Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows2449
Duplicate rows (%)24.5%
Total size in memory888.7 KiB
Average record size in memory91.0 B

Variable types

Numeric3
Categorical2
Text5

Dataset

Description농림수산식품교육문화정보원 농업온 시스템의 경락 가격에서 사용되는 컬럼에 대한 데이터로서 도매시장코드, 도매시장명, 법인코드, 도매법인명, 대분류코드, 대분류명, 중분류코드, 중분류명, 소분류코드, 소분류명명 항목을 포함하고 있습니다.
Author농림수산식품교육문화정보원
URLhttps://www.data.go.kr/data/15122557/fileData.do

Alerts

Dataset has 2449 (24.5%) duplicate rowsDuplicates
도매시장코드 is highly overall correlated with 법인코드 and 1 other fieldsHigh correlation
법인코드 is highly overall correlated with 도매시장코드 and 1 other fieldsHigh correlation
대분류코드 is highly overall correlated with 대분류명High correlation
도매시장명 is highly overall correlated with 도매시장코드 and 1 other fieldsHigh correlation
대분류명 is highly overall correlated with 대분류코드High correlation

Reproduction

Analysis started2023-12-12 16:53:48.894257
Analysis finished2023-12-12 16:53:51.469901
Duration2.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도매시장코드
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean270902.06
Minimum110001
Maximum380401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:53:51.568301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110001
5-th percentile110001
Q1220001
median250001
Q3330101
95-th percentile380303
Maximum380401
Range270400
Interquartile range (IQR)110100

Descriptive statistics

Standard deviation75797.544
Coefficient of variation (CV)0.27979686
Kurtosis-0.48688291
Mean270902.06
Median Absolute Deviation (MAD)60900
Skewness-0.3522508
Sum2.7090206 × 109
Variance5.7452677 × 109
MonotonicityNot monotonic
2023-12-13T01:53:51.721678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
230001 866
 
8.7%
220001 767
 
7.7%
210001 564
 
5.6%
110001 564
 
5.6%
310901 544
 
5.4%
330101 534
 
5.3%
230003 522
 
5.2%
380201 472
 
4.7%
210009 463
 
4.6%
311201 430
 
4.3%
Other values (19) 4274
42.7%
ValueCountFrequency (%)
110001 564
5.6%
110008 279
 
2.8%
210001 564
5.6%
210005 5
 
0.1%
210009 463
4.6%
220001 767
7.7%
230001 866
8.7%
230003 522
5.2%
240001 341
 
3.4%
240004 401
4.0%
ValueCountFrequency (%)
380401 171
 
1.7%
380303 370
3.7%
380201 472
4.7%
380101 298
3.0%
371501 139
 
1.4%
370401 57
 
0.6%
360301 176
 
1.8%
350101 99
 
1.0%
330201 288
2.9%
330101 534
5.3%

도매시장명
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
인천구월도매
866 
대구북부도매
767 
부산엄궁도매
 
564
서울가락도매
 
564
안산도매시장
 
544
Other values (24)
6695 

Length

Max length9
Median length6
Mean length6.1351
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대전오정도매
2nd row안산도매시장
3rd row인천삼산도매
4th row부산엄궁도매
5th row강릉도매시장

Common Values

ValueCountFrequency (%)
인천구월도매 866
 
8.7%
대구북부도매 767
 
7.7%
부산엄궁도매 564
 
5.6%
서울가락도매 564
 
5.6%
안산도매시장 544
 
5.4%
청주도매시장 534
 
5.3%
인천삼산도매 522
 
5.2%
울산도매시장 472
 
4.7%
부산반여도매 463
 
4.6%
구리도매시장 430
 
4.3%
Other values (19) 4274
42.7%

Length

2023-12-13T01:53:51.891121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인천구월도매 866
 
8.7%
대구북부도매 767
 
7.7%
부산엄궁도매 564
 
5.6%
서울가락도매 564
 
5.6%
안산도매시장 544
 
5.4%
청주도매시장 534
 
5.3%
인천삼산도매 522
 
5.2%
울산도매시장 472
 
4.7%
부산반여도매 463
 
4.6%
구리도매시장 430
 
4.3%
Other values (19) 4274
42.7%

법인코드
Real number (ℝ)

