I am trying to get the zip demographics data of the year 2015. When I tried the codes below, an error message returns.
library(devtools)
install_github('arilamstein/choroplethrZip#v1.4.0')
library(choroplethrZip)
df_zip_2015 = get_zip_demographics(2015,5)
When the data tries to read in, I first got a few NAs introduced by coercion warnings, but then an error message returns
Error in choroplethr:::convert_acs_obj_to_df("zip", age, 1) :
argument "include_moe" is missing, with no default
Is there a way I can fix this?
It looks like you are installing choroplethrZip version 1.4.0. However, if you go to the choroplethrZip github page you will see that the latest version is actually 1.5.0.
When I run this code:
library(devtools)
install_github('arilamstein/choroplethrZip#v1.5.0')
library(choroplethrZip)
df_zip_2015 = get_zip_demographics(2015,5)
I do not get the error you describe.
Related
I am getting this error when I run:
library(seasonal)
m <- seas(AirPassengers)
I have installed the package.
I have uninstalled R, Rstudio, reinstalled and tried again, same error.
Could someone help?
Thanks
I can't reproduce exactly the same error now but I remember following error after I installed the seasonal package:
Error in seas(AirPassengers) : could not find function "seas"
After cleaning up my workspace the error was gone.
Following code is working for me and resulting in the plot below:
library(seasonal)
head(AirPassengers)
m <- seas(AirPassengers, regression.aictest = c("td", "easter"))
plot(m)
I want to use mice function to handle the missing data that I have in (data). I installed the package and I called the library. However, when I am trying to apply the function to my data it gives me error as below:
(Error in mice(data[, 5:9], m = 3, seed = 123) :
could not find function "mice")
I have a normal data frame that includes NAs
install.packages('mice')
library(mice)
library(VIM)
md.pattern(data)
md.pairs(data)
My_New_Data <- mice(data[,5:9], m=3, seed=123)
I am expecting the function to solve the problem and replace the NAs with reasonable values. It did not work at all!
Edit (incorporating comment suggestion)
In the comments the running mice::mice(data[, 5:9], m = 3, seed = 123). I ran this and the following error was returned.
Error in get(Info[i, 1], envir = env):
lazy-load database 'C:/Users/MUSTAFA KAMAL/Documents/R/win-library/3.5/broom/R/broom.rdb' is corrupt
In addition:
Warning message: In get(Info[i, 1], envir = env) : internal error -3 in R_decompress1
In order to incorporate an answer to this question, I will rewrite my comment which resolved the problem, in the form of a short answer.
From the comments executing mice::mice(data[, 5:9], m = 3, seed = 123) resulted in an error message, showing the directory ~/Documents/R/win-library/**3.5**/broom/R/broom.rdb being corrupt.
From the corrupted directory path, one can see that OP was running R-3.5.x, while the newest version is R-3.6.x. Some packages updated since the most recent R-update has experienced similar problems, as such a first step towards solving these types of issues is updating R. The installr contains the function updateR which can help smooth over such updates, while also updating any outdated packages.
As a side note, an update sometimes fails to update the actual packages or results in other packages being corrupted, as such if an error persists one solution is to simply delete and re-install the package (or the entire ~/Documents/R/win-library/3.z/ directory). In the question from OP the corrupt package is the broom package, as such one could re-install this package by running
remove.packages("broom")
install.packages("broom")
which should resolve any leftover issues. Note however multiple packages might be corrupt, and likely only one will be shown every time the function is executed. In such cases a full package clear will do the trick, but requires re-installing all packages. For this one can export all installed packages prior to removing them all, by noting that a full list of installed packages is contained in installed.packages(), which can then be exported to a file with for example write.table or write.csv.
I am attempting to fetch survey results via API using package qualtRics and command fetch_survey. fetch_survey, however, only returns the following error:
Error in parse_vector(x, col_factor(levels, ordered, include_na), na = na, :
is.character(x) is not TRUE
This technique has worked for me before. I am running RStudio Version 1.1.463 and qualtRics package version has been updated today. My API access is valid and correct, and my survey ID is also correct.
install.packages("qualtRics")
library(qualtRics)
qualtrics_api_credentials("MY_API_KEY", "MY_BASE_URL", install = TRUE)
qualtRics::fetch_survey("MY_SURVEY_ID")
My expected results are an output of the survey, my actual result is the listed error above.
Has anyone used 'tidytextmining' for sentiment analysis in R?
