Overview

Dataset statistics

Number of variables11
Number of observations45
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory94.9 B

Variable types

Numeric4
Text3
Categorical4

Dataset

Description전쟁 및 상수도 체계의 파괴 등과 같은 민방위사태 발생으로 상수도 공급 중단 시 최소의 음용 및 생활용수를 주민에게 공급하기 위한 부산광역시 연제구 민방위 비상급수시설 현황입니다.
Author부산광역시 연제구
URLhttps://www.data.go.kr/data/15028596/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
수질구분 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
2024년1분기 is highly overall correlated with 수질구분High correlation
연번 is highly overall correlated with 시설구분High correlation
경도 is highly overall correlated with 수질구분High correlation
시설구분 is highly overall correlated with 연번High correlation
도로명주소 has 1 (2.2%) missing valuesMissing
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:03:21.617103
Analysis finished2024-04-06 08:03:26.051682
Duration4.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-04-06T17:03:26.294497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.2
Q112
median23
Q334
95-th percentile42.8
Maximum45
Range44
Interquartile range (IQR)22

Descriptive statistics

Standard deviation13.133926
Coefficient of variation (CV)0.57104024
Kurtosis-1.2
Mean23
Median Absolute Deviation (MAD)11
Skewness0
Sum1035
Variance172.5
MonotonicityStrictly increasing
2024-04-06T17:03:26.573441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 1
 
2.2%
35 1
 
2.2%
26 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%
36 1
2.2%

시설명
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2024-04-06T17:03:26.991507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length7.2666667
Min length3

Characters and Unicode

Total characters327
Distinct characters110
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row부산교육대학교
2nd row창신초등학교
3rd row거제초등학교
4th row쌍미공원
5th row연제초등학교(A)
ValueCountFrequency (%)
부산교육대학교 1
 
2.2%
망미주공아파트 1
 
2.2%
연산선경아파트 1
 
2.2%
부전타워아파트 1
 
2.2%
부산의료원 1
 
2.2%
국가기록원역사기록관 1
 
2.2%
아시아드주경기장 1
 
2.2%
연산중학교 1
 
2.2%
연제초등학교(b 1
 
2.2%
동명초등학교 1
 
2.2%
Other values (35) 35
77.8%
2024-04-06T17:03:28.199529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 17
 
5.2%
파 16
 
4.9%
트 15
 
4.6%
산 13
 
4.0%
) 12
 
3.7%
( 12
 
3.7%
교 11
 
3.4%
학 11
 
3.4%
연 11
 
3.4%
제 8
 
2.4%
Other values (100) 201
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 289
88.4%
Close Punctuation 12
 
3.7%
Open Punctuation 12
 
3.7%
Uppercase Letter 11
 
3.4%
Other Punctuation 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 17
 
5.9%
파 16
 
5.5%
트 15
 
5.2%
산 13
 
4.5%
교 11
 
3.8%
학 11
 
3.8%
연 11
 
3.8%
제 8
 
2.8%
부 7
 
2.4%
등 6
 
2.1%
Other values (95) 174
60.2%
Uppercase Letter
ValueCountFrequency (%)
B 6
54.5%
A 5
45.5%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 289
88.4%
Common 27
 
8.3%
Latin 11
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 17
 
5.9%
파 16
 
5.5%
트 15
 
5.2%
산 13
 
4.5%
교 11
 
3.8%
학 11
 
3.8%
연 11
 
3.8%
제 8
 
2.8%
부 7
 
2.4%
등 6
 
2.1%
Other values (95) 174
60.2%
Common
ValueCountFrequency (%)
) 12
44.4%
( 12
44.4%
. 3
 
11.1%
Latin
ValueCountFrequency (%)
B 6
54.5%
A 5
45.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 289
88.4%
ASCII 38
 
11.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 17
 
5.9%
파 16
 
5.5%
트 15
 
5.2%
산 13
 
4.5%
교 11
 
3.8%
학 11
 
3.8%
연 11
 
3.8%
제 8
 
2.8%
부 7
 
2.4%
등 6
 
2.1%
Other values (95) 174
60.2%
ASCII
ValueCountFrequency (%)
) 12
31.6%
( 12
31.6%
B 6
15.8%
A 5
13.2%
. 3
 
