Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells4
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory556.6 KiB
Average record size in memory57.0 B

Variable types

Numeric1
Text5

Dataset

Description농림축산식품부에서 제공하는 농수축산물 표준코드 데이터로 부류코드, 부류명, 품목코드, 품목명, 품종코드, 품종명을 제공합니다.
URLhttps://www.data.go.kr/data/15060250/fileData.do

Reproduction

Analysis started2023-12-12 21:41:11.722594
Analysis finished2023-12-12 21:41:13.210671
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

부류코드
Real number (ℝ)

Distinct77
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.4051
Minimum1
Maximum98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:41:13.297574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q122
median26
Q371
95-th percentile84
Maximum98
Range97
Interquartile range (IQR)49

Descriptive statistics

Standard deviation27.375587
Coefficient of variation (CV)0.64557297
Kurtosis-1.4272407
Mean42.4051
Median Absolute Deviation (MAD)17
Skewness0.33532247
Sum424051
Variance749.42274
MonotonicityNot monotonic
2023-12-13T06:41:13.464229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 946
 
9.5%
22 863
 
8.6%
71 840
 
8.4%
81 834
 
8.3%
61 813
 
8.1%
6 449
 
4.5%
26 394
 
3.9%
25 375
 
3.8%
20 348
 
3.5%
43 246
 
2.5%
Other values (67) 3892
38.9%
ValueCountFrequency (%)
1 35
 
0.4%
2 24
 
0.2%
3 59
 
0.6%
4 36
 
0.4%
5 34
 
0.3%
6 449
4.5%
7 85
 
0.9%
8 72
 
0.7%
9 40
 
0.4%
10 166
 
1.7%
ValueCountFrequency (%)
98 1
 
< 0.1%
93 132
1.3%
92 6
 
0.1%
91 105
1.1%
89 81
0.8%
87 38
 
0.4%
86 94
0.9%
85 42
 
0.4%
84 57
0.6%
83 55
0.5%

부류명
Text

Distinct77
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:41:13.729926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.8093
Min length2

Characters and Unicode

Total characters48093
Distinct characters102
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row숙근류
2nd row숙근류
3rd row활 해면어류
4th row냉동 해면어류
5th row활 해면어류
ValueCountFrequency (%)
해면어류 2487
17.9%
신선 1250
 
9.0%
냉동 1232
 
8.9%
활 1175
 
8.5%
숙근류 946
 
6.8%
난류 863
 
6.2%
과실류 449
 
3.2%
관엽식물류 394
 
2.8%
구근류 375
 
2.7%
화목류 348
 
2.5%
Other values (60) 4358
31.4%
2023-12-13T06:41:14.087128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 9205
19.1%
3877
 
8.1%
면 3620
 
7.5%
해 3267
 
6.8%
어 2787
 
5.8%
근 1359
 
2.8%
선 1332
 
2.8%
동 1270
 
2.6%
신 1250
 
2.6%
냉 1232
 
2.6%
Other values (92) 18894
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43867
91.2%
Space Separator 3877
 
8.1%
Open Punctuation 121
 
0.3%
Close Punctuation 121
 
0.3%
Other Punctuation 104
 
0.2%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 9205
21.0%
면 3620
 
8.3%
해 3267
 
7.4%
어 2787
 
6.4%
근 1359
 
3.1%
선 1332
 
3.0%
동 1270
 
2.9%
신 1250
 
2.8%
냉 1232
 
2.8%
활 1175
 
2.7%
Other values (83) 17370
39.6%
Other Punctuation
ValueCountFrequency (%)
/ 82
78.8%
. 14
 
13.5%
, 8
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
M 1
33.3%
O 1
33.3%
Space Separator
ValueCountFrequency (%)
3877
100.0%
Open Punctuation
ValueCountFrequency (%)
( 121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 121
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43867
91.2%
Common 4223
 
