Overview

Dataset statistics

Number of variables8
Number of observations91
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory68.5 B

Variable types

Numeric3
Text3
Categorical2

Dataset

Description부산교통공사_도시철도역세권관광지현황_20211020
Author부산교통공사
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3057433

Alerts

연번 is highly overall correlated with 호선 and 2 other fieldsHigh correlation
호선 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
역번호 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
인근역명 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연락처 has 2 (2.2%) missing valuesMissing
연번 has unique valuesUnique
관광지명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:47:20.788477
Analysis finished2023-12-10 17:47:25.441227
Duration4.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46
Minimum1
Maximum91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-11T02:47:25.647992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.5
Q123.5
median46
Q368.5
95-th percentile86.5
Maximum91
Range90
Interquartile range (IQR)45

Descriptive statistics

Standard deviation26.41338
Coefficient of variation (CV)0.57420392
Kurtosis-1.2
Mean46
Median Absolute Deviation (MAD)23
Skewness0
Sum4186
Variance697.66667
MonotonicityStrictly increasing
2023-12-11T02:47:25.967183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
59 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
Other values (81) 81
89.0%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%

관광지명
Text

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-11T02:47:26.556458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length7.3076923
Min length3

Characters and Unicode

Total characters665
Distinct characters211
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)100.0%

Sample

1st row다대포 해수욕장·꿈의낙조분수
2nd row아미산전망대
3rd row몰운대
4th row을숙도 조각공원
5th row을숙도 문화회관
ValueCountFrequency (%)
낙동강 3
 
2.3%
을숙도 3
 
2.3%
해수욕장 3
 
2.3%
서면 2
 
1.5%
부산 2
 
1.5%
apec 2
 
1.5%
해운대 2
 
1.5%
먹자골목 2
 
1.5%
우장춘기념관 1
 
0.8%
sea 1
 
0.8%
Other values (111) 111
84.1%
2023-12-11T02:47:27.443130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41
 
6.2%
관 19
 
2.9%
원 19
 
2.9%
공 18
 
2.7%
산 17
 
2.6%
부 15
 
2.3%
대 15
 
2.3%
해 14
 
2.1%
장 13
 
2.0%
동 13
 
2.0%
Other values (201) 481
72.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 582
87.5%
Space Separator 41
 
6.2%
Uppercase Letter 26
 
3.9%
Close Punctuation 6
 
0.9%
Open Punctuation 6
 
0.9%
Decimal Number 3
 
0.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 19
 
3.3%
원 19
 
3.3%
공 18
 
3.1%
산 17
 
2.9%
부 15
 
2.6%
대 15
 
2.6%
해 14
 
2.4%
장 13
 
2.2%
동 13
 
2.2%
수 11
 
1.9%
Other values (181) 428
73.5%
Uppercase Letter
ValueCountFrequency (%)
E 5
19.2%
F 3
11.5%
A 3
11.5%
C 3
11.5%
B 2
 
7.7%
I 2
 
7.7%
P 2
 
7.7%
L 1
 
3.8%
S 1
 
3.8%
N 1
 
3.8%
Other values (3) 3
11.5%
Decimal Number
ValueCountFrequency (%)
0 1
33.3%
4 1
33.3%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 582
87.5%
Common 57
 
8.6%
Latin 26
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 19
 
3.3%
원 19
 
3.3%
공 18
 
3.1%
산 17
 
2.9%
부 15
 
2.6%
대 15
 
2.6%
해 14
 
2.4%
장 13
 
2.2%
동 13
 
2.2%
수 11
 
1.9%
Other values (181) 428
73.5%
Latin
ValueCountFrequency (%)
E 5
19.2%
F 3
11.5%
A 3
11.5%
C 3
11.5%
B 2
 
7.7%
I 2
 
7.7%
P 2
 
7.7%
L 1
 
3.8%
S 1
 
3.8%
N 1
 
3.8%
Other values (3) 3
11.5%
Common
ValueCountFrequency (%)
41
71.9%
) 6
 
10.5%
( 6
 
10.5%
· 1
 
1.8%
0 1
 
1.8%
4 1
 
1.8%
1 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 582
87.5%
ASCII 82
 
12.3%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41
50.0%
) 6
 
7.3%
( 6
 
7.3%
E 5
 
6.1%
F 3
 
3.7%
A 3
 
3.7%
C 3
 
3.7%
B 2
 
2.4%
I 2
 
2.4%
P 2
 
2.4%
Other values (9) 9
 
11.0%
Hangul
ValueCountFrequency (%)
관 19
 
3.3%
원 19
 
3.3%
공 18
 
3.1%
산 17
 
2.9%
부 15
 
2.6%
대 15
 
2.6%
해 14
 
2.4%
장 13
 
2.2%
동 13
 
2.2%
수 11
 
1.9%
Other values (181) 428
73.5%
None
ValueCountFrequency (%)
· 1
100.0%

연락처
Text

MISSING 

Distinct80
Distinct (%)89.9%
Missing2
Missing (%)2.2%
Memory size860.0 B
2023-12-11T02:47:27.951079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.067416
Min length12