HIGH CORRELATION 

Distinct84
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27090208
Minimum11000101
Maximum38040101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:53:52.043474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11000101
5-th percentile11000105
Q122000105
median25000104
Q333010101
95-th percentile38030301
Maximum38040101
Range27040000
Interquartile range (IQR)11009996

Descriptive statistics

Standard deviation7579754
Coefficient of variation (CV)0.27979682
Kurtosis-0.48688285
Mean27090208
Median Absolute Deviation (MAD)6089997
Skewness-0.35225085
Sum2.7090208 × 1011
Variance5.7452671 × 1013
MonotonicityNot monotonic
2023-12-13T01:53:52.203986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32030101 298
 
3.0%
23000303 247
 
2.5%
23000101 247
 
2.5%
38020101 237
 
2.4%
33010101 236
 
2.4%
33010102 221
 
2.2%
21000101 221
 
2.2%
31090101 219
 
2.2%
21000901 215
 
2.1%
23000102 214
 
2.1%
Other values (74) 7645
76.4%
ValueCountFrequency (%)
11000101 97
1.0%
11000102 98
1.0%
11000103 112
1.1%
11000104 100
1.0%
11000105 108
1.1%
11000106 7
 
0.1%
11000108 42
 
0.4%
11000801 96
1.0%
11000802 93
0.9%
11000803 90
0.9%
ValueCountFrequency (%)
38040101 171
1.7%
38030302 210
2.1%
38030301 160
1.6%
38020103 32
 
0.3%
38020102 203
2.0%
38020101 237
2.4%
38010102 169
1.7%
38010101 129
1.3%
37150102 63
 
0.6%
37150101 76
 
0.8%

도매법인명
Text

Distinct83
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:53:52.531241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length5.4651
Min length4

Characters and Unicode

Total characters54651
Distinct characters74
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st row대전한밭
2nd row농협안산(공)
3rd row삼산원협(공)
4th row항도청과
5th row강릉농산물
ValueCountFrequency (%)
강릉농산물 298
 
3.0%
대인농산 247
 
2.5%
삼산원협(공 247
 
2.5%
울산원협(공 237
 
2.4%
충북원협(청주 236
 
2.4%
청주청과 221
 
2.2%
농협부산(공 221
 
2.2%
농협안산(공 219
 
2.2%
동부청과 215
 
2.1%
인천농산물 214
 
2.1%
Other values (73) 7645
76.4%
2023-12-13T01:53:53.044450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
청 5110
 
9.4%
과 4576
 
8.4%
( 3815
 
7.0%
) 3815
 
7.0%
협 3810
 
7.0%
산 3524
 
6.4%
공 3370
 
6.2%
원 2919
 
5.3%
농 2585
 
4.7%
주 1562
 
2.9%
Other values (64) 19565
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47021
86.0%
Open Punctuation 3815
 
7.0%
Close Punctuation 3815
 
7.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 5110
 
10.9%
과 4576
 
9.7%
협 3810
 
8.1%
산 3524
 
7.5%
공 3370
 
7.2%
원 2919
 
6.2%
농 2585
 
5.5%
주 1562
 
3.3%
대 1321
 
2.8%
중 1074
 
2.3%
Other values (62) 17170
36.5%
Open Punctuation
ValueCountFrequency (%)
( 3815
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3815
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47021
86.0%
Common 7630
 
14.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 5110
 
10.9%
과 4576
 
9.7%
협 3810
 
8.1%
산 3524
 
7.5%
공 3370
 
7.2%
원 2919
 
6.2%
농 2585
 
5.5%
주 1562
 
3.3%
대 1321
 
2.8%
중 1074
 
2.3%
Other values (62) 17170
36.5%
Common
ValueCountFrequency (%)
( 3815
50.0%
) 3815
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47021
86.0%
ASCII 7630
 
14.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
청 5110
 
10.9%
과 4576
 
9.7%
협 3810
 
8.1%
산 3524
 
7.5%
공 3370
 
7.2%
원 2919
 
6.2%
농 2585
 
5.5%
주 1562
 
3.3%
대 1321
 
2.8%
중 1074
 
2.3%
Other values (62) 17170
36.5%
ASCII
ValueCountFrequency (%)
( 3815
50.0%
) 3815
50.0%