8.8%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 9205
21.0%
면 3620
 
8.3%
해 3267
 
7.4%
어 2787
 
6.4%
근 1359
 
3.1%
선 1332
 
3.0%
동 1270
 
2.9%
신 1250
 
2.8%
냉 1232
 
2.8%
활 1175
 
2.7%
Other values (83) 17370
39.6%
Common
ValueCountFrequency (%)
3877
91.8%
( 121
 
2.9%
) 121
 
2.9%
/ 82
 
1.9%
. 14
 
0.3%
, 8
 
0.2%
Latin
ValueCountFrequency (%)
G 1
33.3%
M 1
33.3%
O 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43867
91.2%
ASCII 4226
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 9205
21.0%
면 3620
 
8.3%
해 3267
 
7.4%
어 2787
 
6.4%
근 1359
 
3.1%
선 1332
 
3.0%
동 1270
 
2.9%
신 1250
 
2.8%
냉 1232
 
2.8%
활 1175
 
2.7%
Other values (83) 17370
39.6%
ASCII
ValueCountFrequency (%)
3877
91.7%
( 121
 
2.9%
) 121
 
2.9%
/ 82
 
1.9%
. 14
 
0.3%
, 8
 
0.2%
G 1
 
< 0.1%
M 1
 
< 0.1%
O 1
 
< 0.1%

품목코드
Text

Distinct181
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:41:14.429663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters20000
Distinct characters27
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

Unique24 ?
Unique (%)0.2%

Sample

1st row02
2nd row13
3rd row03
4th row27
5th rowB3
ValueCountFrequency (%)
03 1197
 
12.0%
02 877
 
8.8%
01 722
 
7.2%
07 435
 
4.3%
27 402
 
4.0%
04 373
 
3.7%
28 329
 
3.3%
26 302
 
3.0%
10 287
 
2.9%
09 261
 
2.6%
Other values (171) 4815
48.1%
2023-12-13T06:41:14.953037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5104
25.5%
2 3017
15.1%
1 2332
11.7%
3 2248
11.2%
7 1375
 
6.9%
4 1356
 
6.8%
6 1106
 
5.5%
5 1051
 
5.3%
8 1048
 
5.2%
9 819
 
4.1%
Other values (17) 544
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19456
97.3%
Uppercase Letter 544
 
2.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 90
16.5%
A 85
15.6%
G 83
15.3%
E 77
14.2%
B 68
12.5%
C 62
11.4%
Z 46
8.5%
W 8
 
1.5%
N 5
 
0.9%
V 5
 
0.9%
Other values (7) 15
 
2.8%
Decimal Number
ValueCountFrequency (%)
0 5104
26.2%
2 3017
15.5%
1 2332
12.0%
3 2248
11.6%
7 1375
 
7.1%
4 1356
 
7.0%
6 1106
 
5.7%
5 1051
 
5.4%
8 1048
 
5.4%
9 819
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Common 19456
97.3%
Latin 544
 
2.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 90
16.5%
A 85
15.6%
G 83
15.3%
E 77
14.2%
B 68
12.5%
C 62
11.4%
Z 46
8.5%
W 8
 
1.5%
N 5
 
0.9%
V 5
 
0.9%
Other values (7) 15
 
2.8%
Common
ValueCountFrequency (%)
0 5104
26.2%
2 3017
15.5%
1 2332
12.0%
3 2248
11.6%
7 1375
 
7.1%
4 1356
 
7.0%
6 1106
 
5.7%
5 1051
 
5.4%
8 1048
 
5.4%
9 819
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5104
25.5%
2 3017
15.1%
1 2332
11.7%
3 2248
11.2%
7 1375
 
6.9%
4 1356
 
6.8%
6 1106
 
5.5%
5 1051
 
5.3%
8 1048
 
5.2%
9 819
 
4.1%
Other values (17) 544
 
2.7%

품목명
Text

Distinct1321
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:41:15.342809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length3.6257
Min length1

Characters and Unicode

Total characters36257
Distinct characters593
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique604 ?
Unique (%)6.0%

