Overview

Dataset statistics

Number of variables10
Number of observations8143
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory668.1 KiB
Average record size in memory84.0 B

Variable types

Text3
Numeric3
Categorical3
DateTime1

Dataset

Description수산물 수협창고 입출고 정보는 수협이 보유하고 있는 창고(이용가공)에 대한 기본정보 및 해당 창고에 입출고 되는 품목에 대한 정보 및 품목별 입출고 정보, 그리고 해당 창고를 이용하는 매출처에 대한 기본적인 정보를 제공하는 목록입니다.
Author해양수산부
URLhttps://www.data.go.kr/data/15102799/fileData.do

Alerts

입출고구분 is highly overall correlated with 입출고구분명High correlation
입출고구분명 is highly overall correlated with 입출고구분High correlation
조합코드 is highly overall correlated with 창고코드 and 1 other fieldsHigh correlation
창고코드 is highly overall correlated with 조합코드 and 1 other fieldsHigh correlation
창고명 is highly overall correlated with 조합코드 and 1 other fieldsHigh correlation

Reproduction

Analysis started2024-04-21 02:11:25.753287
Analysis finished2024-04-21 02:11:29.305317
Duration3.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

표준코드
Text

Distinct372
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
2024-04-21T11:11:29.512394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters65144
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

Unique57 ?
Unique (%)0.7%

Sample

1st row61010020
2nd row61019930
3rd row61019930
4th row61020020
5th row61020020
ValueCountFrequency (%)
61030030 303
 
3.7%
61a40430 285
 
3.5%
61080230 240
 
2.9%
61a40230 162
 
2.0%
64050130 147
 
1.8%
61440130 144
 
1.8%
63020130 142
 
1.7%
63049930 139
 
1.7%
61zz0030 134
 
1.6%
61960120 130
 
1.6%
Other values (362) 6317
77.6%
2024-04-21T11:11:29.875998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21639
33.2%
6 9295
14.3%
1 9245
14.2%
3 7667
 
11.8%
2 5044
 
7.7%
4 4462
 
6.8%
9 3818
 
5.9%
5 1143
 
1.8%
8 1111
 
1.7%
A 668
 
1.0%
Other values (3) 1052
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64064
98.3%
Uppercase Letter 1080
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21639
33.8%
6 9295
14.5%
1 9245
14.4%
3 7667
 
12.0%
2 5044
 
7.9%
4 4462
 
7.0%
9 3818
 
6.0%
5 1143
 
1.8%
8 1111
 
1.7%
7 640
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
A 668
61.9%
Z 346
32.0%
B 66
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
Common 64064
98.3%
Latin 1080
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21639
33.8%
6 9295
14.5%
1 9245
14.4%
3 7667
 
12.0%
2 5044
 
7.9%
4 4462
 
7.0%
9 3818
 
6.0%
5 1143
 
1.8%
8 1111
 
1.7%
7 640
 
1.0%
Latin
ValueCountFrequency (%)
A 668
61.9%
Z 346
32.0%
B 66
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65144
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21639
33.2%
6 9295
14.3%
1 9245
14.2%
3 7667
 
11.8%
2 5044
 
7.7%
4 4462
 
6.8%
9 3818
 
5.9%
5 1143
 
1.8%
8 1111
 
1.7%
A 668
 
1.0%
Other values (3) 1052
 
1.6%

조합코드
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean359.83888
Minimum300
Maximum516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.7 KiB
2024-04-21T11:11:30.028610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile307
Q1337
median351
Q3368
95-th percentile512
Maximum516
Range216
Interquartile range (IQR)31

Descriptive statistics

Standard deviation51.995022
Coefficient of variation (CV)0.14449529
Kurtosis3.7530952
Mean359.83888
Median Absolute Deviation (MAD)17
Skewness2.0711244
Sum2930168
Variance2703.4823
MonotonicityNot monotonic
2024-04-21T11:11:30.176970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
339 1123
 
