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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# nse2r
> Fetch data from the National Stock Exchange, India.
<!-- badges: start -->
[](https://cran.r-project.org/package=nse2r)
[](https://cran.r-project.org/web/checks/check_results_nse2r.html)
[](https://github.com/rsquaredacademy/nse2r/actions)
[](https://codecov.io/github/rsquaredacademy/nse2r?branch=master) [](https://lifecycle.r-lib.org/articles/stages.html)
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## Overview
[NSE](https://www.nseindia.com/) (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](https://nsetools.readthedocs.io/en/latest/). 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
You can install the development version of nse2r from [GitHub](https://github.com/rsquaredacademy/nse2r/) with:
```{r cran-install, eval=FALSE}
# install.packages("devtools")
devtools::install_github("rsquaredacademy/nse2r")
```
## Usage
```{r load_nse2r, echo=FALSE, message=FALSE, warning=FALSE}
library(nse2r)
```
nse2r uses consistent prefix `nse_` for easy tab completion.
- `nse_index_` for index
- `nse_stock_` for stocks
- `nse_fo_` for futures and options
- `nse_preopen_` for preopen data
## Preprocessing
nse2r does basic data preprocessing which are listed below:
- modify column data types from `character` to `numeric` and `Date`
- modify column names
- make them more descriptive
- to `snake_case` from `camelCase`
Users can retain the names and format as returned by NSE using the `clean_names` argument and setting it to `FALSE`.
### Index
##### Fetch Indices Quote
```{r index_quote}
nse_index_quote()
# retain original column names as returned by NSE
nse_index_quote(clean_names = FALSE)
```
### Stock
##### Top gainers for the last trading session.
```{r stock_top_gainers}
nse_stock_top_gainers()
# retain original column names as returned by NSE
nse_stock_top_gainers(clean_names = FALSE)
```
##### Stocks that have touched their 52 week highs during the day
```{r stock_year_high}
nse_stock_year_high()
# retain original column names as returned by NSE
nse_stock_year_high(clean_names = FALSE)
```
##### Most actively traded stocks in a month
```{r stock_most_traded}
nse_stock_most_traded()
# retain original column names as returned by NSE
nse_stock_most_traded(clean_names = FALSE)
```
### Futures & Options
##### Top futures and options gainers for the last trading session.
```{r fo_top_gainers}
nse_fo_top_gainers()
# retain original column names as returned by NSE
nse_fo_top_gainers(clean_names = FALSE)
```
### Pre Open Market Data
##### Fetch data of pre open session of Nifty Bank.
```{r popen_nb}
nse_preopen_nifty_bank()
# retain original column names as returned by NSE
nse_preopen_nifty(clean_names = FALSE)
```
### Advances & Declines
```{r advances_declines}
nse_advances_declines()
# retain original column names as returned by NSE
nse_advances_declines(clean_names = FALSE)
```