Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory115.0 B

Variable types

Numeric2
Text10
Categorical1

Dataset

Description2015년 제·개정된 농축수산물 표준코드의 품목코드(부류, 품목, 품종)와 동일한 의미를 가지는 2013년 농축수산물 표준코드의 품목코드(부류, 품목, 품종)를 나타낸 정보
Author농림수산식품교육문화정보원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220210000000001770

Alerts

UPDT_DE has constant value ""Constant
CATGORY_NEW_CODE is highly overall correlated with CATGORY_CODEHigh correlation
CATGORY_CODE is highly overall correlated with CATGORY_NEW_CODEHigh correlation
STD_SPCIES_CODE has unique valuesUnique

Reproduction

Analysis started2023-12-11 03:18:08.926599
Analysis finished2023-12-11 03:18:11.628715
Duration2.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

CATGORY_NEW_CODE
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.2435
Minimum1
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:11.725701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q122
median26
Q361
95-th percentile72
Maximum93
Range92
Interquartile range (IQR)39

Descriptive statistics

Standard deviation23.511288
Coefficient of variation (CV)0.59911294
Kurtosis-1.0987883
Mean39.2435
Median Absolute Deviation (MAD)17
Skewness0.33550923
Sum392435
Variance552.78069
MonotonicityNot monotonic
2023-12-11T12:18:11.872344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
61 2514
25.1%
24 1043
 
10.4%
22 1016
 
10.2%
6 544
 
5.4%
25 438
 
4.4%
43 381
 
3.8%
62 364
 
3.6%
20 353
 
3.5%
26 317
 
3.2%
71 235
 
2.4%
Other values (42) 2795
28.0%
ValueCountFrequency (%)
1 26
 
0.3%
2 16
 
0.2%
3 54
 
0.5%
4 34
 
0.3%
5 33
 
0.3%
6 544
5.4%
9 128
 
1.3%
10 142
 
1.4%
11 45
 
0.4%
12 86
 
0.9%
ValueCountFrequency (%)
93 148
1.5%
92 7
 
0.1%
91 201
2.0%
83 5
 
0.1%
81 52
 
0.5%
79 14
 
0.1%
73 21
 
0.2%
72 55
 
0.5%
71 235
2.4%
69 78
 
0.8%

CATGORY_NEW_NM
Text

Distinct53
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:12.091623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length3.5483
Min length2

Characters and Unicode

Total characters35483
Distinct characters79
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

Unique3 ?
Unique (%)< 0.1%

Sample

1st row관엽식물류
2nd row해면어류
3rd row난류
4th row해면어류
5th row농림가공
ValueCountFrequency (%)
해면어류 2514
25.1%
숙근류 1043
 
10.4%
난류 1016
 
10.2%
과실류 544
 
5.4%
구근류 438
 
4.4%
육류 381
 
3.8%
해면패류 364
 
3.6%
화목류 353
 
3.5%
관엽식물류 317
 
3.2%
내수면어류 235
 
2.4%
Other values (43) 2795
28.0%
2023-12-11T12:18:12.551653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 9394
26.5%
면 3645
 
10.3%
해 3367
 
9.5%
어 2749
 
7.7%
근 1526
 
4.3%
숙 1043
 
2.9%
난 1016
 
2.9%
물 805
 
2.3%
과 672
 
1.9%
산 597
 
1.7%
Other values (69) 10669
30.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35454
99.9%
Other Punctuation 27
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 9394
26.5%
면 3645
 
10.3%
해 3367
 
9.5%
어 2749
 
7.8%
근 1526
 
4.3%
숙 1043
 
2.9%
난 1016
 
2.9%
물 805
 
2.3%
과 672
 
1.9%
산 597
 
1.7%
Other values (65) 10640
30.0%
Other Punctuation
ValueCountFrequency (%)
/ 23
85.2%
. 4
 
14.8%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35454
99.9%
Common 29
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 9394
26.5%
면 3645
 
10.3%
해 3367
 
9.5%
어 2749
 
7.8%
근 1526
 
4.3%
숙 1043
 
2.9%
난 1016
 
2.9%
물 805
 
2.3%
과 672
 
1.9%
산 597
 
1.7%
Other values (65) 10640
30.0%
Common
ValueCountFrequency (%)
/ 23
79.3%
. 4
 
13.8%
( 1
 
3.4%
) 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35454
99.9%
ASCII 29
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 9394
26.5%
면 3645
 
10.3%
해 3367
 
9.5%
어 2749
 
7.8%
근 1526
 
4.3%
숙 1043
 
2.9%
난 1016
 
2.9%
물 805
 
2.3%
과 672
 
1.9%
산 597
 
1.7%
Other values (65) 10640
30.0%
ASCII
ValueCountFrequency (%)
/ 23
79.3%
. 4
 
13.8%
( 1
 
3.4%
) 1
 
3.4%

CATGORY_CODE
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.6583
Minimum1
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:12.690130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q122
median26
Q371
95-th percentile86
Maximum93
Range92
Interquartile range (IQR)49

