Overview

Dataset statistics

Number of variables9
Number of observations403
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.9 KiB
Average record size in memory73.3 B

Variable types

Numeric1
Categorical7
Text1

Dataset

Description광주광역시 보건환경연구원에서 식품 중 방사는 검사 현황으로 유통식품, 학교급식 식재료, 농수산물검사소 수산물 중 방사능(요오드, 세슘) 정밀검사 결과를 등록합니다.
URLhttps://www.data.go.kr/data/3082300/fileData.do

Alerts

세슘검출량 has constant value ""Constant
요오드검출량 has constant value ""Constant
적부판정 has constant value ""Constant
수거일 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
분류 is highly overall correlated with 수거일 and 1 other fieldsHigh correlation
수입국(채취장소) is highly overall correlated with 분류 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 수거일High correlation
원산지 is highly imbalanced (73.7%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:10:08.081221
Analysis finished2023-12-12 13:10:08.829018
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct403
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202
Minimum1
Maximum403
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-12T22:10:08.910891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.1
Q1101.5
median202
Q3302.5
95-th percentile382.9
Maximum403
Range402
Interquartile range (IQR)201

Descriptive statistics

Standard deviation116.48033
Coefficient of variation (CV)0.57663528
Kurtosis-1.2
Mean202
Median Absolute Deviation (MAD)101
Skewness0
Sum81406
Variance13567.667
MonotonicityStrictly increasing
2023-12-12T22:10:09.085591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
267 1
 
0.2%
277 1
 
0.2%
276 1
 
0.2%
275 1
 
0.2%
274 1
 
0.2%
273 1
 
0.2%
272 1
 
0.2%
271 1
 
0.2%
270 1
 
0.2%
Other values (393) 393
97.5%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
403 1
0.2%
402 1
0.2%
401 1
0.2%
400 1
0.2%
399 1
0.2%
398 1
0.2%
397 1
0.2%
396 1
0.2%
395 1
0.2%
394 1
0.2%

분류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
가공식품
157 
수산물
152 
농산물
94 

Length

Max length4
Median length3
Mean length3.3895782
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가공식품 157
39.0%
수산물 152
37.7%
농산물 94
23.3%

Length

2023-12-12T22:10:09.238675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:09.346042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가공식품 157
39.0%
수산물 152
37.7%
농산물 94
23.3%

제품명
Text

Distinct251
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-12T22:10:09.586868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length4.4789082
Min length1

Characters and Unicode

Total characters1805
Distinct characters355
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique203 ?
Unique (%)50.4%

Sample

1st row고등어
2nd row삼치
3rd row갈치
4th row조기
5th row가자미
ValueCountFrequency (%)
고등어 20
 
4.8%
갈치 16
 
3.8%
가리비 13
 
3.1%
조기 10
 
2.4%
부세 10
 
2.4%
병어 10
 
2.4%
삼치 7
 
1.7%
아귀 7
 
1.7%
오징어 6
 
1.4%
민어 6
 
1.4%
Other values (251) 314
74.9%
2023-12-12T22:10:10.125241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 58
 
3.2%
어 56
 
3.1%
고 53
 
2.9%
가 44
 
2.4%
치 40
 
2.2%
스 36
 
2.0%
기 33
 
1.8%
이 32
 
1.8%
오 30
 
1.7%
장 29
 
1.6%
Other values (345) 1394
77.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1736
96.2%
Space Separator 17
 
0.9%
Decimal Number 16
 
0.9%
Open Punctuation 11
 
0.6%
Close Punctuation 11
 
0.6%
Lowercase Letter 8
 
0.4%
Uppercase Letter 3
 
0.2%
Other Punctuation 2
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 58
 
3.3%
어 56
 
3.2%
고 53
 
3.1%
가 44
 
2.5%
치 40
 
2.3%
스 36
 
2.1%
기 33
 
1.9%
이 32
 
1.8%
오 30
 
1.7%
장 29
 
1.7%
Other values (323) 1325
76.3%
Lowercase Letter
ValueCountFrequency (%)
i 1
12.5%
o 1
12.5%
t 1
12.5%
r 1
12.5%
p 1
12.5%
c 1
12.5%
a 1
12.5%
l 1
12.5%
Decimal Number
ValueCountFrequency (%)
0 5
31.2%
1 4
25.0%
3 3
18.8%
2 1
 
6.2%
8 1
 
6.2%
7 1
 
6.2%
5 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
S 2
66.7%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Punctuation
ValueCountFrequency (%)
% 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1736
96.2%
Common 58
 
3.2%
Latin 11
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 58
 
3.3%
어 56
 
3.2%
고 53
 
3.1%
가 44
 
2.5%
치 40
 
2.3%
스 36
 
2.1%
기 33
 
1.9%
이 32
 
1.8%
오 30
 
1.7%
장 29
 
1.7%
Other values (323) 1325
76.3%
Common
ValueCountFrequency (%)
17
29.3%
( 11
19.0%
) 11
19.0%
0 5
 
8.6%
1 4
 
6.9%
3 3
 
5.2%
% 2
 
3.4%
2 1
 
1.7%
8 1
 
1.7%
+ 1
 
1.7%
Other values (2) 2
 
3.4%
Latin
ValueCountFrequency (%)
S 2
18.2%
A 1
9.1%
i 1
9.1%
o 1
9.1%
t 1
9.1%
r 1
9.1%
p 1
9.1%
c 1
9.1%
a 1
9.1%
l 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1736
96.2%
ASCII 69
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 58
 
