Construction employees in the construction sector include: Working supervisors, qualified craft workers, mechanics, apprentices, helpers, laborers, and so forth, engaged in new work, alterations, demolition, repair, maintenance, and the like, whether working at the site of construction or in shops or yards at jobs (such as precutting and preassembling) ordinarily performed by members of the construction trades. The series comes from the 'Current Employment Statistics (Establishment Survey).' The source code is: CES2023610001

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU06000002023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

Construction employees in the construction sector include: Working supervisors, qualified craft workers, mechanics, apprentices, helpers, laborers, and so forth, engaged in new work, alterations, demolition, repair, maintenance, and the like, whether working at the site of construction or in shops or yards at jobs (such as precutting and preassembling) ordinarily performed by members of the construction trades. The series comes from the 'Current Employment Statistics (Establishment Survey).' The source code is: CES2023800101

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU22000002023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU41000002023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU06360842023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU27334602023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU27000002023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU40000002023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU16000002023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU36000002023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU34000002023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU53000002023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU06310842023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU41389002023610001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.