Data group by and Visualization(googlevis)

################googleVis####################
#install.packages('googleVis')
# library(googleVis)
# library(dplyr)
A %>%
  filter(Technology_transfer_amount>0 & Reinvestment_amount>0 & Sales_Amount>0  ) %>%
  group_by(Industry_type,Technology_transfer_year)%>%
  summarise(
    case_NO=n(),
    Technology_transfer_amount=mean(Technology_transfer_amount,na.rm = T),
    Reinvestment_amount=mean(Reinvestment_amount,na.rm=T),
    Material_costs=mean(Reinvestment_amount*(Material_costs/100),na.rm=T),
    Facilities_costs=mean(Reinvestment_amount*(Facilities_costs/100),na.rm=T),
    Research_Development_cost=mean(Reinvestment_amount*(Research_Development_cost/100),na.rm=T),
    Marketing_cost=mean(Reinvestment_amount*(Marketing_cost/100),na.rm=T),
    Other_cost=mean(Reinvestment_amount*(Other_cost/100),na.rm=T),
    Sales_Amount=mean(Sales_Amount,na.rm=T)
  )  -> df

Warning message:
In strsplit(code, "\n", fixed = TRUE) :
  input string 1 is invalid in this locale

df = as.data.frame((df))
df$Industry_type = sapply(df$Industry_type, function(v) 
  ifelse(v=='林業','forestry',ifelse(v=='畜牧','Livestock',ifelse(v=='農糧','Agricultural','Fisheries')))) 
plot(gvisMotionChart(
  df,'Industry_type','Technology_transfer_year',
  options=list(width=1000, height=600)))
df