Overview

Dataset statistics

Number of variables13
Number of observations1733
Missing cells120
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory176.1 KiB
Average record size in memory104.1 B

Variable types

Text6
DateTime1
Categorical6

Dataset

Description승강기안전 인증은 승강기 사용자가 승강기를 안전하게 사용할 수 있도록 하기 위하여, 안전인증기관이 승강기를 시험하고 제조·검사설비 등 생산체제를 평가함으로써 승강기의 안전성을 확보하기 위한 인증제도입니다.
Author한국승강기안전공단
URLhttps://www.data.go.kr/data/15039131/fileData.do

Alerts

모델/개별 has constant value ""Constant
파생모델명 is highly overall correlated with 적용안전기준 and 3 other fieldsHigh correlation
적용안전기준 is highly overall correlated with 파생모델명 and 2 other fieldsHigh correlation
제조국가 is highly overall correlated with 적용안전기준 and 2 other fieldsHigh correlation
인증품목명 is highly overall correlated with 적용안전기준 and 2 other fieldsHigh correlation
인증서상태 is highly overall correlated with 파생모델명High correlation
적용안전기준 is highly imbalanced (62.3%)Imbalance
인증서상태 is highly imbalanced (53.3%)Imbalance
파생모델명 is highly imbalanced (85.0%)Imbalance
인증품목명 is highly imbalanced (85.0%)Imbalance
제조국가 is highly imbalanced (69.1%)Imbalance
인증업체코드 has 120 (6.9%) missing valuesMissing

Reproduction

Analysis started2024-04-06 08:26:13.612486
Analysis finished2024-04-06 08:26:16.545030
Duration2.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

안전인증번호
Text

Distinct297
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2024-04-06T17:26:16.829616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length16.001154
Min length16

Characters and Unicode

Total characters27730
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)2.2%

Sample

1st rowABB73-R001-19001
2nd rowABB73-R001-19002
3rd rowABA71-K001-19005
4th rowABA71-K001-19001
5th rowABA71-K001-19002
ValueCountFrequency (%)
aba71-h009-20001 18
 
1.0%
aba71-k001-19010 17
 
1.0%
aba71-h005-20003 16
 
0.9%
aba71-h011-20001 15
 
0.9%
aba71-h003-19001 15
 
0.9%
aba71-h008-20001 14
 
0.8%
aba71-n001-20002 14
 
0.8%
aba71-h001-19003 14
 
0.8%
aba71-h015-20001 14
 
0.8%
aba71-h011-21001 14
 
0.8%
Other values (286) 1582
91.3%
2024-04-06T17:26:17.743396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7359
26.5%
1 4251
15.3%
- 3466
12.5%
A 3464
12.5%
2 2118
 
7.6%
7 1858
 
6.7%
B 1795
 
6.5%
3 649
 
2.3%
H 567
 
2.0%
9 496
 
1.8%
Other values (19) 1707
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17330
62.5%
Uppercase Letter 6931
 
25.0%
Dash Punctuation 3466
 
12.5%
Space Separator 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 3464
50.0%
B 1795
25.9%
H 567
 
8.2%
K 279
 
4.0%
D 264
 
3.8%
J 179
 
2.6%
M 107
 
1.5%
R 96
 
1.4%
N 63
 
0.9%
O 44
 
0.6%
Other values (6) 73
 
1.1%
Decimal Number
ValueCountFrequency (%)
0 7359
42.5%
1 4251
24.5%
2 2118
 
12.2%
7 1858
 
10.7%
3 649
 
3.7%
9 496
 
2.9%
5 198
 
1.1%
4 190
 
1.1%
6 119
 
0.7%
8 92
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 3466
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20798
75.0%
Latin 6932
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 3464
50.0%
B 1795
25.9%
H 567
 
8.2%
K 279
 
4.0%
D 264
 
3.8%
J 179
 
2.6%
M 107
 
1.5%
R 96
 
1.4%
N 63
 
0.9%
O 44
 
0.6%
Other values (7) 74
 
1.1%
Common
ValueCountFrequency (%)
0 7359
35.4%
1 4251
20.4%
- 3466
16.7%
2 2118
 
