Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells1178
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory322.3 KiB
Average record size in memory33.0 B

Variable types

Numeric1
Text2

Dataset

Description전기용품 및 생활용품 안전관리법, 어린이제품안전 특별법 등 KC 인증제품에 대한 제조사명, 제조국가명 등을 확인할 수 있는 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15040701/fileData.do

Alerts

제조사명 has 1177 (11.8%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:46:24.438413
Analysis finished2023-12-11 23:46:25.189427
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10962.168
Minimum5
Maximum21870
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:46:25.266269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile1101.85
Q15583.5
median11044
Q316311.5
95-th percentile20733.15
Maximum21870
Range21865
Interquartile range (IQR)10728

Descriptive statistics

Standard deviation6255.8027
Coefficient of variation (CV)0.57067203
Kurtosis-1.1789436
Mean10962.168
Median Absolute Deviation (MAD)5355.5
Skewness-0.018884496
Sum1.0962168 × 108
Variance39135067
MonotonicityNot monotonic
2023-12-12T08:46:25.416759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12382 1
 
< 0.1%
7803 1
 
< 0.1%
1114 1
 
< 0.1%
11717 1
 
< 0.1%
19901 1
 
< 0.1%
5816 1
 
< 0.1%
889 1
 
< 0.1%
19244 1
 
< 0.1%
9663 1
 
< 0.1%
1272 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
5 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
20 1
< 0.1%
ValueCountFrequency (%)
21870 1
< 0.1%
21869 1
< 0.1%
21868 1
< 0.1%
21867 1
< 0.1%
21860 1
< 0.1%
21858 1
< 0.1%
21857 1
< 0.1%
21856 1
< 0.1%
21854 1
< 0.1%
21853 1
< 0.1%

제조사명
Text

MISSING 

Distinct2857
Distinct (%)32.4%
Missing1177
Missing (%)11.8%
Memory size156.2 KiB
2023-12-12T08:46:25.691004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length53
Mean length21.689108
Min length2

Characters and Unicode

Total characters191363
Distinct characters515
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1535 ?
Unique (%)17.4%

Sample

1st row피에스텍(주)광천지점
2nd rowNingboGoodfriendsElectricApplianceCoLtd
3rd rowLGEnergySolution(Nanjing)CoLtd
4th rowShenzhenHuntkeyElectronicsCoLtd
5th rowShenZhenHuiLiElectronicsCOLTD
ValueCountFrequency (%)
ptlgelectronicsindonesia 94
 
1.1%
lgenergysolution(nanjing)coltd 71
 
0.8%
주)쿠첸 66
 
0.7%
chiconypowertechnology(suzhou)coltd 63
 
0.7%
shandongxinghongyuantyrecoltd 62
 
0.7%
nanjingnexconelectronicscoltd 62
 
0.7%
chongqingc-techtechnologycoltd 51
 
0.6%
킴스일렉(주 47
 
0.5%
에코그린피아(주 47
 
0.5%
jiangsushincotechnologycoltd 46
 
0.5%
Other values (2788) 8214
93.1%
2023-12-12T08:46:26.211111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 12603
 
6.6%
o 11553
 
6.0%
e 8743
 
4.6%
i 8715
 
4.6%
t 7946
 
4.2%
C 6851
 
3.6%
L 6590
 
3.4%
a 6543
 
3.4%
g 6132
 
3.2%
c 6002
 
3.1%
Other values (505) 109685
57.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 103771
54.2%
Uppercase Letter 56624
29.6%
Other Letter 23590
 
12.3%
Open Punctuation 3425
 
1.8%
Close Punctuation 3425
 
1.8%
Dash Punctuation 256
 
0.1%
Other Punctuation 180
 
0.1%
Decimal Number 88
 
< 0.1%
Math Symbol 3
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3085
 
13.1%
이 1106
 
4.7%
스 981
 
4.2%
사 907
 
3.8%
회 869
 
3.7%
식 816
 
3.5%
에 504
 
2.1%
전 461
 
2.0%
지 403
 
1.7%
아 331
 
1.4%
Other values (439) 14127
59.9%
Lowercase Letter
ValueCountFrequency (%)
n 12603
12.1%
o 11553
11.1%
e 8743
 
8.4%
i 8715
 
8.4%
t 7946
 
7.7%
a 6543
 
6.3%
g 6132
 
5.9%
c 6002
 
5.8%
h 5920
 
5.7%
l 4581
 
4.4%
Other values (16) 25033
24.1%
Uppercase Letter
ValueCountFrequency (%)
C 6851
12.1%
L 6590
11.6%
E 4643
 
8.2%
T 4553
 
8.0%
N 3896
 
6.9%
S 3184
 
5.6%
O 3104
 
5.5%
I 3070
 
5.4%
A 2793
 
4.9%
G 2472
 
4.4%
Other values (16) 15468
27.3%
Decimal Number
ValueCountFrequency (%)
2 58
65.9%
1 15
 
17.0%
3 8
 
9.1%
0 4
 
4.5%
4 3
 
3.4%
Close Punctuation
ValueCountFrequency (%)
) 3424
> 99.9%
） 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
& 140
77.8%
/ 40
 
22.2%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
| 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 3425
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 256
100.0%
Other Symbol
ValueCountFrequency (%)
ⓡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 160395
83.8%
Hangul 23590
 
