Overview

Dataset statistics

Number of variables15
Number of observations729
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory89.8 KiB
Average record size in memory126.2 B

Variable types

Numeric2
Text1
Categorical11
DateTime1

Dataset

Description대전교통공사에서 관리하는 엘리베이터 법정 검사 결과(2022년 까지 엘리베이터 법정 검사)(22개역 엘리베이터 점검 결과)
Author대전교통공사
URLhttps://www.data.go.kr/data/15056489/fileData.do

Alerts

구분 has constant value ""Constant
검사결과 has constant value ""Constant
제조사 is highly overall correlated with 역사명 and 3 other fieldsHigh correlation
형식 is highly overall correlated with 역사명 and 1 other fieldsHigh correlation
역사명 is highly overall correlated with 용도 and 6 other fieldsHigh correlation
위치 is highly overall correlated with 호기 and 7 other fieldsHigh correlation
운행속도(m_min) is highly overall correlated with 역사명 and 2 other fieldsHigh correlation
호기 is highly overall correlated with 위치High correlation
용도 is highly overall correlated with 역사명 and 1 other fieldsHigh correlation
기준층 is highly overall correlated with 역사명 and 1 other fieldsHigh correlation
검사분기 is highly overall correlated with 역사명 and 2 other fieldsHigh correlation
용도 is highly imbalanced (82.6%)Imbalance
형식 is highly imbalanced (90.4%)Imbalance
기준층 is highly imbalanced (61.1%)Imbalance
운행속도(m_min) is highly imbalanced (52.3%)Imbalance
수시(검사분기) is highly imbalanced (92.1%)Imbalance

Reproduction

Analysis started2023-12-12 20:51:24.283598
Analysis finished2023-12-12 20:51:26.454604
Duration2.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정연도
Real number (ℝ)

Distinct9
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018
Minimum2014
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2023-12-13T05:51:26.510614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12016
median2018
Q32020
95-th percentile2022
Maximum2022
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.5837616
Coefficient of variation (CV)0.0012803576
Kurtosis-1.2302022
Mean2018
Median Absolute Deviation (MAD)2
Skewness0
Sum1471122
Variance6.6758242
MonotonicityIncreasing
2023-12-13T05:51:26.636291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2014 81
11.1%
2015 81
11.1%
2016 81
11.1%
2017 81
11.1%
2018 81
11.1%
2019 81
11.1%
2020 81
11.1%
2021 81
11.1%
2022 81
11.1%
ValueCountFrequency (%)
2014 81
11.1%
2015 81
11.1%
2016 81
11.1%
2017 81
11.1%
2018 81
11.1%
2019 81
11.1%
2020 81
11.1%
2021 81
11.1%
2022 81
11.1%
ValueCountFrequency (%)
2022 81
11.1%
2021 81
11.1%
2020 81
11.1%
2019 81
11.1%
2018 81
11.1%
2017 81
11.1%
2016 81
11.1%
2015 81
11.1%
2014 81
11.1%

고유번호
Text

Distinct81
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-13T05:51:26.926620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters7290
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

Unique0 ?
Unique (%)0.0%

Sample

1st row 5003_501
2nd row 5003_502
3rd row 5003_503
4th row 5003_504
5th row 5003_505
ValueCountFrequency (%)
5003_501 9
 
1.2%
5003_542 9
 
1.2%
5003_560 9
 
1.2%
5003_559 9
 
1.2%
5003_558 9
 
1.2%
5003_557 9
 
1.2%
5003_556 9
 
1.2%
5003_555 9
 
1.2%
5003_554 9
 
1.2%
5003_553 9
 
1.2%
Other values (71) 639
87.7%
2023-12-13T05:51:27.356029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1620
22.2%
0 1611
22.1%
1458
20.0%
3 891
12.2%
_ 729
10.0%
1 171
 
2.3%
2 162
 
2.2%
4 162
 
2.2%
6 162
 
2.2%
7 162
 
2.2%
Other values (2) 162
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5103
70.0%
Space Separator 1458
 
20.0%
Connector Punctuation 729
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1620
31.7%
0 1611
31.6%
3 891
17.5%
1 171
 
3.4%
2 162
 
3.2%
4 162
 
3.2%
6 162
 
3.2%
7 162
 
3.2%
8 90
 
1.8%
9 72
 
1.4%
Space Separator
ValueCountFrequency (%)
1458
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 729
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7290
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1620
22.2%
0 1611
22.1%
1458
20.0%
3 891
12.2%
_ 729
10.0%
1 171
 
