Delete elements with specific field from list (r language) - r

I have a vector of lists in it. Every list contain field category
I need delete all lists with fields category == resource.
I tried
for(i in 1:length(myList)){
if(myList[[as.numeric(i)]]$data$category == "resource"){
myList[[as.numeric(i)]]<-NULL
}
}
Is it correct?
> dput(myList[1:2])
list(structure(list(data = structure(list(device = "iPad2,4",
os_version = "ios 7.1.2", connection_type = "wifi", category = "user",
platform = "ios", session_num = 2, ios_idfv = "E12AA218-4061-4BA1-AFA3-47FEE1511C2E",
client_ts = 1454926346, sdk_version = "unity 2.4.3", limited_ad_tracking = TRUE,
user_id = "436E8588-B2FA-411A-896C-5757E7A2A377", manufacturer = "apple",
jailbroken = TRUE, ios_idfa = "436E8588-B2FA-411A-896C-5757E7A2A377",
build = "1.0", session_id = "558910f2-7c2c-4280-84fc-2fef1a50d291",
v = 2, engine_version = "unity 4.6.9"), .Names = c("device",
"os_version", "connection_type", "category", "platform", "session_num",
"ios_idfv", "client_ts", "sdk_version", "limited_ad_tracking",
"user_id", "manufacturer", "jailbroken", "ios_idfa", "build",
"session_id", "v", "engine_version")), first_in_batch = TRUE,
country_code = "RO", arrival_ts = 1454926344, game_id = 24540,
ip = "93.168.249.0"), .Names = c("data", "first_in_batch",
"country_code", "arrival_ts", "game_id", "ip")), structure(list(
data = structure(list(os_version = "ios 9.2.1", engine_version = "unity 4.6.9",
category = "user", v = 2, ios_idfa = "F06962FE-FCE5-475F-8CC2-83FF1F89E573",
sdk_version = "unity 2.4.3", user_id = "F06962FE-FCE5-475F-8CC2-83FF1F89E573",
session_num = 2, platform = "ios", connection_type = "wifi",
manufacturer = "apple", client_ts = 1454925528, limited_ad_tracking = TRUE,
session_id = "3ab1fbbb-5103-4ad8-bf56-94f70fea94a7",
device = "iPad4,1", ios_idfv = "2C940E82-B074-4A15-B9A7-A5983759042F",
build = "1.0"), .Names = c("os_version", "engine_version",
"category", "v", "ios_idfa", "sdk_version", "user_id", "session_num",
"platform", "connection_type", "manufacturer", "client_ts",
"limited_ad_tracking", "session_id", "device", "ios_idfv",
"build")), first_in_batch = TRUE, country_code = "AU", arrival_ts = 1454925528,
game_id = 24540, ip = "110.175.52.0"), .Names = c("data",
"first_in_batch", "country_code", "arrival_ts", "game_id", "ip"
)))


You could use rlist package :
library(rlist)
filtered_list <- list.exclude(myList, data$category == "ressource")


We could use Filter from base R
Filter(function(x) x$data$category!="resource", myList)

Related

How to loop dataframe in R

I want to get data from IMF.However the API data is limited
Therefor I get the data by continent.
How to loop the dateframe? (The data can get from "Before loop part",load data from api)
The reference cannot work.https://stackoverflow.com/questions/25284539/loop-over-a-string-variable-in-r
Before the loop
library(imfr)
library(countrycode)
data(codelist)
country_set <- codelist
country_set<- country_set %>%
select(country.name.en , iso2c, iso3c, imf, continent, region) %>% filter(!is.na(imf) & !is.na(iso2c))
africa_iso2<- country_set$iso2c[country_set$continent=="Africa"]
asia_iso2<- country_set$iso2c[country_set$continent=="Asia"]
americas_iso2<- country_set$iso2c[country_set$continent=="Americas"]
europe_iso2<- country_set$iso2c[country_set$continent=="Europe"]
oceania_iso2<- country_set$iso2c[country_set$continent=="Oceania"]
loop part
continent <- c("africa", "asia", "americas","europe","oceania")
for(i in 1:length(continent)){
var <- paste0("gdp_nsa_xdc_", continent[i])
var1 <- paste0(continent[i],"_iso2")
[[var]]<- imf_data(database_id = "IFS" , indicator = c("NGDP_NSA_XDC"),country =[[var1]],start = 2010, end = 2022,return_raw = TRUE)
[[var]]<- [[var]]$CompactData$DataSet$Series
}
data sample is
list(CompactData = list(`#xmlns:xsi` = "http://www.w3.org/2001/XMLSchema-instance",
`#xmlns:xsd` = "http://www.w3.org/2001/XMLSchema", `#xsi:schemaLocation` = "http://www.SDMX.org/resources/SDMXML/schemas/v2_0/message https://registry.sdmx.org/schemas/v2_0/SDMXMessage.xsd http://dataservices.imf.org/compact/IFS http://dataservices.imf.org/compact/IFS.xsd",
`#xmlns` = "http://www.SDMX.org/resources/SDMXML/schemas/v2_0/message",
Header = list(ID = "18e0aeae-09ec-4dfe-ab72-60aa16aaea84",
Test = "false", Prepared = "2022-10-19T12:02:28", Sender = list(
`#id` = "1C0", Name = list(`#xml:lang` = "en", `#text` = "IMF"),
Contact = list(URI = "http://www.imf.org", Telephone = "+ 1 (202) 623-6220")),
Receiver = list(`#id` = "ZZZ"), DataSetID = "IFS"), DataSet = list(
`#xmlns` = "http://dataservices.imf.org/compact/IFS",
Series = list(`#FREQ` = "Q", `#REF_AREA` = "US", `#INDICATOR` = "NGDP_NSA_XDC",
`#UNIT_MULT` = "6", `#TIME_FORMAT` = "P3M", Obs = structure(list(
`#TIME_PERIOD` = c("2020-Q1", "2020-Q2", "2020-Q3",
"2020-Q4", "2021-Q1", "2021-Q2", "2021-Q3", "2021-Q4",
"2022-Q1", "2022-Q2"), `#OBS_VALUE` = c("5254152",
"4930197", "5349433", "5539370", "5444406", "5784816",
"5883177", "6203369", "6010733", "6352982")), class = "data.frame", row.names = c(NA,
10L))))))

