Overview

Dataset statistics

Number of variables15
Number of observations27
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory128.9 B

Variable types

Text6
Numeric3
DateTime2
Categorical4

Dataset

Description부산광역시_서구_공개공지현황_20220630
Author부산광역시 서구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15035252

Alerts

공개공지면적 is highly overall correlated with 연면적 and 2 other fieldsHigh correlation
연면적 is highly overall correlated with 공개공지면적 and 1 other fieldsHigh correlation
용도 is highly overall correlated with 연면적High correlation
공개공지개소 is highly overall correlated with 공개공지면적 and 1 other fieldsHigh correlation
공개공지위치 is highly overall correlated with 공개공지면적 and 1 other fieldsHigh correlation
공개공지편의시설 has 1 (3.7%) missing valuesMissing
건축물명 has unique valuesUnique
공개공지면적 has unique valuesUnique
도로명주소 has unique valuesUnique
지번주소 has unique valuesUnique
허가일자 has unique valuesUnique
사용승인일자 has unique valuesUnique
연면적 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:44:02.727274
Analysis finished2023-12-10 16:44:05.954148
Duration3.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축물명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-11T01:44:06.179633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.7037037
Min length4

Characters and Unicode

Total characters181
Distinct characters93
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row동대신센츄럴타운
2nd row아크로폴리스
3rd row송도의 봄여름가을겨울
4th row허브센티움
5th rowLG마린타워
ValueCountFrequency (%)
동대신센츄럴타운 1
 
3.3%
아크로폴리스 1
 
3.3%
에코펠리스7 1
 
3.3%
에코펠리스6 1
 
3.3%
르헤리티지 1
 
3.3%
남명더라우부용 1
 
3.3%
수현빌리지 1
 
3.3%
메리어트호텔 1
 
3.3%
베스트웨스턴플러스송도호텔 1
 
3.3%
경동리인타워 1
 
3.3%
Other values (20) 20
66.7%
2023-12-11T01:44:06.695344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 11
 
6.1%
스 10
 
5.5%
동 5
 
2.8%
타 5
 
2.8%
코 5
 
2.8%
펠 5
 
2.8%
에 5
 
2.8%
3 4
 
2.2%
송 4
 
2.2%
도 4
 
2.2%
Other values (83) 123
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 164
90.6%
Decimal Number 10
 
5.5%
Uppercase Letter 4
 
2.2%
Space Separator 3
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 11
 
6.7%
스 10
 
6.1%
동 5
 
3.0%
타 5
 
3.0%
코 5
 
3.0%
펠 5
 
3.0%
에 5
 
3.0%
송 4
 
2.4%
도 4
 
2.4%
트 4
 
2.4%
Other values (73) 106
64.6%
Decimal Number
ValueCountFrequency (%)
3 4
40.0%
1 2
20.0%
9 1
 
10.0%
6 1
 
10.0%
2 1
 
10.0%
7 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
G 2
50.0%
L 1
25.0%
D 1
25.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164
90.6%
Common 13
 
7.2%
Latin 4
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 11
 
6.7%
스 10
 
6.1%
동 5
 
3.0%
타 5
 
3.0%
코 5
 
3.0%
펠 5
 
3.0%
에 5
 
3.0%
송 4
 
2.4%
도 4
 
2.4%
트 4
 
2.4%
Other values (73) 106
64.6%
Common
ValueCountFrequency (%)
3 4
30.8%
3
23.1%
1 2
15.4%
9 1
 
7.7%
6 1
 
7.7%
2 1
 
7.7%
7 1
 
7.7%
Latin
ValueCountFrequency (%)
G 2
50.0%
L 1
25.0%
D 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 164
90.6%
ASCII 17
 
9.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 11
 
6.7%
스 10
 
6.1%
동 5
 
3.0%
타 5
 
3.0%
코 5
 
3.0%
펠 5
 
3.0%
에 5
 
3.0%
송 4
 
2.4%
도 4
 
2.4%
트 4
 
2.4%
Other values (73) 106
64.6%
ASCII
ValueCountFrequency (%)
3 4
23.5%
3
17.6%
G 2
11.8%
1 2
11.8%
9 1
 
