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We are excited to announce the nse2r package. NSE (National Stock Exchange) is the leading stock exchange of India, located in the city of Mumbai. While users can manually download data from NSE through a browser, importing this data into R becomes cumbersome. The nse2r R package implements the retrieval of data from NSE and aims to reduce the pre-processing steps needed in analyzing such data.
nse2r is inspired by and a port of the Python package nsetools. The authors and contributors for this R package are not affiliated with NSE and NSE does not offer support for this R package.
With nse2r, you can fetch the following data related to:
- stocks
- quote for a given stock
- stock description
- validate stock symbol/ticker
- most actively traded stocks in a month
- 52 week high/low
- top gainers/losers for the last trading session
- index
- list of NSE indices
- validate index symbol/ticker
- quote for a given index
- futures & options
- top gainers/losers for the last trading session
- pre open market data
- nifty
- nifty bank
- indices advances & declines
Installation
# Install release version from CRAN
install.packages("nse2r")
# Install development version from GitHub
# install.packages("devtools")
devtools::install_github("rsquaredacademy/nse2r")
Usage
nse2r uses consistent prefix nse_ for easy tab completion.
nse_index_for indexnse_stock_for stocksnse_fo_for futures and optionsnse_preopen_for preopen data
Preprocessing
nse2r does basic data preprocessing which are listed below:
- modify column data types from
charactertonumericandDate - modify column names
- make them more descriptive
- to
snake_casefromcamelCase
Users can retain the names and format as returned by NSE using the clean_names argument and setting it to FALSE.
Quick Overview
Fetch Indices Quote
nse_index_quote() ## # A tibble: 55 x 4 ## index_name last_traded_price change percent_change ## <chr> <dbl> <dbl> <dbl> ## 1 NIFTY 50 Pre Open 12328. -27.1 -0.22 ## 2 NIFTY 50 12371. 15.4 0.12 ## 3 NIFTY NEXT 50 29009. 30.2 0.1 ## 4 NIFTY100 LIQ 15 3794. -11.2 -0.290 ## 5 NIFTY BANK 31661. -193. -0.6 ## 6 INDIA VIX 14.4 0.24 1.67 ## 7 NIFTY 100 12486. 15.2 0.12 ## 8 NIFTY 500 10125. 15.4 0.15 ## 9 NIFTY MIDCAP 100 18037. 52.1 0.290 ## 10 NIFTY MIDCAP 50 4978. 9.5 0.19 ## # ... with 45 more rows # retain original column names as returned by NSE nse_index_quote(clean_names = FALSE) ## # A tibble: 55 x 4 ## name lastPrice change pChange ## <chr> <dbl> <dbl> <dbl> ## 1 NIFTY 50 Pre Open 12328. -27.1 -0.22 ## 2 NIFTY 50 12371. 15.4 0.12 ## 3 NIFTY NEXT 50 29009. 30.2 0.1 ## 4 NIFTY100 LIQ 15 3794. -11.2 -0.290 ## 5 NIFTY BANK 31661. -193. -0.6 ## 6 INDIA VIX 14.4 0.24 1.67 ## 7 NIFTY 100 12486. 15.2 0.12 ## 8 NIFTY 500 10125. 15.4 0.15 ## 9 NIFTY MIDCAP 100 18037. 52.1 0.290 ## 10 NIFTY MIDCAP 50 4978. 9.5 0.19 ## # ... with 45 more rows
Top gainers for the last trading session.
