Get the Data

This article is an attempt to make .gif file on earthquake data from 1965-2016. It is better to plot year wise global seismic activity rather than a static look of all the values on the map. The data set for earthquake is available on Kaggle.
The data set contains data for global seismic activity from 1965 to 2016. Please visit the above link and scroll down to get the .csv file.

Data Manipulation

From the .csv file we have only selected few parameters for the sake of simplicity.

• Date
• Time
• Latitude
• Longitude
• Type is the type of seismic activity
• Depth is the distance of the epicenter from the seal level.
• Magnitude is the reading on the richter scale
• ID is the event ID of the seismic activity

We are all set to start coding in R. I have used RStudio environment. You are free to use any environment you prefer.

R Codes

## Read the datatset and load the necessary packages
library(plyr)
library(dplyr)
library(ggmap)
library(ggplot2)
library(gganimate)
EQ=read.csv("eq.csv",stringsAsFactors = FALSE)
names(EQ)
## Only Select the data with magnitude greater than or equal to 7.
EQ<-EQ%>%filter(Magnitude>=7)

Split the Date into year, month and date

This is done in order to get the frame which is important for the plot. In other words, The core of the approach is to treat frame
(as in, the time point within an animation) as another dimension, just like x, y, size, color, or so on. Thus, a variable in your data can be mapped to frame just as others are mapped to x or y.

## Convert the dates into character in order to split the coloumn into "dd" "mm" "yy"" columns
EQ$Date<-as.character(EQ$Date)

## Split the date and create a list for the same

list<-strsplit(EQ$Date,"-")

## Convert the list into dataframe
library(plyr)
EQ_Date1<-ldply(list)
colnames(EQ_Date1)<-c("Day","Month","Year")

## Column bind with the main dataframe
EQ<-cbind(EQ,EQ_Date1)
names(EQ)
## Change the Date to numeric
EQ$Year=as.numeric(EQ$Year)

## Get the world map for plot and load the necessary package
library(ggmap)
world<-map_data("world")

## Remove Antarctica region from the world map

world <- world[world$region != "Antarctica",]
map<-ggplot()+geom_map(data=world,map=world,aes(x=long,y=lat,map_id=region),color='#333300',fill='#663300')

#Plot points on world Map

p <- map + geom_point(data = EQ, aes(x = Longitude, y = Latitude, 
 frame = Year, 
 cumulative = TRUE,size=EQ$Magnitude), alpha = 0.3, 
 size = 2.5,color="#336600")+
 geom_jitter(width = 0.1) +labs(title = "Earthquake above 7 point on richter scale")+theme_void()

# Plot .gif file using gganimate function

gganimate(p)

Speed up projection in .gif using animation package

As we can see that plot has too many years from 1965 to 2016. Thus, in order to speed up the visualization, we can use the animation package to fast forward using ani.option()

library(animation)
ani.options(interval=0.15)
gganimate(p)

Conclusion

This article was an introductory tutorial to the world of animated map. Readers can try this and apply the same in other projects. Some of the example are,

• The same technology can be used to compare the heat map for the weather data across nation
• Flood or other natural disaster in a particular location over a period of time.
• Can be used to see the growth of metro in city using delaunay triangle. Please see the interesting article posted by Page Piccinini in r-Bloggers, Metro Systems over Time or you can directly access her page from her official site Page Piccinin.

Hope you found the article useful. If you have any questions, please feel free to ask in comments below.