Overview

Dataset statistics

Number of variables9
Number of observations6085
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory433.9 KiB
Average record size in memory73.0 B

Variable types

Categorical1
Text8

Dataset

Description한국무역보험공사의 최근 5년간(2017년 ~ 2021년)의 국가별 그리고 업종별 6가지 결제조건 비율입니다.
Author한국무역보험공사
URLhttps://www.data.go.kr/data/15104441/fileData.do

Reproduction

Analysis started2023-12-12 21:59:13.671430
Analysis finished2023-12-12 21:59:14.961496
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size47.7 KiB
2017
1217 
2018
1217 
2019
1217 
2020
1217 
2021
1217 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2017 1217
20.0%
2018 1217
20.0%
2019 1217
20.0%
2020 1217
20.0%
2021 1217
20.0%

Length

2023-12-13T06:59:15.039559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:59:15.178262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 1217
20.0%
2018 1217
20.0%
2019 1217
20.0%
2020 1217
20.0%
2021 1217
20.0%

국가
Text

Distinct77
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size47.7 KiB
2023-12-13T06:59:15.387519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length2.989318
Min length2

Characters and Unicode

Total characters18190
Distinct characters117
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중국
2nd row중국
3rd row중국
4th row중국
5th row중국
ValueCountFrequency (%)
미국 635
 
10.3%
중국 480
 
7.8%
인도 350
 
5.7%
일본 345
 
5.6%
독일 265
 
4.3%
베트남 260
 
4.2%
말레이시아 225
 
3.6%
대만 210
 
3.4%
인도네시아 200
 
3.2%
태국 180
 
2.9%
Other values (68) 3025
49.0%
2023-12-13T06:59:15.785421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 1545
 
8.5%
아 1175
 
6.5%
미 745
 
4.1%
시 725
 
4.0%
인 640
 
3.5%
일 625
 
3.4%
도 590
 
3.2%
이 570
 
3.1%
리 490
 
2.7%
중 480
 
2.6%
Other values (107) 10605
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18100
99.5%
Space Separator 90
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 1545
 
8.5%
아 1175
 
6.5%
미 745
 
4.1%
시 725
 
4.0%
인 640
 
3.5%
일 625
 
3.5%
도 590
 
3.3%
이 570
 
3.1%
리 490
 
2.7%
중 480
 
2.7%
Other values (106) 10515
58.1%
Space Separator
ValueCountFrequency (%)
90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18100
99.5%
Common 90
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 1545
 
8.5%
아 1175
 
6.5%
미 745
 
4.1%
시 725
 
4.0%
인 640
 
3.5%
일 625
 
3.5%
도 590
 
3.3%
이 570
 
3.1%
리 490
 
2.7%
중 480
 
2.7%
Other values (106) 10515
58.1%
Common
ValueCountFrequency (%)
90
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18100
99.5%
ASCII 90
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 1545
 
8.5%
아 1175
 
6.5%
미 745
 
4.1%
시 725
 
4.0%
인 640
 
3.5%
일 625
 
3.5%
도 590
 
3.3%
이 570
 
3.1%
리 490
 
2.7%
중 480
 
2.7%
Other values (106) 10515
58.1%
ASCII
ValueCountFrequency (%)
90
100.0%

업종
Text

Distinct285
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size47.7 KiB
2023-12-13T06:59:16.165055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length15.715694
Min length4

Characters and Unicode

Total characters95630
Distinct characters279
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

Unique0 ?
Unique (%)0.0%

Sample

1st row전구 램프 및 조명장치 도매업
2nd row전기용 기계 장비 및 관련 기자재 도매업
3rd row액정 표시장치 제조업
4th row이동 전화기 제조업
5th row그 외 기타 전자 부품 제조업
ValueCountFrequency (%)
제조업 3445
 
11.6%
및 3035
 
10.2%
기타 2620
 
8.8%
도매업 1900
 
6.4%
외 1080
 
3.6%
그 1080
 
3.6%
물질 570
 
1.9%
기계 565
 
1.9%
신품 560
 
1.9%
플라스틱 520
 
1.7%
Other values (472) 14435
48.4%
2023-12-13T06:59:16.742451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24320
25.4%
업 6335
 