Sample

1st row국화(스탠다드)
2nd row스타티스
3rd row가자미
4th row돔
5th row실치
ValueCountFrequency (%)
국화(스프레이 445
 
4.4%
심비디움 271
 
2.7%
돔 252
 
2.5%
장미(스탠다드 238
 
2.4%
덴파레 233
 
2.3%
카네이션(스프레이 184
 
1.8%
동양란 134
 
1.3%
조개 130
 
1.3%
상어 119
 
1.2%
망둑어 103
 
1.0%
Other values (1319) 7929
79.0%
2023-12-13T06:41:15.853143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 1500
 
4.1%
( 1416
 
3.9%
) 1416
 
3.9%
이 1262
 
3.5%
레 1019
 
2.8%
어 942
 
2.6%
리 713
 
2.0%
프 703
 
1.9%
화 700
 
1.9%
미 551
 
1.5%
Other values (583) 26035
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33347
92.0%
Open Punctuation 1416
 
3.9%
Close Punctuation 1416
 
3.9%
Space Separator 38
 
0.1%
Other Punctuation 29
 
0.1%
Uppercase Letter 6
 
< 0.1%
Decimal Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 1500
 
4.5%
이 1262
 
3.8%
레 1019
 
3.1%
어 942
 
2.8%
리 713
 
2.1%
프 703
 
2.1%
화 700
 
2.1%
미 551
 
1.7%
국 550
 
1.6%
아 545
 
1.6%
Other values (575) 24862
74.6%
Decimal Number
ValueCountFrequency (%)
3 2
40.0%
1 2
40.0%
2 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 1416
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1416
100.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33347
92.0%
Common 2904
 
8.0%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 1500
 
4.5%
이 1262
 
3.8%
레 1019
 
3.1%
어 942
 
2.8%
리 713
 
2.1%
프 703
 
2.1%
화 700
 
2.1%
미 551
 
1.7%
국 550
 
1.6%
아 545
 
1.6%
Other values (575) 24862
74.6%
Common
ValueCountFrequency (%)
( 1416
48.8%
) 1416
48.8%
38
 
1.3%
, 29
 
1.0%
3 2
 
0.1%
1 2
 
0.1%
2 1
 
< 0.1%
Latin
ValueCountFrequency (%)
F 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33347
92.0%
ASCII 2910
 
8.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 1500
 
4.5%
이 1262
 
3.8%
레 1019
 
3.1%
어 942
 
2.8%
리 713
 
2.1%
프 703
 
2.1%
화 700
 
2.1%
미 551
 
1.7%
국 550
 
1.6%
아 545
 
1.6%
Other values (575) 24862
74.6%
ASCII
ValueCountFrequency (%)
( 1416
48.7%
) 1416
48.7%
38
 
1.3%
, 29
 
1.0%
F 6
 
0.2%
3 2
 
0.1%
1 2
 
0.1%
2 1
 
< 0.1%

품종코드
Text

Distinct546
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T06:41:16.230463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters20000
Distinct characters37
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique188 ?
Unique (%)1.9%

Sample

1st row50
2nd row21
3rd row10
4th row67
5th row99
ValueCountFrequency (%)
01 1062
 
10.6%
00 791
 
7.9%
99 658
 
6.6%
98 557
 
5.6%
02 501
 
5.0%
03 405
 
4.1%
04 306
 
3.1%
05 266
 
2.7%
06 228
 
2.3%
07 207
 
2.1%
Other values (535) 5018
50.2%
2023-12-13T06:41:16.670151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5432
27.2%
1 2669
13.3%
9 2530
12.7%
2 1635
 
8.2%
3 1340
 
6.7%
8 1257
 
6.3%
4 1073
 
5.4%
5 959
 
4.8%
6 831
 
4.2%
7 778
 
3.9%
Other values (27) 1496
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18504
92.5%
Uppercase Letter 1487
 
