Overview

Dataset statistics

Number of variables8
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory69.1 B

Variable types

Categorical3
Text3
Numeric2

Dataset

Description부산광역시 수영구 민방위급수시설 현황 데이터 자료로 민방위급수시설구분, 민방위급수시설, 소재지 주소 정보등을 제공하고 있다.
Author부산광역시 수영구
URLhttps://www.data.go.kr/data/15022962/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
급수능력 is highly overall correlated with 급수인원수 and 1 other fieldsHigh correlation
급수인원수 is highly overall correlated with 급수능력 and 1 other fieldsHigh correlation
민방위급수시설구분 is highly overall correlated with 급수능력 and 1 other fieldsHigh correlation
민방위급수시설 has unique valuesUnique

Reproduction

Analysis started2024-03-14 11:14:10.314469
Analysis finished2024-03-14 11:14:12.550153
Duration2.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

민방위급수시설구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size456.0 B
생활용수
27 
음용수
14 

Length

Max length4
Median length4
Mean length3.6585366
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생활용수
2nd row음용수
3rd row생활용수
4th row음용수
5th row음용수

Common Values

ValueCountFrequency (%)
생활용수 27
65.9%
음용수 14
34.1%

Length

2024-03-14T20:14:12.772120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:14:13.007118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활용수 27
65.9%
음용수 14
34.1%

민방위급수시설
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size456.0 B
2024-03-14T20:14:13.759758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.804878
Min length3

Characters and Unicode

Total characters197
Distinct characters99
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

Unique41 ?
Unique (%)100.0%

Sample

1st row망미초등학교(구)
2nd row망미초등학교(신)
3rd row수영사적공원
4th row수영구 스포츠문화타운
5th row덕문여자고등학교
ValueCountFrequency (%)
망미초등학교(구 1
 
2.4%
산수탕 1
 
2.4%
그린탕 1
 
2.4%
동산원 1
 
2.4%
해수탕 1
 
2.4%
미주탕 1
 
2.4%
망미탕 1
 
2.4%
한신아파트 1
 
2.4%
금은사우나 1
 
2.4%
하나님의교회 1
 
2.4%
Other values (32) 32
76.2%
2024-03-14T20:14:15.086362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 14
 
7.1%
원 9
 
4.6%
수 8
 
4.1%
성 7
 
3.6%
교 6
 
3.0%
아 6
 
3.0%
학 5
 
2.5%
미 5
 
2.5%
옥 4
 
2.0%
청 4
 
2.0%
Other values (89) 129
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 192
97.5%
Close Punctuation 2
 
1.0%
Open Punctuation 2
 
1.0%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 14
 
7.3%
원 9
 
4.7%
수 8
 
4.2%
성 7
 
3.6%
교 6
 
3.1%
아 6
 
3.1%
학 5
 
2.6%
미 5
 
2.6%
옥 4
 
2.1%
청 4
 
2.1%
Other values (86) 124
64.6%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 192
97.5%
Common 5
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 14
 
7.3%
원 9
 
4.7%
수 8
 
4.2%
성 7
 
3.6%
교 6
 
3.1%
아 6
 
3.1%
학 5
 
2.6%
미 5
 
2.6%
옥 4
 
2.1%
청 4
 
2.1%
Other values (86) 124
64.6%
Common
ValueCountFrequency (%)
) 2
40.0%
( 2
40.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 192
97.5%
ASCII 5
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 14
 
7.3%
원 9
 
4.7%
수 8
 
4.2%
성 7
 
3.6%
교 6
 
3.1%
아 6
 
3.1%
학 5
 
2.6%
미 5
 
2.6%
옥 4
 
2.1%
청 4
 
2.1%
Other values (86) 124
64.6%
ASCII
ValueCountFrequency (%)
) 2
40.0%
( 2
40.0%
1
20.0%

소재지도로명주소
Text

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size456.0 B
2024-03-14T20:14:16.027613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length19.926829
Min length16

Characters and Unicode

Total characters817
Distinct characters43
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

Unique37 ?
Unique (%)90.2%

Sample

1st row부산광역시 수영구 수미로35번길 27
2nd row부산광역시 수영구 수미로35번길 27
3rd row부산광역시 수영구 연수로379번길 42
4th row부산광역시 수영로 521번길 77
5th row부산광역시 수영구 연수로310번길 114
ValueCountFrequency (%)
부산광역시 41
25.2%
수영구 39
23.9%
수영로 5
 
