Overview

Dataset statistics

Number of variables29
Number of observations500
Missing cells3475
Missing cells (%)24.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory122.7 KiB
Average record size in memory251.3 B

Variable types

Text7
Categorical8
Numeric12
Unsupported2

Dataset

Description샘플 데이터
Author국토교통부(open.eais.go.kr)
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=28

Alerts

로트 has constant value ""Constant
새주소_지상지하_코드 has constant value ""Constant
단위_구분_코드_명 has constant value ""Constant
대장_구분_코드 is highly imbalanced (67.3%)Imbalance
대장_구분_코드_명 is highly imbalanced (67.3%)Imbalance
대장_종류_코드 is highly imbalanced (59.6%)Imbalance
대장_종류_코드_명 is highly imbalanced (60.7%)Imbalance
대지_구분_코드 is highly imbalanced (95.3%)Imbalance
특수지_명 is highly imbalanced (97.9%)Imbalance
형식_코드_명 is highly imbalanced (51.7%)Imbalance
도로명_대지_위치 has 96 (19.2%) missing valuesMissing
건물_명 has 443 (88.6%) missing valuesMissing
블록 has 500 (100.0%) missing valuesMissing
로트 has 499 (99.8%) missing valuesMissing
새주소_도로_코드 has 86 (17.2%) missing valuesMissing
새주소_법정동_코드 has 89 (17.8%) missing valuesMissing
새주소_본_번 has 69 (13.8%) missing valuesMissing
새주소_부_번 has 90 (18.0%) missing valuesMissing
형식_코드 has 302 (60.4%) missing valuesMissing
기타_형식 has 302 (60.4%) missing valuesMissing
단위_구분_코드 has 500 (100.0%) missing valuesMissing
단위_구분_코드_명 has 499 (99.8%) missing valuesMissing
용량_인용 is highly skewed (γ1 = 20.66639826)Skewed
관리_건축물대장_PK has unique valuesUnique
대지_위치 has unique valuesUnique
블록 is an unsupported type, check if it needs cleaning or further analysisUnsupported
단위_구분_코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지 has 156 (31.2%) zerosZeros
새주소_본_번 has 12 (2.4%) zerosZeros
새주소_부_번 has 222 (44.4%) zerosZeros
용량_인용 has 371 (74.2%) zerosZeros
용량_루베 has 459 (91.8%) zerosZeros

Reproduction

Analysis started2023-12-10 15:01:51.358114
Analysis finished2023-12-10 15:01:52.299403
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리_건축물대장_PK
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T00:01:52.622766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length11.476
Min length8

Characters and Unicode

Total characters5738
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

Unique500 ?
Unique (%)100.0%

Sample

1st row48870-20542
2nd row11560-33525
3rd row43740-100195992
4th row47830-8747
5th row28170-19466
ValueCountFrequency (%)
48870-20542 1
 
0.2%
45710-100218509 1
 
0.2%
11560-33776 1
 
0.2%
27710-13361 1
 
0.2%
47150-7823 1
 
0.2%
11410-25726 1
 
0.2%
48880-100199065 1
 
0.2%
45750-980 1
 
0.2%
41650-45600 1
 
0.2%
41590-100304013 1
 
0.2%
Other values (490) 490
98.0%
2023-12-11T00:01:53.409740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 918
16.0%
0 864
15.1%
4 639
11.1%
2 577
10.1%
- 500
8.7%
3 463
8.1%
7 450
7.8%
8 380
6.6%
5 353
 
6.2%
6 316
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5238
91.3%
Dash Punctuation 500
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 918
17.5%
0 864
16.5%
4 639
12.2%
2 577
11.0%
3 463
8.8%
7 450
8.6%
8 380
7.3%
5 353
 
6.7%
6 316
 
6.0%
9 278
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 500
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5738
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 918
16.0%
0 864
15.1%
4 639
11.1%
2 577
10.1%
- 500
8.7%
3 463
8.1%
7 450
7.8%
8 380
6.6%
5 353
 
6.2%
6 316
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5738
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 918
16.0%
0 864
15.1%
4 639
11.1%
2 577
10.1%
- 500
8.7%
3 463
8.1%
7 450
7.8%
8 380
6.6%
5 353
 
6.2%
6 316
 
5.5%

대장_구분_코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
470 
2
 
30

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 470
94.0%
2 30
 
6.0%

Length

2023-12-11T00:01:53.696157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:53.868399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 470
94.0%
2 30
 
6.0%

대장_구분_코드_명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
일반
470 
집합
 
30

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 470
94.0%
집합 30
 
6.0%

Length

2023-12-11T00:01:54.087290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:54.332289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 470
94.0%
집합 30
 
6.0%

대장_종류_코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
441 
3
 
32
1
 
27

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 441
88.2%
3 32
 
6.4%
1 27
 
5.4%

Length

2023-12-11T00:01:54.541481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:54.769646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 441
88.2%
3 32
 
6.4%
1 27
 
5.4%

대장_종류_코드_명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
일반건축물
443 
표제부
 
34
총괄표제부
 
23

Length

Max length5
Median length5
Mean length4.864
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row표제부
2nd row일반건축물
3rd row일반건축물
4th row일반건축물
5th row표제부

Common Values

ValueCountFrequency (%)
일반건축물 443
88.6%
표제부 34
 
6.8%
총괄표제부 23
 
4.6%

Length

2023-12-11T00:01:55.046921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:01:55.302413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반건축물 443
88.6%
표제부 34
 