nse_stock_top_gainers() ## # A tibble: 10 x 12 ## symbol series last_corp_annou~ last_corp_annou~ open_price high_price ## <chr> <chr> <date> <chr> <dbl> <dbl> ## 1 BHART~ EQ 2019-04-23 Rights 19:67 @ ~ 475. 499. ## 2 RELIA~ EQ 2019-08-02 Annual General ~ 1554. 1572. ## 3 HEROM~ EQ 2019-07-16 Annual General ~ 2445 2475. ## 4 WIPRO EQ 2020-01-24 Interim Dividen~ 252 254. ## 5 M&M EQ 2019-07-18 Annual General ~ 567. 574. ## 6 NESTL~ EQ 2019-12-10 Interim Dividen~ 15399 15600 ## 7 DRRED~ EQ 2019-07-15 Annual General ~ 2944. 2990 ## 8 UPL EQ 2019-07-02 Bonus 1:2 590. 597. ## 9 EICHE~ EQ 2019-07-24 Annual General ~ 21509. 21770 ## 10 ULTRA~ EQ 2019-07-10 Annual General ~ 4440 4522. ## # ... with 6 more variables: low_price <dbl>, last_traded_price <dbl>, ## # prev_close_price <dbl>, percent_change <dbl>, traded_quantity <dbl>, ## # turnover_in_lakhs <dbl> # retain original column names as returned by NSE nse_stock_top_gainers(clean_names = FALSE) ## # A tibble: 10 x 12 ## symbol series lastCorpAnnounc~ lastCorpAnnounc~ openPrice highPrice ## <chr> <chr> <date> <chr> <dbl> <dbl> ## 1 BHART~ EQ 2019-04-23 Rights 19:67 @ ~ 475. 499. ## 2 RELIA~ EQ 2019-08-02 Annual General ~ 1554. 1572. ## 3 HEROM~ EQ 2019-07-16 Annual General ~ 2445 2475. ## 4 WIPRO EQ 2020-01-24 Interim Dividen~ 252 254. ## 5 M&M EQ 2019-07-18 Annual General ~ 567. 574. ## 6 NESTL~ EQ 2019-12-10 Interim Dividen~ 15399 15600 ## 7 DRRED~ EQ 2019-07-15 Annual General ~ 2944. 2990 ## 8 UPL EQ 2019-07-02 Bonus 1:2 590. 597. ## 9 EICHE~ EQ 2019-07-24 Annual General ~ 21509. 21770 ## 10 ULTRA~ EQ 2019-07-10 Annual General ~ 4440 4522. ## # ... with 6 more variables: lowPrice <dbl>, ltp <dbl>, ## # previousPrice <dbl>, netPrice <dbl>, tradedQuantity <dbl>, ## # turnoverInLakhs <dbl>
Stocks that have touched their 52 week highs during the day
nse_stock_year_high() ## # A tibble: 55 x 10 ## symbol symbol_desc date new_high year last_traded_pri~ prev_high ## <chr> <chr> <date> <dbl> <dbl> <dbl> <dbl> ## 1 AGCNET AGC Networ~ 2020-01-16 202. 202. 202. 193. ## 2 ALKYL~ Alkyl Amin~ 2020-01-16 1300 1300 1297. 1300 ## 3 APOLL~ Apollo Pip~ 2020-01-16 408. 408. 403 399 ## 4 AUBANK AU Small F~ 2020-01-16 888 888 874. 885. ## 5 AVANT~ Avanti Fee~ 2020-01-16 770 770 732. 756 ## 6 BAJAJ~ Bajaj Fins~ 2020-01-16 9681. 9681. 9656 9640 ## 7 BALKR~ Balkrishna~ 2020-01-16 1112. 1112. 1096 1107. ## 8 BCP B.C. Power~ 2020-01-16 20.2 20.2 19.0 20.0 ## 9 BERGE~ Berger Pai~ 2020-01-16 556. 556. 554. 550 ## 10 BHART~ Bharti Air~ 2019-12-02 499. 499. 493. 486. ## # ... with 45 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: 55 x 10 ## symbol symbolDesc dt value year ltp value_old prev ## <chr> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 AGCNET AGC Netwo~ 2020-01-16 202. 202. 202. 193. 193. ## 2 ALKYL~ Alkyl Ami~ 2020-01-16 1300 1300 1297. 1300 1296. ## 3 APOLL~ Apollo Pi~ 2020-01-16 408. 408. 403 399 395. ## 4 AUBANK AU Small ~ 2020-01-16 888 888 874. 885. 877. ## 5 AVANT~ Avanti Fe~ 2020-01-16 770 770 732. 756 746. ## 6 BAJAJ~ Bajaj Fin~ 2020-01-16 9681. 9681. 9656 9640 9622. ## 7 BALKR~ Balkrishn~ 2020-01-16 1112. 1112. 1096 1107. 1103. ## 8 BCP B.C. Powe~ 2020-01-16 20.2 20.2 19.0 20.0 19.6 ## 9 BERGE~ Berger Pa~ 2020-01-16 556. 556. 554. 550 547. ## 10 BHART~ Bharti Ai~ 2019-12-02 499. 499. 493. 486. 474. ## # ... with 45 more rows, and 2 more variables: change <dbl>, pChange <dbl>
Learning More
Feedback
All feedback is welcome. Issues (bugs and feature requests) can be posted to github tracker. For help with code or other related questions, feel free to reach out to us at pkgs@rsquaredacademy.com.
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