Downloading Geonames
I am interested in downloading Lake Geonames for Canada. Max. rows that can be downloaded per day is 1000. When I run the below code, few records are being missed and some records are overlapped. Is there a way to get total number of lake geonames records available and download the record only once without any overlap ?
library(geonames); GN_lake <- GNsearch(featureCode='LK', country='CA',startRow=1,maxRows = 1000)
GN_lake <- GNsearch(featureCode='LK', country='CA',startRow=1000, maxRows=1000)
r geonames
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I am interested in downloading Lake Geonames for Canada. Max. rows that can be downloaded per day is 1000. When I run the below code, few records are being missed and some records are overlapped. Is there a way to get total number of lake geonames records available and download the record only once without any overlap ?
library(geonames); GN_lake <- GNsearch(featureCode='LK', country='CA',startRow=1,maxRows = 1000)
GN_lake <- GNsearch(featureCode='LK', country='CA',startRow=1000, maxRows=1000)
r geonames
add a comment |
I am interested in downloading Lake Geonames for Canada. Max. rows that can be downloaded per day is 1000. When I run the below code, few records are being missed and some records are overlapped. Is there a way to get total number of lake geonames records available and download the record only once without any overlap ?
library(geonames); GN_lake <- GNsearch(featureCode='LK', country='CA',startRow=1,maxRows = 1000)
GN_lake <- GNsearch(featureCode='LK', country='CA',startRow=1000, maxRows=1000)
r geonames
I am interested in downloading Lake Geonames for Canada. Max. rows that can be downloaded per day is 1000. When I run the below code, few records are being missed and some records are overlapped. Is there a way to get total number of lake geonames records available and download the record only once without any overlap ?
library(geonames); GN_lake <- GNsearch(featureCode='LK', country='CA',startRow=1,maxRows = 1000)
GN_lake <- GNsearch(featureCode='LK', country='CA',startRow=1000, maxRows=1000)
r geonames
r geonames
asked Nov 21 '18 at 12:54
roshualineroshualine
1316
1316
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1 Answer
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Why not just work with the CA database locally?
library(httr)
library(tidyverse)
# Get CA database
httr::GET(
url = "http://download.geonames.org/export/dump/CA.zip",
httr::write_disk("CA.zip"),
httr::progress()
) -> res
# unzip it
unzip("CA.zip")
read.csv( # readr::read_tsv doesn't like this file at least when I read it
file = "CA.txt",
header = FALSE,
sep = "t",
col.names = c(
"geonameid", "name", "asciiname", "alternatenames", "latitude",
"longitude", "feature_class", "feature_code", "country", "cc2",
"admin1_code1", "admin2_code", "admin3_code", "admin4_code",
"population", "elevation", "dem", "timezone", "modification_date"
),
stringsAsFactors = FALSE
) %>% tbl_df() -> ca_geo
filter(ca_geo, feature_code == "LK")
## # A tibble: 104,663 x 19
## geonameid name asciiname alternatenames latitude longitude
## <int> <chr> <chr> <chr> <dbl> <dbl>
## 1 5881640 101 Mile Lake 101 Mile Lake "" 51.7 -121.
## 2 5881642 103 Mile Lake 103 Mile Lake "" 51.7 -121.
## 3 5881644 105 Mile Lake 105 Mile Lake "" 51.7 -121.
## 4 5881647 108 Mile Lake 108 Mile Lake "" 51.7 -121.
## 5 5881660 130 Mile Lake 130 Mile Lake "" 51.9 -122.
## 6 5881666 16 1/2 Mile … 16 1/2 Mile … "" 52.7 -118.
## 7 5881668 180 Lake 180 Lake "" 57.4 -130.
## 8 5881673 {1}útsaw Lake {1}utsaw Lake "" 62.7 -137.
## 9 5881680 24 Mile Lake 24 Mile Lake "" 46.5 -82.0
## 10 5881683 28 Mile Lake 28 Mile Lake "" 54.8 -124.
## # ... with 104,653 more rows, and 13 more variables: feature_class <chr>,
## # feature_code <chr>, country <chr>, cc2 <chr>, admin1_code1 <int>,
## # admin2_code <chr>, admin3_code <int>, admin4_code <chr>,
## # population <int>, elevation <int>, dem <int>, timezone <chr>,
## # modification_date <chr>
Thank you very much. This is a better solution than what I planned.
– roshualine
Nov 21 '18 at 13:59
👍🏼 download.geonames.org/export/dump has all the databases and metadata about them.
