Overview

Dataset statistics

Number of variables15
Number of observations881
Missing cells916
Missing cells (%)6.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory103.4 KiB
Average record size in memory120.1 B

Variable types

Text7
Categorical7
DateTime1

Dataset

Description국가기술표준원에서 운영하고 있는 제품안전정보포털(센터)에서 제공하고 있는 제품안전 관련 국내리콜 정보를 공유합니다.
URLhttps://www.data.go.kr/data/15040696/fileData.do

Alerts

리콜종류 is highly overall correlated with 리콜방법 and 1 other fieldsHigh correlation
안전성조사명 is highly overall correlated with 리콜종류 and 1 other fieldsHigh correlation
사업자구분 is highly overall correlated with 제조국가명High correlation
제조국가명 is highly overall correlated with 사업자구분 and 1 other fieldsHigh correlation
제조사국가명 is highly overall correlated with 제조국가명High correlation
리콜방법 is highly overall correlated with 리콜종류 and 1 other fieldsHigh correlation
리콜종류 is highly imbalanced (78.7%)Imbalance
제조국가명 is highly imbalanced (60.8%)Imbalance
제조사국가명 is highly imbalanced (64.0%)Imbalance
인증번호 has 242 (27.5%) missing valuesMissing
제품명 has 14 (1.6%) missing valuesMissing
브랜드명 has 376 (42.7%) missing valuesMissing
법정제품분류 has 19 (2.2%) missing valuesMissing
제조사명 has 256 (29.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 13:31:24.872233
Analysis finished2023-12-12 13:31:27.956593
Duration3.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

인증번호
Text

MISSING 

Distinct461
Distinct (%)72.1%
Missing242
Missing (%)27.5%
Memory size7.0 KiB
2023-12-12T22:31:28.160517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length266
Median length64
Mean length16.838811
Min length3

Characters and Unicode

Total characters10760
Distinct characters226
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

Unique413 ?
Unique (%)64.6%

Sample

1st rowCB063R4097-20001
2nd rowCB063R3279-9001CB063R3279-9001A
3rd rowcb063r3362-9001
4th rowCb063r239-5001
5th rowCB064H045-6001(온라인)
ValueCountFrequency (%)
비대상 31
 
4.9%
br>(인증모델 29
 
4.5%
xh100219-19001a 14
 
2.2%
인증모델 10
 
1.6%
b025r0010-19001 6
 
0.9%
cb061r2539-7001 6
 
0.9%
cb061h326-9001 5
 
0.8%
cb061r3952-8001 5
 
0.8%
cb065j0001-8002 5
 
0.8%
cb063r2734-8001 5
 
0.8%
Other values (450) 523
81.8%
2023-12-12T22:31:28.638658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2182
20.3%
1 1341
 
12.5%
- 702
 
6.5%
2 463
 
4.3%
6 452
 
4.2%
B 400
 
3.7%
3 381
 
3.5%
7 360
 
3.3%
C 334
 
3.1%
R 307
 
2.9%
Other values (216) 3838
35.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6310
58.6%
Uppercase Letter 1800
 
16.7%
Other Letter 934
 
8.7%
Dash Punctuation 702
 
6.5%
Lowercase Letter 336
 
3.1%
Math Symbol 262
 
2.4%
Close Punctuation 142
 
1.3%
Open Punctuation 140
 
1.3%
Other Punctuation 132
 
1.2%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 136
14.6%
모 130
13.9%
델 128
13.7%
증 128
13.7%
대 32
 
3.4%
비 32
 
3.4%
상 32
 
3.4%
이 18
 
1.9%
놀 10
 
1.1%
아 9
 
1.0%
Other values (151) 279
29.9%
Uppercase Letter
ValueCountFrequency (%)
B 400
22.2%
C 334
18.6%
R 307
17.1%
H 183
10.2%
A 149
 
8.3%
U 63
 
3.5%
J 57
 
3.2%
X 43
 
2.4%
L 33
 
1.8%
S 28
 
1.6%
Other values (16) 203
11.3%
Lowercase Letter
ValueCountFrequency (%)
r 140
41.7%
b 137
40.8%
e 9
 
2.7%
i 8
 
2.4%
c 7
 
2.1%
a 6
 
1.8%
t 5
 
1.5%
k 4
 
1.2%
s 4
 
1.2%
o 3
 
0.9%
Other values (8) 13
 
3.9%
Decimal Number
ValueCountFrequency (%)
0 2182
34.6%
1 1341
21.3%
2 463
 
7.3%
6 452
 
7.2%
3 381
 
6.0%
7 360
 
5.7%
9 298
 
4.7%
8 286
 
4.5%
4 280
 
4.4%
5 267
 
4.2%
Other Punctuation
ValueCountFrequency (%)
: 128
97.0%
/ 2
 
1.5%
. 2
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 141
99.3%
] 1
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 139
99.3%
[ 1
 
0.7%
Math Symbol
ValueCountFrequency (%)
< 131
50.0%
> 131
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 702
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7690
71.5%
Latin 2136
 
19.9%
Hangul 934
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 136
14.6%
모 130
13.9%
델 128
13.7%
증 128
13.7%
대 32
 
3.4%
비 32
 
3.4%
상 32
 
3.4%
이 18
 
1.9%
놀 10
 
1.1%
아 9
 
1.0%
Other values (151) 279
29.9%
Latin
ValueCountFrequency (%)
B 400
18.7%
C 334
15.6%
R 307
14.4%
H 183
8.6%
A 149
 
7.0%
r 140
 
6.6%
b 137
 
6.4%
U 63
 
2.9%
J 57
 
2.7%
X 43
 
2.0%
Other values (34) 323
15.1%
Common
ValueCountFrequency (%)
0 2182
28.4%
1 1341
17.4%
- 702
 
9.1%
2 463
 
6.0%
6 452
 
5.9%
3 381
 
5.0%
7 360
 
4.7%
9 298
 
3.9%
8 286
 
3.7%
4 280
 
3.6%
Other values (11) 945
12.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9826
91.3%
Hangul 934
 
