Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows455
Duplicate rows (%)4.5%
Total size in memory996.1 KiB
Average record size in memory102.0 B

Variable types

Categorical4
Text3
Numeric4

Dataset

Description대전광역시 노은농수산물도매시장 경락정보입니다. 해당데이터는 도매시장안법인명, 품목명, 품종명, 산지명, 단위수량, 가격, 적재일시, 총물량 등을 포함하고 있습니다. 참고사항으로 단위는 1KG입니다. 2022년 1월~12월 실시간 경락정보 데이터이며, 추후 오픈api로 개발하여 제공할 예정입니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15119450/fileData.do

Alerts

도매시장명 has constant value ""Constant
적재일시 has constant value ""Constant
Dataset has 455 (4.5%) duplicate rowsDuplicates
수량 is highly overall correlated with 총물량High correlation
총물량 is highly overall correlated with 수량High correlation

Reproduction

Analysis started2024-04-17 13:30:39.828281
Analysis finished2024-04-17 13:30:42.203532
Duration2.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
202201
7371 
202202
2629 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202201
2nd row202201
3rd row202201
4th row202201
5th row202201

Common Values

ValueCountFrequency (%)
202201 7371
73.7%
202202 2629
 
26.3%

Length

2024-04-17T22:30:42.257455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:30:42.329565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202201 7371
73.7%
202202 2629
 
26.3%

도매시장명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대전노은도매
10000 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전노은도매 10000
100.0%

Length

2024-04-17T22:30:42.411501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:30:42.486200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전노은도매 10000
100.0%

도매시장안법인명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대전중앙청과
6119 
대전원협(공)
3881 

Length

Max length7
Median length6
Mean length6.3881
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대전중앙청과
2nd row대전중앙청과
3rd row대전중앙청과
4th row대전중앙청과
5th row대전원협(공)

Common Values

ValueCountFrequency (%)
대전중앙청과 6119
61.2%
대전원협(공) 3881
38.8%

Length

2024-04-17T22:30:42.575849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:30:42.684278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전중앙청과 6119
61.2%
대전원협(공 3881
38.8%

품목명
Text

Distinct139
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T22:30:42.945485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length2.6931
Min length1

Characters and Unicode

Total characters26931
Distinct characters181
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

Unique9 ?
Unique (%)0.1%

Sample

1st row만감
2nd row감귤
3rd row숙주나물
4th row새발나물
5th row근대
ValueCountFrequency (%)
딸기 1151
 
11.3%
감귤 880
 
8.6%
만감 433
 
4.2%
사과 424
 
4.2%
깻잎 286
 
2.8%
토마토 275
 
2.7%
호박 232
 
2.3%
시금치 230
 
2.3%
상추 230
 
2.3%
배 219
 
2.1%
Other values (131) 5840
57.3%
2024-04-17T22:30:43.751945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
감 1593
 
5.9%
기 1232
 
4.6%
딸 1151
 
4.3%
추 1113
 
4.1%
귤 880
 
3.3%
나 861
 
3.2%
리 746
 
2.8%
토 742
 
2.8%
배 661
 
2.5%
파 623
 
2.3%
Other values (171) 17329
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26301
97.7%
Close Punctuation 215
 
0.8%
Open Punctuation 215
 
0.8%
Space Separator 200
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
감 1593
 
6.1%
기 1232
 
4.7%
딸 1151
 
4.4%
추 1113
 
4.2%
귤 880
 
3.3%
나 861
 
3.3%
리 746
 
2.8%
토 742
 
2.8%
배 661
 
2.5%
파 623
 
2.4%
Other values (168) 16699
63.5%
Close Punctuation
ValueCountFrequency (%)
) 215
100.0%
Open Punctuation
ValueCountFrequency (%)
( 215
100.0%
Space Separator
ValueCountFrequency (%)
200
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26301
97.7%
Common 630
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
감 1593
 
6.1%
기 1232
 
4.7%
딸 1151
 
4.4%
추 1113
 
4.2%
귤 880
 
3.3%
나 861
 
3.3%
리 746
 
2.8%
토 742
 
2.8%
배 661
 
2.5%
파 623
 
2.4%
Other values (168) 16699
63.5%
Common
ValueCountFrequency (%)
) 215
34.1%
( 215
34.1%
200
31.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26301
97.7%
ASCII 630
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
감 1593
 