10.2%
7 1858
 
8.9%
3 649
 
3.1%
9 496
 
2.4%
5 198
 
1.0%
4 190
 
0.9%
6 119
 
0.6%
Other values (2) 94
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27730
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7359
26.5%
1 4251
15.3%
- 3466
12.5%
A 3464
12.5%
2 2118
 
7.6%
7 1858
 
6.7%
B 1795
 
6.5%
3 649
 
2.3%
H 567
 
2.0%
9 496
 
1.8%
Other values (19) 1707
 
6.2%

인증업체코드
Text

MISSING 

Distinct80
Distinct (%)5.0%
Missing120
Missing (%)6.9%
Memory size13.7 KiB
2024-04-06T17:26:18.331560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.9900806
Min length1

Characters and Unicode

Total characters14501
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.6%

Sample

1st row919971182
2nd row919971182
3rd row919920034
4th row919920034
5th row919920034
ValueCountFrequency (%)
919920035 267
 
16.6%
919920034 235
 
14.6%
919920075 116
 
7.2%
920020007 97
 
6.0%
919920056 48
 
3.0%
920040006 37
 
2.3%
920100013 33
 
2.0%
920040021 32
 
2.0%
920130015 31
 
1.9%
920020121 28
 
1.7%
Other values (70) 689
42.7%
2024-04-06T17:26:19.126802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4352
30.0%
9 3632
25.0%
2 1905
13.1%
1 1797
12.4%
3 752
 
5.2%
5 692
 
4.8%
4 501
 
3.5%
7 405
 
2.8%
6 294
 
2.0%
8 169
 
1.2%
Other values (2) 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14499
> 99.9%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4352
30.0%
9 3632
25.1%
2 1905
13.1%
1 1797
12.4%
3 752
 
5.2%
5 692
 
4.8%
4 501
 
3.5%
7 405
 
2.8%
6 294
 
2.0%
8 169
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
Q 1
50.0%
H 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14499
> 99.9%
Latin 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4352
30.0%
9 3632
25.1%
2 1905
13.1%
1 1797
12.4%
3 752
 
5.2%
5 692
 
4.8%
4 501
 
3.5%
7 405
 
2.8%
6 294
 
2.0%
8 169
 
1.2%
Latin
ValueCountFrequency (%)
Q 1
50.0%
H 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14501
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4352
30.0%
9 3632
25.0%
2 1905
13.1%
1 1797
12.4%
3 752
 
5.2%
5 692
 
4.8%
4 501
 
3.5%
7 405
 
2.8%
6 294
 
2.0%
8 169
 
1.2%
Other values (2) 2
 
< 0.1%

업체명
Text

Distinct85
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2024-04-06T17:26:19.580702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.8695903
Min length3

Characters and Unicode

Total characters13638
Distinct characters102
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.5%

Sample

1st row삼정엘리베이터
2nd row삼정엘리베이터
3rd row티센크루프엘리베이터코리아
4th row티센크루프엘리베이터코리아
5th row티센크루프엘리베이터코리아
ValueCountFrequency (%)
현대엘리베이터 275
 
15.9%
티케이엘리베이터코리아 154
 
8.9%
오티스엘리베이터 122
 
7.0%
한국미쓰비시엘리베이터 100
 
5.8%
티센크루프엘리베이터코리아 85
 
4.9%
성원엘리베이터 44
 
2.5%
그린엘리베이터 42
 
2.4%
새한엘리베이터 41
 
2.4%
지에스엘리베이터 33
 
1.9%
명원엘리베이터 32
 
1.8%
Other values (75) 805
46.5%
2024-04-06T17:26:20.298201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 1696
 
12.4%
이 1652
 
12.1%
엘 1396
 
10.2%
베 1395
 
10.2%
터 1395
 
10.2%
티 385
 
2.8%
대 380
 
2.8%
한 333
 
2.4%
아 293
 
2.1%
현 280
 
2.1%
Other values (92) 4433
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13532
99.2%
Open Punctuation 37
 