13.8%
372 708
 
8.7%
362 439
 
5.4%
311 423
 
5.2%
356 395
 
4.9%
349 308
 
3.8%
361 305
 
3.7%
512 279
 
3.4%
351 246
 
3.0%
369 189
 
2.3%
Other values (42) 3728
45.8%
ValueCountFrequency (%)
300 83
 
1.0%
303 20
 
0.2%
304 105
 
1.3%
305 16
 
0.2%
306 163
 
2.0%
307 109
 
1.3%
308 84
 
1.0%
311 423
5.2%
312 4
 
< 0.1%
313 23
 
0.3%
ValueCountFrequency (%)
516 48
 
0.6%
515 119
 
1.5%
512 279
 
3.4%
511 130
 
1.6%
509 47
 
0.6%
507 73
 
0.9%
505 43
 
0.5%
373 154
 
1.9%
372 708
8.7%
371 38
 
0.5%

창고코드
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3598391.9
Minimum3000002
Maximum5160005
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.7 KiB
2024-04-21T11:11:30.337792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000002
5-th percentile3070002
Q13370002
median3510002
Q33680002
95-th percentile5120002
Maximum5160005
Range2160003
Interquartile range (IQR)310000

Descriptive statistics

Standard deviation519949.88
Coefficient of variation (CV)0.14449507
Kurtosis3.7530963
Mean3598391.9
Median Absolute Deviation (MAD)170000
Skewness2.0711246
Sum2.9301705 × 1010
Variance2.7034788 × 1011
MonotonicityNot monotonic
2024-04-21T11:11:30.521089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3390002 1123
 
13.8%
3720002 639
 
7.8%
3620002 439
 
5.4%
3110002 423
 
5.2%
3560003 349
 
4.3%
3490002 308
 
3.8%
3610002 305
 
3.7%
5120002 279
 
3.4%
3510002 246
 
3.0%
3690002 189
 
2.3%
Other values (50) 3843
47.2%
ValueCountFrequency (%)
3000002 73
 
0.9%
3000114 10
 
0.1%
3030002 20
 
0.2%
3040002 105
 
1.3%
3050002 16
 
0.2%
3060002 163
 
2.0%
3070002 109
 
1.3%
3080007 84
 
1.0%
3110002 423
5.2%
3120002 4
 
< 0.1%
ValueCountFrequency (%)
5160005 48
 
0.6%
5150002 119
 
1.5%
5120002 279
3.4%
5110002 130
 
1.6%
5090002 47
 
0.6%
5070002 73
 
0.9%
5050002 43
 
0.5%
3730002 154
 
1.9%
3720004 69
 
0.8%
3720002 639
7.8%

입출고구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
2
5277 
1
2866 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 5277
64.8%
1 2866
35.2%

Length

2024-04-21T11:11:30.659990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:11:30.754410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5277
64.8%
1 2866
35.2%

기준일자
Date

Distinct31
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
Minimum2024-03-01 00:00:00
Maximum2024-03-31 00:00:00
2024-04-21T11:11:30.862300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:30.992859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

조합명
Text

Distinct52
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
2024-04-21T11:11:31.195470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length9.8028982
Min length9

Characters and Unicode

Total characters79825
Distinct characters83
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row울산수산업협동조합
2nd row영광군수산업협동조합
3rd row영광군수산업협동조합
4th row보령수산업협동조합
5th row경주시수산업협동조합
ValueCountFrequency (%)
여수 1123
 
12.1%
수산업협동조합 1123
 
12.1%
한림수산업협동조합 708
 
7.6%
통영수산업협동조합 439
 
4.7%
강릉시수산업협동조합 423
 
4.6%
마산수산업협동조합 395
 
4.3%
죽변수산업협동조합 308
 
3.3%
진해수산업협동조합 305
 
3.3%
근해통발수산업협동조합 279
 
3.0%
포항수산업협동조합 246
 
2.7%
Other values (43) 3917
42.3%
2024-04-21T11:11:31.538096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 9588
12.0%
산 8979
11.2%
동 8306
10.4%
업 8143
10.2%
협 8143
10.2%
조 8143
10.2%
합 8143
10.2%
여 1123
 