5.9%
6 1
 
5.9%
L 1
 
5.9%
2 1
 
5.9%
D 1
 
5.9%
7 1
 
5.9%

공개공지면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176.85803
Minimum24.63
Maximum846.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-11T01:44:06.899415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24.63
5-th percentile44.573
Q175.16
median113.77
Q3180.34
95-th percentile518.886
Maximum846.6
Range821.97
Interquartile range (IQR)105.18

Descriptive statistics

Standard deviation183.00224
Coefficient of variation (CV)1.0347409
Kurtosis6.5327144
Mean176.85803
Median Absolute Deviation (MAD)49.87
Skewness2.4545653
Sum4775.1668
Variance33489.82
MonotonicityNot monotonic
2023-12-11T01:44:07.073337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
181.95 1
 
3.7%
50.95 1
 
3.7%
118.2 1
 
3.7%
68.4 1
 
3.7%
258.36 1
 
3.7%
24.63 1
 
3.7%
80.9 1
 
3.7%
72.5 1
 
3.7%
164.2368 1
 
3.7%
178.73 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
24.63 1
3.7%
41.84 1
3.7%
50.95 1
3.7%
56.98 1
3.7%
63.9 1
3.7%
68.4 1
3.7%
72.5 1
3.7%
77.82 1
3.7%
77.98 1
3.7%
80.9 1
3.7%
ValueCountFrequency (%)
846.6 1
3.7%
533.97 1
3.7%
483.69 1
3.7%
349.0 1
3.7%
258.36 1
3.7%
185.61 1
3.7%
181.95 1
3.7%
178.73 1
3.7%
164.2368 1
3.7%
161.0 1
3.7%

도로명주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-11T01:44:07.385202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length18.037037
Min length15

Characters and Unicode

Total characters487
Distinct characters49
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

Unique27 ?
Unique (%)100.0%

Sample

1st row부산광역시 서구 구덕로346번길 4
2nd row부산광역시 서구 구덕로 135
3rd row부산광역시 서구 충무대로 72
4th row부산광역시 서구 구덕로 196
5th row부산광역시 서구 충무대로 181
ValueCountFrequency (%)
부산광역시 27
24.8%
서구 27
24.8%
구덕로 4
 
3.7%
충무대로 4
 
3.7%
충무시장길 3
 
2.8%
6 3
 
2.8%
송도해변로 2
 
1.8%
7 1
 
0.9%
50 1
 
0.9%
등대로 1
 
0.9%
Other values (36) 36
33.0%
2023-12-11T01:44:08.040869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
83
17.0%
구 36
 
7.4%
시 30
 
6.2%
부 27
 
5.5%
광 27
 
5.5%
역 27
 
5.5%
서 27
 
5.5%
산 27
 
5.5%
로 24
 
4.9%
2 20
 
4.1%
Other values (39) 159
32.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 313
64.3%
Decimal Number 87
 
17.9%
Space Separator 83
 
17.0%
Dash Punctuation 2
 
0.4%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 36
11.5%
시 30
9.6%
부 27
8.6%
광 27
8.6%
역 27
8.6%
서 27
8.6%
산 27
8.6%
로 24
 
7.7%
길 13
 
4.2%
대 10
 
3.2%
Other values (25) 65
20.8%
Decimal Number
ValueCountFrequency (%)
2 20
23.0%
1 16
18.4%
4 10
11.5%
6 9
10.3%
7 9
10.3%
5 7
 
8.0%
3 7
 
8.0%
0 4
 
4.6%
8 3
 
3.4%
9 2
 
2.3%
Space Separator
ValueCountFrequency (%)
83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 313
64.3%
Common 174
35.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 36
11.5%
시 30
9.6%
부 27
8.6%
광 27
8.6%
역 27
8.6%
서 27
8.6%
산 27
8.6%
로 24
 
7.7%
길 13
 
4.2%
대 10
 
3.2%
Other values (25) 65
20.8%
Common
ValueCountFrequency (%)
83
47.7%
2 20
 
11.5%
1 16
 
9.2%
4 10
 
5.7%
6 9
 
5.2%
7 9
 
5.2%
5 7
 
4.0%
3 7
 
4.0%
0 4
 
2.3%
8 3
 
1.7%
Other values (4) 6
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 313
64.3%
ASCII 174
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
83
47.7%
2 20
 