0.3%
Close Punctuation 37
 
0.3%
Other Punctuation 28
 
0.2%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 1696
 
12.5%
이 1652
 
12.2%
엘 1396
 
10.3%
베 1395
 
10.3%
터 1395
 
10.3%
티 385
 
2.8%
대 380
 
2.8%
한 333
 
2.5%
아 293
 
2.2%
현 280
 
2.1%
Other values (87) 4327
32.0%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
R 2
50.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Other Punctuation
ValueCountFrequency (%)
. 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13532
99.2%
Common 102
 
0.7%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 1696
 
12.5%
이 1652
 
12.2%
엘 1396
 
10.3%
베 1395
 
10.3%
터 1395
 
10.3%
티 385
 
2.8%
대 380
 
2.8%
한 333
 
2.5%
아 293
 
2.2%
현 280
 
2.1%
Other values (87) 4327
32.0%
Common
ValueCountFrequency (%)
( 37
36.3%
) 37
36.3%
. 28
27.5%
Latin
ValueCountFrequency (%)
K 2
50.0%
R 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13532
99.2%
ASCII 106
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 1696
 
12.5%
이 1652
 
12.2%
엘 1396
 
10.3%
베 1395
 
10.3%
터 1395
 
10.3%
티 385
 
2.8%
대 380
 
2.8%
한 333
 
2.5%
아 293
 
2.2%
현 280
 
2.1%
Other values (87) 4327
32.0%
ASCII
ValueCountFrequency (%)
( 37
34.9%
) 37
34.9%
. 28
26.4%
K 2
 
1.9%
R 2
 
1.9%

인증업체주소
Text

Distinct94
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2024-04-06T17:26:20.809400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length22.278707
Min length15

Characters and Unicode

Total characters38609
Distinct characters177
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.6%

Sample

1st row서울특별시 양천구 목동서로 301-5
2nd row서울특별시 양천구 목동서로 301-5
3rd row충청남도 천안시 서북구 입장면 연곡길 235
4th row충청남도 천안시 서북구 입장면 연곡길 235
5th row충청남도 천안시 서북구 입장면 연곡길 235
ValueCountFrequency (%)
경기도 546
 
6.4%
서울특별시 326
 
3.8%
충청남도 274
 
3.2%
영등포구 236
 
2.8%
천안시 233
 
2.7%
서북구 233
 
2.7%
연곡길 216
 
2.5%
235 216
 
2.5%
입장면 216
 
2.5%
충청북도 179
 
2.1%
Other values (284) 5800
68.4%
2024-04-06T17:26:21.692308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6834
 
17.7%
시 1676
 
4.3%
로 1321
 
3.4%
도 1299
 
3.4%
1 1286
 
3.3%
2 1262
 
3.3%
충 865
 
2.2%
구 834
 
2.2%
길 774
 
2.0%
경 766
 
2.0%
Other values (167) 21692
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24403
63.2%
Space Separator 6834
 
17.7%
Decimal Number 6420
 
16.6%
Dash Punctuation 354
 
0.9%
Close Punctuation 252
 
0.7%
Open Punctuation 252
 
0.7%
Other Punctuation 94
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1676
 
6.9%
로 1321
 
5.4%
도 1299
 
5.3%
충 865
 
3.5%
구 834
 
3.4%
길 774
 
3.2%
경 766
 
3.1%
산 727
 
3.0%
서 688
 
2.8%
기 638
 
2.6%
Other values (152) 14815
60.7%
Decimal Number
ValueCountFrequency (%)
1 1286
20.0%
2 1262
19.7%
0 640
10.0%
5 574
8.9%
3 557
8.7%
7 487
 
7.6%
8 440
 
6.9%
6 439
 
6.8%
4 414
 
6.4%
9 321
 
5.0%
Space Separator
ValueCountFrequency (%)
6834
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 354
100.0%
Close Punctuation
ValueCountFrequency (%)
) 252
100.0%
Open Punctuation
ValueCountFrequency (%)
( 252
100.0%
Other Punctuation
ValueCountFrequency (%)
, 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24403
63.2%
Common 14206
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1676
 