3.1%
42 2
 
1.2%
15 2
 
1.2%
35 2
 
1.2%
망미번영로55번길 2
 
1.2%
17 2
 
1.2%
광일로 2
 
1.2%
연수로260번길 2
 
1.2%
Other values (59) 64
39.3%
2024-03-14T20:14:17.399999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
14.9%
수 58
 
7.1%
광 50
 
6.1%
영 50
 
6.1%
산 43
 
5.3%
부 41
 
5.0%
역 41
 
5.0%
시 41
 
5.0%
로 41
 
5.0%
구 40
 
4.9%
Other values (33) 290
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 525
64.3%
Decimal Number 168
 
20.6%
Space Separator 122
 
14.9%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 58
11.0%
광 50
9.5%
영 50
9.5%
산 43
8.2%
부 41
7.8%
역 41
7.8%
시 41
7.8%
로 41
7.8%
구 40
7.6%
번 36
6.9%
Other values (21) 84
16.0%
Decimal Number
ValueCountFrequency (%)
5 29
17.3%
2 25
14.9%
1 24
14.3%
3 23
13.7%
7 16
9.5%
4 16
9.5%
0 11
 
6.5%
6 9
 
5.4%
9 8
 
4.8%
8 7
 
4.2%
Space Separator
ValueCountFrequency (%)
122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 525
64.3%
Common 292
35.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 58
11.0%
광 50
9.5%
영 50
9.5%
산 43
8.2%
부 41
7.8%
역 41
7.8%
시 41
7.8%
로 41
7.8%
구 40
7.6%
번 36
6.9%
Other values (21) 84
16.0%
Common
ValueCountFrequency (%)
122
41.8%
5 29
 
9.9%
2 25
 
8.6%
1 24
 
8.2%
3 23
 
7.9%
7 16
 
5.5%
4 16
 
5.5%
0 11
 
3.8%
6 9
 
3.1%
9 8
 
2.7%
Other values (2) 9
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 525
64.3%
ASCII 292
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
41.8%
5 29
 
9.9%
2 25
 
8.6%
1 24
 
8.2%
3 23
 
7.9%
7 16
 
5.5%
4 16
 
5.5%
0 11
 
3.8%
6 9
 
3.1%
9 8
 
2.7%
Other values (2) 9
 
3.1%
Hangul
ValueCountFrequency (%)
수 58
11.0%
광 50
9.5%
영 50
9.5%
산 43
8.2%
부 41
7.8%
역 41
7.8%
시 41
7.8%
로 41
7.8%
구 40
7.6%
번 36
6.9%
Other values (21) 84
16.0%

소재지지번주소
Text

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size456.0 B
2024-03-14T20:14:18.160749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.9268293
Min length7

Characters and Unicode

Total characters366
Distinct characters24
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

Unique37 ?
Unique (%)90.2%

Sample

1st row망미동 268-2
2nd row망미동 268-2
3rd row수영동 372
4th row광안4동 산105
5th row광안동 8-8
ValueCountFrequency (%)
광안동 17
20.7%
망미동 13
 
15.9%
남천동 4
 
4.9%
수영동 3
 
3.7%
민락동 3
 
3.7%
777 2
 
2.4%
268-2 2
 
2.4%
498-3 1
 
1.2%
14-22 1
 
1.2%
1062-34 1
 
1.2%
Other values (35) 35
42.7%
2024-03-14T20:14:19.366268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 41
 
11.2%
41
 
11.2%
- 32
 
8.7%
1 30
 
8.2%
2 25
 
6.8%
7 21
 
5.7%
안 18
 
4.9%
광 18
 
4.9%
4 17
 
4.6%
5 16
 
4.4%
Other values (14) 107
29.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 169
46.2%
Other Letter 124
33.9%
Space Separator 41
 
11.2%
Dash Punctuation 32
 
8.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 41
33.1%
안 18
14.5%
광 18
14.5%
미 13
 
10.5%
망 13
 
10.5%
남 4
 
3.2%
천 4
 
3.2%
영 3
 
2.4%
수 3
 
2.4%
민 3
 
2.4%
Other values (2) 4
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 30
17.8%
2 25
14.8%
7 21
12.4%
4 17
10.1%
5 16
9.5%
8 15
8.9%
3 12
 