– hrbrmstr
Nov 21 '18 at 14:06
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Why not just work with the CA database locally?
library(httr)
library(tidyverse)
# Get CA database
httr::GET(
url = "http://download.geonames.org/export/dump/CA.zip",
httr::write_disk("CA.zip"),
httr::progress()
) -> res
# unzip it
unzip("CA.zip")
read.csv( # readr::read_tsv doesn't like this file at least when I read it
file = "CA.txt",
header = FALSE,
sep = "t",
col.names = c(
"geonameid", "name", "asciiname", "alternatenames", "latitude",
"longitude", "feature_class", "feature_code", "country", "cc2",
"admin1_code1", "admin2_code", "admin3_code", "admin4_code",
"population", "elevation", "dem", "timezone", "modification_date"
),
stringsAsFactors = FALSE
) %>% tbl_df() -> ca_geo
filter(ca_geo, feature_code == "LK")
## # A tibble: 104,663 x 19
## geonameid name asciiname alternatenames latitude longitude
## <int> <chr> <chr> <chr> <dbl> <dbl>
## 1 5881640 101 Mile Lake 101 Mile Lake "" 51.7 -121.
## 2 5881642 103 Mile Lake 103 Mile Lake "" 51.7 -121.
## 3 5881644 105 Mile Lake 105 Mile Lake "" 51.7 -121.
## 4 5881647 108 Mile Lake 108 Mile Lake "" 51.7 -121.
## 5 5881660 130 Mile Lake 130 Mile Lake "" 51.9 -122.
## 6 5881666 16 1/2 Mile … 16 1/2 Mile … "" 52.7 -118.
## 7 5881668 180 Lake 180 Lake "" 57.4 -130.
## 8 5881673 {1}útsaw Lake {1}utsaw Lake "" 62.7 -137.
## 9 5881680 24 Mile Lake 24 Mile Lake "" 46.5 -82.0
## 10 5881683 28 Mile Lake 28 Mile Lake "" 54.8 -124.
## # ... with 104,653 more rows, and 13 more variables: feature_class <chr>,
## # feature_code <chr>, country <chr>, cc2 <chr>, admin1_code1 <int>,
## # admin2_code <chr>, admin3_code <int>, admin4_code <chr>,
## # population <int>, elevation <int>, dem <int>, timezone <chr>,
## # modification_date <chr>
Thank you very much. This is a better solution than what I planned.
– roshualine
Nov 21 '18 at 13:59
👍🏼 download.geonames.org/export/dump has all the databases and metadata about them.
– hrbrmstr
Nov 21 '18 at 14:06
add a comment |
Why not just work with the CA database locally?
library(httr)
library(tidyverse)
# Get CA database
httr::GET(
url = "http://download.geonames.org/export/dump/CA.zip",
httr::write_disk("CA.zip"),
httr::progress()
) -> res
# unzip it
unzip("CA.zip")
read.csv( # readr::read_tsv doesn't like this file at least when I read it
file = "CA.txt",
header = FALSE,
sep = "t",
col.names = c(
"geonameid", "name", "asciiname", "alternatenames", "latitude",
"longitude", "feature_class", "feature_code", "country", "cc2",
"admin1_code1", "admin2_code", "admin3_code", "admin4_code",
"population", "elevation", "dem", "timezone", "modification_date"
),
stringsAsFactors = FALSE
) %>% tbl_df() -> ca_geo
filter(ca_geo, feature_code == "LK")
## # A tibble: 104,663 x 19
## geonameid name asciiname alternatenames latitude longitude
## <int> <chr> <chr> <chr> <dbl> <dbl>
## 1 5881640 101 Mile Lake 101 Mile Lake "" 51.7 -121.
## 2 5881642 103 Mile Lake 103 Mile Lake "" 51.7 -121.
## 3 5881644 105 Mile Lake 105 Mile Lake "" 51.7 -121.
## 4 5881647 108 Mile Lake 108 Mile Lake "" 51.7 -121.
## 5 5881660 130 Mile Lake 130 Mile Lake "" 51.9 -122.
## 6 5881666 16 1/2 Mile … 16 1/2 Mile … "" 52.7 -118.
## 7 5881668 180 Lake 180 Lake "" 57.4 -130.
## 8 5881673 {1}útsaw Lake {1}utsaw Lake "" 62.7 -137.
## 9 5881680 24 Mile Lake 24 Mile Lake "" 46.5 -82.0
## 10 5881683 28 Mile Lake 28 Mile Lake "" 54.8 -124.
## # ... with 104,653 more rows, and 13 more variables: feature_class <chr>,
## # feature_code <chr>, country <chr>, cc2 <chr>, admin1_code1 <int>,
## # admin2_code <chr>, admin3_code <int>, admin4_code <chr>,
## # population <int>, elevation <int>, dem <int>, timezone <chr>,
## # modification_date <chr>
Thank you very much. This is a better solution than what I planned.
– roshualine
Nov 21 '18 at 13:59
👍🏼 download.geonames.org/export/dump has all the databases and metadata about them.
