Process: I created a MongoDB cluster for free on Atlas account, then tried to migrate my movierating database to the cluster. Because my IP is whitelisted, only my IP will be allowed to access my Mongodb cluster. So, from a reproducibility standpoint, I may have to list another IP address if a connection should be allowed into my cloud account. Once done, I then tried to use some query through Mongolite user manual here https://jeroen.github.io/mongolite/
con <- DBI::dbConnect(RMySQL::MySQL(),
host = "localhost",
username = "cunyuser",
dbname="dbmovierating",
password = "bar"
)
dbListTables(con)## [1] "movieinfo" "personinfo" "personrating" "ratingdef"
## [5] "table2" "testtable"movieinfo_df = dbSendQuery(con, "select * from movieinfo")
dfmovieinfo = fetch(movieinfo_df, n=-1)
head(dfmovieinfo)## movieinfo_id Title MPAARating
## 1 1 Aquaman (2018) PG-13
## 2 2 Alita: Battle Angel (2019) PG-13
## 3 3 Wonder Woman (2017) PG-13
## 4 4 Wonder Woman (2008) PG-13
## 5 5 Wonder Woman: Bloodlines (2019) PG-13
## 6 6 Wonder Woman: Director's Cut (2017) R
## Rating
## 1 Parental Guidance Suggested
## 2 Parental Strongly Cautioned
## 3 General Audiences
## 4 Parental Strongly Cautioned
## 5 General Audiences
## 6 Restricted
## RATINGLONGDESC
## 1 Some Material may be inappropriate for children under 13
## 2 Some Material may be inappropriate for children under 13
## 3 Some Material may be inappropriate for children under 13
## 4 Some Material may be inappropriate for children under 13
## 5 Some Material may be inappropriate for children under 13
## 6 Under 17 Requires Accompanying Parent or Adult Guardian
## REASON
## 1 Rated PG-13 for sequences of sci-fi violence and action, and for some language.
## 2 Rated PG-13 for sequences of sci-fi violence and action, and for some language.
## 3 Rated PG-13 for sequences of violence and action, and some suggestive content.
## 4 Rated PG-13 for violence throughout and some suggestive material.
## 5 Rated PG-13 for sequences of fantasy action and violence, and some bloody images.
## 6 Rated R for some violence.
## DISTRIBUTOR
## 1 Warner Bros. Pictures
## 2 Twentieth Century Fox Film Corp.
## 3 Warner Bros. Pictures
## 4 Warner Home Video
## 5 Warner Bros. Home Entertainment
## 6 Warner Home Entertainment, Inc.## [1] 26prsninfo_df = dbSendQuery(con, "select * from personinfo")
dfprsninfo = fetch(prsninfo_df , n=-1)
head(dfprsninfo)## personinfo_id FirstName Age Sex
## 1 1 Peter 7 M
## 2 2 Liam 4 M
## 3 3 Golan 42 M
## 4 4 Nathaniel 62 M
## 5 5 Simba 3 M
## 6 6 Max 17 M## [1] 15prsnrating_df = dbSendQuery(con, "select * from personrating")
dfprsnrating = fetch(prsnrating_df, n=-1)
head(dfprsnrating)## personrating_id Title RaterName Rating
## 1 1 Aquaman (2018) Golan 4
## 2 2 Alita: Battle Angel (2019) Golan 0
## 3 3 Wonder Woman (2017) Golan 4
## 4 4 Avengers: Endgame (2019) Golan 0
## 5 5 Avengers: Infinity War (2018) Golan 3
## 6 6 Toy Story 4 (2019) Golan 5## [1] 98ratingdef_df = dbSendQuery(con, "select * from ratingdef")
dfratingdef = fetch(ratingdef_df, n=-1)