대분류코드
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.0073
Minimum2
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:53:53.239696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q19
median10
Q313
95-th percentile76
Maximum93
Range91
Interquartile range (IQR)4

Descriptive statistics

Standard deviation19.941219
Coefficient of variation (CV)1.1725094
Kurtosis5.9623992
Mean17.0073
Median Absolute Deviation (MAD)2
Skewness2.7378923
Sum170073
Variance397.65221
MonotonicityNot monotonic
2023-12-13T01:53:53.413069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
10 2485
24.9%
13 1256
12.6%
12 1128
11.3%
6 1013
10.1%
8 766
 
7.7%
14 640
 
6.4%
9 513
 
5.1%
17 484
 
4.8%
11 334
 
3.3%
5 242
 
2.4%
Other values (36) 1139
11.4%
ValueCountFrequency (%)
2 1
 
< 0.1%
3 27
 
0.3%
4 1
 
< 0.1%
5 242
 
2.4%
6 1013
10.1%
7 19
 
0.2%
8 766
 
7.7%
9 513
 
5.1%
10 2485
24.9%
11 334
 
3.3%
ValueCountFrequency (%)
93 13
 
0.1%
91 179
1.8%
89 20
 
0.2%
87 3
 
< 0.1%
85 2
 
< 0.1%
84 15
 
0.1%
83 10
 
0.1%
82 6
 
0.1%
81 62
 
0.6%
78 3
 
< 0.1%

대분류명
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
엽경채류
2485 
양채류
1256 
조미채소류
1128 
과실류
1013 
과일과채류
766 
Other values (41)
3352 

Length

Max length8
Median length7
Mean length3.9239
Min length2

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row건제품
2nd row버섯류
3rd row양채류
4th row서류
5th row과일과채류

Common Values

ValueCountFrequency (%)
엽경채류 2485
24.9%
양채류 1256
12.6%
조미채소류 1128
11.3%
과실류 1013
10.1%
과일과채류 766
 
7.7%
산채류 640
 
6.4%
과채류 513
 
5.1%
버섯류 484
 
4.8%
근채류 334
 
3.3%
서류 242
 
2.4%
Other values (36) 1139
11.4%

Length

2023-12-13T01:53:53.582602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
엽경채류 2485
23.1%
양채류 1256
11.7%
조미채소류 1128
10.5%
과실류 1013
9.4%
과일과채류 766
 
7.1%
산채류 640
 
6.0%
신선 532
 
5.0%
과채류 513
 
4.8%
버섯류 484
 
4.5%
근채류 334
 
3.1%
Other values (27) 1594
14.8%

중분류코드
Text

Distinct339
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:53:53.995697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters40000
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)0.6%

Sample

1st row8912
2nd row1719
3rd row1301
4th row0501
5th row0806
ValueCountFrequency (%)
1005 300
 
3.0%
0902 263
 
2.6%
1205 252
 
2.5%
0804 243
 
2.4%
1209 186
 
1.9%
1326 181
 
1.8%
0601 173
 
1.7%
0901 169
 
1.7%
1203 161
 
1.6%
1001 150
 
1.5%
Other values (329) 7922
79.2%
2023-12-13T01:53:54.510474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12186
30.5%
1 10834
27.1%
2 3585
 
9.0%
3 2831
 
7.1%
6 2475
 
6.2%
4 1696
 
4.2%
5 1624
 
4.1%
7 1623
 
4.1%
9 1607
 
4.0%
8 1535
 
3.8%
Other values (2) 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39996
> 99.9%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12186
30.5%
1 10834
27.1%
2 3585
 
9.0%
3 2831
 
7.1%
6 2475
 
6.2%
4 1696
 
4.2%
5 1624
 
4.1%
7 1623
 
4.1%
9 1607
 
4.0%
8 1535
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
V 3
75.0%
E 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39996
> 99.9%
Latin 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12186
30.5%
1 10834
27.1%
2 3585
 
