Overview

Dataset statistics

Number of variables9
Number of observations239
Missing cells181
Missing cells (%)8.4%
Duplicate rows8
Duplicate rows (%)3.3%
Total size in memory16.9 KiB
Average record size in memory72.6 B

Variable types

Text4
DateTime2
Categorical3

Dataset

Description해외제조공장(가스레인지 등) 중 국내 유통이 가능하도록 심사완료된 업체 현황(등록번호, 업소명, 등록종류, 소재지, 대표자 등)데이터 입니다.
Author한국가스안전공사
URLhttps://www.data.go.kr/data/15043846/fileData.do

Alerts

Dataset has 8 (3.3%) duplicate rowsDuplicates
등록종류 has a high cardinality: 51 distinct valuesHigh cardinality
등록종류 is highly overall correlated with 제조기준High correlation
제조기준 is highly overall correlated with 등록종류High correlation
등록번호 has 30 (12.6%) missing valuesMissing
업소명 has 30 (12.6%) missing valuesMissing
최초등록일 has 30 (12.6%) missing valuesMissing
만료일 has 30 (12.6%) missing valuesMissing
소재지 has 30 (12.6%) missing valuesMissing
대표자 has 31 (13.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:22:16.551461
Analysis finished2023-12-12 18:22:17.346698
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

MISSING 

Distinct209
Distinct (%)100.0%
Missing30
Missing (%)12.6%
Memory size2.0 KiB
2023-12-13T03:22:17.856815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.4832536
Min length7

Characters and Unicode

Total characters1773
Distinct characters16
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

Unique209 ?
Unique (%)100.0%

Sample

1st row제 GA-1호
2nd row제 GA-2호
3rd row제 GA-3호
4th row제 GA-4호
5th row제 GA-5호
ValueCountFrequency (%)
제 209
50.0%
ga-129호 1
 
0.2%
ga-156호 1
 
0.2%
ga-143호 1
 
0.2%
ga-145호 1
 
0.2%
ga-134호 1
 
0.2%
ga-135호 1
 
0.2%
ga-136호 1
 
0.2%
ga-137호 1
 
0.2%
ga-138호 1
 
0.2%
Other values (200) 200
47.8%
2023-12-13T03:22:18.366906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 209
11.8%
209
11.8%
G 209
11.8%
A 209
11.8%
- 209
11.8%
호 209
11.8%
1 140
7.9%
2 52
 
2.9%
5 41
 
2.3%
6 41
 
2.3%
Other values (6) 245
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 519
29.3%
Other Letter 418
23.6%
Uppercase Letter 418
23.6%
Space Separator 209
11.8%
Dash Punctuation 209
11.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 140
27.0%
2 52
 
10.0%
5 41
 
7.9%
6 41
 
7.9%
3 41
 
7.9%
4 41
 
7.9%
8 41
 
7.9%
9 41
 
7.9%
0 41
 
7.9%
7 40
 
7.7%
Other Letter
ValueCountFrequency (%)
제 209
50.0%
호 209
50.0%
Uppercase Letter
ValueCountFrequency (%)
G 209
50.0%
A 209
50.0%
Space Separator
ValueCountFrequency (%)
209
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 209
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 937
52.8%
Hangul 418
23.6%
Latin 418
23.6%

Most frequent character per script

Common
ValueCountFrequency (%)
209
22.3%
- 209
22.3%
1 140
14.9%
2 52
 
5.5%
5 41
 
4.4%
6 41
 
4.4%
3 41
 
4.4%
4 41
 
4.4%
8 41
 
4.4%
9 41
 
4.4%
Other values (2) 81
 
8.6%
Hangul
ValueCountFrequency (%)
제 209
50.0%
호 209
50.0%
Latin
ValueCountFrequency (%)
G 209
50.0%
A 209
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1355
76.4%
Hangul 418
 
23.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 209
50.0%
호 209
50.0%
ASCII
ValueCountFrequency (%)
209
15.4%
G 209
15.4%
A 209
15.4%
- 209
15.4%
1 140
10.3%
2 52
 
3.8%
5 41
 
3.0%
6 41
 
3.0%
3 41
 
3.0%
4 41
 
3.0%
Other values (4) 163
12.0%

업소명
Text

MISSING 

Distinct197
Distinct (%)94.3%
Missing30
Missing (%)12.6%
Memory size2.0 KiB
2023-12-13T03:22:18.750919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length43
Mean length27.866029
Min length7

