Overview

Dataset statistics

Number of variables14
Number of observations500
Missing cells500
Missing cells (%)7.1%
Duplicate rows10
Duplicate rows (%)2.0%
Total size in memory58.7 KiB
Average record size in memory120.3 B

Variable types

Categorical12
Unsupported1
Boolean1

Dataset

Description해당 파일 데이터는 신용보증기금의 PC장애 처리내역에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092986/fileData.do

Alerts

피시(PC)장애요청유형코드 has constant value ""Constant
피시(PC)장애진행상태코드 has constant value ""Constant
피시(PC)장애해결유형코드 has constant value ""Constant
삭제여부 has constant value ""Constant
최종수정수 has constant value ""Constant
처리직원번호 has constant value ""Constant
최초처리직원번호 has constant value ""Constant
Dataset has 10 (2.0%) duplicate rowsDuplicates
접수자직원번호 is highly overall correlated with 담당자직원번호 and 1 other fieldsHigh correlation
담당자직원번호 is highly overall correlated with 접수자직원번호 and 1 other fieldsHigh correlation
최종처리직원번호 is highly overall correlated with 접수자직원번호 and 1 other fieldsHigh correlation
피시(PC)장애장애유형코드 is highly overall correlated with 피시(PC)장애요청경로코드High correlation
피시(PC)장애요청경로코드 is highly overall correlated with 피시(PC)장애장애유형코드High correlation
피시(PC)장애장애유형코드 is highly imbalanced (93.3%)Imbalance
피시(PC)장애요청경로코드 is highly imbalanced (85.9%)Imbalance
2차지원직원번호 has 500 (100.0%) missing valuesMissing
2차지원직원번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 17:12:50.343162
Analysis finished2023-12-12 17:12:51.355071
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

피시(PC)장애요청유형코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 500
100.0%

Length

2023-12-13T02:12:51.445632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:51.553684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 500
100.0%

피시(PC)장애장애유형코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
496 
2
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 496
99.2%
2 4
 
0.8%

Length

2023-12-13T02:12:51.689488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:51.819038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 496
99.2%
2 4
 
0.8%

피시(PC)장애요청경로코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
490 
1
 
10

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 490
98.0%
1 10
 
2.0%

Length

2023-12-13T02:12:51.973380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:52.112054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 490
98.0%
1 10
 
2.0%

피시(PC)장애진행상태코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
5
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 500
100.0%

Length

2023-12-13T02:12:52.248381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:52.379501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 500
100.0%

접수자직원번호
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
EXK28
201 
EXC94
161 
EXG82
138 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEXK28
2nd rowEXG82
3rd rowEXK28
4th rowEXC94
5th rowEXG82

Common Values

ValueCountFrequency (%)
EXK28 201
40.2%
EXC94 161
32.2%
EXG82 138
27.6%

Length

2023-12-13T02:12:52.511133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:52.631535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
exk28 201
40.2%
exc94 161
32.2%
exg82 138
27.6%

담당자직원번호
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
EXK28
201 
EXC94
161 
EXG82
138 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEXK28
2nd rowEXG82
3rd rowEXK28
4th rowEXC94
5th rowEXG82

Common Values

ValueCountFrequency (%)
EXK28 201
40.2%
EXC94 161
32.2%
EXG82 138
27.6%

Length

2023-12-13T02:12:52.773632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:52.931391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
exk28 201
40.2%
exc94 161
32.2%
exg82 138
27.6%

피시(PC)장애해결유형코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
4
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 500
100.0%

Length

2023-12-13T02:12:53.056235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:53.165676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 500
100.0%

피시(PC)장애처리방법코드
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
261 
2
236 
3
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 261
52.2%
2 236
47.2%
3 3
 
0.6%

Length

2023-12-13T02:12:53.280976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:53.378824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 261
52.2%
2 236
47.2%
3 3
 
0.6%

2차지원직원번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500
Missing (%)100.0%
Memory size4.5 KiB

최종처리직원번호
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
EXK28
201 
EXC94
161 
EXG82
138 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEXK28
2nd rowEXG82
3rd rowEXK28
4th rowEXC94
5th rowEXG82

Common Values

ValueCountFrequency (%)
EXK28 201
40.2%
EXC94 161
32.2%
EXG82 138
27.6%

Length

2023-12-13T02:12:53.492730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:53.599928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
exk28 201
40.2%
exc94 161
32.2%
exg82 138
27.6%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-13T02:12:53.690053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2023-12-13T02:12:53.805082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:53.894608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

처리직원번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
ACI01
500 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowACI01
2nd rowACI01
3rd rowACI01
4th rowACI01
5th rowACI01

Common Values

ValueCountFrequency (%)
ACI01 500
100.0%

Length

2023-12-13T02:12:54.009315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:54.108875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
aci01 500
100.0%

최초처리직원번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
ACI01
500 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowACI01
2nd rowACI01
3rd rowACI01
4th rowACI01
5th rowACI01

Common Values

ValueCountFrequency (%)
ACI01 500
100.0%

Length

2023-12-13T02:12:54.194858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:12:54.279958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
aci01 500
100.0%

