Working with the American community survey in R a guide to using the acs package /
This book serves as a hands-on guide to the "acs" R package for demographers, planners, and other researchers who work with American Community Survey (ACS) data. It gathers the most common problems associated with using ACS data and implements functions as a package in the R statistical pr...
| Main Author: | Glenn, Ezra. |
|---|---|
| Other Authors: | SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Cham :
Springer,
©2016.
Cham : [2016] |
| Physical Description: |
1 online resource. |
| Series: |
SpringerBriefs in statistics.
|
| Subjects: |
| Summary: |
This book serves as a hands-on guide to the "acs" R package for demographers, planners, and other researchers who work with American Community Survey (ACS) data. It gathers the most common problems associated with using ACS data and implements functions as a package in the R statistical programming language. The package defines a new "acs" class object (containing estimates, standard errors, and metadata for tables from the ACS) with methods to deal appropriately with common tasks (e.g., creating and combining subgroups or geographies, automatic fetching of data via the Census API, mathematical operations on estimates, tests of significance, plots of confidence intervals) |
|---|---|
| Item Description: |
Includes bibliographical references. Preface; Acknowledgments; Contents; 1 The Dawn of the ACS: The Nature of Estimates; 1.1 Challenges of Estimates in General; 1.2 Challenges of Multi-Year Estimates in Particular; 1.3 Additional Issues in Using ACS Data; 1.4 Putting it All Together: A Brief Example; 2 Getting Started in R; 2.1 Introduction; 2.2 Getting and Installing R; 2.3 Getting and Installing the acs Package; 2.3.1 Installing from cran; 2.3.2 Installing from a Zipped Tarball; 2.4 Getting and Installing a Census API Key; 2.4.1 Using a Blank Key: An Informal Workaround; 3 Working with the New Functions; 3.1 Overview. 3.2 User-Specific Geographies3.2.1 Basic Building Blocks: The Single Element geo.set; 3.2.2 But Where's the Data & ; 3.2.3 Real geo.sets: Complex Groups and Combinations; 3.2.4 Changing combine and combine.term; 3.2.5 Nested and Flat geo.sets; 3.2.6 Subsetting geo.sets; 3.2.7 Two Tools to Reduce Frustration in Selecting Geographies; 3.3 Getting Data; 3.3.1 acs.fetch(): The Workhorse Function; 3.3.2 More Descriptive Variable Names: col.names=; 3.3.3 The acs.lookup() Function: Finding the Variables You Want; 4 Exporting Data; 5 Additional Resources. A A Worked Example Using Blockgroup-Level Data and Nested Combined geo.setsA. 1 Making the geo.set; A.2 Using combine=T to Make a Neighborhood; A.3 Even More Complex geo.sets; A.4 Gathering Neighborhood Data on Transit Mode-Share; References. This book serves as a hands-on guide to the "acs" R package for demographers, planners, and other researchers who work with American Community Survey (ACS) data. It gathers the most common problems associated with using ACS data and implements functions as a package in the R statistical programming language. The package defines a new "acs" class object (containing estimates, standard errors, and metadata for tables from the ACS) with methods to deal appropriately with common tasks (e.g., creating and combining subgroups or geographies, automatic fetching of data via the Census API, mathematical operations on estimates, tests of significance, plots of confidence intervals) |
| Physical Description: |
1 online resource. |
| Bibliography: |
Includes bibliographical references. |
| ISBN: |
9783319457727 3319457721 |
| ISSN: |
2191-544X. |