Overview

Dataset statistics

Number of variables6
Number of observations502
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.2 KiB
Average record size in memory49.3 B

Variable types

Numeric1
Text3
Categorical1
Boolean1

Dataset

Description한국농수산식품유통공사의 정가수의매매예약거래시스템 내 등록되어있는 중도매인 주요 관심품목(품목 대분류, 중분류, 소분류 등) 정보 제공
Author한국농수산식품유통공사
URLhttps://www.data.go.kr/data/15072151/fileData.do

Alerts

중도매인코드 is highly overall correlated with SMS수신여부High correlation
SMS수신여부 is highly overall correlated with 중도매인코드High correlation

Reproduction

Analysis started2023-12-12 05:13:14.494129
Analysis finished2023-12-12 05:13:15.204094
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

중도매인코드
Real number (ℝ)

HIGH CORRELATION 

Distinct217
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200832.68
Minimum200001
Maximum201499
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T14:13:15.276458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200001
5-th percentile200206
Q1200419
median200968
Q3201080
95-th percentile201471
Maximum201499
Range1498
Interquartile range (IQR)661

Descriptive statistics

Standard deviation399.244
Coefficient of variation (CV)0.0019879434
Kurtosis-0.99383811
Mean200832.68
Median Absolute Deviation (MAD)150.5
Skewness-0.33375264
Sum1.00818 × 108
Variance159395.77
MonotonicityIncreasing
2023-12-12T14:13:15.422437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200232 14
 
2.8%
201472 12
 
2.4%
200995 10
 
2.0%
201072 10
 
2.0%
201452 10
 
2.0%
201118 9
 
1.8%
201285 8
 
1.6%
201073 7
 
1.4%
201117 7
 
1.4%
201451 7
 
1.4%
Other values (207) 408
81.3%
ValueCountFrequency (%)
200001 4
0.8%
200002 1
 
0.2%
200004 1
 
0.2%
200007 1
 
0.2%
200017 1
 
0.2%
200122 1
 
0.2%
200123 1
 
0.2%
200128 1
 
0.2%
200131 1
 
0.2%
200142 1
 
0.2%
ValueCountFrequency (%)
201499 1
 
0.2%
201498 1
 
0.2%
201497 1
 
0.2%
201474 5
1.0%
201473 5
1.0%
201472 12
2.4%
201471 2
 
0.4%
201452 10
2.0%
201451 7
1.4%
201443 1
 
0.2%

품목명
Text

Distinct79
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-12T14:13:15.755907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.7290837
Min length1

Characters and Unicode

Total characters1370
Distinct characters114
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

Unique30 ?
Unique (%)6.0%

Sample

1st row딸기
2nd row수박
3rd row배
4th row사과
5th row사과
ValueCountFrequency (%)
마늘 31
 
6.2%
팽이버섯 31
 
6.2%
당근 27
 
5.4%
상추 26
 
5.2%
배추 25
 
5.0%
만가닥 20
 
4.0%
호박 20
 
4.0%
봄동배추 19
 
3.8%
사과 18
 
3.6%
표고버섯 16
 
3.2%
Other values (69) 269
53.6%
2023-12-12T14:13:16.141672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 101
 
7.4%
배 79
 
5.8%
이 67
 
4.9%
섯 66
 
4.8%
버 66
 
4.8%
마 48
 
3.5%
고 39
 
2.8%
리 33
 
2.4%
팽 31
 
2.3%
늘 31
 
2.3%
Other values (104) 809
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1354
98.8%
Close Punctuation 8
 
0.6%
Open Punctuation 8
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 101
 
7.5%
배 79
 
5.8%
이 67
 
4.9%
섯 66
 
4.9%
버 66
 
4.9%
마 48
 
3.5%
고 39
 
2.9%
리 33
 
2.4%
팽 31
 
2.3%
늘 31
 
2.3%
Other values (102) 793
58.6%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1354
98.8%
Common 16
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 101
 
7.5%
배 79
 
5.8%
이 67
 
4.9%
섯 66
 
4.9%
버 66
 
4.9%
마 48
 
3.5%
고 39
 
2.9%
리 33
 
2.4%
팽 31
 
2.3%
늘 31
 
2.3%
Other values (102) 793
58.6%
Common
ValueCountFrequency (%)
) 8
50.0%
( 8
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1354
98.8%
ASCII 16
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 101
 
