Overview

Dataset statistics

Number of variables13
Number of observations268
Missing cells102
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.9 KiB
Average record size in memory110.5 B

Variable types

Numeric5
Categorical3
Text4
DateTime1

Dataset

Description강원특별자치도 인제군 다세대주택 현황에 관한 데이터입니다. 시군구명, 대지위치주소(지번주소), 도로명주소, 대지면적, 건물명, 주용도, 세부용도, 가구수, 연면적, 지상층수, 지하층수, 사용승인일의 데이터를 제공합니다.
Author강원특별자치도 인제군
URLhttps://www.data.go.kr/data/15127261/fileData.do

Alerts

시군구명 has constant value ""Constant
연면적(제곱미터) is highly overall correlated with 지상층수High correlation
지상층수 is highly overall correlated with 연면적(제곱미터)High correlation
주용도 is highly imbalanced (79.5%)Imbalance
도로명주소 has 6 (2.2%) missing valuesMissing
건물명(있는 경우만) has 96 (35.8%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-23 05:39:37.340043
Analysis finished2024-03-23 05:39:48.875371
Duration11.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct268
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134.5
Minimum1
Maximum268
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-23T05:39:49.200828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.35
Q167.75
median134.5
Q3201.25
95-th percentile254.65
Maximum268
Range267
Interquartile range (IQR)133.5

Descriptive statistics

Standard deviation77.509139
Coefficient of variation (CV)0.57627613
Kurtosis-1.2
Mean134.5
Median Absolute Deviation (MAD)67
Skewness0
Sum36046
Variance6007.6667
MonotonicityStrictly increasing
2024-03-23T05:39:49.730845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
186 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
174 1
 
0.4%
175 1
 
0.4%
176 1
 
0.4%
177 1
 
0.4%
178 1
 
0.4%
179 1
 
0.4%
Other values (258) 258
96.3%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
268 1
0.4%
267 1
0.4%
266 1
0.4%
265 1
0.4%
264 1
0.4%
263 1
0.4%
262 1
0.4%
261 1
0.4%
260 1
0.4%
259 1
0.4%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
강원특별자치도 인제군
268 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원특별자치도 인제군
2nd row강원특별자치도 인제군
3rd row강원특별자치도 인제군
4th row강원특별자치도 인제군
5th row강원특별자치도 인제군

Common Values

ValueCountFrequency (%)
강원특별자치도 인제군 268
100.0%

Length

2024-03-23T05:39:50.305768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:39:50.682583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원특별자치도 268
50.0%
인제군 268
50.0%

대지위치주소
Text

Distinct255
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-03-23T05:39:51.253418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length24.261194
Min length20

Characters and Unicode

Total characters6502
Distinct characters63
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique243 ?
Unique (%)90.7%

Sample

1st row강원특별자치도 인제군 인제읍 상동리 361-29
2nd row강원특별자치도 인제군 인제읍 상동리 361-03
3rd row강원특별자치도 인제군 북면 용대리 902-8
4th row강원특별자치도 인제군 인제읍 상동리 345-13
5th row강원특별자치도 인제군 서화면 서화리 659-12
ValueCountFrequency (%)
강원특별자치도 268
20.0%
인제군 268
20.0%
인제읍 116
 
8.7%
북면 58
 
4.3%
기린면 49
 
3.7%
상동리 32
 
2.4%
용대리 31
 
2.3%
진동리 24
 
1.8%
원통리 24
 
1.8%
상남면 23
 
1.7%
Other values (284) 447
33.4%
2024-03-23T05:39:52.488731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1072
 
16.5%
인 384
 
5.9%
제 384
 
5.9%
원 298
 
4.6%
리 275
 
4.2%
강 274
 
4.2%
치 270
 
4.2%
도 270
 
4.2%
특 268
 
4.1%
별 268
 
4.1%
Other values (53) 2739
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4202
64.6%
Space Separator 1072
 
16.5%
Decimal Number 1032
 
15.9%
Dash Punctuation 196
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 384
 
9.1%
제 384
 
9.1%
원 298
 
7.1%
리 275
 
6.5%
강 274
 
6.5%
치 270
 
6.4%
도 270
 
6.4%
특 268
 
6.4%
별 268
 
6.4%
자 268
 
6.4%
Other values (41) 1243
29.6%
Decimal Number
ValueCountFrequency (%)
1 196
19.0%
2 158
15.3%
4 112
10.9%
3 111
10.8%
6 100
9.7%
5 98
9.5%
7 77
 
