Overview

Dataset statistics

Number of variables9
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory80.1 B

Variable types

Text1
Numeric5
Categorical3

Dataset

Description제주국제자유도시개발센터에서 서귀포시에 조성 중인 제주헬스케어타운 관련한 시설 및 용도, 면적 등 2018년 8월 기준의 상세내역
Author제주국제자유도시개발센터
URLhttps://www.data.go.kr/data/15071150/fileData.do

Alerts

면적 is highly overall correlated with 건폐율(퍼센트) and 1 other fieldsHigh correlation
건축면적(제곱미터) is highly overall correlated with 건축연면적(제곱미터) and 1 other fieldsHigh correlation
건축연면적(제곱미터) is highly overall correlated with 건축면적(제곱미터) and 2 other fieldsHigh correlation
건폐율(퍼센트) is highly overall correlated with 면적 and 3 other fieldsHigh correlation
용적률(퍼센트) is highly overall correlated with 건축면적(제곱미터) and 3 other fieldsHigh correlation
높이 is highly overall correlated with 건폐율(퍼센트) and 1 other fieldsHigh correlation
건축물용도 is highly overall correlated with 면적 and 1 other fieldsHigh correlation
객실수 is highly overall correlated with 건축연면적(제곱미터)High correlation
객실수 is highly imbalanced (62.7%)Imbalance
구분 has unique valuesUnique
면적 has unique valuesUnique
건축면적(제곱미터) has 10 (23.8%) zerosZeros
건축연면적(제곱미터) has 10 (23.8%) zerosZeros
건폐율(퍼센트) has 9 (21.4%) zerosZeros
용적률(퍼센트) has 9 (21.4%) zerosZeros

Reproduction

Analysis started2023-12-12 09:38:33.033597
Analysis finished2023-12-12 09:38:36.932547
Duration3.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T18:38:37.146108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7.5
Mean length5.6666667
Min length3

Characters and Unicode

Total characters238
Distinct characters98
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row도 로
2nd row보행자전용도로
3rd row중앙관리센터
4th row공용주차장
5th row저류지
ValueCountFrequency (%)
도 1
 
2.3%
로 1
 
2.3%
웰니스몰8 1
 
2.3%
경관녹지 1
 
2.3%
웰니스몰9 1
 
2.3%
워터파크 1
 
2.3%
재활훈련센터 1
 
2.3%
명상원 1
 
2.3%
헬스사이언스가든 1
 
2.3%
힐링가든 1
 
2.3%
Other values (34) 34
77.3%
2023-12-12T18:38:37.639020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 19
 
8.0%
트 14
 
5.9%
니 12
 
5.0%
리 9
 
3.8%
웰 9
 
3.8%
몰 9
 
3.8%
디 6
 
2.5%
컬 6
 
2.5%
터 6
 
2.5%
메 6
 
2.5%
Other values (88) 142
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 214
89.9%
Decimal Number 17
 
7.1%
Space Separator 4
 
1.7%
Uppercase Letter 2
 
0.8%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 19
 
8.9%
트 14
 
6.5%
니 12
 
5.6%
리 9
 
4.2%
웰 9
 
4.2%
몰 9
 
4.2%
디 6
 
2.8%
컬 6
 
2.8%
터 6
 
2.8%
메 6
 
2.8%
Other values (75) 118
55.1%
Decimal Number
ValueCountFrequency (%)
1 3
17.6%
2 3
17.6%
3 2
11.8%
6 2
11.8%
4 2
11.8%
5 2
11.8%
7 1
 
5.9%
8 1
 
5.9%
9 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
R 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 214
89.9%
Common 22
 
9.2%
Latin 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 19
 
8.9%
트 14
 
6.5%
니 12
 
5.6%
리 9
 
4.2%
웰 9
 
4.2%
몰 9
 
4.2%
디 6
 
2.8%
컬 6
 
2.8%
터 6
 
2.8%
메 6
 
2.8%
Other values (75) 118
55.1%
Common
ValueCountFrequency (%)
4
18.2%
1 3
13.6%
2 3
13.6%
3 2
9.1%
6 2
9.1%
4 2
9.1%
5 2
9.1%
& 1
 
