Overview

Dataset statistics

Number of variables8
Number of observations1835
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory118.4 KiB
Average record size in memory66.1 B

Variable types

Numeric2
Categorical2
Text4

Dataset

Description서울교통공사의 역사 에스컬레이터 설치 현황 데이터 입니다. 해당 데이터는 연번, 호선, 역명, 장비종류, 호기, 승강기번호, 운행구간, 설치위치를 포함하고 있습니다. 2023년 11월 기준입니다.
Author서울교통공사
URLhttps://www.data.go.kr/data/15044260/fileData.do

Alerts

장비종류 has constant value ""Constant
연번 is highly overall correlated with 호선High correlation
호선 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
승강기번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:03:50.853744
Analysis finished2023-12-12 19:03:51.787262
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1835
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean918
Minimum1
Maximum1835
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2023-12-13T04:03:51.857225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile92.7
Q1459.5
median918
Q31376.5
95-th percentile1743.3
Maximum1835
Range1834
Interquartile range (IQR)917

Descriptive statistics

Standard deviation529.86319
Coefficient of variation (CV)0.57719302
Kurtosis-1.2
Mean918
Median Absolute Deviation (MAD)459
Skewness0
Sum1684530
Variance280755
MonotonicityStrictly increasing
2023-12-13T04:03:51.988579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1234 1
 
0.1%
1232 1
 
0.1%
1231 1
 
0.1%
1230 1
 
0.1%
1229 1
 
0.1%
1228 1
 
0.1%
1227 1
 
0.1%
1226 1
 
0.1%
1225 1
 
0.1%
Other values (1825) 1825
99.5%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1835 1
0.1%
1834 1
0.1%
1833 1
0.1%
1832 1
0.1%
1831 1
0.1%
1830 1
0.1%
1829 1
0.1%
1828 1
0.1%
1827 1
0.1%
1826 1
0.1%

호선
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
7
386 
5
348 
6
290 
2
236 
3
210 
Other values (4)
365 

Length

Max length4
Median length1
Mean length1.1798365
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
7 386
21.0%
5 348
19.0%
6 290
15.8%
2 236
12.9%
3 210
11.4%
4 133
 
7.2%
5(연) 110
 
6.0%
8 89
 
4.9%
1 33
 
1.8%

Length

2023-12-13T04:03:52.123225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:03:52.229614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 386
21.0%
5 348
19.0%
6 290
15.8%
2 236
12.9%
3 210
11.4%
4 133
 
7.2%
5(연 110
 
6.0%
8 89
 
4.9%
1 33
 
1.8%

역명
Text

Distinct251
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
2023-12-13T04:03:52.521155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length4.0408719
Min length2

Characters and Unicode

Total characters7415
Distinct characters209
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

Unique2 ?
Unique (%)0.1%

Sample

1st row서울역(1)
2nd row서울역(1)
3rd row서울역(1)
4th row서울역(1)
5th row서울역(1)
ValueCountFrequency (%)
하남시청 28
 
1.5%
고속터미널(3 24
 
1.3%
하남풍산 24
 
1.3%
충무로(4 23
 
1.3%
이수(7 23
 
1.3%
미사 22
 
1.2%
가락시장(3 22
 
1.2%
고속터미널(7 21
 
1.1%
하남검단산 20
 
1.1%
경찰병원 20
 
1.1%
Other values (241) 1608
87.6%
2023-12-13T04:03:52.921112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 634
 
8.6%
( 634
 
8.6%
대 192
 
2.6%
구 176
 
2.4%
산 141
 
1.9%
7 140
 
1.9%
6 131
 
1.8%
신 130
 
1.8%
3 127
 
1.7%
동 122
 
1.6%
Other values (199) 4988
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5478
73.9%
Decimal Number 669
 
9.0%
Close Punctuation 634
 
8.6%
Open Punctuation 634
 
8.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 192
 
3.5%
구 176
 
3.2%
산 141
 
2.6%
신 130
 
2.4%
동 122
 
2.2%
남 120
 
2.2%
청 111
 
2.0%
수 96
 
1.8%
가 93
 
1.7%
장 93
 
1.7%
Other values (189) 4204
76.7%
Decimal Number
ValueCountFrequency (%)
7 140
20.9%
6 131
19.6%
3 127
19.0%
4 89
13.3%
2 81
12.1%
5 50
 
7.5%
1 29
 
4.3%
8 22
 
3.3%
Close Punctuation
ValueCountFrequency (%)
) 634
100.0%
Open Punctuation
ValueCountFrequency (%)
( 634
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5478
73.9%
Common 1937
 