7.5%
8 61
 
5.9%
9 60
 
5.8%
0 59
 
5.7%
Space Separator
ValueCountFrequency (%)
1072
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4202
64.6%
Common 2300
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 384
 
9.1%
제 384
 
9.1%
원 298
 
7.1%
리 275
 
6.5%
강 274
 
6.5%
치 270
 
6.4%
도 270
 
6.4%
특 268
 
6.4%
별 268
 
6.4%
자 268
 
6.4%
Other values (41) 1243
29.6%
Common
ValueCountFrequency (%)
1072
46.6%
1 196
 
8.5%
- 196
 
8.5%
2 158
 
6.9%
4 112
 
4.9%
3 111
 
4.8%
6 100
 
4.3%
5 98
 
4.3%
7 77
 
3.3%
8 61
 
2.7%
Other values (2) 119
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4202
64.6%
ASCII 2300
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1072
46.6%
1 196
 
8.5%
- 196
 
8.5%
2 158
 
6.9%
4 112
 
4.9%
3 111
 
4.8%
6 100
 
4.3%
5 98
 
4.3%
7 77
 
3.3%
8 61
 
2.7%
Other values (2) 119
 
5.2%
Hangul
ValueCountFrequency (%)
인 384
 
9.1%
제 384
 
9.1%
원 298
 
7.1%
리 275
 
6.5%
강 274
 
6.5%
치 270
 
6.4%
도 270
 
6.4%
특 268
 
6.4%
별 268
 
6.4%
자 268
 
6.4%
Other values (41) 1243
29.6%

도로명주소
Text

MISSING 

Distinct244
Distinct (%)93.1%
Missing6
Missing (%)2.2%
Memory size2.2 KiB
2024-03-23T05:39:53.096868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length25.076336
Min length21

Characters and Unicode

Total characters6570
Distinct characters129
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique227 ?
Unique (%)86.6%

Sample

1st row강원특별자치도 인제군 인제읍 인제로 197-1
2nd row강원특별자치도 인제군 인제읍 인제로 199
3rd row강원특별자치도 인제군 북면 백담로 88
4th row강원특별자치도 인제군 인제읍 인제로187번길 11-5
5th row강원특별자치도 인제군 서화면 서화길 13-17
ValueCountFrequency (%)
강원특별자치도 262
20.0%
인제군 262
20.0%
인제읍 114
 
8.7%
북면 58
 
4.4%
기린면 47
 
3.6%
내린천로 31
 
2.4%
상남면 22
 
1.7%
남면 17
 
1.3%
조침령로 13
 
1.0%
설피밭길 10
 
0.8%
Other values (313) 477
36.3%
2024-03-23T05:39:54.112039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1051
 
16.0%
인 410
 
6.2%
제 409
 
6.2%
원 278
 
4.2%
자 274
 
4.2%
강 271
 
4.1%
치 265
 
4.0%
특 262
 
4.0%
별 262
 
4.0%
도 262
 
4.0%
Other values (119) 2826
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4411
67.1%
Space Separator 1051
 
16.0%
Decimal Number 1019
 
15.5%
Dash Punctuation 83
 
1.3%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 410
 
9.3%
제 409
 
9.3%
원 278
 
6.3%
자 274
 
6.2%
강 271
 
6.1%
치 265
 
6.0%
특 262
 
5.9%
별 262
 
5.9%
도 262
 
5.9%
군 262
 
5.9%
Other values (105) 1456
33.0%
Decimal Number
ValueCountFrequency (%)
1 185
18.2%
2 141
13.8%
3 127
12.5%
4 122
12.0%
5 86
8.4%
0 84
8.2%
7 76
7.5%
6 70
 
6.9%
8 69
 
6.8%
9 59
 
5.8%
Space Separator
ValueCountFrequency (%)
1051
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 83
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4411
67.1%
Common 2159
32.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 410
 
9.3%
제 409
 
9.3%
원 278
 
6.3%
자 274
 
6.2%
강 271
 
6.1%
치 265
 
6.0%
특 262
 
5.9%
별 262
 
5.9%
도 262
 
5.9%
군 262
 
5.9%
Other values (105) 1456
33.0%
Common
ValueCountFrequency (%)
1051
48.7%
1 185
 
