How to convert a list into a dataframe with titles (in R)-CodePudding

I have a list which is very long. I would like to find out the percentages of clearing the violent cases for each data (percentage of clearing = cleared cases/actual cases).

    dput(crime_data)
list(results = list(list(ori = "NY0010000", data_year = 2008L, 
    offense = "violent-crime", state_abbr = "NY", cleared = 33L, 
    actual = 33L, data_range = NULL), list(ori = "NY0010000", 
    data_year = 2009L, offense = "violent-crime", state_abbr = "NY", 
    cleared = 22L, actual = 24L, data_range = NULL), list(ori = "NY0010100", 
    data_year = 2008L, offense = "violent-crime", state_abbr = "NY", 
    cleared = 333L, actual = 1033L, data_range = NULL), list(
    ori = "NY0010100", data_year = 2009L, offense = "violent-crime", 
    state_abbr = "NY", cleared = 372L, actual = 1007L, data_range = NULL), 
    list(ori = "NY0010200", data_year = 2008L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 0L, actual = 61L, data_range = NULL), 
    list(ori = "NY0010200", data_year = 2009L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 34L, actual = 51L, data_range = NULL), 
    list(ori = "NY0010300", data_year = 2008L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 20L, actual = 32L, data_range = NULL), 
    list(ori = "NY0010300", data_year = 2009L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 32L, actual = 40L, data_range = NULL), 
    list(ori = "NY0012000", data_year = 2008L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 1L, actual = 4L, data_range = NULL), 
    list(ori = "NY0012000", data_year = 2009L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 5L, actual = 8L, data_range = NULL), 
    list(ori = "NY0012100", data_year = 2008L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 0L, actual = 0L, data_range = NULL), 
    list(ori = "NY0012100", data_year = 2009L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 0L, actual = 0L, data_range = NULL), 
    list(ori = "NY0012500", data_year = 2008L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 5L, actual = 10L, data_range = NULL), 
    list(ori = "NY0012500", data_year = 2009L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 7L, actual = 9L, data_range = NULL), 
    list(ori = "NY0015100", data_year = 2008L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 17L, actual = 20L, data_range = NULL), 
    list(ori = "NY0015100", data_year = 2009L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 22L, actual = 30L, data_range = NULL), 
    list(ori = "NY0015200", data_year = 2008L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 0L, actual = 24L, data_range = NULL), 
    list(ori = "NY0015200", data_year = 2009L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 0L, actual = 19L, data_range = NULL), 
    list(ori = "NY0015300", data_year = 2008L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 38L, actual = 54L, data_range = NULL), 
    list(ori = "NY0015300", data_year = 2009L, offense = "violent-crime", 
        state_abbr = "NY", cleared = 40L, actual = 61L, data_range = NULL)), 
    pagination = list(count = 1188L, page = 0L, pages = 60L, 
        per_page = 20L))

I tried to convert it into a dataframe using the standard methods, but I always get "Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, : arguments imply differing number of rows: 1, 0"

Or if I use "df <- data.frame(matrix(unlist(crime_data), nrow=length(crime_data), byrow=TRUE))" I get this

How would I do this better/at all? Is it easier to do it in a list format or convert into DF

CodePudding user response：

The problem is that crime_data is a list with two parts. All of the crime data is in crime_data[[1]] with crime_data$pagination attached to the end. To get what you want just extract the first part:

crime.data <- do.call(rbind, crime_data[[1]])
colnames <- unlist(dimnames(crime.data))
cols <- sapply(colnames, function(x) unlist(crime.data[, x]))
crime.df <- as.data.frame(do.call(cbind, cols))

The first line extracts the crime data from the list. The next three lines extract the column lists and combine them into a data frame. There may be an easier way to do this.