Overview

Dataset statistics

Number of variables14
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory117.6 B

Variable types

Categorical6
Text6
Numeric2

Dataset

Description제주국제자유도시개발센터에서 추진 중인 제주헬스케어타운 조성사업 시설 및 용도, 면적 등 2014년 4월 기준의 상세내역
Author제주국제자유도시개발센터
URLhttps://www.data.go.kr/data/15044077/fileData.do

Alerts

결정조서 건폐율(%) is highly overall correlated with 용적률(%) and 5 other fieldsHigh correlation
용적률(%) is highly overall correlated with 결정조서 건폐율(%) and 1 other fieldsHigh correlation
구 분 is highly overall correlated with 결정조서 건폐율(%) and 3 other fieldsHigh correlation
높이(층수) is highly overall correlated with 결정조서 건폐율(%) and 4 other fieldsHigh correlation
건축물용도 1 is highly overall correlated with 결정조서 건폐율(%) and 4 other fieldsHigh correlation
건축물용도 2 is highly overall correlated with 결정조서 건폐율(%) and 3 other fieldsHigh correlation
건축물용도 3 is highly overall correlated with 결정조서 건폐율(%) and 2 other fieldsHigh correlation
객실수 is highly overall correlated with 높이(층수)High correlation
건축물용도 3 is highly imbalanced (67.2%)Imbalance
객실수 is highly imbalanced (59.0%)Imbalance
구분(상세) has unique valuesUnique
결정조서 건폐율(%) has 8 (21.6%) zerosZeros
용적률(%) has 8 (21.6%) zerosZeros

Reproduction

Analysis started2023-12-12 07:03:07.043445
Analysis finished2023-12-12 07:03:08.922159
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구 분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size428.0 B
상가시설
9 
공공편익시설
7 
숙박시설
7 
기타시설(의료연구)
7 
휴양문화시설
3 
Other values (2)
4 

Length

Max length10
Median length6
Mean length5.6756757
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상가시설 9
24.3%
공공편익시설 7
18.9%
숙박시설 7
18.9%
기타시설(의료연구) 7
18.9%
휴양문화시설 3
 
8.1%
운동오락시설 2
 
5.4%
녹지 2
 
5.4%

Length

2023-12-12T16:03:09.032828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:09.185546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상가시설 9
24.3%
공공편익시설 7
18.9%
숙박시설 7
18.9%
기타시설(의료연구 7
18.9%
휴양문화시설 3
 
8.1%
운동오락시설 2
 
5.4%
녹지 2
 
5.4%

구분(상세)
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T16:03:09.499138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length5.4864865
Min length3

Characters and Unicode

Total characters203
Distinct characters97
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

Unique37 ?
Unique (%)100.0%

Sample

1st row도 로
2nd row보행자전용도로
3rd row중앙관리센터
4th row공용주차장
5th row저류지
ValueCountFrequency (%)
도 1
 
2.5%
로 1
 
2.5%
웰니스몰6 1
 
2.5%
웰니스몰7 1
 
2.5%
웰니스몰8 1
 
2.5%
웰니스몰9 1
 
2.5%
워터파크 1
 
2.5%
재활훈련센터 1
 
2.5%
명상원 1
 
2.5%
헬스사이언스가든 1
 
2.5%
Other values (30) 30
75.0%
2023-12-12T16:03:09.963951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 15
 
7.4%
니 12
 
5.9%
몰 9
 
4.4%
웰 9
 
4.4%
터 6
 
3.0%
센 5
 
2.5%
트 5
 
2.5%
리 5
 
2.5%
지 4
 
2.0%
도 4
 
2.0%
Other values (87) 129
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 183
90.1%
Decimal Number 13
 
6.4%
Space Separator 4
 
2.0%
Uppercase Letter 2
 
1.0%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 15
 
8.2%
니 12
 
6.6%
몰 9
 
4.9%
웰 9
 
4.9%
터 6
 
3.3%
센 5
 
2.7%
트 5
 
2.7%
리 5
 
2.7%
지 4
 
2.2%
도 4
 
2.2%
Other values (74) 109
59.6%
Decimal Number
ValueCountFrequency (%)
2 3
23.1%
1 3
23.1%
5 1
 