8.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2182
22.2%
1 1341
13.6%
- 702
 
7.1%
2 463
 
4.7%
6 452
 
4.6%
B 400
 
4.1%
3 381
 
3.9%
7 360
 
3.7%
C 334
 
3.4%
R 307
 
3.1%
Other values (55) 2904
29.6%
Hangul
ValueCountFrequency (%)
인 136
14.6%
모 130
13.9%
델 128
13.7%
증 128
13.7%
대 32
 
3.4%
비 32
 
3.4%
상 32
 
3.4%
이 18
 
1.9%
놀 10
 
1.1%
아 9
 
1.0%
Other values (151) 279
29.9%

모델명
Text

Distinct837
Distinct (%)95.9%
Missing8
Missing (%)0.9%
Memory size7.0 KiB
2023-12-12T22:31:29.095927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length144
Median length47
Mean length13.79496
Min length2

Characters and Unicode

Total characters12043
Distinct characters629
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique813 ?
Unique (%)93.1%

Sample

1st row하프토이MR-T002
2nd row구체관절인형(미니프린세스돌30cm)
3rd row꾸러기상자
4th row시크릿쥬쥬핸드백쥬얼리세트
5th row여러가지직업입체북만들기
ValueCountFrequency (%)
23
 
1.9%
df15plus모델중일부제품(사업자문의 14
 
1.2%
서랍장 13
 
1.1%
5단 12
 
1.0%
800 6
 
0.5%
수입 3
 
0.3%
프로 3
 
0.3%
마스터 3
 
0.3%
세트 3
 
0.3%
슈레드 3
 
0.3%
Other values (1050) 1099
93.0%
2023-12-12T22:31:29.678881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 608
 
5.0%
1 416
 
3.5%
315
 
2.6%
- 299
 
2.5%
( 253
 
2.1%
) 249
 
2.1%
2 225
 
1.9%
S 224
 
1.9%
5 200
 
1.7%
A 184
 
1.5%
Other values (619) 9070
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5340
44.3%
Uppercase Letter 2751
22.8%
Decimal Number 2173
18.0%
Lowercase Letter 515
 
4.3%
Space Separator 315
 
2.6%
Dash Punctuation 299
 
2.5%
Open Punctuation 263
 
2.2%
Close Punctuation 259
 
2.2%
Other Punctuation 104
 
0.9%
Connector Punctuation 20
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 182
 
3.4%
라 173
 
3.2%
리 125
 
2.3%
트 116
 
2.2%
스 114
 
2.1%
아 97
 
1.8%
슬 95
 
1.8%
임 89
 
1.7%
품 73
 
1.4%
드 71
 
1.3%
Other values (544) 4205
78.7%
Uppercase Letter
ValueCountFrequency (%)
S 224
 
8.1%
A 184
 
6.7%
E 181
 
6.6%
L 173
 
6.3%
B 162
 
5.9%
D 146
 
5.3%
P 143
 
5.2%
T 138
 
5.0%
C 137
 
5.0%
K 134
 
4.9%
Other values (16) 1129
41.0%
Lowercase Letter
ValueCountFrequency (%)
l 51
 
9.9%
e 47
 
9.1%
i 40
 
7.8%
o 36
 
7.0%
p 35
 
6.8%
s 33
 
6.4%
r 31
 
6.0%
a 29
 
5.6%
u 28
 
5.4%
m 25
 
4.9%
Other values (15) 160
31.1%
Decimal Number
ValueCountFrequency (%)
0 608
28.0%
1 416
19.1%
2 225
 
10.4%
5 200
 
9.2%
3 156
 
7.2%
8 132
 
6.1%
6 129
 
5.9%
7 104
 
4.8%
9 103
 
4.7%
4 100
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/ 59
56.7%
. 12
 
11.5%
: 11
 
10.6%
* 11
 
10.6%
! 7
 
6.7%
& 4
 
3.8%
Open Punctuation
ValueCountFrequency (%)
( 253
96.2%
[ 10
 
3.8%
Close Punctuation
ValueCountFrequency (%)
) 249
96.1%
] 10
 
3.9%
Space Separator
ValueCountFrequency (%)
315
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 299
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 20
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5340
44.3%
Common 3437
28.5%
Latin 3266
27.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 182
 
3.4%
라 173
 
3.2%
리 125
 
2.3%
트 116
 
2.2%
스 114
 
2.1%
아 97
 
1.8%
슬 95
 
1.8%
임 89
 
1.7%
품 73
 
1.4%
드 71
 
1.3%
Other values (544) 4205
78.7%
Latin
ValueCountFrequency (%)
S 224
 
6.9%
A 184
 
5.6%
E 181
 
5.5%
L 173
 
5.3%
B 162
 
5.0%
D 146
 
4.5%
P 143
 
4.4%
T 138
 
4.2%
C 137
 
4.2%
K 134
 
4.1%
Other values (41) 1644
50.3%
Common
ValueCountFrequency (%)
0 608
17.7%
1 416
12.1%
315
9.2%
- 299
8.7%
( 253
7.4%
) 249
7.2%
2 225
 
6.5%
5 200
 
5.8%
3 156
 
4.5%
8 132
 
3.8%
Other values (14) 584
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6703
55.7%
Hangul 5340
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 608
 
9.1%
1 416
 
6.2%
315
 
4.7%
- 299
 
4.5%
( 253
 
3.8%
) 249
 
3.7%
2 225
 
3.4%
S 224
 
3.3%
5 200
 
3.0%
A 184
 
2.7%
Other values (65) 3730
55.6%
Hangul
ValueCountFrequency (%)
이 182
 
3.4%
라 173
 
3.2%
리 125
 
2.3%
트 116
 
2.2%
스 114
 
2.1%
아 97
 
1.8%
슬 95
 
1.8%
임 89
 
1.7%
품 73
 
1.4%
드 71
 
1.3%
Other values (544) 4205
78.7%

제품명
Text

MISSING 

Distinct225
Distinct (%)26.0%
Missing14
Missing (%)1.6%
Memory size7.0 KiB
2023-12-12T22:31:29.900861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length28
Mean length9.4971165
Min length2