I suggest you create a list first, to which you will assign the value you want your loop to create. The following code creates a named list, and then at the end of the loop, assigns the value of each iteration to that named list:
continent <-
sapply(c("africa", "asia", "americas","europe","oceania"),
c, simplify = FALSE, USE.NAMES = TRUE)
for(i in seq_len(length(continent))) {
var <- paste0("gdp_nsa_xdc_", continent[i])
var1 <- get(paste0(continent[i],"_iso2"))
var <- imf_data(database_id = "IFS" , indicator = c("NGDP_NSA_XDC"),
country = var1, start = 2010, end = 2022,
return_raw = TRUE)
continent[[i]] <- var$CompactData$DataSet$Series
}
I don't necessarily understand the double brackets around [[var]]. Let me know if my answer does not correspond to what you were looking for!

We could use assign to create objects in the global env
for(i in 1:length(continent)){
var <- paste0("gdp_nsa_xdc_", continent[i])
var1 <- paste0(continent[i],"_iso2")
assign(var, imf_data(database_id = "IFS" , indicator = c("NGDP_NSA_XDC"),country =[[var1]],start = 2010, end = 2022,
return_raw = TRUE))
assign(var, get(var)$CompactData$DataSet$Series)
}

flattern nested list with uneven column numbers into data frame in R

I face a challenge of binding a nested list into a dataframe for processing.
Edit: here below is the example of original nested data before I tried to flat them.
list(list(list(url = "https://lda.senate.gov/api/v1/filings/5e4bbd96-db94-4ea3-a310-7a7fb1e93fff/",
filing_uuid = "5e4bbd96-db94-4ea3-a310-7a7fb1e93fff", filing_type = "Q1",
filing_type_display = "1st Quarter - Report", filing_year = 2021L,
filing_period = "first_quarter", filing_period_display = "1st Quarter (Jan 1 - Mar 31)",
filing_document_url = "https://lda.senate.gov/filings/public/filing/5e4bbd96-db94-4ea3-a310-7a7fb1e93fff/print/",
filing_document_content_type = "text/html", income = "15000.00",
expenses = NULL, expenses_method = NULL, expenses_method_display = NULL,
posted_by_name = "Christian Smith", dt_posted = "2021-04-30T10:20:59.217000-04:00",
termination_date = NULL, registrant = list(id = 8214L, url = "https://lda.senate.gov/api/v1/registrants/8214/",
house_registrant_id = 31113L, name = "CAPSTONE NATIONAL PARTNERS",
description = "public affairs", address_1 = "501 Capitol Court NE",
address_2 = "Suite 100", address_3 = NULL, address_4 = NULL,
city = "Washington", state = "DC", state_display = "District of Columbia",
zip = "20002", country = "US", country_display = "United States of America",
ppb_country = "US", ppb_country_display = "United States of America",
contact_name = "", contact_telephone = "", dt_updated = "2022-01-13T14:47:31.828778-05:00"),
client = list(id = 111342L, url = "https://lda.senate.gov/api/v1/clients/111342/",
client_id = 303L, name = "OSHKOSH CORPORATION", general_description = "manufacturing",
client_government_entity = FALSE, client_self_select = NULL,
state = "WI", state_display = "Wisconsin", country = "US",
country_display = "United States of America", ppb_state = "WI",
ppb_state_display = "Wisconsin", ppb_country = "US",
ppb_country_display = "United States of America", effective_date = "2016-04-01"),
lobbying_activities = list(list(general_issue_code = "BUD",
general_issue_code_display = "Budget/Appropriations",
description = "FY22 Appropriations", foreign_entity_issues = "",
lobbyists = list(list(lobbyist = list(id = 63767L, prefix = NULL,
prefix_display = NULL, first_name = "WILLIAM", nickname = NULL,
middle_name = NULL, last_name = "STONE", suffix = NULL,
suffix_display = NULL), covered_position = "Chief of Staff, Dave Obey: House Appropriations Committee",
new = FALSE)), government_entities = list(list(id = 2L,
name = "HOUSE OF REPRESENTATIVES"), list(id = 1L,
name = "SENATE")))), conviction_disclosures = list(),
foreign_entities = list(), affiliated_organizations = list())),
list(list(url = "https://lda.senate.gov/api/v1/filings/177b995a-3be2-4127-b962-795e76974617/",
filing_uuid = "177b995a-3be2-4127-b962-795e76974617",
filing_type = "Q1", filing_type_display = "1st Quarter - Report",
filing_year = 2021L, filing_period = "first_quarter",