6.8%
총괄표제부 23
 
4.6%

대지_위치
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T00:01:55.927853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length22.232
Min length17

Characters and Unicode

Total characters11116
Distinct characters256
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st row전라남도 여수시 덕충동 102-2번지
2nd row경상북도 울진군 울진읍 읍내리 281-5번지
3rd row서울특별시 도봉구 도봉동 95-36번지
4th row울산광역시 남구 야음동 385-4번지
5th row경상북도 포항시 남구 장기면 양포리 254번지
ValueCountFrequency (%)
경상북도 75
 
3.2%
경기도 62
 
2.7%
서울특별시 52
 
2.2%
전라남도 50
 
2.1%
경상남도 45
 
1.9%
강원도 34
 
1.5%
충청남도 33
 
1.4%
전라북도 29
 
1.2%
충청북도 24
 
1.0%
부산광역시 22
 
0.9%
Other values (1353) 1900
81.7%
2023-12-11T00:01:56.856097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1828
 
16.4%
지 512
 
4.6%
번 499
 
4.5%
도 401
 
3.6%
1 378
 
3.4%
시 367
 
3.3%
- 338
 
3.0%
동 297
 
2.7%
리 275
 
2.5%
2 249
 
2.2%
Other values (246) 5972
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7003
63.0%
Decimal Number 1945
 
17.5%
Space Separator 1828
 
16.4%
Dash Punctuation 338
 
3.0%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 512
 
7.3%
번 499
 
7.1%
도 401
 
5.7%
시 367
 
5.2%
동 297
 
4.2%
리 275
 
3.9%
구 215
 
3.1%
경 202
 
2.9%
면 201
 
2.9%
남 193
 
2.8%
Other values (232) 3841
54.8%
Decimal Number
ValueCountFrequency (%)
1 378
19.4%
2 249
12.8%
3 237
12.2%
7 183
9.4%
4 171
8.8%
5 161
8.3%
6 156
8.0%
9 139
 
7.1%
0 136
 
7.0%
8 135
 
6.9%
Space Separator
ValueCountFrequency (%)
1828
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 338
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7001
63.0%
Common 4113
37.0%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 512
 
7.3%
번 499
 
7.1%
도 401
 
5.7%
시 367
 
5.2%
동 297
 
4.2%
리 275
 
3.9%
구 215
 
3.1%
경 202
 
2.9%
면 201
 
2.9%
남 193
 
2.8%
Other values (230) 3839
54.8%
Common
ValueCountFrequency (%)
1828
44.4%
1 378
 
9.2%
- 338
 
8.2%
2 249
 
6.1%
3 237
 
5.8%
7 183
 
4.4%
4 171
 
4.2%
5 161
 
3.9%
6 156
 
3.8%
9 139
 
3.4%
Other values (4) 273
 
6.6%
Han
ValueCountFrequency (%)
岩 1
50.0%
岐 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7001
63.0%
ASCII 4113
37.0%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1828
44.4%
1 378
 
9.2%
- 338
 
8.2%
2 249
 
6.1%
3 237
 
5.8%
7 183
 
4.4%
4 171
 
4.2%
5 161
 
3.9%
6 156
 
3.8%
9 139
 
3.4%
Other values (4) 273
 
6.6%
Hangul
ValueCountFrequency (%)
지 512
 
7.3%
번 499
 
7.1%
도 401
 
5.7%
시 367
 
5.2%
동 297
 
4.2%
리 275
 
3.9%
구 215
 
3.1%
경 202
 
2.9%
면 201
 
2.9%
남 193
 
2.8%
Other values (230) 3839
54.8%
CJK
ValueCountFrequency (%)
岩 1
50.0%
岐 1
50.0%

도로명_대지_위치
Text

MISSING 

Distinct404
Distinct (%)100.0%
Missing96
Missing (%)19.2%
Memory size4.0 KiB
2023-12-11T00:01:57.440972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length19.039604
Min length14

Characters and Unicode

Total characters7692
Distinct characters271
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

Unique404 ?
Unique (%)100.0%

Sample

1st row전라남도 순천시 호현1길 34
2nd row경기도 평택시 부용로17번길 9
3rd row전라남도 장흥군 방촌길 91-23
4th row대구광역시 남구 봉덕로5길 17
5th row경상북도 영천시 운북로 1772
ValueCountFrequency (%)
경기도 69
 
4.1%
경상남도 48
 
2.9%
경상북도 42
 
2.5%
전라남도 37
 
2.2%
서울특별시 29
 
1.7%
부산광역시 25
 
1.5%
전라북도 25
 
1.5%
충청남도 23
 
1.4%
강원도 22
 
1.3%
대구광역시 19
 
1.1%
Other values (874) 1336
79.8%
2023-12-11T00:01:58.331465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1272
 
16.5%
1 328
 
4.3%
시 322
 
4.2%
도 309
 
4.0%
길 309
 
4.0%
로 252
 
3.3%
2 234
 
3.0%
구 195
 
2.5%
3 180
 
2.3%
경 178
 
2.3%
Other values (261) 4113
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4719
61.3%
Decimal Number 1526
 
19.8%
Space Separator 1272
 
16.5%
Dash Punctuation 175
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 322
 
6.8%
도 309
 
6.5%
길 309
 
6.5%
로 252
 
5.3%
구 195
 
4.1%
경 178
 
3.8%
남 159
 
3.4%
상 117
 
2.5%
북 111
 
2.4%
번 111
 
2.4%
Other values (249) 2656
56.3%
Decimal Number
ValueCountFrequency (%)
1 328
21.5%
2 234
15.3%
3 180
11.8%
5 139
9.1%
4 128
 