6.9%
로 1321
 
5.4%
도 1299
 
5.3%
충 865
 
3.5%
구 834
 
3.4%
길 774
 
3.2%
경 766
 
3.1%
산 727
 
3.0%
서 688
 
2.8%
기 638
 
2.6%
Other values (152) 14815
60.7%
Common
ValueCountFrequency (%)
6834
48.1%
1 1286
 
9.1%
2 1262
 
8.9%
0 640
 
4.5%
5 574
 
4.0%
3 557
 
3.9%
7 487
 
3.4%
8 440
 
3.1%
6 439
 
3.1%
4 414
 
2.9%
Other values (5) 1273
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24403
63.2%
ASCII 14206
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6834
48.1%
1 1286
 
9.1%
2 1262
 
8.9%
0 640
 
4.5%
5 574
 
4.0%
3 557
 
3.9%
7 487
 
3.4%
8 440
 
3.1%
6 439
 
3.1%
4 414
 
2.9%
Other values (5) 1273
 
9.0%
Hangul
ValueCountFrequency (%)
시 1676
 
6.9%
로 1321
 
5.4%
도 1299
 
5.3%
충 865
 
3.5%
구 834
 
3.4%
길 774
 
3.2%
경 766
 
3.1%
산 727
 
3.0%
서 688
 
2.8%
기 638
 
2.6%
Other values (152) 14815
60.7%

접수번호
Text

Distinct1730
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2024-04-06T17:26:22.165476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length15.44951
Min length12

Characters and Unicode

Total characters26774
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1728 ?
Unique (%)99.7%

Sample

1st rowC400120190503001
2nd rowC400120190503002
3rd rowC400120190430001
4th rowC400120190430002
5th rowC400120190430004
ValueCountFrequency (%)
b20231206103 3
 
0.2%
b20230911101 2
 
0.1%
b20231222103 2
 
0.1%
b20240205102 1
 
0.1%
c400020220916013 1
 
0.1%
c400020221027011 1
 
0.1%
c400020221027010 1
 
0.1%
c400020221011017 1
 
0.1%
c400020220907054 1
 
0.1%
c400020221031023 1
 
0.1%
Other values (1719) 1719
99.2%
2024-04-06T17:26:22.875220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10554
39.4%
2 5319
19.9%
1 3677
 
13.7%
4 2087
 
7.8%
C 1493
 
5.6%
3 1191
 
4.4%
9 525
 
2.0%
8 471
 
1.8%
7 419
 
1.6%
6 404
 
1.5%
Other values (4) 634
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25037
93.5%
Uppercase Letter 1734
 
6.5%
Control 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10554
42.2%
2 5319
21.2%
1 3677
 
14.7%
4 2087
 
8.3%
3 1191
 
4.8%
9 525
 
2.1%
8 471
 
1.9%
7 419
 
1.7%
6 404
 
1.6%
5 390
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
C 1493
86.1%
B 241
 
13.9%
Control
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25040
93.5%
Latin 1734
 
6.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10554
42.1%
2 5319
21.2%
1 3677
 
14.7%
4 2087
 
8.3%
3 1191
 
4.8%
9 525
 
2.1%
8 471
 
1.9%
7 419
 
1.7%
6 404
 
1.6%
5 390
 
1.6%
Other values (2) 3
 
< 0.1%
Latin
ValueCountFrequency (%)
C 1493
86.1%
B 241
 
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26774
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10554
39.4%
2 5319
19.9%
1 3677
 
13.7%
4 2087
 
7.8%
C 1493
 
5.6%
3 1191
 
4.4%
9 525
 
2.0%
8 471
 
1.8%
7 419
 
1.6%
6 404
 
1.5%
Other values (4) 634
 
2.4%

인증서발행일
Date

Distinct589
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
Minimum2019-06-05 00:00:00
Maximum2024-03-04 00:00:00
2024-04-06T17:26:23.141473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:26:23.395115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

적용안전기준
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
승강기안전기준 별표 22
1372 
(종전)「승강기 안전검사기준」별표 1
241 
승강기안전기준 별표 24
 