Characters and Unicode

Total characters8234
Distinct characters320
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

Unique114 ?
Unique (%)13.1%

Sample

1st row완구
2nd row완구
3rd row완구
4th row완구
5th row완구
ValueCountFrequency (%)
액체괴물(완구 100
 
8.2%
완구 53
 
4.3%
아동용섬유제품 52
 
4.2%
및 36
 
2.9%
섬유제품 28
 
2.3%
직류전원장치 25
 
2.0%
일반조명기구 24
 
2.0%
가구 21
 
1.7%
완구(완구 20
 
1.6%
어린이용가죽제품 16
 
1.3%
Other values (288) 849
69.4%
2023-12-12T22:31:30.337022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
용 470
 
5.7%
) 464
 
5.6%
( 460
 
5.6%
구 432
 
5.2%
360
 
4.4%
완 276
 
3.4%
품 272
 
3.3%
이 268
 
3.3%
기 252
 
3.1%
제 236
 
2.9%
Other values (310) 4744
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6682
81.2%
Close Punctuation 465
 
5.6%
Open Punctuation 461
 
5.6%
Space Separator 360
 
4.4%
Uppercase Letter 116
 
1.4%
Decimal Number 72
 
0.9%
Lowercase Letter 71
 
0.9%
Other Punctuation 5
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 470
 
7.0%
구 432
 
6.5%
완 276
 
4.1%
품 272
 
4.1%
이 268
 
4.0%
기 252
 
3.8%
제 236
 
3.5%
유 197
 
2.9%
어 188
 
2.8%
아 181
 
2.7%
Other values (249) 3910
58.5%
Uppercase Letter
ValueCountFrequency (%)
L 15
12.9%
D 13
11.2%
E 12
10.3%
A 12
10.3%
S 8
 
6.9%
C 7
 
6.0%
I 7
 
6.0%
B 6
 
5.2%
T 5
 
4.3%
K 4
 
3.4%
Other values (15) 27
23.3%
Lowercase Letter
ValueCountFrequency (%)
m 31
43.7%
t 6
 
8.5%
o 5
 
7.0%
i 5
 
7.0%
e 4
 
5.6%
a 4
 
5.6%
b 2
 
2.8%
d 2
 
2.8%
p 2
 
2.8%
k 2
 
2.8%
Other values (7) 8
 
11.3%
Decimal Number
ValueCountFrequency (%)
2 19
26.4%
7 18
25.0%
6 16
22.2%
0 7
 
9.7%
1 6
 
8.3%
9 2
 
2.8%
3 2
 
2.8%
5 1
 
1.4%
4 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
· 2
40.0%
& 1
20.0%
. 1
20.0%
/ 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 464
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 460
99.8%
[ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
360
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6682
81.2%
Common 1365
 
16.6%
Latin 187
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 470
 
7.0%
구 432
 
6.5%
완 276
 
4.1%
품 272
 
4.1%
이 268
 
4.0%
기 252
 
3.8%
제 236
 
3.5%
유 197
 
2.9%
어 188
 
2.8%
아 181
 
2.7%
Other values (249) 3910
58.5%
Latin
ValueCountFrequency (%)
m 31
16.6%
L 15
 
8.0%
D 13
 
7.0%
E 12
 
6.4%
A 12
 
6.4%
S 8
 
4.3%
C 7
 
3.7%
I 7
 
3.7%
t 6
 
3.2%
B 6
 
3.2%
Other values (32) 70
37.4%
Common
ValueCountFrequency (%)
) 464
34.0%
( 460
33.7%
360
26.4%
2 19
 
1.4%
7 18
 
1.3%
6 16
 
1.2%
0 7
 
0.5%
1 6
 
0.4%
9 2
 
0.1%
- 2
 
0.1%
Other values (9) 11
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6682
81.2%
ASCII 1550
 
18.8%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
용 470
 
7.0%
구 432
 
6.5%
완 276
 
4.1%
품 272
 
4.1%
이 268
 
4.0%
기 252
 
3.8%
제 236
 
3.5%
유 197
 
2.9%
어 188
 
2.8%
아 181
 
2.7%
Other values (249) 3910
58.5%
ASCII
ValueCountFrequency (%)
) 464
29.9%
( 460
29.7%
360
23.2%
m 31
 
2.0%
2 19
 
1.2%
7 18
 
1.2%
6 16
 
1.0%
L 15
 
1.0%
D 13
 
0.8%
E 12
 
0.8%
Other values (50) 142
 
9.2%
None
ValueCountFrequency (%)
· 2
100.0%

브랜드명
Text

MISSING 

Distinct323
Distinct (%)64.0%
Missing376
Missing (%)42.7%
Memory size7.0 KiB
2023-12-12T22:31:30.650083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length42
Mean length5.1980198
Min length1

Characters and Unicode

Total characters2625
Distinct characters427
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique276 ?
Unique (%)54.7%

Sample

1st row하프토이
2nd row키즈커즈
3rd row시크릿쥬쥬
4th row마마루
5th row리엔더
ValueCountFrequency (%)
115
 
22.2%
전지 14
 
2.7%
오닐 6
 
1.2%
jeep 4
 
0.8%
세이지폴 4
 
0.8%
에뜨와 3
 
0.6%
스포츠용구명복(부력보조복 3
 
0.6%
slimy 3
 
0.6%
압소바 3
 
0.6%
레노마키즈 2
 
0.4%
Other values (325) 362
69.7%
2023-12-12T22:31:31.053461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 120
 
4.6%
스 67
 
2.6%
이 56
 
2.1%
즈 48
 
1.8%
리 42
 
1.6%
A 39
 
1.5%
E 37
 
1.4%
키 37
 
1.4%
e 35
 
1.3%
아 35
 
1.3%
Other values (417) 2109
80.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1590
60.6%
Uppercase Letter 425
 