Characters and Unicode

Total characters1074
Distinct characters11
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

Unique75 ?
Unique (%)84.3%

Sample

1st row051-207-6041
2nd row051-265-6863
3rd row051-220-4071
4th row051-2205-8014
5th row051-2205-8014
ValueCountFrequency (%)
051-220-1444 4
 
4.5%
051-605-0116 3
 
3.4%
051-2205-8014 3
 
3.4%
051-5500-3314 2
 
2.2%
051-605-4091 2
 
2.2%
051-207-6041 1
 
1.1%
051-749-5714 1
 
1.1%
051-744-2602 1
 
1.1%
051-780-6000 1
 
1.1%
051-749-7621 1
 
1.1%
Other values (70) 70
78.7%
2023-12-11T02:47:28.743513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 224
20.9%
- 178
16.6%
5 144
13.4%
1 144
13.4%
4 101
9.4%
2 76
 
7.1%
7 52
 
4.8%
6 45
 
4.2%
8 40
 
3.7%
3 40
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 896
83.4%
Dash Punctuation 178
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 224
25.0%
5 144
16.1%
1 144
16.1%
4 101
11.3%
2 76
 
8.5%
7 52
 
5.8%
6 45
 
5.0%
8 40
 
4.5%
3 40
 
4.5%
9 30
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1074
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 224
20.9%
- 178
16.6%
5 144
13.4%
1 144
13.4%
4 101
9.4%
2 76
 
7.1%
7 52
 
4.8%
6 45
 
4.2%
8 40
 
3.7%
3 40
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1074
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 224
20.9%
- 178
16.6%
5 144
13.4%
1 144
13.4%
4 101
9.4%
2 76
 
7.1%
7 52
 
4.8%
6 45
 
4.2%
8 40
 
3.7%
3 40
 
3.7%

주소
Text

Distinct83
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-11T02:47:29.444923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length26
Mean length19.065934
Min length12

Characters and Unicode

Total characters1735
Distinct characters136
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)85.7%

Sample

1st row부산광역시 사하구 다대동
2nd row부산광역시 사하구 다대낙조 2길 77
3rd row부산광역시 사하구 몰운대1길 73
4th row부산광역시 사하구 낙동남로 1233번길 25
5th row부산광역시 사하구 낙동남로 1233번길 25
ValueCountFrequency (%)
부산광역시 91
23.7%
해운대구 14
 
3.6%
사하구 13
 
3.4%
중구 12
 
3.1%
동래구 10
 
2.6%
남구 8
 
2.1%
서구 7
 
1.8%
낙동남로 6
 
1.6%
부산진구 6
 
1.6%
영도구 6
 
1.6%
Other values (157) 211
54.9%
2023-12-11T02:47:30.657474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
293
16.9%
산 102
 
5.9%
부 100
 
5.8%
광 96
 
5.5%
시 95
 
5.5%
역 93
 
5.4%
구 91
 
5.2%
로 69
 
4.0%
1 63
 
3.6%
동 44
 
2.5%
Other values (126) 689
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1151
66.3%
Space Separator 293
 
16.9%
Decimal Number 262
 
15.1%
Uppercase Letter 12
 
0.7%
Dash Punctuation 9
 
0.5%
Other Punctuation 4
 
0.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 102
 
8.9%
부 100
 
8.7%
광 96
 
8.3%
시 95
 
8.3%
역 93
 
8.1%
구 91
 
7.9%
로 69
 
6.0%
동 44
 
3.8%
대 33
 
2.9%
길 27
 
2.3%
Other values (107) 401
34.8%
Decimal Number
ValueCountFrequency (%)
1 63
24.0%
2 37
14.1%
3 30
11.5%
6 23
 
8.8%
4 21
 
8.0%
7 21
 
8.0%
5 20
 
7.6%
9 19
 
7.3%
8 16
 
6.1%
0 12
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
P 3
25.0%
A 3
25.0%
E 3
25.0%
C 3
25.0%
Space Separator
ValueCountFrequency (%)
293
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1151
66.3%
Common 572
33.0%
Latin 12
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 102
 
