Fetch stocks that have touched their 52 week high and low.

nse_stock_year_high(clean_names = TRUE)

nse_stock_year_low(clean_names = TRUE)

Arguments

clean_names

Logical; if TRUE, makes the column names descriptive and uses snake_case.

Value

A tibble with the following column names:

symbol

NSE ticker.

symbol_desc

Name of the firm.

date

Previous high date.

new_high

New 52 week high price.

new_low

New 52 week low price.

year

Year.

last_traded_price

Last traded price.

prev_high

Previous high price.

prev_low

Previous low price.

prev_close

Previous close price.

change

Change in price.

percent_change

Percentage change in price.

Examples

# \donttest{ # 52 week high nse_stock_year_high()
#> # A tibble: 24 x 10 #> symbol symbol_desc date new_high year last_traded_pri~ prev_high #> <chr> <chr> <date> <dbl> <dbl> <dbl> <dbl> #> 1 ADANI~ Adani Gree~ 2020-01-07 221. 2.21e2 221. 211. #> 2 ALKYL~ Alkyl Amin~ 2020-01-07 1250 1.25e3 1235 1250 #> 3 AMBER Amber Ente~ 2020-01-02 1230 1.23e3 1200. 1177. #> 4 BCP B.C. Power~ 2020-01-01 16.8 1.68e1 16.4 16.4 #> 5 CHEMB~ Chembond C~ 2019-12-02 250. 2.50e2 221 241. #> 6 GOLDB~ NIPPON IND~ 2020-01-06 36.9 3.69e1 36.3 36.8 #> 7 HDFCM~ HDFC Mutua~ 2020-01-06 3740. 3.74e3 3723 3728. #> 8 HLVLTD HLV LIMITED NA 5.95 5.95e0 5.85 NA #> 9 IIFLS~ IIFL Secur~ 2020-01-07 54.4 5.44e1 54.4 51.8 #> 10 JKCEM~ JK Cement ~ 2020-01-07 1315. 1.31e3 1279 1314. #> # ... with 14 more rows, and 3 more variables: prev_close <dbl>, change <dbl>, #> # percent_change <dbl>
# retain original column names as returned by NSE nse_stock_year_high(clean_names = FALSE)
#> # A tibble: 24 x 10 #> symbol symbolDesc dt value year ltp value_old prev change #> <chr> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 ADANI~ Adani Gre~ 2020-01-07 2.21e2 2.21e2 2.21e2 211. 2.11e2 10.5 #> 2 ALKYL~ Alkyl Ami~ 2020-01-07 1.25e3 1.25e3 1.24e3 1250 1.24e3 -6.65 #> 3 AMBER Amber Ent~ 2020-01-02 1.23e3 1.23e3 1.20e3 1177. 1.17e3 27.9 #> 4 BCP B.C. Powe~ 2020-01-01 1.68e1 1.68e1 1.64e1 16.4 1.60e1 0.45 #> 5 CHEMB~ Chembond ~ 2019-12-02 2.50e2 2.50e2 2.21e2 241. 2.13e2 8.1 #> 6 GOLDB~ NIPPON IN~ 2020-01-06 3.69e1 3.69e1 3.63e1 36.8 3.55e1 0.8 #> 7 HDFCM~ HDFC Mutu~ 2020-01-06 3.74e3 3.74e3 3.72e3 3728. 3.63e3 91.3 #> 8 HLVLTD HLV LIMIT~ NA 5.95e0 5.95e0 5.85e0 NA 5.85e0 0 #> 9 IIFLS~ IIFL Secu~ 2020-01-07 5.44e1 5.44e1 5.44e1 51.8 5.18e1 2.55 #> 10 JKCEM~ JK Cement~ 2020-01-07 1.31e3 1.31e3 1.28e3 1314. 1.28e3 -4 #> # ... with 14 more rows, and 1 more variable: pChange <dbl>
