in_classs
Aritra
rm(list = ls())#Importing libraries
library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.3 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.0
## ✔ purrr 1.0.2
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## ✖ dplyr::filter() masks stats::filter()
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(bea.R)## Loading required package: data.table
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## Attaching package: 'data.table'
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## yday, year
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## Note: As of February 2018, beaGet() requires 'TableName' for NIPA and NIUnderlyingDetail data instead of 'TableID.' See https://github.us-bea/bea.R for details.- Setup
# Setup API key
beaKey <- "485487AB-425F-4275-BB33-5E522472A238"#Assigning the key
beaSets(beaKey = beaKey)## No encoding supplied: defaulting to UTF-8.## $Dataset
## DatasetName DatasetDescription
## 1 NIPA Standard NIPA tables
## 2 NIUnderlyingDetail Standard NI underlying detail tables
## 3 MNE Multinational Enterprises
## 4 FixedAssets Standard Fixed Assets tables
## 5 ITA International Transactions Accounts
## 6 IIP International Investment Position
## 7 InputOutput Input-Output Data
## 8 IntlServTrade International Services Trade
## 9 IntlServSTA International Services Supplied Through Affiliates
## 10 GDPbyIndustry GDP by Industry
## 11 Regional Regional data sets
## 12 UnderlyingGDPbyIndustry Underlying GDP by Industry
## 13 APIDatasetMetaData Metadata about other API datasets
##
## attr(,"params")
## ParameterName ParameterValue
## 1 USERID 485487AB-425F-4275-BB33-5E522472A238
## 2 METHOD GETDATASETLIST
## 3 RESULTFORMAT JSONbeadf <- list(
"UserID" = beaKey,
"Method" = "GetData",
"datasetname" = "NIPA",
"TableName" = "T10705",
"Frequency" = "A",
"Year" = "X")beartd <- beaGet(beadf, asWide = FALSE)## No encoding supplied: defaulting to UTF-8.?beaGet#Studying dataset
unique(beartd$LineDescription)## [1] "Gross domestic product (GDP)"
## [2] "Plus: Income receipts from the rest of the world"
## [3] "Less: Income payments to the rest of the world"
## [4] "Equals: Gross national product"
## [5] "Less: Consumption of fixed capital"
## [6] "Private"
## [7] "Domestic business"
## [8] "Capital consumption allowances"
## [9] "Less: Capital consumption adjustment"
## [10] "Households and institutions"
## [11] "Government"
## [12] "General government"
## [13] "Government enterprises"
## [14] "Equals: Net national product"
## [15] "Less: Statistical discrepancy"
## [16] "Equals: National income"
## [17] "Corporate profits with inventory valuation and capital consumption adjustments"
## [18] "Taxes on production and imports less subsidies"
## [19] "Contributions for government social insurance, domestic"
## [20] "Net interest and miscellaneous payments on assets"
## [21] "Business current transfer payments (net)"
## [22] "Current surplus of government enterprises"
## [23] "Plus: Personal income receipts on assets"
## [24] "Plus: Personal current transfer receipts"
## [25] "Equals: Personal income"
## [26] "Gross domestic income (GDI)"
## [27] "Average of GDP and GDI"
## [28] "Gross national income"
## [29] "Gross national factor income"
## [30] "Net domestic product"
## [31] "Net domestic income"
## [32] "Net national factor income"
## [33] "Net domestic purchases"
## [34] "Statistical discrepancy as a percentage of GDP"# Filter the data for GDP
beadf_GDP <- beartd %>%
filter(LineDescription == "Gross domestic product (GDP)")range(beadf_GDP$TimePeriod)## [1] "1929" "2022"# Set up the plotting area
plot(beadf_GDP$TimePeriod,
beadf_GDP$DataValue,
type = "l", # Type: "l" for lines
col = "darkgreen", # Line color
xlab = "Year",
ylab = "GDP",
main = "GDP Over Time")
# Add grid lines for better readability
grid()
# Customize the legend if needed
legend("topright", legend = "GDP", col = "darkgreen", lty = 1)
Yes.
COVID-19 Pandemic (2020):
- Lockdowns and disruptions led to a decline in economic activity.
- Global supply chains were disrupted, affecting production and distribution.
- Decreased consumer spending due to job losses and reduced confidence.
2008 Financial Crisis:
- Triggered by the collapse of financial institutions and the subprime mortgage market.
- Financial market instability led to a freeze in credit markets.
- Housing market collapse resulted in reduced consumer spending and a global recession.
# Convert 'TimePeriod' column from characters to numeric
beadf_GDP$TimePeriod <- as.numeric(beadf_GDP$TimePeriod)
# verify class
class(beadf_GDP$TimePeriod)## [1] "numeric"#Checking for missing values
any(is.na(beadf_GDP$TimePeriod))## [1] FALSE#Omit missing values
beadf_GDP <- na.omit(beadf_GDP)library(ggplot2)
#Graph
ggplot(beadf_GDP, aes(x = TimePeriod, y = DataValue)) +
geom_line(color = "red") +
labs(title = "GDP Track", x = "Year", y = "GDP") +
theme_minimal()