Overview

Dataset statistics

Number of variables8
Number of observations81
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory69.6 B

Variable types

Categorical4
Text1
Numeric3

Dataset

DescriptionTRQ 운영 현황(물량계획, 수입관리 방식)입니다. * 농산물 시장접근물량의 정의(TRQ : Tariff Rate Quotas): UR 농산물협상의 예외 없는 관세 원칙에 따라 관세상당치(TE)를 적용하여 관세를 부과할 경우 수출국의 시장접근이 어렵게 되어 협정국들 간에는 일정물량에 대해서 수입이 보장될 수 있도록 저율관세(양허관세)를 적용한 농산물
URLhttps://www.data.go.kr/data/15072356/fileData.do

Alerts

도입물량 is highly overall correlated with 낙찰물량 and 2 other fieldsHigh correlation
낙찰물량 is highly overall correlated with 도입물량 and 1 other fieldsHigh correlation
잔량 is highly overall correlated with 도입물량High correlation
품목군명 is highly overall correlated with 도입물량 and 3 other fieldsHigh correlation
산지명 is highly overall correlated with 품목군명 and 1 other fieldsHigh correlation
방식 is highly overall correlated with 품목군명 and 1 other fieldsHigh correlation
계획명 has unique valuesUnique
낙찰물량 has 16 (19.8%) zerosZeros
잔량 has 27 (33.3%) zerosZeros

Reproduction

Analysis started2023-12-12 00:52:32.780310
Analysis finished2023-12-12 00:52:34.450214
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

계획년도
Categorical

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size780.0 B
2022
42 
2023
39 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 42
51.9%
2023 39
48.1%

Length

2023-12-12T09:52:34.525849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:52:34.643849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 42
51.9%
2023 39
48.1%

계획명
Text

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-12T09:52:34.880239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length31
Mean length29.395062
Min length17

Characters and Unicode

Total characters2381
Distinct characters101
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)100.0%

Sample

1st row2022년 WTO TRQ [녹차] 수입권배분
2nd row2022년 WTO TRQ [기타가공곡물] 수입권배분
3rd row2022년 WTO TRQ [옥수수] 수입권배분
4th row2022년 WTO TRQ [감귤류] 수입권배분
5th row2022년 WTO TRQ [오렌지] 수입권배분
ValueCountFrequency (%)
trq 79
17.1%
fta 63
13.6%
수입권배분 47
 
10.2%
2022년 42
 
9.1%
2023년 39
 
8.4%
수입권공매 31
 
6.7%
wto 16
 
3.5%
한-칠레 10
 
2.2%
한-eu 9
 
1.9%
오렌지 8
 
1.7%
Other values (40) 119
25.7%
2023-12-12T09:52:35.328297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
385
 
16.2%
2 204
 
8.6%
T 160
 
6.7%
수 87
 
3.7%
년 81
 
3.4%
0 81
 
3.4%
R 79
 
3.3%
Q 79
 
3.3%
[ 78
 
3.3%
] 78
 
3.3%
Other values (91) 1069
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 952
40.0%
Uppercase Letter 500
21.0%
Space Separator 385
16.2%
Decimal Number 324
 
13.6%
Open Punctuation 78
 
3.3%
Close Punctuation 78
 
3.3%
Dash Punctuation 63
 
2.6%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 87
 
9.1%
년 81
 
8.5%
입 78
 
8.2%
권 78
 
8.2%
분 68
 
7.1%
한 63
 
6.6%
배 50
 
5.3%
공 33
 
3.5%
매 33
 
3.5%
맥 28
 
2.9%
Other values (74) 353
37.1%
Uppercase Letter
ValueCountFrequency (%)
T 160
32.0%
R 79
15.8%
Q 79
15.8%
F 65
13.0%
A 65
13.0%
W 16
 
3.2%
O 16
 
3.2%
E 11
 
2.2%
U 9
 
1.8%
Decimal Number
ValueCountFrequency (%)
2 204
63.0%
0 81
 
25.0%
3 39
 
12.0%
Space Separator
ValueCountFrequency (%)
385
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 78
100.0%
Close Punctuation
ValueCountFrequency (%)
] 78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 952
40.0%
Common 929
39.0%
Latin 500
21.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 87
 
9.1%
년 81
 
8.5%
입 78
 
8.2%
권 78
 
8.2%
분 68
 
7.1%
한 63
 
6.6%
배 50
 
5.3%
공 33
 
3.5%
매 33
 
3.5%
맥 28
 
2.9%
Other values (74) 353
37.1%
Latin
ValueCountFrequency (%)
T 160
32.0%
R 79
15.8%
Q 79
15.8%
F 65
13.0%
A 65
13.0%
W 16
 