9.0%
3 2831
 
7.1%
6 2475
 
6.2%
4 1696
 
4.2%
5 1624
 
4.1%
7 1623
 
4.1%
9 1607
 
4.0%
8 1535
 
3.8%
Latin
ValueCountFrequency (%)
V 3
75.0%
E 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12186
30.5%
1 10834
27.1%
2 3585
 
9.0%
3 2831
 
7.1%
6 2475
 
6.2%
4 1696
 
4.2%
5 1624
 
4.1%
7 1623
 
4.1%
9 1607
 
4.0%
8 1535
 
3.8%
Other values (2) 4
 
< 0.1%

중분류명
Text

Distinct274
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:53:54.876110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length3.005
Min length1

Characters and Unicode

Total characters30050
Distinct characters269
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

Unique36 ?
Unique (%)0.4%

Sample

1st row명태
2nd row상황버섯
3rd row양상추
4th row감자
5th row방울토마토
ValueCountFrequency (%)
상추 300
 
3.0%
호박 263
 
2.6%
풋고추 252
 
2.5%
딸기 243
 
2.4%
마늘 186
 
1.8%
파프리카 181
 
1.8%
사과 173
 
1.7%
오이 169
 
1.7%
쪽파 161
 
1.6%
배추 150
 
1.5%
Other values (266) 8054
79.5%
2023-12-13T01:53:55.422196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 1750
 
5.8%
리 1144
 
3.8%
고 972
 
3.2%
나 773
 
2.6%
파 749
 
2.5%
배 699
 
2.3%
마 656
 
2.2%
양 644
 
2.1%
이 610
 
2.0%
) 572
 
1.9%
Other values (259) 21481
71.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28774
95.8%
Close Punctuation 572
 
1.9%
Open Punctuation 572
 
1.9%
Space Separator 132
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 1750
 
6.1%
리 1144
 
4.0%
고 972
 
3.4%
나 773
 
2.7%
파 749
 
2.6%
배 699
 
2.4%
마 656
 
2.3%
양 644
 
2.2%
이 610
 
2.1%
토 546
 
1.9%
Other values (256) 20231
70.3%
Close Punctuation
ValueCountFrequency (%)
) 572
100.0%
Open Punctuation
ValueCountFrequency (%)
( 572
100.0%
Space Separator
ValueCountFrequency (%)
132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28774
95.8%
Common 1276
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 1750
 
6.1%
리 1144
 
4.0%
고 972
 
3.4%
나 773
 
2.7%
파 749
 
2.6%
배 699
 
2.4%
마 656
 
2.3%
양 644
 
2.2%
이 610
 
2.1%
토 546
 
1.9%
Other values (256) 20231
70.3%
Common
ValueCountFrequency (%)
) 572
44.8%
( 572
44.8%
132
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28774
95.8%
ASCII 1276
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 1750
 
6.1%
리 1144
 
4.0%
고 972
 
3.4%
나 773
 
2.7%
파 749
 
2.6%
배 699
 
2.4%
마 656
 
2.3%
양 644
 
2.2%
이 610
 
2.1%
토 546
 
1.9%
Other values (256) 20231
70.3%
ASCII
ValueCountFrequency (%)
) 572
44.8%
( 572
44.8%
132
 
10.3%

소분류코드
Text

Distinct873
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:53:55.851814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters60000
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique230 ?
Unique (%)2.3%

Sample

1st row891203
2nd row171901
3rd row130103
4th row050103
5th row080601
ValueCountFrequency (%)
100801 89
 
0.9%
080413 86
 
0.9%
101201 83
 
0.8%
130601 82
 
0.8%
120301 82
 
0.8%
120201 79
 
0.8%
100201 79
 
0.8%
060103 79
 
0.8%
090202 78
 
0.8%
101101 78
 
0.8%
Other values (863) 9185
91.8%
2023-12-13T01:53:56.405512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19582
32.6%
1 15831
26.4%
9 5416
 
9.0%
2 4611
 
7.7%
3 3695
 
6.2%
6 2742
 
4.6%
4 2229
 
3.7%
8 2079
 
3.5%
5 2001
 
3.3%
7 1797
 
3.0%
Other values (3) 17
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59983
> 99.9%
Uppercase Letter 17
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19582
32.6%
1 15831
26.4%
9 5416
 