# 52 week low nse_stock_year_low()
#> # A tibble: 18 x 10 #> symbol symbol_desc date new_low year last_traded_pri~ prev_low #> <chr> <chr> <date> <dbl> <dbl> <dbl> <dbl> #> 1 APARI~ Apar Indus~ 2019-12-30 385 385 393. 385. #> 2 CENTE~ Century En~ 2019-08-22 154 154 176. 161. #> 3 CKFSL Cox & King~ 2019-11-06 0.35 0.35 0.4 0.35 #> 4 DQE DQ Enterta~ 2020-01-07 1.85 1.85 1.85 1.9 #> 5 GTLIN~ GTL Infras~ 2020-01-07 0.35 0.35 0.4 0.35 #> 6 HLVLTD HLV LIMITED NA 5.7 5.7 5.85 NA #> 7 INDIA~ Indian Bank 2020-01-07 97.2 97.2 98 98.1 #> 8 ITC ITC Limited 2019-09-18 233. 233. 234. 234. #> 9 J&KBA~ The Jammu ~ 2020-01-06 28.6 28.6 29 28.8 #> 10 MVL MVL Limited 2020-01-07 0.05 0.05 0.05 0.05 #> 11 RAJRA~ Raj Rayon ~ 2020-01-07 0.05 0.05 0.1 0.05 #> 12 REGEN~ Regency Ce~ 2020-01-02 1.4 1.4 1.4 1.45 #> 13 SMPL Splendid M~ 2020-01-03 0.1 0.1 0.15 0.1 #> 14 STAMP~ Stampede C~ 2020-01-07 0.35 0.35 0.4 0.35 #> 15 SUJAN~ Sujana Uni~ 2020-01-02 0.1 0.1 0.15 0.1 #> 16 VIKAS~ Vikas WSP ~ 2020-01-07 8.5 8.5 8.6 8.6 #> 17 VISES~ Visesh Inf~ 2020-01-07 0.05 0.05 0.05 0.05 #> 18 VISHAL Vishal Fab~ 2020-01-07 247 247 253 247 #> # ... with 3 more variables: prev_close <dbl>, change <dbl>, #> # percent_change <dbl>
# retain original column names as returned by NSE nse_stock_year_low(clean_names = FALSE)
#> # A tibble: 18 x 10 #> symbol symbolDesc dt value year ltp value_old prev change #> <chr> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 APARI~ Apar Indu~ 2019-12-30 385 385 393. 385. 395. -1.85 #> 2 CENTE~ Century E~ 2019-08-22 154 154 176. 161. 180. -3.95 #> 3 CKFSL Cox & Kin~ 2019-11-06 0.35 0.35 0.4 0.35 0.4 0 #> 4 DQE DQ Entert~ 2020-01-07 1.85 1.85 1.85 1.9 1.9 -0.05 #> 5 GTLIN~ GTL Infra~ 2020-01-07 0.35 0.35 0.4 0.35 0.4 0 #> 6 HLVLTD HLV LIMIT~ NA 5.7 5.7 5.85 NA 5.85 0 #> 7 INDIA~ Indian Ba~ 2020-01-07 97.2 97.2 98 98.1 99.6 -1.6 #> 8 ITC ITC Limit~ 2019-09-18 233. 233. 234. 234. 235. -1.2 #> 9 J&KBA~ The Jammu~ 2020-01-06 28.6 28.6 29 28.8 29.1 -0.1 #> 10 MVL MVL Limit~ 2020-01-07 0.05 0.05 0.05 0.05 0.1 -0.05 #> 11 RAJRA~ Raj Rayon~ 2020-01-07 0.05 0.05 0.1 0.05 0.1 0 #> 12 REGEN~ Regency C~ 2020-01-02 1.4 1.4 1.4 1.45 1.45 -0.05 #> 13 SMPL Splendid ~ 2020-01-03 0.1 0.1 0.15 0.1 0.15 0 #> 14 STAMP~ Stampede ~ 2020-01-07 0.35 0.35 0.4 0.35 0.4 0 #> 15 SUJAN~ Sujana Un~ 2020-01-02 0.1 0.1 0.15 0.1 0.15 0 #> 16 VIKAS~ Vikas WSP~ 2020-01-07 8.5 8.5 8.6 8.6 8.7 -0.1 #> 17 VISES~ Visesh In~ 2020-01-07 0.05 0.05 0.05 0.05 0.05 0 #> 18 VISHAL Vishal Fa~ 2020-01-07 247 247 253 247 247 6 #> # ... with 1 more variable: pChange <dbl>
# }