head(dfratingdef)## ratingdef_id
## 1 1
## 2 2
## 3 3
## 4 4
## 5 5
## Ratingdef
## 1 Rated G: General audiences – All ages admitted
## 2 Rated PG: Parental guidance suggested – Some material may not be suitable for children.
## 3 Rated PG-13: Parents strongly cautioned – Some material may be inappropriate for children under 13.
## 4 Rated R: Restricted – Under 17 requires accompanying parent or adult guardian.
## 5 Rated NC-17: No one 17 and under admitted.## [1] 5## Warning: Closing open result sets## [1] TRUE#make connection object that specifies new database and collection (dataset)
url_path = 'mongodb+srv://BBMongoUser:cunybar@clusterbb0-ya3fv.azure.mongodb.net/test?retryWrites=true&w=majority'
mongocon <- mongo(collection = "listingsAndReviews", db = "sample_airbnb",
url = url_path,
verbose = TRUE)
str(mongocon)## Classes 'mongo', 'jeroen', 'environment' <environment: 0x0000000018537880>## <Mongo collection> 'listingsAndReviews'
## $aggregate(pipeline = "{}", options = "{\"allowDiskUse\":true}", handler = NULL, pagesize = 1000, iterate = FALSE)
## $count(query = "{}")
## $disconnect(gc = TRUE)
## $distinct(key, query = "{}")
## $drop()
## $export(con = stdout(), bson = FALSE, query = "{}", fields = "{}", sort = "{\"_id\":1}")
## $find(query = "{}", fields = "{\"_id\":0}", sort = "{}", skip = 0, limit = 0, handler = NULL, pagesize = 1000)
## $import(con, bson = FALSE)
## $index(add = NULL, remove = NULL)
## $info()
## $insert(data, pagesize = 1000, stop_on_error = TRUE, ...)
## $iterate(query = "{}", fields = "{\"_id\":0}", sort = "{}", skip = 0, limit = 0)
## $mapreduce(map, reduce, query = "{}", sort = "{}", limit = 0, out = NULL, scope = NULL)
## $remove(query, just_one = FALSE)
## $rename(name, db = NULL)
## $replace(query, update = "{}", upsert = FALSE)
## $run(command = "{\"ping\": 1}", simplify = TRUE)
## $update(query, update = "{\"$set\":{}}", filters = NULL, upsert = FALSE, multiple = FALSE)## [1] 5555#data("dfmovieinfo")
moviecon <- mongo(collection = "dfmovieinfo", # Creating collection
db = "sample_dbmovierating_R", # Creating DataBase
url = url_path,
verbose = TRUE)
# insert code
moviecon$insert(dfmovieinfo)##
Complete! Processed total of 26 rows.## List of 5
## $ nInserted : num 26
## $ nMatched : num 0
## $ nRemoved : num 0
## $ nUpserted : num 0
## $ writeErrors: list()##
Found 5 records...
Imported 5 records. Simplifying into dataframe...## movieinfo_id Title MPAARating
## 1 1 Aquaman (2018) PG-13
## 2 2 Alita: Battle Angel (2019) PG-13
## 3 3 Wonder Woman (2017) PG-13
## 4 4 Wonder Woman (2008) PG-13
## 5 5 Wonder Woman: Bloodlines (2019) PG-13
## Rating
## 1 Parental Guidance Suggested
## 2 Parental Strongly Cautioned
## 3 General Audiences
## 4 Parental Strongly Cautioned
## 5 General Audiences
## RATINGLONGDESC
## 1 Some Material may be inappropriate for children under 13
## 2 Some Material may be inappropriate for children under 13
## 3 Some Material may be inappropriate for children under 13
## 4 Some Material may be inappropriate for children under 13
## 5 Some Material may be inappropriate for children under 13
## REASON
## 1 Rated PG-13 for sequences of sci-fi violence and action, and for some language.
## 2 Rated PG-13 for sequences of sci-fi violence and action, and for some language.
## 3 Rated PG-13 for sequences of violence and action, and some suggestive content.
## 4 Rated PG-13 for violence throughout and some suggestive material.
## 5 Rated PG-13 for sequences of fantasy action and violence, and some bloody images.
## DISTRIBUTOR
## 1 Warner Bros. Pictures
## 2 Twentieth Century Fox Film Corp.
## 3 Warner Bros. Pictures
## 4 Warner Home Video
## 5 Warner Bros. Home Entertainment##
Complete! Processed total of 98 rows.## List of 5
## $ nInserted : num 98
## $ nMatched : num 0
## $ nRemoved : num 0
## $ nUpserted : num 0
## $ writeErrors: list()##
Found 5 records...