26.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 192
 
3.5%
구 176
 
3.2%
산 141
 
2.6%
신 130
 
2.4%
동 122
 
2.2%
남 120
 
2.2%
청 111
 
2.0%
수 96
 
1.8%
가 93
 
1.7%
장 93
 
1.7%
Other values (189) 4204
76.7%
Common
ValueCountFrequency (%)
) 634
32.7%
( 634
32.7%
7 140
 
7.2%
6 131
 
6.8%
3 127
 
6.6%
4 89
 
4.6%
2 81
 
4.2%
5 50
 
2.6%
1 29
 
1.5%
8 22
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5478
73.9%
ASCII 1937
 
26.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 634
32.7%
( 634
32.7%
7 140
 
7.2%
6 131
 
6.8%
3 127
 
6.6%
4 89
 
4.6%
2 81
 
4.2%
5 50
 
2.6%
1 29
 
1.5%
8 22
 
1.1%
Hangul
ValueCountFrequency (%)
대 192
 
3.5%
구 176
 
3.2%
산 141
 
2.6%
신 130
 
2.4%
동 122
 
2.2%
남 120
 
2.2%
청 111
 
2.0%
수 96
 
1.8%
가 93
 
1.7%
장 93
 
1.7%
Other values (189) 4204
76.7%

장비종류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
E/S
1835 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowE/S
2nd rowE/S
3rd rowE/S
4th rowE/S
5th rowE/S

Common Values

ValueCountFrequency (%)
E/S 1835
100.0%

Length

2023-12-13T04:03:53.041241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:03:53.130928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
e/s 1835
100.0%

호기
Real number (ℝ)

Distinct28
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8485014
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.3 KiB
2023-12-13T04:03:53.214977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q38
95-th percentile15.3
Maximum28
Range27
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.6653485
Coefficient of variation (CV)0.79769982
Kurtosis2.2693074
Mean5.8485014
Median Absolute Deviation (MAD)2
Skewness1.4605065
Sum10732
Variance21.765476
MonotonicityNot monotonic
2023-12-13T04:03:53.344501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 248
13.5%
2 246
13.4%
3 215
11.7%
4 209
11.4%
5 152
8.3%
6 146
8.0%
7 107
5.8%
8 104
 
5.7%
9 73
 
4.0%
10 69
 
3.8%
Other values (18) 266
14.5%
ValueCountFrequency (%)
1 248
13.5%
2 246
13.4%
3 215
11.7%
4 209
11.4%
5 152
8.3%
6 146
8.0%
7 107
5.8%
8 104
5.7%
9 73
 
4.0%
10 69
 
3.8%
ValueCountFrequency (%)
28 1
 
0.1%
27 1
 
0.1%
26 1
 
0.1%
25 1
 
0.1%
24 4
 
0.2%
23 5
0.3%
22 7
0.4%
21 8
0.4%
20 10
0.5%
19 11
0.6%

승강기번호
Text

UNIQUE 

Distinct1835
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
2023-12-13T04:03:53.652327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8.0016349
Min length8

Characters and Unicode

Total characters14683
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1835 ?
Unique (%)100.0%

Sample

1st row1800-448
2nd row1806-600
3rd row1806-599
4th row1810-816
5th row1810-817
ValueCountFrequency (%)
1800-448 1
 
0.1%
1809-212 1
 
0.1%
1808-199 1
 
0.1%
1812-500 1
 
0.1%
1812-510 1
 
0.1%
1810-743 1
 
0.1%
1810-744 1
 
0.1%
1808-192 1
 
0.1%
1808-191 1
 
0.1%
1809-500 1
 
0.1%
Other values (1825) 1825
99.5%
2023-12-13T04:03:54.082463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2914
19.8%
8 2719
18.5%
0 2325
15.8%
- 1835
12.5%
3 883
 
6.0%
9 863
 
5.9%
7 701
 
4.8%
4 628
 
4.3%
2 612
 
4.2%
6 601
 
4.1%
Other values (2) 602
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12845
87.5%
Dash Punctuation 1835
 
12.5%
Space Separator 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2914
22.7%
8 2719
21.2%
0 2325
18.1%
3 883
 
6.9%
9 863
 
6.7%
7 701
 
5.5%
4 628
 
4.9%
2 612
 
4.8%
6 601
 
4.7%
5 599
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 1835
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14683
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2914
19.8%
8 2719
18.5%
0 2325
15.8%
- 1835
12.5%
3 883
 
6.0%
9 863
 
5.9%
7 701
 
4.8%
4 628
 
4.3%
2 612
 
4.2%
6 601
 
4.1%
Other values (2) 602
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14683
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2914
19.8%
8 2719
18.5%
0 2325
15.8%
- 1835
12.5%
3 883
 