6.6%
제 5035
 
5.3%
기 4670
 
4.9%
조 3660
 
3.8%
품 3185
 
3.3%
및 3035
 
3.2%
타 2840
 
3.0%
매 2345
 
2.5%
도 2105
 
2.2%
Other values (269) 38100
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71190
74.4%
Space Separator 24320
 
25.4%
Decimal Number 110
 
0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 6335
 
8.9%
제 5035
 
7.1%
기 4670
 
6.6%
조 3660
 
5.1%
품 3185
 
4.5%
및 3035
 
4.3%
타 2840
 
4.0%
매 2345
 
3.3%
도 2105
 
3.0%
용 1680
 
2.4%
Other values (265) 36300
51.0%
Space Separator
ValueCountFrequency (%)
24320
100.0%
Decimal Number
ValueCountFrequency (%)
1 110
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71190
74.4%
Common 24440
 
25.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 6335
 
8.9%
제 5035
 
7.1%
기 4670
 
6.6%
조 3660
 
5.1%
품 3185
 
4.5%
및 3035
 
4.3%
타 2840
 
4.0%
매 2345
 
3.3%
도 2105
 
3.0%
용 1680
 
2.4%
Other values (265) 36300
51.0%
Common
ValueCountFrequency (%)
24320
99.5%
1 110
 
0.5%
( 5
 
< 0.1%
) 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71190
74.4%
ASCII 24440
 
25.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24320
99.5%
1 110
 
0.5%
( 5
 
< 0.1%
) 5
 
< 0.1%
Hangul
ValueCountFrequency (%)
업 6335
 
8.9%
제 5035
 
7.1%
기 4670
 
6.6%
조 3660
 
5.1%
품 3185
 
4.5%
및 3035
 
4.3%
타 2840
 
4.0%
매 2345
 
3.3%
도 2105
 
3.0%
용 1680
 
2.4%
Other values (265) 36300
51.0%

사후송금
Text

Distinct102
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size47.7 KiB
2023-12-13T06:59:17.044829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.2933443
Min length1

Characters and Unicode

Total characters20040
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row100%
2nd row93%
3rd row94%
4th row96%
5th row92%
ValueCountFrequency (%)
100 2350
39.1%
99 196
 
3.3%
0 191
 
3.2%
98 170
 
2.8%
97 125
 
2.1%
96 117
 
1.9%
95 97
 
1.6%
94 87
 
1.4%
90 87
 
1.4%
93 78
 
1.3%
Other values (91) 2507
41.7%
2023-12-13T06:59:17.479731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
% 6005
30.0%
0 5184
25.9%
1 2814
14.0%
9 1551
 
7.7%
8 956
 
4.8%
7 766
 
3.8%
5 639
 
3.2%
6 611
 
3.0%
4 518
 
2.6%
3 481
 
2.4%
Other values (2) 515
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13955
69.6%
Other Punctuation 6005
30.0%
Space Separator 80
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5184
37.1%
1 2814
20.2%
9 1551
 
11.1%
8 956
 
6.9%
7 766
 
5.5%
5 639
 
4.6%
6 611
 
4.4%
4 518
 
3.7%
3 481
 
3.4%
2 435
 
3.1%
Other Punctuation
ValueCountFrequency (%)
% 6005
100.0%
Space Separator
ValueCountFrequency (%)
80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20040
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
% 6005
30.0%
0 5184
25.9%
1 2814
14.0%
9 1551
 
7.7%
8 956
 
4.8%
7 766
 
3.8%
5 639
 
3.2%
6 611
 
3.0%
4 518
 
2.6%
3 481
 
2.4%
Other values (2) 515
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20040
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
% 6005
30.0%
0 5184
25.9%
1 2814
14.0%
9 1551
 
7.7%
8 956
 
4.8%
7 766
 
3.8%
5 639
 
3.2%
6 611
 
3.0%
4 518
 
2.6%
3 481
 
2.4%
Other values (2) 515
 
2.6%

인수인도
Text

Distinct102
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size47.7 KiB
2023-12-13T06:59:17.726189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.2216927
Min length1