1.4%
1123
 
1.4%
포 1082
 
1.4%
Other values (73) 17052
21.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78702
98.6%
Space Separator 1123
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 9588
12.2%
산 8979
11.4%
동 8306
10.6%
업 8143
10.3%
협 8143
10.3%
조 8143
10.3%
합 8143
10.3%
여 1123
 
1.4%
포 1082
 
1.4%
해 983
 
1.2%
Other values (72) 16069
20.4%
Space Separator
ValueCountFrequency (%)
1123
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78702
98.6%
Common 1123
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 9588
12.2%
산 8979
11.4%
동 8306
10.6%
업 8143
10.3%
협 8143
10.3%
조 8143
10.3%
합 8143
10.3%
여 1123
 
1.4%
포 1082
 
1.4%
해 983
 
1.2%
Other values (72) 16069
20.4%
Common
ValueCountFrequency (%)
1123
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78702
98.6%
ASCII 1123
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 9588
12.2%
산 8979
11.4%
동 8306
10.6%
업 8143
10.3%
협 8143
10.3%
조 8143
10.3%
합 8143
10.3%
여 1123
 
1.4%
포 1082
 
1.4%
해 983
 
1.2%
Other values (72) 16069
20.4%
ASCII
ValueCountFrequency (%)
1123
100.0%

창고명
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
이용가공과(이용)
1134 
이용가공과 (여수수협제빙냉동공장)(이용)
1123 
한림수협(이용과)
639 
제빙냉동공장(이용)
 
423
유통사업과(이용)
 
407
Other values (41)
4417 

Length

Max length22
Median length16
Mean length11.503623
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row울산수협(창고)(이용)
2nd row이용가공사업소(이용)
3rd row이용가공사업소(이용)
4th row이용가공과(이용)
5th row이용가공과(이용)

Common Values

ValueCountFrequency (%)
이용가공과(이용) 1134
 
13.9%
이용가공과 (여수수협제빙냉동공장)(이용) 1123
 
13.8%
한림수협(이용과) 639
 
7.8%
제빙냉동공장(이용) 423
 
5.2%
유통사업과(이용) 407
 
5.0%
마산수협 제빙공장(이용) 349
 
4.3%
사업이용가공과(이용) 308
 
3.8%
이용팀(이용) 305
 
3.7%
이용과(이용) 280
 
3.4%
냉동냉장창고(이용) 279
 
3.4%
Other values (36) 2896
35.6%

Length

2024-04-21T11:11:31.697679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이용가공과(이용 1134
 
11.5%
여수수협제빙냉동공장)(이용 1123
 
11.4%
이용가공과 1123
 
11.4%
한림수협(이용과 639
 
6.5%
제빙공장(이용 461
 
4.7%
제빙냉동공장(이용 423
 
4.3%
유통사업과(이용 407
 
4.1%
마산수협 395
 
4.0%
사업이용가공과(이용 308
 
3.1%
이용팀(이용 305
 
3.1%
Other values (42) 3569
36.1%

표준코드명
Text

Distinct371
Distinct (%)4.6%
Missing3
Missing (%)< 0.1%
Memory size63.7 KiB
2024-04-21T11:11:31.918454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8.0796069
Min length3

Characters and Unicode

Total characters65768
Distinct characters178
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

Unique55 ?
Unique (%)0.7%

Sample

1st row가오리류(냉장/신선)
2nd row기타가오리류(냉동)
3rd row기타가오리류(냉동)
4th row가자미류(냉장/신선)
5th row가자미류(냉장/신선)
ValueCountFrequency (%)
정어리(냉동 261
 
3.2%
갈치류(냉동 249
 
3.1%
고등어(냉동 228
 
2.8%
참조기(냉장/신선 169
 
2.1%
살오징어(냉동 151
 
1.9%
청어(냉동 151
 
1.9%
갈치류(냉장/신선 150
 
1.8%
가자미류(냉장/신선 146
 
1.8%
기타해면기타(냉장/신선 146
 
1.8%
멸치(냉동 144
 
1.8%
Other values (361) 6345
77.9%
2024-04-21T11:11:32.315081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 8160
 
