as AmyRaw and KeyAndPeeleRaw, but wouldn’t it be nice if I could put the entire thing together into a custom function?

Ideally, I would just provide the url for a playlist (playlist_url), and the number of videos (video_count), and have the function return a data set with the columns I wanted. Let’s give it a try!

youtube_video_data <- function(playlist_url, video_count) {
    
    # packages -----------------------------------------------------------------
    require(stringr)
    require(tuber)
    require(purrr)
    require(dplyr)
    require(janitor)
    
    # step 1) split url into playlistId ----------------------------------------
    raw_url <- playlist_url
    
    # get playlist id
    playlist_id <- stringr::str_split(
    string = raw_url, 
    pattern = "=", 
    n = 2,
    simplify = TRUE)[ , 2]
    
    # get raw snippet df -------------------------------------------------------
    RawSnippets <- tuber::get_playlist_items(filter = 
                            c(playlist_id = playlist_id), 
                            # get snippets 
                            part = "snippet",
                            # set this to the number of videos
                                              max_results = video_count,
                                              # return a data frame
                                              simplify = TRUE)
    
    # extract the videoId ------------------------------------------------------
    snip_videoIds <- base::as.vector(RawSnippets$snippet.resourceId.videoId)
    
    # create custom stats function ---------------------------------------------
    get_all_stats <- function(id) {
        tuber::get_stats(video_id = id)
    } 
    
    # apply stats function to vector of video ids ------------------------------
    YouTubeStatsRaw <- purrr::map_df(.x = snip_videoIds, 
                  .f = get_all_stats) %>% 
        
        # join to RawSnippets data.frame ---------------------------------------
        dplyr::inner_join(x = ., 
               RawSnippets, 
               by = c("id" = "snippet.resourceId.videoId"))
    
    # clean names --------------------------------------------------------------
    YouTubeStatsRaw <- YouTubeStatsRaw %>% 
        janitor::clean_names(dat = ., case = "snake")
    
    # return df ----------------------------------------------------------------
    return(YouTubeStatsRaw)
}

Ok, now we should test our youtube_video_data() function and see if it works with a fresh playlist just to make sure there’s nothing fishy going on.

Paste this url from Funny or Die’s playlist “FOD has Tech”. There are 146 videos in this playlist, so we will specify video_count = 146.

youtube_video_data(playlist_url = "https://www.youtube.com/playlist?list=PLRcB4n4CGcy8_3l1f6G1DGQCC6Jt3JEtZ",
                   video_count = 146) %>% dplyr::glimpse(78)