7.4%
Space Separator 9
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 147
 
9.9%
B 110
 
7.4%
Z 107
 
7.2%
C 80
 
5.4%
G 75
 
5.0%
D 75
 
5.0%
F 73
 
4.9%
E 72
 
4.8%
H 71
 
4.8%
I 68
 
4.6%
Other values (16) 609
41.0%
Decimal Number
ValueCountFrequency (%)
0 5432
29.4%
1 2669
14.4%
9 2530
13.7%
2 1635
 
8.8%
3 1340
 
7.2%
8 1257
 
6.8%
4 1073
 
5.8%
5 959
 
5.2%
6 831
 
4.5%
7 778
 
4.2%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18513
92.6%
Latin 1487
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 147
 
9.9%
B 110
 
7.4%
Z 107
 
7.2%
C 80
 
5.4%
G 75
 
5.0%
D 75
 
5.0%
F 73
 
4.9%
E 72
 
4.8%
H 71
 
4.8%
I 68
 
4.6%
Other values (16) 609
41.0%
Common
ValueCountFrequency (%)
0 5432
29.3%
1 2669
14.4%
9 2530
13.7%
2 1635
 
8.8%
3 1340
 
7.2%
8 1257
 
6.8%
4 1073
 
5.8%
5 959
 
5.2%
6 831
 
4.5%
7 778
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5432
27.2%
1 2669
13.3%
9 2530
12.7%
2 1635
 
8.2%
3 1340
 
6.7%
8 1257
 
6.3%
4 1073
 
5.4%
5 959
 
4.8%
6 831
 
4.2%
7 778
 
3.9%
Other values (27) 1496
 
7.5%

품종명
Text

Distinct7147
Distinct (%)71.5%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T06:41:16.941049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length4.0763305
Min length1

Characters and Unicode

Total characters40747
Distinct characters952
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5554 ?
Unique (%)55.6%

Sample

1st row천원
2nd row리모늄
3rd row홍가자미
4th row와레후
5th row기타
ValueCountFrequency (%)
기타 553
 
5.5%
화이트 10
 
0.1%
혼합 10
 
0.1%
핑크 10
 
0.1%
알 7
 
0.1%
한우 7
 
0.1%
레드 7
 
0.1%
빙어(수입 6
 
0.1%
난소 6
 
0.1%
갑상선 6
 
0.1%
Other values (7118) 9481
93.8%
2023-12-13T06:41:17.345729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 1160
 
2.8%
( 1160
 
2.8%
기 1137
 
2.8%
리 1004
 
2.5%
타 947
 
2.3%
수 842
 
2.1%
어 798
 
2.0%
777
 
1.9%
이 700
 
1.7%
스 616
 
1.5%
Other values (942) 31606
77.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37132
91.1%
Close Punctuation 1160
 
2.8%
Open Punctuation 1160
 
2.8%
Space Separator 777
 
1.9%
Decimal Number 304
 
0.7%
Uppercase Letter 112
 
0.3%
Lowercase Letter 51
 
0.1%
Other Punctuation 31
 
0.1%
Dash Punctuation 15
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1137
 
3.1%
리 1004
 
2.7%
타 947
 
2.6%
수 842
 
2.3%
어 798
 
2.1%
이 700
 
1.9%
스 616
 
1.7%
입 609
 
1.6%
치 553
 
1.5%
일 500
 
1.3%
Other values (887) 29426
79.2%
Uppercase Letter
ValueCountFrequency (%)
K 18
16.1%
M 13
11.6%
N 8
 
7.1%
R 7
 
6.2%
S 7
 
6.2%
O 7
 
6.2%
B 6
 
5.4%
W 6
 
5.4%
D 6
 
5.4%
L 5
 
4.5%
Other values (12) 29
25.9%
Lowercase Letter
ValueCountFrequency (%)
g 8
15.7%
a 8
15.7%
r 6
11.8%
k 6
11.8%
o 5
9.8%
s 5
9.8%
e 4
7.8%
d 3
 