7.9%

도로명주소
Text

MISSING 

Distinct39
Distinct (%)88.6%
Missing1
Missing (%)2.2%
Memory size492.0 B
2024-04-06T17:03:28.581295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length22.977273
Min length19

Characters and Unicode

Total characters1011
Distinct characters97
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)77.3%

Sample

1st row부산광역시연제구교대로19,(거제동)
2nd row부산광역시연제구종합운동장로12번길15,(거제동)
3rd row부산광역시연제구해맞이로39,(거제동)
4th row부산광역시연제구쌍미천로172,(연산동)
5th row부산광역시연제구중앙대로1065번길14,(연산동)
ValueCountFrequency (%)
부산광역시연제구고분로170,(연산동 2
 
4.5%
부산광역시연제구월드컵대로399,(거제동 2
 
4.5%
부산광역시연제구황령산로495,(연산동 2
 
4.5%
부산광역시연제구고분로200,(연산동,연산엘지 2
 
4.5%
부산광역시연제구중앙대로1065번길14,(연산동 2
 
4.5%
부산광역시연제구토곡로20,(연산동 1
 
2.3%
부산광역시연제구교대로19,(거제동 1
 
2.3%
부산광역시연제구월드컵대로359,(거제동 1
 
2.3%
부산광역시연제구경기장로28,(거제동 1
 
2.3%
부산광역시연제구월드컵대로344,(거제동 1
 
2.3%
Other values (29) 29
65.9%
2024-04-06T17:03:29.250735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
연 84
 
8.3%
산 82
 
8.1%
제 63
 
6.2%
, 61
 
6.0%
시 46
 
4.5%
구 46
 
4.5%
부 45
 
4.5%
동 45
 
4.5%
로 44
 
4.4%
) 44
 
4.4%
Other values (87) 451
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 736
72.8%
Decimal Number 126
 
12.5%
Other Punctuation 61
 
6.0%
Close Punctuation 44
 
4.4%
Open Punctuation 44
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 84
11.4%
산 82
11.1%
제 63
 
8.6%
시 46
 
6.2%
구 46
 
6.2%
부 45
 
6.1%
동 45
 
6.1%
로 44
 
6.0%
광 44
 
6.0%
역 44
 
6.0%
Other values (74) 193
26.2%
Decimal Number
ValueCountFrequency (%)
1 26
20.6%
2 17
13.5%
4 15
11.9%
3 14
11.1%
9 13
10.3%
0 11
8.7%
5 9
 
7.1%
6 8
 
6.3%
7 7
 
5.6%
8 6
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 736
72.8%
Common 275
 
27.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 84
11.4%
산 82
11.1%
제 63
 
8.6%
시 46
 
6.2%
구 46
 
6.2%
부 45
 
6.1%
동 45
 
6.1%
로 44
 
6.0%
광 44
 
6.0%
역 44
 
6.0%
Other values (74) 193
26.2%
Common
ValueCountFrequency (%)
, 61
22.2%
) 44
16.0%
( 44
16.0%
1 26
9.5%
2 17
 
6.2%
4 15
 
5.5%
3 14
 
5.1%
9 13
 
4.7%
0 11
 
4.0%
5 9
 
3.3%
Other values (3) 21
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 736
72.8%
ASCII 275
 
27.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
연 84
11.4%
산 82
11.1%
제 63
 
8.6%
시 46
 
6.2%
구 46
 
6.2%
부 45
 
6.1%
동 45
 
6.1%
로 44
 
6.0%
광 44
 
6.0%
역 44
 
6.0%
Other values (74) 193
26.2%
ASCII
ValueCountFrequency (%)
, 61
22.2%
) 44
16.0%
( 44
16.0%
1 26
9.5%
2 17
 
