Unemployment rates in Texas

Occupational Employment Statistics Query SystemOES OES Program Links

library(tigris)

## To enable 
## caching of data, set `options(tigris_use_cache = TRUE)` in your R script or .Rprofile.

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## Attaching package: 'tigris'

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##     plot

library(rvest)

## Loading required package: xml2

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## Attaching package: 'rvest'

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##     pluck

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##     guess_encoding

library(leaflet)

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## Attaching package: 'leaflet'

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library(dplyr)
library(stringr)

All Employees: Mining: Oil and Gas Extraction in Texas (SMU48000001021100001)

Thousands of Persons, Not Seasonally Adjusted
Monthly

oil <-fredr_series_observations(series_id = "SMU48000001021100001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(oil) + geom_line(mapping = aes(x=date,y=value), 
                              color = "red4") +
  labs(title = "Employees: Oil and Gas Extraction in Texas", 
       subtitle = str_glue("Monthly from {min(oil$date)} through {max(oil$date)}"),
       x="Monthly", y="Thousands of workers",caption = "Illustration by @JoeLongSanDiego")+
    theme_economist()

## All Employees: Oil and Gas Extraction in Houston-The Woodlands-Sugar Land, TX (MSA) (SMU48264201021100001)

oil <-fredr_series_observations(series_id = "SMU48264201021100001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(oil) + geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4") +
  labs(title = "Employees in Oil and Gas Extraction in Houston Metropolitan", 
       subtitle =str_glue("Monthly from {min(oil$date)} through {max(oil$date)}"),
           x="Monthly", y="Thousands of workers",caption = "Illustration by @JoeLongSanDiego")+
  
  theme_economist()+
 scale_color_economist()

## Civilian Labor Force in Houston-The Woodlands-Sugar Land, TX (MSA) (HOUS448LFN)

labor <-fredr_series_observations(series_id = "HOUS448LFN",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(labor) + geom_line(mapping = aes(x=date,y=value), 
                              color = "brown4") +
  labs(title = "Civilian Labor Force in Houston Metropolitan, TX", 
       subtitle = str_glue("Monthly from {min(labor$date)} through {max(labor$date)}"),
           x="Monthly", y="Thousands of workers",caption = "Illustration by @JoeLongSanDiego")+
  theme_economist()+
 scale_color_economist()

## All Employees: Manufacturing in Texas (TXMFGN) * Thousands of Persons, Not Seasonally Adjusted

manufacturing <-fredr_series_observations(series_id = "TXMFGN", observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(manufacturing) + geom_line(mapping = aes(x=date,y=value), 
                              color = "green4") +
  labs(title = "All Employees: Manufacturing in Texas (TXMFG)", 
        subtitle = str_glue("Monthly from {min(manufacturing$date)} through {max(manufacturing$date)}"), 
       x="Monthly", y="Thousands of workers",caption = "Illustration by @JoeLongSanDiego")+
  theme_economist()

All Employees: Retail Trade in Texas (SMS48000004200000001)

retail <-fredr_series_observations(series_id = "SMS48000004200000001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(retail) + geom_line(mapping = aes(x=date,y=value), 
                              color = "goldenrod4") +
  labs(title = "All Employees: Retail Trade in Texas", 
        subtitle = str_glue("Monthly from {min(retail$date)} through {max(retail$date)}",
        x="Monthly", y="Thousands of workers",caption = "Illustration by @JoeLongSanDiego"))+
  theme_economist()

All Employees: Durable Goods: Motor Vehicle Manufacturing in Texas (SMU48000003133610001)

Thousands of Persons, Not Seasonally Adjusted

car <-fredr_series_observations(series_id = "SMU48000003133610001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(car) + geom_line(mapping = aes(x=date,y=value), color = "gold4") +
  labs(title = "All Employees: Car Manufacturing in Texas", 
        x="Monthly", y="Thousands of workers",caption = "Illustration by @JoeLongSanDiego",
   subtitle = str_glue("Monthly from {min(car$date)} through {max(car$date)}"))+
  theme_economist()

All Employees: Durable Goods: Semiconductor and Other Electronic Component Manufacturing in Texas (SMU48000003133440001)

Thousands of Persons, Not Seasonally Adjusted

indicator <-fredr_series_observations(series_id = "SMU48000003133440001",
        observation_start = as.Date("2019-01-01")) 

# plotting data
ggplot(indicator) + geom_line(mapping = aes(x=date,y=value), color = "gold4") +
  labs(title = "All Employees: Semiconductor & Electronic Manufacturing in Texas", 
        x="Monthly", y="Thousands of workers",caption = "Illustration by @JoeLongSanDiego",
   subtitle = str_glue("Monthly from {min(indicator$date)} through {max(indicator$date)}"))+
  theme_economist()

## M2V * M1 is defined by the Federal Reserve as the sum of all currency held by the public and transaction deposits at depository institutions. * M2 is a broader measure of money supply, adding in savings deposits, time deposits, and real money market mutual funds.

indicator <-fredr_series_observations(series_id = "M2V",
        observation_start = as.Date("1960-01-01")) 

# plotting data
ggplot(indicator) + geom_line(mapping = aes(x=date,y=value), color = "brown4") +
  labs(title = "M2 Velocity Since 1960", 
        x="Quarterly", y="Ratio",caption = "Illustration by @JoeLongSanDiego",
   subtitle = str_glue("Monthly from {min(indicator$date)} through {max(indicator$date)}"))+
  theme_economist()