8.6%
2 141
 
6.5%
3 127
 
5.9%
4 122
 
5.7%
5 86
 
4.0%
0 84
 
3.9%
- 83
 
3.8%
7 76
 
3.5%
6 70
 
3.2%
Other values (4) 134
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4411
67.1%
ASCII 2159
32.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1051
48.7%
1 185
 
8.6%
2 141
 
6.5%
3 127
 
5.9%
4 122
 
5.7%
5 86
 
4.0%
0 84
 
3.9%
- 83
 
3.8%
7 76
 
3.5%
6 70
 
3.2%
Other values (4) 134
 
6.2%
Hangul
ValueCountFrequency (%)
인 410
 
9.3%
제 409
 
9.3%
원 278
 
6.3%
자 274
 
6.2%
강 271
 
6.1%
치 265
 
6.0%
특 262
 
5.9%
별 262
 
5.9%
도 262
 
5.9%
군 262
 
5.9%
Other values (105) 1456
33.0%

대지면적(제곱미터)
Real number (ℝ)

Distinct207
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean903.57239
Minimum87
Maximum8854
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-23T05:39:54.706663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum87
5-th percentile215.35
Q1373.725
median667.5
Q31000
95-th percentile2533.25
Maximum8854
Range8767
Interquartile range (IQR)626.275

Descriptive statistics

Standard deviation1006.4215
Coefficient of variation (CV)1.113825
Kurtosis30.88827
Mean903.57239
Median Absolute Deviation (MAD)324
Skewness4.8077617
Sum242157.4
Variance1012884.3
MonotonicityNot monotonic
2024-03-23T05:39:55.812011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000.0 12
 
4.5%
660.0 11
 
4.1%
990.0 10
 
3.7%
1166.0 4
 
1.5%
998.0 4
 
1.5%
820.0 3
 
1.1%
330.0 3
 
1.1%
985.0 2
 
0.7%
188.0 2
 
0.7%
661.0 2
 
0.7%
Other values (197) 215
80.2%
ValueCountFrequency (%)
87.0 1
0.4%
94.0 1
0.4%
117.0 1
0.4%
119.0 1
0.4%
126.0 1
0.4%
142.0 1
0.4%
151.0 1
0.4%
155.0 1
0.4%
176.5 1
0.4%
188.0 2
0.7%
ValueCountFrequency (%)
8854.0 2
0.7%
5519.0 1
0.4%
4767.8 1
0.4%
4064.0 1
0.4%
3913.0 1
0.4%
3400.0 2
0.7%
3292.0 1
0.4%
3284.0 1
0.4%
3154.0 1
0.4%
3140.0 1
0.4%

건물명(있는 경우만)
Text

MISSING 

Distinct56
Distinct (%)32.6%
Missing96
Missing (%)35.8%
Memory size2.2 KiB
2024-03-23T05:39:56.568677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length7
Mean length6.1395349
Min length1

Characters and Unicode

Total characters1056
Distinct characters82
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)26.2%

Sample

1st row1동
2nd row제1동
3rd row주동
4th row주축물제1동
5th row제1호
ValueCountFrequency (%)
주건축물제1동 79
43.4%
제1호 19
 
10.4%
가동 7
 
3.8%
주건축물제2동 5
 
2.7%
1 5
 
2.7%
주건축물제3동 4
 
2.2%
제2호 4
 
2.2%
주동 4
 
2.2%
1동 2
 
1.1%
2
 
1.1%
Other values (47) 51
28.0%
2024-03-23T05:39:57.704526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 124
11.7%
제 123
11.6%
1 118
11.2%
주 116
11.0%
축 107
10.1%
물 96
9.1%
건 94
8.9%
호 27
 
2.6%
가 17
 
1.6%
택 17
 
1.6%
Other values (72) 217
20.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 880
83.3%
Decimal Number 150
 
14.2%
Space Separator 10
 
0.9%
Open Punctuation 4
 
0.4%
Close Punctuation 4
 
0.4%
Dash Punctuation 4
 
0.4%
Uppercase Letter 3
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 124
14.1%
제 123
14.0%
주 116
13.2%
축 107
12.2%
물 96
10.9%
건 94
10.7%
호 27
 
3.1%
가 17
 
1.9%
택 17
 
1.9%
사 13
 
1.5%
Other values (57) 146
16.6%
Decimal Number
ValueCountFrequency (%)
1 118
78.7%
2 14
 
9.3%
3 8
 
5.3%
7 4
 
2.7%
6 2
 
1.3%
8 2
 
1.3%
0 1
 
0.7%
4 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 880
83.3%
Common 173
 
