Overview

Dataset statistics

Number of variables4
Number of observations308
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.4 KiB
Average record size in memory34.4 B

Variable types

Categorical1
Numeric1
Text2

Dataset

Description국내외 가격차에 상당한 율로 양허한 농림축산물의 수입물량이 급증하거나 수입가격이 하락하는 경우에 특별긴급관세(SSG)를 부과할 수 있는 품목 현황 데이터
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220217000000002058

Reproduction

Analysis started2023-12-11 03:21:17.533732
Analysis finished2023-12-11 03:21:18.938569
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

YEAR
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2015
162 
2014
146 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2014
2nd row2014
3rd row2014
4th row2014
5th row2014

Common Values

ValueCountFrequency (%)
2015 162
52.6%
2014 146
47.4%

Length

2023-12-11T12:21:19.014922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:21:19.175655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015 162
52.6%
2014 146
47.4%

ORDR
Real number (ℝ)

Distinct162
Distinct (%)52.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.707792
Minimum1
Maximum162
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-11T12:21:19.312747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.35
Q139
median77.5
Q3116
95-th percentile146.65
Maximum162
Range161
Interquartile range (IQR)77

Descriptive statistics

Standard deviation44.885947
Coefficient of variation (CV)0.57762478
Kurtosis-1.1623354
Mean77.707792
Median Absolute Deviation (MAD)38.5
Skewness0.02736554
Sum23934
Variance2014.7482
MonotonicityNot monotonic
2023-12-11T12:21:19.502710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2
 
0.6%
111 2
 
0.6%
95 2
 
0.6%
96 2
 
0.6%
97 2
 
0.6%
98 2
 
0.6%
99 2
 
0.6%
100 2
 
0.6%
101 2
 
0.6%
102 2
 
0.6%
Other values (152) 288
93.5%
ValueCountFrequency (%)
1 2
0.6%
2 2
0.6%
3 2
0.6%
4 2
0.6%
5 2
0.6%
6 2
0.6%
7 2
0.6%
8 2
0.6%
9 2
0.6%
10 2
0.6%
ValueCountFrequency (%)
162 1
0.3%
161 1
0.3%
160 1
0.3%
159 1
0.3%
158 1
0.3%
157 1
0.3%
156 1
0.3%
155 1
0.3%
154 1
0.3%
153 1
0.3%

HSK
Text

Distinct162
Distinct (%)52.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-11T12:21:19.796770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters3696
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)5.2%

Sample

1st row0102.21.1000
2nd row0102.21.2000
3rd row0102.21.9000
4th row0102.31.0000
5th row0102.90.1000
ValueCountFrequency (%)
0102.21.1000 2
 
0.6%
1108.14.9000 2
 
0.6%
1209.91.2000 2
 
0.6%
1202.30.1000 2
 
0.6%
1202.30.2000 2
 
0.6%
1202.41.0000 2
 
0.6%
1202.42.0000 2
 
0.6%
1209.91.1010 2
 
0.6%
1209.91.1090 2
 
0.6%
1209.91.9000 2
 
0.6%
Other values (152) 288
93.5%
2023-12-11T12:21:20.237455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1388
37.6%
1 679
18.4%
. 616
16.7%
2 327
 
8.8%
9 289
 
7.8%
3 149
 
4.0%
5 78
 
2.1%
4 66
 
1.8%
7 40
 
1.1%
8 34
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3080
83.3%
Other Punctuation 616
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1388
45.1%
1 679
22.0%
2 327
 
10.6%
9 289
 
9.4%
3 149
 
4.8%
5 78
 
2.5%
4 66
 
2.1%
7 40
 
1.3%
8 34
 
1.1%
6 30
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 616
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3696
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1388
37.6%
1 679
18.4%
. 616
16.7%
2 327
 
8.8%
9 289
 
7.8%
3 149
 
4.0%
5 78
 
2.1%
4 66
 
1.8%
7 40
 
1.1%
8 34
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3696
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1388
37.6%
1 679
18.4%
. 616
16.7%
2 327
 
8.8%
9 289
 
7.8%
3 149
 
4.0%
5 78
 
2.1%
4 66
 
1.8%
7 40
 
1.1%
8 34
 
0.9%

KOREAN_PRDNM
Text

Distinct157
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-11T12:21:20.423693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length20
Mean length10.873377
Min length1

Characters and Unicode

Total characters3349
Distinct characters215
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

Unique8 ?
Unique (%)2.6%

Sample

1st row축우(번식용의 것/젖소)
2nd row축우(번식용의 것/육우)
3rd row축우(번식용의 것/기타)
4th row버팔로(번식용의 것)
5th row기타(번식용의 것)
ValueCountFrequency (%)
것 61
 
10.0%
기타 12
 
2.0%
분쇄물 10
 
1.6%
및 10
 
1.6%
종자 10
 
1.6%
또는 10
 
1.6%
변형되는 6
 
1.0%
포함되지 6
 
1.0%
인삼류(기타 6
 
1.0%
것/기타 6
 
1.0%
Other values (197) 472
77.5%
2023-12-11T12:21:20.798750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
304
 