11.5%
1 16
 
9.2%
4 10
 
5.7%
6 9
 
5.2%
7 9
 
5.2%
5 7
 
4.0%
3 7
 
4.0%
0 4
 
2.3%
8 3
 
1.7%
Other values (4) 6
 
3.4%
Hangul
ValueCountFrequency (%)
구 36
11.5%
시 30
9.6%
부 27
8.6%
광 27
8.6%
역 27
8.6%
서 27
8.6%
산 27
8.6%
로 24
 
7.7%
길 13
 
4.2%
대 10
 
3.2%
Other values (25) 65
20.8%

지번주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-11T01:44:08.449481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length19.444444
Min length17

Characters and Unicode

Total characters525
Distinct characters37
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

Unique27 ?
Unique (%)100.0%

Sample

1st row부산광역시 서구 동대신동3가 190
2nd row부산광역시 서구 토성동5가 46-1
3rd row부산광역시 서구 암남동 201-1 외
4th row부산광역시 서구 부민동1가 32-6 외
5th row부산광역시 서구 남부민동 654
ValueCountFrequency (%)
부산광역시 27
23.3%
서구 27
23.3%
외 6
 
5.2%
암남동 5
 
4.3%
충무동1가 3
 
2.6%
부민동1가 3
 
2.6%
부용동1가 2
 
1.7%
남부민동 2
 
1.7%
서대신동2가 2
 
1.7%
토성동1가 2
 
1.7%
Other values (37) 37
31.9%
2023-12-11T01:44:09.003455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90
17.1%
부 34
 
6.5%
서 30
 
5.7%
동 29
 
5.5%
1 29
 
5.5%
산 27
 
5.1%
광 27
 
5.1%
역 27
 
5.1%
시 27
 
5.1%
구 27
 
5.1%
Other values (27) 178
33.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 312
59.4%
Decimal Number 105
 
20.0%
Space Separator 90
 
17.1%
Dash Punctuation 18
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 34
10.9%
서 30
9.6%
동 29
9.3%
산 27
8.7%
광 27
8.7%
역 27
8.7%
시 27
8.7%
구 27
8.7%
가 19
 
6.1%
남 7
 
2.2%
Other values (15) 58
18.6%
Decimal Number
ValueCountFrequency (%)
1 29
27.6%
2 16
15.2%
3 14
13.3%
6 10
 
9.5%
5 10
 
9.5%
4 7
 
6.7%
0 5
 
4.8%
8 5
 
4.8%
7 5
 
4.8%
9 4
 
3.8%
Space Separator
ValueCountFrequency (%)
90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 312
59.4%
Common 213
40.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 34
10.9%
서 30
9.6%
동 29
9.3%
산 27
8.7%
광 27
8.7%
역 27
8.7%
시 27
8.7%
구 27
8.7%
가 19
 
6.1%
남 7
 
2.2%
Other values (15) 58
18.6%
Common
ValueCountFrequency (%)
90
42.3%
1 29
 
13.6%
- 18
 
8.5%
2 16
 
7.5%
3 14
 
6.6%
6 10
 
4.7%
5 10
 
4.7%
4 7
 
3.3%
0 5
 
2.3%
8 5
 
2.3%
Other values (2) 9
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 312
59.4%
ASCII 213
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
90
42.3%
1 29
 
13.6%
- 18
 
8.5%
2 16
 
7.5%
3 14
 
6.6%
6 10
 
4.7%
5 10
 
4.7%
4 7
 
3.3%
0 5
 
2.3%
8 5
 
2.3%
Other values (2) 9
 
4.2%
Hangul
ValueCountFrequency (%)
부 34
10.9%
서 30
9.6%
동 29
9.3%
산 27
8.7%
광 27
8.7%
역 27
8.7%
시 27
8.7%
구 27
8.7%
가 19
 
6.1%
남 7
 
2.2%
Other values (15) 58
18.6%

허가일자
Date

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum1994-09-01 00:00:00
Maximum2021-01-12 00:00:00
2023-12-11T01:44:09.242912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:09.412898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

사용승인일자
Date

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum1999-08-14 00:00:00
Maximum2023-04-14 00:00:00
2023-12-11T01:44:09.576942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:09.732880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

연면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13264.34
Minimum95.28
Maximum79835.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-11T01:44:09.930580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95.28
5-th percentile1555.047
Q15609.55
median8425.3
Q312519.122
95-th percentile36334.92
Maximum79835.39
Range79740.11
Interquartile range (IQR)6909.5716