66
승강기안전기준 별표22
 
20
(종전)「승강기 안전검사기준」별표 3
 
15
Other values (2)
 
19

Length

Max length20
Median length13
Mean length14.022504
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row(종전)「승강기 안전검사기준」별표 3
2nd row(종전)「승강기 안전검사기준」별표 3
3rd row(종전)「승강기 안전검사기준」별표 1
4th row(종전)「승강기 안전검사기준」별표 1
5th row(종전)「승강기 안전검사기준」별표 1

Common Values

ValueCountFrequency (%)
승강기안전기준 별표 22 1372
79.2%
(종전)「승강기 안전검사기준」별표 1 241
 
13.9%
승강기안전기준 별표 24 66
 
3.8%
승강기안전기준 별표22 20
 
1.2%
(종전)「승강기 안전검사기준」별표 3 15
 
0.9%
승강기안전기준 별표 25 11
 
0.6%
승강기안전기준 별표 26 8
 
0.5%

Length

2024-04-06T17:26:23.662496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:26:23.960233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
승강기안전기준 1477
28.5%
별표 1457
28.1%
22 1372
26.5%
종전)「승강기 256
 
4.9%
안전검사기준」별표 256
 
4.9%
1 241
 
4.7%
24 66
 
1.3%
별표22 20
 
0.4%
3 15
 
0.3%
25 11
 
0.2%

인증서상태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
회수
1453 
정상
236 
반납
 
44

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row반납
2nd row반납
3rd row반납
4th row회수
5th row회수

Common Values

ValueCountFrequency (%)
회수 1453
83.8%
정상 236
 
13.6%
반납 44
 
2.5%

Length

2024-04-06T17:26:24.344466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:26:24.541776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
회수 1453
83.8%
정상 236
 
13.6%
반납 44
 
2.5%

모델명
Text

Distinct282
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2024-04-06T17:26:24.980257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length8.1546451
Min length3

Characters and Unicode

Total characters14132
Distinct characters63
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)2.1%

Sample

1st rowK300A
2nd rowK200
3rd rowsynergy
4th rowEnta
5th rowElexess2
ValueCountFrequency (%)
acd4 71
 
3.5%
mr 47
 
2.3%
mrl 38
 
1.9%
acd5 29
 
1.4%
gm1 23
 
1.1%
wbss(e 22
 
1.1%
wbss-gy-2 21
 
1.0%
wblx(e 21
 
1.0%
elevator 20
 
1.0%
wbhs(e 19
 
0.9%
Other values (282) 1705
84.6%
2024-04-06T17:26:25.784186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1818
 
12.9%
M 1219
 
8.6%
R 929
 
6.6%
S 894
 
6.3%
L 858
 
6.1%
1 767
 
5.4%
E 650
 
4.6%
G 499
 
3.5%
A 421
 
3.0%
T 393
 
2.8%
Other values (53) 5684
40.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 9009
63.7%
Decimal Number 2093
 
14.8%
Dash Punctuation 1818
 
12.9%
Lowercase Letter 427
 
3.0%
Space Separator 293
 
2.1%
Open Punctuation 162
 
1.1%
Close Punctuation 162
 
1.1%
Other Punctuation 62
 
0.4%
Other Letter 57
 
0.4%
Connector Punctuation 39
 
0.3%
Other values (2) 10
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 1219
13.5%
R 929
 
10.3%
S 894
 
9.9%
L 858
 
9.5%
E 650
 
7.2%
G 499
 
5.5%
A 421
 
4.7%
T 393
 
4.4%
D 365
 
4.1%
H 351
 
3.9%
Other values (15) 2430
27.0%
Lowercase Letter
ValueCountFrequency (%)
e 96
22.5%
s 67
15.7%
o 58
13.6%
l 45
10.5%
i 44
10.3%
n 27
 
6.3%
v 24
 
5.6%
x 19
 
4.4%
r 19
 
4.4%
t 9
 
2.1%
Other values (5) 19
 
4.4%
Decimal Number
ValueCountFrequency (%)
1 767
36.6%
0 344
16.4%
2 343
16.4%
7 152
 