16.2%
Lowercase Letter 327
 
12.5%
Dash Punctuation 120
 
4.6%
Decimal Number 81
 
3.1%
Other Punctuation 25
 
1.0%
Open Punctuation 20
 
0.8%
Close Punctuation 20
 
0.8%
Space Separator 15
 
0.6%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 67
 
4.2%
이 56
 
3.5%
즈 48
 
3.0%
리 42
 
2.6%
키 37
 
2.3%
아 35
 
2.2%
프 25
 
1.6%
전 24
 
1.5%
지 23
 
1.4%
베 21
 
1.3%
Other values (347) 1212
76.2%
Uppercase Letter
ValueCountFrequency (%)
A 39
 
9.2%
E 37
 
8.7%
L 32
 
7.5%
T 29
 
6.8%
N 27
 
6.4%
O 27
 
6.4%
S 21
 
4.9%
B 20
 
4.7%
I 20
 
4.7%
D 16
 
3.8%
Other values (16) 157
36.9%
Lowercase Letter
ValueCountFrequency (%)
e 35
 
10.7%
i 31
 
9.5%
n 29
 
8.9%
a 27
 
8.3%
o 23
 
7.0%
g 19
 
5.8%
t 19
 
5.8%
l 19
 
5.8%
h 16
 
4.9%
r 15
 
4.6%
Other values (14) 94
28.7%
Decimal Number
ValueCountFrequency (%)
0 29
35.8%
5 14
17.3%
2 14
17.3%
1 13
16.0%
3 4
 
4.9%
9 4
 
4.9%
6 2
 
2.5%
4 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 17
68.0%
/ 4
 
16.0%
& 3
 
12.0%
' 1
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 17
85.0%
[ 3
 
15.0%
Close Punctuation
ValueCountFrequency (%)
) 17
85.0%
] 3
 
15.0%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1590
60.6%
Latin 752
28.6%
Common 283
 
10.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 67
 
4.2%
이 56
 
3.5%
즈 48
 
3.0%
리 42
 
2.6%
키 37
 
2.3%
아 35
 
2.2%
프 25
 
1.6%
전 24
 
1.5%
지 23
 
1.4%
베 21
 
1.3%
Other values (347) 1212
76.2%
Latin
ValueCountFrequency (%)
A 39
 
5.2%
E 37
 
4.9%
e 35
 
4.7%
L 32
 
4.3%
i 31
 
4.1%
n 29
 
3.9%
T 29
 
3.9%
N 27
 
3.6%
a 27
 
3.6%
O 27
 
3.6%
Other values (40) 439
58.4%
Common
ValueCountFrequency (%)
- 120
42.4%
0 29
 
10.2%
( 17
 
6.0%
) 17
 
6.0%
. 17
 
6.0%
15
 
5.3%
5 14
 
4.9%
2 14
 
4.9%
1 13
 
4.6%
3 4
 
1.4%
Other values (10) 23
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1590
60.6%
ASCII 1033
39.4%
Punctuation 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 120
 
11.6%
A 39
 
3.8%
E 37
 
3.6%
e 35
 
3.4%
L 32
 
3.1%
i 31
 
3.0%
0 29
 
2.8%
n 29
 
2.8%
T 29
 
2.8%
N 27
 
2.6%
Other values (58) 625
60.5%
Hangul
ValueCountFrequency (%)
스 67
 
4.2%
이 56
 
3.5%
즈 48
 
3.0%
리 42
 
2.6%
키 37
 
2.3%
아 35
 
2.2%
프 25
 
1.6%
전 24
 
1.5%
지 23
 
1.4%
베 21
 
1.3%
Other values (347) 1212
76.2%
Punctuation
ValueCountFrequency (%)
“ 1
50.0%
” 1
50.0%

사업자구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
수입
559 
제조
304 
판매
 
10
<NA>
 
8

Length

Max length4
Median length2
Mean length2.0181612
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수입
2nd row수입
3rd row수입
4th row수입
5th row제조

Common Values

ValueCountFrequency (%)
수입 559
63.5%
제조 304
34.5%
판매 10
 
1.1%
<NA> 8
 
0.9%

Length

2023-12-12T22:31:31.206306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:31:31.324329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수입 559
63.5%
제조 304
34.5%
판매 10
 
1.1%
na 8
 
0.9%

법정제품분류
Text

MISSING 

Distinct149
Distinct (%)17.3%
Missing19
Missing (%)2.2%
Memory size7.0 KiB
2023-12-12T22:31:31.479592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length86
Median length40
Mean length16.301624
Min length2

Characters and Unicode

Total characters14052
Distinct characters251
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)7.2%

Sample

1st row어린이>완구
2nd row어린이>완구
3rd row어린이>완구
4th row어린이>완구
5th row어린이>완구
ValueCountFrequency (%)
완구>기타완구>기타 112
 
8.8%
어린이>완구 104
 
8.2%
어린이>아동용섬유제품 78
 
6.1%
및 49
 
3.9%
어린이>어린이용 32
 
2.5%
조명기기>일반조명기구>led등기구 30
 
2.4%
섬유제품 28
 
2.2%
캐비닛에 26
 
2.0%
파일링 26
 
2.0%
사무용 26
 
2.0%
Other values (184) 759
59.8%
2023-12-12T22:31:31.817231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
> 1291
 
9.2%
기 988
 
7.0%
이 734
 
5.2%
용 659
 
4.7%
구 580
 
4.1%
어 552
 
3.9%
린 544
 
3.9%
408
 
2.9%
전 394
 
2.8%
완 348
 
2.5%
Other values (241) 7554
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11549
82.2%
Math Symbol 1291
 