4.5%
7 1
 
4.5%
8 1
 
4.5%
Latin
ValueCountFrequency (%)
D 1
50.0%
R 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 214
89.9%
ASCII 24
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 19
 
8.9%
트 14
 
6.5%
니 12
 
5.6%
리 9
 
4.2%
웰 9
 
4.2%
몰 9
 
4.2%
디 6
 
2.8%
컬 6
 
2.8%
터 6
 
2.8%
메 6
 
2.8%
Other values (75) 118
55.1%
ASCII
ValueCountFrequency (%)
4
16.7%
1 3
12.5%
2 3
12.5%
3 2
8.3%
6 2
8.3%
4 2
8.3%
5 2
8.3%
D 1
 
4.2%
& 1
 
4.2%
R 1
 
4.2%
Other values (3) 3
12.5%

면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36643.167
Minimum150
Maximum395634
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T18:38:37.823067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150
5-th percentile1994.8
Q16360.5
median14480.5
Q330711
95-th percentile115151.9
Maximum395634
Range395484
Interquartile range (IQR)24350.5

Descriptive statistics

Standard deviation66834.655
Coefficient of variation (CV)1.8239323
Kurtosis20.743084
Mean36643.167
Median Absolute Deviation (MAD)10629
Skewness4.1763768
Sum1539013
Variance4.4668711 × 109
MonotonicityNot monotonic
2023-12-12T18:38:38.004675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
160116 1
 
2.4%
6184 1
 
2.4%
15197 1
 
2.4%
31897 1
 
2.4%
23288 1
 
2.4%
20450 1
 
2.4%
13764 1
 
2.4%
15737 1
 
2.4%
63354 1
 
2.4%
6236 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
150 1
2.4%
1974 1
2.4%
1993 1
2.4%
2029 1
2.4%
2360 1
2.4%
2371 1
2.4%
5036 1
2.4%
5206 1
2.4%
5421 1
2.4%
6184 1
2.4%
ValueCountFrequency (%)
395634 1
2.4%
160116 1
2.4%
115407 1
2.4%
110305 1
2.4%
87426 1
2.4%
87334 1
2.4%
63354 1
2.4%
49829 1
2.4%
35274 1
2.4%
31897 1
2.4%

건축면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3709.0952
Minimum0
Maximum17922
Zeros10
Zeros (%)23.8%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T18:38:38.182324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1887.75
median2820
Q35612.5
95-th percentile10199.5
Maximum17922
Range17922
Interquartile range (IQR)4724.75

Descriptive statistics

Standard deviation3880.941
Coefficient of variation (CV)1.0463309
Kurtosis3.0164529
Mean3709.0952
Median Absolute Deviation (MAD)2785
Skewness1.5128338
Sum155782
Variance15061703
MonotonicityNot monotonic
2023-12-12T18:38:38.309294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 10
23.8%
7000 2
 
4.8%
4000 2
 
4.8%
3000 2
 
4.8%
1066 1
 
2.4%
4561 1
 
2.4%
5546 1
 
2.4%
7976 1
 
2.4%
3385 1
 
2.4%
2640 1
 
2.4%
Other values (20) 20
47.6%
ValueCountFrequency (%)
0 10
23.8%
882 1
 
2.4%
905 1
 
2.4%
916 1
 
2.4%
1055 1
 
2.4%
1066 1
 
2.4%
1500 1
 
2.4%
2125 1
 
2.4%
2260 1
 
2.4%
2390 1
 
2.4%
ValueCountFrequency (%)
17922 1
2.4%
10498 1
2.4%
10210 1
2.4%
10000 1
2.4%
9335 1
2.4%
7976 1
2.4%
7000 2
4.8%
6602 1
2.4%
6000 1
2.4%
5620 1
2.4%