Characters and Unicode

Total characters5824
Distinct characters66
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)88.5%

Sample

1st rowAERCO International, Inc.
2nd rowEloma GmbH
3rd rowMSA, a.s.
4th rowTIANJIN HANXIN PRECISION ELECTRON CO.,LTD
5th rowRATIONAL AG
ValueCountFrequency (%)
ltd 58
 
7.3%
co 50
 
6.3%
co.,ltd 19
 
2.4%
gmbh 17
 
2.1%
inc 15
 
1.9%
s.p.a 14
 
1.8%
corporation 13
 
1.6%
manufacturing 12
 
1.5%
valve 8
 
1.0%
llc 8
 
1.0%
Other values (413) 583
73.1%
2023-12-13T03:22:19.351067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
591
 
10.1%
a 295
 
5.1%
n 283
 
4.9%
o 260
 
4.5%
e 246
 
4.2%
r 223
 
3.8%
i 215
 
3.7%
t 214
 
3.7%
. 205
 
3.5%
A 171
 
2.9%
Other values (56) 3121
53.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2887
49.6%
Uppercase Letter 1966
33.8%
Space Separator 591
 
10.1%
Other Punctuation 296
 
5.1%
Open Punctuation 33
 
0.6%
Close Punctuation 33
 
0.6%
Dash Punctuation 10
 
0.2%
Other Letter 4
 
0.1%
Math Symbol 2
 
< 0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 295
 
10.2%
n 283
 
9.8%
o 260
 
9.0%
e 246
 
8.5%
r 223
 
7.7%
i 215
 
7.4%
t 214
 
7.4%
u 144
 
5.0%
s 128
 
4.4%
l 120
 
4.2%
Other values (16) 759
26.3%
Uppercase Letter
ValueCountFrequency (%)
A 171
 
8.7%
C 163
 
8.3%
L 162
 
8.2%
I 143
 
7.3%
E 117
 
6.0%
N 115
 
5.8%
S 113
 
5.7%
O 113
 
5.7%
T 102
 
5.2%
R 101
 
5.1%
Other values (16) 666
33.9%
Other Punctuation
ValueCountFrequency (%)
. 205
69.3%
, 81
 
27.4%
& 6
 
2.0%
? 3
 
1.0%
' 1
 
0.3%
Other Letter
ValueCountFrequency (%)
장 2
50.0%
공 2
50.0%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
591
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4853
83.3%
Common 967
 
16.6%
Hangul 4
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 295
 
6.1%
n 283
 
5.8%
o 260
 
5.4%
e 246
 
5.1%
r 223
 
4.6%
i 215
 
4.4%
t 214
 
4.4%
A 171
 
3.5%
C 163
 
3.4%
L 162
 
3.3%
Other values (42) 2621
54.0%
Common
ValueCountFrequency (%)
591
61.1%
. 205
 
21.2%
, 81
 
8.4%
( 33
 
3.4%
) 33
 
3.4%
- 10
 
1.0%
& 6
 
0.6%
? 3
 
0.3%
+ 2
 
0.2%
1 1
 
0.1%
Other values (2) 2
 
0.2%
Hangul
ValueCountFrequency (%)
장 2
50.0%
공 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5820
99.9%
Hangul 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
591
 
10.2%
a 295
 
5.1%
n 283
 
4.9%
o 260
 
4.5%
e 246
 
4.2%
r 223
 
3.8%
i 215
 
3.7%
t 214
 
3.7%
. 205
 
3.5%
A 171
 
2.9%
Other values (54) 3117
53.6%
Hangul
ValueCountFrequency (%)
장 2
50.0%
공 2
50.0%

최초등록일
Date

MISSING 

Distinct158
Distinct (%)75.6%
Missing30
Missing (%)12.6%
Memory size2.0 KiB
Minimum2012-06-22 00:00:00
Maximum2023-05-26 00:00:00
2023-12-13T03:22:19.532798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:19.686517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

만료일
Date

MISSING 

Distinct177
Distinct (%)84.7%
Missing30
Missing (%)12.6%
Memory size2.0 KiB
Minimum2012-11-24 00:00:00
Maximum2026-05-25 00:00:00
2023-12-13T03:22:19.860708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:22:20.016071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