Descriptive statistics

Standard deviation27.485743
Coefficient of variation (CV)0.64432346
Kurtosis-1.4346272
Mean42.6583
Median Absolute Deviation (MAD)17
Skewness0.33118373
Sum426583
Variance755.46609
MonotonicityNot monotonic
2023-12-11T12:18:13.007803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 1043
 
10.4%
22 1016
 
10.2%
61 834
 
8.3%
81 827
 
8.3%
71 827
 
8.3%
6 487
 
4.9%
25 438
 
4.4%
20 353
 
3.5%
43 283
 
2.8%
26 239
 
2.4%
Other values (58) 3653
36.5%
ValueCountFrequency (%)
1 26
 
0.3%
2 16
 
0.2%
3 54
 
0.5%
4 34
 
0.3%
5 33
 
0.3%
6 487
4.9%
7 66
 
0.7%
8 87
 
0.9%
9 41
 
0.4%
10 142
 
1.4%
ValueCountFrequency (%)
93 105
1.1%
92 7
 
0.1%
91 192
1.9%
89 91
0.9%
87 35
 
0.4%
86 75
 
0.8%
85 34
 
0.3%
84 48
 
0.5%
83 60
 
0.6%
82 119
1.2%

CATGORY_NM
Text

Distinct68
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:13.205717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.6755
Min length2

Characters and Unicode

Total characters46755
Distinct characters87
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st row관엽식물류
2nd row냉동 해면어류
3rd row난류
4th row활 해면어류
5th row농림가공
ValueCountFrequency (%)
해면어류 2488
18.2%
신선 1237
 
9.1%
활 1214
 
8.9%
냉동 1198
 
8.8%
숙근류 1043
 
7.6%
난류 1016
 
7.4%
과실류 487
 
3.6%
구근류 438
 
3.2%
해면패류 354
 
2.6%
화목류 353
 
2.6%
Other values (47) 3821
28.0%
2023-12-11T12:18:13.549112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 9172
19.6%
3649
 
7.8%
면 3604
 
7.7%
해 3307
 
7.1%
어 2730
 
5.8%
근 1526
 
3.3%
선 1260
 
2.7%
신 1237
 
2.6%
동 1234
 
2.6%
활 1214
 
2.6%
Other values (77) 17822
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42845
91.6%
Space Separator 3649
 
7.8%
Open Punctuation 117
 
0.3%
Close Punctuation 117
 
0.3%
Other Punctuation 27
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 9172
21.4%
면 3604
 
8.4%
해 3307
 
7.7%
어 2730
 
6.4%
근 1526
 
3.6%
선 1260
 
2.9%
신 1237
 
2.9%
동 1234
 
2.9%
활 1214
 
2.8%
냉 1198
 
2.8%
Other values (72) 16363
38.2%
Other Punctuation
ValueCountFrequency (%)
/ 23
85.2%
. 4
 
14.8%
Space Separator
ValueCountFrequency (%)
3649
100.0%
Open Punctuation
ValueCountFrequency (%)
( 117
100.0%
Close Punctuation
ValueCountFrequency (%)
) 117
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42845
91.6%
Common 3910
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 9172
21.4%
면 3604
 
8.4%
해 3307
 
7.7%
어 2730
 
6.4%
근 1526
 
3.6%
선 1260
 
2.9%
신 1237
 
2.9%
동 1234
 
2.9%
활 1214
 
2.8%
냉 1198
 
2.8%
Other values (72) 16363
38.2%
Common
ValueCountFrequency (%)
3649
93.3%
( 117
 
3.0%
) 117
 
3.0%
/ 23
 
0.6%
. 4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42845
91.6%
ASCII 3910
 
8.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 9172
21.4%
면 3604
 
8.4%
해 3307
 
7.7%
어 2730
 
6.4%
근 1526
 
3.6%
선 1260
 
2.9%
신 1237
 
2.9%
동 1234
 
2.9%
활 1214
 
2.8%
냉 1198
 
2.8%
Other values (72) 16363
38.2%
ASCII
ValueCountFrequency (%)
3649
93.3%
( 117
 
3.0%
) 117
 
3.0%
/ 23
 
0.6%
. 4
 
0.1%

STD_PRDLST_NEW_CODE
Text

Distinct883
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:13.917088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters40000
Distinct characters23
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

Unique323 ?
Unique (%)3.2%

Sample

1st row2633
2nd row6126
3rd row2207
4th row6157
5th row9107
ValueCountFrequency (%)
2403 501
 