Tidytextmining
I am using R V 3.4.1 and I am getting the following error for this piece of code.
library(tidytext)
library(dplyr)
get_sentiments("afinn")
Error - Error in get_sentiments("afinn") :
could not find function "get_sentiments"
I have the right package installed and the library reference. What am I missing?
I tried your code and it's working just fine. Are you sure you have the right library reference? I would double-check!
I am trying to use the acs package in R to download Census data for a basic map, but I am unable to download the data and I'm receiving a confusing error message.
My code is as follows:
#Including all packages here in case this is somehow the issue
install.packages(c("choroplethr", "choroplethrMaps", "tidycensus", "tigris", "leaflet", "acs", "sf"))
library(choroplethr)
library(choroplethrMaps)
library(tidycensus)
library(tigris)
library(leaflet)
library(acs)
library(sf)
library(tidyverse)
api.key.install("my_api_key")
SD_geo <- geo.make(state="CA", county = 73, tract = "*", block.group = "*")
median_income <- acs.fetch(endyear = 2015, span = 5, geography = SD_geo, table.number = "B19013", col.names="pretty")
Everything appears to work until the final command, when I receive the following error message:
trying URL 'http://web.mit.edu/eglenn/www/acs/acs-variables/acs_5yr_2015_var.xml.gz'
Content type 'application/xml' length 735879 bytes (718 KB)
downloaded 718 KB
Error in if (url.test["statusMessage"] != "OK") { :
missing value where TRUE/FALSE needed
In addition: Warning message:
In (function (endyear, span = 5, dataset = "acs", keyword, table.name, :
XML variable lookup tables for this request
seem to be missing from ' https://api.census.gov/data/2015/acs5/variables.xml ';
temporarily downloading and using archived copies instead;
since this is *much* slower, recommend running
acs.tables.install()
This is puzzling to me because 1) it appears like something is in fact being downloaded at first? and 2) 'Error in if (url.test["statusMessage"] != "OK") { :
missing value where TRUE/FALSE needed' makes no sense to me. It doesn't align with any of the arguments in the function.
I have tried:
Downloading the tables using acs.tables.install() as recommended in the second half of the error message. Doesn't help.
Changing the endyear and span to be sure that I'm falling within the years of data supported by the API. I seem to be, according to the API documentation. Have also used the package default arguments with no luck.
Using 'variable =' and the code for the variable as found in the official API documentation. This returns only the two lines with the mysterious "Error in if..." message.
Removing colnames = "pretty"
I'm going to just download the datafile as a CSV and read it into R for now, but I'd like to be able to perform this function from the script for future maps. Any information on what's going on here would be appreciated. I am running R version 3.3.2. Also, I'm new to using this package and the API. But I'm following the documentation and can't find evidence that I'm doing anything wrong.
Tutorial I am working off of:
http://zevross.com/blog/2015/10/14/manipulating-and-mapping-us-census-data-in-r-using-the-acs-tigris-and-leaflet-packages-3/#get-the-tabular-data-acs
And documentation of the acs package: http://eglenn.scripts.mit.edu/citystate/wp-content/uploads/2013/02/wpid-working_with_acs_R2.pdf
To follow up on Brandon's comment, version 2.1.1 of the package is now on CRAN, which should resolve this issue.
Your code runs for me. My guess would be that the Census API was temporarily down.
As you loaded tidycensus and you'd like to do some mapping, you might also consider the following code:
library(tidycensus)
census_api_key("your key here") # use `install = TRUE` to install the key
options(tigris_use_cache = TRUE) # optional - to cache the Census shapefile
median_income <- get_acs(geography = "block group",
variables = "B19013_001",
state = "CA", county = "San Diego",
geometry = TRUE)
This will get you the data you need, along with feature geometry for mapping, as a tidy data frame.
I emailed Ezra Haber Glenn, the author of the package, about this as I was having the same issue. I received a response within 30 minutes and it was after midnight, which I thought was amazing. Long story short, the acs package version 2.1.0 is configured to work with the changes the Census Bureau is making to their API later this summer, and it is currently presenting some problems windows users in the mean time. Ezra is going to be releasing an update with a fix, but in the mean time I reverted back to version 2.0 and it works fine. I'm sure there are a few ways to do this, but I installed the devtools package and ran:
require(devtools)
install_version("acs", version = "2.0", repos = "http://cran.us.r-project.org")
Hope this helps anyone else having a similar issue.