Overview

Dataset statistics

Number of variables7
Number of observations1012
Missing cells2024
Missing cells (%)28.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory57.4 KiB
Average record size in memory58.1 B

Variable types

DateTime1
Text3
Categorical1
Unsupported2

Dataset

Description○ 제공내용 : 전국에 운행 중인 승강기의 중대사고 및 중대고장 이력 등을 제공하여 국민이 안심하고 승강기를 이용할 수 있도록 하는 서비스
Author행정안전부
URLhttps://www.data.go.kr/data/3033839/fileData.do

Alerts

사고구분 has constant value ""Constant
Unnamed: 5 has 1012 (100.0%) missing valuesMissing
Unnamed: 6 has 1012 (100.0%) missing valuesMissing
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 18:24:24.324946
Analysis finished2023-12-12 18:24:24.888980
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

발생일시
Date

Distinct1011
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
Minimum2007-01-01 15:20:00
Maximum2017-09-19 11:40:00
2023-12-13T03:24:24.948364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:24:25.068402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

건물명
Text

Distinct795
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2023-12-13T03:24:25.352700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length9.951581
Min length3

Characters and Unicode

Total characters10071
Distinct characters422
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique674 ?
Unique (%)66.6%

Sample

1st row심가면옥
2nd row호포역사
3rd row황실관광호텔
4th row삼화빌딩
5th row중계그린아파트
ValueCountFrequency (%)
롯데마트 82
 
4.0%
이마트 80
 
3.9%
한국철도공사 74
 
3.6%
홈플러스 74
 
3.6%
부산교통공사 47
 
2.3%
대구도시철도공사 46
 
2.3%
서울 44
 
2.2%
신세계이마트 36
 
1.8%
경기 31
 
1.5%
도시철도공사 30
 
1.5%
Other values (882) 1499
73.4%
2023-12-13T03:24:25.787001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1031
 
10.2%
트 340
 
3.4%
점 339
 
3.4%
도 318
 
3.2%
역 311
 
3.1%
사 298
 
3.0%
공 267
 
2.7%
마 247
 
2.5%
구 221
 
2.2%
철 206
 
2.0%
Other values (412) 6493
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8799
87.4%
Space Separator 1031
 
10.2%
Decimal Number 136
 
1.4%
Uppercase Letter 38
 
0.4%
Other Symbol 27
 
0.3%
Close Punctuation 18
 
0.2%
Open Punctuation 18
 
0.2%
Lowercase Letter 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 340
 
3.9%
점 339
 
3.9%
도 318
 
3.6%
역 311
 
3.5%
사 298
 
3.4%
공 267
 
3.0%
마 247
 
2.8%
구 221
 
2.5%
철 206
 
2.3%
대 199
 
2.3%
Other values (380) 6053
68.8%
Uppercase Letter
ValueCountFrequency (%)
K 9
23.7%
S 9
23.7%
L 3
 
7.9%
H 2
 
5.3%
J 2
 
5.3%
M 2
 
5.3%
T 2
 
5.3%
I 2
 
5.3%
A 1
 
2.6%
C 1
 
2.6%
Other values (5) 5
13.2%
Decimal Number
ValueCountFrequency (%)
2 35
25.7%
5 17
12.5%
1 17
12.5%
7 16
11.8%
3 16
11.8%
6 15
11.0%
4 12
 
8.8%
9 3
 
2.2%
8 3
 
2.2%
0 2
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
e 2
66.7%
a 1
33.3%
Space Separator
ValueCountFrequency (%)
1031
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8826
87.6%
Common 1204
 
12.0%
Latin 41
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 340
 
3.9%
점 339
 
3.8%
도 318
 
3.6%
역 311
 
3.5%
사 298
 
3.4%
공 267
 
3.0%
마 247
 
2.8%
구 221
 
2.5%
철 206
 
2.3%
대 199
 
2.3%
Other values (381) 6080
68.9%
Latin
ValueCountFrequency (%)
K 9
22.0%
S 9
22.0%
L 3
 
7.3%
H 2
 
4.9%
e 2
 
4.9%
J 2
 
4.9%
M 2
 
4.9%
T 2
 
4.9%
I 2
 
4.9%
A 1
 
2.4%
Other values (7) 7
17.1%
Common
ValueCountFrequency (%)
1031
85.6%
2 35
 
2.9%
) 18
 
1.5%
( 18
 
1.5%
5 17
 
1.4%
1 17
 
1.4%
7 16
 
1.3%
3 16
 
1.3%
6 15
 
1.2%
4 12
 
1.0%
Other values (4) 9
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8799
87.4%
ASCII 1245
 
12.4%
None 27
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1031
82.8%
2 35
 
