Overview

Dataset statistics

Number of variables10
Number of observations749
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory62.3 KiB
Average record size in memory85.2 B

Variable types

Categorical4
Numeric5
Text1

Dataset

Description수산물 수출입정보는 국내에 수출 및 수입되는 수산물에 대한 월별 통계정보로 관세청에서 보유한 데이터를 집계하여 제공하는 데이터로 수산물 품목별 수출입 현황를 제공하는 목록입니다.
Author해양수산부
URLhttps://www.data.go.kr/data/15102783/fileData.do

Alerts

기준년월 has constant value ""Constant
데이터기준일자 has constant value ""Constant
수출입구분명 is highly overall correlated with 수출입구분코드High correlation
수출입구분코드 is highly overall correlated with 수출입구분명High correlation
당월수출입중량(킬로그램) is highly overall correlated with 당월수출입미화금액(달러) and 2 other fieldsHigh correlation
당월수출입미화금액(달러) is highly overall correlated with 당월수출입중량(킬로그램) and 2 other fieldsHigh correlation
당해누계수출입중량(킬로그램) is highly overall correlated with 당월수출입중량(킬로그램) and 2 other fieldsHigh correlation
당해누계수출입미화금액(달러) is highly overall correlated with 당월수출입중량(킬로그램) and 2 other fieldsHigh correlation
당월수출입중량(킬로그램) is highly skewed (γ1 = 27.17099163)Skewed
당해누계수출입중량(킬로그램) is highly skewed (γ1 = 27.07844295)Skewed
당월수출입중량(킬로그램) has 89 (11.9%) zerosZeros
당월수출입미화금액(달러) has 85 (11.3%) zerosZeros
당해누계수출입중량(킬로그램) has 8 (1.1%) zerosZeros

Reproduction

Analysis started2024-04-21 02:09:26.625130
Analysis finished2024-04-21 02:09:31.564549
Duration4.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-02
749 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02
2nd row2024-02
3rd row2024-02
4th row2024-02
5th row2024-02

Common Values

ValueCountFrequency (%)
2024-02 749
100.0%

Length

2024-04-21T11:09:31.681265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:09:31.797426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02 749
100.0%

HSK품목코드
Real number (ℝ)

Distinct476
Distinct (%)63.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.152698 × 108
Minimum1.06199 × 108
Maximum9.606291 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-21T11:09:31.950014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.06199 × 108
5-th percentile3.019991 × 108
Q13.0389909 × 108
median3.07229 × 108
Q31.302312 × 109
95-th percentile1.847673 × 109
Maximum9.606291 × 109
Range9.500092 × 109
Interquartile range (IQR)9.9841291 × 108

Descriptive statistics

Standard deviation1.0822342 × 109
Coefficient of variation (CV)1.3274553
Kurtosis31.451759
Mean8.152698 × 108
Median Absolute Deviation (MAD)3789000
Skewness4.8173133
Sum6.1063708 × 1011
Variance1.171231 × 1018
MonotonicityNot monotonic
2024-04-21T11:09:32.124207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
106199000 2
 
0.3%
309100000 2
 
0.3%
1212212010 2
 
0.3%
1212211090 2
 
0.3%
1212211010 2
 
0.3%
511919000 2
 
0.3%
508009000 2
 
0.3%
508002090 2
 
0.3%
508001000 2
 
0.3%
308902090 2
 
0.3%
Other values (466) 729
97.3%
ValueCountFrequency (%)
106199000 2
0.3%
106201000 2
0.3%
106202000 1
0.1%
106203000 2
0.3%
106209000 2
0.3%
106903010 1
0.1%
106903090 1
0.1%
301111000 1
0.1%
301119000 2
0.3%
301190000 1
0.1%
ValueCountFrequency (%)
9606291000 2
0.3%
9601901090 2
0.3%
7116102000 2
0.3%
7116101000 2
0.3%
7101220000 2
0.3%
7101210000 1
0.1%
2501009090 2
0.3%
2501009020 2
0.3%
2501009010 2
0.3%
2501001020 2
0.3%

수출입구분코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
I
401 
E
348 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 401
53.5%
E 348
46.5%