filing_period_display = "1st Quarter (Jan 1 - Mar 31)",
filing_document_url = "https://lda.senate.gov/filings/public/filing/177b995a-3be2-4127-b962-795e76974617/print/",
filing_document_content_type = "text/html", income = "22500.00",
expenses = NULL, expenses_method = NULL, expenses_method_display = NULL,
posted_by_name = "Doyce Boesch", dt_posted = "2021-04-30T11:22:12.233000-04:00",
termination_date = NULL, registrant = list(id = 400677020L,
url = "https://lda.senate.gov/api/v1/registrants/400677020/",
house_registrant_id = NULL, name = "MR. DOYCE BOESCH",
description = "Government Relations", address_1 = "4515 W Street NW",
address_2 = NULL, address_3 = NULL, address_4 = NULL,
city = "Washington", state = "DC", state_display = "District of Columbia",
zip = "20007", country = "US", country_display = "United States of America",
ppb_country = "US", ppb_country_display = "United States of America",
contact_name = "DOYCE BOESCH", contact_telephone = "+1 202-731-9995",
dt_updated = "2022-01-13T14:59:12.412096-05:00"),
client = list(id = 194057L, url = "https://lda.senate.gov/api/v1/clients/194057/",
client_id = 75L, name = "INVESTMENT COMPANY INSTITUTE",
general_description = "Stock Market and Financial Services",
client_government_entity = FALSE, client_self_select = FALSE,
state = "DC", state_display = "District of Columbia",
country = "US", country_display = "United States of America",
ppb_state = NULL, ppb_state_display = NULL, ppb_country = "US",
ppb_country_display = "United States of America",
effective_date = "2012-07-01"), lobbying_activities = list(
list(general_issue_code = "FIN", general_issue_code_display = "Financial Institutions/Investments/Securities",
description = "providing awareness of members positions",
foreign_entity_issues = "", lobbyists = list(
list(lobbyist = list(id = 52828L, prefix = NULL,
prefix_display = NULL, first_name = "DOYCE",
nickname = NULL, middle_name = NULL, last_name = "BOESCH",
suffix = NULL, suffix_display = NULL), covered_position = NULL,
new = FALSE)), government_entities = list(
list(id = 2L, name = "HOUSE OF REPRESENTATIVES"),
list(id = 1L, name = "SENATE")))), conviction_disclosures = list(),
foreign_entities = list(), affiliated_organizations = list())))
So taking this highly nested data, call it
my.data
then I tried to flatten it by
flat.df <- lapply(my.data, function(i) list(unlist(i, recursive = F)))
it sort of worked, but still each element in the flat.df list still have multiple sublists, for example "lobbying_activities", "lobbyists". And they are not expaned(I want the information inside).
But if I set recursive to "TRUE", then the flattened list have duplicated columns and most frustratingly I see some columns got lumped together (for example people's name got into expense column)
Ideally I want to flat such sublists in each table and make the whole thing in one table. Then join them into a dataframe by
df<- as.data.frame(do.call("rbind", flat.df))

tibbles are a nice format, as they support nested data.frames. I would aim for a tibble with 2 rows, a wide format. In it, each nested list element would be its own data.frame, which we could manipulate later when needed. I would do something like this:
library(tidyverse)
l = unlist(l, recursive = F)
ind_to_nest <- which(map_lgl(l[[1]], is.list))
non_tbl <- map(l, ~ .x[-ind_to_nest])
tbl <- map(l, ~ .x[ind_to_nest])
df <- bind_rows(non_tbl) %>%
mutate(n = 1:n(), .before = 1) %>%
mutate(data = map(tbl, ~ map(.x, ~flatten(.x) %>% bind_cols))) %>%
unnest_wider(data, simplify = F)
Note that this does throw a bunch of warnings. This is because of the name conflicts present within the list.
#> New names:
#> * id -> id...5
#> * id -> id...10
Can be resolved by specifying a naming policy, or by rethinking how the data is read into R to resolve naming conflicts early.
#> Outer names are only allowed for unnamed scalar atomic inputs
This is a bit tougher to resolve, but this issue is a starting point.
For analysis some cleaning of sub-tibbles can be performed when needed, as different tasks require different shapes.