8.4%
6 125
 
8.2%
9 99
 
6.5%
7 99
 
6.5%
0 97
 
6.4%
8 97
 
6.4%
Space Separator
ValueCountFrequency (%)
1272
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 175
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4719
61.3%
Common 2973
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 322
 
6.8%
도 309
 
6.5%
길 309
 
6.5%
로 252
 
5.3%
구 195
 
4.1%
경 178
 
3.8%
남 159
 
3.4%
상 117
 
2.5%
북 111
 
2.4%
번 111
 
2.4%
Other values (249) 2656
56.3%
Common
ValueCountFrequency (%)
1272
42.8%
1 328
 
11.0%
2 234
 
7.9%
3 180
 
6.1%
- 175
 
5.9%
5 139
 
4.7%
4 128
 
4.3%
6 125
 
4.2%
9 99
 
3.3%
7 99
 
3.3%
Other values (2) 194
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4719
61.3%
ASCII 2973
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1272
42.8%
1 328
 
11.0%
2 234
 
7.9%
3 180
 
6.1%
- 175
 
5.9%
5 139
 
4.7%
4 128
 
4.3%
6 125
 
4.2%
9 99
 
3.3%
7 99
 
3.3%
Other values (2) 194
 
6.5%
Hangul
ValueCountFrequency (%)
시 322
 
6.8%
도 309
 
6.5%
길 309
 
6.5%
로 252
 
5.3%
구 195
 
4.1%
경 178
 
3.8%
남 159
 
3.4%
상 117
 
2.5%
북 111
 
2.4%
번 111
 
2.4%
Other values (249) 2656
56.3%

건물_명
Text

MISSING 

Distinct54
Distinct (%)94.7%
Missing443
Missing (%)88.6%
Memory size4.0 KiB
2023-12-11T00:01:58.805840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length15
Mean length6.1578947
Min length1

Characters and Unicode

Total characters351
Distinct characters156
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)89.5%

Sample

1st row삼호아파트
2nd row여천전남병원
3rd row서정동 867 의료시설 ((주)송림의료재단)
4th row성서우방유쉘
5th row(주)신도리코
ValueCountFrequency (%)
2
 
2.9%
a동 2
 
2.9%
삼성아파트 2
 
2.9%
주)기흥대표박옥희 1
 
1.4%
그린맨션3차 1
 
1.4%
주공외인연립 1
 
1.4%
성서우방유쉘 1
 
1.4%
대웅빌라 1
 
1.4%
혁성쉐르빌 1
 
1.4%
봉곡프라자 1
 
1.4%
Other values (56) 56
81.2%
2023-12-11T00:01:59.586959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 12
 
3.4%
12
 
3.4%
빌 12
 
3.4%
동 11
 
3.1%
( 9
 
2.6%
) 9
 
2.6%
아 9
 
2.6%
트 8
 
2.3%
성 7
 
2.0%
리 7
 
2.0%
Other values (146) 255
72.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 294
83.8%
Decimal Number 17
 
4.8%
Space Separator 12
 
3.4%
Open Punctuation 9
 
2.6%
Close Punctuation 9
 
2.6%
Other Punctuation 5
 
1.4%
Uppercase Letter 3
 
0.9%
Dash Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 12
 
4.1%
빌 12
 
4.1%
동 11
 
3.7%
아 9
 
3.1%
트 8
 
2.7%
성 7
 
2.4%
리 7
 
2.4%
대 6
 
2.0%
파 6
 
2.0%
라 6
 
2.0%
Other values (128) 210
71.4%
Decimal Number
ValueCountFrequency (%)
2 4
23.5%
3 3
17.6%
7 3
17.6%
1 2
11.8%
0 1
 
5.9%
6 1
 
5.9%
8 1
 
5.9%
9 1
 
5.9%
4 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
' 2
40.0%
. 2
40.0%
· 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
D 1
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 294
83.8%
Common 54
 
15.4%
Latin 3
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 12
 
4.1%
빌 12
 
4.1%
동 11
 
3.7%
아 9
 
3.1%
트 8
 
2.7%
성 7
 
2.4%
리 7
 
2.4%
대 6
 
2.0%
파 6
 
2.0%
라 6
 
2.0%
Other values (128) 210
71.4%
Common
ValueCountFrequency (%)
12
22.2%
( 9
16.7%
) 9
16.7%
2 4
 
7.4%
3 3
 
5.6%
7 3
 
5.6%
1 2
 
3.7%
' 2
 
3.7%
- 2
 
3.7%
. 2
 
3.7%
Other values (6) 6
11.1%
Latin
ValueCountFrequency (%)
A 2
66.7%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 294
83.8%
ASCII 56
 
16.0%
None 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 12
 
4.1%
빌 12
 
4.1%
동 11
 
3.7%
아 9
 
3.1%
트 8
 
2.7%
성 7
 
2.4%
리 7
 
2.4%
대 6
 
2.0%
파 6
 
2.0%
라 6
 
2.0%
Other values (128) 210
71.4%
ASCII
ValueCountFrequency (%)
12
21.4%
( 9
16.1%
) 9
16.1%
2 4
 
7.1%
3 3
 
5.4%
7 3
 
5.4%
1 2
 
3.6%
' 2
 
3.6%
- 2
 
3.6%
. 2
 
3.6%
Other values (7) 8
14.3%
None
ValueCountFrequency (%)
· 1
100.0%

시군구_코드
Real number (ℝ)