7.7%
3 1
 
7.7%
4 1
 
7.7%
6 1
 
7.7%
7 1
 
7.7%
8 1
 
7.7%
9 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
R 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 183
90.1%
Common 18
 
8.9%
Latin 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 15
 
8.2%
니 12
 
6.6%
몰 9
 
4.9%
웰 9
 
4.9%
터 6
 
3.3%
센 5
 
2.7%
트 5
 
2.7%
리 5
 
2.7%
지 4
 
2.2%
도 4
 
2.2%
Other values (74) 109
59.6%
Common
ValueCountFrequency (%)
4
22.2%
2 3
16.7%
1 3
16.7%
& 1
 
5.6%
5 1
 
5.6%
3 1
 
5.6%
4 1
 
5.6%
6 1
 
5.6%
7 1
 
5.6%
8 1
 
5.6%
Latin
ValueCountFrequency (%)
R 1
50.0%
D 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 183
90.1%
ASCII 20
 
9.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 15
 
8.2%
니 12
 
6.6%
몰 9
 
4.9%
웰 9
 
4.9%
터 6
 
3.3%
센 5
 
2.7%
트 5
 
2.7%
리 5
 
2.7%
지 4
 
2.2%
도 4
 
2.2%
Other values (74) 109
59.6%
ASCII
ValueCountFrequency (%)
4
20.0%
2 3
15.0%
1 3
15.0%
R 1
 
5.0%
& 1
 
5.0%
D 1
 
5.0%
5 1
 
5.0%
3 1
 
5.0%
4 1
 
5.0%
6 1
 
5.0%
Other values (3) 3
15.0%

면적(㎡)
Text

Distinct36
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T16:03:10.232771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.8378378
Min length5

Characters and Unicode

Total characters216
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)94.6%

Sample

1st row160,674
2nd row7,595
3rd row11,798
4th row25,063
5th row49,824
ValueCountFrequency (%)
15,169 2
 
5.4%
160,674 1
 
2.7%
20,413 1
 
2.7%
7,595 1
 
2.7%
5,026 1
 
2.7%
9,988 1
 
2.7%
2,370 1
 
2.7%
31,897 1
 
2.7%
23,253 1
 
2.7%
14,047 1
 
2.7%
Other values (26) 26
70.3%
2023-12-12T16:03:10.626017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 37
17.1%
2 24
11.1%
1 22
10.2%
3 21
9.7%
4 20
9.3%
0 19
8.8%
5 17
7.9%
6 15
6.9%
7 14
 
6.5%
8 14
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 179
82.9%
Other Punctuation 37
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 24
13.4%
1 22
12.3%
3 21
11.7%
4 20
11.2%
0 19
10.6%
5 17
9.5%
6 15
8.4%
7 14
7.8%
8 14
7.8%
9 13
7.3%
Other Punctuation
ValueCountFrequency (%)
, 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 37
17.1%
2 24
11.1%
1 22
10.2%
3 21
9.7%
4 20
9.3%
0 19
8.8%
5 17
7.9%
6 15
6.9%
7 14
 
6.5%
8 14
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 37
17.1%
2 24
11.1%
1 22
10.2%
3 21
9.7%
4 20
9.3%
0 19
8.8%
5 17
7.9%
6 15
6.9%
7 14
 
6.5%
8 14
 
6.5%

건축면적(㎡)
Text

Distinct26
Distinct (%)70.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T16:03:10.818609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.3243243
Min length1

Characters and Unicode

Total characters160
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)59.5%

Sample

1st row0
2nd row0
3rd row3,000
4th row0
5th row0
ValueCountFrequency (%)
0 9
24.3%
3,000 2
 
5.4%
7,000 2
 
5.4%
4,000 2
 
5.4%
882 1
 
2.7%
916 1
 
2.7%
4,181 1
 
2.7%
13,652 1
 
2.7%
11,200 1
 
2.7%
4,800 1
 
2.7%
Other values (16) 16
43.2%
2023-12-12T16:03:11.192019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 50
31.2%
, 25
15.6%
1 13
 