5.0%
2207 333
 
3.3%
2026 283
 
2.8%
2202 276
 
2.8%
6137 262
 
2.6%
2428 210
 
2.1%
2203 167
 
1.7%
6142 137
 
1.4%
6169 130
 
1.3%
0604 129
 
1.3%
Other values (873) 7572
75.7%
2023-12-11T12:18:14.387919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 7791
19.5%
0 6751
16.9%
1 6613
16.5%
6 5506
13.8%
3 3467
8.7%
4 3086
 
7.7%
7 2009
 
5.0%
9 1797
 
4.5%
5 1752
 
4.4%
8 909
 
2.3%
Other values (13) 319
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39681
99.2%
Uppercase Letter 319
 
0.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 148
46.4%
G 84
26.3%
B 56
 
17.6%
V 6
 
1.9%
T 4
 
1.3%
H 4
 
1.3%
O 4
 
1.3%
N 4
 
1.3%
I 3
 
0.9%
U 2
 
0.6%
Other values (3) 4
 
1.3%
Decimal Number
ValueCountFrequency (%)
2 7791
19.6%
0 6751
17.0%
1 6613
16.7%
6 5506
13.9%
3 3467
8.7%
4 3086
 
7.8%
7 2009
 
5.1%
9 1797
 
4.5%
5 1752
 
4.4%
8 909
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 39681
99.2%
Latin 319
 
0.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 148
46.4%
G 84
26.3%
B 56
 
17.6%
V 6
 
1.9%
T 4
 
1.3%
H 4
 
1.3%
O 4
 
1.3%
N 4
 
1.3%
I 3
 
0.9%
U 2
 
0.6%
Other values (3) 4
 
1.3%
Common
ValueCountFrequency (%)
2 7791
19.6%
0 6751
17.0%
1 6613
16.7%
6 5506
13.9%
3 3467
8.7%
4 3086
 
7.8%
7 2009
 
5.1%
9 1797
 
4.5%
5 1752
 
4.4%
8 909
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 7791
19.5%
0 6751
16.9%
1 6613
16.5%
6 5506
13.8%
3 3467
8.7%
4 3086
 
7.7%
7 2009
 
5.0%
9 1797
 
4.5%
5 1752
 
4.4%
8 909
 
2.3%
Other values (13) 319
 
0.8%

PRDLST_NEW_NM
Text

Distinct859
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:14.727321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length4.0661
Min length1

Characters and Unicode

Total characters40661
Distinct characters481
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique302 ?
Unique (%)3.0%

Sample

1st row안스리움
2nd row농어류
3rd row심비디움
4th row배불뚝류
5th row곡물제조
ValueCountFrequency (%)
국화(스프레이 501
 
5.0%
심비디움 333
 
3.3%
장미(스탠다드 283
 
2.8%
덴파레 276
 
2.7%
돔류 262
 
2.6%
카네이션(스프레이 210
 
2.1%
동양란 167
 
1.7%
망둑어류 137
 
1.4%
상어류 130
 
1.3%
복숭아 129
 
1.3%
Other values (851) 7632
75.9%
2023-12-11T12:18:15.240195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
류 4016
 
9.9%
스 1637
 
4.0%
( 1593
 
3.9%
) 1593
 
3.9%
이 1335
 
3.3%
레 1123
 
2.8%
어 853
 
2.1%
프 783
 
1.9%
화 704
 
1.7%
리 693
 
1.7%
Other values (471) 26331
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37410
92.0%
Open Punctuation 1593
 
3.9%
Close Punctuation 1593
 
3.9%
Space Separator 60
 
0.1%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
류 4016
 
10.7%
스 1637
 
4.4%
이 1335
 
3.6%
레 1123
 
3.0%
어 853
 
2.3%
프 783
 
2.1%
화 704
 
1.9%
리 693
 
1.9%
다 648
 
1.7%
국 620
 
1.7%
Other values (467) 24998
66.8%
Open Punctuation
ValueCountFrequency (%)
( 1593
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1593
100.0%
Space Separator
ValueCountFrequency (%)
60
100.0%
Other Punctuation
ValueCountFrequency (%)
？ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37410
92.0%
Common 3251
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
류 4016
 
10.7%
스 1637
 
4.4%
이 1335
 
3.6%
레 1123
 
3.0%
어 853
 
2.3%
프 783
 
2.1%
화 704
 
1.9%
리 693
 
1.9%
다 648
 
1.7%
국 620
 
1.7%
Other values (467) 24998
66.8%
Common
ValueCountFrequency (%)
( 1593
49.0%
) 1593
49.0%
60
 
1.8%
？ 5
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37410
92.0%
ASCII 3246
 
8.0%
None 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
류 4016
 
10.7%
스 1637
 
4.4%
이 1335
 
3.6%
레 1123
 
3.0%
어 853
 
2.3%
프 783
 
2.1%
화 704
 
1.9%
리 693
 
1.9%
다 648
 
1.7%
국 620
 
1.7%
Other values (467) 24998
66.8%
ASCII
ValueCountFrequency (%)
( 1593
49.1%
) 1593
49.1%
60
 
