Overview

Dataset statistics

Number of variables6
Number of observations254
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.0 KiB
Average record size in memory52.5 B

Variable types

Categorical3
Text1
Numeric2

Dataset

Description국립농산물품질관리원에서 관리하는 농산물 방사능 검사현황 정보(년도, 구분, 품목, 검사건수, 적합건수, 부적합건수)
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220204000000001682

Alerts

구분 has constant value ""Constant
부적합건수 has constant value ""Constant
검사건수 is highly overall correlated with 적합건수High correlation
적합건수 is highly overall correlated with 검사건수High correlation

Reproduction

Analysis started2024-03-23 07:52:56.820765
Analysis finished2024-03-23 07:52:59.145193
Duration2.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

Distinct5
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2018
63 
2021
53 
2017
53 
2019
43 
2020
42 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2018 63
24.8%
2021 53
20.9%
2017 53
20.9%
2019 43
16.9%
2020 42
16.5%

Length

2024-03-23T07:52:59.347111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:52:59.645981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 63
24.8%
2021 53
20.9%
2017 53
20.9%
2019 43
16.9%
2020 42
16.5%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
국내산
254 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내산 254
100.0%

Length

2024-03-23T07:52:59.979622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:53:00.250894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내산 254
100.0%

품목
Text

Distinct85
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-03-23T07:53:00.819430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length2.9488189
Min length1

Characters and Unicode

Total characters749
Distinct characters129
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)11.0%

Sample

1st row가지
2nd row감귤
3rd row감자
4th row고구마
5th row고구마순(고구마줄기)
ValueCountFrequency (%)
가지 5
 
2.0%
포도 5
 
2.0%
배추 5
 
2.0%
오이 5
 
2.0%
감귤 5
 
2.0%
우엉 5
 
2.0%
쪽파 5
 
2.0%
열무 5
 
2.0%
부추 5
 
2.0%
양배추 5
 
2.0%
Other values (75) 204
80.3%
2024-03-23T07:53:01.971027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 49
 
6.5%
고 32
 
4.3%
마 26
 
3.5%
배 23
 
3.1%
리 21
 
2.8%
감 20
 
2.7%
토 20
 
2.7%
파 17
 
2.3%
대 16
 
2.1%
양 16
 
2.1%
Other values (119) 509
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 716
95.6%
Open Punctuation 16
 
2.1%
Close Punctuation 16
 
2.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 49
 
6.8%
고 32
 
4.5%
마 26
 
3.6%
배 23
 
3.2%
리 21
 
2.9%
감 20
 
2.8%
토 20
 
2.8%
파 17
 
2.4%
대 16
 
2.2%
양 16
 
2.2%
Other values (116) 476
66.5%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 716
95.6%
Common 33
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 49
 
6.8%
고 32
 
4.5%
마 26
 
3.6%
배 23
 
3.2%
리 21
 
2.9%
감 20
 
2.8%
토 20
 
2.8%
파 17
 
2.4%
대 16
 
2.2%
양 16
 
2.2%
Other values (116) 476
66.5%
Common
ValueCountFrequency (%)
( 16
48.5%
) 16
48.5%
, 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 716
95.6%
ASCII 33
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 49
 
6.8%
고 32
 
4.5%
마 26
 
3.6%
배 23
 
3.2%
리 21
 
2.9%
감 20
 
2.8%
토 20
 
2.8%
파 17
 
2.4%
대 16
 
2.2%
양 16
 
2.2%
Other values (116) 476
66.5%
ASCII
ValueCountFrequency (%)
( 16
48.5%
) 16
48.5%
, 1
 
3.0%

검사건수
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.3110236
Minimum1
Maximum82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-03-23T07:53:02.456488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q313
95-th percentile36
Maximum82
Range81
Interquartile range (IQR)11