8.9%
부 100
 
8.7%
광 96
 
8.3%
시 95
 
8.3%
역 93
 
8.1%
구 91
 
7.9%
로 69
 
6.0%
동 44
 
3.8%
대 33
 
2.9%
길 27
 
2.3%
Other values (107) 401
34.8%
Common
ValueCountFrequency (%)
293
51.2%
1 63
 
11.0%
2 37
 
6.5%
3 30
 
5.2%
6 23
 
4.0%
4 21
 
3.7%
7 21
 
3.7%
5 20
 
3.5%
9 19
 
3.3%
8 16
 
2.8%
Other values (5) 29
 
5.1%
Latin
ValueCountFrequency (%)
P 3
25.0%
A 3
25.0%
E 3
25.0%
C 3
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1150
66.3%
ASCII 584
33.7%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
293
50.2%
1 63
 
10.8%
2 37
 
6.3%
3 30
 
5.1%
6 23
 
3.9%
4 21
 
3.6%
7 21
 
3.6%
5 20
 
3.4%
9 19
 
3.3%
8 16
 
2.7%
Other values (9) 41
 
7.0%
Hangul
ValueCountFrequency (%)
산 102
 
8.9%
부 100
 
8.7%
광 96
 
8.3%
시 95
 
8.3%
역 93
 
8.1%
구 91
 
7.9%
로 69
 
6.0%
동 44
 
3.8%
대 33
 
2.9%
길 27
 
2.3%
Other values (106) 400
34.8%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

출구번호
Categorical

Distinct21
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size860.0 B
1
23 
5
14 
8
10 
2
7 
57
5 
Other values (16)
32 

Length

Max length5
Median length1
Mean length1.3736264
Min length1

Unique

Unique7 ?
Unique (%)7.7%

Sample

1st row24
2nd row1
3rd row4
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 23
25.3%
5 14
15.4%
8 10
11.0%
2 7
 
7.7%
57 5
 
5.5%
3 4
 
4.4%
13 4
 
4.4%
4 3
 
3.3%
10 3
 
3.3%
7 3
 
3.3%
Other values (11) 15
16.5%

Length

2023-12-11T02:47:31.013708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 23
24.7%
5 14
15.1%
8 10
10.8%
2 7
 
7.5%
57 5
 
5.4%
3 4
 
4.3%
13 4
 
4.3%
4 3
 
3.2%
10 3
 
3.2%
7 3
 
3.2%
Other values (12) 17
18.3%

호선
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5164835
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-11T02:47:31.323918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile12
Maximum23
Range22
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.679863
Coefficient of variation (CV)1.4623037
Kurtosis13.269758
Mean2.5164835
Median Absolute Deviation (MAD)0
Skewness3.540238
Sum229
Variance13.541392
MonotonicityNot monotonic
2023-12-11T02:47:31.562804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 51
56.0%
2 26
28.6%
4 4
 
4.4%
12 3
 
3.3%
14 3
 
3.3%
3 3
 
3.3%
23 1
 
1.1%
ValueCountFrequency (%)
1 51
56.0%
2 26
28.6%
3 3
 
3.3%
4 4
 
4.4%
12 3
 
3.3%
14 3
 
3.3%
23 1
 
1.1%
ValueCountFrequency (%)
23 1
 
1.1%
14 3
 
3.3%
12 3
 
3.3%
4 4
 
4.4%
3 3
 
3.3%
2 26
28.6%
1 51
56.0%

인근역명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
남포역
11 
토성역
8 
하단역
6 
부산역
 
5
대연역
 
5
Other values (25)
56 

Length

Max length7
Median length3
Mean length3.5934066
Min length3

Unique

Unique9 ?
Unique (%)9.9%

Sample

1st row다대포해수욕장
2nd row다대포해수욕장
3rd row다대포해수욕장
4th row하단역
5th row하단역

Common Values

ValueCountFrequency (%)
남포역 11
 
12.1%
토성역 8
 
8.8%
하단역 6
 
6.6%
부산역 5
 
5.5%
대연역 5
 
5.5%
해운대역 4
 
4.4%
자갈치역 4
 
4.4%
중앙역 4
 
4.4%
온천장역 4
 
4.4%
동백역 3
 
3.3%
Other values (20) 37
40.7%

Length

2023-12-11T02:47:31.888120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남포역 11
 
12.1%
토성역 8
 
8.8%
하단역 6
 
6.6%
부산역 5
 
5.5%
대연역 5
 
5.5%
해운대역 4
 
4.4%
자갈치역 4
 
4.4%
중앙역 4
 
4.4%
온천장역 4
 
4.4%
서면역 3
 
3.3%
Other values (20) 37
40.7%

역번호
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.89011
Minimum95
Maximum414
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-11T02:47:32.164320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95
5-th percentile102
Q1111
median120
Q3205
95-th percentile312
Maximum414
Range319
Interquartile range (IQR)94