Descriptive statistics

Standard deviation16077.385
Coefficient of variation (CV)1.2120758
Kurtosis11.341148
Mean13264.34
Median Absolute Deviation (MAD)3024.31
Skewness3.1054145
Sum358137.17
Variance2.584823 × 108
MonotonicityNot monotonic
2023-12-11T01:44:10.088785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
7576.6 1
 
3.7%
5082.2 1
 
3.7%
6922.8 1
 
3.7%
5066.3678 1
 
3.7%
14144.9332 1
 
3.7%
2622.47 1
 
3.7%
5400.99 1
 
3.7%
1097.58 1
 
3.7%
9760.4719 1
 
3.7%
21841.54 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
95.28 1
3.7%
1097.58 1
3.7%
2622.47 1
3.7%
4322.25 1
3.7%
5066.3678 1
3.7%
5082.2 1
3.7%
5400.99 1
3.7%
5818.11 1
3.7%
5883.0 1
3.7%
6298.8 1
3.7%
ValueCountFrequency (%)
79835.39 1
3.7%
36747.6 1
3.7%
35372.0 1
3.7%
23220.0 1
3.7%
21841.54 1
3.7%
15710.9 1
3.7%
14144.9332 1
3.7%
10893.31 1
3.7%
10639.92 1
3.7%
9760.4719 1
3.7%

층수
Text

Distinct17
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-11T01:44:10.280408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.5925926
Min length3

Characters and Unicode

Total characters205
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)40.7%

Sample

1st row지하1/지상13
2nd row지하2/지상15
3rd row지하4/지상20
4th row지하2/지상15
5th row지하2/지상20
ValueCountFrequency (%)
지하1/지상15 5
18.5%
지하2/지상20 3
11.1%
지하1/지상17 2
 
7.4%
지하1/지상14 2
 
7.4%
지하2/지상15 2
 
7.4%
지하1/지상20 2
 
7.4%
지하4/지상22 1
 
3.7%
지하3/지상5 1
 
3.7%
지하4/지상15 1
 
3.7%
지하4/지상20 1
 
3.7%
Other values (7) 7
25.9%
2023-12-11T01:44:10.614511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 51
24.9%
1 29
14.1%
상 27
13.2%
하 24
11.7%
/ 24
11.7%
2 15
 
7.3%
5 9
 
4.4%
0 7
 
3.4%
4 6
 
2.9%
9 4
 
2.0%
Other values (3) 9
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 106
51.7%
Decimal Number 75
36.6%
Other Punctuation 24
 
11.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 29
38.7%
2 15
20.0%
5 9
 
12.0%
0 7
 
9.3%
4 6
 
8.0%
9 4
 
5.3%
7 3
 
4.0%
3 2
 
2.7%
Other Letter
ValueCountFrequency (%)
지 51
48.1%
상 27
25.5%
하 24
22.6%
층 4
 
3.8%
Other Punctuation
ValueCountFrequency (%)
/ 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 106
51.7%
Common 99
48.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 29
29.3%
/ 24
24.2%
2 15
15.2%
5 9
 
9.1%
0 7
 
7.1%
4 6
 
6.1%
9 4
 
4.0%
7 3
 
3.0%
3 2
 
2.0%
Hangul
ValueCountFrequency (%)
지 51
48.1%
상 27
25.5%
하 24
22.6%
층 4
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 106
51.7%
ASCII 99
48.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 51
48.1%
상 27
25.5%
하 24
22.6%
층 4
 
3.8%
ASCII
ValueCountFrequency (%)
1 29
29.3%
/ 24
24.2%
2 15
15.2%
5 9
 
9.1%
0 7
 
7.1%
4 6
 
6.1%
9 4
 
4.0%
7 3
 
3.0%
3 2
 
2.0%

용도
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
공동주택 업무시설
15 
공동주택업무시설
 
1
공동주택 제2종근생
 
1
공동주택 근생
 
1
공동주택 업무시설 판매시설 근생
 
1
Other values (8)
8 

Length

Max length22
Median length9
Mean length9.4074074
Min length4

Unique

Unique12 ?
Unique (%)44.4%

Sample

1st row공동주택업무시설
2nd row공동주택 제2종근생
3rd row공동주택 업무시설
4th row공동주택 근생
5th row공동주택 업무시설 판매시설 근생