7.5%
배 79
 
5.8%
이 67
 
4.9%
섯 66
 
4.9%
버 66
 
4.9%
마 48
 
3.5%
고 39
 
2.9%
리 33
 
2.4%
팽 31
 
2.3%
늘 31
 
2.3%
Other values (102) 793
58.6%
ASCII
ValueCountFrequency (%)
) 8
50.0%
( 8
50.0%

대분류명
Categorical

Distinct15
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
엽경채류
120 
버섯류
100 
과실류
81 
조미채소류
63 
근채류
44 
Other values (10)
94 

Length

Max length5
Median length3
Mean length3.5159363
Min length2

Unique

Unique4 ?
Unique (%)0.8%

Sample

1st row과일과채류
2nd row과일과채류
3rd row과실류
4th row과실류
5th row과실류

Common Values

ValueCountFrequency (%)
엽경채류 120
23.9%
버섯류 100
19.9%
과실류 81
16.1%
조미채소류 63
12.5%
근채류 44
 
8.8%
과채류 33
 
6.6%
서류 20
 
4.0%
과일과채류 17
 
3.4%
양채류 10
 
2.0%
산채류 8
 
1.6%
Other values (5) 6
 
1.2%

Length

2023-12-12T14:13:16.319238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
엽경채류 120
23.9%
버섯류 100
19.9%
과실류 81
16.1%
조미채소류 63
12.5%
근채류 44
 
8.8%
과채류 33
 
6.6%
서류 20
 
4.0%
과일과채류 17
 
3.4%
양채류 10
 
2.0%
산채류 8
 
1.6%
Other values (5) 6
 
1.2%

중분류명
Text

Distinct79
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-12T14:13:16.870090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.7290837
Min length1

Characters and Unicode

Total characters1370
Distinct characters114
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

Unique30 ?
Unique (%)6.0%

Sample

1st row딸기
2nd row수박
3rd row배
4th row사과
5th row사과
ValueCountFrequency (%)
마늘 31
 
6.2%
팽이버섯 31
 
6.2%
당근 27
 
5.4%
상추 26
 
5.2%
배추 25
 
5.0%
만가닥 20
 
4.0%
호박 20
 
4.0%
봄동배추 19
 
3.8%
사과 18
 
3.6%
표고버섯 16
 
3.2%
Other values (69) 269
53.6%
2023-12-12T14:13:17.296979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 101
 
7.4%
배 79
 
5.8%
이 67
 
4.9%
섯 66
 
4.8%
버 66
 
4.8%
마 48
 
3.5%
고 39
 
2.8%
리 33
 
2.4%
팽 31
 
2.3%
늘 31
 
2.3%
Other values (104) 809
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1354
98.8%
Close Punctuation 8
 
0.6%
Open Punctuation 8
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 101
 
7.5%
배 79
 
5.8%
이 67
 
4.9%
섯 66
 
4.9%
버 66
 
4.9%
마 48
 
3.5%
고 39
 
2.9%
리 33
 
2.4%
팽 31
 
2.3%
늘 31
 
2.3%
Other values (102) 793
58.6%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1354
98.8%
Common 16
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 101
 
7.5%
배 79
 
5.8%
이 67
 
4.9%
섯 66
 
4.9%
버 66
 
4.9%
마 48
 
3.5%
고 39
 
2.9%
리 33
 
2.4%
팽 31
 
2.3%
늘 31
 
2.3%
Other values (102) 793
58.6%
Common
ValueCountFrequency (%)
) 8
50.0%
( 8
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1354
98.8%
ASCII 16
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 101
 
7.5%
배 79
 
5.8%
이 67
 
4.9%
섯 66
 
4.9%
버 66
 
4.9%
마 48
 
3.5%
고 39
 
2.9%
리 33
 
2.4%
팽 31
 
2.3%
늘 31
 
2.3%
Other values (102) 793
58.6%
ASCII
ValueCountFrequency (%)
) 8
50.0%
( 8
50.0%

소분류명
Text

Distinct78
Distinct (%)15.6%
Missing1
Missing (%)0.2%
Memory size4.1 KiB
2023-12-12T14:13:17.545659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.7305389
Min length1

