Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells19979
Missing cells (%)22.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory830.1 KiB
Average record size in memory85.0 B

Variable types

Numeric3
Categorical5
Unsupported1

Dataset

Description품목번호별로 관세율을 표시한 데이터로 품목번호, 관세율 구분, 단위당세액, 기준가격, 적용국가구분, 용도세율구분, 적용개시일, 적용만료일 등의 항목을 제공합니다.- 단위당세액, 기준가격, 용도세율구분 항목은 값이 없거나 기준에 해당하지 않는 품목번호에 대해서는 해당값을 공란처리하였습니다.- 관세율구분과 용도세율구분 항목은 A(기본세율), C(WTO 협정에 의한 양허관세) 등 관세율을 구분해 놓은 부호로 세부적이 내용은 아래 링크를 참조하시면 됩니다.https://unipass.customs.go.kr/csp/index.do?tgMenuId=MYC_MNU_00000337(UNIPASS > 정보조회 > 신고지원정보 > 관세율(협정, 탄력))
Author관세청
URLhttps://www.data.go.kr/data/15051179/fileData.do

Alerts

적용개시일 has constant value ""Constant
적용만료일 has constant value ""Constant
관세율구분 is highly overall correlated with 적용국가구분High correlation
적용국가구분 is highly overall correlated with 관세율구분High correlation
관세율 is highly overall correlated with 용도세율구분High correlation
용도세율구분 is highly overall correlated with 관세율High correlation
용도세율구분 is highly imbalanced (98.4%)Imbalance
단위당세액 has 9979 (99.8%) missing valuesMissing
기준가격 has 10000 (100.0%) missing valuesMissing
관세율 is highly skewed (γ1 = 21.2591257)Skewed
기준가격 is an unsupported type, check if it needs cleaning or further analysisUnsupported
관세율 has 7057 (70.6%) zerosZeros

Reproduction

Analysis started2024-04-06 08:24:43.577648
Analysis finished2024-04-06 08:24:48.884766
Duration5.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목번호
Real number (ℝ)

Distinct6788
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.209946 × 109
Minimum1.01211 × 108
Maximum9.706903 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T17:24:49.030182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.01211 × 108
5-th percentile3.0791196 × 108
Q12.9081975 × 109
median5.201001 × 109
Q38.4147252 × 109
95-th percentile9.0222111 × 109
Maximum9.706903 × 109
Range9.605692 × 109
Interquartile range (IQR)5.5065278 × 109

Descriptive statistics

Standard deviation2.8421849 × 109
Coefficient of variation (CV)0.54553058
Kurtosis-1.2904737
Mean5.209946 × 109
Median Absolute Deviation (MAD)2.395846 × 109
Skewness-0.11302499
Sum5.209946 × 1013
Variance8.0780151 × 1018
MonotonicityNot monotonic
2024-04-06T17:24:49.624457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
303990000 6
 
0.1%
4414900000 5
 
0.1%
307219000 5
 
0.1%
2508501000 5
 
0.1%
7227909020 5
 
0.1%
2920230000 5
 
0.1%
6104320000 5
 
0.1%
4802549090 5
 
0.1%
2831102000 5
 
0.1%
3102101000 5
 
0.1%
Other values (6778) 9949
99.5%
ValueCountFrequency (%)
101211000 1
< 0.1%
101219000 1
< 0.1%
101291000 1
< 0.1%
101299000 2
< 0.1%
101300000 2
< 0.1%
101900000 1
< 0.1%
102211000 2
< 0.1%
102219000 2
< 0.1%
102292000 1
< 0.1%
102299000 2
< 0.1%
ValueCountFrequency (%)
9706903000 2
< 0.1%
9706902000 1
 
< 0.1%
9706901000 3
< 0.1%
9706103000 2
< 0.1%
9706102000 1
 
< 0.1%
9705390000 2
< 0.1%
9705100000 1
 
< 0.1%
9704000000 2
< 0.1%
9703102000 1
 
< 0.1%
9702902000 1
 
< 0.1%

관세율구분
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
FAU1
1145 
FCA1
1141 
FAS1
1129 
A
1127 
FCECR1
1104 
Other values (41)
4354 

