How to Make a Data Frame into a Simple Features Data Frame

how to make a data frame into a simple features data frame?

UPDATE
The answer from @Franz Plumpton is the correct correct solution with a single epsg. My answer below is only necessary when each row of a data.frame has a different epsg. Otherwise, this would be a duplicate (as pointed out by @Henrik above).

library(sf)
library(tibble)

df <- data_frame(place = c("London", "Kalamazoo"), 
           lat = c(51.5074, 396088), lon = c(0.1278, 5452158),
           epsg = c(4326, 32610))

l <- lapply(unique(df$place), function(x){
  df <- df[df$place == x,]
  epsg <- df$epsg[1]
  df  <-  st_as_sf(df, coords = c('lon', 'lat'), crs = epsg)
}) 

you could then transform all to the same epsg and combine into a single data.frame:

do.call(rbind, lapply(l, function(x) x <- st_transform(x, 4326)))

Convert from simple feature geometry to dataframe

You already have a data.frame, and you can perform transformations on the st_sfc objects in it,
using basic affine transformations. For example

df1[1,1] = df1[1,1] + c(2,0) 

ggplot(df1) +
  geom_sf(aes(geometry = geometry)) 

Explanatory note: df1[1,1] selects the first column and row, which is the star. Adding c(2,0) translates it by +2 in the x direction.

The answer to the question you actually asked:
If you really need the x,y cordinates as columns in a data.frame, you can use

df2 = data.frame(st_coordinates(df1[,1]))

However, for the use case you described, the first method above will be better. Not just because it is faster and neater, but because manipulating the sf objects themselves will take care of things like crs and extent.

How to convert list of -sf dataframes into single dataframe with geometry per row in R?

You need to make sure your sf objects have the same crs, otherwise you cannot combine their geometries into a single sfc (simple feature column). Once we transform them into longlat for example, we can just rbind them.

df_ll = map(df, ~ st_transform(., 4326))

df_sf = do.call(rbind, df_ll)
## or using Reduce
df_sf = Reduce(rbind, df_ll)
## or using purrr version of reduce
df_sf = reduce(df_ll, rbind)

Convert data frame containing coordinates of polygons to sf

I always struggle with doing this sf transformation too, because it's not straight forward.

The first step (and hard part) is to build a st_object (here st_polygon) for each individual geometry represented.

To do that, convert each existing list into a matrix. Once each polygon representation is a n-row matrix (one row for each point) we convert the matrix to a one element list to feed into st_polygon(). Now dat$geometry is a list appropriately classed of POLYGONS.

library(tidyverse)

dat %>%
  mutate(geometry = map(geometry,
                        ~ do.call(rbind, .) %>% # make each list a matrix
                          list() %>% # st_polygon() requires a list
                          st_polygon()
                    )
         ) %>% 
  st_as_sf()

Then the final step is to call st_as_sf() on the entire data frame. It will auto-detect the now properly formatted geometry column and produce a nice new sf object for you. Happy mapping!

EDIT: If you want to build polygons with holes, the process is similar. st_polygon() will process a multi-element list as if the the first element is the polygon and the remaining elements are holes in the first. It does require that you use map twice, because you still need to build a matrix out of each list element, but need keep the lists of grouped matrixs together for processing the holes.

dat2 <- tibble::tribble( ~code, ~geometry, "MIE", list(list(c(1.24, 45), c(1.25, 45), c(1.25, 46), c(1.24, 45)), list(c(1.245,45.5), c(1.246,45.7), c(1.245,45.5))) )

 dat %>%
  mutate(geometry = map(dat$geometry,
                        ~ map(.,
                          ~ do.call(rbind, .) # make each list a matrix
                          ) %>% 
                        st_polygon()
                        )
  ) %>% 
  st_as_sf()

Convert sf object to dataframe and restore it to original state

I think geom isn't in a format st_geometry is expecting. st_as_text converted your geometry into WKT as discussed in the help:

The returned WKT representation of simple feature geometry conforms to the simple features access specification and extensions, known as EWKT, supported by PostGIS and other simple features implementations for addition of SRID to a WKT string.

https://r-spatial.github.io/sf/reference/st_as_text.html

Instead, use st_as_sf(wkt=) to set the new (old) geometry.

st_as_sf(geo_df, wkt = "geom", crs = 4326)

Create sf object from two-column matrix

As per the sf docs

m %>% 
  as.data.frame %>% 
  sf::st_as_sf(coords = c(1,2))

Creating sf polygons from a dataframe

I figured out an answer based on paqmo's suggestion to look at Convert sequence of longitude and latitude to polygon via sf in R

The answer provided in that question groups all the points in the data frame as a single polygon. I've added a step to group the dataframe by the variable that identifies the polygon.

polygon <- my.df %>%
  st_as_sf(coords = c("Easting", "Northing"), crs = utm18) %>%
  group_by(Plot) %>%
  summarise(geometry = st_combine(geometry)) %>%
  st_cast("POLYGON")

Create a sfc_GEOMETRY object from a data frame of vectors in R

Each element of the geometry column is simply a two-column matrix wrapped in a list in another list. You can therefore just edit them directly...

States$geometry[n][[1]][[1]] <- as.matrix(exCoords)

where n is the row number of States that you want to replace. All of the sfc_geometry attributes are retained.

R create sf polyline from nested list of coordinates

Your feature looks like the result of converting geojson into an R object

If you have access to the geojson object before it is converted into your feature, then you can ignore the to_json() step(s) here

library(sf)

## convert back to JSON

### Option 1
js <- jsonify::to_json(feature, unbox = TRUE)

### Option 2
js <- jsonlite::toJSON(feature, auto_unbox = TRUE)

## Then you can convert to SF

### Option 1
geojsonsf::geojson_sf(js)

### Option 2
sf::st_read(js)

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