5.9%
n 3
 
5.9%
c 1
 
2.0%
Other values (2) 2
 
3.9%
Decimal Number
ValueCountFrequency (%)
1 58
19.1%
3 38
12.5%
2 38
12.5%
0 36
11.8%
5 34
11.2%
4 30
9.9%
6 28
9.2%
7 20
 
6.6%
9 12
 
3.9%
8 10
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 13
41.9%
, 9
29.0%
# 4
 
12.9%
/ 3
 
9.7%
% 2
 
6.5%
Math Symbol
ValueCountFrequency (%)
~ 4
80.0%
× 1
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 1160
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1160
100.0%
Space Separator
ValueCountFrequency (%)
777
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37132
91.1%
Common 3452
 
8.5%
Latin 163
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1137
 
3.1%
리 1004
 
2.7%
타 947
 
2.6%
수 842
 
2.3%
어 798
 
2.1%
이 700
 
1.9%
스 616
 
1.7%
입 609
 
1.6%
치 553
 
1.5%
일 500
 
1.3%
Other values (887) 29426
79.2%
Latin
ValueCountFrequency (%)
K 18
 
11.0%
M 13
 
8.0%
N 8
 
4.9%
g 8
 
4.9%
a 8
 
4.9%
R 7
 
4.3%
S 7
 
4.3%
O 7
 
4.3%
B 6
 
3.7%
W 6
 
3.7%
Other values (24) 75
46.0%
Common
ValueCountFrequency (%)
) 1160
33.6%
( 1160
33.6%
777
22.5%
1 58
 
1.7%
3 38
 
1.1%
2 38
 
1.1%
0 36
 
1.0%
5 34
 
1.0%
4 30
 
0.9%
6 28
 
0.8%
Other values (11) 93
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37132
91.1%
ASCII 3614
 
8.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 1160
32.1%
( 1160
32.1%
777
21.5%
1 58
 
1.6%
3 38
 
1.1%
2 38
 
1.1%
0 36
 
1.0%
5 34
 
0.9%
4 30
 
0.8%
6 28
 
0.8%
Other values (44) 255
 
7.1%
Hangul
ValueCountFrequency (%)
기 1137
 
3.1%
리 1004
 
2.7%
타 947
 
2.6%
수 842
 
2.3%
어 798
 
2.1%
이 700
 
1.9%
스 616
 
1.7%
입 609
 
1.6%
치 553
 
1.5%
일 500
 
1.3%
Other values (887) 29426
79.2%
None
ValueCountFrequency (%)
× 1
100.0%

Interactions

2023-12-13T06:41:12.852057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:41:17.446702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부류코드부류명
부류코드1.0001.000
부류명1.0001.000

Missing values

2023-12-13T06:41:13.001959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:41:13.136698image/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

부류코드부류명품목코드품목명품종코드품종명
487524숙근류02국화(스탠다드)50천원
562324숙근류13스타티스21리모늄
850661활 해면어류03가자미10홍가자미
1228581냉동 해면어류27돔67와레후
956261활 해면어류B3실치99기타
199515농산물 종자류22벼종자06수라벼
1237381냉동 해면어류28망둑어37갈문망둑어
1403493수산가공02조미가공03개량조개
1190677신선 내수면어류19잉어03미리갈잉어
986763활 해면갑각류03새우03꽃새우
부류코드부류명품목코드품목명품종코드품종명
408622난류07심비디움40사까다
278220화목류26장미(스탠다드)70아마데우스
195515농산물 종자류04고추종자01고추종자(일반)
1243581냉동 해면어류35민어12등갈민태
583124숙근류28카네이션(스프레이)42웨스트로지
1396591농림가공10기타식품13복숭아식초
1263081냉동 해면어류48상어33고래상어
934961활 해면어류67청어03정어리
1024771신선 해면어류03가자미29검정가자미
1069371신선 해면어류40뱅어02벚꽃뱅어