7.1%
9 12
 
7.1%
6 11
 
6.5%
0 10
 
5.9%
Space Separator
ValueCountFrequency (%)
41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 242
66.1%
Hangul 124
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 41
33.1%
안 18
14.5%
광 18
14.5%
미 13
 
10.5%
망 13
 
10.5%
남 4
 
3.2%
천 4
 
3.2%
영 3
 
2.4%
수 3
 
2.4%
민 3
 
2.4%
Other values (2) 4
 
3.2%
Common
ValueCountFrequency (%)
41
16.9%
- 32
13.2%
1 30
12.4%
2 25
10.3%
7 21
8.7%
4 17
7.0%
5 16
 
6.6%
8 15
 
6.2%
3 12
 
5.0%
9 12
 
5.0%
Other values (2) 21
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242
66.1%
Hangul 124
33.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 41
33.1%
안 18
14.5%
광 18
14.5%
미 13
 
10.5%
망 13
 
10.5%
남 4
 
3.2%
천 4
 
3.2%
영 3
 
2.4%
수 3
 
2.4%
민 3
 
2.4%
Other values (2) 4
 
3.2%
ASCII
ValueCountFrequency (%)
41
16.9%
- 32
13.2%
1 30
12.4%
2 25
10.3%
7 21
8.7%
4 17
7.0%
5 16
 
6.6%
8 15
 
6.2%
3 12
 
5.0%
9 12
 
5.0%
Other values (2) 21
8.7%

급수능력
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.02439
Minimum30
Maximum158
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size497.0 B
2024-03-14T20:14:19.742043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile34
Q160
median80
Q394
95-th percentile110
Maximum158
Range128
Interquartile range (IQR)34

Descriptive statistics

Standard deviation28.771069
Coefficient of variation (CV)0.37353192
Kurtosis0.97568669
Mean77.02439
Median Absolute Deviation (MAD)20
Skewness0.51772105
Sum3158
Variance827.77439
MonotonicityNot monotonic
2024-03-14T20:14:20.150207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
80 7
17.1%
100 4
 
9.8%
90 3
 
7.3%
70 3
 
7.3%
60 3
 
7.3%
35 2
 
4.9%
40 2
 
4.9%
95 2
 
4.9%
30 2
 
4.9%
75 1
 
2.4%
Other values (12) 12
29.3%
ValueCountFrequency (%)
30 2
4.9%
34 1
 
2.4%
35 2
4.9%
40 2
4.9%
50 1
 
2.4%
55 1
 
2.4%
57 1
 
2.4%
60 3
7.3%
69 1
 
2.4%
70 3
7.3%
ValueCountFrequency (%)
158 1
 
2.4%
150 1
 
2.4%
110 1
 
2.4%
108 1
 
2.4%
100 4
9.8%
95 2
4.9%
94 1
 
2.4%
93 1
 
2.4%
90 3
7.3%
85 1
 
2.4%

급수인원수
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3080.9756
Minimum1200
Maximum6320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size497.0 B
2024-03-14T20:14:20.524873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1200
5-th percentile1360
Q12400
median3200
Q33760
95-th percentile4400
Maximum6320
Range5120
Interquartile range (IQR)1360

Descriptive statistics

Standard deviation1150.8427
Coefficient of variation (CV)0.37353192
Kurtosis0.97568669
Mean3080.9756
Median Absolute Deviation (MAD)800
Skewness0.51772105
Sum126320
Variance1324439
MonotonicityNot monotonic
2024-03-14T20:14:20.920030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3200 7
17.1%
4000 4
 
9.8%
3600 3
 
7.3%
2800 3
 
7.3%
2400 3
 
7.3%
1400 2
 
4.9%
1600 2
 
4.9%
3800 2
 
4.9%
1200 2
 
4.9%
3000 1
 
2.4%
Other values (12) 12
29.3%
ValueCountFrequency (%)
1200 2
4.9%
1360 1
 
2.4%
1400 2
4.9%
1600 2
4.9%
2000 1
 
2.4%
2200 1
 
2.4%
2280 1
 
2.4%
2400 3
7.3%
2760 1
 
2.4%
2800 3
7.3%
ValueCountFrequency (%)
6320 1
 
2.4%
6000 1
 
2.4%
4400 1
 
2.4%
4320 1
 
2.4%
4000 4
9.8%
3800 2
4.9%
3760 1
 
2.4%
3720 1
 
2.4%
3600 3
7.3%
3400 1
 
2.4%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size456.0 B
수영구청
41 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수영구청 41
100.0%