R - Nested list to (wide) dataframe

I currently have the following problem: I extracted some data via the crunchbase API, resulting in a big nested list of the following structure (there are many more nested lists on several instances included, I here only display the part of the structure currently relevant for me):
> str(x[[1]])
$ uuid : chr "5f9957b0841251e6e439d757XXXXXX"
$ relationships: List of 27
..$ websites: List of 3
.. ..$ cardinality: chr "OneToMany"
.. ..$ items :'data.frame': 4 obs. of 7 variables:
.. .. ..$ properties.website_type: chr [1:4] "homepage" "facebook" "twitter" "linkedin"
.. .. ..$ properties.url : chr [1:4] "http://www.example.com" "https://www.facebook.com/example" "http://twitter.com/example" "http://www.linkedin.com/company/example"
Consider the following minimal example:
x <- list()
x[[1]] <- list(uuid = "123",
relationships = list(websites = list(items = list(
properties.website_type = c("homepage", "facebook", "twitter", "linkedin"),
properties.url = c("www.example1.com", "www.fbex1.com", "www.twitterex1.com", "www.linkedinex1.com") ) ) ) )
x[[2]] <- list(uuid = "987",
relationships = list(websites = list(items = list(
properties.website_type = c("homepage", "facebook", "twitter" ),
properties.url = c("www.example2.com", "www.fbex2.com", "www.twitterex2.com") ) ) ) )
Now, I would like to create a dataframe with the following column structure:
> x.df
uuid web.url web.facebook web.twitter web.linkedin
1 123 www.example1.com www.fbex1.com www.twitterex1.com www.linkedinex1.com
2 987 www.example2.com www.fbex2.com www.twitterex2.com <NA>
Meaning: I would like to have every uuid (a unique firm identifier) in a single column, followed by the urls of the different platforms (fb, twitter...). I tried a lot of different things with a combination of lapply(), spread(), and row_bind(), yet didn't manage to make anything work. Any help on that would be appreciated.

dplyr approach could be
library(dplyr)
library(tidyr)
#convert list to dataframe in long format
df <- do.call(rbind, lapply(x, data.frame, stringsAsFactors = FALSE))
#final result
df1 <- df %>%
spread(relationships.websites.items.properties.website_type, relationships.websites.items.properties.url)
which gives
uuid facebook homepage linkedin twitter
1 123 www.fbex1.com www.example1.com www.linkedinex1.com www.twitterex1.com
2 987 www.fbex2.com www.example2.com <NA> www.twitterex2.com
Sample data:
x <- list(structure(list(uuid = "123", relationships = structure(list(
websites = structure(list(items = structure(list(properties.website_type = c("homepage",
"facebook", "twitter", "linkedin"), properties.url = c("www.example1.com",
"www.fbex1.com", "www.twitterex1.com", "www.linkedinex1.com"
)), .Names = c("properties.website_type", "properties.url"
))), .Names = "items")), .Names = "websites")), .Names = c("uuid",
"relationships")), structure(list(uuid = "987", relationships = structure(list(
websites = structure(list(items = structure(list(properties.website_type = c("homepage",
"facebook", "twitter"), properties.url = c("www.example2.com",
"www.fbex2.com", "www.twitterex2.com")), .Names = c("properties.website_type",
"properties.url"))), .Names = "items")), .Names = "websites")), .Names = c("uuid",
"relationships")))
Update: In order to fix below error
Error in (function (..., row.names = NULL, check.rows = FALSE,
check.names = TRUE, : arguments imply differing number of rows: 1,
0
you would need to remove corrupted elements from input data where website_type has one value but properties.url has NULL. Run this chunk of code as a pre-processing step before executing the main solution:
idx <- which(sapply(x, function(k) is.null(k$relationships$websites$items$properties.url)))
x <- x[-idx]
Sample data to test this pre-processing step:
x <- list(structure(list(uuid = "123", relationships = structure(list(
websites = structure(list(items = structure(list(properties.website_type = c("homepage",
"facebook", "twitter", "linkedin"), properties.url = c("www.example1.com",
"www.fbex1.com", "www.twitterex1.com", "www.linkedinex1.com"
)), .Names = c("properties.website_type", "properties.url"
))), .Names = "items")), .Names = "websites")), .Names = c("uuid",
"relationships")), structure(list(uuid = "987", relationships = structure(list(
websites = structure(list(items = structure(list(properties.website_type = "homepage",
properties.url = NULL), .Names = c("properties.website_type",
"properties.url"))), .Names = "items")), .Names = "websites")), .Names = c("uuid",
"relationships")), structure(list(uuid = "345", relationships = structure(list(
websites = structure(list(items = structure(list(properties.website_type = "homepage",
properties.url = NULL), .Names = c("properties.website_type",
"properties.url"))), .Names = "items")), .Names = "websites")), .Names = c("uuid",
"relationships")))