9.2%
Space Separator 408
 
2.9%
Decimal Number 207
 
1.5%
Uppercase Letter 144
 
1.0%
Lowercase Letter 134
 
1.0%
Open Punctuation 130
 
0.9%
Close Punctuation 130
 
0.9%
Other Punctuation 42
 
0.3%
Dash Punctuation 17
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 988
 
8.6%
이 734
 
6.4%
용 659
 
5.7%
구 580
 
5.0%
어 552
 
4.8%
린 544
 
4.7%
전 394
 
3.4%
완 348
 
3.0%
품 324
 
2.8%
타 273
 
2.4%
Other values (221) 6153
53.3%
Uppercase Letter
ValueCountFrequency (%)
L 43
29.9%
D 43
29.9%
E 43
29.9%
P 4
 
2.8%
V 4
 
2.8%
C 4
 
2.8%
A 3
 
2.1%
Decimal Number
ValueCountFrequency (%)
2 65
31.4%
7 65
31.4%
6 63
30.4%
0 8
 
3.9%
1 4
 
1.9%
4 2
 
1.0%
Math Symbol
ValueCountFrequency (%)
> 1291
100.0%
Space Separator
ValueCountFrequency (%)
408
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 134
100.0%
Open Punctuation
ValueCountFrequency (%)
( 130
100.0%
Close Punctuation
ValueCountFrequency (%)
) 130
100.0%
Other Punctuation
ValueCountFrequency (%)
· 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11549
82.2%
Common 2225
 
15.8%
Latin 278
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 988
 
8.6%
이 734
 
6.4%
용 659
 
5.7%
구 580
 
5.0%
어 552
 
4.8%
린 544
 
4.7%
전 394
 
3.4%
완 348
 
3.0%
품 324
 
2.8%
타 273
 
2.4%
Other values (221) 6153
53.3%
Common
ValueCountFrequency (%)
> 1291
58.0%
408
 
18.3%
( 130
 
5.8%
) 130
 
5.8%
2 65
 
2.9%
7 65
 
2.9%
6 63
 
2.8%
· 42
 
1.9%
- 17
 
0.8%
0 8
 
0.4%
Other values (2) 6
 
0.3%
Latin
ValueCountFrequency (%)
m 134
48.2%
L 43
 
15.5%
D 43
 
15.5%
E 43
 
15.5%
P 4
 
1.4%
V 4
 
1.4%
C 4
 
1.4%
A 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11549
82.2%
ASCII 2461
 
17.5%
None 42
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
> 1291
52.5%
408
 
16.6%
m 134
 
5.4%
( 130
 
5.3%
) 130
 
5.3%
2 65
 
2.6%
7 65
 
2.6%
6 63
 
2.6%
L 43
 
1.7%
D 43
 
1.7%
Other values (9) 89
 
3.6%
Hangul
ValueCountFrequency (%)
기 988
 
8.6%
이 734
 
6.4%
용 659
 
5.7%
구 580
 
5.0%
어 552
 
4.8%
린 544
 
4.7%
전 394
 
3.4%
완 348
 
3.0%
품 324
 
2.8%
타 273
 
2.4%
Other values (221) 6153
53.3%
None
ValueCountFrequency (%)
· 42
100.0%

리콜종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
명령에따른리콜
835 
자발적리콜
 
35
<NA>
 
11

Length

Max length7
Median length7
Mean length6.8830874
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
명령에따른리콜 835
94.8%
자발적리콜 35
 
4.0%
<NA> 11
 
1.2%

Length

2023-12-12T22:31:31.970448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:31:32.100250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
명령에따른리콜 835
94.8%
자발적리콜 35
 
4.0%
na 11
 
1.2%

리콜사업자명
Text

Distinct663
Distinct (%)75.3%
Missing1
Missing (%)0.1%
Memory size7.0 KiB
2023-12-12T22:31:32.284908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length23
Mean length6.7193182
Min length2

Characters and Unicode

Total characters5913
Distinct characters456
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique550 ?
Unique (%)62.5%

Sample

1st row주식회사해브잇올
2nd row와니월드
3rd row(주)메디블루
4th row(주)올림포스
5th row(주)코너스톤에스에이치
ValueCountFrequency (%)
주식회사 25
 
2.7%
자연과학습 9
 
1.0%
주)필박스 8
 
0.9%
은혜사 7
 
0.8%
주)종이나라 7
 
0.8%
주)점프 7
 
0.8%
㈜프랜즈코리아 7
 
0.8%
주)오엔케이알트레이딩 6
 
0.6%
주)비앤씨 6
 
0.6%
러브미슬라임 5
 
0.5%
Other values (670) 840
90.6%
2023-12-12T22:31:32.767052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 385
 
6.5%
( 308
 
5.2%
) 307
 
5.2%
이 259
 
4.4%
스 207
 
3.5%
㈜ 154
 
2.6%
아 133
 
2.2%
사 133
 
2.2%
리 124
 
2.1%
회 97
 
1.6%
Other values (446) 3806
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4813
81.4%
Open Punctuation 308
 
5.2%
Close Punctuation 307
 
5.2%
Uppercase Letter 165
 
2.8%
Other Symbol 154
 
2.6%
Lowercase Letter 82
 
1.4%
Space Separator 47
 
0.8%
Other Punctuation 22
 
0.4%
Decimal Number 13
 
0.2%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 385
 
8.0%
이 259
 
5.4%
스 207
 
4.3%
아 133
 
2.8%
사 133
 
2.8%
리 124
 
2.6%
회 97
 
2.0%
식 94
 
2.0%
코 90
 
1.9%
에 82
 
1.7%
Other values (387) 3209
66.7%
Uppercase Letter
ValueCountFrequency (%)
I 13
 
7.9%
E 13
 
7.9%
K 13
 
7.9%
C 11
 
6.7%
T 11
 
6.7%
S 11
 
6.7%
O 10
 
6.1%
L 9
 
5.5%
G 8
 
4.8%
D 8
 
4.8%
Other values (13) 58
35.2%
Lowercase Letter
ValueCountFrequency (%)
i 12
14.6%
o 10
12.2%
t 9
11.0%
n 9
11.0%
d 5
 
