Overview

Dataset statistics

Number of variables4
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory37.7 B

Variable types

Text2
DateTime1
Numeric1

Dataset

Description울산광역시 내 개발 제한 구역 해제 현황에 대한 데이터로 구분, 고시, 고시일, 해제된면적(제곱미터)을 제공합니다.
URLhttps://www.data.go.kr/data/15020186/fileData.do

Alerts

해제된면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:14:58.261375
Analysis finished2023-12-12 08:14:58.778021
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-12T17:14:58.946124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length10.892857
Min length6

Characters and Unicode

Total characters305
Distinct characters100
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

Unique26 ?
Unique (%)92.9%

Sample

1st row서생면 전체
2nd row화봉동 임대주택
3rd row화봉동(지구추가)
4th row취락(97개소)해제
5th row정밀화학단지
ValueCountFrequency (%)
공공주택지구 5
 
9.3%
다운2지구 3
 
5.6%
북구 2
 
3.7%
산업단지 2
 
3.7%
우정지구 2
 
3.7%
중구 2
 
3.7%
울산태화강변 1
 
1.9%
범서읍 1
 
1.9%
상안 1
 
1.9%
보금자리주택 1
 
1.9%
Other values (34) 34
63.0%
2023-12-12T17:14:59.411182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 29
 
9.5%
26
 
8.5%
구 20
 
6.6%
단 12
 
3.9%
공 10
 
3.3%
주 10
 
3.3%
택 10
 
3.3%
산 10
 
3.3%
업 8
 
2.6%
정 7
 
2.3%
Other values (90) 163
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 261
85.6%
Space Separator 26
 
8.5%
Decimal Number 7
 
2.3%
Close Punctuation 5
 
1.6%
Open Punctuation 5
 
1.6%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 29
 
11.1%
구 20
 
7.7%
단 12
 
4.6%
공 10
 
3.8%
주 10
 
3.8%
택 10
 
3.8%
산 10
 
3.8%
업 8
 
3.1%
정 7
 
2.7%
화 6
 
2.3%
Other values (83) 139
53.3%
Decimal Number
ValueCountFrequency (%)
2 5
71.4%
7 1
 
14.3%
9 1
 
14.3%
Space Separator
ValueCountFrequency (%)
26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 261
85.6%
Common 44
 
14.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 29
 
11.1%
구 20
 
7.7%
단 12
 
4.6%
공 10
 
3.8%
주 10
 
3.8%
택 10
 
3.8%
산 10
 
3.8%
업 8
 
3.1%
정 7
 
2.7%
화 6
 
2.3%
Other values (83) 139
53.3%
Common
ValueCountFrequency (%)
26
59.1%
2 5
 
11.4%
) 5
 
11.4%
( 5
 
11.4%
7 1
 
2.3%
9 1
 
2.3%
/ 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 261
85.6%
ASCII 44
 
14.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 29
 
11.1%
구 20
 
7.7%
단 12
 
4.6%
공 10
 
3.8%
주 10
 
3.8%
택 10
 
3.8%
산 10
 
3.8%
업 8
 
3.1%
정 7
 
2.7%
화 6
 
2.3%
Other values (83) 139
53.3%
ASCII
ValueCountFrequency (%)
26
59.1%
2 5
 
11.4%
) 5
 
11.4%
( 5
 
11.4%
7 1
 
2.3%
9 1
 
2.3%
/ 1
 
2.3%

고시
Text

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-12T17:14:59.665635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length17.964286
Min length17

Characters and Unicode

Total characters503
Distinct characters29
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

Unique26 ?
Unique (%)92.9%

Sample

1st row건설교통부고시 제2001-364호
2nd row건설교통부고시 제2003-130호
3rd row건설교통부고시 제2003-261호
4th row울산광역시고시 제2003-218호
5th row건설교통부고시 제2004-333호
ValueCountFrequency (%)
건설교통부고시 9
 
15.8%
울산광역시고시 7
 
12.3%
국토교통부고시 6
 
10.5%
국토해양부고시 5
 
8.8%
제2007-192호 2
 
3.5%
고시 1
 
1.8%
울산광역시 1
 
1.8%
제2012-24호 1
 
1.8%
제2021-942호 1
 
1.8%
제2020-876호 1
 
1.8%
Other values (23) 23
40.4%
2023-12-12T17:15:00.135587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 52
 
10.3%
2 46
 
9.1%
시 36
 
7.2%
29
 
5.8%
1 29
 
5.8%
고 28
 
5.6%
제 28
 
5.6%
- 28
 
5.6%
호 28
 
5.6%
부 20
 
4.0%
Other values (19) 179
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
50.1%
Decimal Number 194
38.6%
Space Separator 29
 
5.8%
Dash Punctuation 28
 
5.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 36
14.3%
고 28
11.1%
제 28
11.1%
호 28
11.1%
부 20
 
7.9%
교 15
 
6.0%
통 15
 
6.0%
국 11
 
4.4%
토 11
 
4.4%
건 9
 
3.6%
Other values (7) 51
20.2%
Decimal Number
ValueCountFrequency (%)
0 52
26.8%
2 46
23.7%
1 29
14.9%
8 14
 