16.4%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 124
14.1%
제 123
14.0%
주 116
13.2%
축 107
12.2%
물 96
10.9%
건 94
10.7%
호 27
 
3.1%
가 17
 
1.9%
택 17
 
1.9%
사 13
 
1.5%
Other values (57) 146
16.6%
Common
ValueCountFrequency (%)
1 118
68.2%
2 14
 
8.1%
10
 
5.8%
3 8
 
4.6%
7 4
 
2.3%
( 4
 
2.3%
) 4
 
2.3%
- 4
 
2.3%
6 2
 
1.2%
8 2
 
1.2%
Other values (3) 3
 
1.7%
Latin
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 880
83.3%
ASCII 176
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 124
14.1%
제 123
14.0%
주 116
13.2%
축 107
12.2%
물 96
10.9%
건 94
10.7%
호 27
 
3.1%
가 17
 
1.9%
택 17
 
1.9%
사 13
 
1.5%
Other values (57) 146
16.6%
ASCII
ValueCountFrequency (%)
1 118
67.0%
2 14
 
8.0%
10
 
5.7%
3 8
 
4.5%
7 4
 
2.3%
( 4
 
2.3%
) 4
 
2.3%
- 4
 
2.3%
A 2
 
1.1%
6 2
 
1.1%
Other values (5) 6
 
3.4%

주용도
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
단독주택
248 
제2종근린생활시설
 
14
제1종근린생활시설
 
4
숙박시설
 
1
공동주택
 
1

Length

Max length9
Median length4
Mean length4.3358209
Min length4

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
단독주택 248
92.5%
제2종근린생활시설 14
 
5.2%
제1종근린생활시설 4
 
1.5%
숙박시설 1
 
0.4%
공동주택 1
 
0.4%

Length

2024-03-23T05:39:58.191649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:39:58.538428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독주택 248
92.5%
제2종근린생활시설 14
 
5.2%
제1종근린생활시설 4
 
1.5%
숙박시설 1
 
0.4%
공동주택 1
 
0.4%

기타 세부용도
Text

Distinct88
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-03-23T05:39:59.150048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length10.037313
Min length3

Characters and Unicode

Total characters2690
Distinct characters69
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)28.0%

Sample

1st row다가구, 근린생활
2nd row다가구주택, 근린생활
3rd row다가구주택,근린생활시설
4th row주택(다가구)
5th row다가구주택
ValueCountFrequency (%)
다가구주택 106
34.6%
단독주택(다가구주택 39
 
12.7%
단독주택(다가구 36
 
11.8%
다가구 13
 
4.2%
주택(다가구 8
 
2.6%
및 7
 
2.3%
제2종근린생활시설 6
 
2.0%
사무소 4
 
1.3%
근린생활시설 4
 
1.3%
단독주택,다가구주택 3
 
1.0%
Other values (72) 80
26.1%
2024-03-23T05:40:00.421319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
택 314
11.7%
주 313
11.6%
구 270
 
10.0%
가 270
 
10.0%
다 268
 
10.0%
( 134
 
5.0%
) 134
 
5.0%
단 108
 
4.0%
독 108
 
4.0%
, 73
 
2.7%
Other values (59) 698
25.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2239
83.2%
Open Punctuation 134
 
5.0%
Close Punctuation 134
 
5.0%
Other Punctuation 92
 
3.4%
Decimal Number 51
 
1.9%
Space Separator 38
 
1.4%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
택 314
14.0%
주 313
14.0%
구 270
12.1%
가 270
12.1%
다 268
12.0%
단 108
 
4.8%
독 108
 
4.8%
생 58
 
2.6%
근 58
 
2.6%
시 54
 
2.4%
Other values (48) 418
18.7%
Decimal Number
ValueCountFrequency (%)
2 37
72.5%
1 12
 
23.5%
9 1
 
2.0%
4 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 73
79.3%
/ 16
 
17.4%
. 3
 
3.3%
Open Punctuation
ValueCountFrequency (%)
( 134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 134
100.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2239
83.2%
Common 451
 
16.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
택 314
14.0%
주 313
14.0%
구 270
12.1%
가 270
12.1%
다 268
12.0%
단 108
 
4.8%
독 108
 
4.8%
생 58
 
2.6%
근 58
 
2.6%
시 54
 
2.4%
Other values (48) 418
18.7%
Common
ValueCountFrequency (%)
( 134
29.7%
) 134
29.7%
, 73
16.2%
38
 