I know this is a clunkier solution, but it helped me seeing the process step by step (running str (x_df) to see each result):
library(tidyverse)
# Using your example
x <- list()
x[[1]] <- list(uuid = "123",
relationships = list(websites = list(items = list(
properties.website_type = c("homepage", "facebook", "twitter", "linkedin"),
properties.url = c("www.example1.com", "www.fbex1.com", "www.twitterex1.com", "www.linkedinex1.com") ) ) ) )
x[[2]] <- list(uuid = "987",
relationships = list(websites = list(items = list(
properties.website_type = c("homepage", "facebook", "twitter" ),
properties.url = c("www.example2.com", "www.fbex2.com", "www.twitterex2.com") ) ) ) )
# --- Iterations of unnest:
x_df <- x %>% tibble::as_tibble_col( .) %>%
tidyr::unnest_wider(col = "value") %>%
tidyr::unnest_longer(col = "relationships") %>%
tidyr::unnest_wider(col = "relationships") %>%
tidyr::unnest_wider(col = "items") %>%
tidyr::unnest_longer(col = c("properties.website_type", "properties.url")) %>%
# --- Lastly, group by id:
group_by(uuid) %>%
tidyr::pivot_wider(data = .,
names_from = properties.website_type,
values_from = c("properties.url"))

How to create new column from existing column value in R dynamically

i have data frame called df,how to create new column from existing list column data frame.
my data frame.
Policy Item
Checked list(Processed = "Valid", Gmail = "yy#gmail", Information = list(list(Descrption = "T1, R1", VID = "YUY")))
Sample list(Processed = "Valid", Gmail = "tt#gmail", Information = list(list(Descrption = "D3, Y3", VID = "RT")))
Processed list(Processed = "Valid", Gmail = "pp#gmail", Information = list(list(Descrption = "Y2, LE", VID = "UIU")))
my expected data frame.
Policy Processed Gmail Descrption VID
Checked Valid yy#gmail "T1,R1" "YUY"
Sample Valid tt#gmail "D3,Y3" "RT"
Processed Valid pp#gmail "Y2,LE" "UIU"
i'm using below code to get my expected dataframe .
na_if_null <- function(x) if (is.null(x)) NA else x
new_cols <- lapply(
Filter(is.list, df),
function(list_col) {
names_ <- setNames(nm = unique(do.call(c, lapply(list_col, names))))
lapply(names_, function(name) sapply(list_col, function(x)
trimws(na_if_null(as.list(x)[[name]]))))
}
)
res <- do.call(
data.frame,
c(
list(df, check.names = FALSE, stringsAsFactors = FALSE),
do.call(c, new_cols)
)
)
But i'm getting below Data frame.please help me to done my post.
Policy Item Item.Processed Item.Gmail Item.Information
Checked list(Processed = "Valid", Gmail = "yy#gmail", Information = list(list(Descrption = "T1, R1", VID = "YUY"))) Processed yy#gmail list(Descrption = "T1, R1", VID = "YUY")
Sample list(Processed = "Valid", Gmail = "tt#gmail", Information = list(list(Descrption = "D3, Y3", VID = "RT"))) Processed tt#gmail list(Descrption = "D3, Y3", VID = "RT")
Processed list(Processed = "Valid", Gmail = "pp#gmail", Information = list(list(Descrption = "Y2, LE", VID = "UIU"))) Processed pp#gmail list(Descrption = "Y2, LE", VID = "UIU")
dput
structure(list(Policy = c("Checked", "Sample", "Processed"), Item = list(
structure(list(Processed = "Valid", Gmail = "yy#gmail", Information = list(
structure(list(Descrption = "T1, R1", VID = "YUY"), .Names = c("Descrption",
"VID"), class = "data.frame", row.names = 1L))), .Names = c("Processed",
"Gmail", "Information"), class = "data.frame", row.names = 1L),
structure(list(Processed = "Valid", Gmail = "tt#gmail", Information = list(
structure(list(Descrption = "D3, Y3", VID = "RT"), .Names = c("Descrption",
"VID"), class = "data.frame", row.names = 1L))), .Names = c("Processed",
"Gmail", "Information"), class = "data.frame", row.names = 1L),
structure(list(Processed = "Valid", Gmail = "pp#gmail", Information = list(
structure(list(Descrption = "Y2, LE", VID = "UIU"), .Names = c("Descrption",
"VID"), class = "data.frame", row.names = 1L))), .Names = c("Processed",
"Gmail", "Information"), class = "data.frame", row.names = 1L))), row.names = c(NA,
3L), class = "data.frame", .Names = c("Policy", "Item"))
Sample data frame
Policy colval Item
Checked list(PID="4",Bdetail ="ui,89") list(Processed = "Valid", Gmail = "yy#gmail", Information = list(list(Descrption = "T1, R1", VID = "YUY")))
Sample list(PID="7",Bdetail ="ju,78") list(Processed = "Valid", Gmail = "tt#gmail", Information = list(list(Descrption = "D3, Y3", VID = "RT")))
Processed list(PID ="8",Bdetail ="nj,45") list(Processed = "Valid", Gmail = "pp#gmail", Information = list(list(Descrption = "Y2, LE", VID = "UIU")))