등록종류
Categorical

HIGH CARDINALITY  HIGH CORRELATION 

Distinct51
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Commercial Gas Burning Appliances
58 
<NA>
46 
Valves for Pipes
17 
Gas Heaters
13 
Portable Butane Gas stoves
 
9
Other values (46)
96 

Length

Max length75
Median length51
Mean length23.372385
Min length4

Unique

Unique28 ?
Unique (%)11.7%

Sample

1st rowForced Mixed type Gas Burners
2nd rowCommercial Gas Burning Appliances
3rd rowValves for Pipes
4th rowFully welded Ball valves for underground use
5th rowGlobe Valves for Pipes

Common Values

ValueCountFrequency (%)
Commercial Gas Burning Appliances 58
24.3%
<NA> 46
19.2%
Valves for Pipes 17
 
7.1%
Gas Heaters 13
 
5.4%
Portable Butane Gas stoves 9
 
3.8%
Clothes Gas Dryers 7
 
2.9%
Forced Mixed type Gas Burners 7
 
2.9%
Pressure Regulators for Urban Gas 7
 
2.9%
Portable Butane Gas Stoves 6
 
2.5%
Portable Propane Gas Stoves 5
 
2.1%
Other values (41) 64
26.8%

Length

2023-12-13T03:22:20.167959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
gas 147
17.4%
burning 61
 
7.2%
appliances 60
 
7.1%
commercial 59
 
7.0%
for 52
 
6.2%
na 46
 
5.5%
valves 38
 
4.5%
pipes 28
 
3.3%
portable 24
 
2.8%
stoves 23
 
2.7%
Other values (64) 306
36.3%

제조기준
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
KGS AB338
55 
<NA>
46 
KGS AA331
19 
KGS AB336
18 
KGS AB933
15 
Other values (23)
86 

Length

Max length13
Median length9
Mean length8.0669456
Min length4

Unique

Unique9 ?
Unique (%)3.8%

Sample

1st rowKGS AB931
2nd rowKGS AB338
3rd rowKGS AA331
4th rowKGS AA332
5th rowKGS AA335

Common Values

ValueCountFrequency (%)
KGS AB338 55
23.0%
<NA> 46
19.2%
KGS AA331 19
 
7.9%
KGS AB336 18
 
7.5%
KGS AB933 15
 
6.3%
KGS AB231 13
 
5.4%
KGS AB931 11
 
4.6%
KGS AA431 8
 
3.3%
KGS AA336 6
 
2.5%
KGS AB131 6
 
2.5%
Other values (18) 42
17.6%

Length

2023-12-13T03:22:20.316665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
kgs 193
44.6%
ab338 57
 
13.2%
na 46
 
10.6%
aa331 19
 
4.4%
ab336 18
 
4.2%
ab933 15
 
3.5%
ab231 13
 
3.0%
ab931 12
 
2.8%
aa431 8
 
1.8%
aa336 6
 
1.4%
Other values (17) 46
 
10.6%

소재지
Text

MISSING 

Distinct209
Distinct (%)100.0%
Missing30
Missing (%)12.6%
Memory size2.0 KiB
2023-12-13T03:22:20.702133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length150
Median length84
Mean length57.119617
Min length30

Characters and Unicode

Total characters11938
Distinct characters77
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

Unique209 ?
Unique (%)100.0%

Sample

1st row100 Oritani Drive, Blauvelt, NY 10913 USA
2nd rowOberer Ladenberg 10, 01819 Bad Gottleuba-Berggießh?bel, Germany
3rd rowHlucinska. 641 747 22 Dolni Benesov, Czech Republic
4th rowXiaoDian Industry park 2Th South Jinwei Road East Beichen Distric TianJin, China
5th rowSiegfried-Meister-Strasse 1, 86899 Landsberg am Lech, Germany
ValueCountFrequency (%)
china 55
 
3.3%
road 37
 
2.2%
usa 31
 
1.9%
japan 24
 
1.4%
industrial 22
 
1.3%
city 20
 
1.2%
via 20
 
1.2%
italy 20
 
1.2%
district 19
 
1.1%
germany 19
 
1.1%
Other values (1016) 1390
83.9%
2023-12-13T03:22:21.386910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1509
 
12.6%
a 802
 
6.7%
n 636
 
5.3%
i 585
 
4.9%
, 545
 
4.6%
e 516
 
4.3%
o 495
 
4.1%
r 345
 
2.9%
t 311
 
2.6%
h 300
 
2.5%
Other values (67) 5894
49.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5970
50.0%
Uppercase Letter 2260
 
