2  Foundations of Accounting Data

Learning Objectives of the Chapter

At the End of the Chapter, Students should be Able to -

  • Gain an understanding about the types of accounting data

  • Gain an understanding about the sources of accounting data

  • Gain an understanding how accounting data can be collected

  • Gain an understanding how accounting data are evolving

  • Collect some accounting data

2.1 Types of Accounting Data

2.2 Data Sources and Collection Methods

2.3 Data Quality & Integrity

summary, this book has no content whatsoever.

1 + 1
[1] 2
plot(mtcars[1:3])

See Figure 2.1 for first ggplot graph

library(tidyverse)
mtcars %>% 
  as_tibble() %>% 
  ggplot(mapping = aes(x = mpg, y = disp))+
  geom_point()+
  geom_smooth()+
  labs(x = 'Miles Per Gallon (mpg)',
       y = 'Displacement in Cubic Inches (disp)')
Figure 2.1: Scatter plot and line plot of the relation between mpg and disp 
library(lubridate)
import os
import sys
sys.version
'3.11.0 (main, Oct 24 2022, 18:26:48) [MSC v.1933 64 bit (AMD64)]'
for x in os.listdir():
  print (x)
.env
.git
.gitattributes
.gitignore
.quarto
.README.md.swp
.README_BASE_1260.md.swp
.README_LOCAL_1260.md.swp
.README_REMOTE_1260.md.swp
.Rhistory
.vdoc.b7f6298e-a6af-42d8-806b-03c5619ab147.py
accounting_analytics_book
advanced_analytics.qmd
advanced_analytics.quarto_ipynb
advanced_analytics.quarto_ipynb_1
advanced_analytics.quarto_ipynb_2
advanced_analytics.quarto_ipynb_3
advanced_analytics.quarto_ipynb_4
advanced_analytics.quarto_ipynb_5
advanced_analytics.quarto_ipynb_6
advanced_analytics.quarto_ipynb_7
advanced_analytics.quarto_ipynb_8
chapter1_solution.qmd
chapter2_solution.qmd
cover.png
dashboard.qmd
dashboard.quarto_ipynb
dashboard.quarto_ipynb_1
dashboard.quarto_ipynb_2
dashboard.quarto_ipynb_3
dashboard.quarto_ipynb_4
dashboard.quarto_ipynb_5
dashboard.quarto_ipynb_6
dashboard.quarto_ipynb_7
dashboard.quarto_ipynb_8
DATA
data_management.qmd
eda.qmd
ethics.qmd
file3e9c78b886c
file6ed81b1d1d61
file729017a834a5
file83641dc16f6f
foundations.qmd
foundations.rmarkdown
foundations_files
fraud.qmd
future.qmd
images
index.aux
index.html
index.log
index.pdf
index.qmd
index.tex
index.toc
intro.qmd
machine_learning.qmd
machine_learning.quarto_ipynb
machine_learning.quarto_ipynb_1
machine_learning.quarto_ipynb_2
machine_learning.quarto_ipynb_3
machine_learning.quarto_ipynb_4
machine_learning.quarto_ipynb_5
machine_learning.quarto_ipynb_6
machine_learning.quarto_ipynb_7
machine_learning.quarto_ipynb_8
nlp.qmd
nlp.quarto_ipynb
nlp.quarto_ipynb_1
nlp.quarto_ipynb_2
nlp.quarto_ipynb_3
nlp.quarto_ipynb_4
nlp.quarto_ipynb_5
nlp.quarto_ipynb_6
nlp.quarto_ipynb_7
nlp.quarto_ipynb_8
overview.html
overview.qmd
performance_measurement.qmd
predictive.ipynb
predictive.qmd
prescriptive.qmd
python_basics.qmd
python_basics.quarto_ipynb
python_basics.quarto_ipynb_1
python_basics.quarto_ipynb_2
python_basics.quarto_ipynb_3
python_basics.quarto_ipynb_4
python_basics.quarto_ipynb_5
python_basics.quarto_ipynb_6
python_basics.quarto_ipynb_7
python_basics.quarto_ipynb_8
python_version_used.txt
README.html
README.md
README_files
references.bib
references.qmd
requirements.txt
r_basics.qmd
site_libs
visualization.qmd
_book
_quarto.yml