건축연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12050.643
Minimum0
Maximum53929
Zeros10
Zeros (%)23.8%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T18:38:38.431296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11947.5
median7710
Q318167.25
95-th percentile36962.9
Maximum53929
Range53929
Interquartile range (IQR)16219.75

Descriptive statistics

Standard deviation13424.442
Coefficient of variation (CV)1.1140022
Kurtosis1.248252
Mean12050.643
Median Absolute Deviation (MAD)7710
Skewness1.3174929
Sum506127
Variance1.8021565 × 108
MonotonicityNot monotonic
2023-12-12T18:38:38.541322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 10
23.8%
12000 2
 
4.8%
16000 2
 
4.8%
2110 1
 
2.4%
18223 1
 
2.4%
26290 1
 
2.4%
9520 1
 
2.4%
7420 1
 
2.4%
8580 1
 
2.4%
5980 1
 
2.4%
Other values (21) 21
50.0%
ValueCountFrequency (%)
0 10
23.8%
1940 1
 
2.4%
1970 1
 
2.4%
2010 1
 
2.4%
2110 1
 
2.4%
2140 1
 
2.4%
4000 1
 
2.4%
4930 1
 
2.4%
5980 1
 
2.4%
6720 1
 
2.4%
ValueCountFrequency (%)
53929 1
2.4%
41315 1
2.4%
36965 1
2.4%
36923 1
2.4%
30000 1
2.4%
29000 1
2.4%
28000 1
2.4%
26290 1
2.4%
21000 1
2.4%
19482 1
2.4%

건폐율(퍼센트)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.642857
Minimum0
Maximum60
Zeros9
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T18:38:38.650718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median40
Q340
95-th percentile45
Maximum60
Range60
Interquartile range (IQR)20

Descriptive statistics

Standard deviation18.326073
Coefficient of variation (CV)0.61822897
Kurtosis-0.87535252
Mean29.642857
Median Absolute Deviation (MAD)5
Skewness-0.61112494
Sum1245
Variance335.84495
MonotonicityNot monotonic
2023-12-12T18:38:38.754686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
40 12
28.6%
0 9
21.4%
45 8
19.0%
20 4
 
9.5%
30 3
 
7.1%
35 3
 
7.1%
60 2
 
4.8%
10 1
 
2.4%
ValueCountFrequency (%)
0 9
21.4%
10 1
 
2.4%
20 4
 
9.5%
30 3
 
7.1%
35 3
 
7.1%
40 12
28.6%
45 8
19.0%
60 2
 
4.8%
ValueCountFrequency (%)
60 2
 
4.8%
45 8
19.0%
40 12
28.6%
35 3
 
7.1%
30 3
 
7.1%
20 4
 
9.5%
10 1
 
2.4%
0 9
21.4%

용적률(퍼센트)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.333333
Minimum0
Maximum200
Zeros9
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-12T18:38:38.875999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q160
median120
Q3120
95-th percentile160
Maximum200
Range200
Interquartile range (IQR)60

Descriptive statistics

Standard deviation59.864345
Coefficient of variation (CV)0.6414037
Kurtosis-0.98286238
Mean93.333333
Median Absolute Deviation (MAD)40
Skewness-0.46899745
Sum3920
Variance3583.7398
MonotonicityNot monotonic
2023-12-12T18:38:39.019720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
120 15
35.7%
0 9
21.4%
160 5
 
11.9%
60 4
 
9.5%
140 3
 
7.1%
80 2
 
4.8%
100 1
 
2.4%
180 1
 
2.4%
20 1
 
2.4%
200 1
 
2.4%
ValueCountFrequency (%)
0 9
21.4%
20 1
 
2.4%
60 4
 
9.5%
80 2
 
4.8%
100 1
 
2.4%
120 15
35.7%
140 3
 
7.1%
160 5
 
11.9%
180 1
 
2.4%
200 1
 
2.4%
ValueCountFrequency (%)
200 1
 
2.4%
180 1
 
2.4%
160 5
 
11.9%
140 3
 
7.1%
120 15
35.7%
100 1
 
2.4%
80 2
 
4.8%
60 4
 
9.5%
20 1
 
2.4%
0 9
21.4%

높이
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
12m(3층)이하
13 
15m(4층)이하
11 
0
9 
12m(4층)이하
4 
20m(5층)이하
 