2.3%
2 162
 
2.2%
4 162
 
2.2%
6 162
 
2.2%
7 162
 
2.2%
Other values (2) 162
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1620
22.2%
0 1611
22.1%
1458
20.0%
3 891
12.2%
_ 729
10.0%
1 171
 
2.3%
2 162
 
2.2%
4 162
 
2.2%
6 162
 
2.2%
7 162
 
2.2%
Other values (2) 162
 
2.2%

역사명
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
월드컵
 
48
갈마
 
40
현충원
 
36
유성온천
 
36
노은
 
32
Other values (40)
537 

Length

Max length10
Median length2
Mean length2.8820302
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row판암
2nd row판암
3rd row판암
4th row판암
5th row신흥

Common Values

ValueCountFrequency (%)
월드컵 48
 
6.6%
갈마 40
 
5.5%
현충원 36
 
4.9%
유성온천 36
 
4.9%
노은 32
 
4.4%
갑천 32
 
4.4%
월평 32
 
4.4%
정부청사 32
 
4.4%
판암 32
 
4.4%
본사 27
 
3.7%
Other values (35) 382
52.4%

Length

2023-12-13T05:51:27.512644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
월드컵 54
 
7.4%
갈마 45
 
6.2%
현충원 36
 
4.9%
유성온천 36
 
4.9%
노은 36
 
4.9%
갑천 36
 
4.9%
월평 36
 
4.9%
정부청사 36
 
4.9%
판암 36
 
4.9%
중앙로 27
 
3.7%
Other values (15) 351
48.1%

호기
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2962963
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2023-12-13T05:51:27.653435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile4
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.1602387
Coefficient of variation (CV)0.50526524
Kurtosis0.060864064
Mean2.2962963
Median Absolute Deviation (MAD)1
Skewness0.69134483
Sum1674
Variance1.3461538
MonotonicityNot monotonic
2023-12-13T05:51:27.771063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 225
30.9%
2 207
28.4%
3 189
25.9%
4 81
 
11.1%
5 18
 
2.5%
6 9
 
1.2%
ValueCountFrequency (%)
1 225
30.9%
2 207
28.4%
3 189
25.9%
4 81
 
11.1%
5 18
 
2.5%
6 9
 
1.2%
ValueCountFrequency (%)
6 9
 
1.2%
5 18
 
2.5%
4 81
 
11.1%
3 189
25.9%
2 207
28.4%
1 225
30.9%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
EL
729 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
EL 729
100.0%

Length

2023-12-13T05:51:27.889710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:28.010695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
el 729
100.0%

용도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
장애인용
710 
승객용
 
19

Length

Max length4
Median length4
Mean length3.9739369
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장애인용 710
97.4%
승객용 19
 
2.6%

Length

2023-12-13T05:51:28.143903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:28.274496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장애인용 710
97.4%
승객용 19
 
2.6%

위치
Categorical

HIGH CORRELATION 

Distinct39
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
1_2번출구측
89 
승강장 상선 시점
72 
3_4번출구측
72 
승강장 하선 종점
72 
3번출구측
 
36
Other values (34)
388 

Length

Max length12
Median length11
Mean length7.4938272
Min length3

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row1_2번출구측
2nd row3_4번출구측
3rd row상선 승강장 중앙
4th row하선 승강장 중앙
5th row2번출구측

Common Values

ValueCountFrequency (%)
1_2번출구측 89
 
12.2%
승강장 상선 시점 72
 
9.9%
3_4번출구측 72
 
9.9%
승강장 하선 종점 72
 
9.9%
3번출구측 36
 
4.9%
상선 승강장 중앙 27
 
3.7%
2번출구측 27
 
3.7%
승강장 상선 종점 18
 
2.5%
하선 승강장 중앙 18
 
2.5%
승강장 하선 시점 18
 
2.5%
Other values (29) 280
38.4%

Length

2023-12-13T05:51:28.445719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
승강장 261
18.5%
상선 153
10.8%
하선 144
10.2%
종점 117
8.3%
시점 108
7.6%
중앙 108
7.6%
1_2번출구측 89
 