6.2%
4 15
 
5.5%
3 14
 
5.1%
9 13
 
4.7%
0 11
 
4.0%
5 9
 
3.3%
Other values (3) 21
 
7.6%

지번주소
Text

Distinct40
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
2024-04-06T17:03:29.698593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length19.644444
Min length16

Characters and Unicode

Total characters884
Distinct characters64
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

Unique35 ?
Unique (%)77.8%

Sample

1st row부산광역시연제구거제동263번지
2nd row부산광역시연제구거제동897-3번지
3rd row부산광역시연제구거제동676-152번지
4th row부산광역시연제구연산동2275번지
5th row부산광역시연제구연산동1300번지
ValueCountFrequency (%)
부산광역시연제구연산동277-4번지 2
 
4.4%
부산광역시연제구거제동1368번지 2
 
4.4%
부산광역시연제구연산동산182번지 2
 
4.4%
부산광역시연제구연산동243-18번지연산엘지 2
 
4.4%
부산광역시연제구연산동1300번지 2
 
4.4%
부산광역시연제구연산동1784-19번지 1
 
2.2%
부산광역시연제구연산동1777-10번지 1
 
2.2%
부산광역시연제구거제동263번지 1
 
2.2%
부산광역시연제구거제동1518번지 1
 
2.2%
부산광역시연제구거제동1400번지 1
 
2.2%
Other values (30) 30
66.7%
2024-04-06T17:03:30.573821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 83
 
9.4%
연 82
 
9.3%
제 60
 
6.8%
지 47
 
5.3%
구 47
 
5.3%
부 46
 
5.2%
광 45
 
5.1%
역 45
 
5.1%
시 45
 
5.1%
동 45
 
5.1%
Other values (54) 339
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 657
74.3%
Decimal Number 198
 
22.4%
Dash Punctuation 29
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 83
12.6%
연 82
12.5%
제 60
9.1%
지 47
7.2%
구 47
7.2%
부 46
7.0%
광 45
6.8%
역 45
6.8%
시 45
6.8%
동 45
6.8%
Other values (43) 112
17.0%
Decimal Number
ValueCountFrequency (%)
1 39
19.7%
2 23
11.6%
7 22
11.1%
3 21
10.6%
8 21
10.6%
4 17
8.6%
5 16
8.1%
0 14
 
7.1%
6 13
 
6.6%
9 12
 
6.1%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 657
74.3%
Common 227
 
25.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 83
12.6%
연 82
12.5%
제 60
9.1%
지 47
7.2%
구 47
7.2%
부 46
7.0%
광 45
6.8%
역 45
6.8%
시 45
6.8%
동 45
6.8%
Other values (43) 112
17.0%
Common
ValueCountFrequency (%)
1 39
17.2%
- 29
12.8%
2 23
10.1%
7 22
9.7%
3 21
9.3%
8 21
9.3%
4 17
7.5%
5 16
7.0%
0 14
 
6.2%
6 13
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 657
74.3%
ASCII 227
 
25.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 83
12.6%
연 82
12.5%
제 60
9.1%
지 47
7.2%
구 47
7.2%
부 46
7.0%
광 45
6.8%
역 45
6.8%
시 45
6.8%
동 45
6.8%
Other values (43) 112
17.0%
ASCII
ValueCountFrequency (%)
1 39
17.2%
- 29
12.8%
2 23
10.1%
7 22
9.7%
3 21
9.3%
8 21
9.3%
4 17
7.5%
5 16
7.0%
0 14
 
6.2%
6 13
 
5.7%

위도
Real number (ℝ)

Distinct40
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.181602
Minimum35.163827
Maximum35.195736
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-04-06T17:03:30.870416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.163827
5-th percentile35.166456
Q135.178172
median35.18328
Q335.185429
95-th percentile35.19048
Maximum35.195736
Range0.03190976
Interquartile range (IQR)0.00725669

Descriptive statistics

Standard deviation0.0066996555
Coefficient of variation (CV)0.00019043065
Kurtosis1.2550876
Mean35.181602
Median Absolute Deviation (MAD)0.00399634
Skewness-0.82436973
Sum1583.1721
Variance4.4885384 × 10-5
MonotonicityNot monotonic
2024-04-06T17:03:31.176720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
35.18408872 2
 