12.4%
) 8160
 
12.4%
냉 7256
 
11.0%
동 4965
 
7.5%
류 3161
 
4.8%
어 2623
 
4.0%
장 2490
 
3.8%
기 2380
 
3.6%
선 2310
 
3.5%
신 2297
 
3.5%
Other values (168) 21966
33.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47151
71.7%
Open Punctuation 8160
 
12.4%
Close Punctuation 8160
 
12.4%
Other Punctuation 2297
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
냉 7256
15.4%
동 4965
 
10.5%
류 3161
 
6.7%
어 2623
 
5.6%
장 2490
 
5.3%
기 2380
 
5.0%
선 2310
 
4.9%
신 2297
 
4.9%
타 1672
 
3.5%
치 1264
 
2.7%
Other values (165) 16733
35.5%
Open Punctuation
ValueCountFrequency (%)
( 8160
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8160
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2297
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47151
71.7%
Common 18617
 
28.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
냉 7256
15.4%
동 4965
 
10.5%
류 3161
 
6.7%
어 2623
 
5.6%
장 2490
 
5.3%
기 2380
 
5.0%
선 2310
 
4.9%
신 2297
 
4.9%
타 1672
 
3.5%
치 1264
 
2.7%
Other values (165) 16733
35.5%
Common
ValueCountFrequency (%)
( 8160
43.8%
) 8160
43.8%
/ 2297
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47151
71.7%
ASCII 18617
 
28.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 8160
43.8%
) 8160
43.8%
/ 2297
 
12.3%
Hangul
ValueCountFrequency (%)
냉 7256
15.4%
동 4965
 
10.5%
류 3161
 
6.7%
어 2623
 
5.6%
장 2490
 
5.3%
기 2380
 
5.0%
선 2310
 
4.9%
신 2297
 
4.9%
타 1672
 
3.5%
치 1264
 
2.7%
Other values (165) 16733
35.5%

입출고구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size63.7 KiB
출고
5277 
입고
2866 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row입고
2nd row입고
3rd row출고
4th row입고
5th row입고

Common Values

ValueCountFrequency (%)
출고 5277
64.8%
입고 2866
35.2%

Length

2024-04-21T11:11:32.444760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:11:32.543169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
출고 5277
64.8%
입고 2866
35.2%

수량
Real number (ℝ)

Distinct1205
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean305.67109
Minimum1
Maximum14261
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size71.7 KiB
2024-04-21T11:11:32.675325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q19
median37
Q3168
95-th percentile1476.2
Maximum14261
Range14260
Interquartile range (IQR)159

Descriptive statistics

Standard deviation934.89061
Coefficient of variation (CV)3.0584855
Kurtosis55.702317
Mean305.67109
Median Absolute Deviation (MAD)34
Skewness6.5352081
Sum2489079.7
Variance874020.45
MonotonicityNot monotonic
2024-04-21T11:11:32.843051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.0 421
 
5.2%
1.0 376
 
4.6%
10.0 286
 
3.5%
3.0 272
 
3.3%
5.0 263
 
3.2%
4.0 194
 
2.4%
20.0 185
 
2.3%
6.0 165
 
2.0%
7.0 146
 
1.8%
30.0 128
 
1.6%
Other values (1195) 5707
70.1%
ValueCountFrequency (%)
1.0 376
4.6%
2.0 421
5.2%
2.4 1
 
< 0.1%
2.5 1
 
< 0.1%
3.0 272
3.3%
3.3 1
 
< 0.1%
3.7 1
 
< 0.1%
4.0 194
2.4%
4.4 3
 
< 0.1%
4.5 4
 
< 0.1%
ValueCountFrequency (%)
14261.0 1
< 0.1%
13375.0 1
< 0.1%
12440.0 1
< 0.1%
11596.0 1
< 0.1%
11107.0 2
< 0.1%
10980.0 1
< 0.1%
10869.0 1
< 0.1%
10855.0 1
< 0.1%
10583.0 1
< 0.1%
10471.0 1
< 0.1%