8.4%
2 37
 
8.2%
/ 16
 
3.5%
1 12
 
2.7%
. 3
 
0.7%
- 2
 
0.4%
9 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2239
83.2%
ASCII 451
 
16.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
택 314
14.0%
주 313
14.0%
구 270
12.1%
가 270
12.1%
다 268
12.0%
단 108
 
4.8%
독 108
 
4.8%
생 58
 
2.6%
근 58
 
2.6%
시 54
 
2.4%
Other values (48) 418
18.7%
ASCII
ValueCountFrequency (%)
( 134
29.7%
) 134
29.7%
, 73
16.2%
38
 
8.4%
2 37
 
8.2%
/ 16
 
3.5%
1 12
 
2.7%
. 3
 
0.7%
- 2
 
0.4%
9 1
 
0.2%

가구수
Real number (ℝ)

Distinct16
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1753731
Minimum1
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-23T05:40:00.802415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median3
Q35
95-th percentile10
Maximum17
Range16
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.8904838
Coefficient of variation (CV)0.69226959
Kurtosis4.8820057
Mean4.1753731
Median Absolute Deviation (MAD)1
Skewness2.0147208
Sum1119
Variance8.3548969
MonotonicityNot monotonic
2024-03-23T05:40:01.285505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 82
30.6%
3 45
16.8%
4 38
14.2%
5 34
12.7%
6 20
 
7.5%
1 12
 
4.5%
7 12
 
4.5%
8 5
 
1.9%
9 5
 
1.9%
12 3
 
1.1%
Other values (6) 12
 
4.5%
ValueCountFrequency (%)
1 12
 
4.5%
2 82
30.6%
3 45
16.8%
4 38
14.2%
5 34
12.7%
6 20
 
7.5%
7 12
 
4.5%
8 5
 
1.9%
9 5
 
1.9%
10 3
 
1.1%
ValueCountFrequency (%)
17 1
 
0.4%
16 2
 
0.7%
15 3
 
1.1%
13 2
 
0.7%
12 3
 
1.1%
11 1
 
0.4%
10 3
 
1.1%
9 5
1.9%
8 5
1.9%
7 12
4.5%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct263
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean265.93625
Minimum16
Maximum1552.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-23T05:40:01.786567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile50.75
Q1147.6
median199.35
Q3328.4775
95-th percentile608.11825
Maximum1552.4
Range1536.4
Interquartile range (IQR)180.8775

Descriptive statistics

Standard deviation194.23681
Coefficient of variation (CV)0.73038861
Kurtosis10.311464
Mean265.93625
Median Absolute Deviation (MAD)76.115
Skewness2.3827146
Sum71270.915
Variance37727.938
MonotonicityNot monotonic
2024-03-23T05:40:02.424949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
656.04 2
 
0.7%
211.5 2
 
0.7%
120.32 2
 
0.7%
16.0 2
 
0.7%
33.75 2
 
0.7%
251.49 1
 
0.4%
123.12 1
 
0.4%
136.54 1
 
0.4%
125.12 1
 
0.4%
139.49 1
 
0.4%
Other values (253) 253
94.4%
ValueCountFrequency (%)
16.0 2
0.7%
22.9 1
0.4%
33.75 2
0.7%
34.2 1
0.4%
36.0 1
0.4%
39.28 1
0.4%
40.68 1
0.4%
41.4 1
0.4%
45.63 1
0.4%
45.8 1
0.4%
ValueCountFrequency (%)
1552.4 1
0.4%
1379.47 1
0.4%
897.36 1
0.4%
744.56 1
0.4%
713.23 1
0.4%
676.67 1
0.4%
656.69 1
0.4%
656.04 2
0.7%
647.52 1
0.4%
645.03 1
0.4%

지상층수
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0223881
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-23T05:40:02.938562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile4
Maximum6
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.86085419
Coefficient of variation (CV)0.42566222
Kurtosis3.0669291
Mean2.0223881
Median Absolute Deviation (MAD)0
Skewness1.2345002
Sum542
Variance0.74106993
MonotonicityNot monotonic
2024-03-23T05:40:03.514417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 144
53.7%
1 69
25.7%
3 40
 
