Overview

Dataset statistics

Number of variables4
Number of observations1539
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory52.7 KiB
Average record size in memory35.1 B

Variable types

Categorical2
Numeric1
Text1

Dataset

Description아임셀러에 상품에 대한 재료 정보에 대한 데이터를 제공합니다. 기준연도, 기준월, 상품재료명 등의 데이터를 제공합니다.
Author(주)중소기업유통센터
URLhttps://www.data.go.kr/data/15067189/fileData.do

Alerts

기준연도 has constant value ""Constant
기준월 has constant value ""Constant

Reproduction

Analysis started2023-12-12 07:00:49.068733
Analysis finished2023-12-12 07:00:49.696557
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
2020
1539 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 1539
100.0%

Length

2023-12-12T16:00:49.774692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:00:49.900223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 1539
100.0%

기준월
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
9
1539 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row9
3rd row9
4th row9
5th row9

Common Values

ValueCountFrequency (%)
9 1539
100.0%

Length

2023-12-12T16:00:50.017194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:00:50.137592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9 1539
100.0%

상품재료번호
Real number (ℝ)

Distinct10
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3398311
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.7 KiB
2023-12-12T16:00:50.232714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1130122
Coefficient of variation (CV)0.83071082
Kurtosis21.40364
Mean1.3398311
Median Absolute Deviation (MAD)0
Skewness4.3498244
Sum2062
Variance1.2387961
MonotonicityNot monotonic
2023-12-12T16:00:50.359809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 1332
86.5%
2 86
 
5.6%
3 47
 
3.1%
4 26
 
1.7%
5 17
 
1.1%
6 11
 
0.7%
7 7
 
0.5%
8 6
 
0.4%
9 5
 
0.3%
10 2
 
0.1%
ValueCountFrequency (%)
1 1332
86.5%
2 86
 
5.6%
3 47
 
3.1%
4 26
 
1.7%
5 17
 
1.1%
6 11
 
0.7%
7 7
 
0.5%
8 6
 
0.4%
9 5
 
0.3%
10 2
 
0.1%
ValueCountFrequency (%)
10 2
 
0.1%
9 5
 
0.3%
8 6
 
0.4%
7 7
 
0.5%
6 11
 
0.7%
5 17
 
1.1%
4 26
 
1.7%
3 47
 
3.1%
2 86
 
5.6%
1 1332
86.5%

상품재료명
Text

Distinct1459
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
2023-12-12T16:00:50.604924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19
Mean length6.1351527
Min length1

Characters and Unicode

Total characters9442
Distinct characters742
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1397 ?
Unique (%)90.8%

Sample

1st row액상차
2nd row굿나잇슬리밍다이어트
3rd row천연가죽
4th row고무장갑
5th row볶은우엉차
ValueCountFrequency (%)
상품상세설명참조 10
 
0.6%
기운센차 4
 
0.3%
든든한차 4
 
0.3%
유기농분말현미녹차 3
 
0.2%
우엉차 3
 
0.2%
흑마늘먹은천일염 3
 
0.2%
호박식초 3
 
0.2%
자몽식초 3
 
0.2%
포도식초 3
 
0.2%
현미누룽지 2
 
0.1%
Other values (1449) 1501
97.5%
2023-12-12T16:00:51.023461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 199
 
2.1%
초 181
 
1.9%
스 176
 
1.9%
기 144
 
1.5%
리 142
 
1.5%
차 140
 
1.5%
식 125
 
1.3%
미 116
 
1.2%
장 106
 
1.1%
마 104
 
1.1%
Other values (732) 8009
84.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9195
97.4%
Uppercase Letter 130
 
1.4%
Decimal Number 73
 
0.8%
Lowercase Letter 44
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 199
 
2.2%
초 181
 
2.0%
스 176
 
1.9%
기 144
 
1.6%
리 142
 
1.5%
차 140
 
1.5%
식 125
 
1.4%
미 116
 
1.3%
장 106
 
1.2%
마 104
 
1.1%
Other values (685) 7762
84.4%
Uppercase Letter
ValueCountFrequency (%)
S 12
 
9.2%
C 11
 
8.5%
D 10
 
7.7%
E 9
 
6.9%
L 9
 
6.9%
M 9
 
6.9%
O 8
 
6.2%
P 8
 
6.2%
B 8
 
6.2%
T 7
 
5.4%
Other values (12) 39
30.0%
Lowercase Letter
ValueCountFrequency (%)
r 7
15.9%
e 6
13.6%
i 5
11.4%
a 4
9.1%
l 3
6.8%
n 3
6.8%
t 3
6.8%
g 2
 
4.5%
p 2
 
4.5%
u 2
 
4.5%
Other values (6) 7
15.9%
Decimal Number
ValueCountFrequency (%)
3 15
20.5%
4 14
19.2%
6 10
13.7%
1 8
11.0%
5 7
9.6%
2 6
 
8.2%
7 5
 
6.8%
9 4
 
5.5%
8 4
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9195
97.4%
Latin 174
 
1.8%
Common 73
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 199
 
2.2%
초 181
 
2.0%
스 176
 
1.9%
기 144
 
1.6%
리 142
 
1.5%
차 140
 
1.5%
식 125
 
1.4%
미 116
 
1.3%
장 106
 
1.2%
마 104
 
1.1%
Other values (685) 7762
84.4%
Latin
ValueCountFrequency (%)
S 12
 
6.9%
C 11
 
6.3%
D 10
 
5.7%
E 9
 
5.2%
L 9
 
5.2%
M 9
 
5.2%
O 8
 
4.6%
P 8
 
4.6%
B 8
 
4.6%
r 7
 
4.0%
Other values (28) 83
47.7%
Common
ValueCountFrequency (%)
3 15
20.5%
4 14
19.2%
6 10
13.7%
1 8
11.0%
5 7
9.6%
2 6
 
8.2%
7 5
 
6.8%
9 4
 
5.5%
8 4
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9195
97.4%
ASCII 247
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 199
 
2.2%
초 181
 
2.0%
스 176
 
1.9%
기 144
 
1.6%
리 142
 
1.5%
차 140
 
1.5%
식 125
 
1.4%
미 116
 
1.3%
장 106
 
1.2%
마 104
 
1.1%
Other values (685) 7762
84.4%
ASCII
ValueCountFrequency (%)
3 15
 
6.1%
4 14
 
5.7%
S 12
 
4.9%
C 11
 
4.5%
D 10
 
4.0%
6 10
 
4.0%
E 9
 
3.6%
L 9
 
3.6%
M 9
 
3.6%
O 8
 
3.2%
Other values (37) 140
56.7%

Interactions

2023-12-12T16:00:49.451393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T16:00:49.559100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:00:49.650548image/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

기준연도기준월상품재료번호상품재료명
0202091액상차
1202091굿나잇슬리밍다이어트
2202091천연가죽
3202091고무장갑
4202091볶은우엉차
5202091천연비타민C보충제
6202091혼합음료
7202091씨엘교육용플루트
8202091절임류
9202091김치
기준연도기준월상품재료번호상품재료명
1529202091명진미니고무장갑소대
1530202091빠져라
1531202091마미손라텍스니트릴장갑
1532202091제습제
1533202091쿠팡마스크크린케이스
1534202091울금환
1535202091틈새선반
1536202091초사랑초란
1537202091광천웰빙자반김
1538202091명진업소용대용량롤팩롤백