Descriptive statistics

Standard deviation74.174337
Coefficient of variation (CV)0.46390822
Kurtosis3.5874979
Mean159.89011
Median Absolute Deviation (MAD)11
Skewness1.8395401
Sum14550
Variance5501.8322
MonotonicityIncreasing
2023-12-11T02:47:32.459506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
111 11
 
12.1%
109 8
 
8.8%
102 6
 
6.6%
113 5
 
5.5%
213 5
 
5.5%
203 4
 
4.4%
110 4
 
4.4%
112 4
 
4.4%
127 4
 
4.4%
212 3
 
3.3%
Other values (20) 37
40.7%
ValueCountFrequency (%)
95 3
 
3.3%
102 6
6.6%
109 8
8.8%
110 4
 
4.4%
111 11
12.1%
112 4
 
4.4%
113 5
5.5%
116 1
 
1.1%
119 3
 
3.3%
120 2
 
2.2%
ValueCountFrequency (%)
414 2
 
2.2%
405 1
 
1.1%
403 1
 
1.1%
316 1
 
1.1%
308 1
 
1.1%
235 1
 
1.1%
233 1
 
1.1%
213 5
5.5%
212 3
3.3%
209 3
3.3%

Interactions

2023-12-11T02:47:24.312496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:47:23.081631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:47:23.739746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:47:24.495661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:47:23.267798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:47:23.925290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:47:24.687085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:47:23.518987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:47:24.104370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:47:32.715099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관광지명연락처주소출구번호호선인근역명역번호
연번1.0001.0001.0001.0000.7220.6350.9940.810
관광지명1.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0000.9990.8361.0000.9951.000
주소1.0001.0000.9991.0001.0001.0001.0001.000
출구번호0.7221.0000.8361.0001.0000.7520.8770.689
호선0.6351.0001.0001.0000.7521.0001.0000.838
인근역명0.9941.0000.9951.0000.8771.0001.0001.000
역번호0.8101.0001.0001.0000.6890.8381.0001.000
2023-12-11T02:47:33.049950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출구번호인근역명
출구번호1.0000.400
인근역명0.4001.000
2023-12-11T02:47:33.267678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선역번호출구번호인근역명
연번1.0000.7690.9980.3140.734
호선0.7691.0000.7700.4940.842
역번호0.9980.7701.0000.3540.847
출구번호0.3140.4940.3541.0000.400
인근역명0.7340.8420.8470.4001.000

Missing values

2023-12-11T02:47:24.981066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:47:25.331319image/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

연번관광지명연락처주소출구번호호선인근역명역번호
01다대포 해수욕장·꿈의낙조분수051-207-6041부산광역시 사하구 다대동241다대포해수욕장95
12아미산전망대051-265-6863부산광역시 사하구 다대낙조 2길 7711다대포해수욕장95
23몰운대051-220-4071부산광역시 사하구 몰운대1길 7341다대포해수욕장95
34을숙도 조각공원051-2205-8014부산광역시 사하구 낙동남로 1233번길 2511하단역102
45을숙도 문화회관051-2205-8014부산광역시 사하구 낙동남로 1233번길 2511하단역102
56을숙도 생태공원051-2205-8014부산광역시 사하구 낙동남로 1233번길 2511하단역102
67낙동강 하구 에코센터051-209-2032부산광역시 사하구 낙동남로 124021하단역102
78낙동강 하류 철새도래지051-209-2000부산광역시 사하구 낙동남로 124021하단역102
89낙동강 문화관051-292-1042부산광역시 사하구 낙동남로 1233번길 111하단역102
910감천문화마을051-220-1444부산광역시 사하구 감내2로 177-1181토성역109
연번관광지명연락처주소출구번호호선인근역명역번호
8182부산문화회관051-607-6070부산광역시 남구 유엔평화로 76번길132대연역213
8283UN기념공원051-625-0625부산광역시 남구 유엔평화로 9312대연역213
8384구포시장051-333-9033부산광역시 북구 구포시장길 9123덕천역233
8485부산어촌민속관051-363-8900부산광역시 북구 학사로 11812화명역235
8586사직야구장051-505-7422부산광역시 동래구 사직로 4513사직역308
8687강서체육공원051-970-1211부산광역시 강서구 체육공원로 4313체육공원역316
8788동래읍성 임진왜란 역사관051-605-0116부산광역시 동래구 수민동 도시철도 4호선 수안역 (수안역내)역사내4수안역403
8889충렬사051-523-4223부산광역시 동래구 충렬대로 34514충렬사역405
8990경전철홍보관051-605-0116부산광역시 기장군 철마면 반송로 1180기지창 내4안평역414
9091휴메트로테마공원051-605-0116부산광역시 기장군 철마면 반송로 1180기지창 내4안평역414