Length

2024-04-21T11:09:32.288738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:09:32.399825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 401
53.5%
e 348
46.5%

수산물수출입품목명
Text

Distinct433
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-04-21T11:09:32.606342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length108
Median length50
Mean length17.658211
Min length1

Characters and Unicode

Total characters13226
Distinct characters379
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)23.8%

Sample

1st row기타 포유동물
2nd row뱀
3rd row거북
4th row기타 파충류
5th row기타(활어)(비단잉어 외 민물의 것)
ValueCountFrequency (%)
것 210
 
10.1%
또는 129
 
6.2%
기타 108
 
5.2%
넣은 46
 
2.2%
냉장한 33
 
1.6%
이외 31
 
1.5%
신선 26
 
1.2%
냉장 24
 
1.2%
저장처리)(밀폐용기에 24
 
1.2%
피레트 21
 
1.0%
Other values (621) 1434
68.7%
2024-04-21T11:09:33.027606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1345
 
10.2%
( 803
 
6.1%
) 803
 
6.1%
/ 439
 
3.3%
기 435
 
3.3%
어 341
 
2.6%
타 340
 
2.6%
것 307
 
2.3%
스 260
 
2.0%
장 253
 
1.9%
Other values (369) 7900
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9177
69.4%
Space Separator 1345
 
10.2%
Open Punctuation 842
 
6.4%
Close Punctuation 836
 
6.3%
Lowercase Letter 501
 
3.8%
Other Punctuation 445
 
3.4%
Uppercase Letter 51
 
0.4%
Dash Punctuation 17
 
0.1%
Decimal Number 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 435
 
4.7%
어 341
 
3.7%
타 340
 
3.7%
것 307
 
3.3%
스 260
 
2.8%
장 253
 
2.8%
냉 252
 
2.7%
조 229
 
2.5%
한 202
 
2.2%
동 190
 
2.1%
Other values (325) 6368
69.4%
Lowercase Letter
ValueCountFrequency (%)
a 64
12.8%
s 63
12.6%
o 60
12.0%
i 51
10.2%
r 39
7.8%
l 32
 
6.4%
u 31
 
6.2%
e 28
 
5.6%
m 28
 
5.6%
p 19
 
3.8%
Other values (9) 86
17.2%
Uppercase Letter
ValueCountFrequency (%)
S 15
29.4%
P 8
15.7%
O 5
 
9.8%
C 5
 
9.8%
R 4
 
7.8%
H 4
 
7.8%
N 3
 
5.9%
L 2
 
3.9%
J 2
 
3.9%
E 2
 
3.9%
Decimal Number
ValueCountFrequency (%)
6 4
33.3%
0 3
25.0%
3 2
16.7%
2 2
16.7%
5 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 803
95.4%
[ 37
 
4.4%
{ 2
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 803
96.1%
] 33
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/ 439
98.7%
. 6
 
1.3%
Space Separator
ValueCountFrequency (%)
1345
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9154
69.2%
Common 3497
 
26.4%
Latin 552
 
4.2%
Han 23
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 435
 
4.8%
어 341
 
3.7%
타 340
 
3.7%
것 307
 
3.4%
스 260
 
2.8%
장 253
 
2.8%
냉 252
 
2.8%
조 229
 
2.5%
한 202
 
2.2%
동 190
 
2.1%
Other values (315) 6345
69.3%
Latin
ValueCountFrequency (%)
a 64
11.6%
s 63
11.4%
o 60
10.9%
i 51
 
9.2%
r 39
 
7.1%
l 32
 
5.8%
u 31
 
5.6%
e 28
 
5.1%
m 28
 
5.1%
p 19
 
3.4%
Other values (20) 137
24.8%
Common
ValueCountFrequency (%)
1345
38.5%
( 803
23.0%
) 803
23.0%
/ 439
 
12.6%
[ 37
 
1.1%
] 33
 
0.9%
- 17
 
0.5%
. 6
 
0.2%
6 4
 
0.1%
0 3
 
0.1%
Other values (4) 7
 
0.2%
Han
ValueCountFrequency (%)
魚 4
17.4%
肝 4
17.4%
油 4
17.4%
鹽 2
8.7%
白 2
8.7%
卵 2
8.7%
岩 2
8.7%
冷 1
 