Observations: 137
Variables: 33
$ id                                 <chr> "70YAFPoMCQc", "vbdosqKMJxA", "l…
$ view_count                         <chr> "200793", "3512", "1960", "6169"…
$ like_count                         <chr> "6414", "26", "17", "19", "466",…
$ dislike_count                      <chr> "152", "19", "9", "12", "35", "8…
$ favorite_count                     <chr> "0", "0", "0", "0", "0", "0", "0…
$ comment_count                      <chr> "907", NA, NA, NA, "36", "55", "…
$ id_2                               <chr> "items1", "items2", "items3", "i…
$ kind                               <fct> youtube#playlistItem, youtube#pl…
$ etag                               <fct> "p4VTdlkQv3HQeTEaXgvLePAydmU/YQv…
$ id_y                               <fct> UExSY0I0bjRDR2N5OF8zbDFmNkcxREdR…
$ snippet_published_at               <fct> 2019-06-19T14:54:07.000Z, 2019-0…
$ snippet_channel_id                 <fct> UCzS3-65Y91JhOxFiM7j6grg, UCzS3-…
$ snippet_title                      <fct> Jeff Goldblum Dishes With Regina…
$ snippet_description                <fct> "Secrets don’t make friends, but…
$ snippet_thumbnails_default_url     <fct> https://i.ytimg.com/vi/70YAFPoMC…
$ snippet_thumbnails_default_width   <int> 120, 120, 120, 120, 120, 120, 12…
$ snippet_thumbnails_default_height  <int> 90, 90, 90, 90, 90, 90, 90, 90, …
$ snippet_thumbnails_medium_url      <fct> https://i.ytimg.com/vi/70YAFPoMC…
$ snippet_thumbnails_medium_width    <int> 320, 320, 320, 320, 320, 320, 32…
$ snippet_thumbnails_medium_height   <int> 180, 180, 180, 180, 180, 180, 18…
$ snippet_thumbnails_high_url        <fct> https://i.ytimg.com/vi/70YAFPoMC…
$ snippet_thumbnails_high_width      <int> 480, 480, 480, 480, 480, 480, 48…
$ snippet_thumbnails_high_height     <int> 360, 360, 360, 360, 360, 360, 36…
$ snippet_thumbnails_standard_url    <fct> https://i.ytimg.com/vi/70YAFPoMC…
$ snippet_thumbnails_standard_width  <int> 640, 640, 640, 640, 640, 640, 64…
$ snippet_thumbnails_standard_height <int> 480, 480, 480, 480, 480, 480, 48…
$ snippet_thumbnails_maxres_url      <fct> https://i.ytimg.com/vi/70YAFPoMC…
$ snippet_thumbnails_maxres_width    <int> 1280, 1280, 1280, 1280, 1280, 12…
$ snippet_thumbnails_maxres_height   <int> 720, 720, 720, 720, 720, 720, 72…
$ snippet_channel_title              <fct> Funny Or Die, Funny Or Die, Funn…
$ snippet_playlist_id                <fct> PLRcB4n4CGcy8_3l1f6G1DGQCC6Jt3JE…
$ snippet_position                   <int> 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10…
$ snippet_resource_id_kind           <fct> youtube#video, youtube#video, yo…

Awesome! Now this totally reproducible–we can create new YouTube datasets with just a playlist url and the number of videos.

Reduce columns and export

Just to make test data look identical to the imoprted AmyRaw, KeyAndPeeleRaw .csv files, I’ll check the names and reduce the columns to only those in the original datasets.

# KeyAndPeeleRaw %>% dplyr::glimpse(78)
DrunkHistData <- DrunkHistRawStatsSnips %>% 
    dplyr::select(
       published_at = snippet_published_at,
       dislike_count,
       url = snippet_thumbnails_default_url,
       id,
       comment_count,
       title = snippet_title,
       view_count,
       like_count) 
# check
DrunkHistData %>% glimpse(78)

Observations: 111
Variables: 8
$ published_at  <fct> 2019-09-26T18:34:54.000Z, 2019-09-19T19:37:40.000Z, 2…
$ dislike_count <chr> "142", "82", "140", "269", "59", "63", "332", "179", …
$ url           <fct> https://i.ytimg.com/vi/3yi0FNwOYiI/default.jpg, https…
$ id            <chr> "3yi0FNwOYiI", "agsiFcRGAQo", "4iRwHLRS8Qw", "fD_zMzw…
$ comment_count <chr> "637", "224", "249", "240", "292", "157", "679", "537…
$ title         <fct> "Alexander Hamilton’s Salacious Sex Scandal (feat. Li…
$ view_count    <chr> "392821", "155224", "183979", "110611", "106962", "15…
$ like_count    <chr> "14912", "3010", "3769", "1993", "3892", "3248", "146…

Great! Now I can export this and start analyzing!

# timestamp
readr::write_csv(base::as.data.frame(DrunkHistData), 
    path = base::paste0(
        "data/", 
        base::noquote(lubridate::today()), 
        "-DrunkHistData.csv"
))
fs::dir_tree("data")

data
├── 2019-09-30-DrunkHistData.csv
├── 2019-09-30-amy.csv
├── 2019-09-30-kap.csv
└── README.md
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