R Notebook

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# Load library
library(readxl)
library(ggplot2)
library(scales)
library(grid)
library(gridExtra)
library(corrplot)
library(ggforce)
library(ggridges)
library(plyr)
library(plotly)
library(tibble)
library(data.table)
library(dplyr)
# Load the data
gis<-as.tibble(fread('D:/gis_BNAM/Book1.csv'))
# Show the structure of data
attach(gis)

The following objects are masked from gis (pos = 3):

    BIRT, CHIL, DEAT, EMPL, FIRM, FISC, FORE, HOSP, HPIA, LIBR, LIFE, LISP, MAGE,
    OBJECTID, PARK, PKSP, POP65, POPU, SHOP, SIEH, SUIC, TAX, WSTG, WSTR

The following objects are masked from gis (pos = 4):

    BIRT, CHIL, DEAT, EMPL, FIRM, FISC, FORE, HOSP, HPIA, LIBR, LIFE, LISP, MAGE,
    OBJECTID, PARK, PKSP, POP65, POPU, SHOP, SIEH, SUIC, TAX, WSTG, WSTR

The following objects are masked from gis (pos = 7):

    BIRT, CHIL, DEAT, EMPL, FIRM, FISC, FORE, HOSP, HPIA, LIBR, LIFE, LISP, MAGE,
    OBJECTID, PARK, PKSP, POP65, POPU, SHOP, SIEH, SUIC, TAX, WSTG, WSTR

The following objects are masked from gis (pos = 8):

    BIRT, CHIL, DEAT, EMPL, FIRM, FISC, FORE, HOSP, HPIA, LIBR, LIFE, LISP, MAGE,
    OBJECTID, PARK, PKSP, POP65, POPU, SHOP, SIEH, SUIC, TAX, WSTG, WSTR

summary(gis)

    OBJECTID       POPU            POP65            MAGE            FORE            LIFE      
 Min.   : 1   Min.   :134436   Min.   :20431   Min.   :39.10   Min.   : 1995   Min.   :80.27  
 1st Qu.: 7   1st Qu.:333615   1st Qu.:47319   1st Qu.:39.90   1st Qu.: 4583   1st Qu.:81.10  
 Median :13   Median :417209   Median :52401   Median :41.10   Median : 8671   Median :81.41  
 Mean   :13   Mean   :411313   Mean   :51211   Mean   :41.16   Mean   :10929   Mean   :81.48  
 3rd Qu.:19   3rd Qu.:487368   3rd Qu.:60958   3rd Qu.:41.90   3rd Qu.:13793   3rd Qu.:81.73  
 Max.   :25   Max.   :663904   Max.   :70311   Max.   :43.70   Max.   :38764   Max.   :83.14  
      BIRT           DEAT           SIEH            SUIC             TAX               FISC      
 Min.   : 905   Min.   : 683   Min.   : 5344   Min.   : 36.00   Min.   : 183257   Min.   :19.20  
 1st Qu.:2553   1st Qu.:1404   1st Qu.: 8799   1st Qu.: 68.00   1st Qu.: 277933   1st Qu.:25.50  
 Median :3480   Median :1666   Median :11170   Median : 93.00   Median : 354070   Median :31.30  
 Mean   :3348   Mean   :1686   Mean   :10928   Mean   : 98.68   Mean   : 524053   Mean   :36.22  
 3rd Qu.:4089   3rd Qu.:1968   3rd Qu.:12588   3rd Qu.:133.00   3rd Qu.: 523352   3rd Qu.:45.10  
 Max.   :6001   Max.   :2639   Max.   :16632   Max.   :158.00   Max.   :2130162   Max.   :65.20  
      FIRM            EMPL             HPIA            LISP            HOSP           LIBR     
 Min.   :18584   Min.   : 66137   Min.   :109.3   Min.   :23.45   Min.   : 619   Min.   : 400  
 1st Qu.:24760   1st Qu.:107496   1st Qu.:133.6   1st Qu.:25.48   1st Qu.:2386   1st Qu.:1070  
 Median :28047   Median :137079   Median :144.9   Median :27.71   Median :3185   Median :1428  
 Mean   :32512   Mean   :189595   Mean   :142.8   Mean   :27.50   Mean   :3414   Mean   :1688  
 3rd Qu.:36679   3rd Qu.:227966   3rd Qu.:150.5   3rd Qu.:28.38   3rd Qu.:3706   3rd Qu.:2278  
 Max.   :70262   Max.   :645060   Max.   :171.4   Max.   :34.97   Max.   :7306   Max.   :3391  
      PARK               PKSP             SHOP             CHIL            WSTG       
 Min.   : 1279518   Min.   : 65598   Min.   : 25521   Min.   : 66.0   Min.   : 641.7  
 1st Qu.: 3134003   1st Qu.:111803   1st Qu.: 42574   1st Qu.:192.0   1st Qu.:1024.0  
 Median : 4404111   Median :143921   Median : 73169   Median :244.0   Median :1192.2  
 Mean   : 6439076   Mean   :155093   Mean   :107749   Mean   :263.9   Mean   :1488.0  
 3rd Qu.:10069616   3rd Qu.:161648   3rd Qu.:111280   3rd Qu.:329.0   3rd Qu.:1860.8  
 Max.   :15874534   Max.   :379400   Max.   :521623   Max.   :521.0   Max.   :3225.7  
      WSTR       
 Min.   : 573.1  
 1st Qu.: 911.3  
 Median :1051.7  
 Mean   :1261.3  
 3rd Qu.:1710.7  
 Max.   :2401.7  