8.1%
2 12
 
7.5%
5 11
 
6.9%
6 11
 
6.9%
4 10
 
6.2%
3 9
 
5.6%
8 7
 
4.4%
9 6
 
3.8%
Other values (2) 6
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 131
81.9%
Other Punctuation 29
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 50
38.2%
1 13
 
9.9%
2 12
 
9.2%
5 11
 
8.4%
6 11
 
8.4%
4 10
 
7.6%
3 9
 
6.9%
8 7
 
5.3%
9 6
 
4.6%
7 2
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 25
86.2%
. 4
 
13.8%

Most occurring scripts

ValueCountFrequency (%)
Common 160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 50
31.2%
, 25
15.6%
1 13
 
8.1%
2 12
 
7.5%
5 11
 
6.9%
6 11
 
6.9%
4 10
 
6.2%
3 9
 
5.6%
8 7
 
4.4%
9 6
 
3.8%
Other values (2) 6
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 50
31.2%
, 25
15.6%
1 13
 
8.1%
2 12
 
7.5%
5 11
 
6.9%
6 11
 
6.9%
4 10
 
6.2%
3 9
 
5.6%
8 7
 
4.4%
9 6
 
3.8%
Other values (2) 6
 
3.8%

건축연면적(㎡)
Text

Distinct26
Distinct (%)70.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T16:03:11.388592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length4.7567568
Min length1

Characters and Unicode

Total characters176
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)62.2%

Sample

1st row0
2nd row0
3rd row9,000
4th row0
5th row0
ValueCountFrequency (%)
0 9
24.3%
16,000 3
 
8.1%
12,000 2
 
5.4%
1,970 1
 
2.7%
1,940 1
 
2.7%
31,500 1
 
2.7%
13,500 1
 
2.7%
28,000 1
 
2.7%
30,000 1
 
2.7%
4,000 1
 
2.7%
Other values (16) 16
43.2%
2023-12-12T16:03:11.773742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 69
39.2%
, 28
15.9%
1 19
 
10.8%
2 11
 
6.2%
9 11
 
6.2%
3 9
 
5.1%
5 8
 
4.5%
4 7
 
4.0%
6 5
 
2.8%
8 4
 
2.3%
Other values (2) 5
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 145
82.4%
Other Punctuation 31
 
17.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 69
47.6%
1 19
 
13.1%
2 11
 
7.6%
9 11
 
7.6%
3 9
 
6.2%
5 8
 
5.5%
4 7
 
4.8%
6 5
 
3.4%
8 4
 
2.8%
7 2
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 28
90.3%
. 3
 
9.7%

Most occurring scripts

ValueCountFrequency (%)
Common 176
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 69
39.2%
, 28
15.9%
1 19
 
10.8%
2 11
 
6.2%
9 11
 
6.2%
3 9
 
5.1%
5 8
 
4.5%
4 7
 
4.0%
6 5
 
2.8%
8 4
 
2.3%
Other values (2) 5
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 176
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 69
39.2%
, 28
15.9%
1 19
 
10.8%
2 11
 
6.2%
9 11
 
6.2%
3 9
 
5.1%
5 8
 
4.5%
4 7
 
4.0%
6 5
 
2.8%
8 4
 
2.3%
Other values (2) 5
 
2.8%

결정조서 건폐율(%)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.324324
Minimum0
Maximum60
Zeros8
Zeros (%)21.6%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T16:03:11.892985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median35
Q345
95-th percentile48
Maximum60
Range60
Interquartile range (IQR)25

Descriptive statistics

Standard deviation18.602649
Coefficient of variation (CV)0.63437606
Kurtosis-0.95246493
Mean29.324324
Median Absolute Deviation (MAD)10
Skewness-0.51709361
Sum1085
Variance346.05856
MonotonicityNot monotonic
2023-12-12T16:03:11.987054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 8
21.6%
40 8
21.6%
45 8
21.6%
20 4
10.8%
30 3
 