4.3%
水 1
 
4.3%
性 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9122
69.0%
ASCII 4049
30.6%
Compat Jamo 32
 
0.2%
CJK 22
 
0.2%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1345
33.2%
( 803
19.8%
) 803
19.8%
/ 439
 
10.8%
a 64
 
1.6%
s 63
 
1.6%
o 60
 
1.5%
i 51
 
1.3%
r 39
 
1.0%
[ 37
 
0.9%
Other values (34) 345
 
8.5%
Hangul
ValueCountFrequency (%)
기 435
 
4.8%
어 341
 
3.7%
타 340
 
3.7%
것 307
 
3.4%
스 260
 
2.9%
장 253
 
2.8%
냉 252
 
2.8%
조 229
 
2.5%
한 202
 
2.2%
동 190
 
2.1%
Other values (314) 6313
69.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 32
100.0%
CJK
ValueCountFrequency (%)
魚 4
18.2%
肝 4
18.2%
油 4
18.2%
鹽 2
9.1%
白 2
9.1%
卵 2
9.1%
岩 2
9.1%
水 1
 
4.5%
性 1
 
4.5%
CJK Compat Ideographs
ValueCountFrequency (%)
冷 1
100.0%

수출입구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
수입
401 
수출
348 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수입 401
53.5%
수출 348
46.5%

Length

2024-04-21T11:09:33.170624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:09:33.261700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수입 401
53.5%
수출 348
46.5%

당월수출입중량(킬로그램)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct579
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean846587.13
Minimum0
Maximum4.5336272 × 108
Zeros89
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-21T11:09:33.382324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q149
median2805
Q364723
95-th percentile1258722
Maximum4.5336272 × 108
Range4.5336272 × 108
Interquartile range (IQR)64674

Descriptive statistics

Standard deviation16597210
Coefficient of variation (CV)19.604846
Kurtosis741.68496
Mean846587.13
Median Absolute Deviation (MAD)2805
Skewness27.170992
Sum6.3409376 × 108
Variance2.7546739 × 1014
MonotonicityNot monotonic
2024-04-21T11:09:33.592241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 89
 
11.9%
1 20
 
2.7%
2 11
 
1.5%
5 6
 
0.8%
10 4
 
0.5%
30 4
 
0.5%
15 4
 
0.5%
14 3
 
0.4%
27 3
 
0.4%
22 3
 
0.4%
Other values (569) 602
80.4%
ValueCountFrequency (%)
0 89
11.9%
1 20
 
2.7%
2 11
 
1.5%
3 3
 
0.4%
4 1
 
0.1%
5 6
 
0.8%
6 3
 
0.4%
7 2
 
0.3%
8 1
 
0.1%
9 2
 
0.3%
ValueCountFrequency (%)
453362724 1
0.1%
17851834 1
0.1%
15512930 1
0.1%
13708933 1
0.1%
5949831 1
0.1%
5943249 1
0.1%
5577856 1
0.1%
5552796 1
0.1%
3999089 1
0.1%
3662610 1
0.1%

당월수출입미화금액(달러)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct653
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean927396.45
Minimum0
Maximum41707526
Zeros85
Zeros (%)11.3%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-21T11:09:33.812446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1851
median28463
Q3337303
95-th percentile4035603.2
Maximum41707526
Range41707526
Interquartile range (IQR)336452

Descriptive statistics

Standard deviation3379833
Coefficient of variation (CV)3.6444317
Kurtosis65.091947
Mean927396.45
Median Absolute Deviation (MAD)28463
Skewness7.209027
Sum6.9461994 × 108
Variance1.1423271 × 1013
MonotonicityNot monotonic
2024-04-21T11:09:34.199513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 85
 
11.3%
15 3
 
0.4%
2 2
 
0.3%
19 2
 
0.3%
84 2
 
0.3%
6 2
 
0.3%
3 2
 
0.3%
1443 2
 
0.3%
12 2
 
0.3%
8 2
 
0.3%
Other values (643) 645
86.1%
ValueCountFrequency (%)
0 85
11.3%
1 1
 
0.1%
2 2
 
0.3%
3 2
 
0.3%
4 1
 
0.1%
6 2
 
0.3%
7 2
 
0.3%
8 2
 
0.3%
12 2
 
0.3%
15 3
 
0.4%
ValueCountFrequency (%)
41707526 1
0.1%
39837044 1
0.1%
25784373 1
0.1%
22963393 1
0.1%
21476989 1
0.1%
20928139 1
0.1%
20221551 1
0.1%
19593263 1
0.1%
18195519 1
0.1%
15594762 1
0.1%