9.0%
2 4611
 
7.7%
3 3695
 
6.2%
6 2742
 
4.6%
4 2229
 
3.7%
8 2079
 
3.5%
5 2001
 
3.3%
7 1797
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
Z 13
76.5%
V 3
 
17.6%
E 1
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common 59983
> 99.9%
Latin 17
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19582
32.6%
1 15831
26.4%
9 5416
 
9.0%
2 4611
 
7.7%
3 3695
 
6.2%
6 2742
 
4.6%
4 2229
 
3.7%
8 2079
 
3.5%
5 2001
 
3.3%
7 1797
 
3.0%
Latin
ValueCountFrequency (%)
Z 13
76.5%
V 3
 
17.6%
E 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19582
32.6%
1 15831
26.4%
9 5416
 
9.0%
2 4611
 
7.7%
3 3695
 
6.2%
6 2742
 
4.6%
4 2229
 
3.7%
8 2079
 
3.5%
5 2001
 
3.3%
7 1797
 
3.0%
Other values (3) 17
 
< 0.1%

소분류명
Text

Distinct658
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:53:56.677689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length4.5131
Min length1

Characters and Unicode

Total characters45131
Distinct characters379
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)1.6%

Sample

1st row북어채
2nd row상황버섯(일반)
3rd row양상추(일반)
4th row대지
5th row방울토마토
ValueCountFrequency (%)
기타 1542
 
15.4%
시금치(일반 89
 
0.9%
설향 86
 
0.9%
쑥갓(일반 83
 
0.8%
브로코리(일반 82
 
0.8%
쪽파(일반 82
 
0.8%
대파(일반 79
 
0.8%
얼갈이배추 79
 
0.8%
후지 79
 
0.8%
양배추(일반 78
 
0.8%
Other values (651) 7727
77.2%
2023-12-13T01:53:57.072571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 4027
 
8.9%
) 4027
 
8.9%
일 3536
 
7.8%
반 3509
 
7.8%
기 1842
 
4.1%
타 1753
 
3.9%
추 965
 
2.1%
리 954
 
2.1%
파 702
 
1.6%
나 626
 
1.4%
Other values (369) 23190
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37022
82.0%
Open Punctuation 4027
 
8.9%
Close Punctuation 4027
 
8.9%
Decimal Number 49
 
0.1%
Space Separator 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 3536
 
9.6%
반 3509
 
9.5%
기 1842
 
5.0%
타 1753
 
4.7%
추 965
 
2.6%
리 954
 
2.6%
파 702
 
1.9%
나 626
 
1.7%
수 621
 
1.7%
고 571
 
1.5%
Other values (362) 21943
59.3%
Decimal Number
ValueCountFrequency (%)
1 42
85.7%
7 4
 
8.2%
0 2
 
4.1%
2 1
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 4027
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4027
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37022
82.0%
Common 8109
 
18.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 3536
 
9.6%
반 3509
 
9.5%
기 1842
 
5.0%
타 1753
 
4.7%
추 965
 
2.6%
리 954
 
2.6%
파 702
 
1.9%
나 626
 
1.7%
수 621
 
1.7%
고 571
 
1.5%
Other values (362) 21943
59.3%
Common
ValueCountFrequency (%)
( 4027
49.7%
) 4027
49.7%
1 42
 
0.5%
6
 
0.1%
7 4
 
< 0.1%
0 2
 
< 0.1%
2 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37022
82.0%
ASCII 8109
 
18.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 4027
49.7%
) 4027
49.7%
1 42
 