6.1%
e 5
 
6.1%
c 4
 
4.9%
b 4
 
4.9%
a 4
 
4.9%
r 3
 
3.7%
Other values (10) 17
20.7%
Decimal Number
ValueCountFrequency (%)
2 4
30.8%
0 2
15.4%
5 2
15.4%
4 1
 
7.7%
1 1
 
7.7%
9 1
 
7.7%
6 1
 
7.7%
8 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 12
54.5%
& 9
40.9%
/ 1
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 308
100.0%
Close Punctuation
ValueCountFrequency (%)
) 307
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 154
100.0%
Space Separator
ValueCountFrequency (%)
47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4967
84.0%
Common 699
 
11.8%
Latin 247
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 385
 
7.8%
이 259
 
5.2%
스 207
 
4.2%
㈜ 154
 
3.1%
아 133
 
2.7%
사 133
 
2.7%
리 124
 
2.5%
회 97
 
2.0%
식 94
 
1.9%
코 90
 
1.8%
Other values (388) 3291
66.3%
Latin
ValueCountFrequency (%)
I 13
 
5.3%
E 13
 
5.3%
K 13
 
5.3%
i 12
 
4.9%
C 11
 
4.5%
T 11
 
4.5%
S 11
 
4.5%
o 10
 
4.0%
O 10
 
4.0%
t 9
 
3.6%
Other values (33) 134
54.3%
Common
ValueCountFrequency (%)
( 308
44.1%
) 307
43.9%
47
 
6.7%
. 12
 
1.7%
& 9
 
1.3%
2 4
 
0.6%
0 2
 
0.3%
- 2
 
0.3%
5 2
 
0.3%
4 1
 
0.1%
Other values (5) 5
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4813
81.4%
ASCII 946
 
16.0%
None 154
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 385
 
8.0%
이 259
 
5.4%
스 207
 
4.3%
아 133
 
2.8%
사 133
 
2.8%
리 124
 
2.6%
회 97
 
2.0%
식 94
 
2.0%
코 90
 
1.9%
에 82
 
1.7%
Other values (387) 3209
66.7%
ASCII
ValueCountFrequency (%)
( 308
32.6%
) 307
32.5%
47
 
5.0%
I 13
 
1.4%
E 13
 
1.4%
K 13
 
1.4%
i 12
 
1.3%
. 12
 
1.3%
C 11
 
1.2%
T 11
 
1.2%
Other values (48) 199
21.0%
None
ValueCountFrequency (%)
㈜ 154
100.0%

제조국가명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct19
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
국외>아시아지역>중국
478 
국내>아시아지역>대한민국
308 
국외>아시아지역>베트남
 
28
<NA>
 
26
미상>미상>미상
 
17
Other values (14)
 
24

Length

Max length14
Median length11
Mean length11.482406
Min length4

Unique

Unique9 ?
Unique (%)1.0%

Sample

1st row국외>아시아지역>중국
2nd row국외>아시아지역>중국
3rd row국외>아시아지역>중국
4th row국외>아시아지역>중국
5th row국내>아시아지역>대한민국

Common Values

ValueCountFrequency (%)
국외>아시아지역>중국 478
54.3%
국내>아시아지역>대한민국 308
35.0%
국외>아시아지역>베트남 28
 
3.2%
<NA> 26
 
3.0%
미상>미상>미상 17
 
1.9%
국외>아시아지역>일본 4
 
0.5%
국외>아시아지역>인도네시아 3
 
0.3%
국외>그밖의지역>대만 3
 
0.3%
국외>미주지역>브라질 3
 
0.3%
국외>미주지역>미국 2
 
0.2%
Other values (9) 9
 
1.0%

Length

2023-12-12T22:31:32.939156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
국외>아시아지역>중국 478
54.1%
국내>아시아지역>대한민국 308
34.9%
국외>아시아지역>베트남 28
 
3.2%
na 26
 
2.9%
미상>미상>미상 17
 
1.9%
국외>아시아지역>일본 4
 
0.5%
국외>아시아지역>인도네시아 3
 
0.3%
국외>그밖의지역>대만 3
 
0.3%
국외>미주지역>브라질 3
 
0.3%
국외>미주지역>미국 2
 
0.2%
Other values (11) 11
 
1.2%

제조사명
Text

MISSING 

Distinct454
Distinct (%)72.6%
Missing256
Missing (%)29.1%
Memory size7.0 KiB
2023-12-12T22:31:33.207909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length42
Mean length8.5296
Min length2

Characters and Unicode

Total characters5331
Distinct characters420
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique368 ?
Unique (%)58.9%

Sample

1st row주식회사해브잇올
2nd rowYIMEiCRAFTWORKTOYSFACTORY
3rd row(주)메디블루
4th row(주)올림포스
5th row(주)코너스톤에스에이치
ValueCountFrequency (%)
자연과학습 9
 
1.4%
주)필박스 8
 
1.3%
주)종이나라 7
 
1.1%
㈜프랜즈코리아 7
 
1.1%
은혜사 7
 
1.1%
주)점프 7
 
1.1%
winningindustrialco.ltd 6
 
1.0%
러브미슬라임 5
 
0.8%
주)비앤씨 5
 
0.8%
주)윙하우스 5
 
0.8%
Other values (444) 559
89.4%
2023-12-12T22:31:33.668318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 250
 
4.7%
) 213
 
4.0%
( 211
 
4.0%
이 170
 
3.2%
스 130
 
2.4%
n 93
 
1.7%
I 91
 
1.7%
O 87
 
1.6%
C 86
 
1.6%
사 81
 
1.5%
Other values (410) 3919
73.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3041
57.0%
Uppercase Letter 1093
 