glimpse(gis)

Observations: 25
Variables: 24
$ OBJECTID <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 2...
$ POPU     <int> 163993, 134436, 247297, 304565, 374798, 373657, 418341, 468699, 333615, 3525...
$ POP65    <int> 24999, 20431, 35912, 38559, 40764, 52965, 54687, 63782, 53023, 49161, 69578,...
$ MAGE     <dbl> 42.8, 43.2, 41.9, 40.9, 39.6, 41.4, 42.4, 41.1, 43.7, 42.9, 41.1, 41.8, 41.4...
$ FORE     <int> 8851, 8671, 14613, 7990, 14715, 13793, 4736, 10249, 3557, 1995, 3741, 4583, ...
$ LIFE     <dbl> 81.06, 81.10, 81.90, 81.37, 81.87, 80.59, 80.51, 81.41, 80.52, 81.36, 81.26,...
$ BIRT     <int> 905, 1041, 1976, 2654, 3011, 2634, 3288, 3537, 2360, 2553, 4715, 4085, 2334,...
$ DEAT     <int> 864, 683, 1120, 1265, 1398, 1831, 1968, 2117, 1747, 1632, 2639, 2296, 1405, ...
$ SIEH     <int> 7604, 5344, 8391, 7562, 8799, 12050, 11714, 14530, 12588, 10228, 16632, 1542...
$ SUIC     <int> 36, 40, 70, 60, 67, 106, 147, 90, 101, 97, 158, 125, 60, 89, 93, 144, 92, 68...
$ TAX      <int> 662922, 1039202, 521257, 354070, 277933, 325385, 249836, 302951, 183257, 191...
$ FISC     <dbl> 54.6, 65.2, 47.1, 40.0, 32.3, 29.5, 23.3, 25.5, 22.8, 23.8, 19.2, 23.7, 30.1...
$ FIRM     <int> 40923, 65364, 20482, 25714, 24760, 32878, 28047, 25104, 19223, 18584, 26081,...
$ EMPL     <int> 245698, 380407, 126073, 152831, 117420, 137079, 99712, 107496, 70919, 66137,...
$ HPIA     <dbl> 146.0, 141.0, 135.3, 132.0, 143.8, 144.8, 159.7, 144.9, 160.1, 161.8, 171.4,...
$ LISP     <dbl> 30.45, 25.10, 30.81, 27.07, 26.08, 27.77, 25.14, 28.38, 23.54, 27.46, 24.34,...
$ HOSP     <int> 3277, 1580, 992, 1897, 2579, 5907, 3185, 3364, 2170, 2769, 3503, 3635, 3706,...
$ LIBR     <int> 3391, 892, 2037, 1922, 1282, 1098, 989, 1138, 811, 1752, 2819, 1252, 968, 14...
$ PARK     <int> 11575356, 3134003, 1795960, 3061710, 3396156, 1279518, 5231744, 8391240, 143...
$ PKSP     <int> 86478, 107313, 110751, 116675, 118208, 122229, 119592, 149216, 85446, 108858...
$ SHOP     <int> 196965, 521623, 32876, 63854, 85716, 314153, 126215, 88625, 73169, 35597, 42...
$ CHIL     <int> 79, 66, 129, 192, 221, 232, 262, 329, 192, 280, 521, 331, 172, 244, 353, 439...
$ WSTG     <dbl> 1860.8, 1574.8, 1210.2, 2700.2, 1099.4, 1014.9, 1165.6, 1117.6, 744.2, 641.7...
$ WSTR     <dbl> 1710.7, 1365.6, 1095.7, 1898.6, 997.2, 874.5, 1053.3, 994.2, 661.2, 573.1, 9...

# Visualising the data
plot(WSTG, WSTR,main="BNam and Ngoc")
abline(lm(WSTG~WSTR))

ID=c(gis$OBJECTID)
Type=c(rep("WSTG",25),rep("WSTR",25))
value=c(gis$WSTG,gis$WSTR)
data=data.frame(ID,Type,value)
ggplot(data, aes(fill=Type, y=value, x=ID)) + 
  geom_bar( stat="identity")