2.8%
) 18
 
1.4%
( 18
 
1.4%
5 17
 
1.4%
1 17
 
1.4%
7 16
 
1.3%
3 16
 
1.3%
6 15
 
1.2%
4 12
 
1.0%
Other values (21) 50
 
4.0%
Hangul
ValueCountFrequency (%)
트 340
 
3.9%
점 339
 
3.9%
도 318
 
3.6%
역 311
 
3.5%
사 298
 
3.4%
공 267
 
3.0%
마 247
 
2.8%
구 221
 
2.5%
철 206
 
2.3%
대 199
 
2.3%
Other values (380) 6053
68.8%
None
ValueCountFrequency (%)
㈜ 27
100.0%

승강기번호
Text

Distinct896
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2023-12-13T03:24:26.037886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.8972332
Min length2

Characters and Unicode

Total characters9004
Distinct characters13
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

Unique817 ?
Unique (%)80.7%

Sample

1st row122-01919
2nd row626-00758
3rd row701-00310
4th row100-01445
5th row139-01810
ValueCountFrequency (%)
461-01294 5
 
0.5%
702-01383 4
 
0.4%
614-03380 4
 
0.4%
617-02137 4
 
0.4%
614-02506 4
 
0.4%
412-01742 4
 
0.4%
330-03178 4
 
0.4%
무적 3
 
0.3%
464-01650 3
 
0.3%
750-00462 3
 
0.3%
Other values (886) 974
96.2%
2023-12-13T03:24:26.465112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2008
22.3%
1 1121
12.5%
- 1009
11.2%
4 812
9.0%
3 775
 
8.6%
2 759
 
8.4%
6 692
 
7.7%
5 582
 
6.5%
7 536
 
6.0%
8 377
 
4.2%
Other values (3) 333
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7989
88.7%
Dash Punctuation 1009
 
11.2%
Other Letter 6
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2008
25.1%
1 1121
14.0%
4 812
10.2%
3 775
 
9.7%
2 759
 
9.5%
6 692
 
8.7%
5 582
 
7.3%
7 536
 
6.7%
8 377
 
4.7%
9 327
 
4.1%
Other Letter
ValueCountFrequency (%)
무 3
50.0%
적 3
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1009
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8998
99.9%
Hangul 6
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2008
22.3%
1 1121
12.5%
- 1009
11.2%
4 812
9.0%
3 775
 
8.6%
2 759
 
8.4%
6 692
 
7.7%
5 582
 
6.5%
7 536
 
6.0%
8 377
 
4.2%
Hangul
ValueCountFrequency (%)
무 3
50.0%
적 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8998
99.9%
Hangul 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2008
22.3%
1 1121
12.5%
- 1009
11.2%
4 812
9.0%
3 775
 
8.6%
2 759
 
8.4%
6 692
 
7.7%
5 582
 
6.5%
7 536
 
6.0%
8 377
 
4.2%
Hangul
ValueCountFrequency (%)
무 3
50.0%
적 3
50.0%

주소
Text

Distinct782
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2023-12-13T03:24:26.789079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27
Mean length16.537549
Min length11

Characters and Unicode

Total characters16736
Distinct characters293
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

Unique643 ?
Unique (%)63.5%

Sample

1st row서울 은평구 응암동 109-2
2nd row경남 양산시 동면 가산리 546
3rd row대구 동구 신천2동 45-2
4th row서울 중구 소공동 21-1
5th row서울 노원구 중계2동 503
ValueCountFrequency (%)
서울 231
 
5.4%
경기 210
 
4.9%
부산 138
 
3.2%
대구 112
 
2.6%
중구 50
 
1.2%
인천 45
 
1.0%
경남 41
 
1.0%
충남 39
 
0.9%
북구 38
 
0.9%
대전 34
 
0.8%
Other values (1551) 3359
78.2%
2023-12-13T03:24:27.241462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3285
 
19.6%
구 931
 
5.6%
1 871
 
5.2%
동 863
 
5.2%
2 491
 
2.9%
- 482
 
2.9%
3 428
 
2.6%
시 390
 
2.3%
서 387
 
2.3%
산 379
 
2.3%
Other values (283) 8229
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9066
54.2%
Decimal Number 3872
23.1%
Space Separator 3285
 
19.6%
Dash Punctuation 482
 
2.9%
Open Punctuation 14
 
0.1%
Close Punctuation 14
 
0.1%
Uppercase Letter 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 931
 
10.3%
동 863
 
9.5%
시 390
 
4.3%
서 387
 
4.3%
산 379
 
4.2%
경 300
 
3.3%
부 256
 
2.8%
울 250
 
2.8%
대 248
 
2.7%
기 237
 
2.6%
Other values (266) 4825
53.2%
Decimal Number
ValueCountFrequency (%)
1 871
22.5%
2 491
12.7%
3 428
11.1%
5 348
 