Common Values

ValueCountFrequency (%)
공동주택 업무시설 15
55.6%
공동주택업무시설 1
 
3.7%
공동주택 제2종근생 1
 
3.7%
공동주택 근생 1
 
3.7%
공동주택 업무시설 판매시설 근생 1
 
3.7%
공동주택 의료시설 판매시설 운동시설 근생 1
 
3.7%
의료시설 1
 
3.7%
근린생활시설 1
 
3.7%
공동주택 근린생활시설 1
 
3.7%
숙박시설 및 근린생활시설 1
 
3.7%
Other values (3) 3
 
11.1%

Length

2023-12-11T01:44:10.759057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공동주택 22
39.3%
업무시설 16
28.6%
근생 3
 
5.4%
근린생활시설 3
 
5.4%
판매시설 2
 
3.6%
의료시설 2
 
3.6%
숙박시설 2
 
3.6%
및 2
 
3.6%
공동주택업무시설 1
 
1.8%
제2종근생 1
 
1.8%
Other values (2) 2
 
3.6%

공개공지개소
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
1
22 
2
5 

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 22
81.5%
2 5
 
18.5%

Length

2023-12-11T01:44:10.948249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:44:11.056272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 22
81.5%
2 5
 
18.5%

공개공지위치
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size348.0 B
전면
20 
전측면
5 
후면
 
1
측면
 
1

Length

Max length3
Median length2
Mean length2.1851852
Min length2

Unique

Unique2 ?
Unique (%)7.4%

Sample

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

Common Values

ValueCountFrequency (%)
전면 20
74.1%
전측면 5
 
18.5%
후면 1
 
3.7%
측면 1
 
3.7%

Length

2023-12-11T01:44:11.149851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:44:11.253728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전면 20
74.1%
전측면 5
 
18.5%
후면 1
 
3.7%
측면 1
 
3.7%

공개공지편의시설
Text

MISSING 

Distinct20
Distinct (%)76.9%
Missing1
Missing (%)3.7%
Memory size348.0 B
2023-12-11T01:44:11.403141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length10.153846
Min length5

Characters and Unicode

Total characters264
Distinct characters30
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

Unique16 ?
Unique (%)61.5%

Sample

1st row의자 1, 표지판 1
2nd row표지판 1
3rd row 표지판 1
4th row의자 5, 파고라 1
5th row표지판 1
ValueCountFrequency (%)
표지판 18
22.0%
1 18
22.0%
의자 15
18.3%
표지판1 5
 
6.1%
2 3
 
3.7%
6 3
 
3.7%
3 2
 
2.4%
4 2
 
2.4%
5 2
 
2.4%
파고라 2
 
2.4%
Other values (10) 12
14.6%
2023-12-11T01:44:11.720676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
22.3%
표 25
9.5%
판 25
9.5%
지 25
9.5%
, 25
9.5%
1 24
9.1%
의 20
 
7.6%
자 20
 
7.6%
2 8
 
3.0%
5 3
 
1.1%
Other values (20) 30
11.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134
50.8%
Space Separator 59
22.3%
Decimal Number 46
 
17.4%
Other Punctuation 25
 
9.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
표 25
18.7%
판 25
18.7%
지 25
18.7%
의 20
14.9%
자 20
14.9%
등 2
 
1.5%
파 2
 
1.5%
조 2
 
1.5%
명 2
 
1.5%
라 2
 
1.5%
Other values (8) 9
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 24
52.2%
2 8
 
17.4%
5 3
 
6.5%
6 3
 
6.5%
4 2
 
4.3%
3 2
 
4.3%
8 1
 
2.2%
9 1
 
2.2%
7 1
 
2.2%
0 1
 
2.2%
Space Separator
ValueCountFrequency (%)
59
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134
50.8%
Common 130
49.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
표 25
18.7%
판 25
18.7%
지 25
18.7%
의 20
14.9%
자 20
14.9%
등 2
 
1.5%
파 2
 
1.5%
조 2
 
1.5%
명 2
 
1.5%
라 2
 
1.5%
Other values (8) 9
 
6.7%
Common
ValueCountFrequency (%)
59
45.4%
, 25
19.2%
1 24
18.5%
2 8
 
6.2%
5 3
 
2.3%
6 3
 
2.3%
4 2
 
1.5%
3 2
 
1.5%
8 1
 
0.8%
9 1
 
0.8%
Other values (2) 2
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134
50.8%
ASCII 130
49.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
59
45.4%
, 25
19.2%
1 24
18.5%
2 8
 