당해누계수출입중량(킬로그램)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct664
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1656793.7
Minimum0
Maximum8.2368551 × 108
Zeros8
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-21T11:09:34.357683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.4
Q1410
median9313
Q3148813
95-th percentile3013889.8
Maximum8.2368551 × 108
Range8.2368551 × 108
Interquartile range (IQR)148403

Descriptive statistics

Standard deviation30185082
Coefficient of variation (CV)18.218974
Kurtosis738.23587
Mean1656793.7
Median Absolute Deviation (MAD)9308
Skewness27.078443
Sum1.2409385 × 109
Variance9.1113916 × 1014
MonotonicityNot monotonic
2024-04-21T11:09:34.487190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 13
 
1.7%
0 8
 
1.1%
20 7
 
0.9%
3 7
 
0.9%
2 7
 
0.9%
5 6
 
0.8%
200 4
 
0.5%
10 4
 
0.5%
110 4
 
0.5%
4 3
 
0.4%
Other values (654) 686
91.6%
ValueCountFrequency (%)
0 8
1.1%
1 13
1.7%
2 7
0.9%
3 7
0.9%
4 3
 
0.4%
5 6
0.8%
6 2
 
0.3%
7 3
 
0.4%
8 3
 
0.4%
9 1
 
0.1%
ValueCountFrequency (%)
823685513 1
0.1%
36212969 1
0.1%
31663335 1
0.1%
28186297 1
0.1%
23562395 1
0.1%
16393801 1
0.1%
14768823 1
0.1%
9789046 1
0.1%
8610256 1
0.1%
8601213 1
0.1%

당해누계수출입미화금액(달러)
Real number (ℝ)

HIGH CORRELATION 

Distinct732
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1958697.3
Minimum0
Maximum82480627
Zeros2
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2024-04-21T11:09:34.622403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile56.2
Q18111
median84238
Q3756172
95-th percentile9889709.2
Maximum82480627
Range82480627
Interquartile range (IQR)748061

Descriptive statistics

Standard deviation6643443.8
Coefficient of variation (CV)3.3917664
Kurtosis52.455998
Mean1958697.3
Median Absolute Deviation (MAD)84008
Skewness6.4718172
Sum1.4670643 × 109
Variance4.4135345 × 1013
MonotonicityNot monotonic
2024-04-21T11:09:34.765203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 3
 
0.4%
283 3
 
0.4%
7 3
 
0.4%
19 2
 
0.3%
0 2
 
0.3%
84 2
 
0.3%
15 2
 
0.3%
9 2
 
0.3%
237 2
 
0.3%
67 2
 
0.3%
Other values (722) 726
96.9%
ValueCountFrequency (%)
0 2
0.3%
1 1
 
0.1%
3 1
 
0.1%
6 2
0.3%
7 3
0.4%
9 2
0.3%
13 1
 
0.1%
15 2
0.3%
17 1
 
0.1%
18 1
 
0.1%
ValueCountFrequency (%)
82480627 1
0.1%
58574952 1
0.1%
52490363 1
0.1%
51511952 1
0.1%
42107072 1
0.1%
41253059 1
0.1%
39962019 1
0.1%
38862594 1
0.1%
37743775 1
0.1%
35872783 1
0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-02-29
749 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-29
2nd row2024-02-29
3rd row2024-02-29
4th row2024-02-29
5th row2024-02-29

Common Values

ValueCountFrequency (%)
2024-02-29 749
100.0%

Length

2024-04-21T11:09:34.894038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:09:35.003796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-29 749
100.0%