8.1%
35 3
 
8.1%
60 2
 
5.4%
10 1
 
2.7%
ValueCountFrequency (%)
0 8
21.6%
10 1
 
2.7%
20 4
10.8%
30 3
 
8.1%
35 3
 
8.1%
40 8
21.6%
45 8
21.6%
60 2
 
5.4%
ValueCountFrequency (%)
60 2
 
5.4%
45 8
21.6%
40 8
21.6%
35 3
 
8.1%
30 3
 
8.1%
20 4
10.8%
10 1
 
2.7%
0 8
21.6%

건축면적
Text

Distinct29
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T16:03:12.143479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.2162162
Min length1

Characters and Unicode

Total characters156
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)73.0%

Sample

1st row0
2nd row0
3rd row4,719
4th row0
5th row0
ValueCountFrequency (%)
0 8
21.6%
6,068 2
 
5.4%
917 1
 
2.7%
2,262 1
 
2.7%
4,181 1
 
2.7%
13,652 1
 
2.7%
11,428 1
 
2.7%
4,968 1
 
2.7%
25,342 1
 
2.7%
4,214 1
 
2.7%
Other values (19) 19
51.4%
2023-12-12T16:03:12.447101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 26
16.7%
1 23
14.7%
0 19
12.2%
6 16
10.3%
4 13
8.3%
2 13
8.3%
8 11
7.1%
5 11
7.1%
9 9
 
5.8%
3 9
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 130
83.3%
Other Punctuation 26
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
17.7%
0 19
14.6%
6 16
12.3%
4 13
10.0%
2 13
10.0%
8 11
8.5%
5 11
8.5%
9 9
 
6.9%
3 9
 
6.9%
7 6
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 156
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 26
16.7%
1 23
14.7%
0 19
12.2%
6 16
10.3%
4 13
8.3%
2 13
8.3%
8 11
7.1%
5 11
7.1%
9 9
 
5.8%
3 9
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 26
16.7%
1 23
14.7%
0 19
12.2%
6 16
10.3%
4 13
8.3%
2 13
8.3%
8 11
7.1%
5 11
7.1%
9 9
 
5.8%
3 9
 
5.8%

용적률(%)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.972973
Minimum0
Maximum200
Zeros8
Zeros (%)21.6%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T16:03:12.573702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q160
median120
Q3140
95-th percentile164
Maximum200
Range200
Interquartile range (IQR)80

Descriptive statistics

Standard deviation61.321777
Coefficient of variation (CV)0.65956563
Kurtosis-1.0833354
Mean92.972973
Median Absolute Deviation (MAD)40
Skewness-0.38781499
Sum3440
Variance3760.3604
MonotonicityNot monotonic
2023-12-12T16:03:12.684504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
120 11
29.7%
0 8
21.6%
160 5
13.5%
60 4
 
10.8%
140 3
 
8.1%
80 2
 
5.4%
100 1
 
2.7%
180 1
 
2.7%
20 1
 
2.7%
200 1
 
2.7%
ValueCountFrequency (%)
0 8
21.6%
20 1
 
2.7%
60 4
 
10.8%
80 2
 
5.4%
100 1
 
2.7%
120 11
29.7%
140 3
 
8.1%
160 5
13.5%
180 1
 
2.7%
200 1
 
2.7%
ValueCountFrequency (%)
200 1
 
2.7%
180 1
 
2.7%
160 5
13.5%
140 3
 
8.1%
120 11
29.7%
100 1
 
2.7%
80 2
 
5.4%
60 4
 
10.8%
20 1
 
2.7%
0 8
21.6%

건축연면적
Text

Distinct30
Distinct (%)81.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T16:03:12.887934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.7297297
Min length1

