#city wise temperature analysis St. Louis , Miss
require(ggplot2)
require(data.table)
require(knitr)
#install.packages("insol")
#install.packages("solaR")
# install.packages("sunshine") un available since 3.3.2
# require(sunshine)
require(solaR)
require(insol)
df <- fread("C:/Users/vivek/Documents/GlobalLandTemperatures/GlobalLandTemperaturesByCity.csv",showProgress =  TRUE)
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Read 8599212 rows and 7 (of 7) columns from 0.496 GB file in 00:00:25
df <- df[City=="Saint Louis"]
df<-df[Country =="United States"]

# doing above because there is another St.Louis even in Senegal!! 

# Remove the missing values
df <- na.omit(df)

kable(df[1:5,1:7])
dt AverageTemperature AverageTemperatureUncertainty City Country Latitude Longitude
1743-11-01 4.766 2.385 Saint Louis United States 39.38N 89.48W
1744-04-01 13.778 2.428 Saint Louis United States 39.38N 89.48W
1744-05-01 17.657 2.233 Saint Louis United States 39.38N 89.48W
1744-06-01 23.067 2.078 Saint Louis United States 39.38N 89.48W
1744-07-01 24.699 1.941 Saint Louis United States 39.38N 89.48W 
# Format the date field
df <- df[,dt:=as.Date(dt,"%Y-%m-%d")]

Month wise average temperatures in St.Louis

ggplot(df,aes(x=dt,y=AverageTemperature,colour=reorder(Month.String,-AverageTemperature,mean)))+
  geom_point()+
  geom_smooth(method="loess")+
  labs(title="Average Temperatures by Month in St.Louis",
       x="Year",
       y="Average Temperature",
       colour="Month")

As expected the June July August are the Hottest months, while February, December and January are coldest. There is a slight upward gradient in the Average temperatures in St.Louis.

Average Uncertaininty in Temperature 1743- Present

#temp uncertainity
ggplot(df,aes(x=dt,y=AverageTemperatureUncertainty))+
  geom_point(shape=1)+
  geom_smooth(method="loess")+
  labs(title="Average Temperature Uncertainty Over Time In St,Louis",
       x="Year",
       y="Average Temperature Uncertainty")

The decrease in average uncertainity, can be attributed to availability in reliable technology for the accurate collection and measurement of sensor data.

#closeup
ggplot(df[Year>1913,], aes(x=AverageTemperatureUncertainty)) + 
  geom_density()+
  labs(title="Density Plot of Temperature Uncertainty: St.Louis : 1913-Present")