18.9%
Space Separator 1509
 
12.6%
Decimal Number 1296
 
10.9%
Other Punctuation 704
 
5.9%
Dash Punctuation 146
 
1.2%
Close Punctuation 26
 
0.2%
Open Punctuation 26
 
0.2%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 802
13.4%
n 636
10.7%
i 585
 
9.8%
e 516
 
8.6%
o 495
 
8.3%
r 345
 
5.8%
t 311
 
5.2%
h 300
 
5.0%
u 267
 
4.5%
g 246
 
4.1%
Other values (18) 1467
24.6%
Uppercase Letter
ValueCountFrequency (%)
A 237
 
10.5%
S 176
 
7.8%
C 165
 
7.3%
N 152
 
6.7%
I 152
 
6.7%
T 130
 
5.8%
R 114
 
5.0%
D 98
 
4.3%
H 89
 
3.9%
G 89
 
3.9%
Other values (16) 858
38.0%
Decimal Number
ValueCountFrequency (%)
1 233
18.0%
0 198
15.3%
2 182
14.0%
3 125
9.6%
4 125
9.6%
5 120
9.3%
6 92
 
7.1%
8 87
 
6.7%
7 76
 
5.9%
9 58
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 545
77.4%
. 122
 
17.3%
? 17
 
2.4%
/ 10
 
1.4%
& 3
 
0.4%
: 3
 
0.4%
# 3
 
0.4%
; 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1509
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 146
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8229
68.9%
Common 3708
31.1%
Greek 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 802
 
9.7%
n 636
 
7.7%
i 585
 
7.1%
e 516
 
6.3%
o 495
 
6.0%
r 345
 
4.2%
t 311
 
3.8%
h 300
 
3.6%
u 267
 
3.2%
g 246
 
3.0%
Other values (43) 3726
45.3%
Common
ValueCountFrequency (%)
1509
40.7%
, 545
 
14.7%
1 233
 
6.3%
0 198
 
5.3%
2 182
 
4.9%
- 146
 
3.9%
3 125
 
3.4%
4 125
 
3.4%
. 122
 
3.3%
5 120
 
3.2%
Other values (13) 403
 
10.9%
Greek
ValueCountFrequency (%)
β 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11934
> 99.9%
None 3
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1509
 
12.6%
a 802
 
6.7%
n 636
 
5.3%
i 585
 
4.9%
, 545
 
4.6%
e 516
 
4.3%
o 495
 
4.1%
r 345
 
2.9%
t 311
 
2.6%
h 300
 
2.5%
Other values (64) 5890
49.4%
None
ValueCountFrequency (%)
ß 2
66.7%
β 1
33.3%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

대표자
Text

MISSING 

Distinct202
Distinct (%)97.1%
Missing31
Missing (%)13.0%
Memory size2.0 KiB
2023-12-13T03:22:21.843186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length23
Mean length14.442308
Min length4

Characters and Unicode

Total characters3004
Distinct characters58
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

Unique196 ?
Unique (%)94.2%

Sample

1st rowJames F Dagley
2nd rowMARK JOSEPH M?LLER
3rd rowAndrey Chaykov
4th rowDr. Peter Stadelmann
5th rowTHOMAS B?HMER, PETER PILAPL
ValueCountFrequency (%)
wang 5
 
1.1%
zhang 5
 
1.1%
lu 4
 
0.8%
robert 4
 
0.8%
marco 4
 
0.8%
michael 4
 
0.8%
liu 3
 
0.6%
qing 3
 
0.6%
frank 3
 
0.6%
mark 3
 
0.6%
Other values (372) 435
92.0%
2023-12-13T03:22:22.426506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
282
 
9.4%
a 224
 
7.5%
n 182
 
6.1%
i 181
 
6.0%
e 170
 
5.7%
o 149
 
5.0%
r 143
 
4.8%
A 88
 
2.9%
u 72
 
2.4%
h 72
 
2.4%
Other values (48) 1441
48.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1778
59.2%
Uppercase Letter 901
30.0%
Space Separator 282
 
9.4%
Other Punctuation 38
 
1.3%
Dash Punctuation 5
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 224
12.6%
n 182
10.2%
i 181
10.2%
e 170
 