Characters and Unicode

Total characters175
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)78.4%

Sample

1st row0
2nd row0
3rd row14,158
4th row0
5th row0
ValueCountFrequency (%)
0 8
 
21.6%
14,158 1
 
2.7%
16,724 1
 
2.7%
54,607 1
 
2.7%
34,285 1
 
2.7%
14,904 1
 
2.7%
101,366 1
 
2.7%
30,338 1
 
2.7%
11,238 1
 
2.7%
4,083 1
 
2.7%
Other values (20) 20
54.1%
2023-12-12T16:03:13.245187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 29
16.6%
4 22
12.6%
2 19
10.9%
0 18
10.3%
1 17
9.7%
8 17
9.7%
3 13
7.4%
5 12
6.9%
6 11
 
6.3%
9 9
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 146
83.4%
Other Punctuation 29
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 22
15.1%
2 19
13.0%
0 18
12.3%
1 17
11.6%
8 17
11.6%
3 13
8.9%
5 12
8.2%
6 11
7.5%
9 9
6.2%
7 8
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 29
16.6%
4 22
12.6%
2 19
10.9%
0 18
10.3%
1 17
9.7%
8 17
9.7%
3 13
7.4%
5 12
6.9%
6 11
 
6.3%
9 9
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 29
16.6%
4 22
12.6%
2 19
10.9%
0 18
10.3%
1 17
9.7%
8 17
9.7%
3 13
7.4%
5 12
6.9%
6 11
 
6.3%
9 9
 
5.1%

높이(층수)
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
15m(4층)이하
11 
0
8 
12m (3층) 이하
4 
12m(3층)이하
4 
12m(4층)이하
2 
Other values (8)
8 

Length

Max length11
Median length9
Mean length7.6756757
Min length1

Unique

Unique8 ?
Unique (%)21.6%

Sample

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

Common Values

ValueCountFrequency (%)
15m(4층)이하 11
29.7%
0 8
21.6%
12m (3층) 이하 4
 
10.8%
12m(3층)이하 4
 
10.8%
12m(4층)이하 2
 
5.4%
12m(3층) 이하 1
 
2.7%
12m(4층) 이하 1
 
2.7%
12m (4층) 이하 1
 
2.7%
20m (5층) 이하 1
 
2.7%
20m(4층)이하 1
 
2.7%
Other values (3) 3
 
8.1%

Length

2023-12-12T16:03:13.402720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
15m(4층)이하 11
21.2%
이하 8
15.4%
0 8
15.4%
12m 5
9.6%
3층 4
 
7.7%
12m(3층)이하 4
 
7.7%
12m(4층)이하 2
 
3.8%
20m(4층)이하 1
 
1.9%
15m 1
 
1.9%
12m(2층)이하 1
 
1.9%
Other values (7) 7
13.5%

건축물용도 1
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
근린생활시설
9 
해당없음
8 
숙박시설
7 
의료시설
6 
교육연구시설
2 
Other values (4)
5 

Length

Max length6
Median length4
Mean length4.7027027
Min length4

Unique

Unique3 ?
Unique (%)8.1%

Sample

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

Common Values

ValueCountFrequency (%)
근린생활시설 9
24.3%
해당없음 8
21.6%
숙박시설 7
18.9%
의료시설 6
16.2%
교육연구시설 2
 
5.4%
관광휴게시설 2
 
5.4%
업무시설 1
 
2.7%
위락시설 1
 
2.7%
운동시설 1
 
2.7%

Length

2023-12-12T16:03:13.527793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:13.657211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
근린생활시설 9
24.3%
해당없음 8
21.6%
숙박시설 7
18.9%
의료시설 6
16.2%
교육연구시설 2
 
5.4%
관광휴게시설 2
 
5.4%
업무시설 1
 
2.7%
위락시설 1
 
2.7%
운동시설 1
 
2.7%

건축물용도 2
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size428.0 B
판매시설
10 
해당없음
9 
근린생활시설
9 
근린생활시설
5 
교육연구시설
2 
Other values (2)
2 

Length

Max length8
Median length7
Mean length5.5135135
Min length4

Unique

Unique2 ?
Unique (%)5.4%

Sample

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

Common Values

ValueCountFrequency (%)
판매시설 10
27.0%
해당없음 9
24.3%
근린생활시설 9
24.3%
근린생활시설 5
13.5%
교육연구시설 2
 