Distinct206
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38828.544
Minimum11110
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:01:59.841210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11500
Q130890
median43130
Q346910
95-th percentile48270
Maximum50130
Range39020
Interquartile range (IQR)16020

Descriptive statistics

Standard deviation11537.372
Coefficient of variation (CV)0.29713636
Kurtosis0.70969154
Mean38828.544
Median Absolute Deviation (MAD)3991.5
Skewness-1.4007779
Sum19414272
Variance1.3311096 × 108
MonotonicityNot monotonic
2023-12-11T00:02:00.141178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46130 8
 
1.6%
48170 8
 
1.6%
47190 8
 
1.6%
41590 8
 
1.6%
47130 8
 
1.6%
44270 7
 
1.4%
11740 7
 
1.4%
11560 7
 
1.4%
11620 7
 
1.4%
48125 7
 
1.4%
Other values (196) 425
85.0%
ValueCountFrequency (%)
11110 3
0.6%
11140 1
 
0.2%
11170 1
 
0.2%
11200 1
 
0.2%
11215 3
0.6%
11230 1
 
0.2%
11260 1
 
0.2%
11290 2
0.4%
11305 3
0.6%
11320 1
 
0.2%
ValueCountFrequency (%)
50130 3
0.6%
50110 2
0.4%
48890 2
0.4%
48880 3
0.6%
48860 4
0.8%
48850 1
 
0.2%
48840 2
0.4%
48820 1
 
0.2%
48740 1
 
0.2%
48730 1
 
0.2%

법정동_코드
Real number (ℝ)

Distinct194
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22114.434
Minimum10100
Maximum47024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:02:00.473799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10100
5-th percentile10195
Q110800
median25021
Q333029.75
95-th percentile40021
Maximum47024
Range36924
Interquartile range (IQR)22229.75

Descriptive statistics

Standard deviation11472.969
Coefficient of variation (CV)0.51880004
Kurtosis-1.5640857
Mean22114.434
Median Absolute Deviation (MAD)12921
Skewness0.28232368
Sum11057217
Variance1.3162903 × 108
MonotonicityNot monotonic
2023-12-11T00:02:01.172743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10100 25
 
5.0%
10300 20
 
4.0%
10200 17
 
3.4%
10800 16
 
3.2%
10400 15
 
3.0%
10600 14
 
2.8%
10700 13
 
2.6%
25021 11
 
2.2%
11200 11
 
2.2%
10500 10
 
2.0%
Other values (184) 348
69.6%
ValueCountFrequency (%)
10100 25
5.0%
10200 17
3.4%
10300 20
4.0%
10400 15
3.0%
10500 10
 
2.0%
10600 14
2.8%
10700 13
2.6%
10800 16
3.2%
10900 10
 
2.0%
11000 8
 
1.6%
ValueCountFrequency (%)
47024 1
0.2%
45026 1
0.2%
44036 1
0.2%
43033 1
0.2%
43023 1
0.2%
42032 1
0.2%
42028 2
0.4%
42025 1
0.2%
42024 1
0.2%
42022 1
0.2%

대지_구분_코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
496 
1
 
3
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 496
99.2%
1 3
 
0.6%
2 1
 
0.2%

Length

2023-12-11T00:02:01.483476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:02:01.720536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 496
99.2%
1 3
 
0.6%
2 1
 
0.2%

번
Real number (ℝ)

Distinct385
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean477.694
Minimum0
Maximum4933
Zeros2
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:02:01.978156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.9
Q1145.75
median366.5
Q3662
95-th percentile1229.2
Maximum4933
Range4933
Interquartile range (IQR)516.25

Descriptive statistics

Standard deviation486.06655
Coefficient of variation (CV)1.017527
Kurtosis19.275455
Mean477.694
Median Absolute Deviation (MAD)250.5
Skewness3.1681104
Sum238847
Variance236260.69
MonotonicityNot monotonic
2023-12-11T00:02:02.303043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
533 5
 
1.0%
3 5
 
1.0%
30 4
 
0.8%
2 4
 
0.8%
71 4
 
0.8%
15 4
 
0.8%
278 3
 
0.6%
35 3
 
0.6%
437 3
 
0.6%
372 3
 
0.6%
Other values (375) 462
92.4%
ValueCountFrequency (%)
0 2
 
0.4%
1 3
0.6%
2 4
0.8%
3 5
1.0%
4 1
 
0.2%
6 1
 
0.2%
7 1
 
0.2%
8 2
 
0.4%
9 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
4933 1
0.2%
3584 1
0.2%
2923 1
0.2%
2751 1
0.2%
2583 1
0.2%
2090 1
0.2%
2014 1
0.2%
1947 1
0.2%
1729 1
0.2%
1685 1
0.2%

지
Real number (ℝ)

ZEROS 

Distinct69
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.024
Minimum0
Maximum851
Zeros156
Zeros (%)31.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:02:02.615739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310
95-th percentile65.05
Maximum851
Range851
Interquartile range (IQR)10

Descriptive statistics

Standard deviation58.528785
Coefficient of variation (CV)3.6525702
Kurtosis110.20641
Mean16.024
Median Absolute Deviation (MAD)2
Skewness9.4055128
Sum8012
Variance3425.6187
MonotonicityNot monotonic
2023-12-11T00:02:02.949033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 156
31.2%
1 66
13.2%
2 37
 