3.2%
O 16
 
3.2%
E 11
 
2.2%
U 9
 
1.8%
Common
ValueCountFrequency (%)
385
41.4%
2 204
22.0%
0 81
 
8.7%
[ 78
 
8.4%
] 78
 
8.4%
- 63
 
6.8%
3 39
 
4.2%
, 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1429
60.0%
Hangul 952
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
385
26.9%
2 204
14.3%
T 160
11.2%
0 81
 
5.7%
R 79
 
5.5%
Q 79
 
5.5%
[ 78
 
5.5%
] 78
 
5.5%
F 65
 
4.5%
A 65
 
4.5%
Other values (7) 155
10.8%
Hangul
ValueCountFrequency (%)
수 87
 
9.1%
년 81
 
8.5%
입 78
 
8.2%
권 78
 
8.2%
분 68
 
7.1%
한 63
 
6.6%
배 50
 
5.3%
공 33
 
3.5%
매 33
 
3.5%
맥 28
 
2.9%
Other values (74) 353
37.1%

품목군명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Memory size780.0 B
맥아맥주맥
12 
오렌지
8 
분유.연유
6 
천연꿀
5 
버터
 
4
Other values (20)
46 

Length

Max length10
Median length6
Mean length3.8148148
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row녹차
2nd row기타가공곡물
3rd row옥수수
4th row감귤류
5th row오렌지

Common Values

ValueCountFrequency (%)
맥아맥주맥 12
 
14.8%
오렌지 8
 
9.9%
분유.연유 6
 
7.4%
천연꿀 5
 
6.2%
버터 4
 
4.9%
고구마전분 4
 
4.9%
감자분 4
 
4.9%
보리 4
 
4.9%
옥수수전분 2
 
2.5%
옥수수 2
 
2.5%
Other values (15) 30
37.0%

Length

2023-12-12T09:52:35.519473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
맥아맥주맥 12
 
14.8%
오렌지 8
 
9.9%
분유.연유 6
 
7.4%
천연꿀 5
 
6.2%
버터 4
 
4.9%
고구마전분 4
 
4.9%
감자분 4
 
4.9%
보리 4
 
4.9%
기타채소 2
 
2.5%
분유 2
 
2.5%
Other values (15) 30
37.0%

산지명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size780.0 B
제한없음
18 
미국
13 
칠레
10 
EU
9 
캐나다
7 
Other values (7)
24 

Length

Max length5
Median length2
Mean length2.8765432
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제한없음 18
22.2%
미국 13
16.0%
칠레 10
12.3%
EU 9
11.1%
캐나다 7
 
8.6%
호주 6
 
7.4%
ASEAN 4
 
4.9%
중국 4
 
4.9%
뉴질랜드 4
 
4.9%
EFTA 2
 
2.5%
Other values (2) 4
 
4.9%

Length

2023-12-12T09:52:35.671184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제한없음 18
22.2%
미국 13
16.0%
칠레 10
12.3%
eu 9
11.1%
캐나다 7
 
8.6%
호주 6
 
7.4%
asean 4
 
4.9%
중국 4
 
4.9%
뉴질랜드 4
 
4.9%
efta 2
 
2.5%
Other values (2) 4
 
4.9%

방식
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size780.0 B
배분
50 
공매
30 
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0246914
Min length2

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
배분 50
61.7%
공매 30
37.0%
<NA> 1
 
1.2%

Length

2023-12-12T09:52:35.811717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:52:35.964432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
배분 50
61.7%
공매 30
37.0%
na 1
 
1.2%

도입물량
Real number (ℝ)

HIGH CORRELATION 

Distinct54
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9802345.7
Minimum7800
Maximum1.05 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T09:52:36.155646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7800
5-th percentile30000
Q1200000
median1995000
Q311190000
95-th percentile43045000
Maximum1.05 × 108
Range1.049922 × 108
Interquartile range (IQR)10990000

Descriptive statistics

Standard deviation19589378
Coefficient of variation (CV)1.9984378
Kurtosis13.130562
Mean9802345.7
Median Absolute Deviation (MAD)1928000
Skewness3.4144117
Sum7.9399 × 108
Variance3.8374374 × 1014
MonotonicityNot monotonic
2023-12-12T09:52:36.333876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 4
 
