Overview

Dataset statistics

Number of variables10
Number of observations82
Missing cells21
Missing cells (%)2.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory84.6 B

Variable types

Numeric2
Categorical5
Text3

Dataset

Description울산광역시 남구 그늘막 설치 현황에 대한 데이터로 관리번호, 시도, 시군구, 읍면동, 설치장소명, 소재지도로명주소, 소재지지번주소, 설치년도, 종류, 폭의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15038454/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
폭 is highly overall correlated with 종류High correlation
종류 is highly overall correlated with 폭High correlation
관리번호 is highly overall correlated with 설치년도High correlation
설치년도 is highly overall correlated with 관리번호High correlation
종류 is highly imbalanced (57.9%)Imbalance
소재지도로명주소 has 21 (25.6%) missing valuesMissing
관리번호 has unique valuesUnique
설치장소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:48:58.893104
Analysis finished2023-12-12 05:49:00.287813
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.5
Minimum1
Maximum82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T14:49:00.354638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.05
Q121.25
median41.5
Q361.75
95-th percentile77.95
Maximum82
Range81
Interquartile range (IQR)40.5

Descriptive statistics

Standard deviation23.815261
Coefficient of variation (CV)0.57386172
Kurtosis-1.2
Mean41.5
Median Absolute Deviation (MAD)20.5
Skewness0
Sum3403
Variance567.16667
MonotonicityStrictly increasing
2023-12-12T14:49:00.489644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
63 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
울산광역시
82 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
울산광역시 82
100.0%

Length

2023-12-12T14:49:00.655812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:49:00.770283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울산광역시 82
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
남구
82 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남구 82
100.0%

Length

2023-12-12T14:49:00.914445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:49:01.015587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남구 82
100.0%

읍면동
Categorical

Distinct15
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size788.0 B
삼산동
19 
달동
14 
무거동
10 
신정동
8 
야음동
5 
Other values (10)
26 

Length

Max length6
Median length3
Mean length3.0243902
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신정2동
2nd row신정4동
3rd row신정2동
4th row신정4동
5th row달동

Common Values

ValueCountFrequency (%)
삼산동 19
23.2%
달동 14
17.1%
무거동 10
12.2%
신정동 8
9.8%
야음동 5
 
6.1%
신정4동 4
 
4.9%
신정3동 4
 
4.9%
대현동 3
 
3.7%
두왕동 3
 
3.7%
신정2동 2
 
2.4%
Other values (5) 10
12.2%

Length

2023-12-12T14:49:01.226096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
삼산동 19
23.2%
달동 14
17.1%
무거동 10
12.2%
신정동 8
9.8%
야음동 5
 
6.1%
신정4동 4
 
4.9%
신정3동 4
 
4.9%
대현동 3
 
3.7%
두왕동 3
 
3.7%
신정2동 2
 
2.4%
Other values (5) 10
12.2%

설치장소명
Text

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-12-12T14:49:01.705346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length11.865854
Min length5

Characters and Unicode

Total characters973
Distinct characters202
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

Unique82 ?
Unique (%)100.0%

Sample

1st row옥동초사거리 경남은행 앞
2nd row동서오거리
3rd row대흥교회 앞
4th row수암시장 앞
5th row달동사거리 롯데마트 앞
ValueCountFrequency (%)
앞 28
 
13.0%
횡단보도 19
 
8.8%
교차로 8
 
3.7%
남측 7
 
3.2%
방면 5
 
2.3%
정동사거리 4
 
1.9%
교통섬 4
 
1.9%
북측 4
 
1.9%
남동측 4
 
1.9%
중리사거리 4
 
1.9%
Other values (111) 129
59.7%
2023-12-12T14:49:02.516234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
134
 
13.8%
리 32
 
3.3%
앞 32
 
3.3%
교 30
 
3.1%
남 25
 
2.6%
측 24
 
2.5%
사 23
 
2.4%
거 23
 
2.4%
도 22
 
2.3%
단 20
 
2.1%
Other values (192) 608
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 797
81.9%
Space Separator 134
 