6.2%
5 3
 
2.3%
6 3
 
2.3%
4 2
 
1.5%
3 2
 
1.5%
8 1
 
0.8%
9 1
 
0.8%
Other values (2) 2
 
1.5%
Hangul
ValueCountFrequency (%)
표 25
18.7%
판 25
18.7%
지 25
18.7%
의 20
14.9%
자 20
14.9%
등 2
 
1.5%
파 2
 
1.5%
조 2
 
1.5%
명 2
 
1.5%
라 2
 
1.5%
Other values (8) 9
 
6.7%

데이터기준일자
Categorical

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
2022-07-19
23 
2023-06-30
4 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-07-19
2nd row2022-07-19
3rd row2022-07-19
4th row2022-07-19
5th row2022-07-19

Common Values

ValueCountFrequency (%)
2022-07-19 23
85.2%
2023-06-30 4
 
14.8%

Length

2023-12-11T01:44:11.867706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:44:11.967929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-07-19 23
85.2%
2023-06-30 4
 
14.8%

위도
Real number (ℝ)

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.100195
Minimum35.076953
Maximum35.179928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-11T01:44:12.102414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.076953
5-th percentile35.077315
Q135.09343
median35.09949
Q335.105836
95-th percentile35.114342
Maximum35.179928
Range0.10297529
Interquartile range (IQR)0.012406025

Descriptive statistics

Standard deviation0.019520792
Coefficient of variation (CV)0.00055614483
Kurtosis10.564807
Mean35.100195
Median Absolute Deviation (MAD)0.00658265
Skewness2.5523731
Sum947.70528
Variance0.00038106132
MonotonicityNot monotonic
2023-12-11T01:44:12.281450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
35.11438606 1
 
3.7%
35.09703339 1
 
3.7%
35.10607265 1
 
3.7%
35.09707351 1
 
3.7%
35.179928 1
 
3.7%
35.10224329 1
 
3.7%
35.1056 1
 
3.7%
35.09949 1
 
3.7%
35.0777 1
 
3.7%
35.07715 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
35.07695271 1
3.7%
35.07715 1
3.7%
35.0777 1
3.7%
35.07865198 1
3.7%
35.07961642 1
3.7%
35.08668037 1
3.7%
35.09258183 1
3.7%
35.09427877 1
3.7%
35.09540627 1
3.7%
35.09552193 1
3.7%
ValueCountFrequency (%)
35.179928 1
3.7%
35.11438606 1
3.7%
35.11423781 1
3.7%
35.11041338 1
3.7%
35.10975995 1
3.7%
35.10784605 1
3.7%
35.10607265 1
3.7%
35.1056 1
3.7%
35.10455521 1
3.7%
35.10224329 1
3.7%

경도
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-11T01:44:12.527909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.592593
Min length8

Characters and Unicode

Total characters286
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

Unique27 ?
Unique (%)100.0%

Sample

1st row129.015901
2nd row129.0213338
3rd row129.0204684
4th row129.0200813
5th row129.0240448
ValueCountFrequency (%)
129.015901 1
 
3.7%
129.0153068 1
 
3.7%
129.0240543 1
 
3.7%
129.075091 1
 
3.7%
129.020291 1
 
3.7%
129.0203 1
 
3.7%
129.01866 1
 
3.7%
129.01928 1
 
3.7%
129.017787 1
 
3.7%
129.0242463 1
 
3.7%
Other values (17) 17
63.0%
2023-12-11T01:44:12.944181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 54
18.9%
1 49
17.1%
0 42
14.7%
9 35
12.2%
. 27
9.4%
3 19
 
6.6%
4 17
 
5.9%
8 15
 
5.2%
7 11
 
3.8%
5 8
 
2.8%
Other values (2) 9
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 258
90.2%
Other Punctuation 28
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 54
20.9%
1 49
19.0%
0 42
16.3%
9 35
13.6%
3 19
 
7.4%
4 17
 
6.6%
8 15
 
5.8%
7 11
 
4.3%
5 8
 
3.1%
6 8
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 27
96.4%
: 1
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Common 286
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 54
18.9%
1 49
17.1%
0 42
14.7%
9 35
12.2%
. 27
9.4%
3 19
 