9.0%
4 342
 
8.8%
0 315
 
8.1%
6 311
 
8.0%
8 260
 
6.7%
9 253
 
6.5%
7 253
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
3285
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 482
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9066
54.2%
Common 7668
45.8%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 931
 
10.3%
동 863
 
9.5%
시 390
 
4.3%
서 387
 
4.3%
산 379
 
4.2%
경 300
 
3.3%
부 256
 
2.8%
울 250
 
2.8%
대 248
 
2.7%
기 237
 
2.6%
Other values (266) 4825
53.2%
Common
ValueCountFrequency (%)
3285
42.8%
1 871
 
11.4%
2 491
 
6.4%
- 482
 
6.3%
3 428
 
5.6%
5 348
 
4.5%
4 342
 
4.5%
0 315
 
4.1%
6 311
 
4.1%
8 260
 
3.4%
Other values (5) 535
 
7.0%
Latin
ValueCountFrequency (%)
B 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9066
54.2%
ASCII 7670
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3285
42.8%
1 871
 
11.4%
2 491
 
6.4%
- 482
 
6.3%
3 428
 
5.6%
5 348
 
4.5%
4 342
 
4.5%
0 315
 
4.1%
6 311
 
4.1%
8 260
 
3.4%
Other values (7) 537
 
7.0%
Hangul
ValueCountFrequency (%)
구 931
 
10.3%
동 863
 
9.5%
시 390
 
4.3%
서 387
 
4.3%
산 379
 
4.2%
경 300
 
3.3%
부 256
 
2.8%
울 250
 
2.8%
대 248
 
2.7%
기 237
 
2.6%
Other values (266) 4825
53.2%

사고구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
중대사고
1012 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중대사고 1012
100.0%

Length

2023-12-13T03:24:27.361859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:24:27.440538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중대사고 1012
100.0%

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1012
Missing (%)100.0%
Memory size9.0 KiB

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1012
Missing (%)100.0%
Memory size9.0 KiB

Missing values

2023-12-13T03:24:24.755033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:24:24.851290image/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

발생일시건물명승강기번호주소사고구분Unnamed: 5Unnamed: 6
02007-01-01 15:20심가면옥122-01919서울 은평구 응암동 109-2중대사고<NA><NA>
12007-01-03 13:40호포역사626-00758경남 양산시 동면 가산리 546중대사고<NA><NA>
22007-01-06 22:15황실관광호텔701-00310대구 동구 신천2동 45-2중대사고<NA><NA>
32007-01-11 22:00삼화빌딩100-01445서울 중구 소공동 21-1중대사고<NA><NA>
42007-01-15 13:00중계그린아파트139-01810서울 노원구 중계2동 503중대사고<NA><NA>
52007-01-15 15:30롯데갤러리움아파트614-03161부산 부산진구 양정동 273-1중대사고<NA><NA>
62007-01-20 09:30의정부성모병원480-02846경기 의정부시 금오동 65-1중대사고<NA><NA>
72007-01-26 16:30부산교통공사 3호선 배산역사611-01586부산 연제구 연산3동 1802중대사고<NA><NA>
82007-01-30 11:38부산교통공사 남산정역616-02186부산 북구 덕천동 462중대사고<NA><NA>
92007-01-30 18:30성민장모텔402-00249인천 남구 주안1동 271-38중대사고<NA><NA>
발생일시건물명승강기번호주소사고구분Unnamed: 5Unnamed: 6
10022017-07-10 16:30수원 홈플러스 서수원점441-4098경기도 수원시 권선구 수인로 291 (구운동)중대사고<NA><NA>
10032017-08-02 13:17인천 송도더샵퍼스트월드206-2400인천시 연수구 해돋이로 107중대사고<NA><NA>
10042017-08-10 13:28경기 화성남양뉴타운LH9단지445-9300경기도 화성시 남양읍 남양중앙로 316중대사고<NA><NA>
10052017-08-23 18:30부산 세신인더스트리㈜604-3163부산광역시 사하구 다산로225번길 20 (장림동)중대사고<NA><NA>
10062017-08-26 22:00신도23차아파트480-668경기도 의정부시 경의로132번길 78중대사고<NA><NA>
10072017-07-11 10:00부산 아이온시티614-3023부산광역시 부산진구 서면로 74중대사고<NA><NA>
10082017-07-26 13:35서울 대청프라자135-5694서울특별시 강남구 개포로109길 34중대사고<NA><NA>
10092017-09-19 11:40경기 한국철도공사 중앙선 덕소역472-2989경기도 남양주시 와부읍 덕소로 56중대사고<NA><NA>
10102017-06-20 09:00서울 성바오로병원130-824서울특별시 동대문구 왕산로 180 (전농동)중대사고<NA><NA>
10112017-08-21 15:38이마트 목동점158-3945서울 양천구 오목로 299중대사고<NA><NA>