9.6%
o 149
 
8.4%
r 143
 
8.0%
u 72
 
4.0%
h 72
 
4.0%
l 71
 
4.0%
t 70
 
3.9%
Other values (16) 444
25.0%
Uppercase Letter
ValueCountFrequency (%)
A 88
 
9.8%
M 58
 
6.4%
R 57
 
6.3%
S 53
 
5.9%
O 53
 
5.9%
N 52
 
5.8%
I 49
 
5.4%
C 39
 
4.3%
G 38
 
4.2%
L 38
 
4.2%
Other values (16) 376
41.7%
Other Punctuation
ValueCountFrequency (%)
. 21
55.3%
, 10
26.3%
? 6
 
15.8%
' 1
 
2.6%
Space Separator
ValueCountFrequency (%)
282
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2679
89.2%
Common 325
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 224
 
8.4%
n 182
 
6.8%
i 181
 
6.8%
e 170
 
6.3%
o 149
 
5.6%
r 143
 
5.3%
A 88
 
3.3%
u 72
 
2.7%
h 72
 
2.7%
l 71
 
2.7%
Other values (42) 1327
49.5%
Common
ValueCountFrequency (%)
282
86.8%
. 21
 
6.5%
, 10
 
3.1%
? 6
 
1.8%
- 5
 
1.5%
' 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3004
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
282
 
9.4%
a 224
 
7.5%
n 182
 
6.1%
i 181
 
6.0%
e 170
 
5.7%
o 149
 
5.0%
r 143
 
4.8%
A 88
 
2.9%
u 72
 
2.4%
h 72
 
2.4%
Other values (48) 1441
48.0%

국가
Categorical

Distinct27
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
China
58 
U.S.A
38 
<NA>
30 
Italy
24 
Japan
24 
Other values (22)
65 

Length

Max length14
Median length5
Mean length5.4686192
Min length3

Unique

Unique12 ?
Unique (%)5.0%

Sample

1st rowU.S.A
2nd rowGermany
3rd rowCzech Republic
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
China 58
24.3%
U.S.A 38
15.9%
<NA> 30
12.6%
Italy 24
10.0%
Japan 24
10.0%
Germany 19
 
7.9%
Czech Republic 6
 
2.5%
Spain 6
 
2.5%
Turkey 5
 
2.1%
THAILAND 4
 
1.7%
Other values (17) 25
10.5%

Length

2023-12-13T03:22:22.587228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
china 58
23.7%
u.s.a 38
15.5%
na 30
12.2%
japan 25
10.2%
italy 24
9.8%
germany 19
 
7.8%
czech 6
 
2.4%
republic 6
 
2.4%
spain 6
 
2.4%
turkey 5
 
2.0%
Other values (16) 28
11.4%

Correlations

2023-12-13T03:22:22.669200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록종류제조기준국가
등록종류1.0000.9950.000
제조기준0.9951.0000.000
국가0.0000.0001.000
2023-12-13T03:22:22.764897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제조기준국가등록종류
제조기준1.0000.0000.823
국가0.0001.0000.000
등록종류0.8230.0001.000
2023-12-13T03:22:22.862565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록종류제조기준국가
등록종류1.0000.8230.000
제조기준0.8231.0000.000
국가0.0000.0001.000

Missing values

2023-12-13T03:22:16.949453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:22:17.077314image/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.
2023-12-13T03:22:17.225100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

