UNMAINTAINED | R-package providing access to fundamental data and valuation metrics for thousands of publicly traded companies worldwide.

Last updated Dec 16, 2025
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README

Fetching Stock Data for Fundamental Analysis

The project relies on data provided by gurufocus.com and tipranks.com

This webscraping toolset provides functionalities for easily gathering stock data for up to the last five fiscal years.

📚 Extensive data for 6.000+ unique listings.
:memo: More than 50 different metrics.
📅 Data for the company's last five fiscal years and current years TTM value.
♻️ Convenient merging-abilities for updating past scraping results.

Demo

Prerequisite

Note that the installation of 'quant' requires RTools in order to build R and R packages from source on Windows.

Installation

# Github Download 'quant'-package (dev version)
devtools::install_github('OliverHennhoefer/quant')

Application

df <- data.frame("symbol" = c("AAPL", "MSFT", "BABA"))

Diluted Earnings per Share

df %>% getdilutedeps() > Symbol EPS2017 EPS2018 EPS2019 EPS2020 EPS2021 EPSTTM 1 AAPL 2.30 2.98 2.97 3.28 5.61 6.04 2 BABA 2.46 3.88 4.97 7.97 8.40 3.74 3 MSFT 3.25 2.13 5.06 5.76 8.05 9.39

Easily fetch several data for the most common financial measures or even more uncustomary ratios:

df <- data.frame("symbol" = c("AAPL", "MSFT", "BABA"))

Profitability Rank, Probability of Financial Distress

df %>% get_profitability() %>% getfinancialdistress() > Symbol Fin.Distress Profitability 1 AAPL 0.02 10 2 BABA 0.29 9 3 MSFT 0.03 10

Data Providers

gurufocus.com
tipranks.com
wikipedia.com
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