14.9%
4 12
 
4.5%
6 2
 
0.7%
5 1
 
0.4%
ValueCountFrequency (%)
1 69
25.7%
2 144
53.7%
3 40
 
14.9%
4 12
 
4.5%
5 1
 
0.4%
6 2
 
0.7%
ValueCountFrequency (%)
6 2
 
0.7%
5 1
 
0.4%
4 12
 
4.5%
3 40
 
14.9%
2 144
53.7%
1 69
25.7%

지하층수
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
123 
0
121 
1
24 

Length

Max length4
Median length1
Mean length2.3768657
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 123
45.9%
0 121
45.1%
1 24
 
9.0%

Length

2024-03-23T05:40:04.226869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:40:04.700119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 123
45.9%
0 121
45.1%
1 24
 
9.0%

사용승인일
Date

Distinct232
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum1982-03-02 00:00:00
Maximum2024-01-24 00:00:00
2024-03-23T05:40:05.070230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:40:05.741664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-03-23T05:39:45.332494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:38.886892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:40.288166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:41.786773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:43.685804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:45.710922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:39.138257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:40.538410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:42.084604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:43.983763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:46.045936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:39.390903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:40.780146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:42.548905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:44.237482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:46.355681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:39.661813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:41.147159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:42.846520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:44.594979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:46.753772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:40.011686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:41.463923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:43.329924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:39:45.065612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T05:40:06.153471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번대지면적(제곱미터)건물명(있는 경우만)주용도기타 세부용도가구수연면적(제곱미터)지상층수지하층수
연번1.0000.2560.7560.0000.6490.2820.1670.3340.391
대지면적(제곱미터)0.2561.0000.9580.0000.0000.3870.0000.0000.142
건물명(있는 경우만)0.7560.9581.0000.0000.0000.0000.0000.0000.840
주용도0.0000.0000.0001.0000.9460.0000.2540.0840.000
기타 세부용도0.6490.0000.0000.9461.0000.5600.9320.8450.602
가구수0.2820.3870.0000.0000.5601.0000.6930.5660.291
연면적(제곱미터)0.1670.0000.0000.2540.9320.6931.0000.7990.345
지상층수0.3340.0000.0000.0840.8450.5660.7991.0000.401
지하층수0.3910.1420.8400.0000.6020.2910.3450.4011.000
2024-03-23T05:40:06.575414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주용도지하층수
주용도1.0000.000
지하층수0.0001.000
2024-03-23T05:40:06.955773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번대지면적(제곱미터)가구수연면적(제곱미터)지상층수주용도지하층수
연번1.0000.2220.076-0.149-0.1670.0000.291
대지면적(제곱미터)0.2221.0000.027-0.093-0.3250.0000.172
가구수0.0760.0271.0000.4790.3580.0000.224
연면적(제곱미터)-0.149-0.0930.4791.0000.7430.1570.253
지상층수-0.167-0.3250.3580.7431.0000.0560.284
주용도0.0000.0000.0000.1570.0561.0000.000
지하층수0.2910.1720.2240.2530.2840.0001.000

Missing values

2024-03-23T05:39:47.256348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T05:39:48.067877image/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.
2024-03-23T05:39:48.666762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번시군구명대지위치주소도로명주소대지면적(제곱미터)건물명(있는 경우만)주용도기타 세부용도가구수연면적(제곱미터)지상층수지하층수사용승인일
01강원특별자치도 인제군강원특별자치도 인제군 인제읍 상동리 361-29강원특별자치도 인제군 인제읍 인제로 197-187.0<NA>단독주택다가구, 근린생활3251.49401982-03-02
12강원특별자치도 인제군강원특별자치도 인제군 인제읍 상동리 361-03강원특별자치도 인제군 인제읍 인제로 19994.0<NA>단독주택다가구주택, 근린생활5223.17401982-03-02
23강원특별자치도 인제군강원특별자치도 인제군 북면 용대리 902-8강원특별자치도 인제군 북면 백담로 88757.0<NA>단독주택다가구주택,근린생활시설4272.513<NA>1986-10-10
34강원특별자치도 인제군강원특별자치도 인제군 인제읍 상동리 345-13강원특별자치도 인제군 인제읍 인제로187번길 11-5334.0<NA>단독주택주택(다가구)2144.0201989-08-29
45강원특별자치도 인제군강원특별자치도 인제군 서화면 서화리 659-12강원특별자치도 인제군 서화면 서화길 13-17323.71동단독주택다가구주택4147.452<NA>1991-04-10
56강원특별자치도 인제군강원특별자치도 인제군 인제읍 상동리 344-12강원특별자치도 인제군 인제읍 인제로177번길 5-4317.0<NA>단독주택다가구주택4164.59201992-06-05
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