6.0%
9 863
 
5.9%
7 701
 
4.8%
4 628
 
4.3%
2 612
 
4.2%
6 601
 
4.1%
Other values (2) 602
 
4.1%

운행구간
Text

Distinct83
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
2023-12-13T04:03:54.284219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length5
Mean length5.0463215
Min length4

Characters and Unicode

Total characters9260
Distinct characters24
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)1.8%

Sample

1st rowB2-B1
2nd rowB1-B2
3rd rowB2-B1
4th rowB1-1F
5th row1F-B1
ValueCountFrequency (%)
b1-1f 359
19.6%
1f-b1 338
18.4%
b2-b1 146
 
8.0%
b1-b2 114
 
6.2%
b3-b2 107
 
5.8%
b2-b3 86
 
4.7%
b1-bm 80
 
4.4%
b3-b1 55
 
3.0%
b1-b3 54
 
2.9%
1f-bm 52
 
2.8%
Other values (72) 445
24.2%
2023-12-13T04:03:54.693492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 2614
28.2%
1 2172
23.5%
- 1838
19.8%
F 1031
 
11.1%
2 673
 
7.3%
3 395
 
4.3%
M 291
 
3.1%
4 138
 
1.5%
5 35
 
0.4%
호 8
 
0.1%
Other values (14) 65
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3939
42.5%
Decimal Number 3421
36.9%
Dash Punctuation 1838
19.8%
Other Letter 42
 
0.5%
Close Punctuation 8
 
0.1%
Open Punctuation 8
 
0.1%
Other Punctuation 3
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 8
19.0%
선 8
19.0%
계 5
11.9%
단 5
11.9%
연 4
9.5%
결 4
9.5%
통 4
9.5%
로 4
9.5%
Decimal Number
ValueCountFrequency (%)
1 2172
63.5%
2 673
 
19.7%
3 395
 
11.5%
4 138
 
4.0%
5 35
 
1.0%
6 6
 
0.2%
8 2
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
B 2614
66.4%
F 1031
 
26.2%
M 291
 
7.4%
A 3
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1838
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5279
57.0%
Latin 3939
42.5%
Hangul 42
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2172
41.1%
- 1838
34.8%
2 673
 
12.7%
3 395
 
7.5%
4 138
 
2.6%
5 35
 
0.7%
) 8
 
0.2%
( 8
 
0.2%
6 6
 
0.1%
, 3
 
0.1%
Other values (2) 3
 
0.1%
Hangul
ValueCountFrequency (%)
호 8
19.0%
선 8
19.0%
계 5
11.9%
단 5
11.9%
연 4
9.5%
결 4
9.5%
통 4
9.5%
로 4
9.5%
Latin
ValueCountFrequency (%)
B 2614
66.4%
F 1031
 
26.2%
M 291
 
7.4%
A 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9218
99.5%
Hangul 42
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 2614
28.4%
1 2172
23.6%
- 1838
19.9%
F 1031
 
11.2%
2 673
 
7.3%
3 395
 
4.3%
M 291
 
3.2%
4 138
 
1.5%
5 35
 
0.4%
) 8
 
0.1%
Other values (6) 23
 
0.2%
Hangul
ValueCountFrequency (%)
호 8
19.0%
선 8
19.0%
계 5
11.9%
단 5
11.9%
연 4
9.5%
결 4
9.5%
통 4
9.5%
로 4
9.5%

설치위치
Text

Distinct379
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size14.5 KiB
2023-12-13T04:03:55.080821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length6
Mean length8.1307902
Min length3

Characters and Unicode

Total characters14920
Distinct characters200
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)5.9%

Sample

1st row연결통로(4호선)
2nd row남영 방면2-3
3rd row시청 방면9-3
4th row4번 출입구
5th row4번 출입구
ValueCountFrequency (%)
출입구 1010
27.3%
1번 208
 
5.6%
3번 165
 
4.5%
2번 157
 
4.2%
대합실 149
 
4.0%
4번 148
 
4.0%
출입구방면 93
 
2.5%
5번 90
 
2.4%
6번 73
 
2.0%
8번 45
 
1.2%
Other values (311) 1568
42.3%
2023-12-13T04:03:55.555897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1881
 
12.6%
구 1151
 
7.7%
입 1128
 
7.6%
출 1115
 
7.5%
번 1115
 
7.5%
방 624
 
4.2%
면 609
 
4.1%
1 575
 
3.9%
- 484
 
3.2%
3 439
 
2.9%
Other values (190) 5799
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9185
61.6%
Decimal Number 2468
 