Characters and Unicode

Total characters13519
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0%
2nd row0%
3rd row2%
4th row0%
5th row0%
ValueCountFrequency (%)
0 3939
65.6%
1 161
 
2.7%
2 112
 
1.9%
3 98
 
1.6%
5 63
 
1.0%
4 61
 
1.0%
6 59
 
1.0%
100 57
 
0.9%
10 53
 
0.9%
9 52
 
0.9%
Other values (91) 1350
 
22.5%
2023-12-13T06:59:18.124810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
% 6005
44.4%
0 4204
31.1%
1 721
 
5.3%
2 465
 
3.4%
3 388
 
2.9%
5 326
 
2.4%
4 318
 
2.4%
6 273
 
2.0%
9 273
 
2.0%
7 237
 
1.8%
Other values (2) 309
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7434
55.0%
Other Punctuation 6005
44.4%
Space Separator 80
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4204
56.6%
1 721
 
9.7%
2 465
 
6.3%
3 388
 
5.2%
5 326
 
4.4%
4 318
 
4.3%
6 273
 
3.7%
9 273
 
3.7%
7 237
 
3.2%
8 229
 
3.1%
Other Punctuation
ValueCountFrequency (%)
% 6005
100.0%
Space Separator
ValueCountFrequency (%)
80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13519
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
% 6005
44.4%
0 4204
31.1%
1 721
 
5.3%
2 465
 
3.4%
3 388
 
2.9%
5 326
 
2.4%
4 318
 
2.4%
6 273
 
2.0%
9 273
 
2.0%
7 237
 
1.8%
Other values (2) 309
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13519
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
% 6005
44.4%
0 4204
31.1%
1 721
 
5.3%
2 465
 
3.4%
3 388
 
2.9%
5 326
 
2.4%
4 318
 
2.4%
6 273
 
2.0%
9 273
 
2.0%
7 237
 
1.8%
Other values (2) 309
 
2.3%

지급인도
Text

Distinct94
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size47.7 KiB
2023-12-13T06:59:18.363176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.0461791
Min length1

Characters and Unicode

Total characters12451
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)0.2%

Sample

1st row0%
2nd row0%
3rd row0%
4th row0%
5th row0%
ValueCountFrequency (%)
0 5370
89.4%
1 87
 
1.4%
2 53
 
0.9%
3 39
 
0.6%
4 27
 
0.4%
100 23
 
0.4%
5 23
 
0.4%
8 21
 
0.3%
7 19
 
0.3%
6 18
 
0.3%
Other values (83) 325
 
5.4%
2023-12-13T06:59:18.705344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
% 6005
48.2%
0 5450
43.8%
1 249
 
2.0%
2 140
 
1.1%
3 119
 
1.0%
80
 
0.6%
5 76
 
0.6%
8 76
 
0.6%
4 74
 
0.6%
7 61
 
0.5%
Other values (2) 121
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6366
51.1%
Other Punctuation 6005
48.2%
Space Separator 80
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5450
85.6%
1 249
 
3.9%
2 140
 
2.2%
3 119
 
1.9%
5 76
 
1.2%
8 76
 
1.2%
4 74
 
1.2%
7 61
 
1.0%
9 61
 
1.0%
6 60
 
0.9%
Other Punctuation
ValueCountFrequency (%)
% 6005
100.0%
Space Separator
ValueCountFrequency (%)
80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12451
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
% 6005
48.2%
0 5450
43.8%
1 249
 
2.0%
2 140
 
1.1%
3 119
 
1.0%
80
 
0.6%
5 76
 
0.6%
8 76
 
0.6%
4 74
 
0.6%
7 61
 
0.5%
Other values (2) 121
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12451
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
% 6005
48.2%
0 5450
43.8%
1 249
 
2.0%
2 140
 
1.1%
3 119
 
1.0%
80
 
0.6%
5 76
 
0.6%
8 76
 
0.6%
4 74
 
0.6%
7 61
 
0.5%
Other values (2) 121
 
1.0%

상계(NET)
Text

Distinct98
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size47.7 KiB
2023-12-13T06:59:18.920305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.0647494
Min length1

Characters and Unicode

Total characters12564
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.2%

Sample

1st row0%
2nd row7%
3rd row3%
4th row4%
5th row2%
ValueCountFrequency (%)
0 5117
85.2%
1 107
 