5.4%
의료시설 1
 
2.7%
문화및집회시설 1
 
2.7%

Length

2023-12-12T16:03:13.806967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:13.932756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
근린생활시설 14
37.8%
판매시설 10
27.0%
해당없음 9
24.3%
교육연구시설 2
 
5.4%
의료시설 1
 
2.7%
문화및집회시설 1
 
2.7%

건축물용도 3
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size428.0 B
해당없음
33 
근린생활시설
 
2
위락시설
 
1
근린 생활시설
 
1

Length

Max length8
Median length4
Mean length4.2432432
Min length4

Unique

Unique2 ?
Unique (%)5.4%

Sample

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

Common Values

ValueCountFrequency (%)
해당없음 33
89.2%
근린생활시설 2
 
5.4%
위락시설 1
 
2.7%
근린 생활시설 1
 
2.7%

Length

2023-12-12T16:03:14.072671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:14.223504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 33
86.8%
근린생활시설 2
 
5.3%
위락시설 1
 
2.6%
근린 1
 
2.6%
생활시설 1
 
2.6%

객실수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size428.0 B
해당없음
30 
188실
 
1
212실
 
1
250실
 
1
60실
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length3.9459459
Min length3

Unique

Unique7 ?
Unique (%)18.9%

Sample

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

Common Values

ValueCountFrequency (%)
해당없음 30
81.1%
188실 1
 
2.7%
212실 1
 
2.7%
250실 1
 
2.7%
60실 1
 
2.7%
80실 1
 
2.7%
340실 1
 
2.7%
255실 1
 
2.7%

Length

2023-12-12T16:03:14.361187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:03:14.481910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 30
81.1%
188실 1
 
2.7%
212실 1
 
2.7%
250실 1
 
2.7%
60실 1
 
2.7%
80실 1
 
2.7%
340실 1
 
2.7%
255실 1
 
2.7%

Interactions

2023-12-12T16:03:08.001337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:07.810494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:08.107118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:07.900229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:03:14.609400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구 분구분(상세)면적(㎡)건축면적(㎡)건축연면적(㎡)결정조서 건폐율(%)건축면적용적률(%)건축연면적높이(층수)건축물용도 1건축물용도 2건축물용도 3객실수
구 분1.0001.0000.2280.6260.0000.8970.6610.7090.8100.8410.9400.9550.5110.000
구분(상세)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
면적(㎡)0.2281.0001.0000.9720.9781.0001.0000.0000.9650.0000.0000.9331.0001.000
건축면적(㎡)0.6261.0000.9721.0000.9970.9380.9970.9451.0000.9230.5270.9500.8830.977
건축연면적(㎡)0.0001.0000.9780.9971.0000.9570.9970.9641.0000.9850.7310.8980.5601.000
결정조서 건폐율(%)0.8971.0001.0000.9380.9571.0001.0000.9181.0000.8920.8120.9630.5950.434
건축면적0.6611.0001.0000.9970.9971.0001.0000.9691.0000.9820.9700.9911.0001.000
용적률(%)0.7091.0000.0000.9450.9640.9180.9691.0001.0000.9260.8690.7940.0000.687
건축연면적0.8101.0000.9651.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
높이(층수)0.8411.0000.0000.9230.9850.8920.9820.9261.0001.0000.9020.7660.6440.849
건축물용도 10.9401.0000.0000.5270.7310.8120.9700.8691.0000.9021.0000.9060.7300.000
건축물용도 20.9551.0000.9330.9500.8980.9630.9910.7941.0000.7660.9061.0000.8620.000
건축물용도 30.5111.0001.0000.8830.5600.5951.0000.0001.0000.6440.7300.8621.0000.764
객실수0.0001.0001.0000.9771.0000.4341.0000.6871.0000.8490.0000.0000.7641.000
2023-12-12T16:03:14.813642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축물용도 2건축물용도 3건축물용도 1구 분객실수높이(층수)
건축물용도 21.0000.7560.7540.6720.0000.430
건축물용도 30.7561.0000.5200.3540.3980.362
건축물용도 10.7540.5201.0000.8320.0000.632
구 분0.6720.3540.8321.0000.0000.528
객실수0.0000.3980.0000.0001.0000.544
높이(층수)0.4300.3620.6320.5280.5441.000
2023-12-12T16:03:14.957462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결정조서 건폐율(%)용적률(%)구 분높이(층수)건축물용도 1건축물용도 2건축물용도 3객실수
결정조서 건폐율(%)1.0000.7970.5650.5990.5770.7430.5310.277
용적률(%)0.7971.0000.4490.6550.4210.5000.3730.411
구 분0.5650.4491.0000.5280.8320.6720.3540.000
높이(층수)0.5990.6550.5281.0000.6320.4300.3620.544
건축물용도 10.5770.4210.8320.6321.0000.7540.5200.000
건축물용도 20.7430.5000.6720.4300.7541.0000.7560.000
건축물용도 30.5310.3730.3540.3620.5200.7561.0000.398
객실수0.2770.4110.0000.5440.0000.0000.3981.000