1.8%
None
ValueCountFrequency (%)
？ 5
100.0%

STD_PRDLST_CODE
Text

Distinct1294
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:15.640921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters40000
Distinct characters25
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

Unique401 ?
Unique (%)4.0%

Sample

1st row2633
2nd row8119
3rd row2207
4th row6181
5th row9107
ValueCountFrequency (%)
2403 501
 
5.0%
2207 333
 
3.3%
2026 283
 
2.8%
2202 276
 
2.8%
2428 210
 
2.1%
2203 167
 
1.7%
0604 129
 
1.3%
2402 119
 
1.2%
2427 95
 
0.9%
2509 91
 
0.9%
Other values (1284) 7796
78.0%
2023-12-11T12:18:16.151188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 8120
20.3%
0 6994
17.5%
1 6270
15.7%
4 3365
8.4%
6 3239
 
8.1%
3 3191
 
8.0%
7 2965
 
7.4%
8 2520
 
6.3%
5 1749
 
4.4%
9 1339
 
3.3%
Other values (15) 248
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39752
99.4%
Uppercase Letter 248
 
0.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 71
28.6%
A 67
27.0%
D 46
18.5%
B 23
 
9.3%
Z 8
 
3.2%
G 6
 
2.4%
T 4
 
1.6%
H 4
 
1.6%
O 4
 
1.6%
N 4
 
1.6%
Other values (5) 11
 
4.4%
Decimal Number
ValueCountFrequency (%)
2 8120
20.4%
0 6994
17.6%
1 6270
15.8%
4 3365
8.5%
6 3239
 
8.1%
3 3191
 
8.0%
7 2965
 
7.5%
8 2520
 
6.3%
5 1749
 
4.4%
9 1339
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common 39752
99.4%
Latin 248
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 71
28.6%
A 67
27.0%
D 46
18.5%
B 23
 
9.3%
Z 8
 
3.2%
G 6
 
2.4%
T 4
 
1.6%
H 4
 
1.6%
O 4
 
1.6%
N 4
 
1.6%
Other values (5) 11
 
4.4%
Common
ValueCountFrequency (%)
2 8120
20.4%
0 6994
17.6%
1 6270
15.8%
4 3365
8.5%
6 3239
 
8.1%
3 3191
 
8.0%
7 2965
 
7.5%
8 2520
 
6.3%
5 1749
 
4.4%
9 1339
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 8120
20.3%
0 6994
17.5%
1 6270
15.7%
4 3365
8.4%
6 3239
 
8.1%
3 3191
 
8.0%
7 2965
 
7.4%
8 2520
 
6.3%
5 1749
 
4.4%
9 1339
 
3.3%
Other values (15) 248
 
0.6%

PRDLST_NM
Text

Distinct850
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:16.536203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length3.6654
Min length1

Characters and Unicode

Total characters36654
Distinct characters482
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

Unique288 ?
Unique (%)2.9%

Sample

1st row안스리움
2nd row농어
3rd row심비디움
4th row배불뚝치
5th row곡물제조
ValueCountFrequency (%)
국화(스프레이 501
 
5.0%
심비디움 333
 
3.3%
장미(스탠다드 283
 
2.8%
덴파레 276
 
2.7%
돔 270
 
2.7%
카네이션(스프레이 210
 
2.1%
동양란 167
 
1.7%
조개 159
 
1.6%
망둑어 132
 
1.3%
상어 130
 
1.3%
Other values (841) 7599
75.5%
2023-12-11T12:18:17.149564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 1640
 
4.5%
( 1571
 
4.3%
) 1571
 
4.3%
이 1348
 
3.7%
레 1123
 
3.1%
어 973
 
2.7%
프 783
 
2.1%
화 709
 
1.9%
리 682
 
1.9%
다 633
 
1.7%
Other values (472) 25621
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33422
91.2%
Open Punctuation 1571
 
4.3%
Close Punctuation 1571
 
4.3%
Space Separator 64
 
0.2%
Other Punctuation 26
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 1640
 
4.9%
이 1348
 
4.0%
레 1123
 
3.4%
어 973
 
2.9%
프 783
 
2.3%
화 709
 
2.1%
리 682
 
2.0%
다 633
 
1.9%
국 620
 
1.9%
미 610
 
1.8%
Other values (468) 24301
72.7%
Open Punctuation
ValueCountFrequency (%)
( 1571
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1571
100.0%
Space Separator
ValueCountFrequency (%)
64
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33422
91.2%
Common 3232
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 1640
 