1
Other values (4)
4 

Length

Max length9
Median length9
Mean length7.2857143
Min length1

Unique

Unique5 ?
Unique (%)11.9%

Sample

1st row0
2nd row0
3rd row12m(3층)이하
4th row0
5th row0

Common Values

ValueCountFrequency (%)
12m(3층)이하 13
31.0%
15m(4층)이하 11
26.2%
0 9
21.4%
12m(4층)이하 4
 
9.5%
20m(5층)이하 1
 
2.4%
20m(4층)이하 1
 
2.4%
15m(3층)이하 1
 
2.4%
12m(2층)이하 1
 
2.4%
15m(5층)이하 1
 
2.4%

Length

2023-12-12T18:38:39.176497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:38:39.322048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12m(3층)이하 13
31.0%
15m(4층)이하 11
26.2%
0 9
21.4%
12m(4층)이하 4
 
9.5%
20m(5층)이하 1
 
2.4%
20m(4층)이하 1
 
2.4%
15m(3층)이하 1
 
2.4%
12m(2층)이하 1
 
2.4%
15m(5층)이하 1
 
2.4%

건축물용도
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)47.6%
Missing0
Missing (%)0.0%
Memory size468.0 B
근린생활시설, 판매시설
9 
의료시설, 근린생활시설
8 
숙박시설, 근린생활시설
6 
의료시설, 교육연구시설, 근린생활시설
2 
교육연구시설, 근린생활시설
2 
Other values (15)
15 

Length

Max length20
Median length12
Mean length10.904762
Min length2

Unique

Unique15 ?
Unique (%)35.7%

Sample

1st row도로
2nd row보행자전용도로
3rd row업무시설, 근린생활시설
4th row공용주차장
5th row저류지

Common Values

ValueCountFrequency (%)
근린생활시설, 판매시설 9
21.4%
의료시설, 근린생활시설 8
19.0%
숙박시설, 근린생활시설 6
14.3%
의료시설, 교육연구시설, 근린생활시설 2
 
4.8%
교육연구시설, 근린생활시설 2
 
4.8%
숙박시설, 판매시설, 위락시설 1
 
2.4%
업무시설, 근린생활시설 1
 
2.4%
공용주차장 1
 
2.4%
저류지 1
 
2.4%
배수지 1
 
2.4%
Other values (10) 10
23.8%

Length

2023-12-12T18:38:39.480678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
근린생활시설 29
36.2%
의료시설 11
 
13.8%
판매시설 10
 
12.5%
숙박시설 7
 
8.8%
교육연구시설 4
 
5.0%
위락시설 2
 
2.5%
관광휴게시설 2
 
2.5%
보행자전용도로 1
 
1.2%
경관녹지 1
 
1.2%
문화및집회시설 1
 
1.2%
Other values (12) 12
15.0%

객실수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
해당없음
35 
188실
 
1
212실
 
1
228실
 
1
60실
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length3.952381
Min length3

Unique

Unique7 ?
Unique (%)16.7%

Sample

1st row해당없음
2nd row해당없음
3rd row해당없음
4th row해당없음
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 35
83.3%
188실 1
 
2.4%
212실 1
 
2.4%
228실 1
 
2.4%
60실 1
 
2.4%
80실 1
 
2.4%
312실 1
 
2.4%
255실 1
 
2.4%

Length

2023-12-12T18:38:39.605652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:38:39.714882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 35
83.3%
188실 1
 
