Posts | AKitsche Blog

Tidy Tuesday 52 2020

Thu, 07 Jan 2021 00:00:00 +0000

Hey folks,

this is the first of a series of blog post where I want to participate on the tidytuesday weekly social data project in R.

The intent of Tidy Tuesday is to provide a safe and supportive forum for individuals to practice their wrangling and data visualization skills independent of drawing conclusions.

The goal of this series is to help me

practice data visualization and data wrangling in R (R Core Team (2019)) using the tidyverse (Wickham et al. (2019))
adopt this skillset to learn Python
master to publish the applications using R Markdown

R code

Check the R code below:

lm(mpg ~ drat, data = mtcars)

Stata code

regress y x

R output

##
## Call:
## lm(formula = mpg ~ drat, data = mtcars)
##
## Coefficients:
## (Intercept) drat
## -7.525 7.678

References

R Core Team. 2019. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org.

Wickham, Hadley, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D’Agostino McGowan, Romain François, Garrett Grolemund, et al. 2019. “Welcome to the tidyverse.” Journal of Open Source Software 4 (43): 1686. https://doi.org/10.21105/joss.01686.

Bonsai Impression Spring 2018

Sun, 30 Apr 2017 21:13:14 -0500

During the last weeks I did some work including root cutting, potting and styling on a couple of my pre-bonsai trees. My collection consists of a stock of approximately 100 trees ranging from European oak (Quercus robur), small-leaved lime (Tilia cordata), pin oak (Quercus palustris), horse-chestnut (Aesculus hippocastanum), European beech (Fagus sylvatica), Ginkgo biloba, Common hazel (Corylus avellana), Creeping pine (Pinus mugo), Scots pine (Pinus sylvestris), English Yew (Taxus Baccata), … . Most of them are currently planted in the field.

The following gallery shows some impression in spring 2018:

Acer monspessulanum

Tilia cordata

Collection of pre-bonsais currently planted in the field

Ginkgo biloba

Tilia cordata

Aesculus hippocastanum

Ginkgo biloba

Connecting R with Salesforce.com

Thu, 23 Jul 2015 21:13:14 -0500

Hey folks,

this blog post will give a short introduction on how to connect salesforce.com with R. According to Takekatsu Hiramura

R statistical computing environment is the most populous statistical computing software, and Salesforce.com is the world´s most innovative cloud-computing based SaaS (Software-as-a-Service) CRM package.

To connect R with salesforce.com Takekatsu Hiramura developed the R add-on package RForcecom. The source code of the package is available from github. You can install the package from CRAN:

install.packages("RForcecom")
library(RForcecom)

To sign in to salesforce.com we can use the rforcecom.login() function. We have to set the username, password, instanceURL, apiVersion arguments as follows:

username <- "yourname@yourcompany.com"
password <- "YourPasswordSECURITY_TOKEN"
instanceURL <- "https://login.salesforce.com/"
apiVersion <- "26.0"
(session <- rforcecom.login(username, password, instanceURL, apiVersion))

Please note: do not forget your security token in the password field. The Salesforce community shows how to reset the security token.

Unfortunatly we probably get an error: Error in curl::curl_fetch_memory(url, handle = handle) : Couldn’t resolve host name, because the corporate network environment uses HTTP Proxy. To pick out the proxy setting we can use the ie_proxy_info() function from the curl R add-on package.:

#install.packages("curl")
library(curl)
ie_proxy_info()

Obviously the corporate network environment uses a global proxy auto-configuration (PUC) file that defines how web browsers and other user agents can automatically choose the appropriate proxy server. We can get the info of the proxy for a specific URL using the ie_get_proxy_for_url() function:

ie_get_proxy_for_url(target_url = "https://login.salesforce.com/")

The function returns a character string with two proxies and their corresponding port. We will further use the first proxy displayed: **. Now we have to set the proxy configurations with the set_config() and use_proxy() functions from the httr R add-on package:

#install.packages("httr")
library(httr)
proxy_for_url <- "your proxy" #from ie_get_proxy_for_url(target_url = "https://login.salesforce.com/")
port_for_url <- 8080
set_config(
use_proxy(url = proxy_for_url",
port = port_for_url,
username = "windows_username",
password = "windows_password",
auth = "ntlm")
)

Under some circumstances you will get the following error message at this point: Error in curl::curl_fetch_memory(url, handle = handle) : Problem with the SSL CA cert (path? access rights?). In this case your security certificate, e.g. curl-ca-bundle.crt is located in the wrong folder. You have to paste the file into C:/mingw64/ssl/certs.

Et voilà, we reached our goal to connect R with salesforce.com:

session <- rforcecom.login(username = username, password = password, loginURL = instanceURL, apiVersion = apiVersion)
session

Use the function rforcecom.retrieve() to retrieve a dataset:

rforcecom.retrieve(session = session,
objectName = "Contact",
fields = c("ID", "Name"),
limit = 50)

After setting up our environment these procedures are very easy and are very useful for projects using R and Salesforce.com. Please let me know if you have any further questions or suggestions.