Interactions

2024-04-21T11:09:30.852050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:28.919653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:29.443217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:29.957937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:30.413201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:30.940463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:29.071455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:29.527260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:30.067253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:30.497429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:31.033621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:29.161723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:29.620877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:30.154884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:30.593218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:31.134220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:29.259395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:29.714360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:30.240840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:30.678552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:31.221459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:29.351512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:29.833102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:30.324516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:09:30.762686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:09:35.071898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
HSK품목코드수출입구분코드수출입구분명당월수출입중량(킬로그램)당월수출입미화금액(달러)당해누계수출입중량(킬로그램)당해누계수출입미화금액(달러)
HSK품목코드1.0000.0000.0000.1430.0260.1430.094
수출입구분코드0.0001.0001.0000.0000.1120.0000.132
수출입구분명0.0001.0001.0000.0000.1120.0000.132
당월수출입중량(킬로그램)0.1430.0000.0001.0000.7440.7050.436
당월수출입미화금액(달러)0.0260.1120.1120.7441.0000.7440.905
당해누계수출입중량(킬로그램)0.1430.0000.0000.7050.7441.0000.436
당해누계수출입미화금액(달러)0.0940.1320.1320.4360.9050.4361.000
2024-04-21T11:09:35.181689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수출입구분명수출입구분코드
수출입구분명1.0000.997
수출입구분코드0.9971.000
2024-04-21T11:09:35.268213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
HSK품목코드당월수출입중량(킬로그램)당월수출입미화금액(달러)당해누계수출입중량(킬로그램)당해누계수출입미화금액(달러)수출입구분코드수출입구분명
HSK품목코드1.000-0.062-0.059-0.058-0.0540.0000.000
당월수출입중량(킬로그램)-0.0621.0000.9590.9190.8920.0000.000
당월수출입미화금액(달러)-0.0590.9591.0000.8650.9230.0840.084
당해누계수출입중량(킬로그램)-0.0580.9190.8651.0000.9440.0000.000
당해누계수출입미화금액(달러)-0.0540.8920.9230.9441.0000.1310.131
수출입구분코드0.0000.0000.0840.0000.1311.0000.997
수출입구분명0.0000.0000.0840.0000.1310.9971.000

Missing values

2024-04-21T11:09:31.344802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:09:31.488162image/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

기준년월HSK품목코드수출입구분코드수산물수출입품목명수출입구분명당월수출입중량(킬로그램)당월수출입미화금액(달러)당해누계수출입중량(킬로그램)당해누계수출입미화금액(달러)데이터기준일자
02024-02106199000E기타 포유동물수출24217629651464132024-02-29
12024-02106201000E뱀수출1254447905442024-02-29
22024-02106203000E거북수출560256022024-02-29
32024-02106209000E기타 파충류수출92486732551246972024-02-29
42024-02301119000E기타(활어)(비단잉어 외 민물의 것)수출2012802012802024-02-29
52024-02301994091E돔(기타/ 참돔)수출740130111060163272024-02-29
62024-02301995000E붕장어(활어)수출132696130834028087028327372024-02-29
72024-02301998000E넙치(활어)수출188230307306737537063392492024-02-29
82024-02301999020E복어(활어)수출0025963622024-02-29
92024-02301999040E볼락(적어포함/활어)수출49006808764371076412024-02-29
기준년월HSK품목코드수출입구분코드수산물수출입품목명수출입구분명당월수출입중량(킬로그램)당월수출입미화금액(달러)당해누계수출입중량(킬로그램)당해누계수출입미화금액(달러)데이터기준일자
7392024-022501001020I천일염수입45336272421476989823685513388625942024-02-29
7402024-022501009010I식염수입1370893312874963621296934139242024-02-29
7412024-022501009020I순염화나트륨수입1416685654926304104317740062024-02-29
7422024-022501009090I기타소금/해수수입34367486819061639380115488782024-02-29
7432024-027101210000I양식진주(가공하지않은것)수입273711167100002024-02-29
7442024-027101220000I양식진주(가공한것)수입30271181052031722024-02-29
7452024-027116101000I천연진주로만든 것수입1153995508139482024-02-29
7462024-027116102000I양식진주로 만든 것수입3417075172752532024-02-29
7472024-029601901090I패각(기타)수입3641231258529684433605132024-02-29
7482024-029606291000I조개껍질로 만든것수입28424208900825562024-02-29