12.3%
Common 7378
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3085
 
13.1%
이 1106
 
4.7%
스 981
 
4.2%
사 907
 
3.8%
회 869
 
3.7%
식 816
 
3.5%
에 504
 
2.1%
전 461
 
2.0%
지 403
 
1.7%
아 331
 
1.4%
Other values (439) 14127
59.9%
Latin
ValueCountFrequency (%)
n 12603
 
7.9%
o 11553
 
7.2%
e 8743
 
5.5%
i 8715
 
5.4%
t 7946
 
5.0%
C 6851
 
4.3%
L 6590
 
4.1%
a 6543
 
4.1%
g 6132
 
3.8%
c 6002
 
3.7%
Other values (42) 78717
49.1%
Common
ValueCountFrequency (%)
( 3425
46.4%
) 3424
46.4%
- 256
 
3.5%
& 140
 
1.9%
2 58
 
0.8%
/ 40
 
0.5%
1 15
 
0.2%
3 8
 
0.1%
0 4
 
0.1%
4 3
 
< 0.1%
Other values (4) 5
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 167771
87.7%
Hangul 23590
 
12.3%
None 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 12603
 
7.5%
o 11553
 
6.9%
e 8743
 
5.2%
i 8715
 
5.2%
t 7946
 
4.7%
C 6851
 
4.1%
L 6590
 
3.9%
a 6543
 
3.9%
g 6132
 
3.7%
c 6002
 
3.6%
Other values (54) 86093
51.3%
Hangul
ValueCountFrequency (%)
주 3085
 
13.1%
이 1106
 
4.7%
스 981
 
4.2%
사 907
 
3.8%
회 869
 
3.7%
식 816
 
3.5%
에 504
 
2.1%
전 461
 
2.0%
지 403
 
1.7%
아 331
 
1.4%
Other values (439) 14127
59.9%
None
ValueCountFrequency (%)
） 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓡ 1
100.0%

제조사국가명
Text

Distinct72
Distinct (%)0.7%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T08:46:26.418029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length2
Mean length3.0159016
Min length2

Characters and Unicode

Total characters30156
Distinct characters113
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

Unique19 ?
Unique (%)0.2%

Sample

1st row대한민국
2nd row중국
3rd row중국
4th row중국
5th row중국
ValueCountFrequency (%)
중국 4805
48.1%
대한민국 3195
32.0%
베트남 413
 
4.1%
한국 332
 
3.3%
인도네시아 145
 
1.5%
대한민국(경기도 101
 
1.0%
대만 96
 
1.0%
대한민국(서울특별시 79
 
0.8%
말레이시아 77
 
0.8%
태국 72
 
0.7%
Other values (62) 684
 
6.8%
2023-12-12T08:46:26.762739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 8692
28.8%
중 4805
15.9%
한 3787
12.6%
대 3555
11.8%
민 3453
 
11.5%
남 440
 
1.5%
트 414
 
1.4%
베 413
 
1.4%
시 408
 
1.4%
아 350
 
1.2%
Other values (103) 3839
12.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29640
98.3%
Open Punctuation 258
 
0.9%
Close Punctuation 258
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 8692
29.3%
중 4805
16.2%
한 3787
12.8%
대 3555
12.0%
민 3453
 
11.6%
남 440
 
1.5%
트 414
 
1.4%
베 413
 
1.4%
시 408
 
1.4%
아 350
 
1.2%
Other values (101) 3323
 
11.2%
Open Punctuation
ValueCountFrequency (%)
( 258
100.0%
Close Punctuation
ValueCountFrequency (%)
) 258
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29640
98.3%
Common 516
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 8692
29.3%
중 4805
16.2%
한 3787
12.8%
대 3555
12.0%
민 3453
 
11.6%
남 440
 
1.5%
트 414
 
1.4%
베 413
 
1.4%
시 408
 
1.4%
아 350
 
1.2%
Other values (101) 3323
 
11.2%
Common
ValueCountFrequency (%)
( 258
50.0%
) 258
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29640
98.3%
ASCII 516
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 8692
29.3%
중 4805
16.2%
한 3787
12.8%
대 3555
12.0%
민 3453
 
11.6%
남 440
 
1.5%
트 414
 
1.4%
베 413
 
1.4%
시 408
 
1.4%
아 350
 
1.2%
Other values (101) 3323
 
11.2%
ASCII
ValueCountFrequency (%)
( 258
50.0%
) 258
50.0%

Interactions

2023-12-12T08:46:24.837292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:46:26.893100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번제조사국가명
순번1.0000.298
제조사국가명0.2981.000

Missing values

2023-12-12T08:46:24.962600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:46:25.052337image/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.
2023-12-12T08:46:25.140600image/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

순번제조사명제조사국가명
1238112382피에스텍(주)광천지점대한민국
1340013401NingboGoodfriendsElectricApplianceCoLtd중국
1650916510LGEnergySolution(Nanjing)CoLtd중국
91059106ShenzhenHuntkeyElectronicsCoLtd중국
42374238ShenZhenHuiLiElectronicsCOLTD중국
76767677ZhejiangTianxiKitchenApplianceCoLtd중국
2008520086ShanghaiMenghuaNetworkTechnologyCoLtd중국
64296430YongkangMeiloy-K&FPToolsCoLtd중국
2149121492(주)선일일렉콤대한민국
89648965ShenzhenLonggangDistrictLiuguangLightingFactory중국
순번제조사명제조사국가명
1379913800CityFocusLightingCoLtd베트남
1470014701ZhongshanYiguangLightingCoLtd중국
2074320744PTVolexIndonesia인도네시아
85008501<NA>대한민국(경기도)
96819682(주)일월한국
97029703ShenzhenJIEKEYUANSCIENCE&TECHNOLOGYCOLTD중국
2060220603FoshanBigClimaticManufactureCoLtdZhongshanBranch중국
1436714368(주)경동나비엔평택공장대한민국
247248DongguanXinEmpressTechnologyCoLtd중국
1550815509코웨이(주)인천지점대한민국