ConnectorSharepoint

In connector.sharepoint: 'Microsoft SharePoint' Interface for the 'connector' Package

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
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The connector.sharepoint package provides a convenient interface for accessing and interacting with Microsoft SharePoint sites directly from R.

Introduction

This vignette will guide you through the process of connecting to a SharePoint site, retrieving data, and performing various operations using this package.

Connecting to a SharePoint Site

Without connector package

To get started, you need to establish a connection to your SharePoint site. Use the connector_sharepoint() function to authenticate and connect to your SharePoint site. Here's an example of how to do this:

library(connector.sharepoint)

# Connect to SharePoint
con <- connector_sharepoint(site_url = "sharepoint_url")

With connector package (recommended)

If you are using the connector package, you can connect to a SharePoint site using the connect() function. This function based on a configuration file or a list creates a connectors() object with a connectorfor each of the specified datasources (for detailed explanation have a look at connector package).

Configuration file for connecting to SharePoint should look like this:

# An example of configuration file
metadata:
  trial: "0001"
  extra_class: "adam_connector"
  url: !!expr Sys.getenv("SHAREPOINT_SITE_URL")

datasources:
  - name: "adam"
    backend:
      type: "connector.sharepoint::connector_sharepoint"
      site_url: "{metadata.url}"
      folder: "{metadata.trial}/adam"
      extra_class: "{metadata.extra_class}"
  - name: "output"
    backend:
      type: "connector.sharepoint::connector_sharepoint"
      site_url: "{metadata.url}"
      folder: "{metadata.trial}/output"

Save this to _connector.yml file and use the connect() function to connect to SharePoint:

library(connector)

# Create connector object
db <- connect()

Now you can access the SharePoint site using the db object and adam field inside of it.

# Connection to SharePoint site. This will print object details
db$adam

After the setup is done we can use this connection to manipulate Sharepoint data.

Reading and writing data

The connector packages provide a set of functions to read and write data from the datasources. They all have similar interface, so it's easy to switch between them.

Now, we will show how to read and write different types data from/to Sharepoint. In these examples we will be using iris and mtcars datasets.

Here is an example of writing data to the ADaM table:

library(dplyr)

# Manipulate data

## Iris data
setosa <- iris |>
  filter(Species == "setosa")

mean_for_all_iris <- iris |>
  group_by(Species) |>
  summarise_all(list(mean, median, sd, min, max))

## mtcars data
cars <- mtcars |>
  filter(mpg > 22)

mean_for_all_mtcars <- mtcars |>
  group_by(gear) |>
  summarise(
    across(
      everything(),
      list("mean" = mean, "median" = median, "sd" = sd, "min" = min, "max" = max),
      .names = "{.col}_{.fn}"
    )
  ) |>
  tidyr::pivot_longer(
    cols = -gear,
    names_to = c(".value", "stat"),
    names_sep = "_"
  )

## Store data
db$adam |>
  write_cnt(x = setosa, name = "setosa.csv", overwrite = TRUE)

db$adam |>
  write_cnt(mean_for_all_iris, "mean_iris.csv", overwrite = TRUE)

db$adam |>
  write_cnt(cars, "cars_mpg.csv", overwrite = TRUE)

db$adam |>
  write_cnt(mean_for_all_mtcars, "mean_mtcars.csv", overwrite = TRUE)

Now, let's read the data back manipulate it a bit and write it to the SharePoint. This way we can save different types of data in different formats.

library(gt)
library(tidyr)
library(ggplot2)

# List and load data
db$adam |>
  list_content_cnt()

table <- db$adam |>
  read_cnt("mean_mtcars.csv")

gttable <- table |>
  gt(groupname_col = "gear")

# Save nontabular data to sharepoint
tmp_file <- tempfile(fileext = ".docx")
gtsave(gttable, tmp_file)
db$output |>
  upload_cnt(tmp_file, "tmeanallmtcars.docx")

# Manipulate data
setosa_fsetosa <- db$adam |>
  read_cnt("setosa.csv") |>
  filter(Sepal.Length > 5)

fsetosa <- ggplot(setosa) +
  aes(x = Sepal.Length, y = Sepal.Width) +
  geom_point()

## Store data into output location
db$output |>
  write_cnt(fsetosa$data, "fsetosa.csv")
db$output |>
  write_cnt(fsetosa, "fsetosa.rds")

tmp_file <- tempfile(fileext = ".png")
ggsave(tmp_file, fsetosa)
db$output |>
  upload_cnt(tmp_file, "fsetosa.png")

Conclusion

In this vignette we showed how to connect to SharePoint site, read and write data from it. We also showed how to use the connector package to connect to SharePoint and how to manipulate data using the connector package.

connector.sharepoint documentation built on June 1, 2026, 9:07 a.m.