20.5%
Lowercase Letter 637
 
11.9%
Close Punctuation 213
 
4.0%
Open Punctuation 211
 
4.0%
Other Symbol 65
 
1.2%
Other Punctuation 64
 
1.2%
Dash Punctuation 4
 
0.1%
Math Symbol 2
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 250
 
8.2%
이 170
 
5.6%
스 130
 
4.3%
사 81
 
2.7%
아 75
 
2.5%
코 57
 
1.9%
리 52
 
1.7%
회 49
 
1.6%
식 47
 
1.5%
트 47
 
1.5%
Other values (348) 2083
68.5%
Uppercase Letter
ValueCountFrequency (%)
I 91
 
8.3%
O 87
 
8.0%
C 86
 
7.9%
T 79
 
7.2%
N 73
 
6.7%
A 73
 
6.7%
L 66
 
6.0%
E 66
 
6.0%
S 56
 
5.1%
G 49
 
4.5%
Other values (16) 367
33.6%
Lowercase Letter
ValueCountFrequency (%)
n 93
14.6%
i 63
9.9%
o 61
9.6%
e 48
 
7.5%
t 46
 
7.2%
g 40
 
6.3%
d 40
 
6.3%
a 38
 
6.0%
l 33
 
5.2%
s 33
 
5.2%
Other values (15) 142
22.3%
Other Punctuation
ValueCountFrequency (%)
. 51
79.7%
& 8
 
12.5%
/ 3
 
4.7%
。 1
 
1.6%
: 1
 
1.6%
Close Punctuation
ValueCountFrequency (%)
) 213
100.0%
Open Punctuation
ValueCountFrequency (%)
( 211
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
> 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3086
57.9%
Latin 1730
32.5%
Common 495
 
9.3%
Han 20
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 250
 
8.1%
이 170
 
5.5%
스 130
 
4.2%
사 81
 
2.6%
아 75
 
2.4%
㈜ 65
 
2.1%
코 57
 
1.8%
리 52
 
1.7%
회 49
 
1.6%
식 47
 
1.5%
Other values (333) 2110
68.4%
Latin
ValueCountFrequency (%)
n 93
 
5.4%
I 91
 
5.3%
O 87
 
5.0%
C 86
 
5.0%
T 79
 
4.6%
N 73
 
4.2%
A 73
 
4.2%
L 66
 
3.8%
E 66
 
3.8%
i 63
 
3.6%
Other values (41) 953
55.1%
Han
ValueCountFrequency (%)
司 2
 
10.0%
公 2
 
10.0%
限 2
 
10.0%
有 2
 
10.0%
田 1
 
5.0%
屋 1
 
5.0%
高 1
 
5.0%
鞋 1
 
5.0%
金 1
 
5.0%
大 1
 
5.0%
Other values (6) 6
30.0%
Common
ValueCountFrequency (%)
) 213
43.0%
( 211
42.6%
. 51
 
10.3%
& 8
 
1.6%
- 4
 
0.8%
/ 3
 
0.6%
> 2
 
0.4%
2 1
 
0.2%
。 1
 
0.2%
: 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3021
56.7%
ASCII 2224
41.7%
None 66
 
1.2%
CJK 20
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 250
 
8.3%
이 170
 
5.6%
스 130
 
4.3%
사 81
 
2.7%
아 75
 
2.5%
코 57
 
1.9%
리 52
 
1.7%
회 49
 
1.6%
식 47
 
1.6%
트 47
 
1.6%
Other values (332) 2063
68.3%
ASCII
ValueCountFrequency (%)
) 213
 
9.6%
( 211
 
9.5%
n 93
 
4.2%
I 91
 
4.1%
O 87
 
3.9%
C 86
 
3.9%
T 79
 
3.6%
N 73
 
3.3%
A 73
 
3.3%
L 66
 
3.0%
Other values (50) 1152
51.8%
None
ValueCountFrequency (%)
㈜ 65
98.5%
。 1
 
1.5%
CJK
ValueCountFrequency (%)
司 2
 
10.0%
公 2
 
10.0%
限 2
 
10.0%
有 2
 
10.0%
田 1
 
5.0%
屋 1
 
5.0%
高 1
 
5.0%
鞋 1
 
5.0%
金 1
 
5.0%
大 1
 
5.0%
Other values (6) 6
30.0%

제조사국가명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct13
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
국내>아시아지역>대한민국
552 
<NA>
262 
국외>아시아지역>중국
 
53
국외>아시아지역>일본
 
3
국외>유럽지역>독일
 
2
Other values (8)
 
9

Length

Max length13
Median length13
Mean length10.163451
Min length4

Unique

Unique7 ?
Unique (%)0.8%

Sample

1st row국내>아시아지역>대한민국
2nd row국외>아시아지역>중국
3rd row국내>아시아지역>대한민국
4th row국내>아시아지역>대한민국
5th row국내>아시아지역>대한민국

Common Values

ValueCountFrequency (%)
국내>아시아지역>대한민국 552
62.7%
<NA> 262
29.7%
국외>아시아지역>중국 53
 
6.0%
국외>아시아지역>일본 3
 
0.3%
국외>유럽지역>독일 2
 
0.2%
국외>그밖의지역>대만 2
 
0.2%
국외>유럽지역>덴마크 1
 
0.1%
국외>아시아지역>싱가포르 1
 
0.1%
대한민국 1
 
0.1%
국외>아시아지역>베트남 1
 
0.1%
Other values (3) 3
 
0.3%

Length

2023-12-12T22:31:33.826066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
국내>아시아지역>대한민국 552
62.7%
na 262
29.7%
국외>아시아지역>중국 53
 
6.0%
국외>아시아지역>일본 3
 
0.3%
국외>유럽지역>독일 2
 
0.2%
국외>그밖의지역>대만 2
 
0.2%
국외>유럽지역>덴마크 1
 
0.1%
국외>아시아지역>싱가포르 1
 
0.1%
대한민국 1
 
0.1%
국외>아시아지역>베트남 1
 
0.1%
Other values (3) 3
 
0.3%

리콜방법
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
교환수거
381 
<NA>
226 
환불
130 
교환수거수리환불
80 
교환
46 
Other values (11)
 
