---
title: "Data Cleaning Part 2 Lab"
output: html_document
---

```{r}
library(tidyverse)
```


1. Read in the UFO dataset (used in the Data IO lectures) as an R object called `ufo`.
You can read directly from the web here: https://raw.githubusercontent.com/SISBID/Module1/gh-pages/data/ufo/ufo_data_complete.csv . 
You can ignore the "problems" with some rows. 

```{r}
library(readr)
ufo <- read_csv("https://raw.githubusercontent.com/SISBID/Module1/gh-pages/data/ufo/ufo_data_complete.csv")
```

Clean up the column/variable names of the `ufo` dataset to remove spaces and non-alphanumeric characters. You can use the `dplyr::rename()` function or look into the `janitor::clean_names()` function. 

```{r}
library(janitor)
ufo <- clean_names(ufo)
```

2. How many UFO sightings were reported on a time scale of minutes, specifically using the `duration (hours/min)` originally-named column? (hint: use `str_detect` and `filter`, you can ignore observations like "1/2 hour" and similar ones that don't contain some version of the word "minutes")

```{r}

```

3. How accurate is the (formerly-named) `duration (seconds)` column? I.e. how many of the above minutes-scale observations have durations less than 60 seconds or greater than 3600 seconds? 

```{r}

```

4. How many ufo sighting cities end in (a) "field", (b) "ton" and (c) "port"?


```{r}

```

