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This is a Markdown document on bridging ArcGIS Pro and R. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

Install arcgisbinding and check connections with ArcGIS Pro
library(arcgisbinding)
## *** Please call arc.check_product() to define a desktop license.
arc.check_product()
## product: ArcGIS Pro (13.0.0.36056)
## license: Advanced
## version: 1.0.1.300
Set a working directory
setwd("D:/New Folder/RBridge")
Reading a geodatabase feature class into R
test_df <- arc.open(path = "D:\\New Folder\\MyProject2\\MyProject2.gdb\\CensusTracts_t_ExportFeature")
Bringing selected fields from a geodatabase feature class into R
test_select_df <- arc.select(object = test_df, fields = c('NAME', 'TOTPOP_CY', 'HHPOP_CY', 'FAMPOP_CY', 'GQPOP_CY', 'POPDENS_CY', 'TOTHH_CY', 'AVGHHSZ_CY'))

Convert your R data frame into a spatial data frame object using the arc.data2sp() function

library(sp)
## Warning: package 'sp' was built under R version 4.2.3
test_spdf <- arc.data2sp(test_select_df) 

Rename columns

col_names <- c("Census_tract", "Total_Populatio",
               "Household-Population", "Family_Population", "Group_Quarters_Population",
               "Population_Density", "Total_Households", "Average_Household_Size")

Assign renamed columns

colnames(test_spdf@data) <- col_names
head(test_spdf@data)
##   Census_tract Total_Populatio Household-Population Family_Population
## 1 060190079.03            6899                 2366              2131
## 2 060190080.00            4851                 4760              3942
## 3 060190081.00            6583                 6577              5666
## 4 060190083.01            6199                 6196              5303
## 5 060190083.03            4093                 4093              3811
## 6 060190083.04            4456                 3629              2893
##   Group_Quarters_Population Population_Density Total_Households
## 1                      4533                9.8              780
## 2                        91              767.8             1681
## 3                         6             2211.4             2106
## 4                         3              467.7             1431
## 5                         0              500.9              820
## 6                       827                9.0              896
##   Average_Household_Size
## 1                   3.03
## 2                   2.83
## 3                   3.12
## 4                   4.33
## 5                   4.99
## 6                   4.05

Write dataframe with renamed columns to CSV

write.csv(test_spdf@data, file = "SelectedRenamed.csv")

Bring in entire tract demographic data - all 9110 raws and 2781 columns

test_select_df2 <- arc.select(object = test_df)

Write entire dataframe from the tract demographic geodatabase to CSV

write.csv(test_select_df2, file = "AllFields.csv")

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