Here a solution in base R:
dd <-
cbind(
dx$Policy,
do.call(rbind,
lapply(seq_len(nrow(dx)), function(i)unlist(dx$Item[i]))
)
)
colnames(dd) <- c("Policy","Processed","Gmail","Descrption","VID")
dd
# Policy Processed Gmail Descrption VID
# [1,] "Checked" "Valid" "yy#gmail" "T1, R1" "YUY"
# [2,] "Sample" "Valid" "tt#gmail" "D3, Y3" "RT"
# [3,] "Processed" "Valid" "pp#gmail" "Y2, LE" "UIU"
Basically I am using unlist for each item. and Then joining them using the classic d.call(rbind,llist).
edit
in case you want tu use the same names as the original sub lists you can do something like :
colnames(dd) <- c("Policy",gsub(".*[.]","",colnames(dd)[-1]))
data.table solution
library(data.table)
setDT(dx)
dx[, rbindlist(lapply(.SD,function(x)data.table(t(unlist(x))))),Policy]

Easily done with unnest from tidyr:
library(dplyr)
library(tidyr)
df %>%
unnest() %>%
unnest()
Result:
Policy Processed Gmail Descrption VID
1 Checked Valid yy#gmail T1, R1 YUY
2 Sample Valid tt#gmail D3, Y3 RT
3 Processed Valid pp#gmail Y2, LE UIU
Data:
df = structure(list(Policy = c("Checked", "Sample", "Processed"), Item = list(
structure(list(Processed = "Valid", Gmail = "yy#gmail", Information = list(
structure(list(Descrption = "T1, R1", VID = "YUY"), .Names = c("Descrption",
"VID"), class = "data.frame", row.names = 1L))), .Names = c("Processed",
"Gmail", "Information"), class = "data.frame", row.names = 1L),
structure(list(Processed = "Valid", Gmail = "tt#gmail", Information = list(
structure(list(Descrption = "D3, Y3", VID = "RT"), .Names = c("Descrption",
"VID"), class = "data.frame", row.names = 1L))), .Names = c("Processed",
"Gmail", "Information"), class = "data.frame", row.names = 1L),
structure(list(Processed = "Valid", Gmail = "pp#gmail", Information = list(
structure(list(Descrption = "Y2, LE", VID = "UIU"), .Names = c("Descrption",
"VID"), class = "data.frame", row.names = 1L))), .Names = c("Processed",
"Gmail", "Information"), class = "data.frame", row.names = 1L))), row.names = c(NA,
3L), class = "data.frame", .Names = c("Policy", "Item"))
Note:
Notice I used two passes of unnest because there are two levels of lists in your original dataframe. unnest automatically flattens all lists in the dataframe and reuses the names, but it does not do it recursively, so you will have to have as many unnest as there are list levels.