7.3%
5 136
 
6.5%
3 93
 
4.4%
8 92
 
4.4%
4 85
 
4.1%
6 62
 
3.0%
9 19
 
0.9%
Other Letter
ValueCountFrequency (%)
즈 17
29.8%
리 17
29.8%
시 17
29.8%
소 3
 
5.3%
형 3
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 1818
100.0%
Space Separator
ValueCountFrequency (%)
293
100.0%
Open Punctuation
ValueCountFrequency (%)
( 162
100.0%
Close Punctuation
ValueCountFrequency (%)
) 162
100.0%
Other Punctuation
ValueCountFrequency (%)
. 62
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 39
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 7
100.0%
Control
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9443
66.8%
Common 4632
32.8%
Hangul 57
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 1219
12.9%
R 929
 
9.8%
S 894
 
9.5%
L 858
 
9.1%
E 650
 
6.9%
G 499
 
5.3%
A 421
 
4.5%
T 393
 
4.2%
D 365
 
3.9%
H 351
 
3.7%
Other values (31) 2864
30.3%
Common
ValueCountFrequency (%)
- 1818
39.2%
1 767
16.6%
0 344
 
7.4%
2 343
 
7.4%
293
 
6.3%
( 162
 
3.5%
) 162
 
3.5%
7 152
 
3.3%
5 136
 
2.9%
3 93
 
2.0%
Other values (7) 362
 
7.8%
Hangul
ValueCountFrequency (%)
즈 17
29.8%
리 17
29.8%
시 17
29.8%
소 3
 
5.3%
형 3
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14068
99.5%
Hangul 57
 
0.4%
Number Forms 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1818
 
12.9%
M 1219
 
8.7%
R 929
 
6.6%
S 894
 
6.4%
L 858
 
6.1%
1 767
 
5.5%
E 650
 
4.6%
G 499
 
3.5%
A 421
 
3.0%
T 393
 
2.8%
Other values (47) 5620
39.9%
Hangul
ValueCountFrequency (%)
즈 17
29.8%
리 17
29.8%
시 17
29.8%
소 3
 
5.3%
형 3
 
5.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 7
100.0%

파생모델명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct29
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
<NA>
1601 
HTEL-P33
 
12
GREL-M-2.0
 
11
KDS11, KDS12
 
9
G2 ELEVATOR
 
8
Other values (24)
 
92

Length

Max length56
Median length4
Mean length4.8251587
Min length4

Unique

Unique7 ?
Unique (%)0.4%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1601
92.4%
HTEL-P33 12
 
0.7%
GREL-M-2.0 11
 
0.6%
KDS11, KDS12 9
 
0.5%
G2 ELEVATOR 8
 
0.5%
DYMR-02 8
 
0.5%
KDS71 8
 
0.5%
G6 ELEVATOR 8
 
0.5%
WBSS-GY-1 7
 
0.4%
DAWON-MRS 7
 
0.4%
Other values (19) 54
 
3.1%

Length

2024-04-06T17:26:26.047407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1601
87.3%
elevator 16
 
0.9%
htel-p33 12
 
0.7%
grel-m-2.0 11
 
0.6%
kds11 9
 
0.5%
kds12 9
 
0.5%
g2 8
 
0.4%
dymr-02 8
 
0.4%
kds71 8
 
0.4%
g6 8
 
0.4%
Other values (34) 143
 
7.8%

인증품목명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
엘리베이터 > 전기식 엘리베이터 > 일반형
1631 
에스컬레이터 > 에스컬레이터 > 일반형
 
66
에스컬레이터 > 무빙워크 > 일반형
 
14
엘리베이터 > 소형화물용 엘리베이터 > 일반형
 
8
휠체어리프트 > 유압식 수직형휠체어리프트 > 일반형
 
7
Other values (2)
 
7

Length

Max length28
Median length23
Mean length22.923832
Min length19

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row에스컬레이터 > 에스컬레이터 > 일반형
2nd row에스컬레이터 > 에스컬레이터 > 일반형
3rd row엘리베이터 > 전기식 엘리베이터 > 일반형
4th row엘리베이터 > 전기식 엘리베이터 > 일반형
5th row엘리베이터 > 전기식 엘리베이터 > 일반형

