combined data.Rmd

---
title: "combined data"
author: "Fatemeh Nosrat"
date: "12/13/2018"
output: html_document
---

```{r }
#data in item_categories.csv
item_categories <- read.csv(file="/Users/fatemehnosrat/Desktop/Applied Regression/all-2/item_categories.csv",header = TRUE, na.strings=c("",".","NA"))

# a summary of item_categories
summary(item_categories)

# data in saless_train.csv
sales_train <- read.csv(file="/Users/fatemehnosrat/Desktop/Applied Regression/all-2/sales_train.csv",header = TRUE, na.strings=c("",".","NA"))

# a summary of sales_train
summary(sales_train)

#data in shops.csv
shops <- read.csv(file="/Users/fatemehnosrat/Desktop/Applied Regression/all-2/shops.csv",header = TRUE, na.strings=c("",".","NA"))

# a summary of shops.csv
summary(shops)
 
#data in items.csv
items <- read.csv(file="/Users/fatemehnosrat/Desktop/Applied Regression/all-2/items.csv",header = TRUE, na.strings=c("",".","NA"))

# a summary od shops
summary(items)
#data in test.csv
test <- read.csv(file="/Users/fatemehnosrat/Desktop/Applied Regression/all-2/test.csv",header = TRUE, na.strings=c("",".","NA"))

# a summary of test.csv
summary(test)

# loading plyr library, we need plyr to use "join"
library(plyr)

 #join 2 data frames (sales_train and items) by their common column (item_id) 
combined_data <- join (x = test, y = sales_train, by = c("shop_id"))

head(combined_data)

# a summary of combined_data
summary(combined_data)
```

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