4.4%
35.18405049 2
 
4.4%
35.18601041 2
 
4.4%
35.18542909 2
 
4.4%
35.16484907 2
 
4.4%
35.19573642 1
 
2.2%
35.18294459 1
 
2.2%
35.19065725 1
 
2.2%
35.18977125 1
 
2.2%
35.18486107 1
 
2.2%
Other values (30) 30
66.7%
ValueCountFrequency (%)
35.16382666 1
2.2%
35.16484907 2
4.4%
35.17288586 1
2.2%
35.17353965 1
2.2%
35.17492326 1
2.2%
35.17559743 1
2.2%
35.17653091 1
2.2%
35.17740455 1
2.2%
35.17763371 1
2.2%
35.17781 1
2.2%
ValueCountFrequency (%)
35.19573642 1
2.2%
35.19281042 1
2.2%
35.19065725 1
2.2%
35.18977125 1
2.2%
35.18787616 1
2.2%
35.18780185 1
2.2%
35.18743495 1
2.2%
35.18601041 2
4.4%
35.18574224 1
2.2%
35.18542909 2
4.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.08506
Minimum129.05319
Maximum129.11106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-04-06T17:03:31.436390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.05319
5-th percentile129.05617
Q1129.07541
median129.08753
Q3129.09637
95-th percentile129.10624
Maximum129.11106
Range0.0578748
Interquartile range (IQR)0.0209612

Descriptive statistics

Standard deviation0.016145302
Coefficient of variation (CV)0.0001250749
Kurtosis-0.80538246
Mean129.08506
Median Absolute Deviation (MAD)0.0121169
Skewness-0.3607627
Sum5808.8279
Variance0.00026067077
MonotonicityNot monotonic
2024-04-06T17:03:31.752219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
129.1046149 2
 
4.4%
129.0778797 2
 
4.4%
129.0559793 2
 
4.4%
129.1009549 2
 
4.4%
129.0830279 2
 
4.4%
129.0754098 1
 
2.2%
129.1055326 1
 
2.2%
129.0531858 1
 
2.2%
129.0569384 1
 
2.2%
129.0890236 1
 
2.2%
Other values (30) 30
66.7%
ValueCountFrequency (%)
129.0531858 1
2.2%
129.0559793 2
4.4%
129.0569384 1
2.2%
129.0596003 1
2.2%
129.0613936 1
2.2%
129.0658511 1
2.2%
129.0659249 1
2.2%
129.0670089 1
2.2%
129.07088 1
2.2%
129.0728152 1
2.2%
ValueCountFrequency (%)
129.1110606 1
2.2%
129.1090913 1
2.2%
129.1063492 1
2.2%
129.1058124 1
2.2%
129.1055326 1
2.2%
129.1046149 2
4.4%
129.10336 1
2.2%
129.1012117 1
2.2%
129.1009549 2
4.4%
129.096371 1
2.2%

톤수
Real number (ℝ)

Distinct24
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104.24444
Minimum30
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2024-04-06T17:03:31.991708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile42
Q165
median90
Q3130
95-th percentile214.4
Maximum350
Range320
Interquartile range (IQR)65

Descriptive statistics

Standard deviation60.024675
Coefficient of variation (CV)0.57580694
Kurtosis5.7927832
Mean104.24444
Median Absolute Deviation (MAD)30
Skewness2.0524336
Sum4691
Variance3602.9616
MonotonicityNot monotonic
2024-04-06T17:03:32.262257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
100 6
13.3%
80 6
13.3%
150 4
 