6.3%
대합실 81
 
5.7%
3_4번출구측 72
 
5.1%
3번출구측 36
 
2.5%
Other values (23) 244
17.3%

형식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
VVVF
720 
유압식
 
9

Length

Max length4
Median length4
Mean length3.9876543
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
VVVF 720
98.8%
유압식 9
 
1.2%

Length

2023-12-13T05:51:28.576054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:28.709391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
vvvf 720
98.8%
유압식 9
 
1.2%

기준층
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2
612 
3
63 
4
 
27
6
 
18
5
 
9

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 612
84.0%
3 63
 
8.6%
4 27
 
3.7%
6 18
 
2.5%
5 9
 
1.2%

Length

2023-12-13T05:51:28.859592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:28.994470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 612
84.0%
3 63
 
8.6%
4 27
 
3.7%
6 18
 
2.5%
5 9
 
1.2%

운행속도(m_min)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
45
594 
60
126 
30
 
9

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row45
2nd row45
3rd row45
4th row45
5th row45

Common Values

ValueCountFrequency (%)
45 594
81.5%
60 126
 
17.3%
30 9
 
1.2%

Length

2023-12-13T05:51:29.140956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:29.298343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
45 594
81.5%
60 126
 
17.3%
30 9
 
1.2%

검사(만료일)
Date

Distinct90
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
Minimum2014-01-10 00:00:00
Maximum2022-10-27 00:00:00
2023-12-13T05:51:29.445922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:29.623142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

검사분기
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
4
252 
1
239 
3
124 
2
114 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row3
4th row3
5th row4

Common Values

ValueCountFrequency (%)
4 252
34.6%
1 239
32.8%
3 124
17.0%
2 114
15.6%

Length

2023-12-13T05:51:29.809848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:29.947899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 252
34.6%
1 239
32.8%
3 124
17.0%
2 114
15.6%

수시(검사분기)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
0
718 
3
 
8
2
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 718
98.5%
3 8
 
1.1%
2 3
 
0.4%

Length

2023-12-13T05:51:30.076180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:30.219657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 718
98.5%
3 8
 
1.1%
2 3
 
0.4%

제조사
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
지암
441 
제일
81 
후지테크
81 
한독
81 
현대
45 

Length

Max length4
Median length2
Mean length2.2222222
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지암 441
60.5%
제일 81
 
11.1%
후지테크 81
 
11.1%
한독 81
 
11.1%
현대 45
 
6.2%

Length

2023-12-13T05:51:30.356058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:30.495418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지암 441
60.5%
제일 81
 
11.1%
후지테크 81
 
11.1%
한독 81
 
11.1%
현대 45
 
6.2%

검사결과
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
합격
729 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
합격 729
100.0%

Length

2023-12-13T05:51:30.639516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:51:30.770364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
합격 729
100.0%