Correlations

2023-12-13T02:12:54.347545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
피시(PC)장애장애유형코드피시(PC)장애요청경로코드접수자직원번호담당자직원번호피시(PC)장애처리방법코드최종처리직원번호
피시(PC)장애장애유형코드1.0000.7580.0170.0170.0000.017
피시(PC)장애요청경로코드0.7581.0000.0000.0000.0100.000
접수자직원번호0.0170.0001.0001.0000.0001.000
담당자직원번호0.0170.0001.0001.0000.0001.000
피시(PC)장애처리방법코드0.0000.0100.0000.0001.0000.000
최종처리직원번호0.0170.0001.0001.0000.0001.000
2023-12-13T02:12:54.474779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접수자직원번호피시(PC)장애요청경로코드피시(PC)장애장애유형코드피시(PC)장애처리방법코드담당자직원번호최종처리직원번호
접수자직원번호1.0000.0000.0280.0001.0001.000
피시(PC)장애요청경로코드0.0001.0000.5470.0170.0000.000
피시(PC)장애장애유형코드0.0280.5471.0000.0000.0280.028
피시(PC)장애처리방법코드0.0000.0170.0001.0000.0000.000
담당자직원번호1.0000.0000.0280.0001.0001.000
최종처리직원번호1.0000.0000.0280.0001.0001.000
2023-12-13T02:12:54.595102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
피시(PC)장애장애유형코드피시(PC)장애요청경로코드접수자직원번호담당자직원번호피시(PC)장애처리방법코드최종처리직원번호
피시(PC)장애장애유형코드1.0000.5470.0280.0280.0000.028
피시(PC)장애요청경로코드0.5471.0000.0000.0000.0170.000
접수자직원번호0.0280.0001.0001.0000.0001.000
담당자직원번호0.0280.0001.0001.0000.0001.000
피시(PC)장애처리방법코드0.0000.0170.0000.0001.0000.000
최종처리직원번호0.0280.0001.0001.0000.0001.000

Missing values

2023-12-13T02:12:50.979170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:12:51.246819image/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

피시(PC)장애요청유형코드피시(PC)장애장애유형코드피시(PC)장애요청경로코드피시(PC)장애진행상태코드접수자직원번호담당자직원번호피시(PC)장애해결유형코드피시(PC)장애처리방법코드2차지원직원번호최종처리직원번호삭제여부최종수정수처리직원번호최초처리직원번호
02125EXK28EXK2841<NA>EXK28N1ACI01ACI01
12125EXG82EXG8241<NA>EXG82N1ACI01ACI01
22125EXK28EXK2842<NA>EXK28N1ACI01ACI01
32125EXC94EXC9441<NA>EXC94N1ACI01ACI01
42125EXG82EXG8242<NA>EXG82N1ACI01ACI01
52125EXK28EXK2841<NA>EXK28N1ACI01ACI01
62125EXC94EXC9441<NA>EXC94N1ACI01ACI01
72125EXK28EXK2841<NA>EXK28N1ACI01ACI01
82125EXK28EXK2841<NA>EXK28N1ACI01ACI01
92125EXG82EXG8242<NA>EXG82N1ACI01ACI01
피시(PC)장애요청유형코드피시(PC)장애장애유형코드피시(PC)장애요청경로코드피시(PC)장애진행상태코드접수자직원번호담당자직원번호피시(PC)장애해결유형코드피시(PC)장애처리방법코드2차지원직원번호최종처리직원번호삭제여부최종수정수처리직원번호최초처리직원번호
4902125EXG82EXG8242<NA>EXG82N1ACI01ACI01
4912125EXG82EXG8241<NA>EXG82N1ACI01ACI01
4922125EXK28EXK2841<NA>EXK28N1ACI01ACI01
4932125EXK28EXK2842<NA>EXK28N1ACI01ACI01
4942125EXG82EXG8242<NA>EXG82N1ACI01ACI01
4952125EXG82EXG8241<NA>EXG82N1ACI01ACI01
4962125EXG82EXG8241<NA>EXG82N1ACI01ACI01
4972125EXK28EXK2841<NA>EXK28N1ACI01ACI01
4982125EXG82EXG8241<NA>EXG82N1ACI01ACI01
4992125EXK28EXK2841<NA>EXK28N1ACI01ACI01

Duplicate rows

Most frequently occurring

피시(PC)장애요청유형코드피시(PC)장애장애유형코드피시(PC)장애요청경로코드피시(PC)장애진행상태코드접수자직원번호담당자직원번호피시(PC)장애해결유형코드피시(PC)장애처리방법코드최종처리직원번호삭제여부최종수정수처리직원번호최초처리직원번호# duplicates
62125EXK28EXK2841EXK28N1ACI01ACI01106
72125EXK28EXK2842EXK28N1ACI01ACI0187
32125EXC94EXC9442EXC94N1ACI01ACI0180
22125EXC94EXC9441EXC94N1ACI01ACI0179
42125EXG82EXG8241EXG82N1ACI01ACI0173
52125EXG82EXG8242EXG82N1ACI01ACI0162
92215EXK28EXK2842EXK28N1ACI01ACI013
02115EXG82EXG8242EXG82N1ACI01ACI012
12115EXK28EXK2841EXK28N1ACI01ACI012
82125EXK28EXK2843EXK28N1ACI01ACI012