4.9%
이 1348
 
4.0%
레 1123
 
3.4%
어 973
 
2.9%
프 783
 
2.3%
화 709
 
2.1%
리 682
 
2.0%
다 633
 
1.9%
국 620
 
1.9%
미 610
 
1.8%
Other values (468) 24301
72.7%
Common
ValueCountFrequency (%)
( 1571
48.6%
) 1571
48.6%
64
 
2.0%
, 26
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33422
91.2%
ASCII 3232
 
8.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 1640
 
4.9%
이 1348
 
4.0%
레 1123
 
3.4%
어 973
 
2.9%
프 783
 
2.3%
화 709
 
2.1%
리 682
 
2.0%
다 633
 
1.9%
국 620
 
1.9%
미 610
 
1.8%
Other values (468) 24301
72.7%
ASCII
ValueCountFrequency (%)
( 1571
48.6%
) 1571
48.6%
64
 
2.0%
, 26
 
0.8%

STD_SPCIES_NEW_CODE
Text

Distinct7639
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:17.541728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters60000
Distinct characters36
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

Unique6338 ?
Unique (%)63.4%

Sample

1st row263314
2nd row612601
3rd row2207S3
4th row615701
5th row910715
ValueCountFrequency (%)
614501 12
 
0.1%
610501 12
 
0.1%
621901 11
 
0.1%
620201 10
 
0.1%
610702 9
 
0.1%
620901 8
 
0.1%
621101 8
 
0.1%
613117 8
 
0.1%
621001 8
 
0.1%
640201 8
 
0.1%
Other values (7629) 9906
99.1%
2023-12-11T12:18:18.086426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11270
18.8%
2 9684
16.1%
1 9613
16.0%
6 6440
10.7%
3 4950
8.2%
4 4336
 
7.2%
9 4062
 
6.8%
7 2914
 
4.9%
5 2838
 
4.7%
8 1815
 
3.0%
Other values (26) 2078
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57922
96.5%
Uppercase Letter 2078
 
3.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 310
14.9%
G 167
 
8.0%
B 167
 
8.0%
Z 152
 
7.3%
C 102
 
4.9%
D 98
 
4.7%
E 93
 
4.5%
H 91
 
4.4%
F 83
 
4.0%
I 83
 
4.0%
Other values (16) 732
35.2%
Decimal Number
ValueCountFrequency (%)
0 11270
19.5%
2 9684
16.7%
1 9613
16.6%
6 6440
11.1%
3 4950
8.5%
4 4336
 
7.5%
9 4062
 
7.0%
7 2914
 
5.0%
5 2838
 
4.9%
8 1815
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common 57922
96.5%
Latin 2078
 
3.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 310
14.9%
G 167
 
8.0%
B 167
 
8.0%
Z 152
 
7.3%
C 102
 
4.9%
D 98
 
4.7%
E 93
 
4.5%
H 91
 
4.4%
F 83
 
4.0%
I 83
 
4.0%
Other values (16) 732
35.2%
Common
ValueCountFrequency (%)
0 11270
19.5%
2 9684
16.7%
1 9613
16.6%
6 6440
11.1%
3 4950
8.5%
4 4336
 
7.5%
9 4062
 
7.0%
7 2914
 
5.0%
5 2838
 
4.9%
8 1815
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11270
18.8%
2 9684
16.1%
1 9613
16.0%
6 6440
10.7%
3 4950
8.2%
4 4336
 
7.2%
9 4062
 
6.8%
7 2914
 
4.9%
5 2838
 
4.7%
8 1815
 
3.0%
Other values (26) 2078
 
3.5%

STD_SPCIES_NEW_NM
Text

Distinct6808
Distinct (%)68.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:18.503260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length4.0166
Min length1

Characters and Unicode

Total characters40166
Distinct characters955
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5195 ?
Unique (%)51.9%

Sample

1st row마꼬야
2nd row농어
3rd row이나사
4th row배불뚝치
5th row떡복이떡
ValueCountFrequency (%)
기타 321
 
3.2%
화이트 14
 
0.1%
명태 13
 
0.1%
황강달이 12
 
0.1%
키조개 11
 
0.1%
혼합 11
 
0.1%
동죽(동조개 10
 
0.1%
바지락 10
 
0.1%
눈볼대 9
 
0.1%
가리맛조개(맛 8
 
0.1%
Other values (6801) 9673
95.8%
2023-12-11T12:18:19.049204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1196
 
3.0%
리 974
 
2.4%
타 946
 
2.4%
) 857
 
2.1%
( 857
 
2.1%
어 771
 
1.9%
이 747
 
1.9%
치 646
 
1.6%
스 564
 
1.4%
라 515
 
1.3%
Other values (945) 32093
79.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37805
94.1%
Close Punctuation 857
 
2.1%
Open Punctuation 857
 
2.1%
Decimal Number 352
 
0.9%
Uppercase Letter 137
 
0.3%
Space Separator 98
 
0.2%
Lowercase Letter 21
 
0.1%
Other Punctuation 20
 
< 0.1%
Dash Punctuation 15
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1196
 