8.9%
130 3
 
6.7%
60 3
 
6.7%
50 3
 
6.7%
90 3
 
6.7%
96 1
 
2.2%
40 1
 
2.2%
220 1
 
2.2%
Other values (14) 14
31.1%
ValueCountFrequency (%)
30 1
 
2.2%
36 1
 
2.2%
40 1
 
2.2%
50 3
6.7%
55 1
 
2.2%
60 3
6.7%
63 1
 
2.2%
65 1
 
2.2%
70 1
 
2.2%
77 1
 
2.2%
ValueCountFrequency (%)
350 1
 
2.2%
250 1
 
2.2%
220 1
 
2.2%
192 1
 
2.2%
160 1
 
2.2%
150 4
8.9%
136 1
 
2.2%
130 3
6.7%
100 6
13.3%
96 1
 
2.2%

수질구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
음용수
30 
생활용수
15 

Length

Max length4
Median length3
Mean length3.3333333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
음용수 30
66.7%
생활용수 15
33.3%

Length

2024-04-06T17:03:32.546234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:03:32.955905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음용수 30
66.7%
생활용수 15
33.3%

시설구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size492.0 B
공공용
35 
정부지원
6 
자치단체시설
4 

Length

Max length6
Median length3
Mean length3.4
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공용 35
77.8%
정부지원 6
 
13.3%
자치단체시설 4
 
8.9%

Length

2024-04-06T17:03:33.186869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:03:33.420402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 35
77.8%
정부지원 6
 
13.3%
자치단체시설 4
 
8.9%

2024년1분기
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size492.0 B
적합
27 
적합(3년주기)
15 
부적합
3 

Length

Max length8
Median length2
Mean length4.0666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row적합
2nd row적합(3년주기)
3rd row적합(3년주기)
4th row적합
5th row적합(3년주기)

Common Values

ValueCountFrequency (%)
적합 27
60.0%
적합(3년주기) 15
33.3%
부적합 3
 
6.7%

Length

2024-04-06T17:03:33.643914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:03:33.868521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 27
60.0%
적합(3년주기 15
33.3%
부적합 3
 
6.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
2024-03-29
45 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-29
2nd row2024-03-29
3rd row2024-03-29
4th row2024-03-29
5th row2024-03-29

Common Values

ValueCountFrequency (%)
2024-03-29 45
100.0%

Length

2024-04-06T17:03:34.083077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:03:34.297721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-29 45
100.0%

Interactions

2024-04-06T17:03:24.834332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:22.519928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:23.236691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:23.984291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:25.026278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:22.662148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:23.405623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:24.199474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:25.206686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:22.835083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:23.608534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:24.377947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:25.399316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:23.009874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:23.797985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:03:24.572427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:03:34.447635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설명도로명주소지번주소위도경도톤수수질구분시설구분2024년1분기
연번1.0001.0000.9290.9510.4820.6770.3090.0000.8790.000
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소0.9291.0001.0001.0001.0001.0000.6130.8830.4930.775
지번주소0.9511.0001.0001.0001.0001.0000.6370.9140.5580.731
위도0.4821.0001.0001.0001.0000.6800.0000.1660.4210.677
경도0.6771.0001.0001.0000.6801.0000.3780.8630.2780.644
톤수0.3091.0000.6130.6370.0000.3781.0000.4130.5600.240
수질구분0.0001.0000.8830.9140.1660.8630.4131.0000.0001.000
시설구분0.8791.0000.4930.5580.4210.2780.5600.0001.0000.000
2024년1분기0.0001.0000.7750.7310.6770.6440.2401.0000.0001.000
2024-04-06T17:03:34.720736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분수질구분2024년1분기
시설구분1.0000.0000.000
수질구분0.0001.0000.988
2024년1분기0.0000.9881.000
2024-04-06T17:03:34.920295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도톤수수질구분시설구분2024년1분기
연번1.000-0.1300.329-0.0590.0000.7440.000
위도-0.1301.000-0.2610.3340.1380.1790.354
경도0.329-0.2611.000-0.1000.6320.1240.453
톤수-0.0590.334-0.1001.0000.2820.3960.134
수질구분0.0000.1380.6320.2821.0000.0000.988
시설구분0.7440.1790.1240.3960.0001.0000.000
2024년1분기0.0000.3540.4530.1340.9880.0001.000

Missing values

2024-04-06T17:03:25.631167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:03:25.934306image/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