2.4%
212실 1
 
2.4%
228실 1
 
2.4%
60실 1
 
2.4%
80실 1
 
2.4%
312실 1
 
2.4%
255실 1
 
2.4%

Interactions

2023-12-12T18:38:36.000152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.516753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.091250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.639289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:35.458387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:36.131565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.634279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.208410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.743568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:35.559225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:36.258462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.754338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.324359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.851945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:35.656918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:36.382454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.863214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.415889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.961145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:35.750598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:36.506809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.974184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.516267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:35.051027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:35.861270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:38:39.814283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분면적건축면적(제곱미터)건축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)높이건축물용도객실수
구분1.0001.0001.0001.0001.0001.0001.0001.0001.000
면적1.0001.0000.0000.0000.0000.2100.0000.9280.222
건축면적(제곱미터)1.0000.0001.0000.9330.7010.7370.4860.5240.725
건축연면적(제곱미터)1.0000.0000.9331.0000.6370.7740.8580.4130.864
건폐율(퍼센트)1.0000.0000.7010.6371.0000.9110.8470.9330.467
용적률(퍼센트)1.0000.2100.7370.7740.9111.0000.9730.5680.718
높이1.0000.0000.4860.8580.8470.9731.0000.8360.472
건축물용도1.0000.9280.5240.4130.9330.5680.8361.0000.000
객실수1.0000.2220.7250.8640.4670.7180.4720.0001.000
2023-12-12T18:38:39.923395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
높이객실수건축물용도
높이1.0000.2400.419
객실수0.2401.0000.000
건축물용도0.4190.0001.000
2023-12-12T18:38:40.015658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적건축면적(제곱미터)건축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)높이건축물용도객실수
면적1.0000.3150.307-0.521-0.1940.0000.5920.132
건축면적(제곱미터)0.3151.0000.9930.3900.6670.2640.1720.488
건축연면적(제곱미터)0.3070.9931.0000.4000.7040.4380.0870.646
건폐율(퍼센트)-0.5210.3900.4001.0000.7840.6300.5900.302
용적률(퍼센트)-0.1940.6670.7040.7841.0000.7160.0910.446
높이0.0000.2640.4380.6300.7161.0000.4190.240
건축물용도0.5920.1720.0870.5900.0910.4191.0000.000
객실수0.1320.4880.6460.3020.4460.2400.0001.000

Missing values

2023-12-12T18:38:36.660023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:38:36.857673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

구분면적건축면적(제곱미터)건축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)높이건축물용도객실수
0도 로16011600000도로해당없음
1보행자전용도로767000000보행자전용도로해당없음
2중앙관리센터11743300090004012012m(3층)이하업무시설, 근린생활시설해당없음
3공용주차장2507400000공용주차장해당없음
4저류지4982900000저류지해당없음
5배수지520600000배수지해당없음
6광 장3079000000광 장해당없음
7가압장15000000가압장해당없음
8휴양콘도미니엄1304749335369234016012m(4층)이하숙박시설, 근린생활시설188실
9휴양콘도미니엄23527410498413154016012m(4층)이하숙박시설, 근린생활시설212실
구분면적건축면적(제곱미터)건축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)높이건축물용도객실수
32메디컬스트리트26184239067204012012m(3층)이하의료시설, 근린생활시설해당없음
33메디컬스트리트35421212559804012012m(3층)이하의료시설, 근린생활시설해당없음
34메디컬스트리트47779305085804012012m(3층)이하의료시설, 근린생활시설해당없음
35메디컬스트리트56734264074204012012m(3층)이하의료시설, 근린생활시설해당없음
36메디컬스트리트68637338595204012012m(3층)이하의료시설, 근린생활시설해당없음
37의료R&D센터226597976262903514015m(4층)이하의료시설, 교육연구시설, 근린생활시설해당없음
38안티에이징센터280025546182233514015m(4층)이하의료시설, 교육연구시설, 근린생활시설해당없음
39기숙동129614561160003514015m(4층)이하교육연구시설, 근린생활시설해당없음
40경관녹지39563400000경관녹지해당없음
41완충녹지11030500000완충녹지해당없음