7.2%
3 11
 
5.7%
4 9
 
4.6%
6 9
 
4.6%
9 9
 
4.6%
7 8
 
4.1%
5 7
 
3.6%
Space Separator
ValueCountFrequency (%)
29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
50.1%
Common 251
49.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 36
14.3%
고 28
11.1%
제 28
11.1%
호 28
11.1%
부 20
 
7.9%
교 15
 
6.0%
통 15
 
6.0%
국 11
 
4.4%
토 11
 
4.4%
건 9
 
3.6%
Other values (7) 51
20.2%
Common
ValueCountFrequency (%)
0 52
20.7%
2 46
18.3%
29
11.6%
1 29
11.6%
- 28
11.2%
8 14
 
5.6%
3 11
 
4.4%
4 9
 
3.6%
6 9
 
3.6%
9 9
 
3.6%
Other values (2) 15
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
50.1%
ASCII 251
49.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 52
20.7%
2 46
18.3%
29
11.6%
1 29
11.6%
- 28
11.2%
8 14
 
5.6%
3 11
 
4.4%
4 9
 
3.6%
6 9
 
3.6%
9 9
 
3.6%
Other values (2) 15
 
6.0%
Hangul
ValueCountFrequency (%)
시 36
14.3%
고 28
11.1%
제 28
11.1%
호 28
11.1%
부 20
 
7.9%
교 15
 
6.0%
통 15
 
6.0%
국 11
 
4.4%
토 11
 
4.4%
건 9
 
3.6%
Other values (7) 51
20.2%

고시일
Date

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
Minimum2002-01-04 00:00:00
Maximum2022-03-10 00:00:00
2023-12-12T17:15:00.291871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:15:00.452411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

해제된면적(제곱미터)
Real number (ℝ)

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1791518.7
Minimum-4276
Maximum35280000
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)7.1%
Memory size384.0 B
2023-12-12T17:15:00.597440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4276
5-th percentile-127.65
Q116173.25
median145161.5
Q3631562.5
95-th percentile3796282
Maximum35280000
Range35284276
Interquartile range (IQR)615389.25

Descriptive statistics

Standard deviation6636582.5
Coefficient of variation (CV)3.7044451
Kurtosis26.637937
Mean1791518.7
Median Absolute Deviation (MAD)144236.5
Skewness5.1137098
Sum50162523
Variance4.4044228 × 1013
MonotonicityNot monotonic
2023-12-12T17:15:00.739750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
35280000 1
 
3.6%
380 1
 
3.6%
8971 1
 
3.6%
314640 1
 
3.6%
137849 1
 
3.6%
18574 1
 
3.6%
5560 1
 
3.6%
49190 1
 
3.6%
1470 1
 
3.6%
152474 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
-4276 1
3.6%
-401 1
3.6%
380 1
3.6%
1470 1
3.6%
5560 1
3.6%
6000 1
3.6%
8971 1
3.6%
18574 1
3.6%
45092 1
3.6%
49190 1
3.6%
ValueCountFrequency (%)
35280000 1
3.6%
4438280 1
3.6%
2604000 1
3.6%
1803403 1
3.6%
1289000 1
3.6%
1197878 1
3.6%
832000 1
3.6%
564750 1
3.6%
442000 1
3.6%
332428 1
3.6%

Interactions

2023-12-12T17:14:58.478254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:15:00.861359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분고시고시일해제된면적(제곱미터)
구분1.0000.9890.9891.000
고시0.9891.0001.0001.000
고시일0.9891.0001.0001.000
해제된면적(제곱미터)1.0001.0001.0001.000

Missing values

2023-12-12T17:14:58.620223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:14:58.729371image/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

구분고시고시일해제된면적(제곱미터)
0서생면 전체건설교통부고시 제2001-364호2002-01-0435280000
1화봉동 임대주택건설교통부고시 제2003-130호2003-06-09442000
2화봉동(지구추가)건설교통부고시 제2003-261호2003-10-316000
3취락(97개소)해제울산광역시고시 제2003-218호2003-12-314438280
4정밀화학단지건설교통부고시 제2004-333호2004-11-20105530
5모듈화산업단지건설교통부고시 제2005-57호2005-03-17832000
6취락(온양외고산)울산광역시고시 제2005-106호2005-03-2489890
7울산신산업단지건설교통부고시 제2005-168호2005-06-24564750
8북구 송정지구건설교통부고시 제2007-192호2007-05-301289000
9중구 우정지구건설교통부고시 제2007-192호2007-05-302604000
구분고시고시일해제된면적(제곱미터)
18청량율리 도시개발사업국토교통부고시 제2014-228호2014-05-0988346
19울산미포국가 산업단지 확장국토교통부고시 제2014-471호2014-08-14332428
20율동 공공주택지구울산광역시고시 제2015-168호2015-07-29152474
21다운2지구 공공주택지구국토교통부고시 제2016-1082호2017-01-031470
22소규모단절토지(재정비)울산광역시고시 제2018-119호2018-06-0749190
23다운2지구 공공주택지구국토교통부고시 제2018-745호2018-12-105560
24덕하지구 토지구획정리사업(단절토지)울산광역시고시 제2019-188호2019-09-0518574
25범서읍 울산태화강변 공공주택지구국토교통부고시 제2020-876호2020-12-18137849
26장현 도시첨단산업단지국토교통부고시 제2021-942호2021-07-13314640
27상안 행복주택 공공주택지구울산광역시 고시 제2022-40호2022-03-108971