Interactions

2024-04-21T11:11:28.773068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:28.137777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:28.513179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:28.859457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:28.307920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:28.601219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:28.944253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:28.404091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:11:28.686190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:11:32.948610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조합코드창고코드입출고구분기준일자조합명창고명입출고구분명수량
조합코드1.0001.0000.0990.1431.0000.9970.0990.325
창고코드1.0001.0000.0990.1421.0000.9890.0990.325
입출고구분0.0990.0991.0000.1190.3150.2961.0000.161
기준일자0.1430.1420.1191.0000.3280.3050.1190.024
조합명1.0001.0000.3150.3281.0000.9980.3150.441
창고명0.9970.9890.2960.3050.9981.0000.2960.336
입출고구분명0.0990.0991.0000.1190.3150.2961.0000.161
수량0.3250.3250.1610.0240.4410.3360.1611.000
2024-04-21T11:11:33.058083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
입출고구분입출고구분명창고명
입출고구분1.0001.0000.235
입출고구분명1.0001.0000.235
창고명0.2350.2351.000
2024-04-21T11:11:33.143711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조합코드창고코드수량입출고구분창고명입출고구분명
조합코드1.0001.0000.2260.1230.9200.123
창고코드1.0001.0000.2270.1230.9200.123
수량0.2260.2271.0000.1230.1210.123
입출고구분0.1230.1230.1231.0000.2351.000
창고명0.9200.9200.1210.2351.0000.235
입출고구분명0.1230.1230.1231.0000.2351.000

Missing values

2024-04-21T11:11:29.074395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:11:29.226544image/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

표준코드조합코드창고코드입출고구분기준일자조합명창고명표준코드명입출고구분명수량
061010020358358000212024-03-01울산수산업협동조합울산수협(창고)(이용)가오리류(냉장/신선)입고14.0
161019930329329000212024-03-01영광군수산업협동조합이용가공사업소(이용)기타가오리류(냉동)입고29.0
261019930329329000222024-03-01영광군수산업협동조합이용가공사업소(이용)기타가오리류(냉동)출고29.0
361020020315315000212024-03-01보령수산업협동조합이용가공과(이용)가자미류(냉장/신선)입고39.0
461020020345345000212024-03-01경주시수산업협동조합이용가공과(이용)가자미류(냉장/신선)입고128.0
561020020345345000222024-03-01경주시수산업협동조합이용가공과(이용)가자미류(냉장/신선)출고99.0
661020020358358000212024-03-01울산수산업협동조합울산수협(창고)(이용)가자미류(냉장/신선)입고80.0
761020020362362000212024-03-01통영수산업협동조합이용가공과(이용)가자미류(냉장/신선)입고12.0
861020030306306000222024-03-01동해시수산업협동조합유통가공과(이용)가자미류(냉동)출고29.0
961020030339339000212024-03-01여수 수산업협동조합이용가공과 (여수수협제빙냉동공장)(이용)가자미류(냉동)입고612.0
표준코드조합코드창고코드입출고구분기준일자조합명창고명표준코드명입출고구분명수량
813364030130316316000212024-03-31서산수산업협동조합서산수협제빙냉동공장(이용)낙지(냉동)입고23.0
813464050130311311000222024-03-31강릉시수산업협동조합제빙냉동공장(이용)살오징어(냉동)출고2.0
813564050130347347000222024-03-31구룡포수산업협동조합구룡포수협제빙냉동공장(이용)살오징어(냉동)출고54.0
813664050130350350000222024-03-31영덕북부수산업협동조합이용가공과(이용)살오징어(냉동)출고100.0
813764059930307307000222024-03-31삼척수산업협동조합냉동공장(이용)기타오징어류(냉동)출고20.0
813864059930347347000222024-03-31구룡포수산업협동조합구룡포수협제빙냉동공장(이용)기타오징어류(냉동)출고235.0
813969990020346346000212024-03-31강구수산업협동조합이용가공과(이용)기타해면기타(냉장/신선)입고18.0
814069990020505505000212024-03-31전남정치망수산업협동조합전남정치망수협(냉동창고)기타해면기타(냉장/신선)입고13.0
814169990030353353000212024-03-31거제수산업협동조합거제수협 이용가공공장(이용)기타해면기타(냉동)입고23.0
814273029930316316000212024-03-31서산수산업협동조합서산수협제빙냉동공장(이용)기타민물게류(냉동)입고114.0