1.8%
2 75
 
1.2%
3 51
 
0.8%
4 43
 
0.7%
8 35
 
0.6%
5 31
 
0.5%
7 29
 
0.5%
9 27
 
0.4%
6 27
 
0.4%
Other values (87) 463
 
7.7%
2023-12-13T06:59:19.322421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
% 6005
47.8%
0 5205
41.4%
1 325
 
2.6%
2 201
 
1.6%
3 148
 
1.2%
8 112
 
0.9%
4 110
 
0.9%
9 101
 
0.8%
6 96
 
0.8%
5 91
 
0.7%
Other values (2) 170
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6479
51.6%
Other Punctuation 6005
47.8%
Space Separator 80
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5205
80.3%
1 325
 
5.0%
2 201
 
3.1%
3 148
 
2.3%
8 112
 
1.7%
4 110
 
1.7%
9 101
 
1.6%
6 96
 
1.5%
5 91
 
1.4%
7 90
 
1.4%
Other Punctuation
ValueCountFrequency (%)
% 6005
100.0%
Space Separator
ValueCountFrequency (%)
80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12564
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
% 6005
47.8%
0 5205
41.4%
1 325
 
2.6%
2 201
 
1.6%
3 148
 
1.2%
8 112
 
0.9%
4 110
 
0.9%
9 101
 
0.8%
6 96
 
0.8%
5 91
 
0.7%
Other values (2) 170
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12564
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
% 6005
47.8%
0 5205
41.4%
1 325
 
2.6%
2 201
 
1.6%
3 148
 
1.2%
8 112
 
0.9%
4 110
 
0.9%
9 101
 
0.8%
6 96
 
0.8%
5 91
 
0.7%
Other values (2) 170
 
1.4%

서류상환
Text

Distinct98
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size47.7 KiB
2023-12-13T06:59:19.548183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.0780608
Min length1

Characters and Unicode

Total characters12645
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row0%
2nd row0%
3rd row0%
4th row0%
5th row5%
ValueCountFrequency (%)
0 4885
81.3%
1 150
 
2.5%
2 111
 
1.8%
3 75
 
1.2%
4 63
 
1.0%
5 57
 
0.9%
7 41
 
0.7%
10 36
 
0.6%
6 35
 
0.6%
11 31
 
0.5%
Other values (87) 521
 
8.7%
2023-12-13T06:59:19.908716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
% 6005
47.5%
0 5009
39.6%
1 426
 
3.4%
2 246
 
1.9%
3 206
 
1.6%
4 153
 
1.2%
5 140
 
1.1%
7 107
 
0.8%
6 102
 
0.8%
8 89
 
0.7%
Other values (2) 162
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6560
51.9%
Other Punctuation 6005
47.5%
Space Separator 80
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5009
76.4%
1 426
 
6.5%
2 246
 
3.8%
3 206
 
3.1%
4 153
 
2.3%
5 140
 
2.1%
7 107
 
1.6%
6 102
 
1.6%
8 89
 
1.4%
9 82
 
1.2%
Other Punctuation
ValueCountFrequency (%)
% 6005
100.0%
Space Separator
ValueCountFrequency (%)
80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12645
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
% 6005
47.5%
0 5009
39.6%
1 426
 
3.4%
2 246
 
1.9%
3 206
 
1.6%
4 153
 
1.2%
5 140
 
1.1%
7 107
 
0.8%
6 102
 
0.8%
8 89
 
0.7%
Other values (2) 162
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12645
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
% 6005
47.5%
0 5009
39.6%
1 426
 
3.4%
2 246
 
1.9%
3 206
 
1.6%
4 153
 
1.2%
5 140
 
1.1%
7 107
 
0.8%
6 102
 
0.8%
8 89
 
0.7%
Other values (2) 162
 
1.3%

현물상환
Text

Distinct83
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size47.7 KiB
2023-12-13T06:59:20.134689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.031553
Min length1

Characters and Unicode

Total characters12362
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.4%

Sample

1st row0%
2nd row0%
3rd row0%
4th row0%
5th row1%
ValueCountFrequency (%)
0 5428
90.4%
1 79
 