– hrbrmstr
Nov 21 '18 at 14:06
add a comment |
Why not just work with the CA database locally?
library(httr)
library(tidyverse)
# Get CA database
httr::GET(
url = "http://download.geonames.org/export/dump/CA.zip",
httr::write_disk("CA.zip"),
httr::progress()
) -> res
# unzip it
unzip("CA.zip")
read.csv( # readr::read_tsv doesn't like this file at least when I read it
file = "CA.txt",
header = FALSE,
sep = "t",
col.names = c(
"geonameid", "name", "asciiname", "alternatenames", "latitude",
"longitude", "feature_class", "feature_code", "country", "cc2",
"admin1_code1", "admin2_code", "admin3_code", "admin4_code",
"population", "elevation", "dem", "timezone", "modification_date"
),
stringsAsFactors = FALSE
) %>% tbl_df() -> ca_geo
filter(ca_geo, feature_code == "LK")
## # A tibble: 104,663 x 19
## geonameid name asciiname alternatenames latitude longitude
## <int> <chr> <chr> <chr> <dbl> <dbl>
## 1 5881640 101 Mile Lake 101 Mile Lake "" 51.7 -121.
## 2 5881642 103 Mile Lake 103 Mile Lake "" 51.7 -121.
## 3 5881644 105 Mile Lake 105 Mile Lake "" 51.7 -121.
## 4 5881647 108 Mile Lake 108 Mile Lake "" 51.7 -121.
## 5 5881660 130 Mile Lake 130 Mile Lake "" 51.9 -122.
## 6 5881666 16 1/2 Mile … 16 1/2 Mile … "" 52.7 -118.
## 7 5881668 180 Lake 180 Lake "" 57.4 -130.
## 8 5881673 {1}útsaw Lake {1}utsaw Lake "" 62.7 -137.
## 9 5881680 24 Mile Lake 24 Mile Lake "" 46.5 -82.0
## 10 5881683 28 Mile Lake 28 Mile Lake "" 54.8 -124.
## # ... with 104,653 more rows, and 13 more variables: feature_class <chr>,
## # feature_code <chr>, country <chr>, cc2 <chr>, admin1_code1 <int>,
## # admin2_code <chr>, admin3_code <int>, admin4_code <chr>,
## # population <int>, elevation <int>, dem <int>, timezone <chr>,
## # modification_date <chr>
Why not just work with the CA database locally?
library(httr)
library(tidyverse)
# Get CA database
httr::GET(
url = "http://download.geonames.org/export/dump/CA.zip",
httr::write_disk("CA.zip"),
httr::progress()
) -> res
# unzip it
unzip("CA.zip")
read.csv( # readr::read_tsv doesn't like this file at least when I read it
file = "CA.txt",
header = FALSE,
sep = "t",
col.names = c(
"geonameid", "name", "asciiname", "alternatenames", "latitude",
"longitude", "feature_class", "feature_code", "country", "cc2",
"admin1_code1", "admin2_code", "admin3_code", "admin4_code",
"population", "elevation", "dem", "timezone", "modification_date"
),
stringsAsFactors = FALSE
) %>% tbl_df() -> ca_geo
filter(ca_geo, feature_code == "LK")
## # A tibble: 104,663 x 19
## geonameid name asciiname alternatenames latitude longitude
## <int> <chr> <chr> <chr> <dbl> <dbl>
## 1 5881640 101 Mile Lake 101 Mile Lake "" 51.7 -121.
## 2 5881642 103 Mile Lake 103 Mile Lake "" 51.7 -121.
## 3 5881644 105 Mile Lake 105 Mile Lake "" 51.7 -121.
## 4 5881647 108 Mile Lake 108 Mile Lake "" 51.7 -121.
## 5 5881660 130 Mile Lake 130 Mile Lake "" 51.9 -122.
## 6 5881666 16 1/2 Mile … 16 1/2 Mile … "" 52.7 -118.
## 7 5881668 180 Lake 180 Lake "" 57.4 -130.
## 8 5881673 {1}útsaw Lake {1}utsaw Lake "" 62.7 -137.
## 9 5881680 24 Mile Lake 24 Mile Lake "" 46.5 -82.0
## 10 5881683 28 Mile Lake 28 Mile Lake "" 54.8 -124.
## # ... with 104,653 more rows, and 13 more variables: feature_class <chr>,
## # feature_code <chr>, country <chr>, cc2 <chr>, admin1_code1 <int>,
## # admin2_code <chr>, admin3_code <int>, admin4_code <chr>,
## # population <int>, elevation <int>, dem <int>, timezone <chr>,
## # modification_date <chr>
answered Nov 21 '18 at 13:12
hrbrmstrhrbrmstr
61.5k691152
61.5k691152
Thank you very much. This is a better solution than what I planned.
– roshualine
Nov 21 '18 at 13:59
👍🏼 download.geonames.org/export/dump has all the databases and metadata about them.
– hrbrmstr
Nov 21 '18 at 14:06
add a comment |
Thank you very much. This is a better solution than what I planned.
– roshualine
Nov 21 '18 at 13:59
👍🏼 download.geonames.org/export/dump has all the databases and metadata about them.
– hrbrmstr
Nov 21 '18 at 14:06
Thank you very much. This is a better solution than what I planned.
– roshualine
Nov 21 '18 at 13:59
Thank you very much. This is a better solution than what I planned.
– roshualine
Nov 21 '18 at 13:59
👍🏼 download.geonames.org/export/dump has all the databases and metadata about them.
– hrbrmstr
Nov 21 '18 at 14:06
👍🏼 download.geonames.org/export/dump has all the databases and metadata about them.
– hrbrmstr
Nov 21 '18 at 14:06
add a comment |
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