6.6%
4 17
 
5.9%
8 15
 
5.2%
7 11
 
3.8%
5 8
 
2.8%
Other values (2) 9
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 286
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 54
18.9%
1 49
17.1%
0 42
14.7%
9 35
12.2%
. 27
9.4%
3 19
 
6.6%
4 17
 
5.9%
8 15
 
5.2%
7 11
 
3.8%
5 8
 
2.8%
Other values (2) 9
 
3.1%

Interactions

2023-12-11T01:44:04.927678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:04.015391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:04.437018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:05.041981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:04.142124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:04.619390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:05.229585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:04.293601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:44:04.785363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:44:13.081248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축물명공개공지면적도로명주소지번주소허가일자사용승인일자연면적층수용도공개공지개소공개공지위치공개공지편의시설데이터기준일자위도경도
건축물명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
공개공지면적1.0001.0001.0001.0001.0001.0000.7910.9290.7820.6070.8700.7820.1660.6551.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
허가일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사용승인일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
연면적1.0000.7911.0001.0001.0001.0001.0000.8910.8580.4160.5650.0000.0000.4871.000
층수1.0000.9291.0001.0001.0001.0000.8911.0000.9470.0000.9540.8180.4440.2521.000
용도1.0000.7821.0001.0001.0001.0000.8580.9471.0000.0000.6040.7330.0000.0001.000
공개공지개소1.0000.6071.0001.0001.0001.0000.4160.0000.0001.0000.8410.3580.1070.2941.000
공개공지위치1.0000.8701.0001.0001.0001.0000.5650.9540.6040.8411.0000.0000.1470.2321.000
공개공지편의시설1.0000.7821.0001.0001.0001.0000.0000.8180.7330.3580.0001.0001.0000.8531.000
데이터기준일자1.0000.1661.0001.0001.0001.0000.0000.4440.0000.1070.1471.0001.0000.3451.000
위도1.0000.6551.0001.0001.0001.0000.4870.2520.0000.2940.2320.8530.3451.0001.000
경도1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-11T01:44:13.236425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공개공지위치용도데이터기준일자공개공지개소
공개공지위치1.0000.2850.0660.609
용도0.2851.0000.0000.000
데이터기준일자0.0660.0001.0000.056
공개공지개소0.6090.0000.0561.000
2023-12-11T01:44:13.373885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공개공지면적연면적위도용도공개공지개소공개공지위치데이터기준일자
공개공지면적1.0000.698-0.1910.4090.5800.7500.129
연면적0.6981.000-0.2260.5400.4700.4760.000
위도-0.191-0.2261.0000.0000.3290.1690.388
용도0.4090.5400.0001.0000.0000.2850.000
공개공지개소0.5800.4700.3290.0001.0000.6090.056
공개공지위치0.7500.4760.1690.2850.6091.0000.066
데이터기준일자0.1290.0000.3880.0000.0560.0661.000

Missing values

2023-12-11T01:44:05.435301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:44:05.811169image/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