6.1%
기 1232
 
4.7%
딸 1151
 
4.4%
추 1113
 
4.2%
귤 880
 
3.3%
나 861
 
3.3%
리 746
 
2.8%
토 742
 
2.8%
배 661
 
2.5%
파 623
 
2.4%
Other values (168) 16699
63.5%
ASCII
ValueCountFrequency (%)
) 215
34.1%
( 215
34.1%
200
31.7%

품종명
Text

Distinct275
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T22:30:44.064103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length4.4589
Min length1

Characters and Unicode

Total characters44589
Distinct characters248
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)0.4%

Sample

1st row한라봉
2nd row조생귤
3rd row숙주나물(수입)
4th row새발나물(일반)
5th row근대(일반)
ValueCountFrequency (%)
설향 1092
 
10.9%
조생귤 548
 
5.5%
후지 373
 
3.7%
신고 219
 
2.2%
완숙토마토 215
 
2.1%
시금치(일반 214
 
2.1%
백다다기 178
 
1.8%
대파(일반 166
 
1.7%
부유 165
 
1.6%
기타만감 164
 
1.6%
Other values (266) 6706
66.8%
2024-04-17T22:30:44.430650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 3378
 
7.6%
) 3363
 
7.5%
일 2661
 
6.0%
반 2626
 
5.9%
향 1227
 
2.8%
기 1221
 
2.7%
타 1123
 
2.5%
설 1092
 
2.4%
추 881
 
2.0%
수 834
 
1.9%
Other values (238) 26183
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37709
84.6%
Open Punctuation 3378
 
7.6%
Close Punctuation 3363
 
7.5%
Decimal Number 96
 
0.2%
Space Separator 40
 
0.1%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 2661
 
7.1%
반 2626
 
7.0%
향 1227
 
3.3%
기 1221
 
3.2%
타 1123
 
3.0%
설 1092
 
2.9%
추 881
 
2.3%
수 834
 
2.2%
나 823
 
2.2%
입 795
 
2.1%
Other values (232) 24426
64.8%
Decimal Number
ValueCountFrequency (%)
1 94
97.9%
4 2
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 3378
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3363
100.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37709
84.6%
Common 6880
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 2661
 
7.1%
반 2626
 
7.0%
향 1227
 
3.3%
기 1221
 
3.2%
타 1123
 
3.0%
설 1092
 
2.9%
추 881
 
2.3%
수 834
 
2.2%
나 823
 
2.2%
입 795
 
2.1%
Other values (232) 24426
64.8%
Common
ValueCountFrequency (%)
( 3378
49.1%
) 3363
48.9%
1 94
 
1.4%
40
 
0.6%
_ 3
 
< 0.1%
4 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37709
84.6%
ASCII 6880
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 3378
49.1%
) 3363
48.9%
1 94
 
1.4%
40
 
0.6%
_ 3
 
< 0.1%
4 2
 
< 0.1%
Hangul
ValueCountFrequency (%)
일 2661
 
7.1%
반 2626
 
7.0%
향 1227
 
3.3%
기 1221
 
3.2%
타 1123
 
3.0%
설 1092
 
2.9%
추 881
 
2.3%
수 834
 
2.2%
나 823
 
2.2%
입 795
 
2.1%
Other values (232) 24426
64.8%

산지명
Text

Distinct130
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T22:30:44.743273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length9
Mean length5.0519
Min length2

Characters and Unicode

Total characters50519
Distinct characters118
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

Unique8 ?
Unique (%)0.1%

Sample

1st row제주도 서귀포시
2nd row제주도 서귀포시
3rd row중국
4th row전라남도 신안군
5th row기타
ValueCountFrequency (%)
기타 3882
25.5%
경상남도 1312
 
8.6%
제주도 1132
 
7.4%
서귀포시 732
 
4.8%
충청남도 700
 
4.6%
경기도 477
 
3.1%
진주시 424
 
2.8%
전라남도 392
 
2.6%
하동군 361
 
2.4%
경상북도 345
 
2.3%
Other values (135) 5463
35.9%
2024-04-17T22:30:45.393749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5220
 
10.3%
도 4913
 
9.7%
기 4360
 
8.6%
타 3882
 
7.7%
시 3318
 
6.6%
남 2649
 
5.2%
주 2407
 
4.8%
경 2138
 
4.2%
군 1864
 
3.7%
상 1722
 
3.4%
Other values (108) 18046
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45291
89.7%
Space Separator 5220
 