Descriptive statistics

Standard deviation12.408149
Coefficient of variation (CV)1.33263
Kurtosis9.662059
Mean9.3110236
Median Absolute Deviation (MAD)3
Skewness2.710229
Sum2365
Variance153.96217
MonotonicityNot monotonic
2024-03-23T07:53:02.973957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 62
24.4%
2 28
 
11.0%
3 26
 
10.2%
4 19
 
7.5%
7 10
 
3.9%
5 10
 
3.9%
6 9
 
3.5%
11 7
 
2.8%
18 6
 
2.4%
13 6
 
2.4%
Other values (29) 71
28.0%
ValueCountFrequency (%)
1 62
24.4%
2 28
11.0%
3 26
10.2%
4 19
 
7.5%
5 10
 
3.9%
6 9
 
3.5%
7 10
 
3.9%
8 6
 
2.4%
9 5
 
2.0%
10 2
 
0.8%
ValueCountFrequency (%)
82 1
 
0.4%
75 1
 
0.4%
71 1
 
0.4%
44 3
1.2%
42 2
0.8%
41 1
 
0.4%
40 1
 
0.4%
39 1
 
0.4%
37 1
 
0.4%
36 2
0.8%

적합건수
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.3110236
Minimum1
Maximum82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-03-23T07:53:03.348627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q313
95-th percentile36
Maximum82
Range81
Interquartile range (IQR)11

Descriptive statistics

Standard deviation12.408149
Coefficient of variation (CV)1.33263
Kurtosis9.662059
Mean9.3110236
Median Absolute Deviation (MAD)3
Skewness2.710229
Sum2365
Variance153.96217
MonotonicityNot monotonic
2024-03-23T07:53:03.663725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 62
24.4%
2 28
 
11.0%
3 26
 
10.2%
4 19
 
7.5%
7 10
 
3.9%
5 10
 
3.9%
6 9
 
3.5%
11 7
 
2.8%
18 6
 
2.4%
13 6
 
2.4%
Other values (29) 71
28.0%
ValueCountFrequency (%)
1 62
24.4%
2 28
11.0%
3 26
10.2%
4 19
 
7.5%
5 10
 
3.9%
6 9
 
3.5%
7 10
 
3.9%
8 6
 
2.4%
9 5
 
2.0%
10 2
 
0.8%
ValueCountFrequency (%)
82 1
 
0.4%
75 1
 
0.4%
71 1
 
0.4%
44 3
1.2%
42 2
0.8%
41 1
 
0.4%
40 1
 
0.4%
39 1
 
0.4%
37 1
 
0.4%
36 2
0.8%

부적합건수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
0
254 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 254
100.0%

Length

2024-03-23T07:53:04.077800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:53:04.379040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 254
100.0%

Interactions

2024-03-23T07:52:57.720889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:52:57.191986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:52:58.033729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:52:57.465997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:53:04.552060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도품목검사건수적합건수
년도1.0000.0000.0000.000
품목0.0001.0000.0000.000
검사건수0.0000.0001.0001.000
적합건수0.0000.0001.0001.000
2024-03-23T07:53:04.795602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
검사건수적합건수년도
검사건수1.0001.0000.000
적합건수1.0001.0000.000
년도0.0000.0001.000

Missing values

2024-03-23T07:52:58.438769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:52:58.813591image/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

년도구분품목검사건수적합건수부적합건수
02021국내산가지660
12021국내산감귤550
22021국내산감자28280
32021국내산고구마17170
42021국내산고구마순(고구마줄기)330
52021국내산단감10100
62021국내산당근550
72021국내산대추220
82021국내산대파40400
92021국내산두릅110
년도구분품목검사건수적합건수부적합건수
2442017국내산유채110
2452017국내산쪽파12120
2462017국내산취나물330
2472017국내산토마토440
2482017국내산포도14140
2492017국내산표고버섯18180
2502017국내산풋고추44440
2512017국내산호박44440
2522017국내산호박잎220
2532017국내산홍고추(붉은고추)16160