Common Values

ValueCountFrequency (%)
엘리베이터 > 전기식 엘리베이터 > 일반형 1631
94.1%
에스컬레이터 > 에스컬레이터 > 일반형 66
 
3.8%
에스컬레이터 > 무빙워크 > 일반형 14
 
0.8%
엘리베이터 > 소형화물용 엘리베이터 > 일반형 8
 
0.5%
휠체어리프트 > 유압식 수직형휠체어리프트 > 일반형 7
 
0.4%
엘리베이터 > 유압식 엘리베이터 > 일반형 6
 
0.3%
휠체어리프트 > 전기식 수직형휠체어리프트 > 일반형 1
 
0.1%

Length

2024-04-06T17:26:26.283172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:26:26.513728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3466
33.6%
엘리베이터 3290
31.9%
일반형 1733
16.8%
전기식 1632
15.8%
에스컬레이터 146
 
1.4%
무빙워크 14
 
0.1%
유압식 13
 
0.1%
소형화물용 8
 
0.1%
휠체어리프트 8
 
0.1%
수직형휠체어리프트 8
 
0.1%

모델/개별
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
모델
1733 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
모델 1733
100.0%

Length

2024-04-06T17:26:26.777178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:26:26.971466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
모델 1733
100.0%

제조국가
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
한국
1637 
중국
 
96

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중국
2nd row중국
3rd row한국
4th row한국
5th row한국

Common Values

ValueCountFrequency (%)
한국 1637
94.5%
중국 96
 
5.5%

Length

2024-04-06T17:26:27.153099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:26:27.345711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국 1637
94.5%
중국 96
 
5.5%

Correlations

2024-04-06T17:26:27.485154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인증업체코드업체명인증업체주소적용안전기준인증서상태파생모델명인증품목명제조국가
인증업체코드1.0001.0001.0000.8630.4630.9960.8820.780
업체명1.0001.0001.0000.8640.3451.0000.8830.761
인증업체주소1.0001.0001.0000.8750.3730.9980.9100.799
적용안전기준0.8630.8640.8751.0000.261NaN0.9540.844
인증서상태0.4630.3450.3730.2611.0000.8550.1510.075
파생모델명0.9961.0000.998NaN0.8551.0001.000NaN
인증품목명0.8820.8830.9100.9540.1511.0001.0000.838
제조국가0.7800.7610.7990.8440.075NaN0.8381.000
2024-04-06T17:26:27.732228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
파생모델명적용안전기준제조국가인증품목명인증서상태
파생모델명1.0001.0001.0000.8940.607
적용안전기준1.0001.0000.9130.6730.181
제조국가1.0000.9131.0000.9070.125
인증품목명0.8940.6730.9071.0000.101
인증서상태0.6070.1810.1250.1011.000
2024-04-06T17:26:27.951920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적용안전기준인증서상태파생모델명인증품목명제조국가
적용안전기준1.0000.1811.0000.6730.913
인증서상태0.1811.0000.6070.1010.125
파생모델명1.0000.6071.0000.8941.000
인증품목명0.6730.1010.8941.0000.907
제조국가0.9130.1251.0000.9071.000

Missing values

2024-04-06T17:26:15.965605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:26:16.404655image/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