3.2%
리 974
 
2.6%
타 946
 
2.5%
어 771
 
2.0%
이 747
 
2.0%
치 646
 
1.7%
스 564
 
1.5%
라 515
 
1.4%
수 500
 
1.3%
일 497
 
1.3%
Other values (896) 30449
80.5%
Uppercase Letter
ValueCountFrequency (%)
K 22
16.1%
N 12
 
8.8%
M 11
 
8.0%
S 11
 
8.0%
O 10
 
7.3%
A 10
 
7.3%
R 9
 
6.6%
W 9
 
6.6%
B 7
 
5.1%
P 6
 
4.4%
Other values (10) 30
21.9%
Decimal Number
ValueCountFrequency (%)
1 74
21.0%
5 47
13.4%
3 42
11.9%
0 41
11.6%
2 41
11.6%
4 28
 
8.0%
7 25
 
7.1%
6 25
 
7.1%
9 15
 
4.3%
8 14
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
k 5
23.8%
g 4
19.0%
o 3
14.3%
s 2
 
9.5%
r 2
 
9.5%
p 1
 
4.8%
u 1
 
4.8%
c 1
 
4.8%
e 1
 
4.8%
t 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 14
70.0%
# 4
 
20.0%
/ 1
 
5.0%
, 1
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 857
100.0%
Open Punctuation
ValueCountFrequency (%)
( 857
100.0%
Space Separator
ValueCountFrequency (%)
98
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37805
94.1%
Common 2203
 
5.5%
Latin 158
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1196
 
3.2%
리 974
 
2.6%
타 946
 
2.5%
어 771
 
2.0%
이 747
 
2.0%
치 646
 
1.7%
스 564
 
1.5%
라 515
 
1.4%
수 500
 
1.3%
일 497
 
1.3%
Other values (896) 30449
80.5%
Latin
ValueCountFrequency (%)
K 22
13.9%
N 12
 
7.6%
M 11
 
7.0%
S 11
 
7.0%
O 10
 
6.3%
A 10
 
6.3%
R 9
 
5.7%
W 9
 
5.7%
B 7
 
4.4%
P 6
 
3.8%
Other values (20) 51
32.3%
Common
ValueCountFrequency (%)
) 857
38.9%
( 857
38.9%
98
 
4.4%
1 74
 
3.4%
5 47
 
2.1%
3 42
 
1.9%
0 41
 
1.9%
2 41
 
1.9%
4 28
 
1.3%
7 25
 
1.1%
Other values (9) 93
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37805
94.1%
ASCII 2361
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1196
 
3.2%
리 974
 
2.6%
타 946
 
2.5%
어 771
 
2.0%
이 747
 
2.0%
치 646
 
1.7%
스 564
 
1.5%
라 515
 
1.4%
수 500
 
1.3%
일 497
 
1.3%
Other values (896) 30449
80.5%
ASCII
ValueCountFrequency (%)
) 857
36.3%
( 857
36.3%
98
 
4.2%
1 74
 
3.1%
5 47
 
2.0%
3 42
 
1.8%
0 41
 
1.7%
2 41
 
1.7%
4 28
 
1.2%
7 25
 
1.1%
Other values (39) 251
 
10.6%

STD_SPCIES_CODE
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:19.487001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters60000
Distinct characters36
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row263314
2nd row811901
3rd row2207S3
4th row618101
5th row910715
ValueCountFrequency (%)
263314 1
 
< 0.1%
862601 1
 
< 0.1%
893601 1
 
< 0.1%
710326 1
 
< 0.1%
2403p3 1
 
< 0.1%
110107 1
 
< 0.1%
818799 1
 
< 0.1%
061103 1
 
< 0.1%
615805 1
 
< 0.1%
2402b4 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-11T12:18:20.025658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11341
18.9%
2 9996
16.7%
1 9254
15.4%
3 4744
7.9%
4 4600
7.7%
6 4180
 
7.0%
7 3877
 
6.5%
9 3721
 
6.2%
8 3443
 
5.7%
5 2857
 
4.8%
Other values (26) 1987
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58013
96.7%
Uppercase Letter 1987
 
3.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 250
 
12.6%
E 155
 
7.8%
B 146
 
7.3%
D 135
 
6.8%
Z 131
 
6.6%
C 98
 
4.9%
H 91
 
4.6%
G 89
 
4.5%
I 83
 
4.2%
F 79
 
4.0%
Other values (16) 730
36.7%
Decimal Number
ValueCountFrequency (%)
0 11341
19.5%
2 9996
17.2%
1 9254
16.0%
3 4744
8.2%
4 4600
7.9%
6 4180
 
