Financial data

with quantmod

Author

Tony Duan

Code

library(quantmod)
library(tidyverse)
library(yahoofinancer)
library(Quandl)
library(plotly)
library(finreportr)
library(rvest)

1 stock price

Code

nifty_50 <- Index$new('^NSEI')

data001=nifty_50$get_history(start = '2023-01-01', interval = '1d') %>% unnest(cols = adj_close)

a=head(data001$adj_close,1)[[1]]

data001b=data001 %>% mutate(adj_close2=adj_close/a)

Code

length(unlist(data001$adj_close))

[1] 528

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length(data001$adj_close)

[1] 528

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test=data001$adj_close %>% unlist()

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aapl <- Ticker$new('aapl')

data002=aapl$get_history(start = '2023-01-01', interval = '1d') %>% mutate(adj_close=adj_close %>% as.numeric())

a=head(data002$adj_close,1)[[1]]

data002b=data002 %>% mutate(adj_close2=adj_close/a)

Code

# initialize plot
fig <- plot_ly()

# add data from first dataframe Df1
fig <- fig %>%
    add_lines(data=data001b, name="NSEI50", x = ~date, y = ~adj_close2)

# add data from second dataframe Df2
fig <- fig %>%
    add_lines(data=data002b, name="apple", x = ~date, y = ~adj_close2)
# show figure
fig

2 financials income statement

Code

library(chromote)
library(httr)

Code

url='https://finance.yahoo.com/quote/AMAT/financials'

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b <- ChromoteSession$new()

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# In a web browser, open a viewer for the headless browser. Works best with
# Chromium-based browsers.
#b$view()
b$Page$navigate(url)

$frameId
[1] "6576FD94B556CF175D378FD965D36EB5"

$loaderId
[1] "C6A16C6616D37C0A2741BA44ADF3A92D"

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x <- b$DOM$getDocument()

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b$screenshot("sidebar.png")

[1] "An error occurred: Error in onRejected(...): code: -32000\n  message: Cannot take screenshot with 0 height.\n"

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page=b$Runtime$evaluate("document.querySelector('html').outerHTML")$result$value %>% 
  read_html()

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b$close()

[1] TRUE

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col1=page%>% 
  html_elements(".row .column:nth-child(1)") %>% html_text2()  %>% head(33)

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col2=page%>% 
  html_elements(".row .column:nth-child(2)") %>% html_text2()

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col3=page%>% 
  html_elements(".row .column:nth-child(3)") %>% html_text2()

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col4=page%>% 
  html_elements(".row .column:nth-child(4)") %>% html_text2()

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col5=page%>% 
  html_elements(".row .column:nth-child(5)") %>% html_text2()

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col6=page%>% 
  html_elements(".row .column:nth-child(6)") %>% html_text2()

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data001=data.frame(col1,col2,col3,col4,col5,col6)

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library(janitor )
colnames(data001) <- data001[1,]
data001 <- data001[-1, ]  %>%clean_names()

Code

glimpse(data001)

Rows: 32
Columns: 6
$ breakdown   <chr> "HTML_TAG_START HTML_TAG_END\nTotal Revenue", "Cost of Rev…
$ ttm         <chr> "27,635,000", "14,446,000", "13,189,000", "5,114,000", "8,…
$ x10_31_2024 <chr> "27,176,000", "14,279,000", "12,897,000", "5,030,000", "7,…
$ x10_31_2023 <chr> "26,517,000", "14,133,000", "12,384,000", "4,730,000", "7,…
$ x10_31_2022 <chr> "25,785,000", "13,792,000", "11,993,000", "4,209,000", "7,…
$ x10_31_2021 <chr> "23,063,000", "12,149,000", "10,914,000", "3,714,000", "7,…

