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Geocoding is the process of converting addresses into geographic coordinates (latitude and longitude) that can be plotted on a map. In this tutorial, we’ll explore how to geocode data using R and visualize the results using the leaflet package.
Step 1: Loading the Required Libraries
The tidyverse
is a collection of R packages designed to make data manipulation and analysis easier and more efficient. It promotes a consistent and tidy data format and provides a set of tools that work seamlessly together.
dplyr
is a core package within the tidyverse
that provides a set of functions for data manipulation and transformation. It introduces a grammar of data manipulation, allowing you to express complex data operations in a concise and readable manner.
tidygeocoder
is an R package that provides geocoding functionality, allowing you to convert addresses into geographic coordinates (latitude and longitude). It leverages various geocoding services and APIs to retrieve the geolocation information.
Finally, leaflet
is an R package that provides an interactive and flexible mapping environment. It allows you to create interactive maps with various layers, markers, pop-ups, and other visual elements, making it an excellent tool for data visualization and exploration.
Step 2: Reading the Data
Step 3: Geocoding the Data
To geocode the addresses, we’ll use the geocode
function from the tidygeocoder
package. This function takes the address field as input and returns the latitude and longitude values.
Step 4: Cleaning the Data
It’s common to encounter null or missing values during the geocoding process. To remove these null values from the geocoded data, we can subset the dataframe using the subset
function.
Step 5: Saving the Geocoded Data
To save the geocoded data as a new CSV file, you can use the `write.csv` function.
To visualize the geocoded data on a map, we’ll utilize the leaflet
package. The leaflet
package provides an interactive mapping environment.
The code above creates a map using the geocoded data and adds circle markers for each location. You can customize the map appearance and markers according to your preference.
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