Imported 5 records. Simplifying into dataframe...## movieinfo_id Title MPAARating
## 1 1 Aquaman (2018) PG-13
## 2 2 Alita: Battle Angel (2019) PG-13
## 3 3 Wonder Woman (2017) PG-13
## 4 4 Wonder Woman (2008) PG-13
## 5 5 Wonder Woman: Bloodlines (2019) PG-13
## Rating
## 1 Parental Guidance Suggested
## 2 Parental Strongly Cautioned
## 3 General Audiences
## 4 Parental Strongly Cautioned
## 5 General Audiences
## RATINGLONGDESC
## 1 Some Material may be inappropriate for children under 13
## 2 Some Material may be inappropriate for children under 13
## 3 Some Material may be inappropriate for children under 13
## 4 Some Material may be inappropriate for children under 13
## 5 Some Material may be inappropriate for children under 13
## REASON
## 1 Rated PG-13 for sequences of sci-fi violence and action, and for some language.
## 2 Rated PG-13 for sequences of sci-fi violence and action, and for some language.
## 3 Rated PG-13 for sequences of violence and action, and some suggestive content.
## 4 Rated PG-13 for violence throughout and some suggestive material.
## 5 Rated PG-13 for sequences of fantasy action and violence, and some bloody images.
## DISTRIBUTOR
## 1 Warner Bros. Pictures
## 2 Twentieth Century Fox Film Corp.
## 3 Warner Bros. Pictures
## 4 Warner Home Video
## 5 Warner Bros. Home Entertainment## [1] 620## <Mongo collection> 'dfmovieinfo'
## $aggregate(pipeline = "{}", options = "{\"allowDiskUse\":true}", handler = NULL, pagesize = 1000, iterate = FALSE)
## $count(query = "{}")
## $disconnect(gc = TRUE)
## $distinct(key, query = "{}")
## $drop()
## $export(con = stdout(), bson = FALSE, query = "{}", fields = "{}", sort = "{\"_id\":1}")
## $find(query = "{}", fields = "{\"_id\":0}", sort = "{}", skip = 0, limit = 0, handler = NULL, pagesize = 1000)
## $import(con, bson = FALSE)
## $index(add = NULL, remove = NULL)
## $info()
## $insert(data, pagesize = 1000, stop_on_error = TRUE, ...)
## $iterate(query = "{}", fields = "{\"_id\":0}", sort = "{}", skip = 0, limit = 0)
## $mapreduce(map, reduce, query = "{}", sort = "{}", limit = 0, out = NULL, scope = NULL)
## $remove(query, just_one = FALSE)
## $rename(name, db = NULL)
## $replace(query, update = "{}", upsert = FALSE)
## $run(command = "{\"ping\": 1}", simplify = TRUE)
## $update(query, update = "{\"$set\":{}}", filters = NULL, upsert = FALSE, multiple = FALSE)Summary: Different between sql and no sql
##
Found 5 records...
Imported 5 records. Simplifying into dataframe...## personrating_id Title RaterName Rating
## 1 28 John Wick (2014) Nathaniel 4.5
## 2 28 John Wick (2014) Nathaniel 0.0
## 3 28 John Wick (2014) Nathaniel 0.0
## 4 28 John Wick (2014) Nathaniel 0.0
## 5 28 John Wick (2014) Nathaniel 0.0## List of 3
## $ modifiedCount: int 0
## $ matchedCount : int 1
## $ upsertedCount: int 0##
Found 5 records...
Imported 5 records. Simplifying into dataframe...## personrating_id Title RaterName Rating
## 1 28 John Wick (2014) Nathaniel 4.5
## 2 28 John Wick (2014) Nathaniel 0.0
## 3 28 John Wick (2014) Nathaniel 0.0
## 4 28 John Wick (2014) Nathaniel 0.0
## 5 28 John Wick (2014) Nathaniel 0.0#Aggregate
stats <- moviecon$aggregate(
'[{"$group":{"_id":"$RaterName", "average":{"$avg":"$Rating"}}}]',
options = '{"allowDiskUse":true}'
)##
Found 15 records...
Imported 15 records. Simplifying into dataframe...## _id average
## 1 Simba 3.428571
## 2 Max 2.571429
## 3 Marina 2.285714
## 4 Olivia 3.142857
## 5 Togo 4.571429
## 6 Liam 1.142857
## 7 Sumita 2.428571
## 8 Nathaniel 2.557143
## 9 Golan 2.857143
## 10 <NA> NA
## 11 Gamora 4.571429
## 12 Jackson 3.571429
## 13 John 4.428571
## 14 Peter 2.428571
## 15 Yong Lee 4.142857#Aggregate
stats1 <- moviecon$aggregate(
'[{"$match":{"Title":"John Wick (2014)"}},{"$group":{"_id":"$Title", "average":{"$avg":"$Rating"}}}]',
options = '{"allowDiskUse":true}'
)##
Found 1 records...