18

Length

Max length14
Median length4
Mean length4.0113507
Min length2

Unique

Unique5 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
교환수거 381
43.2%
<NA> 226
25.7%
환불 130
 
14.8%
교환수거수리환불 80
 
9.1%
교환 46
 
5.2%
수거환불파기제조유통금지 3
 
0.3%
수거환불제조유통금지 2
 
0.2%
수거 2
 
0.2%
파기 2
 
0.2%
수리 2
 
0.2%
Other values (6) 7
 
0.8%

Length

2023-12-12T22:31:33.992684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교환수거 381
43.2%
na 226
25.7%
환불 130
 
14.8%
교환수거수리환불 80
 
9.1%
교환 46
 
5.2%
수거환불파기제조유통금지 3
 
0.3%
수거환불제조유통금지 2
 
0.2%
수거 2
 
0.2%
파기 2
 
0.2%
수리 2
 
0.2%
Other values (6) 7
 
0.8%

위해유형
Categorical

Distinct13
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
유해물질
493 
화재및화상
98 
감전
61 
질식
 
46
제조불량
 
44
Other values (8)
139 

Length

Max length7
Median length4
Mean length3.7094211
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유해물질 493
56.0%
화재및화상 98
 
11.1%
감전 61
 
6.9%
질식 46
 
5.2%
제조불량 44
 
5.0%
기타 42
 
4.8%
낙상 38
 
4.3%
화재 및 화상 20
 
2.3%
<NA> 15
 
1.7%
열상 9
 
1.0%
Other values (3) 15
 
1.7%

Length

2023-12-12T22:31:34.121887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
유해물질 493
53.5%
화재및화상 98
 
10.6%
감전 61
 
6.6%
질식 46
 
5.0%
제조불량 44
 
4.8%
기타 42
 
4.6%
낙상 38
 
4.1%
화재 20
 
2.2%
및 20
 
2.2%
화상 20
 
2.2%
Other values (5) 39
 
4.2%

안전성조사명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
4차
140 
액체괴물
100 
1차
99 
2차
87 
3차
67 
Other values (26)
388 

Length

Max length48
Median length2
Mean length2.7332577
Min length1

Unique

Unique7 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
4차 140
15.9%
액체괴물 100
11.4%
1차 99
11.2%
2차 87
9.9%
3차 67
7.6%
3 55
 
6.2%
4 54
 
6.1%
2 54
 
6.1%
6차 51
 
5.8%
<NA> 28
 
3.2%
Other values (21) 146
16.6%

Length

2023-12-12T22:31:34.259101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4차 140
15.6%
1차 116
12.9%
액체괴물 100
11.1%
2차 87
9.7%
3차 67
7.4%
3 55
 
6.1%
4 54
 
6.0%
2 54
 
6.0%
6차 51
 
5.7%
na 28
 
3.1%
Other values (22) 148
16.4%

등록일
Date

Distinct86
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
Minimum2019-10-22 00:00:00
Maximum2022-07-26 00:00:00
2023-12-12T22:31:34.405910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:31:34.579464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Correlations

2023-12-12T22:31:34.687443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업자구분리콜종류제조국가명제조사국가명리콜방법위해유형안전성조사명등록일
사업자구분1.0000.2120.9070.3660.6850.6550.7090.867
리콜종류0.2121.0000.5440.4310.8090.5671.0000.991
제조국가명0.9070.5441.0000.9070.7500.2860.7690.887
제조사국가명0.3660.4310.9071.0000.2890.3370.2540.753
리콜방법0.6850.8090.7500.2891.0000.5250.9450.999
위해유형0.6550.5670.2860.3370.5251.0000.7620.919
안전성조사명0.7091.0000.7690.2540.9450.7621.0000.999
등록일0.8670.9910.8870.7530.9990.9190.9991.000
2023-12-12T22:31:34.819837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
리콜방법리콜종류제조사국가명제조국가명위해유형안전성조사명사업자구분
리콜방법1.0000.7760.1140.3800.2240.6540.409
리콜종류0.7761.0000.3330.4270.4410.9840.347
제조사국가명0.1140.3331.0000.6160.1480.0860.176
제조국가명0.3800.4270.6161.0000.0990.3210.677
위해유형0.2240.4410.1480.0991.0000.3530.378
안전성조사명0.6540.9840.0860.3210.3531.0000.437
사업자구분0.4090.3470.1760.6770.3780.4371.000
2023-12-12T22:31:34.939276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업자구분리콜종류제조국가명제조사국가명리콜방법위해유형안전성조사명
사업자구분1.0000.3470.6770.1760.4090.3780.437
리콜종류0.3471.0000.4270.3330.7760.4410.984
제조국가명0.6770.4271.0000.6160.3800.0990.321
제조사국가명0.1760.3330.6161.0000.1140.1480.086
리콜방법0.4090.7760.3800.1141.0000.2240.654
위해유형0.3780.4410.0990.1480.2241.0000.353
안전성조사명0.4370.9840.3210.0860.6540.3531.000

Missing values

2023-12-12T22:31:26.975166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:31:27.219275image/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.
2023-12-12T22:31:27.758292image/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

인증번호모델명제품명브랜드명사업자구분법정제품분류리콜종류리콜사업자명제조국가명제조사명제조사국가명리콜방법위해유형안전성조사명등록일
0CB063R4097-20001하프토이MR-T002완구하프토이수입어린이>완구명령에따른리콜주식회사해브잇올국외>아시아지역>중국주식회사해브잇올국내>아시아지역>대한민국교환수거수리환불유해물질42020-09-22
1CB063R3279-9001CB063R3279-9001A구체관절인형(미니프린세스돌30cm)완구<NA>수입어린이>완구명령에따른리콜와니월드국외>아시아지역>중국YIMEiCRAFTWORKTOYSFACTORY국외>아시아지역>중국교환수거수리환불유해물질42020-09-22
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