class2.1.Rmd

#Data Transformation
#package dplyr

```{r}
options(warn = 1)
library("nycflights13")
library("dplyr")
names(flights)
```

#filter
```{r}
jan1 <-filter(flights,month == 1, day == 1)
jan1
```

```{r}
nov_dec <- filter(flights, month %in% c(11,12))
nov_dec
```

#missing values

```{r}
x <-NA
is.na(x)
```

```{r}
df <- data.frame(x = c(1,2,NA,4,5))
filter(df,x>1)
```

```{r}
filter(df,is.na(x)|x>1)
```

```{r}
filter(df, is.na(x))
```

#Arrange
#simillar to order by

```{r}
arrange(flights,year,month,day)
```

```{r}
arrange(flights,desc(year,month,day))
```
```{r}
select(flights,year,day)
```


#select keyword 


```{r}
select(flights,year:day)
```
```{r}
select(flights,-(year:day))
```

#rename and mutate(calculated filed)

```{r}
renamed_df = rename(flights,tail_num = tailnum)
```
```{r}
mutated_df  = select(mutate(flights, day_month = day+month),day_month,day,month)
mutated_df
```


#summarize


```{r}
summarise(flights,delay=mean(dep_delay,na.rm=TRUE))
```

```{r}
by_day <- group_by(flights,year,month,day)
summarise(by_day,delay=mean(dep_delay,na.rm=TRUE))
```
#pipe
```{r}
flight_agg <- flights %>%
  group_by(year,month,day) %>%
  summarise(delay=mean(dep_delay,na.rm=TRUE))

flight_agg
```