0.5%
6
 
0.1%
7 4
 
< 0.1%
0 2
 
< 0.1%
2 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
일 3536
 
9.6%
반 3509
 
9.5%
기 1842
 
5.0%
타 1753
 
4.7%
추 965
 
2.6%
리 954
 
2.6%
파 702
 
1.9%
나 626
 
1.7%
수 621
 
1.7%
고 571
 
1.5%
Other values (362) 21943
59.3%

Interactions

2023-12-13T01:53:50.825308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:53:50.126704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:53:50.477798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:53:50.940238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:53:50.249236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:53:50.590468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:53:51.067039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:53:50.365441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:53:50.706079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:53:57.183631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도매시장코드도매시장명법인코드도매법인명대분류코드대분류명
도매시장코드1.0001.0001.0001.0000.1540.257
도매시장명1.0001.0001.0001.0000.4010.446
법인코드1.0001.0001.0001.0000.1520.261
도매법인명1.0001.0001.0001.0000.7520.775
대분류코드0.1540.4010.1520.7521.0001.000
대분류명0.2570.4460.2610.7751.0001.000
2023-12-13T01:53:57.279902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도매시장명대분류명
도매시장명1.0000.107
대분류명0.1071.000
2023-12-13T01:53:57.377213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도매시장코드법인코드대분류코드도매시장명대분류명
도매시장코드1.0000.9990.0420.9990.108
법인코드0.9991.0000.0460.9990.108
대분류코드0.0420.0461.0000.1700.998
도매시장명0.9990.9990.1701.0000.107
대분류명0.1080.1080.9980.1071.000

Missing values

2023-12-13T01:53:51.218663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:53:51.386767image/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

도매시장코드도매시장명법인코드도매법인명대분류코드대분류명중분류코드중분류명소분류코드소분류명
6145250001대전오정도매25000105대전한밭89건제품8912명태891203북어채
7184310901안산도매시장31090101농협안산(공)17버섯류1719상황버섯171901상황버섯(일반)
4796230003인천삼산도매23000303삼산원협(공)13양채류1301양상추130103양상추(일반)
1497210001부산엄궁도매21000103항도청과5서류0501감자050103대지
8692320301강릉도매시장32030101강릉농산물8과일과채류0806방울토마토080601방울토마토
3094220001대구북부도매22000106대구원협(공)8과일과채류0802참외080219조은대
2110210009부산반여도매21000903농협반여(공)6과실류0615만감061504한라봉
346110001서울가락도매11000103중앙청과13양채류1399기타139999양채류(기타)
2368220001대구북부도매22000101대구중앙청과10엽경채류1011깻잎101101깻잎(일반)
11160380201울산도매시장38020101울산원협(공)13양채류1315아스파라가스131599기타
도매시장코드도매시장명법인코드도매법인명대분류코드대분류명중분류코드중분류명소분류코드소분류명
10800380101창원팔용도매시장38010102농협창원(공)10엽경채류1002얼갈이배추100201얼갈이배추
10920380101창원팔용도매시장38010102농협창원(공)14산채류1424새싹142401새싹(일반)
6134250001대전오정도매25000104대전수산74신선 해면연체류7407쭈꾸미740701쭈꾸미
9613330101청주도매시장33010103청주수산81냉동 해면어류8102가오리810299기타
10636380101창원팔용도매시장38010101창원청과10엽경채류1001배추100108쌈배추
10730380101창원팔용도매시장38010101창원청과14산채류1407도라지140701도라지(일반)
516110001서울가락도매11000105한국청과8과일과채류0804딸기080413설향
4605230003인천삼산도매23000302경인농산91농림가공9104절임식품910453무장아찌
11666380303창원내서도매시장38030301마산청과13양채류1326파프리카132602노랑파프리카
1341210001부산엄궁도매21000102부산청과9과채류0903가지090301가지(일반)

Duplicate rows

Most frequently occurring

도매시장코드도매시장명법인코드도매법인명대분류코드대분류명중분류코드중분류명소분류코드소분류명# duplicates
0210001부산엄궁도매21000101농협부산(공)5서류0501감자050101수미2
1210001부산엄궁도매21000101농협부산(공)5서류0502고구마050299기타2
2210001부산엄궁도매21000101농협부산(공)6과실류0601사과060103후지2
3210001부산엄궁도매21000101농협부산(공)6과실류0601사과060139미시마2
4210001부산엄궁도매21000101농협부산(공)6과실류0602배060201신고2
5210001부산엄궁도매21000101농협부산(공)6과실류0612바나나061299기타2
6210001부산엄궁도매21000101농협부산(공)6과실류0613파인애플061399기타2
7210001부산엄궁도매21000101농협부산(공)6과실류0614감귤061404비가림감귤2
8210001부산엄궁도매21000101농협부산(공)6과실류0618오렌지061809천혜향2
9210001부산엄궁도매21000101농협부산(공)6과실류0621금감062101금감(일반)2