4.9%
200000 4
 
4.9%
60000 4
 
4.9%
5000000 4
 
4.9%
7800 2
 
2.5%
500000 2
 
2.5%
105000000 2
 
2.5%
1000000 2
 
2.5%
2000000 2
 
2.5%
14700 2
 
2.5%
Other values (44) 53
65.4%
ValueCountFrequency (%)
7800 2
2.5%
14700 2
2.5%
30000 2
2.5%
60000 4
4.9%
67000 1
 
1.2%
69000 1
 
1.2%
100000 4
4.9%
132000 1
 
1.2%
135000 2
2.5%
200000 4
4.9%
ValueCountFrequency (%)
105000000 2
2.5%
57017000 2
2.5%
43045000 1
1.2%
40000000 2
2.5%
25000000 1
1.2%
22600000 1
1.2%
22500000 1
1.2%
21400000 1
1.2%
18815000 1
1.2%
18535000 2
2.5%

낙찰물량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct60
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5896859
Minimum0
Maximum1.05 × 108
Zeros16
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T09:52:36.528446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114700
median643960.4
Q33360000
95-th percentile21400000
Maximum1.05 × 108
Range1.05 × 108
Interquartile range (IQR)3345300

Descriptive statistics

Standard deviation17223016
Coefficient of variation (CV)2.9207101
Kurtosis26.624766
Mean5896859
Median Absolute Deviation (MAD)643960.4
Skewness4.980658
Sum4.7764558 × 108
Variance2.9663227 × 1014
MonotonicityNot monotonic
2023-12-12T09:52:36.726449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 16
 
19.8%
7800.0 2
 
2.5%
5500000.0 2
 
2.5%
14700.0 2
 
2.5%
105000000.0 2
 
2.5%
60000.0 2
 
2.5%
5000000.0 2
 
2.5%
115350.0 1
 
1.2%
11951000.0 1
 
1.2%
3360000.0 1
 
1.2%
Other values (50) 50
61.7%
ValueCountFrequency (%)
0.0 16
19.8%
7000.0 1
 
1.2%
7800.0 2
 
2.5%
14700.0 2
 
2.5%
17000.0 1
 
1.2%
27006.0 1
 
1.2%
30000.0 1
 
1.2%
54000.0 1
 
1.2%
60000.0 2
 
2.5%
67000.0 1
 
1.2%
ValueCountFrequency (%)
105000000.0 2
2.5%
37578443.0 1
1.2%
22251565.0 1
1.2%
21400000.0 1
1.2%
20400000.0 1
1.2%
19610000.0 1
1.2%
15730000.0 1
1.2%
15707000.0 1
1.2%
15249999.0 1
1.2%
11951000.0 1
1.2%

잔량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3905486.7
Minimum-140000
Maximum57017000
Zeros27
Zeros (%)33.3%
Negative1
Negative (%)1.2%
Memory size861.0 B
2023-12-12T09:52:36.886789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-140000
5-th percentile0
Q10
median149000
Q32197000
95-th percentile18535000
Maximum57017000
Range57157000
Interquartile range (IQR)2197000

Descriptive statistics

Standard deviation10010350
Coefficient of variation (CV)2.5631505
Kurtosis18.76472
Mean3905486.7
Median Absolute Deviation (MAD)149000
Skewness4.0906279
Sum3.1634442 × 108
Variance1.0020711 × 1014
MonotonicityNot monotonic
2023-12-12T09:52:37.045318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0.0 27
33.3%
100000.0 4
 
4.9%
500000.0 2
 
2.5%
2000000.0 2
 
2.5%
200000.0 2
 
2.5%
57017000.0 2
 
2.5%
248435.0 1
 
1.2%
24270000.0 1
 
1.2%
297415.0 1
 
1.2%
14873250.0 1
 
1.2%
Other values (38) 38
46.9%
ValueCountFrequency (%)
-140000.0 1
 
1.2%
0.0 27
33.3%
1.0 1
 
1.2%
6000.0 1
 
1.2%
30000.0 1
 
1.2%
40000.0 1
 
1.2%
50000.0 1
 
1.2%
60000.0 1
 
1.2%
100000.0 4
 
4.9%
115000.0 1
 
1.2%
ValueCountFrequency (%)
57017000.0 2
2.5%
24270000.0 1
1.2%
20390000.0 1
1.2%
18535000.0 1
1.2%
18507994.0 1
1.2%
14873250.0 1
1.2%
14509010.28 1
1.2%
13672870.0 1
1.2%
13181470.0 1
1.2%
8532500.0 1
1.2%