7.4%
3 30
 
6.0%
5 21
 
4.2%
4 20
 
4.0%
9 14
 
2.8%
6 13
 
2.6%
8 11
 
2.2%
13 9
 
1.8%
Other values (59) 123
24.6%
ValueCountFrequency (%)
0 156
31.2%
1 66
13.2%
2 37
 
7.4%
3 30
 
6.0%
4 20
 
4.0%
5 21
 
4.2%
6 13
 
2.6%
7 6
 
1.2%
8 11
 
2.2%
9 14
 
2.8%
ValueCountFrequency (%)
851 1
0.2%
561 1
0.2%
529 1
0.2%
297 1
0.2%
201 1
0.2%
185 1
0.2%
180 1
0.2%
178 1
0.2%
159 1
0.2%
151 1
0.2%

특수지_명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
499 
3
 
1

Length

Max length4
Median length4
Mean length3.994
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 499
99.8%
3 1
 
0.2%

Length

2023-12-11T00:02:03.255724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:02:03.540937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 499
99.8%
3 1
 
0.2%

블록
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500
Missing (%)100.0%
Memory size4.5 KiB

로트
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing499
Missing (%)99.8%
Memory size4.0 KiB
2023-12-11T00:02:03.662649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row8L
ValueCountFrequency (%)
8l 1
100.0%
2023-12-11T00:02:04.104763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 1
50.0%
L 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
50.0%
Uppercase Letter 1
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
50.0%
Latin 1
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 1
100.0%
Latin
ValueCountFrequency (%)
L 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 1
50.0%
L 1
50.0%

새주소_도로_코드
Real number (ℝ)

MISSING 

Distinct414
Distinct (%)100.0%
Missing86
Missing (%)17.2%
Infinite0
Infinite (%)0.0%
Mean3.8395108 × 1011
Minimum1.111041 × 1011
Maximum5.0130485 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:02:04.395907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111041 × 1011
5-th percentile1.1440414 × 1011
Q12.9200344 × 1011
median4.3730388 × 1011
Q34.6887844 × 1011
95-th percentile4.8730386 × 1011
Maximum5.0130485 × 1011
Range3.9020075 × 1011
Interquartile range (IQR)1.7687499 × 1011

Descriptive statistics

Standard deviation1.1418074 × 1011
Coefficient of variation (CV)0.29738357
Kurtosis0.36319331
Mean3.8395108 × 1011
Median Absolute Deviation (MAD)3.460084 × 1010
Skewness-1.227437
Sum1.5895575 × 1014
Variance1.3037242 × 1022
MonotonicityNot monotonic
2023-12-11T00:02:04.748031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
271104223084 1
 
0.2%
479203324022 1
 
0.2%
292004289643 1
 
0.2%
116204160419 1
 
0.2%
272304235096 1
 
0.2%
116504163730 1
 
0.2%
117404172015 1
 
0.2%
431113236035 1
 
0.2%
418204448005 1
 
0.2%
467804670287 1
 
0.2%
Other values (404) 404
80.8%
(Missing) 86
 
17.2%
ValueCountFrequency (%)
111104100121 1
0.2%
111704106209 1
0.2%
111704106454 1
0.2%
112004109094 1
0.2%
112154112144 1
0.2%
112304115298 1
0.2%
112604118155 1
0.2%
112903005044 1
0.2%
112903107011 1
0.2%
112904121323 1
0.2%
ValueCountFrequency (%)
501304850959 1
0.2%
501303350067 1
0.2%
501303349238 1
0.2%
501104848152 1
0.2%
501103349118 1
0.2%
501103349018 1
0.2%
488904844147 1
0.2%
488904844139 1
0.2%
488903348030 1
0.2%
488804841289 1
0.2%

새주소_법정동_코드
Real number (ℝ)

MISSING 

Distinct107
Distinct (%)26.0%
Missing89
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean20551.129
Minimum10101
Maximum44001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:02:05.101938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10101
Q110701
median13401
Q332001
95-th percentile38001
Maximum44001
Range33900
Interquartile range (IQR)21300

Descriptive statistics

Standard deviation10861.866
Coefficient of variation (CV)0.52852894
Kurtosis-1.3993277
Mean20551.129
Median Absolute Deviation (MAD)3300
Skewness0.47743675
Sum8446514
Variance1.1798014 × 108
MonotonicityNot monotonic
2023-12-11T00:02:05.397090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25001 41
 
8.2%
10101 23
 
4.6%
10201 19
 
3.8%
10901 16
 
3.2%
32001 16
 
3.2%
10301 15
 
3.0%
35001 13
 
2.6%
33001 13
 
2.6%
34001 12
 
2.4%
31001 12
 
2.4%
Other values (97) 231
46.2%
(Missing) 89
 
17.8%
ValueCountFrequency (%)
10101 23
4.6%
10201 19
3.8%
10202 2
 
0.4%
10301 15
3.0%
10302 5
 
1.0%
10401 6
 
1.2%
10402 2
 
0.4%
10403 1
 
0.2%
10501 10
2.0%
10502 1
 
0.2%
ValueCountFrequency (%)
44001 1
 
0.2%
43002 1
 
0.2%
43001 2
 
0.4%
42001 3
 
0.6%
41001 2
 
0.4%
40001 2
 
0.4%
39501 2
 
0.4%
39003 1
 
0.2%
39001 6
1.2%
38001 8
1.6%

새주소_지상지하_코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-11T00:02:05.656213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T00:02:05.851233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