건축물명공개공지면적도로명주소지번주소허가일자사용승인일자연면적층수용도공개공지개소공개공지위치공개공지편의시설데이터기준일자위도경도
0동대신센츄럴타운181.95부산광역시 서구 구덕로346번길 4부산광역시 서구 동대신동3가 1902001-09-032003-02-247576.6지하1/지상13공동주택업무시설1전면의자 1, 표지판 12022-07-1935.114386129.015901
1아크로폴리스50.95부산광역시 서구 구덕로 135부산광역시 서구 토성동5가 46-11996-10-252003-04-305082.2지하2/지상15공동주택 제2종근생1전면표지판 12022-07-1935.097033129.0213338
2송도의 봄여름가을겨울104.08부산광역시 서구 충무대로 72부산광역시 서구 암남동 201-1 외1994-09-012006-04-1215710.9지하4/지상20공동주택 업무시설1전면표지판 12022-07-1935.078652129.0204684
3허브센티움107.58부산광역시 서구 구덕로 196부산광역시 서구 부민동1가 32-6 외2003-10-292008-04-186298.8지하2/지상15공동주택 근생1전면의자 5, 파고라 12022-07-1935.102137129.0200813
4LG마린타워185.61부산광역시 서구 충무대로 181부산광역시 서구 남부민동 6541997-09-191999-12-1123220.0지하2/지상20공동주택 업무시설 판매시설 근생1전면표지판 12022-07-1935.08668129.0240448
5현대타운483.69부산광역시 서구 충무대로 246부산광역시 서구 남부민동 6851996-02-101999-08-1436747.6지하4/지상22공동주택 의료시설 판매시설 운동시설 근생2후면의자, 표지판 12022-07-1935.092582129.024371
6보람아파트533.97부산광역시 서구 대영로 24부산광역시 서구 서대신동2가 2702003-10-312005-12-0935372.0지하4/지상15공동주택 업무시설2측면의자 3, 표지판 12022-07-1935.10976129.0139787
7송도요양병원349.0부산광역시 서구 암남공원로 522부산광역시 서구 암남동 759 외2011-05-252013-05-249066.3지하3/지상5의료시설1전면의자, 파고라, 표지판 12022-07-1935.079616129.0118835
8서대신 엔스타56.98부산광역시 서구 대영로6번길 6부산광역시 서구 서대신동2가 278-32011-12-292013-06-258425.3지하1/지상15공동주택 업무시설1전면의자, 표지판 12022-07-1935.110413129.0123743
9토성동봄여름가을겨울77.82부산광역시 서구 까치고개로245번길 17-20부산광역시 서구 토성동1가 3-22014-04-092015-09-255883.0지하1/지상15공동주택 업무시설1전면의자 6, 가로등 2, 표지판 12022-07-1935.100549129.0223978
건축물명공개공지면적도로명주소지번주소허가일자사용승인일자연면적층수용도공개공지개소공개공지위치공개공지편의시설데이터기준일자위도경도
17송도1913161.0부산광역시 서구 등대로 11부산광역시 서구 암남동 123-642017-07-112018-05-1795.28지상2근린생활시설1전면표지판 12022-07-1935.076953129.0242192
18경동리인타워846.6부산광역시 서구 보수대로 27부산광역시 서구 토성동1가 25-12002-12-272018-07-2779835.39지하7/지상49공동주택 근린생활시설1전면표지판 1, 의자 82022-07-1935.099271129.0242463
19베스트웨스턴플러스송도호텔178.73부산광역시 서구 송도해변로 97(암남동)부산광역시 서구 암남동 234번지2017-02-022019-09-2021841.54지하1층/지상20층숙박시설 및 근린생활시설1전측면표지판1, 의자 52022-07-1935.07715129.017787
20메리어트호텔164.2368부산광역시 서구 송도해변로 113부산광역시 서구 암남동 230번지 외 1필지2016-11-082020-04-089760.4719지상19층숙박시설1전측면표지판12022-07-1935.0777129.01928
21수현빌리지72.5부산광역시 서구 구덕로 165번길 17-2부산광역시 서구 아미동1가 25-3번지2019-06-212020-04-241097.58지상9층공동주택 및 오피스텔1전측면표지판1, 의자2, 조명22022-07-1935.09949129.01866
22남명더라우부용80.9부산광역시 서구 구덕로 234부산광역시 서구 부용동1가 69-72019-08-232021-11-105400.99지하1/지상17공동주택1전면표지판1, 의자92022-07-1935.1056129.0203
23르헤리티지24.63부산광역시 서구 대청로6번길 22부산광역시 서구 부민동1가 31-62021-01-122023-04-142622.47지하1/지상14공동주택 업무시설1전면<NA>2023-06-3035.102243:129.020291
24에코펠리스6258.36부산광역시 서구 충무시장길 34부산광역시 서구 충무동1가 29-8 외 14필지2020-07-312022-11-2914144.9332지하1/지상20공동주택 업무시설2전측면표지판2, 의자7, 야외테이블102023-06-3035.179928129.075091
25에코펠리스768.4부산광역시 서구 구덕로118번길 18부산광역시 서구 충무동1가 5-62019-11-252021-07-055066.3678지하2/지상20공동주택 업무시설2전측면표지판2, 의자52023-06-3035.097074129.0240543
26서원블루오션G동118.2부산광역시 서구 구덕로244번길 6부산광역시 서구 부용동1가 612020-08-192023-04-036922.8지하1/지상20공동주택 업무시설1전면표지판1, 의자22023-06-3035.106073129.0204815