10.3%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 4913
 
10.8%
기 4360
 
9.6%
타 3882
 
8.6%
시 3318
 
7.3%
남 2649
 
5.8%
주 2407
 
5.3%
경 2138
 
4.7%
군 1864
 
4.1%
상 1722
 
3.8%
제 1548
 
3.4%
Other values (105) 16490
36.4%
Space Separator
ValueCountFrequency (%)
5220
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45291
89.7%
Common 5228
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 4913
 
10.8%
기 4360
 
9.6%
타 3882
 
8.6%
시 3318
 
7.3%
남 2649
 
5.8%
주 2407
 
5.3%
경 2138
 
4.7%
군 1864
 
4.1%
상 1722
 
3.8%
제 1548
 
3.4%
Other values (105) 16490
36.4%
Common
ValueCountFrequency (%)
5220
99.8%
( 4
 
0.1%
) 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45291
89.7%
ASCII 5228
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5220
99.8%
( 4
 
0.1%
) 4
 
0.1%
Hangul
ValueCountFrequency (%)
도 4913
 
10.8%
기 4360
 
9.6%
타 3882
 
8.6%
시 3318
 
7.3%
남 2649
 
5.8%
주 2407
 
5.3%
경 2138
 
4.7%
군 1864
 
4.1%
상 1722
 
3.8%
제 1548
 
3.4%
Other values (105) 16490
36.4%

수량
Real number (ℝ)

HIGH CORRELATION 

Distinct210
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.7665
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T22:30:45.610906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median11
Q330
95-th percentile107
Maximum1000
Range999
Interquartile range (IQR)26

Descriptive statistics

Standard deviation54.181668
Coefficient of variation (CV)1.8834988
Kurtosis72.696961
Mean28.7665
Median Absolute Deviation (MAD)9
Skewness6.5888571
Sum287665
Variance2935.6531
MonotonicityNot monotonic
2024-04-17T22:30:45.770139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1077
 
10.8%
2 797
 
8.0%
5 616
 
6.2%
3 553
 
5.5%
10 524
 
5.2%
4 416
 
4.2%
20 312
 
3.1%
6 283
 
2.8%
8 250
 
2.5%
7 234
 
2.3%
Other values (200) 4938
49.4%
ValueCountFrequency (%)
1 1077
10.8%
2 797
8.0%
3 553
5.5%
4 416
 
4.2%
5 616
6.2%
6 283
 
2.8%
7 234
 
2.3%
8 250
 
2.5%
9 181
 
1.8%
10 524
5.2%
ValueCountFrequency (%)
1000 3
 
< 0.1%
900 1
 
< 0.1%
750 3
 
< 0.1%
720 2
 
< 0.1%
676 1
 
< 0.1%
600 3
 
< 0.1%
560 1
 
< 0.1%
540 1
 
< 0.1%
525 1
 
< 0.1%
500 10
0.1%

가격
Real number (ℝ)

Distinct933
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20457.816
Minimum0
Maximum290000
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T22:30:45.947429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2929
Q17800
median15000
Q326800
95-th percentile57000
Maximum290000
Range290000
Interquartile range (IQR)19000

Descriptive statistics

Standard deviation20279.663
Coefficient of variation (CV)0.9912917
Kurtosis25.848408
Mean20457.816
Median Absolute Deviation (MAD)8500
Skewness3.664126
Sum2.0457816 × 108
Variance4.1126472 × 108
MonotonicityNot monotonic
2024-04-17T22:30:46.082592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16000 170
 
1.7%
10000 141
 
1.4%
18000 138
 
1.4%
20000 138
 
1.4%
15000 128
 
1.3%
8000 128
 
1.3%
5000 126
 
1.3%
3500 118
 
1.2%
9000 117
 
1.2%
14000 115
 
1.1%
Other values (923) 8681
86.8%
ValueCountFrequency (%)
0 3
 
< 0.1%
100 6
 
0.1%
320 9
 
0.1%
371 1
 
< 0.1%
400 1
 
< 0.1%
424 36
0.4%
530 3
 
< 0.1%
600 3
 
< 0.1%
636 4
 
< 0.1%
760 1
 
< 0.1%
ValueCountFrequency (%)
290000 1
 
< 0.1%
280000 2
< 0.1%
270000 1
 
< 0.1%
250000 1
 
< 0.1%
245000 1
 
< 0.1%
222400 1
 
< 0.1%
215000 3
< 0.1%
192400 1
 
< 0.1%
186000 1
 
< 0.1%
182400 1
 
< 0.1%

적재일시
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20200000000000
10000 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200000000000
2nd row20200000000000
3rd row20200000000000
4th row20200000000000
5th row20200000000000

