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def pre_processing(dataset, my_stop_list):
    store = []
    ##Use contractions
    dataset['review_modified'] = dataset['review'].apply(lambda x: [contractions.fix(word) for word in x.split()])
    ##convert list to string
    dataset['review_modified_unlist'] = [' '.join(map(str, l)) for l in dataset['review_modified']]
    ##convert string to tokens
    dataset['review_mod_tokens'] = dataset['review_modified_unlist'].apply(nltk.word_tokenize)
    ##convert token to lower case

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my_stop_list_ = ['pizza', 'dominos', 'india', 'dominoz', 'swiggy', 'zomato', 'uber', 'amazonin',
'pizzahut', 'ok', 'okay', 'asia', 'kitchen', 'stir', 'order', 'dominos_india', 'party', 'twitter',
'pic', 'company', 'rt', 'jonerlichman', 'deliver', 'delivery', 'dollar', 'domino']

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```{r echo=FALSE, results='asis'}
library("rmarkdown")
library("tinytex")
library("stargazer")
library("sandwich")

m1 = lm(drat~ disp + hp + wt, data = mtcars)
m2 = lm(mpg~ disp + hp + wt, data = mtcars)

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```{r echo=FALSE, results='asis'}
library("rmarkdown")
library("tinytex")
library("stargazer")
library("sandwich")

m1 = lm(Fertility~ Agriculture, data = swiss)
m2 = lm(Fertility~ Agriculture + Examination, data = swiss)
m3 = lm(Fertility~ Agriculture + Examination + Education, data = swiss)
m4 = lm(Fertility~ Agriculture + Examination + Education + Catholic, data = swiss)

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---
title: "Getting familiar with Rmarkdown PDF"
author: |
  | Arimitra Maiti
  | Author-2
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
  pdf_document:
    keep_tex: yes
    latex_engine: pdflatex

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---
title: "Getting familiar with Rmarkdown PDF"
subtitle: | 
    | Examples for Towards Data Science
    | Focussing on Metadata
    | Reviewed by: Towards Data Science Team
author: | 
    | Arimitra Maiti
    | Author-2
thanks: | 

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---
title: "Getting familiar with Rmarkdown PDF"
subtitle: | 
    | Examples for Towards Data Science
    | Focussing on Metadata
    | Reviewed by: Towards Data Science Team
author: | 
    | Arimitra Maiti
    | Author-2
thanks: | 

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```{r setup, include=FALSE}
knitr::opts_chunk$set(warning = FALSE, message = FALSE)
```

### This is the common header for the document

This is some **notes** below the common header

### Please click on each tab to check results {.tabset}
#### Tab-1

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## Show regression outputs

```{r echo=FALSE}
library("sjPlot")
library("sjmisc")
library("sjlabelled")

data = read.csv("https://stats.idre.ucla.edu/stat/data/binary.csv")
data$rank <- factor(data$rank)

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## Show a table using kableExtra

```{r echo=FALSE}
library(kableExtra)
kable(VADeaths, longtable =T,booktabs =T,caption ="datasets::VADeaths") %>% add_header_above(c(" ","Rural Sample"=2,
                                                                                                         "Urban Sample"=2)) %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), font_size = 12)

```