Data Analysis and Visualization Part 2

Written by jutadmin in Data Visualization

SalaryProfessionRegion
126411Data ScientistSan Francisco
108402Data ScientistSan Francisco
99399Data ScientistSan Francisco
91381Data ScientistSan Francisco
105023Data ScientistSan Francisco
108944Data ScientistSan Francisco
123952Data ScientistSan Francisco
108217Data ScientistSan Francisco
103722Data ScientistSan Francisco
140179Data ScientistSan Francisco
116892Data ScientistSan Francisco
118661Data ScientistSan Francisco
116750Data ScientistSan Francisco
132715Data ScientistSan Francisco
139308Data ScientistSan Francisco
104449Data ScientistSan Francisco
126215Data ScientistSan Francisco
90123Data ScientistSan Francisco
101061Data ScientistSan Francisco
116180Data ScientistSan Francisco
105797Data ScientistSeattle
118749Data ScientistSeattle
118746Data ScientistSeattle
108190Data ScientistSeattle
104155Data ScientistSeattle
95080Data ScientistSeattle
97195Data ScientistSeattle
138768Data ScientistSeattle
118002Data ScientistSeattle
133437Data ScientistSeattle
101295Data ScientistSeattle
102315Data ScientistSeattle
111078Data ScientistSeattle
127669Data ScientistSeattle
103572Data ScientistSeattle
97341Data ScientistSeattle
118923Data ScientistSeattle
132107Data ScientistSeattle
110472Data ScientistSeattle
107652Data ScientistSeattle
75961Data ScientistNew York
75484Data ScientistNew York
116494Data ScientistNew York
99164Data ScientistNew York
76060Data ScientistNew York
116566Data ScientistNew York
77178Data ScientistNew York
87296Data ScientistNew York
100507Data ScientistNew York
107007Data ScientistNew York
79650Data ScientistNew York
81800Data ScientistNew York
105345Data ScientistNew York
87041Data ScientistNew York
128634Data ScientistNew York
84921Data ScientistNew York
91344Data ScientistNew York
72773Data ScientistNew York
96815Data ScientistNew York
92188Data ScientistNew York
92005Software EngineerSan Francisco
99327Software EngineerSan Francisco
126611Software EngineerSan Francisco
94824Software EngineerSan Francisco
96105Software EngineerSan Francisco
101344Software EngineerSan Francisco
109704Software EngineerSan Francisco
103746Software EngineerSan Francisco
116336Software EngineerSan Francisco
102952Software EngineerSan Francisco
89386Software EngineerSan Francisco
111197Software EngineerSan Francisco
114578Software EngineerSan Francisco
98308Software EngineerSan Francisco
113778Software EngineerSan Francisco
118666Software EngineerSan Francisco
116163Software EngineerSan Francisco
106534Software EngineerSan Francisco
92132Software EngineerSan Francisco
105606Software EngineerSan Francisco
94281Software EngineerSeattle
101006Software EngineerSeattle
87344Software EngineerSeattle
107018Software EngineerSeattle
104480Software EngineerSeattle
89333Software EngineerSeattle
103167Software EngineerSeattle
78263Software EngineerSeattle
90935Software EngineerSeattle
87181Software EngineerSeattle
90052Software EngineerSeattle
109727Software EngineerSeattle
74991Software EngineerSeattle
84309Software EngineerSeattle
95323Software EngineerSeattle
102464Software EngineerSeattle
84341Software EngineerSeattle
95533Software EngineerSeattle
116071Software EngineerSeattle
115156Software EngineerSeattle
96868Software EngineerNew York
88012Software EngineerNew York
110653Software EngineerNew York
85931Software EngineerNew York
79505Software EngineerNew York
72723Software EngineerNew York
92517Software EngineerNew York
106335Software EngineerNew York
92380Software EngineerNew York
87724Software EngineerNew York
93080Software EngineerNew York
85412Software EngineerNew York
95040Software EngineerNew York
90367Software EngineerNew York
81026Software EngineerNew York
102894Software EngineerNew York
94194Software EngineerNew York
107241Software EngineerNew York
88650Software EngineerNew York
80039Software EngineerNew York
78898BI EngineerSan Francisco
79420BI EngineerSan Francisco
89388BI EngineerSan Francisco
69050BI EngineerSan Francisco
81554BI EngineerSan Francisco
67235BI EngineerSan Francisco
67062BI EngineerSan Francisco
71902BI EngineerSan Francisco
93594BI EngineerSan Francisco
96299BI EngineerSan Francisco
75614BI EngineerSan Francisco
76899BI EngineerSan Francisco
95617BI EngineerSan Francisco
88354BI EngineerSan Francisco
63640BI EngineerSan Francisco
68403BI EngineerSan Francisco
78709BI EngineerSan Francisco
80797BI EngineerSan Francisco
75026BI EngineerSan Francisco
81341BI EngineerSan Francisco
81048BI EngineerSeattle
73819BI EngineerSeattle
87117BI EngineerSeattle
80532BI EngineerSeattle
83890BI EngineerSeattle
90094BI EngineerSeattle
77243BI EngineerSeattle
57646BI EngineerSeattle
84029BI EngineerSeattle
84038BI EngineerSeattle
81495BI EngineerSeattle
75725BI EngineerSeattle
77256BI EngineerSeattle
87649BI EngineerSeattle
67000BI EngineerSeattle
74265BI EngineerSeattle
80667BI EngineerSeattle
86757BI EngineerSeattle
68724BI EngineerSeattle
96103BI EngineerSeattle
78386BI EngineerNew York
102688BI EngineerNew York
99283BI EngineerNew York
85439BI EngineerNew York
71795BI EngineerNew York
73199BI EngineerNew York
72208BI EngineerNew York
77969BI EngineerNew York
64237BI EngineerNew York
85848BI EngineerNew York
65401BI EngineerNew York
70327BI EngineerNew York
79493BI EngineerNew York
73740BI EngineerNew York
65560BI EngineerNew York
72536BI EngineerNew York
69523BI EngineerNew York
72989BI EngineerNew York
89069BI EngineerNew York
80685BI EngineerNew York
Dataset