7.2%
7 3877
 
6.7%
9 3721
 
6.4%
8 3443
 
5.9%
5 2857
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Common 58013
96.7%
Latin 1987
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 250
 
12.6%
E 155
 
7.8%
B 146
 
7.3%
D 135
 
6.8%
Z 131
 
6.6%
C 98
 
4.9%
H 91
 
4.6%
G 89
 
4.5%
I 83
 
4.2%
F 79
 
4.0%
Other values (16) 730
36.7%
Common
ValueCountFrequency (%)
0 11341
19.5%
2 9996
17.2%
1 9254
16.0%
3 4744
8.2%
4 4600
7.9%
6 4180
 
7.2%
7 3877
 
6.7%
9 3721
 
6.4%
8 3443
 
5.9%
5 2857
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11341
18.9%
2 9996
16.7%
1 9254
15.4%
3 4744
7.9%
4 4600
7.7%
6 4180
 
7.0%
7 3877
 
6.5%
9 3721
 
6.2%
8 3443
 
5.7%
5 2857
 
4.8%
Other values (26) 1987
 
3.3%

STD_SPCIES_CODE_NM
Text

Distinct6711
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:20.340362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length3.7967
Min length1

Characters and Unicode

Total characters37967
Distinct characters956
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5225 ?
Unique (%)52.2%

Sample

1st row마꼬야
2nd row농어
3rd row이나사
4th row배불뚝치
5th row떡복이떡
ValueCountFrequency (%)
기타 775
 
7.7%
화이트 14
 
0.1%
혼합 11
 
0.1%
핑크 8
 
0.1%
레드 7
 
0.1%
한우 7
 
0.1%
줄비늘치 6
 
0.1%
창마이 6
 
0.1%
골드 6
 
0.1%
알 6
 
0.1%
Other values (6711) 9257
91.6%
2023-12-11T12:18:20.788552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1180
 
3.1%
타 980
 
2.6%
리 925
 
2.4%
어 789
 
2.1%
이 704
 
1.9%
( 697
 
1.8%
) 697
 
1.8%
스 565
 
1.5%
일 514
 
1.4%
치 514
 
1.4%
Other values (946) 30402
80.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35901
94.6%
Open Punctuation 697
 
1.8%
Close Punctuation 697
 
1.8%
Decimal Number 352
 
0.9%
Uppercase Letter 122
 
0.3%
Space Separator 104
 
0.3%
Lowercase Letter 54
 
0.1%
Other Punctuation 21
 
0.1%
Dash Punctuation 15
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1180
 
3.3%
타 980
 
2.7%
리 925
 
2.6%
어 789
 
2.2%
이 704
 
2.0%
스 565
 
1.6%
일 514
 
1.4%
치 514
 
1.4%
라 502
 
1.4%
반 499
 
1.4%
Other values (894) 28729
80.0%
Uppercase Letter
ValueCountFrequency (%)
K 22
18.0%
N 12
9.8%
M 11
9.0%
S 11
9.0%
O 10
8.2%
W 9
 
7.4%
B 7
 
5.7%
L 6
 
4.9%
P 6
 
4.9%
H 5
 
4.1%
Other values (10) 23
18.9%
Lowercase Letter
ValueCountFrequency (%)
r 10
18.5%
a 10
18.5%
g 9
16.7%
o 5
9.3%
k 5
9.3%
s 4
 
7.4%
e 3
 
5.6%
d 2
 
3.7%
n 2
 
3.7%
c 1
 
1.9%
Other values (3) 3
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 74
21.0%
5 47
13.4%
3 42
11.9%
2 41
11.6%
0 41
11.6%
4 28
 
8.0%
6 25
 
7.1%
7 25
 
7.1%
9 15
 
4.3%
8 14
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 14
66.7%
# 4
 
19.0%
, 2
 
9.5%
/ 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 697
100.0%
Close Punctuation
ValueCountFrequency (%)
) 697
100.0%
Space Separator
ValueCountFrequency (%)
104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35901
94.6%
Common 1890
 
5.0%
Latin 176
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1180
 
3.3%
타 980
 
2.7%
리 925
 
2.6%
어 789
 
2.2%
이 704
 
2.0%
스 565
 
1.6%
일 514
 
1.4%
치 514
 
1.4%
라 502
 
1.4%
반 499
 
1.4%
Other values (894) 28729
80.0%
Latin
ValueCountFrequency (%)
K 22
 
12.5%
N 12
 
6.8%
M 11
 
6.2%
S 11
 
6.2%
O 10
 
5.7%
r 10
 
5.7%
a 10
 
5.7%
W 9
 
5.1%
g 9
 
5.1%
B 7
 
4.0%
Other values (23) 65
36.9%
Common
ValueCountFrequency (%)
( 697
36.9%
) 697
36.9%
104
 