Error in View : undefined columns selected

Below is a subsample of my data set (only 2 rows by 215 columns). I am trying to view them on RStudio but it gives me the following error:
Error in View : undefined columns selected
Do not really know what is going on. The whole set is 7786 rows by 215 columns. Viewing it works fine, however, when doing any kind of subsetting or removing one row it is no longer want to view.
structure(list(`NA` = structure(c(16343, 16344), class = "Date"),
AVON = c("615.5", "621.5"), BA. = c("471.5", "463.2"), CMRG = c("224.5",
"224.5"), COB = c("291.10000000000002", "283.5"), MGGT = c("451.2",
"444.7"), QQ. = c("224.5", "223.5"), RR. = c("953.65", "933.38"
), SNR = c("268.2", "264.7"), ULE = c("1771", "1746"), GKN = c("319.2",
"311.5"), BRAG = c("617", "603"), BVIC = c("668", "661"),
CCH = c("1333", "1327"), DGE = c("1785", "1760.5"), SAB = c("3428",
"3383"), STCK = c("291.60000000000002", "294"), ALNT = c("328",
"321"), CAR = c("125", "124.5"), CRDA = c("2053", "1990"),
ELM = c("255.5", "254.5"), JMAT = c("2919", "2825"), SYNT = c("212",
"210.8"), VCTA = c("1606", "1605"), DIA = c("901", "924"),
DNO = c("611", "611"), E2V = c("161", "160.5"), HLMA = c("612",
"598.5"), HTY = c("309.8", "308"), MGAM = c("296.8", "289.40000000000003"
), OXFD = c("1020", "1035"), RSHW = c("1630", "1625"), SXS = c("1808",
"1778"), TTG = c("166.75", "167.5"), XAR = c("376", "367"
), X = c("1527", "1520"), ABF = c("2679", "2654"), AE = c("633.5",
"640"), CARM = c("1647", "1637"), CWK = c("1328", "1320"),
DCG = c("383.75", "369"), DVO = c("237.75", "231"), GNCL = c("234",
"229.6"), HFG = c("416", "411"), FD = c("36.5", "34.75"),
TATE = c("591.5", "585"), MNDI = c("1011", "1012"), BI = c("616",
"620"), REX = c("491.8", "483.5"), RC = c("559", "540"),
SMDS = c("266.3", "257"), SMIN = c("1264", "1250"), VSVS = c("451.8",
"438.40000000000003"), AGA = c("163.25", "160.25"), BDEV = c("396.1",
"389.3"), BKG = c("2250", "2224"), BLWY = c("1567", "1558"
), BVS = c("779", "771"), CRST = c("325", "314.60000000000002"
), GLSN = c("393.5", "388.5"), MCB = c("83.53", "83.29"),
SN = c("1334", "1309"), RB. = c("5350", "5305"), RDW = c("280.7",
"273.8"), TW. = c("112.8", "111.8"), BODY = c("668.5", "647"
), FENR = c("317.60000000000002", "313.10000000000002"),
GDWN = c("3500", "3500"), HILS = c("561", "561.5"), IMI = c("1230",
"1206"), MRO = c("247.70000000000002", "246"), VAR = c("304",
"300.75"), RNO = c("56", "54.5"), RTRK = c("2765", "2736"
), SFR = c("63.5", "64"), SRX = c("2826", "2812"), TRI = c("105.75",
"105"), VTC = c("613.5", "612"), WEIR = c("2502", "2430"),
EVR = c("130", "123.60000000000001"), FXO = c("112.3", "105.10000000000001"
), BBA = c("325", "326"), BMS = c("494.38", "492"), CKN = c("2350",
"2341"), FSHR = c("1326", "1294"), RMG = c("392.2", "399.7"
), STOB = c("111", "109"), UKM = c("473.88", "467"), WIN = c("136.25",
"137.5"), GAW = c("597.5", "585"), HTM = c("131.5", "129.25"
), `NA` = c(NA_character_, NA_character_), AAL = c("1384",
"1363.5"), ABG = c("218.8", "209.1"), ANTO = c("721", "702"
), AF = c("131.5", "130.25"), AQ = c("18.5", "18.75"), ARMS = c("69",
"62.25"), BLT = c("1715", "1690.5"), CEY = c("61.15", "61"
), FRES = c("760", "747"), GEMD = c("192", "191.75"), GLEN = c("343.2",
"336.45"), HOC = c("135.30000000000001", "130.19999999999999"
), KAZ = c("263.39999999999998", "260.10000000000002"), KMRL = c("9.5",
"9.3000000000000007"), LMI = c("185.8", "176.8"), NWR = c("1.97",
"1.82"), `NA` = c(NA_character_, NA_character_), DL = c("190.20000000000002",
"190"), OG = c("22", "24"), OLY = c("516", "496.6"), RIO = c("3031.5",
"3020"), RRS = c("4209", "4154"), VED = c("998.5", "974.5"
), AFR = c("103.5", "109.4"), BG. = c("1140", "1093"), B. = c("453.45",
"452.75"), CNE = c("176.5", "171.6"), ENQ = c("109.60000000000001",
"107.8"), EXI = c("157", "150"), HDY = c("102", "99.75"),
JKX = c("48.25", "47"), OHR = c("229.3", "220.9"), MO = c("333",
"324.7"), RDSA = c("2358.5", "2331"), RDSB = c("2437", "2418.5"
), SIA = c("381", "377.90000000000003"), SMDR = c("100",
"98.5"), TLW = c("644.5", "631"), AMEC = c("1104", "1077"
), CIU = c("283.5", "275.75"), GMS = c("157", "157"), HTG = c("892.5",
"876"), LAM = c("163.25", "160"), FC = c("1037", "1011"),
WG. = c("759.5", "743"), BRBY = c("1511", "1476"), ZC = c("365.7",
"366"), SG = c("1133", "1126"), TED = c("1863", "1862"),
ULVR = c("2585", "2547"), AZN = c("4441.5", "4360.5"), BTG = c("700",
"697.5"), CIR = c("304", "300"), DH = c("758", "753"), GNS = c("1130",