Importing the dataset to R as a .csv file

>sbr<- read.csv("salary_by_region.csv")
>head(sbr)
## Salary Profession Region
## 1 126411 Data Scientist San Francisco
## 2 108402 Data Scientist San Francisco
## 3 99399 Data Scientist San Francisco
## 4 91381 Data Scientist San Francisco
## 5 105023 Data Scientist San Francisco
## 6 108944 Data Scientist San Francisco

#Min Salary by Profession
>library('data.table')
>Profession_DT<- as.data.table(sbr)
>Profession_DT[, min(Salary),
by= Profession]
## Profession V1
## 1: Data Scientist 72773
## 2: Software Engineer 72723
## 3: BI Engineer 57646
#Max Salary by Profession
Profession_DT [, max(Salary), by= Profession]
## Profession V1
## 1: Data Scientist 140179
## 2: Software Engineer 126611
## 3: BI Engineer 102688
#Min Salary by Region
Profession_DT [, min(Salary), by= Region]

## Region V1
## 1: San Francisco 63640
## 2: Seattle 57646
## 3: New York 64237
#Max Salary by Region
Profession_DT [, max(Salary), by= Region]
## Region V1
## 1: San Francisco 140179
## 2: Seattle 138768
## 3: New York 128634

I converted the two categorical variables (Profession and Region) to factors.

>sbr$Profession <-as.factor(sbr$Profession)

>str(sbr$Profession)

Factor w/ 3 levels "New York","San Francisco",..: 2 2 2 2 2 2 2 2 2 2 ...

>sbr$Region<-as.factor(sbr$Region)
>str(sbr$Region)

Factor w/ 3 levels "New York","San Francisco",..: 2 2 2 2 2 2 2 2 2 2 ...

I created two boxplots of the variables to visually explore the data. The first plot is a boxplot of the Salaries of the three different professions by region while the second plot shows the three professions by their salaries alone.

>install.packages('ggpubr')
>library("ggpubr")

plot_s<-ggboxplot( sbr, x = "Profession", y = "Salary", color = "Region",
palette = c("#00AFBB", "#E7B800","#FC4E07" ))
plot_s +geom_jitter(color="Gray")+ ggtitle("Boxplot of Salary by Profession in 3 Regions")
Figure1: Boxplot of Salaries by Profession in the three Regions.

As can be seen from the above plot, the Data scientist group appears to be the highest paid of all three professions in all three regions followed by the Software Engineer group. New York is the least paying of all three professions.

sb<- ggplot(data=sbr,aes(x = Profession, y=Salary, color=Profession))

sb + geom_jitter() +geom_boxplot() +geom_point()+ 
  ggtitle("Boxplot of Salary by Profession")
Figure 2. Boxplot of Salary by Profession.

The boxplot shows that the overall median salary as well as the upper and lower quartiles of the Data Scientist group are the highest of all three professions, followed by that of the Software Engineer group.

I plotted a histogram to check for normality.

normality<-ggplot(data=sbr, aes( x=Salary))
normality+geom_histogram(binwidth = 5000,aes (fill=Region), color="Black")
Figure 3. Histogram of Salary

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