연번시설명도로명주소지번주소위도경도톤수수질구분시설구분2024년1분기데이터기준일자
01부산교육대학교부산광역시연제구교대로19,(거제동)부산광역시연제구거제동263번지35.195736129.07541100음용수정부지원적합2024-03-29
12창신초등학교부산광역시연제구종합운동장로12번길15,(거제동)부산광역시연제구거제동897-3번지35.19281129.065851192생활용수정부지원적합(3년주기)2024-03-29
23거제초등학교부산광역시연제구해맞이로39,(거제동)부산광역시연제구거제동676-152번지35.17821129.06700996생활용수정부지원적합(3년주기)2024-03-29
34쌍미공원부산광역시연제구쌍미천로172,(연산동)부산광역시연제구연산동2275번지35.187876129.087527136음용수정부지원적합2024-03-29
45연제초등학교(A)부산광역시연제구중앙대로1065번길14,(연산동)부산광역시연제구연산동1300번지35.18405129.07788130생활용수정부지원적합(3년주기)2024-03-29
56새싹어린이공원<NA>부산광역시연제구연산동2132-1번지35.175597129.092731130음용수정부지원적합2024-03-29
67개인택시조합(A)부산광역시연제구월드컵대로399,(거제동)부산광역시연제구거제동1368번지35.18601129.05597960음용수자치단체시설적합2024-03-29
78거제시장부산광역시연제구거제시장로14번길28,(거제동)부산광역시연제구거제동486-1번지35.181765129.072815250생활용수자치단체시설적합(3년주기)2024-03-29
89연산초등학교부산광역시연제구월드컵대로41,(연산동)부산광역시연제구연산동774-1번지35.178172129.084049130음용수자치단체시설적합2024-03-29
910청마파크아파트부산광역시연제구고분로106,(연산동,청마파크)부산광역시연제구연산동969-2번지청마파크35.185095129.094099150음용수자치단체시설적합2024-03-29
연번시설명도로명주소지번주소위도경도톤수수질구분시설구분2024년1분기데이터기준일자
3536부산경상대학B부산광역시연제구고분로170,(연산동)부산광역시연제구연산동277-4번지35.185429129.100955150음용수공공용적합2024-03-29
3637국세청(B)부산광역시연제구토곡로20,(연산동)부산광역시연제구연산동243-13번지35.182945129.10553380생활용수공공용적합(3년주기)2024-03-29
3738환경자원관리소부산광역시연제구고분로222,(연산동)부산광역시연제구연산동243-19번지35.183253129.10634990음용수공공용적합2024-03-29
3839연산국제아파트부산광역시연제구연수로184,(연산동,국제)부산광역시연제구연산동1873-70번지국제35.17354129.09102470음용수공공용부적합2024-03-29
3940거제청구하이츠아파트부산광역시연제구화지로95,(거제동,거제청구하이츠)부산광역시연제구거제동769-78번지거제청구하이츠35.183345129.06592560생활용수공공용적합(3년주기)2024-03-29
4041진일아파트부산광역시연제구고분로136,(연산동,진일)부산광역시연제구연산동1110-2번지진일35.18502129.09637195음용수공공용적합2024-03-29
4142한독아파트부산광역시연제구봉수로15,(연산동,한독)부산광역시연제구연산동1873-70번지한독35.172886129.08955560음용수공공용부적합2024-03-29
4243닥터메포츠부산광역시연제구거제시장로42,(거제동,닥터메포츠)부산광역시연제구거제동584-1번지닥터메포츠35.18328129.07088350생활용수공공용적합(3년주기)2024-03-29
4344무진빌딩부산광역시연제구연제로27,(연산동,무진빌딩)부산광역시연제구연산동867-51번지무진빌딩35.17781129.0765765생활용수공공용적합(3년주기)2024-03-29
4445럭키랜드부산광역시연제구토곡로39,(연산동,럭키랜드)부산광역시연제구연산동19번지럭키랜드35.18183129.10336220생활용수공공용적합(3년주기)2024-03-29