In this project you will be working with R, SQL, and Python in the same document. We will use the data sets *airlines* and *flights* from the package *nycflights13*.

**In R, install the packages ```nycflights13```, ```sqldf```, ```tydiverse``` and load all data sets and packages**. ```{r, warning=FALSE, message=FALSE} # Install code here - comment the code when you finish installation

# Load all packages here

# Load the data here

```

> **Question 1: List the name of airlines where the destination is ATL airport with their *average arrival delays* and sort them from the smallest to largest average arrival delays. Use data frames ```flights``` and ```airlines```.**

We shall solve this question using R, SQL, and Python.

### R solution You can use the R command ```inner_join()``` to join two tables.

```{r, warning=FALSE, message=FALSE} # Code here

```

### SQL solution Write your SQL query in the function ```sqldf()```. For example,```sqldf("select * from relig_income")``` list the data frame ```relig_income```. ```{r, warning=FALSE, message=FALSE } # Example # sqldf("select * from relig_income limit 3") # code here

```

### Python solution Use [df.join()](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.join.html) from pandas.

```{python} # load python libraries

# load data

# code here

```

> **Question 2: Plot the boxplot of the departure delays vs the name of airlines where the destination is ATL airport. Solve this question using R and Python.**

### R solution Use ggplot ```{r, warning=FALSE, message=FALSE} # code here

```

### Python solution You can use [pandas.boxplot()](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.boxplot.html) or [seaborn.boxplot()](https://seaborn.pydata.org/generated/seaborn.boxplot.html). You can either import data from the R package into Python or use the data Python package [nycflights13](https://pypi.org/project/nycflights13/)

```{python} # import python libraries

# data

# Boxplot

```