5.5%
1 74
 
3.9%
5 47
 
2.5%
3 42
 
2.2%
2 41
 
2.2%
0 41
 
2.2%
4 28
 
1.5%
6 25
 
1.3%
Other values (9) 94
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35901
94.6%
ASCII 2066
 
5.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1180
 
3.3%
타 980
 
2.7%
리 925
 
2.6%
어 789
 
2.2%
이 704
 
2.0%
스 565
 
1.6%
일 514
 
1.4%
치 514
 
1.4%
라 502
 
1.4%
반 499
 
1.4%
Other values (894) 28729
80.0%
ASCII
ValueCountFrequency (%)
( 697
33.7%
) 697
33.7%
104
 
5.0%
1 74
 
3.6%
5 47
 
2.3%
3 42
 
2.0%
2 41
 
2.0%
0 41
 
2.0%
4 28
 
1.4%
6 25
 
1.2%
Other values (42) 270
 
13.1%

UPDT_DE
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20160128
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20160128
2nd row20160128
3rd row20160128
4th row20160128
5th row20160128

Common Values

ValueCountFrequency (%)
20160128 10000
100.0%

Length

2023-12-11T12:18:20.924471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:18:21.031175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20160128 10000
100.0%

Interactions

2023-12-11T12:18:11.115632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:18:10.893080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:18:11.220849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:18:11.000017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:18:21.103182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
CATGORY_NEW_CODECATGORY_NEW_NMCATGORY_CODECATGORY_NM
CATGORY_NEW_CODE1.0001.0000.9940.998
CATGORY_NEW_NM1.0001.0000.9830.999
CATGORY_CODE0.9940.9831.0001.000
CATGORY_NM0.9980.9991.0001.000
2023-12-11T12:18:21.206172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
CATGORY_NEW_CODECATGORY_CODE
CATGORY_NEW_CODE1.0000.964
CATGORY_CODE0.9641.000

Missing values

2023-12-11T12:18:11.355178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:18:11.535106image/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

CATGORY_NEW_CODECATGORY_NEW_NMCATGORY_CODECATGORY_NMSTD_PRDLST_NEW_CODEPRDLST_NEW_NMSTD_PRDLST_CODEPRDLST_NMSTD_SPCIES_NEW_CODESTD_SPCIES_NEW_NMSTD_SPCIES_CODESTD_SPCIES_CODE_NMUPDT_DE
576726관엽식물류26관엽식물류2633안스리움2633안스리움263314마꼬야263314마꼬야20160128
998961해면어류81냉동 해면어류6126농어류8119농어612601농어811901농어20160128
357322난류22난류2207심비디움2207심비디움2207S3이나사2207S3이나사20160128
782661해면어류61활 해면어류6157배불뚝류6181배불뚝치615701배불뚝치618101배불뚝치20160128
1153391농림가공91농림가공9107곡물제조9107곡물제조910715떡복이떡910715떡복이떡20160128
748061해면어류61활 해면어류6159베도라치류6145베도라치615907비늘베도라치614503비늘베도라치20160128
111210엽경채류10엽경채류1043무청1043무청104397건무청(수입)104397건무청(수입)20160128
506124숙근류24숙근류2428카네이션(스프레이)2428카네이션(스프레이)2428K2캐사2428K2캐사20160128
129713양채류13양채류1301양상추1301양상추130199기타130199기타20160128
729161해면어류61활 해면어류6142망둑어류6128망둑어614209꼬마망둑612828꼬마망둑어20160128
CATGORY_NEW_CODECATGORY_NEW_NMCATGORY_CODECATGORY_NMSTD_PRDLST_NEW_CODEPRDLST_NEW_NMSTD_PRDLST_CODEPRDLST_NMSTD_SPCIES_NEW_CODESTD_SPCIES_NEW_NMSTD_SPCIES_CODESTD_SPCIES_CODE_NMUPDT_DE
127812조미채소류12조미채소류1213방아1213방아121301방아(일반)121301방아(일반)20160128
1129072내수면패류87냉동 내수면기타7204재첩류8710재첩720403일본재첩871002일본재첩20160128
1127679내수면기타87냉동 내수면기타7903자라류8707자라790399기타자라류870799기타20160128
753161해면어류61활 해면어류6169상어류6148상어616949흑기흉상어614829흑기흉상어20160128
1164393수산가공93수산가공9311통조림류9301통조림931102게살930102게살20160128
798962해면패류62활 해면패류6204굴류6206굴620401굴(참굴)620601참굴20160128
326222난류22난류2206반다2206반다220618반다블루220618반다블루20160128
597226관엽식물류28기타화훼26G7야생화2803야생화26G731무지개비름꽃280332무지개비름꽃20160128
381722난류22난류2212팔레높시스2212팔레높시스221227리틀슈221227리틀슈20160128
397424숙근류24숙근류2402국화(스탠다드)2402국화(스탠다드)240239양국240239양국20160128