Length

Max length6
Median length5
Mean length4.0533
Min length1

Unique

Unique18 ?
Unique (%)0.2%

Sample

1st rowFCENI1
2nd rowFCA1
3rd rowFAS1
4th rowC
5th rowFAS1

Common Values

ValueCountFrequency (%)
FAU1 1145
11.5%
FCA1 1141
11.4%
FAS1 1129
11.3%
A 1127
11.3%
FCECR1 1104
11.0%
FCENI1 1072
10.7%
FCEHN1 1041
10.4%
C 969
9.7%
FCEPA1 682
6.8%
E1 290
 
2.9%
Other values (36) 300
 
3.0%

Length

2024-04-06T17:24:49.944132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
fau1 1145
11.5%
fca1 1141
11.4%
fas1 1129
11.3%
a 1127
11.3%
fcecr1 1104
11.0%
fceni1 1072
10.7%
fcehn1 1041
10.4%
c 969
9.7%
fcepa1 682
6.8%
e1 290
 
2.9%
Other values (36) 300
 
3.0%

관세율
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct151
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1449
Minimum0
Maximum800.3
Zeros7057
Zeros (%)70.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T17:24:50.192351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile13
Maximum800.3
Range800.3
Interquartile range (IQR)4

Descriptive statistics

Standard deviation23.554669
Coefficient of variation (CV)5.6828075
Kurtosis568.47743
Mean4.1449
Median Absolute Deviation (MAD)0
Skewness21.259126
Sum41449
Variance554.82243
MonotonicityNot monotonic
2024-04-06T17:24:50.523779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 7057
70.6%
8.0 722
 
7.2%
13.0 316
 
3.2%
5.0 220
 
2.2%
10.0 155
 
1.6%
6.5 141
 
1.4%
4.0 104
 
1.0%
20.0 77
 
0.8%
30.0 65
 
0.7%
3.2 58
 
0.6%
Other values (141) 1085
 
10.8%
ValueCountFrequency (%)
0.0 7057
70.6%
0.1 1
 
< 0.1%
0.4 1
 
< 0.1%
0.5 2
 
< 0.1%
0.6 5
 
0.1%
0.7 1
 
< 0.1%
0.8 4
 
< 0.1%
1.0 19
 
0.2%
1.1 2
 
< 0.1%
1.2 1
 
< 0.1%
ValueCountFrequency (%)
800.3 1
 
< 0.1%
754.3 3
< 0.1%
603.4 1
 
< 0.1%
489.2 2
< 0.1%
377.3 3
< 0.1%
360.0 1
 
< 0.1%
308.5 3
< 0.1%
308.0 1
 
< 0.1%
299.7 1
 
< 0.1%
277.4 2
< 0.1%

단위당세액
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)81.0%
Missing9979
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean1813.2857
Minimum140
Maximum6210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T17:24:50.775833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum140
5-th percentile180
Q1454
median931
Q31864
95-th percentile6210
Maximum6210
Range6070
Interquartile range (IQR)1410

Descriptive statistics

Standard deviation1938.2048
Coefficient of variation (CV)1.068891
Kurtosis0.88111161
Mean1813.2857
Median Absolute Deviation (MAD)736
Skewness1.4194019
Sum38079
Variance3756637.8
MonotonicityNot monotonic
2024-04-06T17:24:51.024920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
931 3
 
< 0.1%
6210 2
 
< 0.1%
4640 2
 
< 0.1%
1586 1
 
< 0.1%
180 1
 
< 0.1%
574 1
 
< 0.1%
730 1
 
< 0.1%
195 1
 
< 0.1%
1800 1
 
< 0.1%
454 1
 
< 0.1%
Other values (7) 7
 
0.1%
(Missing) 9979
99.8%
ValueCountFrequency (%)
140 1
 
< 0.1%
180 1
 
< 0.1%
195 1
 
< 0.1%
211 1
 
< 0.1%
361 1
 
< 0.1%
454 1
 
< 0.1%
574 1
 
< 0.1%
730 1
 
< 0.1%
931 3
< 0.1%
1218 1
 
< 0.1%
ValueCountFrequency (%)
6210 2
< 0.1%
4640 2
< 0.1%
2466 1
 
< 0.1%
1864 1
 
< 0.1%
1807 1
 
< 0.1%
1800 1
 
< 0.1%
1586 1
 
< 0.1%
1218 1
 
< 0.1%
931 3
< 0.1%
730 1
 
< 0.1%

기준가격
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

적용국가구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7872 
1
2128 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7872
78.7%
1 2128
 
21.3%

Length

2024-04-06T17:24:51.332510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:24:51.525471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7872
78.7%
1 2128
 
