User Guide

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These pages guide you on what data we provide in EconData, and how to access it. In our dataset docs, we outline hierarchies present in the data, in order to help you understand the datasets. We also outline the dataset IDs, and codes used in the series keys, to facilitate programmatic analysis.

  1. Installation
  2. Introduction
  3. Available Data (detailed list)
  4. Learning R Programming
  5. StatsSA
    1. Primary Sector Mining
    2. Secondary Sector Electricity, Manufacturing, Buildings
    3. Judiciary Civil Cases, Liquidations
    4. Price Indicies (Inflation) CPI, PPI, RPPI
    5. Travel Transport, Tourism
    6. Trade Cars, Retail, Wholesale
    7. Human Capital Population, QLFS, QES
    8. Finance AFS
  6. Prices and Inflation
    1. StatsSA CPI, PPI, RPPI
    2. Central Energy Fund Fuel prices
  7. Public Accounting
    1. National Treasury Government Budgets
    2. StatsSA National Accounts
  8. South African Reserve Bank (SARB)
    1. Data by sector External, Financial, Fiscal, National Accounts
    2. Indicators Business Cycles, Other Macroeconomic Indicators
    3. Monetary Policy Committee Forecasts
    4. Rates CPD Interest Rates, Market Rates
    5. Quarterly Bulletin
  9. Banking Sector Data Prudential Regulatory Reporting
    1. National Credit Regulator
  10. International
    1. International Monetary Fund World Economic Outlook
    2. World Bank
    3. Trade Customs
    4. New Zealand CPI
  11. Codera
    1. Financial Markets Foreign Exchange Forecasts
    2. Spatial Data Weather, Night Lights, Spatial Tax Panel
  12. ASISA
    1. Collective Investment Schemes Local Fund Holdings; Foreign
  13. Glossary

Registry

We have mirrored the most important data structures in our Registry in this User Guide (where you are now), to aid user experience. The pages here are static, but are easy to access.

Please go to https://registry.econdata.co.za/ to view the live version of metadata and SDMX structures in our database, including knowledge graphs.

Go to the EconData web app to browse or download data. All the dataflows, vintages, available series and metadata are available in the app. The app also shows data previews, simple plots, handles filters, and offers data export options via R code, or in .xlsx, .ods, .csv, .html or .txt format.

Accessing metadata with R

Using R, you could access the relevant metadata for a dataset with

library(econdatar)
data_raw <- read_dataset(id = "DATASET_ID",
                         tidy = TRUE,
                         wide = FALSE,
                         combine = FALSE)
str(data_raw)
view(as_tibble(data_raw$metadata))

replacing DATASET_ID with the dataset ID code. This will give you a data table in the first list item, separate to the metadata table in the second list item, where the series_key is the primary key.

You are able to access information on how our datasets are categorized, managed and structured, with the read_registry() function.