Interactions

2023-12-12T09:52:33.917152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:52:33.293097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:52:33.618865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:52:34.015979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:52:33.388799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:52:33.709253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:52:34.120133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:52:33.520180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:52:33.816914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:52:37.156508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계획년도계획명품목군명산지명방식도입물량낙찰물량잔량
계획년도1.0001.0000.0000.0000.0000.0000.0000.000
계획명1.0001.0001.0001.0001.0001.0001.0001.000
품목군명0.0001.0001.0000.9140.9790.9010.8810.787
산지명0.0001.0000.9141.0000.8660.0000.0000.000
방식0.0001.0000.9790.8661.0000.3990.1980.289
도입물량0.0001.0000.9010.0000.3991.0000.9030.793
낙찰물량0.0001.0000.8810.0000.1980.9031.0000.000
잔량0.0001.0000.7870.0000.2890.7930.0001.000
2023-12-12T09:52:37.297386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
방식품목군명산지명계획년도
방식1.0000.8120.6610.000
품목군명0.8121.0000.5480.000
산지명0.6610.5481.0000.000
계획년도0.0000.0000.0001.000
2023-12-12T09:52:37.442050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도입물량낙찰물량잔량계획년도품목군명산지명방식
도입물량1.0000.6350.5090.0000.5820.0000.392
낙찰물량0.6351.000-0.0700.0000.5100.0000.237
잔량0.509-0.0701.0000.0000.4320.0000.208
계획년도0.0000.0000.0001.0000.0000.0000.000
품목군명0.5820.5100.4320.0001.0000.5480.812
산지명0.0000.0000.0000.0000.5481.0000.661
방식0.3920.2370.2080.0000.8120.6611.000

Missing values

2023-12-12T09:52:34.235823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:52:34.386653image/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

계획년도계획명품목군명산지명방식도입물량낙찰물량잔량
020222022년 WTO TRQ [녹차] 수입권배분녹차제한없음배분78007800.00.0
120222022년 WTO TRQ [기타가공곡물] 수입권배분기타가공곡물제한없음배분1470014700.00.0
220222022년 WTO TRQ [옥수수] 수입권배분옥수수제한없음배분4000000019610000.020390000.0
320222022년 WTO TRQ [감귤류] 수입권배분감귤류제한없음배분20970001824080.0272920.0
420222022년 WTO TRQ [오렌지] 수입권배분오렌지제한없음배분570170000.057017000.0
520222022년 WTO TRQ [고구마] 수입권배분고구마제한없음배분1853500027006.018507994.0
620222022년 WTO TRQ [고구마전분] 수입권배분고구마전분제한없음배분2250000022251565.0248435.0
720222022년 WTO TRQ [감자분] 수입권배분감자분제한없음배분16750001109183.521565816.479
820222022년 한-아세안 FTA TRQ [강낭콩] 수입권공매강낭콩ASEAN공매1995000672000.01323000.0
920222022년 한-아세안 FTA TRQ [매니옥전분] 수입권배분매니옥(카사바)전분ASEAN배분55000005500000.00.0
계획년도계획명품목군명산지명방식도입물량낙찰물량잔량
7120232023년 한-EU FTA TRQ [오렌지] 수입권배분오렌지EU배분600000.060000.0
7220232023년 한-호주 FTA TRQ [맥아맥주맥] 수입권배분맥아맥주맥호주배분1195100011951000.00.0
7320232023년 한-캐나다 FTA TRQ [보리] 수입권배분보리캐나다배분2500000115350.02384650.0
7420232023년 한-캐나다 FTA TRQ [맥아] 수입권배분맥아맥주맥캐나다배분2260000020400000.02200000.0
7520232023년 한-캐나다 FTA TRQ [감자분] 수입권배분감자분캐나다배분5000000.0500000.0
7620232023년 한-중국 FTA TRQ [맥아] 수입권배분맥아맥주맥중국배분5000000100000.04900000.0
7720232023년 한-중국 FTA TRQ [고구마전분] 수입권배분고구마전분중국배분50000005000000.00.0
7820232023년 한-영국 FTA TRQ [맥아맥주맥] 수입권배분맥아맥주맥영국배분17120001712000.00.0
7920232023년 한-아세안 FTA TRQ [강낭콩] 수입권공매강낭콩ASEAN공매1995000826000.01169000.0
8020232023년 설탕할당관세물량 배정설탕제한없음배분105000000105000000.00.0