안전인증번호인증업체코드업체명인증업체주소접수번호인증서발행일적용안전기준인증서상태모델명파생모델명인증품목명모델/개별제조국가
0ABB73-R001-19001919971182삼정엘리베이터서울특별시 양천구 목동서로 301-5C4001201905030012019-06-05(종전)「승강기 안전검사기준」별표 3반납K300A<NA>에스컬레이터 > 에스컬레이터 > 일반형모델중국
1ABB73-R001-19002919971182삼정엘리베이터서울특별시 양천구 목동서로 301-5C4001201905030022019-06-05(종전)「승강기 안전검사기준」별표 3반납K200<NA>에스컬레이터 > 에스컬레이터 > 일반형모델중국
2ABA71-K001-19005919920034티센크루프엘리베이터코리아충청남도 천안시 서북구 입장면 연곡길 235C4001201904300012019-07-10(종전)「승강기 안전검사기준」별표 1반납synergy<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
3ABA71-K001-19001919920034티센크루프엘리베이터코리아충청남도 천안시 서북구 입장면 연곡길 235C4001201904300022019-07-10(종전)「승강기 안전검사기준」별표 1회수Enta<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
4ABA71-K001-19002919920034티센크루프엘리베이터코리아충청남도 천안시 서북구 입장면 연곡길 235C4001201904300042019-07-10(종전)「승강기 안전검사기준」별표 1회수Elexess2<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
5ABA71-K001-19003919920034티센크루프엘리베이터코리아충청남도 천안시 서북구 입장면 연곡길 235C4001201904300052019-07-10(종전)「승강기 안전검사기준」별표 1회수GL1<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
6ABA71-K001-19004919920034티센크루프엘리베이터코리아충청남도 천안시 서북구 입장면 연곡길 235C4001201904300082019-07-10(종전)「승강기 안전검사기준」별표 1회수Enta200소형<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
7ABA71-K001-19001919920034티센크루프엘리베이터코리아충청남도 천안시 서북구 입장면 연곡길 235C4001202005061002019-07-10(종전)「승강기 안전검사기준」별표 1회수Enta<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
8ABA71-K001-19004919920034티센크루프엘리베이터코리아충청남도 천안시 서북구 입장면 연곡길 235C4001202006301002019-07-10(종전)「승강기 안전검사기준」별표 1회수Enta200소형<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
9ABA71-K001-19003919920034티센크루프엘리베이터코리아충청남도 천안시 서북구 입장면 연곡길 235C4001202007071002019-07-10(종전)「승강기 안전검사기준」별표 1회수GL1<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
안전인증번호인증업체코드업체명인증업체주소접수번호인증서발행일적용안전기준인증서상태모델명파생모델명인증품목명모델/개별제조국가
1723ABA71-I002-23001920150010금강엔지니어링강원도 속초시 농공단지2길 14B2B202402271012024-02-28승강기안전기준 별표 22정상GK-MOR-B<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
1724ABA71-J003-21002<NA>현대엘리베이터충청북도 충주시 충주산단1로 128B202401241102024-02-29승강기안전기준 별표 22정상GTSS-R<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
1725ABA71-N001-21001<NA>성원엘리베이터전라북도 전주시 덕진구 신흥안길 52B202402271062024-03-04승강기안전기준 별표 22정상SW-MRL-2<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
1726ABA71-N001-22001<NA>성원엘리베이터전라북도 전주시 덕진구 신흥안길 52B202402271052024-03-04승강기안전기준 별표 22정상SW-MOR-R1<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
1727ABA71-N001-20001<NA>성원엘리베이터전라북도 전주시 덕진구 신흥안길 52B202402271042024-03-04승강기안전기준 별표 22정상SW-MRL-1<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
1728ABA71-L002-22001<NA>한국승강기블루부산광역시 북구 금곡대로104번길 10 (덕천동)B202402161012024-02-27승강기안전기준 별표 22정상BLUE-R<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
1729ABA71-B003-24001<NA>영진엘리베이터부산광역시 기장군 장안읍 오리산단7로 25B202310241022024-01-15승강기안전기준 별표22회수CRUZE1-H<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
1730ABA71-B003-24001<NA>영진엘리베이터부산광역시 기장군 장안읍 오리산단7로 25B202401191022024-01-23승강기안전기준 별표22정상CRUZE1-H<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
1731ABA71-N001-20002<NA>성원엘리베이터전라북도 전주시 덕진구 신흥안길 52B202402051022024-02-15승강기안전기준 별표 22회수SW-MR-1<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국
1732ABA71-N001-20002<NA>성원엘리베이터전라북도 전주시 덕진구 신흥안길 52B202402271032024-03-04승강기안전기준 별표 22정상SW-MR-1<NA>엘리베이터 > 전기식 엘리베이터 > 일반형모델한국