새주소_본_번
Real number (ℝ)

MISSING  ZEROS 

Distinct177
Distinct (%)41.1%
Missing69
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean134.82367
Minimum0
Maximum4208
Zeros12
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:02:06.094213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q114
median34
Q395
95-th percentile604
Maximum4208
Range4208
Interquartile range (IQR)81

Descriptive statistics

Standard deviation350.15055
Coefficient of variation (CV)2.5971
Kurtosis57.744515
Mean134.82367
Median Absolute Deviation (MAD)27
Skewness6.5913949
Sum58109
Variance122605.41
MonotonicityNot monotonic
2023-12-11T00:02:06.375063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12
 
2.4%
3 10
 
2.0%
20 10
 
2.0%
13 10
 
2.0%
19 10
 
2.0%
7 9
 
1.8%
6 9
 
1.8%
10 9
 
1.8%
23 8
 
1.6%
2 8
 
1.6%
Other values (167) 336
67.2%
(Missing) 69
 
13.8%
ValueCountFrequency (%)
0 12
2.4%
1 1
 
0.2%
2 8
1.6%
3 10
2.0%
4 6
1.2%
5 7
1.4%
6 9
1.8%
7 9
1.8%
8 7
1.4%
9 4
 
0.8%
ValueCountFrequency (%)
4208 1
0.2%
2905 1
0.2%
2407 1
0.2%
1754 1
0.2%
1728 1
0.2%
1532 1
0.2%
1377 1
0.2%
1284 1
0.2%
1271 1
0.2%
1081 1
0.2%

새주소_부_번
Real number (ℝ)

MISSING  ZEROS 

Distinct45
Distinct (%)11.0%
Missing90
Missing (%)18.0%
Infinite0
Infinite (%)0.0%
Mean5.3682927
Minimum0
Maximum91
Zeros222
Zeros (%)44.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:02:06.641492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile28.55
Maximum91
Range91
Interquartile range (IQR)6

Descriptive statistics

Standard deviation11.210956
Coefficient of variation (CV)2.0883654
Kurtosis15.664115
Mean5.3682927
Median Absolute Deviation (MAD)0
Skewness3.503227
Sum2201
Variance125.68554
MonotonicityNot monotonic
2023-12-11T00:02:06.903361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 222
44.4%
1 27
 
5.4%
2 15
 
3.0%
6 14
 
2.8%
7 14
 
2.8%
3 13
 
2.6%
4 13
 
2.6%
5 12
 
2.4%
8 9
 
1.8%
12 6
 
1.2%
Other values (35) 65
 
13.0%
(Missing) 90
18.0%
ValueCountFrequency (%)
0 222
44.4%
1 27
 
5.4%
2 15
 
3.0%
3 13
 
2.6%
4 13
 
2.6%
5 12
 
2.4%
6 14
 
2.8%
7 14
 
2.8%
8 9
 
1.8%
9 5
 
1.0%
ValueCountFrequency (%)
91 1
0.2%
72 1
0.2%
61 1
0.2%
59 1
0.2%
51 1
0.2%
50 1
0.2%
49 1
0.2%
47 1
0.2%
44 1
0.2%
42 1
0.2%

형식_코드
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)7.6%
Missing302
Missing (%)60.4%
Infinite0
Infinite (%)0.0%
Mean208.55556
Minimum101
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:02:07.096325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile106
Q1199
median201
Q3210.5
95-th percentile300
Maximum300
Range199
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation61.705165
Coefficient of variation (CV)0.2958692
Kurtosis-0.67132554
Mean208.55556
Median Absolute Deviation (MAD)2
Skewness0.071599616
Sum41294
Variance3807.5274
MonotonicityNot monotonic
2023-12-11T00:02:07.312968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
201 74
 
14.8%
300 43
 
8.6%
199 23
 
4.6%
117 19
 
3.8%
106 9
 
1.8%
204 6
 
1.2%
299 5
 
1.0%
119 4
 
0.8%
206 4
 
0.8%
102 4
 
0.8%
Other values (5) 7
 
1.4%
(Missing) 302
60.4%
ValueCountFrequency (%)
101 1
 
0.2%
102 4
 
0.8%
106 9
 
1.8%
117 19
 
3.8%
119 4
 
0.8%
199 23
 
4.6%
201 74
14.8%
202 3
 
0.6%
204 6
 
1.2%
206 4
 
0.8%
ValueCountFrequency (%)
300 43
8.6%
299 5
 
1.0%
212 1
 
0.2%
211 1
 
0.2%
209 1
 
0.2%
206 4
 
0.8%
204 6
 
1.2%
202 3
 
0.6%
201 74
14.8%
199 23
 
4.6%

형식_코드_명
Categorical

IMBALANCE 

Distinct17
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
331 
부패탱크방법
54 
하수종말처리장연결
 
26
접촉폭기방법
 
23
기타오수처리시설
 
20
Other values (12)
46 

Length

Max length13
Median length4
Mean length5.122
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 331
66.2%
부패탱크방법 54
 
10.8%
하수종말처리장연결 26
 
5.2%
접촉폭기방법 23
 
4.6%
기타오수처리시설 20
 
4.0%
현수미생물접촉방법 9
 
1.8%
살수형부패탱크방법 6
 
1.2%
혐기및호기성미생물조정방법 6
 
1.2%
기타단독정화조 6
 
1.2%
임호프방식 4
 
0.8%
Other values (7) 15
 
3.0%

Length

2023-12-11T00:02:07.583200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 331
66.2%
부패탱크방법 54
 