13.8%
Uppercase Letter 21
 
2.2%
Decimal Number 10
 
1.0%
Lowercase Letter 5
 
0.5%
Open Punctuation 3
 
0.3%
Close Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 32
 
4.0%
앞 32
 
4.0%
교 30
 
3.8%
남 25
 
3.1%
측 24
 
3.0%
사 23
 
2.9%
거 23
 
2.9%
도 22
 
2.8%
단 20
 
2.5%
동 19
 
2.4%
Other values (173) 547
68.6%
Uppercase Letter
ValueCountFrequency (%)
K 7
33.3%
S 4
19.0%
B 3
14.3%
H 2
 
9.5%
N 2
 
9.5%
T 2
 
9.5%
I 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 3
30.0%
3 3
30.0%
2 2
20.0%
5 1
 
10.0%
4 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
40.0%
z 1
20.0%
p 1
20.0%
l 1
20.0%
Space Separator
ValueCountFrequency (%)
134
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 797
81.9%
Common 150
 
15.4%
Latin 26
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 32
 
4.0%
앞 32
 
4.0%
교 30
 
3.8%
남 25
 
3.1%
측 24
 
3.0%
사 23
 
2.9%
거 23
 
2.9%
도 22
 
2.8%
단 20
 
2.5%
동 19
 
2.4%
Other values (173) 547
68.6%
Latin
ValueCountFrequency (%)
K 7
26.9%
S 4
15.4%
B 3
11.5%
a 2
 
7.7%
H 2
 
7.7%
N 2
 
7.7%
T 2
 
7.7%
z 1
 
3.8%
p 1
 
3.8%
l 1
 
3.8%
Common
ValueCountFrequency (%)
134
89.3%
( 3
 
2.0%
1 3
 
2.0%
) 3
 
2.0%
3 3
 
2.0%
2 2
 
1.3%
5 1
 
0.7%
4 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 797
81.9%
ASCII 176
 
18.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
134
76.1%
K 7
 
4.0%
S 4
 
2.3%
( 3
 
1.7%
1 3
 
1.7%
) 3
 
1.7%
B 3
 
1.7%
3 3
 
1.7%
a 2
 
1.1%
H 2
 
1.1%
Other values (9) 12
 
6.8%
Hangul
ValueCountFrequency (%)
리 32
 
4.0%
앞 32
 
4.0%
교 30
 
3.8%
남 25
 
3.1%
측 24
 
3.0%
사 23
 
2.9%
거 23
 
2.9%
도 22
 
2.8%
단 20
 
2.5%
동 19
 
2.4%
Other values (173) 547
68.6%

소재지도로명주소
Text

MISSING 

Distinct60
Distinct (%)98.4%
Missing21
Missing (%)25.6%
Memory size788.0 B
2023-12-12T14:49:02.924890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length16
Mean length16.557377
Min length7

Characters and Unicode

Total characters1010
Distinct characters59
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)96.7%

Sample

1st row문수로 403
2nd row울산광역시 남구 중앙로 105
3rd row울산광역시 남구 문수로 461
4th row울산광역시 남구 수암로 117
5th row울산광역시 남구 삼산로 74
ValueCountFrequency (%)
울산광역시 60
24.2%
남구 60
24.2%
삼산로 14
 
5.6%
수암로 6
 
2.4%
돋질로 6
 
2.4%
중앙로 6
 
2.4%
번영로 6
 
2.4%
212 3
 
1.2%
북부순환도로 3
 
1.2%
문수로 3
 
1.2%
Other values (76) 81
32.7%
2023-12-12T14:49:03.667719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
187
18.5%
산 77
 
7.6%
로 61
 
6.0%
울 60
 
5.9%
광 60
 
5.9%
역 60
 
5.9%
시 60
 
5.9%
남 60
 
5.9%
구 60
 
5.9%
2 38
 
3.8%
Other values (49) 287
28.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 637
63.1%
Space Separator 189
 