Imported 1 records. Simplifying into dataframe...## _id average
## 1 John Wick (2014) 2.635714stats2 <- moviecon$aggregate(
'[{"$match":{"Title":"John Wick (2014)"}}]',options = '{"allowDiskUse":true}'
)##
Found 75 records...
Imported 75 records. Simplifying into dataframe...## _id movieinfo_id Title MPAARating
## 1 5ddad233ba27000083001a3a 24 John Wick (2014) R
## 2 5ddad2e0ba27000083001a43 NA John Wick (2014) <NA>
## 3 5ddad2e0ba27000083001a4a NA John Wick (2014) <NA>
## 4 5ddad2e0ba27000083001a51 NA John Wick (2014) <NA>
## 5 5ddad2e0ba27000083001a58 NA John Wick (2014) <NA>
## 6 5ddad2e0ba27000083001a5f NA John Wick (2014) <NA>
## 7 5ddad2e0ba27000083001a66 NA John Wick (2014) <NA>
## 8 5ddad2e0ba27000083001a6d NA John Wick (2014) <NA>
## 9 5ddad2e0ba27000083001a74 NA John Wick (2014) <NA>
## 10 5ddad2e0ba27000083001a7b NA John Wick (2014) <NA>
## 11 5ddad2e0ba27000083001a82 NA John Wick (2014) <NA>
## 12 5ddad2e0ba27000083001a89 NA John Wick (2014) <NA>
## 13 5ddad2e0ba27000083001a90 NA John Wick (2014) <NA>
## 14 5ddad2e0ba27000083001a97 NA John Wick (2014) <NA>
## 15 5ddad2e0ba27000083001a9e NA John Wick (2014) <NA>
## 16 5ddb09c0ba27000083001ab6 24 John Wick (2014) R
## 17 5ddb09c1ba27000083001abf NA John Wick (2014) <NA>
## 18 5ddb09c1ba27000083001ac6 NA John Wick (2014) <NA>
## 19 5ddb09c1ba27000083001acd NA John Wick (2014) <NA>
## 20 5ddb09c1ba27000083001ad4 NA John Wick (2014) <NA>
## 21 5ddb09c1ba27000083001adb NA John Wick (2014) <NA>
## 22 5ddb09c1ba27000083001ae2 NA John Wick (2014) <NA>
## 23 5ddb09c1ba27000083001ae9 NA John Wick (2014) <NA>
## 24 5ddb09c1ba27000083001af0 NA John Wick (2014) <NA>
## 25 5ddb09c1ba27000083001af7 NA John Wick (2014) <NA>
## 26 5ddb09c1ba27000083001afe NA John Wick (2014) <NA>
## 27 5ddb09c1ba27000083001b05 NA John Wick (2014) <NA>
## 28 5ddb09c1ba27000083001b0c NA John Wick (2014) <NA>
## 29 5ddb09c1ba27000083001b13 NA John Wick (2014) <NA>
## 30 5ddb09c1ba27000083001b1a NA John Wick (2014) <NA>
## 31 5ddb0aa7d31600005b007369 24 John Wick (2014) R
## 32 5ddb0aa7d31600005b007372 NA John Wick (2014) <NA>
## 33 5ddb0aa7d31600005b007379 NA John Wick (2014) <NA>
## 34 5ddb0aa7d31600005b007380 NA John Wick (2014) <NA>
## 35 5ddb0aa7d31600005b007387 NA John Wick (2014) <NA>
## 36 5ddb0aa7d31600005b00738e NA John Wick (2014) <NA>
## 37 5ddb0aa7d31600005b007395 NA John Wick (2014) <NA>
## 38 5ddb0aa7d31600005b00739c NA John Wick (2014) <NA>
## 39 5ddb0aa7d31600005b0073a3 NA John Wick (2014) <NA>
## 40 5ddb0aa7d31600005b0073aa NA John Wick (2014) <NA>
## 41 