Interactions

2023-12-13T05:51:25.883209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:25.635660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:26.009858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:51:25.774153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:51:30.845883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정연도고유번호역사명호기용도위치형식기준층운행속도(m_min)검사(만료일)검사분기수시(검사분기)제조사
측정연도1.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.3320.000
고유번호0.0001.0000.9921.0000.7090.9991.0000.9991.0000.0000.9950.0001.000
역사명0.0000.9921.0000.4870.8470.9620.6280.9560.9480.9270.9500.0001.000
호기0.0001.0000.4871.0000.1570.9630.2190.2300.3940.0000.3250.0000.194
용도0.0000.7090.8470.1571.0000.7750.0000.1760.0720.8210.3120.0000.226
위치0.0000.9990.9620.9630.7751.0001.0000.9840.9980.8500.8980.2620.949
형식0.0001.0000.6280.2190.0001.0001.0000.0000.0060.8490.0130.0570.042
기준층0.0000.9990.9560.2300.1760.9840.0001.0000.5160.8440.2810.0000.842
운행속도(m_min)0.0001.0000.9480.3940.0720.9980.0060.5161.0000.6390.2060.1890.718
검사(만료일)1.0000.0000.9270.0000.8210.8500.8490.8440.6391.0001.0000.8930.907
검사분기0.0000.9950.9500.3250.3120.8980.0130.2810.2061.0001.0000.1950.648
수시(검사분기)0.3320.0000.0000.0000.0000.2620.0570.0000.1890.8930.1951.0000.033
제조사0.0001.0001.0000.1940.2260.9490.0420.8420.7180.9070.6480.0331.000
2023-12-13T05:51:31.021182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준층용도제조사형식검사분기수시(검사분기)역사명위치운행속도(m_min)
기준층1.0000.2150.4760.0000.2320.0000.7370.8880.453
용도0.2151.0000.2760.0000.2080.0000.7230.6560.120
제조사0.4760.2761.0000.0520.5780.0240.9500.7710.706
형식0.0000.0000.0521.0000.0080.0940.5150.9740.010
검사분기0.2320.2080.5780.0081.0000.1850.7800.6800.195
수시(검사분기)0.0000.0000.0240.0940.1851.0000.0000.1220.059
역사명0.7370.7230.9500.5150.7800.0001.0000.5250.755
위치0.8880.6560.7710.9740.6800.1220.5251.0000.922
운행속도(m_min)0.4530.1200.7060.0100.1950.0590.7550.9221.000
2023-12-13T05:51:31.183722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정연도호기역사명용도위치형식기준층운행속도(m_min)검사분기수시(검사분기)제조사
측정연도1.0000.0000.2120.2200.0000.0000.0000.0000.0000.2250.000
호기0.0001.0000.2240.1130.7950.1570.1570.1770.2140.0000.132
역사명0.2120.2241.0000.7230.5250.5150.7370.7550.7800.0000.950
용도0.2200.1130.7231.0000.6560.0000.2150.1200.2080.0000.276
위치0.0000.7950.5250.6561.0000.9740.8880.9220.6800.1220.771
형식0.0000.1570.5150.0000.9741.0000.0000.0100.0080.0940.052
기준층0.0000.1570.7370.2150.8880.0001.0000.4530.2320.0000.476
운행속도(m_min)0.0000.1770.7550.1200.9220.0100.4531.0000.1950.0590.706
검사분기0.0000.2140.7800.2080.6800.0080.2320.1951.0000.1850.578
수시(검사분기)0.2250.0000.0000.0000.1220.0940.0000.0590.1851.0000.024
제조사0.0000.1320.9500.2760.7710.0520.4760.7060.5780.0241.000

Missing values

2023-12-13T05:51:26.148210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:51:26.376877image/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

측정연도고유번호역사명호기구분용도위치형식기준층운행속도(m_min)검사(만료일)검사분기수시(검사분기)제조사검사결과
020145003_501판암1EL장애인용1_2번출구측VVVF2452014-10-0140지암합격
120145003_502판암2EL장애인용3_4번출구측VVVF2452014-10-0140지암합격
220145003_503판암3EL장애인용상선 승강장 중앙VVVF2452014-07-0130지암합격
320145003_504판암4EL장애인용하선 승강장 중앙VVVF2452014-07-0130지암합격
420145003_505신흥1EL장애인용2번출구측VVVF2452014-10-0140지암합격
520145003_506신흥2EL장애인용상선 승강장 중앙VVVF2452014-07-0130지암합격
620145003_507신흥3EL장애인용하선 승강장 중앙VVVF2452014-07-0130지암합격
720145003_508대동1EL장애인용대합실 상선 종점VVVF2302014-10-0140지암합격
820145003_509대동2EL장애인용대합실 하선 종점유압식2452014-10-0140지암합격
920145003_510대동3EL장애인용승강장 시점VVVF3452014-07-0130지암합격
측정연도고유번호역사명호기구분용도위치형식기준층운행속도(m_min)검사(만료일)검사분기수시(검사분기)제조사검사결과
71920225003_556구암2EL장애인용승강장 상선 중앙VVVF2452022-10-0140지암합격
72020225003_557구암3EL장애인용승강장 하선 중앙VVVF2452022-10-0140지암합격
72120225003_566월드컵5EL장애인용승강장 상선 종점VVVF2452022-10-0140지암합격
72220225003_567월드컵6EL장애인용승강장 하선 시점VVVF2452022-10-0140지암합격
72320225003_570노은3EL장애인용승강장 상선 시점VVVF2452022-10-0140지암합격
72420225003_571노은4EL장애인용승강장 하선 종점VVVF2452022-10-0140지암합격
72520225003_573지족2EL장애인용대합실 하선 중앙VVVF2452022-10-0140지암합격
72620225003_575반석2EL장애인용승강장 상선 시점VVVF2452022-10-0140지암합격
72720225003_576반석3EL장애인용승강장 하선 종점VVVF2452022-10-0140지암합격
72820225003_580판암기지1EL장애인용종합관리동VVVF6602022-10-2740후지테크합격