1.3%
2 61
 
1.0%
4 40
 
0.7%
5 31
 
0.5%
3 28
 
0.5%
6 24
 
0.4%
8 21
 
0.3%
13 14
 
0.2%
7 14
 
0.2%
Other values (72) 265
 
4.4%
2023-12-13T06:59:20.510534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
% 6005
48.6%
0 5469
44.2%
1 211
 
1.7%
2 149
 
1.2%
3 94
 
0.8%
4 81
 
0.7%
80
 
0.6%
5 72
 
0.6%
6 54
 
0.4%
7 53
 
0.4%
Other values (2) 94
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6277
50.8%
Other Punctuation 6005
48.6%
Space Separator 80
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5469
87.1%
1 211
 
3.4%
2 149
 
2.4%
3 94
 
1.5%
4 81
 
1.3%
5 72
 
1.1%
6 54
 
0.9%
7 53
 
0.8%
8 52
 
0.8%
9 42
 
0.7%
Other Punctuation
ValueCountFrequency (%)
% 6005
100.0%
Space Separator
ValueCountFrequency (%)
80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12362
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
% 6005
48.6%
0 5469
44.2%
1 211
 
1.7%
2 149
 
1.2%
3 94
 
0.8%
4 81
 
0.7%
80
 
0.6%
5 72
 
0.6%
6 54
 
0.4%
7 53
 
0.4%
Other values (2) 94
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12362
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
% 6005
48.6%
0 5469
44.2%
1 211
 
1.7%
2 149
 
1.2%
3 94
 
0.8%
4 81
 
0.7%
80
 
0.6%
5 72
 
0.6%
6 54
 
0.4%
7 53
 
0.4%
Other values (2) 94
 
0.8%

Correlations

2023-12-13T06:59:20.622967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도국가지급인도상계(NET)서류상환현물상환
기준년도1.0000.0000.1140.1040.0700.150
국가0.0001.0000.0000.0000.5000.317
지급인도0.1140.0001.0000.0000.7650.030
상계(NET)0.1040.0000.0001.0000.0000.000
서류상환0.0700.5000.7650.0001.0000.457
현물상환0.1500.3170.0300.0000.4571.000

Missing values

2023-12-13T06:59:14.696995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:59:14.872185image/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

기준년도국가업종사후송금인수인도지급인도상계(NET)서류상환현물상환
02017중국전구 램프 및 조명장치 도매업100%0%0%0%0%0%
12017중국전기용 기계 장비 및 관련 기자재 도매업93%0%0%7%0%0%
22017중국액정 표시장치 제조업94%2%0%3%0%0%
32017중국이동 전화기 제조업96%0%0%4%0%0%
42017중국그 외 기타 전자 부품 제조업92%0%0%2%5%1%
52017중국비메모리용 및 기타 전자집적회로 제조업85%0%0%14%0%1%
62017중국기타 자동차 신품 부품 및 내장품 판매업74%6%0%0%21%0%
72017중국접착제 및 젤라틴 제조업100%0%0%0%0%0%
82017중국메모리용 전자집적회로 제조업100%0%0%0%0%0%
92017중국항공 여객 운송업100%0%0%0%0%0%
기준년도국가업종사후송금인수인도지급인도상계(NET)서류상환현물상환
60752021온두라스기타 자동차 신품 부품 및 내장품 판매업71%29%0%0%0%0%
60762021튀니지기타 화학 물질 및 화학제품 도매업87%0%7%0%7%0%
60772021튀니지의료 기기 도매업4%0%0%96%0%0%
60782021모로코매트리스 및 침대 제조업95%5%0%0%0%0%
60792021레바논기타 자동차 신품 부품 및 내장품 판매업99%1%0%0%0%0%
60802021세르비아기타 자동차 신품 부품 및 내장품 판매업1%99%0%0%0%0%
60812021자메이카자동차 신품 타이어 및 튜브 판매업84%9%0%0%7%0%
60822021니카라과기타 자동차 신품 부품 및 내장품 판매업69%31%0%0%0%0%
60832021탄자니아매트리스 및 침대 제조업0%100%0%0%0%0%
60842021나이지리아전지 및 케이블 도매업100%0%0%0%0%0%