Code

data002=data001 %>% mutate(breakdown=breakdown %>% str_remove_all('HTML_TAG_START HTML_TAG_END')
                           ,ttm=round(as.numeric(gsub(",","",ttm)))
                           ,year_2024=round(as.numeric(gsub(",","",x10_31_2024)))
                             ,year_2022=round(as.numeric(gsub(",","",x10_31_2022)))
                             ,year_2021=round(as.numeric(gsub(",","",x10_31_2021)))
                             ,year_2023=round(as.numeric(gsub(",","",x10_31_2023)))
                           ) %>% select(-x10_31_2023,-x10_31_2022,-x10_31_2021,-x10_31_2024)

Code

glimpse(data002)

Rows: 32
Columns: 6
$ breakdown <chr> "\nTotal Revenue", "Cost of Revenue", "Gross Profit", "\nOpe…
$ ttm       <dbl> 27635000, 14446000, 13189000, 5114000, 8075000, -107000, NA,…
$ year_2024 <dbl> 27176000, 14279000, 12897000, 5030000, 7867000, 285000, NA, …
$ year_2022 <dbl> 25785000, 13792000, 11993000, 4209000, 7784000, -189000, 400…
$ year_2021 <dbl> 23063000, 12149000, 10914000, 3714000, 7200000, -118000, -31…
$ year_2023 <dbl> 26517000, 14133000, 12384000, 4730000, 7654000, 62000, NA, 7…

Code

options(scipen = 999)

library(knitr)
kable(data002)

	breakdown	ttm	year_2024	year_2022	year_2021	year_2023
2	Total Revenue	27635000	27176000	25785000	23063000	26517000
3	Cost of Revenue	14446000	14279000	13792000	12149000	14133000
4	Gross Profit	13189000	12897000	11993000	10914000	12384000
5	Operating Expense	5114000	5030000	4209000	3714000	4730000
6	Operating Income	8075000	7867000	7784000	7200000	7654000
7	Net Non Operating Interest Income Expense	-107000	285000	-189000	-118000	62000
8	Other Income Expense	NA	NA	4000	-311000	NA
9	Pretax Income	7968000	8152000	7599000	6771000	7716000
10	Tax Provision	1625000	975000	1074000	883000	860000
11	Net Income Common Stockholders	6343000	7177000	6525000	5888000	6856000
12	Diluted NI Available to Com Stockholders	6343000	7177000	6525000	5888000	6856000
13	Basic EPS	8	9	7	6	8
14	Diluted EPS	8	9	7	6	8
15	Basic Average Shares	822750	827000	871000	910000	840000
16	Diluted Average Shares	829500	834000	877000	919000	845000
17	Total Operating Income as Reported	8075000	7867000	7788000	6889000	7654000
18	Total Expenses	19560000	19309000	18001000	15863000	18863000
19	Net Income from Continuing & Discontinued Operation	6343000	7177000	6525000	5888000	6856000
20	Normalized Income	6343000	7177000	6521564	6158570	6856000
21	Interest Income	145000	532000	39000	118000	300000
22	Interest Expense	252000	247000	228000	236000	238000
23	Net Interest Income	-107000	285000	-189000	-118000	62000
24	EBIT	8220000	8399000	7827000	7007000	7954000
25	EBITDA	8626000	8791000	8271000	7401000	8469000
26	Reconciled Cost of Revenue	14446000	14279000	13792000	12149000	14133000
27	Reconciled Depreciation	406000	392000	444000	394000	515000
28	Net Income from Continuing Operation Net Minority Interest	6343000	7177000	6525000	5888000	6856000
29	Total Unusual Items Excluding Goodwill	NA	NA	4000	-311000	NA
30	Total Unusual Items	NA	NA	4000	-311000	NA
31	Normalized EBITDA	8626000	8791000	8267000	7712000	8469000
32	Tax Rate for Calcs	0	0	0	0	0
33	Tax Effect of Unusual Items	NA	NA	564	-40430	NA

3 resource:

https://github.com/rsquaredacademy/yahoofinancer

https://github.com/sewardlee337/finreportr

https://www.youtube.com/watch?v=uVHGgSXtQmE