Fetch data of pre open session of Nifty & Nifty Bank.

nse_preopen_nifty(clean_names = TRUE)

nse_preopen_nifty_bank(clean_names = TRUE)

Arguments

clean_names

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

Value

A tibble with the following columns:

symbol

NSE ticker.

series

Equity (EQ)

corp_action_date

Corporate action date.

corp_action

Corporate Action

price

Price

change

Change in price

percent_change

Percentage change in price.

prev_close

Previous close.

quantity

Quantity

value

Value (in lakhs),

mkt_cap

Free float market capitalization (in crores).

year_high

Normal market 52 week high.

year_low

Normal market 52 week low.

Examples

# \donttest{ # nifty nse_preopen_nifty()
#> # A tibble: 50 x 17 #> symbol series corp_action_date corp_action price change percent_change #> <chr> <chr> <date> <chr> <dbl> <dbl> <dbl> #> 1 TATAM~ EQ NA NA 180. -4.5 -2.44 #> 2 BPCL EQ NA NA 450 -11 -2.39 #> 3 SBIN EQ NA NA 312. -6.3 -1.98 #> 4 VEDL EQ NA NA 153. -2.75 -1.76 #> 5 ASIAN~ EQ 2019-10-30 INTERIM DI~ 1696 -28.4 -1.65 #> 6 UPL EQ NA NA 586. -9.3 -1.56 #> 7 ADANI~ EQ NA NA 379 -5.8 -1.51 #> 8 JSWST~ EQ NA NA 261. -3.85 -1.45 #> 9 AXISB~ EQ NA NA 715. -10.5 -1.45 #> 10 BAJFI~ EQ NA NA 3950 -57.6 -1.44 #> # ... with 40 more rows, and 10 more variables: prev_close <dbl>, #> # quantity <dbl>, value <dbl>, mkt_cap <dbl>, year_high <dbl>, #> # year_low <dbl>, sum_val <dbl>, sum_quantity <dbl>, fin_quantity <dbl>, #> # sum_fin_quantity <dbl>
# retain original column names as returned by NSE nse_preopen_nifty(clean_names = FALSE)
#> # A tibble: 50 x 17 #> symbol series xDt caAct iep chn perChn pCls trdQnty iVal mktCap #> <chr> <chr> <date> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 TATAM~ EQ NA NA 180. -4.5 -2.44 185. 71141 128. 3.31e4 #> 2 BPCL EQ NA NA 450 -11 -2.39 461 41761 188. 3.70e4 #> 3 SBIN EQ NA NA 312. -6.3 -1.98 318. 191444 598. 1.22e5 #> 4 VEDL EQ NA NA 153. -2.75 -1.76 156 67628 104. 2.84e4 #> 5 ASIAN~ EQ 2019-10-30 INTE~ 1696 -28.4 -1.65 1724. 9393 159. 7.77e4 #> 6 UPL EQ NA NA 586. -9.3 -1.56 595. 4609 27 3.27e4 #> 7 ADANI~ EQ NA NA 379 -5.8 -1.51 385. 10580 40.1 2.97e4 #> 8 JSWST~ EQ NA NA 261. -3.85 -1.45 265. 15277 39.9 2.69e4 #> 9 AXISB~ EQ NA NA 715. -10.5 -1.45 726. 21060 151. 1.62e5 #> 10 BAJFI~ EQ NA NA 3950 -57.6 -1.44 4008. 5710 226. 1.04e5 #> # ... with 40 more rows, and 6 more variables: yHigh <dbl>, yLow <dbl>, #> # sumVal <dbl>, sumQnty <dbl>, finQnty <dbl>, sumfinQnty <dbl>
# nifty bank nse_preopen_nifty_bank()
#> # A tibble: 12 x 17 #> symbol series corp_action_date corp_action price change percent_change #> <chr> <chr> <date> <chr> <dbl> <dbl> <dbl> #> 1 RBLBA~ EQ NA NA 335 -9 -2.62 #> 2 BANKB~ EQ NA NA 94 -2.15 -2.24 #> 3 SBIN EQ NA NA 312. -6.3 -1.98 #> 4 AXISB~ EQ NA NA 715. -10.5 -1.45 #> 5 INDUS~ EQ NA NA 1441 -20.6 -1.41 #> 6 PNB EQ NA NA 61 -0.85 -1.37 #> 7 ICICI~ EQ NA NA 516 -6.9 -1.32 #> 8 IDFCF~ EQ NA NA 43 -0.5 -1.15 #> 9 FEDER~ EQ NA NA 86.4 -0.95 -1.09 #> 10 HDFCB~ EQ NA NA 1247. -13.6 -1.08 #> 11 YESBA~ EQ NA NA 46.2 1.2 2.66 #> 12 KOTAK~ EQ NA NA 1655. -16.2 -0.97 #> # ... with 10 more variables: prev_close <dbl>, quantity <dbl>, value <dbl>, #> # mkt_cap <dbl>, year_high <dbl>, year_low <dbl>, sum_val <dbl>, #> # sum_quantity <dbl>, fin_quantity <dbl>, sum_fin_quantity <dbl>
# retain original column names as returned by NSE nse_preopen_nifty_bank(clean_names = FALSE)
#> # A tibble: 12 x 17 #> symbol series xDt caAct iep chn perChn pCls trdQnty iVal #> <chr> <chr> <date> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 RBLBA~ EQ NA NA 335 -9 -2.62 344 10557 35.4 #> 2 BANKB~ EQ NA NA 94 -2.15 -2.24 96.2 89008 83.7 #> 3 SBIN EQ NA NA 312. -6.3 -1.98 318. 191444 598. #> 4 AXISB~ EQ NA NA 715. -10.5 -1.45 726. 21060 151. #> 5 INDUS~ EQ NA NA 1441 -20.6 -1.41 1462. 7533 109. #> 6 PNB EQ NA NA 61 -0.85 -1.37 61.8 59892 36.5 #> 7 ICICI~ EQ NA NA 516 -6.9 -1.32 523. 72395 374. #> 8 IDFCF~ EQ NA NA 43 -0.5 -1.15 43.5 57043 24.5 #> 9 FEDER~ EQ NA NA 86.4 -0.95 -1.09 87.4 9282 8.02 #> 10 HDFCB~ EQ NA NA 1247. -13.6 -1.08 1261. 27486 343. #> 11 YESBA~ EQ NA NA 46.2 1.2 2.66 45.0 753830 349. #> 12 KOTAK~ EQ NA NA 1655. -16.2 -0.97 1671. 4373 72.4 #> # ... with 7 more variables: mktCap <dbl>, yHigh <dbl>, yLow <dbl>, #> # sumVal <dbl>, sumQnty <dbl>, finQnty <dbl>, sumfinQnty <dbl>
# }