18.7%
Decimal Number 182
 
18.0%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 77
12.1%
로 61
9.6%
울 60
9.4%
광 60
9.4%
역 60
9.4%
시 60
9.4%
남 60
9.4%
구 60
9.4%
삼 16
 
2.5%
번 14
 
2.2%
Other values (36) 109
17.1%
Decimal Number
ValueCountFrequency (%)
2 38
20.9%
1 37
20.3%
3 20
11.0%
4 17
9.3%
6 15
 
8.2%
8 12
 
6.6%
0 12
 
6.6%
7 12
 
6.6%
5 10
 
5.5%
9 9
 
4.9%
Space Separator
ValueCountFrequency (%)
187
98.9%
　 2
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 637
63.1%
Common 373
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 77
12.1%
로 61
9.6%
울 60
9.4%
광 60
9.4%
역 60
9.4%
시 60
9.4%
남 60
9.4%
구 60
9.4%
삼 16
 
2.5%
번 14
 
2.2%
Other values (36) 109
17.1%
Common
ValueCountFrequency (%)
187
50.1%
2 38
 
10.2%
1 37
 
9.9%
3 20
 
5.4%
4 17
 
4.6%
6 15
 
4.0%
8 12
 
3.2%
0 12
 
3.2%
7 12
 
3.2%
5 10
 
2.7%
Other values (3) 13
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 637
63.1%
ASCII 371
36.7%
None 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
187
50.4%
2 38
 
10.2%
1 37
 
10.0%
3 20
 
5.4%
4 17
 
4.6%
6 15
 
4.0%
8 12
 
3.2%
0 12
 
3.2%
7 12
 
3.2%
5 10
 
2.7%
Other values (2) 11
 
3.0%
Hangul
ValueCountFrequency (%)
산 77
12.1%
로 61
9.6%
울 60
9.4%
광 60
9.4%
역 60
9.4%
시 60
9.4%
남 60
9.4%
구 60
9.4%
삼 16
 
2.5%
번 14
 
2.2%
Other values (36) 109
17.1%
None
ValueCountFrequency (%)
　 2
100.0%

소재지지번주소
Text

Distinct80
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-12-12T14:49:04.096208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length18.04878
Min length16

Characters and Unicode

Total characters1480
Distinct characters31
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

Unique78 ?
Unique (%)95.1%

Sample

1st row울산광역시 남구 신정동 1629-6
2nd row울산광역시 남구 신정동 814-7
3rd row울산광역시 남구 신정동 1649-1
4th row울산광역시 남구 신정동 853-29
5th row울산광역시 남구 달동 830-1
ValueCountFrequency (%)
울산광역시 82
24.9%
남구 82
24.9%
신정동 21
 
6.4%
삼산동 18
 
5.5%
달동 14
 
4.3%
야음동 12
 
3.6%
무거동 12
 
3.6%
두왕동 3
 
0.9%
212 2
 
0.6%
499-19 2
 
0.6%
Other values (78) 81
24.6%
2023-12-12T14:49:04.632929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
247
16.7%
산 101
 
6.8%
1 92
 
6.2%
울 82
 
5.5%
광 82
 
5.5%
역 82
 
5.5%
시 82
 
5.5%
남 82
 
5.5%
구 82
 
5.5%
동 82
 
5.5%
Other values (21) 466
31.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 805
54.4%
Decimal Number 360
24.3%
Space Separator 247
 
16.7%
Dash Punctuation 68
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 101
12.5%
울 82
10.2%
광 82
10.2%
역 82
10.2%
시 82
10.2%
남 82
10.2%
구 82
10.2%
동 82
10.2%
정 21
 
2.6%
신 21
 
2.6%
Other values (9) 88
10.9%
Decimal Number
ValueCountFrequency (%)
1 92
25.6%
4 46
12.8%
3 34
 
