The API exchange is most commonly done through an HTTP request. For example a posted CSV file may be accessible simply by providing the site URL to import() as described in the section on importing from Github.* Note: recall that data may be posted* on a website without an API, which may be easier to retrieve. We will briefly give examples of use of APIs to import data, and link you to further resources. Needless to say, it is necessary to have an internet connection to import data via API. Others, such as platforms with user IDs and credentials, require authentication to access their data. Some sites are publicly available and can be accessed by anyone. The R packages httr and jsonlite can facilitate this process.Įach API-enabled website will have its own documentation and specifics to become familiar with. The client (you) sends a “request” and receives a “response” containing content.
#Praying in silence software#
APIs are a set of rules that allow one software application to interact with another. The imported file is saved as latest_file.Īn “Automated Programming Interface” (API) can be used to directly request data from a website. Finally we can pass this file path to import(). Then we can extract the file path of this latest file only with the dplyr function pull() on the column path. We can sort this data frame of files by the column modification_time, and then keep only the top/latest row (file) with base R’s head(). You can see a visual example of this in the page on Directory interactions.
The result is a data frame with one line per file and columns for modification_time, path, etc. In this case, the folder of interest is in the R project in the folder “data”, the sub-folder “example”, and its sub-folder “linelists”. Use functions from the package fs to examine the metadata information for each file, which includes the last modification time and the file path.īelow, we provide the folder of interest to fs’s dir_info(). If your files do not have dates in their names (or you do not trust those dates), you can try to extract the last modification date from the file metadata. here() file paths can be used for both importing and exportingįor example, below, the function import() is being provided a file path constructed with here().To build the file path, write the names of folders beyond the root, within quotes, separated by commas, finally ending with the file name and file extension as shown below.In your scripts, to reference a file in the R project’s sub-folders, you use the function here() to build the file path in relation to that anchor.When the here package is first loaded within the R project, it places a small file called “.here” in the root folder of your R project as a “benchmark” or “anchor”.This is how here() works within an R project: "C:/Users/Laura/Documents." by “starting” the file path in a place common to all users (the R project root). It prevents complications due to the unique file paths on different computers (e.g.
This is useful when the R project may be shared or accessed by multiple people/computers. Used in conjunction with an R project, here allows you to describe the location of files in your R project in relation to the R project’s root directory (the top-level folder). The package here and its function here() make it easy to tell R where to find and to save your files - in essence, it builds file paths. Import/export of shapefiles requires other packages, as detailed in the page on GIS basics.
It can also be used to import STATA, SAS, and SPSS files, among dozens of other file types. See the end of this page for a complete table of which packages/functions rio uses in the background. Rio’s functions import() and export() use the appropriate package and function for a given file, based on its file extension. These alternatives can be difficult to remember, whereas using import() and export() from rio is easy. For example, read.csv() ( base R), read.xlsx() ( openxlsx package), and write_csv() ( readr pacakge), etc. The alternative to using rio is to use functions from many other packages, each of which is specific to a type of file. When you provide a file path to either of these functions (including the file extension like “.csv”), rio will read the extension and use the correct tool to import or export the file. Its functions import() and export() can handle many different file types (e.g. .xlsx. The name “rio” is an abbreviation of “R I/O” (input/output). 46 Version control and collaboration with Git and Github.33 Demographic pyramids and Likert-scales.19 Univariate and multivariable regression.
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