READY SIGNAL CONTROL DATA

Means Of Transportation To Work

Why Use This Data Source In Your Models?

The Census data on Means of Transportation to Work serves as a vital resource for urban planners, policymakers, and businesses, offering valuable insights into commuting patterns and transportation infrastructure needs. For urban planners, understanding how people commute—whether by car, public transit, bicycle, or foot—helps in designing efficient transportation systems, reducing congestion, and planning for sustainable urban development. Policymakers utilize this data to allocate resources for public transportation, roads, and bike lanes, aiming to enhance mobility and reduce environmental impact. Businesses also find this data invaluable. Retailers, for instance, can use commuting data to identify optimal locations for stores, understanding where potential customers reside and how they travel. Real estate developers use this information to gauge the desirability of residential properties, understanding the convenience of commuting options for potential buyers. Employers leverage this information to make decisions about office locations, offering convenient commutes to employees, thereby aiding in talent acquisition and retention strategies. Moreover, Means of Transportation to Work data is crucial for businesses involved in transportation services, helping them optimize routes, schedules, and services to meet the commuting needs of the population efficiently.

Means Of Transportation To Work

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Automated Data Profiling

Ready Signal automatically profiles each data set and offers up suggested industry standard data science treatments to utilize with these data in your models.

Suggested Treatment:

No treatments recommended.

Grain Transformation:

Data is able to be distributed by geography but not by time. The roll up method used is Sum.

Source:
US Census Bureau

Release:
2020 ACS 1-Year Experimental Data

Units:
Workers 16 years and over

Frequency:
Point in Time 2020

Suggested Treatment:

No treatments recommended.

Grain Transformation:

Data is able to be distributed by geography but not by time. The roll up method used is Sum.

Auto Correlation Analysis:

Trend Analysis:

Distribution Analysis:

Statistics (Pearson P/ df, lower => more normal)

No transform
NA
Box-cox
NA
Log_b(x-a)
NA
sqrt(x+a)
NA
exp(x)
NA
arcsinh(x)
NA
Yeo-Johnson
NA
OrderNorm
NA

Data Notes:

2020 ACS 1-Year Experimental Data

Citation:

U.S. Census Bureau, 2020 American Community Survey 1-Year Experimental Estimates, https://www.census.gov/programs-surveys/acs/data/experimental-data/1-year.html, Table XK200801. Means of Transportation to Work.

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