10.8%
하수종말처리장연결 26
 
5.2%
접촉폭기방법 23
 
4.6%
기타오수처리시설 20
 
4.0%
현수미생물접촉방법 9
 
1.8%
혐기및호기성미생물조정방법 6
 
1.2%
기타단독정화조 6
 
1.2%
살수형부패탱크방법 6
 
1.2%
임호프방식 4
 
0.8%
Other values (7) 15
 
3.0%

기타_형식
Text

MISSING 

Distinct80
Distinct (%)40.4%
Missing302
Missing (%)60.4%
Memory size4.0 KiB
2023-12-11T00:02:07.989334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length6.6767677
Min length2

Characters and Unicode

Total characters1322
Distinct characters98
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)29.8%

Sample

1st row하수종말처리장연결
2nd row부패탱크방법
3rd row콘크리트각형
4th row기타단독정화조
5th row각형
ValueCountFrequency (%)
부패탱크방법 42
20.4%
하수종말처리장연결 24
 
11.7%
기타오수처리시설 14
 
6.8%
접촉폭기식 12
 
5.8%
콘크리트각형 8
 
3.9%
f.r.p 8
 
3.9%
접촉폭기방법 4
 
1.9%
p.e 4
 
1.9%
콘크리트 3
 
1.5%
frp 3
 
1.5%
Other values (67) 84
40.8%
2023-12-11T00:02:08.734763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
크 65
 
4.9%
법 62
 
4.7%
방 61
 
4.6%
기 59
 
4.5%
수 56
 
4.2%
리 55
 
4.2%
부 53
 
4.0%
패 52
 
3.9%
탱 50
 
3.8%
처 40
 
3.0%
Other values (88) 769
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1164
88.0%
Uppercase Letter 109
 
8.2%
Other Punctuation 32
 
2.4%
Space Separator 8
 
0.6%
Decimal Number 7
 
0.5%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
크 65
 
5.6%
법 62
 
5.3%
방 61
 
5.2%
기 59
 
5.1%
수 56
 
4.8%
리 55
 
4.7%
부 53
 
4.6%
패 52
 
4.5%
탱 50
 
4.3%
처 40
 
3.4%
Other values (67) 611
52.5%
Uppercase Letter
ValueCountFrequency (%)
P 32
29.4%
R 23
21.1%
F 22
20.2%
C 10
 
9.2%
E 9
 
8.3%
O 4
 
3.7%
N 4
 
3.7%
B 2
 
1.8%
H 1
 
0.9%
V 1
 
0.9%
Decimal Number
ValueCountFrequency (%)
3 3
42.9%
0 1
 
14.3%
5 1
 
14.3%
8 1
 
14.3%
1 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 30
93.8%
' 2
 
6.2%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1164
88.0%
Latin 109
 
8.2%
Common 49
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
크 65
 
5.6%
법 62
 
5.3%
방 61
 
5.2%
기 59
 
5.1%
수 56
 
4.8%
리 55
 
4.7%
부 53
 
4.6%
패 52
 
4.5%
탱 50
 
4.3%
처 40
 
3.4%
Other values (67) 611
52.5%
Latin
ValueCountFrequency (%)
P 32
29.4%
R 23
21.1%
F 22
20.2%
C 10
 
9.2%
E 9
 
8.3%
O 4
 
3.7%
N 4
 
3.7%
B 2
 
1.8%
H 1
 
0.9%
V 1
 
0.9%
Common
ValueCountFrequency (%)
. 30
61.2%
8
 
16.3%
3 3
 
6.1%
' 2
 
4.1%
0 1
 
2.0%
5 1
 
2.0%
8 1
 
2.0%
1 1
 
2.0%
( 1
 
2.0%
) 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1164
88.0%
ASCII 158
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
크 65
 
5.6%
법 62
 
5.3%
방 61
 
5.2%
기 59
 
5.1%
수 56
 
4.8%
리 55
 
4.7%
부 53
 
4.6%
패 52
 
4.5%
탱 50
 
4.3%
처 40
 
3.4%
Other values (67) 611
52.5%
ASCII
ValueCountFrequency (%)
P 32
20.3%
. 30
19.0%
R 23
14.6%
F 22
13.9%
C 10
 
6.3%
E 9
 
5.7%
8
 
5.1%
O 4
 
2.5%
N 4
 
2.5%
3 3
 
1.9%
Other values (11) 13
8.2%

단위_구분_코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500
Missing (%)100.0%
Memory size4.5 KiB

단위_구분_코드_명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing499
Missing (%)99.8%
Memory size4.0 KiB
2023-12-11T00:02:08.943124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row루베
ValueCountFrequency (%)
루베 1
100.0%
2023-12-11T00:02:09.422601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
루 1
50.0%
베 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
루 1
50.0%
베 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
루 1
50.0%
베 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
루 1
50.0%
베 1
50.0%

용량_인용
Real number (ℝ)

SKEWED  ZEROS 

Distinct32
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.70104
Minimum0
Maximum6400
Zeros371
Zeros (%)74.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:02:09.760653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile90.25
Maximum6400
Range6400
Interquartile range (IQR)5

Descriptive statistics

Standard deviation293.40971
Coefficient of variation (CV)9.8787689
Kurtosis447.7914
Mean29.70104
Median Absolute Deviation (MAD)0
Skewness20.666398
Sum14850.52
Variance86089.258
MonotonicityNot monotonic
2023-12-11T00:02:10.071101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 371
74.2%
5.0 28
 