3.3%
어 56
 
3.2%
고 53
 
3.1%
가 44
 
2.5%
치 40
 
2.3%
스 36
 
2.1%
기 33
 
1.9%
이 32
 
1.8%
오 30
 
1.7%
장 29
 
1.7%
Other values (323) 1325
76.3%
ASCII
ValueCountFrequency (%)
17
24.6%
( 11
15.9%
) 11
15.9%
0 5
 
7.2%
1 4
 
5.8%
3 3
 
4.3%
% 2
 
2.9%
S 2
 
2.9%
2 1
 
1.4%
8 1
 
1.4%
Other values (12) 12
17.4%

수거일
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2022-10-04
 
21
2022-10-18
 
16
2022-06-14
 
15
2022-04-05
 
15
2022-03-28
 
15
Other values (38)
321 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-01-17
2nd row2022-01-17
3rd row2022-01-17
4th row2022-01-17
5th row2022-01-17

Common Values

ValueCountFrequency (%)
2022-10-04 21
 
5.2%
2022-10-18 16
 
4.0%
2022-06-14 15
 
3.7%
2022-04-05 15
 
3.7%
2022-03-28 15
 
3.7%
2022-09-20 15
 
3.7%
2022-08-11 15
 
3.7%
2022-02-15 15
 
3.7%
2022-05-03 15
 
3.7%
2022-07-06 15
 
3.7%
Other values (33) 246
61.0%

Length

2023-12-12T22:10:10.268919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-10-04 21
 
5.2%
2022-10-18 16
 
4.0%
2022-08-11 15
 
3.7%
2022-07-06 15
 
3.7%
2022-02-15 15
 
3.7%
2022-05-03 15
 
3.7%
2022-09-20 15
 
3.7%
2022-03-28 15
 
3.7%
2022-04-05 15
 
3.7%
2022-06-14 15
 
3.7%
Other values (33) 246
61.0%

원산지
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
국내산
364 
일본
 
17
중국
 
16
노르웨이
 
5
세네갈
 
1

Length

Max length4
Median length3
Mean length2.9305211
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
국내산 364
90.3%
일본 17
 
4.2%
중국 16
 
4.0%
노르웨이 5
 
1.2%
세네갈 1
 
0.2%

Length

2023-12-12T22:10:10.405177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:10.524085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내산 364
90.3%
일본 17
 
4.2%
중국 16
 
4.0%
노르웨이 5
 
1.2%
세네갈 1
 
0.2%

수입국(채취장소)
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
서부농수산물도매시장
155 
교육청
50 
서구청
40 
남구청
40 
광산구청
40 
Other values (4)
78 

Length

Max length10
Median length7
Mean length5.9330025
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서부농수산물도매시장 155
38.5%
교육청 50
 
12.4%
서구청 40
 
9.9%
남구청 40
 
9.9%
광산구청 40
 
9.9%
북구청 30
 
7.4%
동구청 30
 
7.4%
평동하나로마트 15
 
3.7%
본량 3
 
0.7%

Length

2023-12-12T22:10:10.651325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:10.794511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서부농수산물도매시장 155
38.5%
교육청 50
 
12.4%
서구청 40
 
9.9%
남구청 40
 
9.9%
광산구청 40
 
9.9%
북구청 30
 
7.4%
동구청 30
 
7.4%
평동하나로마트 15
 
3.7%
본량 3
 
0.7%

세슘검출량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
불검출
403 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
불검출 403
100.0%

Length

2023-12-12T22:10:10.938477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:11.059306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불검출 403
100.0%

요오드검출량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
불검출
403 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
불검출 403
100.0%

Length

2023-12-12T22:10:11.162803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:11.257446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불검출 403
100.0%

적부판정
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
적합
403 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
적합 403
100.0%

Length

2023-12-12T22:10:11.366120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:10:11.461312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 403
100.0%

Interactions

2023-12-12T22:10:08.474651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:10:11.535919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번분류수거일원산지수입국(채취장소)
연번1.0000.3200.9950.0000.718
분류0.3201.0000.9910.3490.956
수거일0.9950.9911.0000.3270.998
원산지0.0000.3490.3271.0000.260
수입국(채취장소)0.7180.9560.9980.2601.000
2023-12-12T22:10:11.654460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수거일원산지분류수입국(채취장소)
수거일1.0000.1490.9070.938
원산지0.1491.0000.2810.152
분류0.9070.2811.0000.746
수입국(채취장소)0.9380.1520.7461.000
2023-12-12T22:10:11.758655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번분류수거일원산지수입국(채취장소)
연번1.0000.2010.9100.0000.430
분류0.2011.0000.9070.2810.746
수거일0.9100.9071.0000.1490.938
원산지0.0000.2810.1491.0000.152
수입국(채취장소)0.4300.7460.9380.1521.000

Missing values

2023-12-12T22:10:08.648541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:10:08.778523image/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

연번분류제품명수거일원산지수입국(채취장소)세슘검출량요오드검출량적부판정
01수산물고등어2022-01-17국내산서부농수산물도매시장불검출불검출적합
12수산물삼치2022-01-17국내산서부농수산물도매시장불검출불검출적합
23수산물갈치2022-01-17국내산서부농수산물도매시장불검출불검출적합
34수산물조기2022-01-17국내산서부농수산물도매시장불검출불검출적합
45수산물가자미2022-01-17국내산서부농수산물도매시장불검출불검출적합
56수산물아귀2022-01-17국내산서부농수산물도매시장불검출불검출적합
67수산물장어2022-01-17국내산서부농수산물도매시장불검출불검출적합
78수산물청어2022-01-17국내산서부농수산물도매시장불검출불검출적합
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