Length

2024-03-14T20:14:21.313700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:14:21.622095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수영구청 41
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size456.0 B
2024-01-15
41 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-15
2nd row2024-01-15
3rd row2024-01-15
4th row2024-01-15
5th row2024-01-15

Common Values

ValueCountFrequency (%)
2024-01-15 41
100.0%

Length

2024-03-14T20:14:21.941670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:14:22.254473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-15 41
100.0%

Interactions

2024-03-14T20:14:11.381581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:14:10.690999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:14:11.630781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:14:11.137716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:14:22.445659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
민방위급수시설구분민방위급수시설소재지도로명주소소재지지번주소급수능력급수인원수
민방위급수시설구분1.0001.0000.5990.5990.5980.694
민방위급수시설1.0001.0001.0001.0001.0001.000
소재지도로명주소0.5991.0001.0001.0000.8420.859
소재지지번주소0.5991.0001.0001.0000.8420.859
급수능력0.5981.0000.8420.8421.0001.000
급수인원수0.6941.0000.8590.8591.0001.000
2024-03-14T20:14:22.722809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급수능력급수인원수민방위급수시설구분
급수능력1.0001.0000.500
급수인원수1.0001.0000.500
민방위급수시설구분0.5000.5001.000

Missing values

2024-03-14T20:14:11.968009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:14:12.384503image/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

민방위급수시설구분민방위급수시설소재지도로명주소소재지지번주소급수능력급수인원수관리기관명데이터기준일자
0생활용수망미초등학교(구)부산광역시 수영구 수미로35번길 27망미동 268-2572280수영구청2024-01-15
1음용수망미초등학교(신)부산광역시 수영구 수미로35번길 27망미동 268-21586320수영구청2024-01-15
2생활용수수영사적공원부산광역시 수영구 연수로379번길 42수영동 3721104400수영구청2024-01-15
3음용수수영구 스포츠문화타운부산광역시 수영로 521번길 77광안4동 산1051084320수영구청2024-01-15
4음용수덕문여자고등학교부산광역시 수영구 연수로310번길 114광안동 8-8903600수영구청2024-01-15
5음용수삼성아파트부산광역시 수영구 망미로30번길 23망미동 777702800수영구청2024-01-15
6음용수고려제강부산광역시 수영구 구락로141번길 37망미동 495933720수영구청2024-01-15
7음용수현대한누리타운부산광역시 수영구 금련로43번길 26망미동 979-72552200수영구청2024-01-15
8음용수수영한서병원부산광역시 수영구 수영로 615광안동 491-101506000수영구청2024-01-15
9음용수광원아파트부산광역시 수영구 광일로 59광안동 526-1943760수영구청2024-01-15
민방위급수시설구분민방위급수시설소재지도로명주소소재지지번주소급수능력급수인원수관리기관명데이터기준일자
31생활용수성화탕부산광역시 수영구 연수로392번길 25광안동 1062-34803200수영구청2024-01-15
32생활용수청송세차장부산광역시 수영구 망미번영로38번길 79광안동 1060-11602400수영구청2024-01-15
33생활용수청옥탕부산광역시 수영구 광서로16번길 51광안동 1074-6953800수영구청2024-01-15
34생활용수남천성당부산광역시 수영로 427번길 15남천동 69-1803200수영구청2024-01-15
35생활용수동아중학교부산광역시 수영구 호암로 55광안동 1222-23401600수영구청2024-01-15
36생활용수부산배화학교부산광역시 수영구 연수로310번길73망미동 787702800수영구청2024-01-15
37생활용수옥천탕부산광역시 수영구 민락본동로27번길 22민락동 15-11903600수영구청2024-01-15
38생활용수보우빌딩부산광역시 수영구 남천동로 15남천동 14-22351400수영구청2024-01-15
39생활용수양지탕부산광역시 수영구 수영로652번길 23-1광안동 96-36301200수영구청2024-01-15
40생활용수장수탕부산광역시 수영구 수영로618번길 38광안동 120-257401600수영구청2024-01-15