Common Values

ValueCountFrequency (%)
20200000000000 10000
100.0%

Length

2024-04-17T22:30:46.234916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T22:30:46.329904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200000000000 10000
100.0%

단위당 수량
Real number (ℝ)

Distinct62
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.974158
Minimum0.05
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T22:30:46.443932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile1
Q12
median5
Q310
95-th percentile15
Maximum21
Range20.95
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.7720227
Coefficient of variation (CV)0.79877744
Kurtosis0.92111031
Mean5.974158
Median Absolute Deviation (MAD)3
Skewness1.1761198
Sum59741.58
Variance22.7722
MonotonicityNot monotonic
2024-04-17T22:30:46.594054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.0 1748
17.5%
10.0 1687
16.9%
4.0 1320
13.2%
2.0 1209
12.1%
1.0 1051
10.5%
3.0 466
 
4.7%
8.0 421
 
4.2%
20.0 347
 
3.5%
15.0 341
 
3.4%
13.0 184
 
1.8%
Other values (52) 1226
12.3%
ValueCountFrequency (%)
0.05 14
 
0.1%
0.06 1
 
< 0.1%
0.07 1
 
< 0.1%
0.08 1
 
< 0.1%
0.09 1
 
< 0.1%
0.1 66
0.7%
0.15 4
 
< 0.1%
0.16 1
 
< 0.1%
0.18 4
 
< 0.1%
0.2 9
 
0.1%
ValueCountFrequency (%)
21.0 1
 
< 0.1%
20.0 347
3.5%
18.0 62
 
0.6%
17.0 16
 
0.2%
16.0 57
 
0.6%
15.0 341
3.4%
14.0 2
 
< 0.1%
13.0 184
1.8%
12.0 52
 
0.5%
11.5 11
 
0.1%

총물량
Real number (ℝ)

HIGH CORRELATION 

Distinct582
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean153.41237
Minimum0.05
Maximum13520
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T22:30:46.835960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile4
Q115
median45
Q3136
95-th percentile630.5
Maximum13520
Range13519.95
Interquartile range (IQR)121

Descriptive statistics

Standard deviation366.87975
Coefficient of variation (CV)2.3914613
Kurtosis244.3922
Mean153.41237
Median Absolute Deviation (MAD)37
Skewness10.616922
Sum1534123.7
Variance134600.75
MonotonicityNot monotonic
2024-04-17T22:30:47.018726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.0 475
 
4.8%
10.0 461
 
4.6%
40.0 363
 
3.6%
8.0 344
 
3.4%
4.0 322
 
3.2%
30.0 273
 
2.7%
60.0 237
 
2.4%
2.0 217
 
2.2%
5.0 217
 
2.2%
100.0 215
 
2.1%
Other values (572) 6876
68.8%
ValueCountFrequency (%)
0.05 7
0.1%
0.1 9
0.1%
0.16 1
 
< 0.1%
0.18 1
 
< 0.1%
0.2 6
 
0.1%
0.3 2
 
< 0.1%
0.4 1
 
< 0.1%
0.5 15
0.1%
0.54 1
 
< 0.1%
0.7 3
 
< 0.1%
ValueCountFrequency (%)
13520.0 1
 
< 0.1%
8400.0 1
 
< 0.1%
7350.0 1
 
< 0.1%
6000.0 1
 
< 0.1%
4000.0 4
< 0.1%
3940.0 1
 
< 0.1%
3600.0 5
0.1%
3375.0 5
0.1%
3240.0 2
 
< 0.1%
3150.0 3
< 0.1%

Interactions

2024-04-17T22:30:41.644795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:40.630681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:40.968025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:41.331293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:41.720322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:40.705994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:41.067271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:41.411413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:41.807658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:40.785033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:41.150666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:41.497657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:41.886826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:40.858082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:41.240226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:30:41.567139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T22:30:47.129889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월도매시장안법인명수량가격단위당 수량총물량
연월1.0000.0210.0000.1260.1220.000
도매시장안법인명0.0211.0000.1070.0370.1450.054
수량0.0000.1071.0000.0630.2050.741
가격0.1260.0370.0631.0000.5050.000
단위당 수량0.1220.1450.2050.5051.0000.280
총물량0.0000.0540.7410.0000.2801.000
2024-04-17T22:30:47.242133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월도매시장안법인명
연월1.0000.013
도매시장안법인명0.0131.000
2024-04-17T22:30:47.343799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수량가격단위당 수량총물량연월도매시장안법인명
수량1.000-0.284-0.0890.8200.0000.082
가격-0.2841.0000.379-0.0230.0970.028
단위당 수량-0.0890.3791.0000.4550.0940.111
총물량0.820-0.0230.4551.0000.0000.058
연월0.0000.0970.0940.0001.0000.013
도매시장안법인명0.0820.0280.1110.0580.0131.000