16.5%
Space Separator 1881
 
12.6%
Dash Punctuation 484
 
3.2%
Close Punctuation 274
 
1.8%
Open Punctuation 274
 
1.8%
Other Punctuation 257
 
1.7%
Uppercase Letter 62
 
0.4%
Math Symbol 35
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1151
12.5%
입 1128
12.3%
출 1115
12.1%
번 1115
12.1%
방 624
 
6.8%
면 609
 
6.6%
대 379
 
4.1%
실 331
 
3.6%
합 312
 
3.4%
로 191
 
2.1%
Other values (166) 2230
24.3%
Decimal Number
ValueCountFrequency (%)
1 575
23.3%
3 439
17.8%
2 401
16.2%
4 381
15.4%
6 171
 
6.9%
5 163
 
6.6%
7 137
 
5.6%
8 109
 
4.4%
9 54
 
2.2%
0 38
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
B 48
77.4%
E 5
 
8.1%
L 3
 
4.8%
S 2
 
3.2%
W 2
 
3.2%
M 2
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 248
96.5%
/ 7
 
2.7%
# 2
 
0.8%
Space Separator
ValueCountFrequency (%)
1881
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 484
100.0%
Close Punctuation
ValueCountFrequency (%)
) 274
100.0%
Open Punctuation
ValueCountFrequency (%)
( 274
100.0%
Math Symbol
ValueCountFrequency (%)
~ 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9185
61.6%
Common 5673
38.0%
Latin 62
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1151
12.5%
입 1128
12.3%
출 1115
12.1%
번 1115
12.1%
방 624
 
6.8%
면 609
 
6.6%
대 379
 
4.1%
실 331
 
3.6%
합 312
 
3.4%
로 191
 
2.1%
Other values (166) 2230
24.3%
Common
ValueCountFrequency (%)
1881
33.2%
1 575
 
10.1%
- 484
 
8.5%
3 439
 
7.7%
2 401
 
7.1%
4 381
 
6.7%
) 274
 
4.8%
( 274
 
4.8%
, 248
 
4.4%
6 171
 
3.0%
Other values (8) 545
 
9.6%
Latin
ValueCountFrequency (%)
B 48
77.4%
E 5
 
8.1%
L 3
 
4.8%
S 2
 
3.2%
W 2
 
3.2%
M 2
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9185
61.6%
ASCII 5735
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1881
32.8%
1 575
 
10.0%
- 484
 
8.4%
3 439
 
7.7%
2 401
 
7.0%
4 381
 
6.6%
) 274
 
4.8%
( 274
 
4.8%
, 248
 
4.3%
6 171
 
3.0%
Other values (14) 607
 
10.6%
Hangul
ValueCountFrequency (%)
구 1151
12.5%
입 1128
12.3%
출 1115
12.1%
번 1115
12.1%
방 624
 
6.8%
면 609
 
6.6%
대 379
 
4.1%
실 331
 
3.6%
합 312
 
3.4%
로 191
 
2.1%
Other values (166) 2230
24.3%

Interactions

2023-12-13T04:03:51.405153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:51.203809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:51.510147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:03:51.299165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:03:55.680698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선호기운행구간
연번1.0000.9110.3260.553
호선0.9111.0000.3030.519
호기0.3260.3031.0000.554
운행구간0.5530.5190.5541.000
2023-12-13T04:03:55.787677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호기호선
연번1.0000.1330.724
호기0.1331.0000.142
호선0.7240.1421.000

Missing values

2023-12-13T04:03:51.628749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:03:51.739696image/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

연번호선역명장비종류호기승강기번호운행구간설치위치
011서울역(1)E/S11800-448B2-B1연결통로(4호선)
121서울역(1)E/S21806-600B1-B2남영 방면2-3
231서울역(1)E/S31806-599B2-B1시청 방면9-3
341서울역(1)E/S41810-816B1-1F4번 출입구
451서울역(1)E/S51810-8171F-B14번 출입구
561시청(1)E/S11808-1191F-B15번 출입구
671시청(1)E/S21808-120B1-1F5번 출입구
781시청(1)E/S31809-239B1-1F1번 출입구
891종각E/S11810-7301F-B11번 출입구
9101종각E/S21810-729B1-1F1번 출입구
연번호선역명장비종류호기승강기번호운행구간설치위치
182518268단대오거리E/S43805-602B2-B1대합실
182618278단대오거리E/S53811-916B1-1F대합실
182718288단대오거리E/S63811-9171F-B11번 출입구
182818298모란(8)E/S13802-183B1-B21번 출입구
182918308모란(8)E/S23802-184B2-B1대합실
183018318산성E/S53802-097B3-B2대합실
183118328산성E/S63802-098B2-B33번 출입구
183218338산성E/S73802-099B3-B23번 출입구
183318348산성E/S83802-100B2-B3대합실
183418358산성E/S93805-449B1-B2대합실