21.3%

용도세율구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9976 
A
 
22
C
 
2

Length

Max length4
Median length4
Mean length3.9928
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9976
99.8%
A 22
 
0.2%
C 2
 
< 0.1%

Length

2024-04-06T17:24:51.832698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:24:52.067732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9976
99.8%
a 22
 
0.2%
c 2
 
< 0.1%

적용개시일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-01
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-01
2nd row2024-01-01
3rd row2024-01-01
4th row2024-01-01
5th row2024-01-01

Common Values

ValueCountFrequency (%)
2024-01-01 10000
100.0%

Length

2024-04-06T17:24:52.280506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:24:52.486803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-01 10000
100.0%

적용만료일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-12-31
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-12-31
2nd row2024-12-31
3rd row2024-12-31
4th row2024-12-31
5th row2024-12-31

Common Values

ValueCountFrequency (%)
2024-12-31 10000
100.0%

Length

2024-04-06T17:24:52.820502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:24:53.004606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-12-31 10000
100.0%

Interactions

2024-04-06T17:24:47.410872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:46.181443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:46.773707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:47.690420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:46.383085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:46.968621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:47.896314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:46.596355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:24:47.184306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:24:53.148109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목번호관세율구분관세율단위당세액적용국가구분용도세율구분
품목번호1.0000.2720.1240.0000.0500.000
관세율구분0.2721.0000.1290.3361.0000.000
관세율0.1240.1291.0000.7710.020NaN
단위당세액0.0000.3360.7711.0000.000NaN
적용국가구분0.0501.0000.0200.0001.0000.000
용도세율구분0.0000.000NaNNaN0.0001.000
2024-04-06T17:24:53.375058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관세율구분적용국가구분용도세율구분
관세율구분1.0000.9980.000
적용국가구분0.9981.0000.000
용도세율구분0.0000.0001.000
2024-04-06T17:24:53.557710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목번호관세율단위당세액관세율구분적용국가구분용도세율구분
품목번호1.000-0.194-0.3100.0960.0380.000
관세율-0.1941.0000.4580.0490.0151.000
단위당세액-0.3100.4581.0000.0000.0000.000
관세율구분0.0960.0490.0001.0000.9980.000
적용국가구분0.0380.0150.0000.9981.0000.000
용도세율구분0.0001.0000.0000.0000.0001.000

Missing values

2024-04-06T17:24:48.245472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:24:48.650142image/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

품목번호관세율구분관세율단위당세액기준가격적용국가구분용도세율구분적용개시일적용만료일
881446306300000FCENI10.0<NA><NA>2<NA>2024-01-012024-12-31
591748608002000FCA10.0<NA><NA>2<NA>2024-01-012024-12-31
329146810199000FAS10.0<NA><NA>2<NA>2024-01-012024-12-31
211719619001090C0.0<NA><NA>1<NA>2024-01-012024-12-31
311104403410000FAS10.0<NA><NA>2<NA>2024-01-012024-12-31
949892825401000FCEPA10.0<NA><NA>2<NA>2024-01-012024-12-31
24972804300000A8.0<NA><NA>1<NA>2024-01-012024-12-31
505291503002000FCA10.0<NA><NA>2<NA>2024-01-012024-12-31
567797410221000FCA10.0<NA><NA>2<NA>2024-01-012024-12-31
850952938102000FCENI10.0<NA><NA>2<NA>2024-01-012024-12-31
품목번호관세율구분관세율단위당세액기준가격적용국가구분용도세율구분적용개시일적용만료일
790628418692090FCEHN10.0<NA><NA>2<NA>2024-01-012024-12-31
722341212940000FCEHN10.0<NA><NA>2<NA>2024-01-012024-12-31
961093104901010FCEPA10.0<NA><NA>2<NA>2024-01-012024-12-31
190948456111000C0.0<NA><NA>1A2024-01-012024-12-31
974544409229000FCEPA14.8<NA><NA>2<NA>2024-01-012024-12-31
701328704521010FCECR10.0<NA><NA>2<NA>2024-01-012024-12-31
814999032892090FCEHN10.0<NA><NA>2<NA>2024-01-012024-12-31
178897322191000C13.0<NA><NA>1<NA>2024-01-012024-12-31
183608301600000C13.0<NA><NA>1<NA>2024-01-012024-12-31
20522309903010A5.0<NA><NA>1<NA>2024-01-012024-12-31