Introducing nse2r
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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 10073. 26.0 0.26 ## 2 NIFTY 50 10116. 69.5 0.69 ## 3 NIFTY NEXT 50 25154. -8.9 -0.04 ## 4 NIFTY100 LIQ 15 2587 17.3 0.67 ## 5 NIFTY BANK 21100. 375. 1.81 ## 6 INDIA VIX 29.4 -0.77 -2.54 ## 7 NIFTY 100 10292. 60.4 0.59 ## 8 NIFTY 500 8293. 55.2 0.67 ## 9 NIFTY MIDCAP 100 14342 173. 1.22 ## 10 NIFTY MIDCAP 50 3993. 52 1.32 ## # ... 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 10073. 26.0 0.26 ## 2 NIFTY 50 10116. 69.5 0.69 ## 3 NIFTY NEXT 50 25154. -8.9 -0.04 ## 4 NIFTY100 LIQ 15 2587 17.3 0.67 ## 5 NIFTY BANK 21100. 375. 1.81 ## 6 INDIA VIX 29.4 -0.77 -2.54 ## 7 NIFTY 100 10292. 60.4 0.59 ## 8 NIFTY 500 8293. 55.2 0.67 ## 9 NIFTY MIDCAP 100 14342 173. 1.22 ## 10 NIFTY MIDCAP 50 3993. 52 1.32 ## # ... 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 INDUS~ EQ 2019-08-08 Annual General ~ 464 510. ## 2 HINDA~ EQ 2019-08-14 Annual General ~ 144. 148 ## 3 AXISB~ EQ 2019-07-04 Annual General ~ 422. 433. ## 4 SHREE~ EQ 2020-02-24 Interim Dividen~ 21171. 21611. ## 5 KOTAK~ EQ 2019-07-12 Annual General ~ 1304. 1344. ## 6 RELIA~ EQ 2020-05-13 Rights 1:15 @ P~ 1543. 1580. ## 7 SBIN EQ 2018-06-15 Annual General ~ 185. 189 ## 8 ICICI~ EQ 2019-07-22 Annual General ~ 349. 357. ## 9 HDFC EQ 2020-07-09 Annual General ~ 1784 1820 ## 10 TCS EQ 2020-06-03 Dividend - Rs 6~ 2077. 2132 ## # ... 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 lowPrice ## <chr> <chr> <date> <chr> <dbl> <dbl> <dbl> ## 1 INDUS~ EQ 2019-08-08 Annual General ~ 464 510. 463. ## 2 HINDA~ EQ 2019-08-14 Annual General ~ 144. 148 142. ## 3 AXISB~ EQ 2019-07-04 Annual General ~ 422. 433. 415. ## 4 SHREE~ EQ 2020-02-24 Interim Dividen~ 21171. 21611. 21150. ## 5 KOTAK~ EQ 2019-07-12 Annual General ~ 1304. 1344. 1304. ## 6 RELIA~ EQ 2020-05-13 Rights 1:15 @ P~ 1543. 1580. 1540. ## 7 SBIN EQ 2018-06-15 Annual General ~ 185. 189 184. ## 8 ICICI~ EQ 2019-07-22 Annual General ~ 349. 357. 345. ## 9 HDFC EQ 2020-07-09 Annual General ~ 1784 1820 1782 ## 10 TCS EQ 2020-06-03 Dividend - Rs 6~ 2077. 2132 2074. ## # ... with 5 more variables: 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: 34 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~ 2020-06-09 328. 328. 328. 313. ## 2 ALCHEM Alchemist ~ 2020-06-09 6.95 6.95 6.95 6.65 ## 3 ALOKI~ Alok Indus~ 2020-06-09 25.8 25.8 25.8 24.6 ## 4 ANDHR~ Andhra Cem~ 2020-06-09 5.35 5.35 5.35 5.1 ## 5 AUROP~ Aurobindo ~ 2020-06-04 800. 800. 796. 791 ## 6 BCG Brightcom ~ 2020-06-09 9.95 9.95 9.95 9.5 ## 7 BIRLA~ Birla Tyre~ 2020-06-09 23.5 23.5 23.5 22.4 ## 8 COMPU~ Compucom S~ 2020-06-09 10.8 10.8 10.8 10.6 ## 9 DAAWAT LT Foods L~ 2020-06-09 37.8 37.8 37.2 37 ## 10 DHANU~ Dhanuka Ag~ 2020-06-09 653. 653. 635. 620 ## # ... with 24 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: 34 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~ 2020-06-09 328. 328. 328. 313. 313. 15.6 ## 2 ALCHEM Alchemist~ 2020-06-09 6.95 6.95 6.95 6.65 6.65 0.3 ## 3 ALOKI~ Alok Indu~ 2020-06-09 25.8 25.8 25.8 24.6 24.6 1.2 ## 4 ANDHR~ Andhra Ce~ 2020-06-09 5.35 5.35 5.35 5.1 5.1 0.25 ## 5 AUROP~ Aurobindo~ 2020-06-04 800. 800. 796. 791 775. 21.1 ## 6 BCG Brightcom~ 2020-06-09 9.95 9.95 9.95 9.5 9.5 0.45 ## 7 BIRLA~ Birla Tyr~ 2020-06-09 23.5 23.5 23.5 22.4 22.4 1.1 ## 8 COMPU~ Compucom ~ 2020-06-09 10.8 10.8 10.8 10.6 10.3 0.5 ## 9 DAAWAT LT Foods ~ 2020-06-09 37.8 37.8 37.2 37 34.7 2.55 ## 10 DHANU~ Dhanuka A~ 2020-06-09 653. 653. 635. 620 594. 41.4 ## # ... with 24 more rows, and 1 more variable: 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 [email protected].
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