5ddb0aa7d31600005b0073b1 NA John Wick (2014) <NA>
## 42 5ddb0aa7d31600005b0073b8 NA John Wick (2014) <NA>
## 43 5ddb0aa7d31600005b0073bf NA John Wick (2014) <NA>
## 44 5ddb0aa7d31600005b0073c6 NA John Wick (2014) <NA>
## 45 5ddb0aa7d31600005b0073cd NA John Wick (2014) <NA>
## 46 5ddb23a52c2f0000cc005a79 24 John Wick (2014) R
## 47 5ddb23a62c2f0000cc005a82 NA John Wick (2014) <NA>
## 48 5ddb23a62c2f0000cc005a89 NA John Wick (2014) <NA>
## 49 5ddb23a62c2f0000cc005a90 NA John Wick (2014) <NA>
## 50 5ddb23a62c2f0000cc005a97 NA John Wick (2014) <NA>
## 51 5ddb23a62c2f0000cc005a9e NA John Wick (2014) <NA>
## 52 5ddb23a62c2f0000cc005aa5 NA John Wick (2014) <NA>
## 53 5ddb23a62c2f0000cc005aac NA John Wick (2014) <NA>
## 54 5ddb23a62c2f0000cc005ab3 NA John Wick (2014) <NA>
## 55 5ddb23a62c2f0000cc005aba NA John Wick (2014) <NA>
## 56 5ddb23a62c2f0000cc005ac1 NA John Wick (2014) <NA>
## 57 5ddb23a62c2f0000cc005ac8 NA John Wick (2014) <NA>
## 58 5ddb23a62c2f0000cc005acf NA John Wick (2014) <NA>
## 59 5ddb23a62c2f0000cc005ad6 NA John Wick (2014) <NA>
## 60 5ddb23a62c2f0000cc005add NA John Wick (2014) <NA>
## 61 5ddb23e9f56c00002c0027b9 24 John Wick (2014) R
## 62 5ddb23e9f56c00002c0027c2 NA John Wick (2014) <NA>
## 63 5ddb23e9f56c00002c0027c9 NA John Wick (2014) <NA>
## 64 5ddb23e9f56c00002c0027d0 NA John Wick (2014) <NA>
## 65 5ddb23e9f56c00002c0027d7 NA John Wick (2014) <NA>
## 66 5ddb23e9f56c00002c0027de NA John Wick (2014) <NA>
## 67 5ddb23e9f56c00002c0027e5 NA John Wick (2014) <NA>
## 68 5ddb23e9f56c00002c0027ec NA John Wick (2014) <NA>
## 69 5ddb23e9f56c00002c0027f3 NA John Wick (2014) <NA>
## 70 5ddb23e9f56c00002c0027fa NA John Wick (2014) <NA>
## 71 5ddb23e9f56c00002c002801 NA John Wick (2014) <NA>
## 72 5ddb23e9f56c00002c002808 NA John Wick (2014) <NA>
## 73 5ddb23e9f56c00002c00280f NA John Wick (2014) <NA>
## 74 5ddb23e9f56c00002c002816 NA John Wick (2014) <NA>
## 75 5ddb23e9f56c00002c00281d NA John Wick (2014) <NA>
## RATINGLONGDESC
## 1 Rated R for strong and bloody violence throughout, language and brief drug use.
## 2 <NA>
## 3 <NA>
## 4 <NA>
## 5 <NA>
## 6 <NA>
## 7 <NA>
## 8 <NA>
## 9 <NA>
## 10 <NA>
## 11 <NA>
## 12 <NA>
## 13 <NA>
## 14 <NA>
## 15 <NA>
## 16 Rated R for strong and bloody violence throughout, language and brief drug use.
## 17 <NA>
## 18 <NA>
## 19 <NA>
## 20 <NA>
## 21 <NA>
## 22 <NA>
## 23 <NA>
## 24 <NA>
## 25 <NA>
## 26 <NA>
## 27 <NA>
## 28 <NA>
## 29 <NA>
## 30 <NA>
## 31 Rated R for strong and bloody violence throughout, language and brief drug use.