Missing values

2024-04-17T22:30:41.999576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T22:30:42.127284image/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

연월도매시장명도매시장안법인명품목명품종명산지명수량가격적재일시단위당 수량총물량
11047202201대전노은도매대전중앙청과만감한라봉제주도 서귀포시1513100202000000000003.045.0
30014202201대전노은도매대전중앙청과감귤조생귤제주도 서귀포시226200202000000000005.0110.0
18899202201대전노은도매대전중앙청과숙주나물숙주나물(수입)중국204500202000000000003.570.0
60759202201대전노은도매대전중앙청과새발나물새발나물(일반)전라남도 신안군1011600202000000000004.040.0
10357202201대전노은도매대전원협(공)근대근대(일반)기타111700202000000000004.04.0
56358202201대전노은도매대전원협(공)단감부유기타7256002020000000000010.070.0
36658202201대전노은도매대전중앙청과대파대파(일반)전라남도 신안군1223860202000000000004.0488.0
30637202201대전노은도매대전원협(공)참다래(키위)기타참다래(키위)기타75026000202000000000002.31725.0
91267202202대전노은도매대전중앙청과곡물제조순두부(수입)미국2140002020000000000016.032.0
87234202202대전노은도매대전원협(공)무순무순(일반)기타35900202000000000001.035.0
연월도매시장명도매시장안법인명품목명품종명산지명수량가격적재일시단위당 수량총물량
24865202201대전노은도매대전중앙청과식용허브기타경기도 광주시21060202000000000000.10.2
58660202201대전노은도매대전중앙청과단감부유광주광역시 광산구10300002020000000000010.0100.0
14432202201대전노은도매대전중앙청과양파양파(일반)경상남도 합천군12890002020000000000015.01920.0
33843202201대전노은도매대전중앙청과딸기설향충청남도 논산시3113700202000000000001.031.0
78408202202대전노은도매대전중앙청과감귤비가림감귤제주도 서귀포시1111500202000000000005.055.0
79374202202대전노은도매대전원협(공)케일쌈케일기타16500202000000000002.02.0
91065202202대전노은도매대전중앙청과감자기타감자제주도 서귀포시58135002020000000000020.01160.0
75501202202대전노은도매대전중앙청과근대근대(일반)경기도 이천시204600202000000000004.080.0
22688202201대전노은도매대전중앙청과딸기설향경상남도 진주시1527000202000000000002.030.0
56486202201대전노은도매대전중앙청과만감한라봉제주도 서귀포시2218000202000000000003.066.0

Duplicate rows

Most frequently occurring

연월도매시장명도매시장안법인명품목명품종명산지명수량가격적재일시단위당 수량총물량# duplicates
194202201대전노은도매대전중앙청과바나나바나나(수입)필리핀1240002020000000000013.013.011
201202201대전노은도매대전중앙청과바나나바나나(수입)필리핀3240002020000000000013.039.010
325202201대전노은도매대전중앙청과콩나물콩나물(수입)중국103500202000000000003.535.010
323202201대전노은도매대전중앙청과콩나물콩나물(수입)중국53500202000000000003.517.59
186202201대전노은도매대전중앙청과무순무순(일반)경기도 의왕시50424202000000000000.15.08
242202201대전노은도매대전중앙청과숙주나물숙주나물(수입)중국105000202000000000003.535.07
80202201대전노은도매대전원협(공)콩나물콩나물(일반)기타2100002020000000000010.020.06
185202201대전노은도매대전중앙청과무순무순(일반)경기도 의왕시30424202000000000000.13.06
238202201대전노은도매대전중앙청과숙주나물숙주나물(수입)중국35000202000000000003.510.56
321202201대전노은도매대전중앙청과콩나물콩나물(수입)중국33500202000000000003.510.56