Missing values

2023-12-12T16:03:08.588674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:03:08.832399image/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

구 분구분(상세)면적(㎡)건축면적(㎡)건축연면적(㎡)결정조서 건폐율(%)건축면적용적률(%)건축연면적높이(층수)건축물용도 1건축물용도 2건축물용도 3객실수
0공공편익시설도 로160,6740000000해당없음해당없음해당없음해당없음
1공공편익시설보행자전용도로7,5950000000해당없음해당없음해당없음해당없음
2공공편익시설중앙관리센터11,7983,0009,000404,71912014,15812m(3층) 이하업무시설근린생활시설해당없음해당없음
3공공편익시설공용주차장25,0630000000해당없음해당없음해당없음해당없음
4공공편익시설저류지49,8240000000해당없음해당없음해당없음해당없음
5공공편익시설배수지5,2060000000해당없음해당없음해당없음해당없음
6공공편익시설광 장30,6540000000해당없음해당없음해당없음해당없음
7숙박시설휴양콘도미니엄130,4749,334.8236,922.554012,19016048,75812m(4층) 이하숙박시설근린생활시설해당없음188실
8숙박시설휴양콘도미니엄235,27410,498.4441,315.324014,11016056,43812m (4층) 이하숙박시설근린생활시설해당없음212실
9숙박시설텔라소리조텔87,34812,50037,0003026,20410087,34812m (3층) 이하숙박시설근린생활시설해당없음250실
구 분구분(상세)면적(㎡)건축면적(㎡)건축연면적(㎡)결정조서 건폐율(%)건축면적용적률(%)건축연면적높이(층수)건축물용도 1건축물용도 2건축물용도 3객실수
27휴양문화시설힐링가든14,04700304,2148011,23812m(2층)이하관광휴게시설해당없음해당없음해당없음
28기타시설(의료연구)헬스케어센터15,1696,00030,000406,06820030,33815m (5층)이하의료시설근린생활시설해당없음해당없음
29기타시설(의료연구)전문병원63,3547,00028,0004025,342160101,36612m(4층)이하의료시설근린생활시설해당없음해당없음
30기타시설(의료연구)메디컬스트리트112,4204,80013,500404,96812014,90412m(3층)이하의료시설근린생활시설해당없음해당없음
31기타시설(의료연구)메디컬스트리트228,57111,20031,5004011,42812034,28512m(3층)이하의료시설근린생활시설해당없음해당없음
32기타시설(의료연구)의료R&D센터39,00513,65245,0003513,65214054,60715m(4층)이하의료시설교육연구시설근린생활시설해당없음
33기타시설(의료연구)안티에이징센터11,9464,18116,000354,18114016,72415m(4층)이하의료시설교육연구시설근린생활시설해당없음
34기타시설(의료연구)기숙동13,0324,56116,000354,56114018,24515m(4층)이하교육연구시설근린생활시설해당없음해당없음
35녹지경관녹지395,7000000000해당없음해당없음해당없음해당없음
36녹지완충녹지108,0850000000해당없음해당없음해당없음해당없음