## 32 <NA>
## 33 <NA>
## 34 <NA>
## 35 <NA>
## 36 <NA>
## 37 <NA>
## 38 <NA>
## 39 <NA>
## 40 <NA>
## 41 <NA>
## 42 <NA>
## 43 <NA>
## 44 <NA>
## 45 <NA>
## 46 Rated R for strong and bloody violence throughout, language and brief drug use.
## 47 <NA>
## 48 <NA>
## 49 <NA>
## 50 <NA>
## 51 <NA>
## 52 <NA>
## 53 <NA>
## 54 <NA>
## 55 <NA>
## 56 <NA>
## 57 <NA>
## 58 <NA>
## 59 <NA>
## 60 <NA>
## 61 Rated R for strong and bloody violence throughout, language and brief drug use.
## 62 <NA>
## 63 <NA>
## 64 <NA>
## 65 <NA>
## 66 <NA>
## 67 <NA>
## 68 <NA>
## 69 <NA>
## 70 <NA>
## 71 <NA>
## 72 <NA>
## 73 <NA>
## 74 <NA>
## 75 <NA>
## DISTRIBUTOR personrating_id RaterName Rating
## 1 Summit Entertainment NA <NA> NA
## 2 <NA> 7 Golan 4.0
## 3 <NA> 14 Peter 0.0
## 4 <NA> 21 Liam 0.0
## 5 <NA> 28 Nathaniel 4.5
## 6 <NA> 35 Gamora 5.0
## 7 <NA> 42 Sumita 1.0
## 8 <NA> 49 Jackson 0.0
## 9 <NA> 56 John 5.0
## 10 <NA> 63 Yong Lee 5.0
## 11 <NA> 70 Togo 5.0
## 12 <NA> 77 Olivia 2.0
## 13 <NA> 84 Marina 4.0
## 14 <NA> 91 Max 1.0
## 15 <NA> 98 Simba 4.0
## 16 Summit Entertainment NA <NA> NA
## 17 <NA> 7 Golan 4.0
## 18 <NA> 14 Peter 0.0
## 19 <NA> 21 Liam 0.0
## 20 <NA> 28 Nathaniel 0.0
## 21 <NA> 35 Gamora 5.0
## 22 <NA> 42 Sumita 1.0
## 23 <NA> 49 Jackson 0.0
## 24 <NA> 56 John 5.0
## 25 <NA> 63 Yong Lee 5.0
## 26 <NA> 70 Togo 5.0
## 27 <NA> 77 Olivia 2.0
## 28 <NA> 84 Marina 4.0
## 29 <NA> 91 Max 1.0
## 30 <NA> 98 Simba 4.0
## 31 Summit Entertainment NA <NA> NA
## 32 <NA> 7 Golan 4.0
## 33 <NA> 14 Peter 0.0
## 34 <NA> 21 Liam 0.0
## 35 <NA> 28 Nathaniel 0.0
## 36 <NA> 35 Gamora 5.0
## 37 <NA> 42 Sumita 1.0
## 38 <NA> 49 Jackson 0.0
## 39 <NA> 56 John 5.0
## 40 <NA> 63 Yong Lee 5.0
## 41 <NA> 70 Togo 5.0
## 42 <NA> 77 Olivia 2.0
## 43 <NA> 84 Marina 4.0
## 44 <NA> 91 Max 1.0
## 45 <NA> 98 Simba 4.0
## 46 Summit Entertainment NA <NA> NA
## 47 <NA> 7 Golan 4.0
## 48 <NA> 14 Peter 0.0
## 49 <NA> 21 Liam 0.0
## 50 <NA> 28 Nathaniel 0.0
## 51 <NA> 35 Gamora 5.0
## 52 <NA> 42 Sumita 1.0
## 53 <NA> 49 Jackson 0.0
## 54 <NA> 56 John 5.0
## 55 <NA> 63 Yong Lee 5.0
## 56 <NA> 70 Togo 5.0
## 57 <NA> 77 Olivia 2.0
## 58 <NA> 84 Marina 4.0
## 59 <NA> 91 Max 1.0
## 60 <NA> 98 Simba 4.0
## 61 Summit Entertainment NA <NA> NA
## 62 <NA> 7 Golan 4.0
## 63 <NA> 14 Peter 0.0
## 64 <NA> 21 Liam 0.0
## 65 <NA> 28 Nathaniel 0.0
## 66 <NA> 35 Gamora 5.0
## 67 <NA> 42 Sumita 1.0
## 68 <NA> 49 Jackson 0.0
## 69 <NA> 56 John 5.0
## 70 <NA> 63 Yong Lee 5.0
## 71 <NA> 70 Togo 5.0
## 72 <NA> 77 Olivia 2.0
## 73 <NA> 84 Marina 4.0
## 74 <NA> 91 Max 1.0
## 75 <NA> 98 Simba 4.0