9.4%
5 32
 
8.9%
6 31
 
8.6%
8 31
 
8.6%
2 31
 
8.6%
9 30
 
8.3%
7 17
 
4.7%
0 16
 
4.4%
Space Separator
ValueCountFrequency (%)
247
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 805
54.4%
Common 675
45.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 101
12.5%
울 82
10.2%
광 82
10.2%
역 82
10.2%
시 82
10.2%
남 82
10.2%
구 82
10.2%
동 82
10.2%
정 21
 
2.6%
신 21
 
2.6%
Other values (9) 88
10.9%
Common
ValueCountFrequency (%)
247
36.6%
1 92
 
13.6%
- 68
 
10.1%
4 46
 
6.8%
3 34
 
5.0%
5 32
 
4.7%
6 31
 
4.6%
8 31
 
4.6%
2 31
 
4.6%
9 30
 
4.4%
Other values (2) 33
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 805
54.4%
ASCII 675
45.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
247
36.6%
1 92
 
13.6%
- 68
 
10.1%
4 46
 
6.8%
3 34
 
5.0%
5 32
 
4.7%
6 31
 
4.6%
8 31
 
4.6%
2 31
 
4.6%
9 30
 
4.4%
Other values (2) 33
 
4.9%
Hangul
ValueCountFrequency (%)
산 101
12.5%
울 82
10.2%
광 82
10.2%
역 82
10.2%
시 82
10.2%
남 82
10.2%
구 82
10.2%
동 82
10.2%
정 21
 
2.6%
신 21
 
2.6%
Other values (9) 88
10.9%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.5244
Minimum2017
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T14:49:04.784897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12019
median2021
Q32022
95-th percentile2023
Maximum2023
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9259476
Coefficient of variation (CV)0.00095319198
Kurtosis-0.94498242
Mean2020.5244
Median Absolute Deviation (MAD)1
Skewness-0.52695207
Sum165683
Variance3.7092743
MonotonicityIncreasing
2023-12-12T14:49:04.906872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2022 23
28.0%
2021 14
17.1%
2023 11
13.4%
2017 9
 
11.0%
2019 9
 
11.0%
2020 9
 
11.0%
2018 7
 
8.5%
ValueCountFrequency (%)
2017 9
 
11.0%
2018 7
 
8.5%
2019 9
 
11.0%
2020 9
 
11.0%
2021 14
17.1%
2022 23
28.0%
2023 11
13.4%
ValueCountFrequency (%)
2023 11
13.4%
2022 23
28.0%
2021 14
17.1%
2020 9
 
11.0%
2019 9
 
11.0%
2018 7
 
8.5%
2017 9
 
11.0%

종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
접이식
75 
스마트
 
7

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
접이식 75
91.5%
스마트 7
 
8.5%

Length

2023-12-12T14:49:05.066605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:49:05.197459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
접이식 75
91.5%
스마트 7
 
8.5%

폭
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size788.0 B
4.0
50 
3.0
22 
5.5
7 
5.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4.0
2nd row3.0
3rd row3.0
4th row3.0
5th row5.0

Common Values

ValueCountFrequency (%)
4.0 50
61.0%
3.0 22
26.8%
5.5 7
 
8.5%
5.0 3
 
3.7%

Length

2023-12-12T14:49:05.346628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:49:05.485741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4.0 50
61.0%
3.0 22
26.8%
5.5 7
 
8.5%
5.0 3
 
3.7%

Interactions

2023-12-12T14:48:59.834414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:48:59.669542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:48:59.928916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:48:59.753668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:49:05.602699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호읍면동설치장소명소재지도로명주소소재지지번주소설치년도종류폭
관리번호1.0000.6861.0001.0001.0000.9910.2830.550
읍면동0.6861.0001.0001.0001.0000.6790.0000.000
설치장소명1.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.000
설치년도0.9910.6791.0001.0001.0001.0000.0000.520
종류0.2830.0001.0001.0001.0000.0001.0001.000
폭0.5500.0001.0001.0001.0000.5201.0001.000
2023-12-12T14:49:05.719353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폭종류읍면동
폭1.0000.9870.000
종류0.9871.0000.000
읍면동0.0000.0001.000
2023-12-12T14:49:05.834586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호설치년도읍면동종류폭
관리번호1.0000.9830.3190.2030.346
설치년도0.9831.0000.3850.0000.348
읍면동0.3190.3851.0000.0000.000
종류0.2030.0000.0001.0000.987
폭0.3460.3480.0000.9871.000