등록번호업소명최초등록일만료일등록종류제조기준소재지대표자국가
0제 GA-1호AERCO International, Inc.2012-06-222024-06-21Forced Mixed type Gas BurnersKGS AB931100 Oritani Drive, Blauvelt, NY 10913 USAJames F DagleyU.S.A
1제 GA-2호Eloma GmbH2012-08-212024-08-20Commercial Gas Burning AppliancesKGS AB338Oberer Ladenberg 10, 01819 Bad Gottleuba-Berggießh?bel, GermanyMARK JOSEPH M?LLERGermany
2제 GA-3호MSA, a.s.2012-09-102024-09-09Valves for PipesKGS AA331Hlucinska. 641 747 22 Dolni Benesov, Czech RepublicAndrey ChaykovCzech Republic
3<NA><NA><NA><NA>Fully welded Ball valves for underground useKGS AA332<NA><NA><NA>
4<NA><NA><NA><NA>Globe Valves for PipesKGS AA335<NA><NA><NA>
5제 GA-4호TIANJIN HANXIN PRECISION ELECTRON CO.,LTD2012-09-252015-09-24<NA><NA>XiaoDian Industry park 2Th South Jinwei Road East Beichen Distric TianJin, China<NA>China
6<NA><NA><NA><NA><NA><NA><NA><NA><NA>
7<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8제 GA-5호RATIONAL AG2012-10-102024-10-09Commercial Gas Burning AppliancesKGS AB338Siegfried-Meister-Strasse 1, 86899 Landsberg am Lech, GermanyDr. Peter StadelmannGermany
9제 GA-6호B?hmer(Boehmer) GmbH(1공장)2012-10-152024-10-14Valves for PipesKGS AA331Gedulderweg 95 45549 Sprockh?vel(Sprockhoevel) GermanyTHOMAS B?HMER, PETER PILAPLGermany
등록번호업소명최초등록일만료일등록종류제조기준소재지대표자국가
229제 GA-201호Electrolux Professional AB2022-02-172025-02-16Gas Clothes DryersKGS AB933Ringvagen 14, 34180 Ljungby, SwedenJonas ThulinSweden
230제 GA-202호Electrolux Professional(Thailand) Co., Ltd.2022-02-252025-02-24Gas Clothes DryersKGS AB933169/3 Moo3 Tambol Nonglalok, Amphur Bankhai, Rayong, 21120 ThailandTommaso OrigoTHAILAND
231제 GA-203호Star Manufacturing International Inc.2022-10-142025-11-13Commercial Gas Burning AppliancesKGS AB338265 Hobson Street Smithville, TN 37166 USAScott JordanU.S.A
232제 GA-204호KONAN DENKI CO., LTD2022-09-152025-09-14Gas Clothes DryersKGS AB9332002-2, Konancho koji, Koka shi, Shiga ken, 520-3306, JapanNobuhide KaneharaJapan
233제 GA-205호GAS-FIRED PRODUCTS, INC.2022-07-162025-07-15Gas HeatersKGS AB2311700 Parker Drive, Charlotte NC 28208, USAMr Paul G. HorneU.S.A
234제 GA-206호Welbilt Deutschland GmbH2022-11-132025-11-12Commercial Gas Burning AppliancesKGS AB338Talstrasse 35, 82436 Eglfing, GermanyHans-Werner SchmidtGermany
235제 GA-207호Shinfuji Burner CO., LTD2023-03-022026-03-01Portable Butane StovesKGS AB3361-2-22, Miyukihama, Mito Town, Toyokawa City, Aichi Prefecture, 441-0314, JapanAkira YamamotoJapan
236제 GA-208호Taishan Winmax Metalwork Industries Ltd2023-04-142026-04-13portable Propane gas stovesKGS AB341No.6 Gao Xin Technology Development District, Taishan City, Guangdong, ChinaMichael LiuChina
237제 GA-209호Zhejiang Deermaple Outdoor Products Co., Ltd2023-04-212026-04-20Portable Butane Gas StovesKGS AB336Southeast Industrial Zone,Shuxi Street,Wuyi Town,Jinhua city,Zhejiang ,ChinaQiding LvChina
238제 GA-210호Ji Hua Fa Men(Shenyang)Corporation2023-05-262026-05-25Valves for PipesKGS AA 331No12, Zhongde Street, Shenyang Ecomomic and Technological Development Zone, Liaoning, ChinaHwang Sung OukChina

Duplicate rows

Most frequently occurring

등록번호업소명최초등록일만료일등록종류제조기준소재지대표자국가# duplicates
7<NA><NA><NA><NA><NA><NA><NA><NA><NA>10
1<NA><NA><NA><NA>Fully Welded Ball Valves for Underground UseKGS AA332<NA><NA><NA>3
4<NA><NA><NA><NA>Globe Valves for PipesKGS AA335<NA><NA><NA>3
0<NA><NA><NA><NA>Forced Mixed type Gas BurnersKGS AB931<NA><NA><NA>2
2<NA><NA><NA><NA>Fully welded Ball valves for underground useKGS AA332<NA><NA><NA>2
3<NA><NA><NA><NA>Gas Water HeatersKGS AB135<NA><NA><NA>2
5<NA><NA><NA><NA>Other Gas Burning AppliancesKGS AB935<NA><NA><NA>2
6<NA><NA><NA><NA>Portable Propane Gas StovesKGS AB341<NA><NA><NA>2