Characters and Unicode

Total characters1368
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

Unique29 ?
Unique (%)5.8%

Sample

1st row딸기
2nd row수박
3rd row배
4th row사과
5th row사과
ValueCountFrequency (%)
마늘 31
 
6.2%
팽이버섯 31
 
6.2%
당근 27
 
5.4%
상추 26
 
5.2%
배추 25
 
5.0%
만가닥 20
 
4.0%
호박 20
 
4.0%
봄동배추 19
 
3.8%
사과 18
 
3.6%
표고버섯 16
 
3.2%
Other values (68) 268
53.5%
2023-12-12T14:13:17.931079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 101
 
7.4%
배 79
 
5.8%
이 67
 
4.9%
버 66
 
4.8%
섯 66
 
4.8%
마 48
 
3.5%
고 39
 
2.9%
리 33
 
2.4%
감 31
 
2.3%
늘 31
 
2.3%
Other values (103) 807
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1352
98.8%
Open Punctuation 8
 
0.6%
Close Punctuation 8
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 101
 
7.5%
배 79
 
5.8%
이 67
 
5.0%
버 66
 
4.9%
섯 66
 
4.9%
마 48
 
3.6%
고 39
 
2.9%
리 33
 
2.4%
감 31
 
2.3%
늘 31
 
2.3%
Other values (101) 791
58.5%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1352
98.8%
Common 16
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 101
 
7.5%
배 79
 
5.8%
이 67
 
5.0%
버 66
 
4.9%
섯 66
 
4.9%
마 48
 
3.6%
고 39
 
2.9%
리 33
 
2.4%
감 31
 
2.3%
늘 31
 
2.3%
Other values (101) 791
58.5%
Common
ValueCountFrequency (%)
( 8
50.0%
) 8
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1352
98.8%
ASCII 16
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 101
 
7.5%
배 79
 
5.8%
이 67
 
5.0%
버 66
 
4.9%
섯 66
 
4.9%
마 48
 
3.6%
고 39
 
2.9%
리 33
 
2.4%
감 31
 
2.3%
늘 31
 
2.3%
Other values (101) 791
58.5%
ASCII
ValueCountFrequency (%)
( 8
50.0%
) 8
50.0%

SMS수신여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size634.0 B
False
293 
True
209 
ValueCountFrequency (%)
False 293
58.4%
True 209
41.6%
2023-12-12T14:13:18.039148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T14:13:14.885255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:13:18.103853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중도매인코드품목명대분류명중분류명소분류명SMS수신여부
중도매인코드1.0000.7880.6240.7880.7800.520
품목명0.7881.0001.0001.0001.0000.735
대분류명0.6241.0001.0001.0001.0000.519
중분류명0.7881.0001.0001.0001.0000.735
소분류명0.7801.0001.0001.0001.0000.751
SMS수신여부0.5200.7350.5190.7350.7511.000
2023-12-12T14:13:18.210822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류명SMS수신여부
대분류명1.0000.470
SMS수신여부0.4701.000
2023-12-12T14:13:18.289325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중도매인코드대분류명SMS수신여부
중도매인코드1.0000.2990.526
대분류명0.2991.0000.470
SMS수신여부0.5260.4701.000

Missing values

2023-12-12T14:13:15.013424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:13:15.159455image/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

중도매인코드품목명대분류명중분류명소분류명SMS수신여부
0200001딸기과일과채류딸기딸기Y
1200001수박과일과채류수박수박Y
2200001배과실류배배Y
3200001사과과실류사과사과Y
4200002사과과실류사과사과Y
5200004현미미곡류현미<NA>Y
6200007태극삼인삼류태극삼태극삼Y
7200017사과과실류사과사과Y
8200122마늘조미채소류마늘마늘Y
9200123마늘조미채소류마늘마늘Y
중도매인코드품목명대분류명중분류명소분류명SMS수신여부
492201473목이버섯류목이목이N
493201473표고버섯버섯류표고버섯표고버섯N
494201474도토리수실류도토리도토리N
495201474숙주나물엽경채류숙주나물숙주나물N
496201474메밀잡곡류메밀메밀N
497201474콩나물엽경채류콩나물콩나물N
498201474콩두류콩콩N
499201497수박과일과채류수박수박Y
500201498수박과일과채류수박수박N
501201499수박과일과채류수박수박Y