5.6%
10.0 21
 
4.2%
30.0 10
 
2.0%
25.0 7
 
1.4%
20.0 7
 
1.4%
60.0 6
 
1.2%
50.0 6
 
1.2%
15.0 6
 
1.2%
120.0 5
 
1.0%
Other values (22) 33
 
6.6%
ValueCountFrequency (%)
0.0 371
74.2%
5.0 28
 
5.6%
9.52 1
 
0.2%
10.0 21
 
4.2%
15.0 6
 
1.2%
17.0 1
 
0.2%
19.0 1
 
0.2%
20.0 7
 
1.4%
25.0 7
 
1.4%
30.0 10
 
2.0%
ValueCountFrequency (%)
6400.0 1
 
0.2%
700.0 1
 
0.2%
555.0 1
 
0.2%
500.0 4
0.8%
340.0 1
 
0.2%
300.0 1
 
0.2%
235.0 1
 
0.2%
230.0 1
 
0.2%
200.0 1
 
0.2%
180.0 1
 
0.2%

용량_루베
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.66038
Minimum0
Maximum40
Zeros459
Zeros (%)91.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:02:10.385938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum40
Range40
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.6065715
Coefficient of variation (CV)5.4613579
Kurtosis76.72792
Mean0.66038
Median Absolute Deviation (MAD)0
Skewness8.1887248
Sum330.19
Variance13.007358
MonotonicityNot monotonic
2023-12-11T00:02:10.741141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 459
91.8%
1.0 6
 
1.2%
3.0 4
 
0.8%
2.0 4
 
0.8%
10.0 3
 
0.6%
6.0 2
 
0.4%
4.0 2
 
0.4%
40.0 2
 
0.4%
8.0 2
 
0.4%
20.0 2
 
0.4%
Other values (13) 14
 
2.8%
ValueCountFrequency (%)
0.0 459
91.8%
0.51 1
 
0.2%
0.68 1
 
0.2%
1.0 6
 
1.2%
1.4 1
 
0.2%
2.0 4
 
0.8%
3.0 4
 
0.8%
3.1 1
 
0.2%
4.0 2
 
0.4%
4.5 1
 
0.2%
ValueCountFrequency (%)
40.0 2
0.4%
35.0 1
 
0.2%
20.0 2
0.4%
18.0 1
 
0.2%
16.0 1
 
0.2%
11.0 1
 
0.2%
10.0 3
0.6%
8.0 2
0.4%
7.2 1
 
0.2%
6.0 2
0.4%

생성_일자
Real number (ℝ)

Distinct203
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20120494
Minimum20090318
Maximum20160601
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-11T00:02:11.102721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090318
5-th percentile20091100
Q120110420
median20111123
Q320140245
95-th percentile20151118
Maximum20160601
Range70283
Interquartile range (IQR)29824.75

Descriptive statistics

Standard deviation17973.889
Coefficient of variation (CV)0.00089331248
Kurtosis-0.63853008
Mean20120494
Median Absolute Deviation (MAD)709
Skewness0.61778346
Sum1.0060247 × 1010
Variance3.2306068 × 108
MonotonicityNot monotonic
2023-12-11T00:02:11.457565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110420 44
 
8.8%
20110415 33
 
6.6%
20111124 32
 
6.4%
20111123 31
 
6.2%
20111117 27
 
5.4%
20110418 16
 
3.2%
20111118 13
 
2.6%
20111021 12
 
2.4%
20090319 8
 
1.6%
20140902 8
 
1.6%
Other values (193) 276
55.2%
ValueCountFrequency (%)
20090318 4
0.8%
20090319 8
1.6%
20090320 1
 
0.2%
20090321 3
 
0.6%
20090323 1
 
0.2%
20090515 1
 
0.2%
20090618 1
 
0.2%
20090714 1
 
0.2%
20090807 1
 
0.2%
20090814 1
 
0.2%
ValueCountFrequency (%)
20160601 1
 
0.2%
20160513 1
 
0.2%
20160429 1
 
0.2%
20160421 1
 
0.2%
20160415 1
 
0.2%
20160407 2
0.4%
20160323 1
 
0.2%
20160218 1
 
0.2%
20160217 1
 
0.2%
20160212 3
0.6%

Sample

관리_건축물대장_PK대장_구분_코드대장_구분_코드_명대장_종류_코드대장_종류_코드_명대지_위치도로명_대지_위치건물_명시군구_코드법정동_코드대지_구분_코드번지특수지_명블록로트새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번형식_코드형식_코드_명기타_형식단위_구분_코드단위_구분_코드_명용량_인용용량_루베생성_일자
048870-205421일반2표제부전라남도 여수시 덕충동 102-2번지<NA><NA>468301040004805<NA><NA><NA>471304715116<NA>0467<NA>접촉폭기방법하수종말처리장연결<NA><NA>0.00.020110415
111560-335251일반2일반건축물경상북도 울진군 울진읍 읍내리 281-5번지전라남도 순천시 호현1길 34<NA>43130104000309139<NA><NA><NA>416304436167320010780<NA><NA>부패탱크방법<NA><NA>25.00.020150207
243740-1001959921일반2일반건축물서울특별시 도봉구 도봉동 95-36번지경기도 평택시 부용로17번길 9<NA>479001190003751<NA><NA><NA>4511346014601340101643300<NA>콘크리트각형<NA><NA>0.00.020121116
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