9.1%
) 247
 
7.4%
( 247
 
7.4%
기 124
 
3.7%
타 124
 
3.7%
삼 98
 
2.9%
의 80
 
2.4%
것 79
 
2.4%
분 78
 
2.3%
/ 72
 
2.1%
Other values (205) 1896
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2437
72.8%
Space Separator 304
 
9.1%
Close Punctuation 247
 
7.4%
Open Punctuation 247
 
7.4%
Other Punctuation 96
 
2.9%
Lowercase Letter 12
 
0.4%
Decimal Number 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 124
 
5.1%
타 124
 
5.1%
삼 98
 
4.0%
의 80
 
3.3%
것 79
 
3.2%
분 78
 
3.2%
용 62
 
2.5%
자 58
 
2.4%
종 52
 
2.1%
수 48
 
2.0%
Other values (187) 1634
67.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
16.7%
r 2
16.7%
g 2
16.7%
o 1
8.3%
i 1
8.3%
n 1
8.3%
k 1
8.3%
b 1
8.3%
c 1
8.3%
Other Punctuation
ValueCountFrequency (%)
/ 72
75.0%
, 18
 
18.8%
. 6
 
6.2%
Decimal Number
ValueCountFrequency (%)
5 2
33.3%
8 2
33.3%
1 2
33.3%
Space Separator
ValueCountFrequency (%)
304
100.0%
Close Punctuation
ValueCountFrequency (%)
) 247
100.0%
Open Punctuation
ValueCountFrequency (%)
( 247
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2437
72.8%
Common 900
 
26.9%
Latin 12
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 124
 
5.1%
타 124
 
5.1%
삼 98
 
4.0%
의 80
 
3.3%
것 79
 
3.2%
분 78
 
3.2%
용 62
 
2.5%
자 58
 
2.4%
종 52
 
2.1%
수 48
 
2.0%
Other values (187) 1634
67.0%
Common
ValueCountFrequency (%)
304
33.8%
) 247
27.4%
( 247
27.4%
/ 72
 
8.0%
, 18
 
2.0%
. 6
 
0.7%
5 2
 
0.2%
8 2
 
0.2%
1 2
 
0.2%
Latin
ValueCountFrequency (%)
e 2
16.7%
r 2
16.7%
g 2
16.7%
o 1
8.3%
i 1
8.3%
n 1
8.3%
k 1
8.3%
b 1
8.3%
c 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2437
72.8%
ASCII 912
 
27.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
304
33.3%
) 247
27.1%
( 247
27.1%
/ 72
 
7.9%
, 18
 
2.0%
. 6
 
0.7%
e 2
 
0.2%
r 2
 
0.2%
g 2
 
0.2%
5 2
 
0.2%
Other values (8) 10
 
1.1%
Hangul
ValueCountFrequency (%)
기 124
 
5.1%
타 124
 
5.1%
삼 98
 
4.0%
의 80
 
3.3%
것 79
 
3.2%
분 78
 
3.2%
용 62
 
2.5%
자 58
 
2.4%
종 52
 
2.1%
수 48
 
2.0%
Other values (187) 1634
67.0%

Interactions

2023-12-11T12:21:18.559051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:21:20.906664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
YEARORDR
YEAR1.0000.159
ORDR0.1591.000
2023-12-11T12:21:20.989665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ORDRYEAR
ORDR1.0000.120
YEAR0.1201.000

Missing values

2023-12-11T12:21:18.798900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:21:18.896721image/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

YEARORDRHSKKOREAN_PRDNM
0201410102.21.1000축우(번식용의 것/젖소)
1201420102.21.2000축우(번식용의 것/육우)
2201430102.21.9000축우(번식용의 것/기타)
3201440102.31.0000버팔로(번식용의 것)
4201450102.90.1000기타(번식용의 것)
5201460103.10.0000돼지(번식용의 것)
6201470105.11.1000닭(185g 이하/번식용의 것)
7201480105.94.1000닭(번식용의 것)
8201490407.11.0000조란(부화용 수정란/닭의 것)
92014100407.19.0000조란(부화용 수정란/기타)
YEARORDRHSKKOREAN_PRDNM
29820151533505.10.3000배소전분
29920151543505.10.4010프리젤라티나이지드 또는 스웰링전분(식품용)
30020151553505.10.4090프리젤라티나이지드 또는 스웰링전분(기타)
30120151563505.10.5010에테르화 또는 에스테르화전분(식품용)
30220151573505.10.5090에테르화 또는 에스테르화전분(기타)
30320151583505.10.9010기타 변성전분(식품용)
30420151593505.10.9090기타 변성전분(기타)
30520151603505.20.1000전분 글루
30620151613505.20.2000덱스트린 글루
30720151623505.20.9000기타 글루