"1130"), GSK = c("1413", "1414"), HIK = c("1733", "1715"),
SH = c("5340", "5310"), SK = c("329.25", "319"), VEC = c("132",
"132"), AGK = c("1548", "1528"), AHT = c("1043", "1024"),
ATK = c("1317", "1323"), BAB = c("1092", "1085"), BNZL = c("1610",
"1597"), BRAM = c("376", "374"), BRSN = c("980", "979"),
CLLN = c("304.60000000000002", "304.3"), CMS = c("59.75",
"59.5"), CNCT = c("149.25", "151"), CI = c("1164", "1165"
), CTR = c("259.5", "255"), DCC = c("3422", "3405"), DLAR = c("477",
"478"), DLM = c("689.5", "685"), ECOM = c("223", "219.8"),
ESNT = c("797.5", "792.5"), EXO = c("176.5", "180"), EXN = c("983.5",
"968"), GFS = c("250.70000000000002", "251.6"), GFTU = c("626",
"616"), HAS = c("116.3", "115.7"), HRG = c("45.75", "45.75"
), HSV = c("319.7", "319"), HWDN = c("339.1", "335"), HYC = c("749",
"748"), IRV = c("599.5", "592.5"), ITRK = c("2621", "2631"
), LVD = c("201.75", "201.5"), MER = c("435", "436.75"),
MMC = c("25.25", "25"), MNZS = c("569", "575.5"), MI = c("418.6",
"421"), MTO = c("287.90000000000003", "286.60000000000002"
), NTG = c("483.8", "481.3"), AY = c("983.5", "989"), FL = c("182",
"180.1"), RCDO = c("671", "667.5"), RENT = c("117.8", "116"
), RGU = c("169.70000000000002", "169.9"), RS = c("261",
"251.6"), RWA = c("302.5", "302.5"), SDY = c("70.5", "69.75"
), SERC = c("286.10000000000002", "279.8"), SHI = c("166.6",
"161.1"), SIV = c("199.75", "200"), SKS = c("90", "92"),
STHR = c("350.25", "358.5"), TK = c("1664", "1635"), TRB = c("170.5",
"172"), V. = c("609.5", "600"), WOS = c("3242", "3243"),
XCH = c("188", "184.75"), ARM = c("906", "887.5"), BVC = c("16.38",
"16.25"), CSR = c("758", "756"), IMG = c("188.5", "184.75"
), LRD = c("309.7", "306.7"), IC = c("298.10000000000002",
"299"), SEU = c("141", "141"), ST = c("104.60000000000001",
"99.9"), BATS = c("3482", "3480"), IMT = c("2664", "2679"
)), .Names = c("NA", "AVON", "BA.", "CMRG", "COB", "MGGT",
"QQ.", "RR.", "SNR", "ULE", "GKN", "BRAG", "BVIC", "CCH", "DGE",
"SAB", "STCK", "ALNT", "CAR", "CRDA", "ELM", "JMAT", "SYNT",
"VCTA", "DIA", "DNO", "E2V", "HLMA", "HTY", "MGAM", "OXFD", "RSHW",
"SXS", "TTG", "XAR", "X", "ABF", "AE", "CARM", "CWK", "DCG",
"DVO", "GNCL", "HFG", "FD", "TATE", "MNDI", "BI", "REX", "RC",
"SMDS", "SMIN", "VSVS", "AGA", "BDEV", "BKG", "BLWY", "BVS",
"CRST", "GLSN", "MCB", "SN", "RB.", "RDW", "TW.", "BODY", "FENR",
"GDWN", "HILS", "IMI", "MRO", "VAR", "RNO", "RTRK", "SFR", "SRX",
"TRI", "VTC", "WEIR", "EVR", "FXO", "BBA", "BMS", "CKN", "FSHR",
"RMG", "STOB", "UKM", "WIN", "GAW", "HTM", NA, "AAL", "ABG",
"ANTO", "AF", "AQ", "ARMS", "BLT", "CEY", "FRES", "GEMD", "GLEN",
"HOC", "KAZ", "KMRL", "LMI", "NWR", NA, "DL", "OG", "OLY", "RIO",
"RRS", "VED", "AFR", "BG.", "B.", "CNE", "ENQ", "EXI", "HDY",
"JKX", "OHR", "MO", "RDSA", "RDSB", "SIA", "SMDR", "TLW", "AMEC",
"CIU", "GMS", "HTG", "LAM", "FC", "WG.", "BRBY", "ZC", "SG",
"TED", "ULVR", "AZN", "BTG", "CIR", "DH", "GNS", "GSK", "HIK",
"SH", "SK", "VEC", "AGK", "AHT", "ATK", "BAB", "BNZL", "BRAM",
"BRSN", "CLLN", "CMS", "CNCT", "CI", "CTR", "DCC", "DLAR", "DLM",
"ECOM", "ESNT", "EXO", "EXN", "GFS", "GFTU", "HAS", "HRG", "HSV",
"HWDN", "HYC", "IRV", "ITRK", "LVD", "MER", "MMC", "MNZS", "MI",
"MTO", "NTG", "AY", "FL", "RCDO", "RENT", "RGU", "RS", "RWA",
"SDY", "SERC", "SHI", "SIV", "SKS", "STHR", "TK", "TRB", "V.",
"WOS", "XCH", "ARM", "BVC", "CSR", "IMG", "LRD", "IC", "SEU",
"ST", "BATS", "IMT"), row.names = 7785:7786, class = "data.frame")
I am on Mac OS 10.10, R 3.1.1 and RStudio 0.98.1060.

One of your column names is NA. If d is your data defined above, then try names(d)[92]. Try replacing with a non-missing column name.

As allready mentioned by DMC, but with a short version of your example code.
a <- structure(list(`NA` = structure(c(16343, 16344), class = "Date"),
AVON = c("615.5", "621.5"),
BA. = c("471.5", "463.2"),
`NA` = c(NA_character_, NA_character_), AAL = c("1384", "1363.5")),
.Names = c(NA, "AVON", "BA.", "NA", "AAL"), row.names = 7785:7786, class = "data.frame")
View(a)
Error in View : undefined columns selected
names(a)
[1] NA "AVON" "BA." "NA" "AAL"
a <- structure(list(`NA` = structure(c(16343, 16344), class = "Date"),
AVON = c("615.5", "621.5"),
BA. = c("471.5", "463.2"),
`NA` = c(NA_character_, NA_character_), AAL = c("1384", "1363.5")),
.Names = c("NA", "AVON", "BA.", "NA", "AAL"), row.names = 7785:7786, class = "data.frame")
View(a)
names(a)
[1] "NA" "AVON" "BA." "NA" "AAL"
You need to have proper names in the data frame to View it.

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