Error in eval(substitute(expr), data, enclos = parent.frame()) : invalid 'envir' argument of type 'character'

[kevinbsc]

I am getting an error. Can you explain why? Thanks.

> doc_term_mat = presidential_debates_2012 %>%
+ with(gofastr::q_dtm_stem(dialogue, paste(person, time, sep = "_"))) %>% 
+ gofastr::remove_stopwords(stops, stem=TRUE) %>% 
+ gofastr::filter_tf_idf() %>%
+ gofastr::filter_documents()
Error in eval(substitute(expr), data, enclos = parent.frame()) : 
 invalid 'envir' argument of type 'character'

[trinker]

Please provide session info.

[kevinbsc]

Thanks for your reply.

R version 3.2.3 (2015-12-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] magrittr_1.5 wakefield_0.2.1 Rmpfr_0.6-0 gmp_0.5-12 ggplot2_2.0.0 LDAvis_0.3.3
[7] devtools_1.10.0 igraph_1.0.1 tidyr_0.4.1 dplyr_0.4.3 topicmodels_0.2-3 tm_0.6-2
[13] NLP_0.1-9 gofastr_0.1.0 pacman_0.3.0

loaded via a namespace (and not attached):
[1] Rcpp_0.12.3 quanteda_0.9.4 ca_0.64 plyr_1.8.3 tools_3.2.3 digest_0.6.9
[7] memoise_1.0.0 gtable_0.2.0 lattice_0.20-33 Matrix_1.2-3 DBI_0.3.1 curl_0.9.6
[13] parallel_3.2.3 httr_1.1.0 stats4_3.2.3 grid_3.2.3 data.table_1.9.6 R6_2.1.2
[19] SnowballC_0.5.1 scales_0.4.0 modeltools_0.2-21 assertthat_0.1 colorspace_1.2-6 stringi_1.0-1
[25] lazyeval_0.1.10 munsell_0.4.3 slam_0.1-32 chron_2.3-47

[anujs5586]

please someone answer this. I'm also getting this error.

product_data <- function(data){

Creating two vectors which holds numeric and categorical variables

col_numeric <- c("week","Units", "SLA", "MRP")
col_factor <- c("Product_analytic_vertical", "Order_payment_type")

# Convering the continuous variables into numeric format and Categorical variables in to factors

data[,col_numeric] <- sapply(data[,col_numeric], as.numeric)
data[,col_factor] <- sapply(data[,col_factor], as.factor)

Created a data frame which holds only categorical variables

df_dummies <- data[,col_factor] 

Creating dummy variables for categorical/factor attributes

dummies<- data.frame(sapply(df_dummies, function(x) data.frame(model.matrix(~x-1,data =unlist(df_dummies))[,-1])))
dummies <- as.data.frame(cbind(as.factor(data[1]), data=unlist(dummies)))

Aggregate the dummy variables data by weeks

dummies_aggregate <- aggregate(.~ as.factor(week), data=dummies, FUN=sum,na.rm=TRUE,collapse=" & ")

Aggregating the Actual dtaa variables by weeks

data <- data %>% group_by(as.factor(week)) %>% summarise(gmv = sum(gmv), Units = sum(Units), SLA = mean(SLA), MRP = sum(MRP), Product_procurement_SLA =mean(Product_procurement_SLA),
 NPS_Score = mean(NPS_Score),list_price = sum(list_price), Promotional_offer = sum(Promotional_offer)/length(week),
 TV_adstock= mean(TV_adstock),Digital_adstock = mean(Digital_adstock), Sponsorship_adstock = mean(Sponsorship_adstock), Content_Marketing_adstock = mean(Content_Marketing_adstock),
 Online_Marketing_adstock = mean(Online_Marketing_adstock), Affiliates_adstock = mean(Affiliates_adstock), SEM_adtock = mean(SEM_adstock),
 Radio_adstock = mean(Radio_adstock), Other_adstock = mean(Other_adstock))

Merging the Dummy and actual data variables in to one data frame

data <- merge(unlist(data), unlist(dummies_aggregate), by = c("week"), all.x = TRUE)

return(data)

}

GamingAccessory_df<- product_data(GamingAccessory)

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Above is the code I ran in R