Missing values

2023-12-12T14:49:00.081338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:49:00.235677image/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

관리번호시도시군구읍면동설치장소명소재지도로명주소소재지지번주소설치년도종류폭
01울산광역시남구신정2동옥동초사거리 경남은행 앞문수로 403울산광역시 남구 신정동 1629-62017접이식4.0
12울산광역시남구신정4동동서오거리울산광역시 남구 중앙로 105울산광역시 남구 신정동 814-72017접이식3.0
23울산광역시남구신정2동대흥교회 앞울산광역시 남구 문수로 461울산광역시 남구 신정동 1649-12017접이식3.0
34울산광역시남구신정4동수암시장 앞울산광역시 남구 수암로 117울산광역시 남구 신정동 853-292017접이식3.0
45울산광역시남구달동달동사거리 롯데마트 앞울산광역시 남구 삼산로 74울산광역시 남구 달동 830-12017접이식5.0
56울산광역시남구달동남구청사거리 문화공원 앞울산광역시 남구 돋질로 233울산광역시 남구 달동 1320-12017접이식3.0
67울산광역시남구삼산동태화강역 알리바바모텔 앞울산광역시 남구 삼산로 406울산광역시 남구 삼산동 1638-102017접이식5.0
78울산광역시남구무거동쇠정사거리 산림조합 앞울산광역시 남구 옥현로 117울산광역시 남구 무거동 464-72017접이식4.0
89울산광역시남구대현동야음사거리 농협 맞은편울산광역시 남구 수암로 216울산광역시 남구 야음동 832-112017접이식5.0
910울산광역시남구신정3동신정시장 IBK기업은행 앞울산광역시 남구 중앙로 248울산광역시 남구 신정동 496-122018접이식4.0
관리번호시도시군구읍면동설치장소명소재지도로명주소소재지지번주소설치년도종류폭
7273울산광역시남구달동올리브영 횡단보도울산광역시 남구 삼산로 136울산광역시 남구 달동 114-12023접이식4.0
7374울산광역시남구무거동올포유 횡단보도울산광역시 남구 북부순환도로 36울산광역시 남구 무거동 169-62023접이식4.0
7475울산광역시남구신정동시청사거리 시청 횡단보도울산광역시 남구 중앙로 201울산광역시 남구 신정동 646-42023스마트5.5
7576울산광역시남구대현동만호공인중개사 횡단보도울산광역시 남구 번영로 28울산광역시 남구 야음동 646-42023접이식4.0
7677울산광역시남구삼산동웰빙약국 횡단보도울산광역시 남구 삼산로 260울산광역시 남구 삼산동 1474-12023스마트5.5
7778울산광역시남구삼산동농수산물도매시장 정문 횡단보도울산광역시 남구 삼산로 324울산광역시 남구 삼산동 904-102023접이식4.0
7879울산광역시남구삼산동KT plaza 횡단보도<NA>울산광역시 남구 삼산동 562-232023접이식4.0
7980울산광역시남구달동NH농협은행 횡단보도울산광역시 남구 삼산로 156울산광역시 남구 달동 116-12023접이식4.0
8081울산광역시남구달동유원빌딩 횡단보도울산광역시 남구 삼산로 63울산광역시 남구 달동 886-82023접이식4.0
8182울산광역시남구달동SK주유소 횡단보도울산광역시 남구 번영로 76울산광역시 남구 달동 1297-42023접이식3.0