Overview

Dataset statistics

Number of variables11
Number of observations500
Missing cells500
Missing cells (%)9.1%
Duplicate rows87
Duplicate rows (%)17.4%
Total size in memory45.1 KiB
Average record size in memory92.3 B

Variable types

Categorical6
Numeric2
Unsupported1
Boolean2

Dataset

Description해당 파일 데이터는 신용보증기금의 고객신용정보신용고객기본정보에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15093082/fileData.do

Alerts

기업형태코드 has constant value ""Constant
직업구분코드 has constant value ""Constant
정정청구중여부 has constant value ""Constant
삭제일자 has constant value ""Constant
삭제여부 has constant value ""Constant
처리직원번호 has constant value ""Constant
최초처리직원번호 has constant value ""Constant
Dataset has 87 (17.4%) duplicate rowsDuplicates
최종업데이트일자 has 500 (100.0%) missing valuesMissing
최종업데이트일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업종코드 has 94 (18.8%) zerosZeros

Reproduction

Analysis started2023-12-12 00:19:34.974673
Analysis finished2023-12-12 00:19:35.919350
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기업형태코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
500
100.0%

Length

2023-12-12T09:19:35.981317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:19:36.087529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

기업형태앞뒤구분코드
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
315 
1
157 
 
28

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 315
63.0%
1 157
31.4%
28
 
5.6%

Length

2023-12-12T09:19:36.197180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:19:36.306804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 315
66.7%
1 157
33.3%

직업구분코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-12T09:19:36.423662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:19:36.512354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

업종코드
Real number (ℝ)

ZEROS 

Distinct132
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4406.45
Minimum0
Maximum9900
Zeros94
Zeros (%)18.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T09:19:36.644868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11576.5
median4631
Q35916.75
95-th percentile9900
Maximum9900
Range9900
Interquartile range (IQR)4340.25

Descriptive statistics

Standard deviation3261.7049
Coefficient of variation (CV)0.74021149
Kurtosis-0.91720631
Mean4406.45
Median Absolute Deviation (MAD)2407.5
Skewness0.27601377
Sum2203225
Variance10638719
MonotonicityNot monotonic
2023-12-12T09:19:36.785054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 94
 
18.8%
9900 69
 
13.8%
5611 18
 
3.6%
4631 16
 
3.2%
5822 9
 
1.8%
4111 9
 
1.8%
5299 7
 
1.4%
4672 7
 
1.4%
4112 7
 
1.4%
4212 6
 
1.2%
Other values (122) 258
51.6%
ValueCountFrequency (%)
0 94
18.8%
111 1
 
0.2%
114 1
 
0.2%
129 1
 
0.2%
204 2
 
0.4%
322 1
 
0.2%
1012 3
 
0.6%
1061 3
 
0.6%
1071 2
 
0.4%
1074 1
 
0.2%
ValueCountFrequency (%)
9900 69
13.8%
9700 1
 
0.2%
9699 5
 
1.0%
9691 1
 
0.2%
9611 1
 
0.2%
9511 1
 
0.2%
9411 1
 
0.2%
9113 3
 
0.6%
8610 2
 
0.4%
8570 1
 
0.2%

최종업데이트일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

정정청구중여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-12T09:19:36.899224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

삭제일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
500 

Length

Max length26
Median length26
Mean length26
Min length26

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row0001-01-01 00:00:00.000000
4th row0001-01-01 00:00:00.000000
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 500
100.0%

Length

2023-12-12T09:19:36.999963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:19:37.100649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 500
50.0%
00:00:00.000000 500
50.0%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-12T09:19:37.163925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Real number (ℝ)

Distinct73
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.964
Minimum1
Maximum352
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T09:19:37.260377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median11
Q323
95-th percentile66.05
Maximum352
Range351
Interquartile range (IQR)18

Descriptive statistics

Standard deviation33.610684
Coefficient of variation (CV)1.6835646
Kurtosis45.3655
Mean19.964
Median Absolute Deviation (MAD)7
Skewness5.8446408
Sum9982
Variance1129.6781
MonotonicityNot monotonic
2023-12-12T09:19:37.384029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 38
 
7.6%
4 32
 
6.4%
3 30
 
6.0%
11 26
 
5.2%
7 25
 
5.0%
2 23
 
4.6%
12 21
 
4.2%
13 21
 
4.2%
10 19
 
3.8%
8 18
 
3.6%
Other values (63) 247
49.4%
ValueCountFrequency (%)
1 38
7.6%
2 23
4.6%
3 30
6.0%
4 32
6.4%
5 13
 
2.6%
6 17
3.4%
7 25
5.0%
8 18
3.6%
9 15
 
3.0%
10 19
3.8%
ValueCountFrequency (%)
352 1
0.2%
349 1
0.2%
225 1
0.2%
224 1
0.2%
207 1
0.2%
180 2
0.4%
113 1
0.2%
112 1
0.2%
107 1
0.2%
104 1
0.2%

처리직원번호
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BATCH 500
100.0%

Length

2023-12-12T09:19:37.500833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:19:37.622391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
batch 500
100.0%

최초처리직원번호
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BATCH 500
100.0%

Length

2023-12-12T09:19:37.716967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:19:37.809226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
batch 500
100.0%

Interactions

2023-12-12T09:19:35.380424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:19:35.172805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:19:35.476571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:19:35.266744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:19:37.873316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기업형태앞뒤구분코드업종코드최종수정수
기업형태앞뒤구분코드1.0000.3540.075
업종코드0.3541.0000.224
최종수정수0.0750.2241.000
2023-12-12T09:19:37.955720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종코드최종수정수기업형태앞뒤구분코드
업종코드1.0000.1060.226
최종수정수0.1061.0000.050
기업형태앞뒤구분코드0.2260.0501.000

Missing values

2023-12-12T09:19:35.646930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:19:35.857776image/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

기업형태코드기업형태앞뒤구분코드직업구분코드업종코드최종업데이트일자정정청구중여부삭제일자삭제여부최종수정수처리직원번호최초처리직원번호
0202919<NA>N0001-01-01 00:00:00.000000N32BATCHBATCH
1209900<NA>N0001-01-01 00:00:00.000000N92BATCHBATCH
2102919<NA>N0001-01-01 00:00:00.000000N20BATCHBATCH
3109900<NA>N0001-01-01 00:00:00.000000N14BATCHBATCH
4204662<NA>N0001-01-01 00:00:00.000000N225BATCHBATCH
5204649<NA>N0001-01-01 00:00:00.000000N112BATCHBATCH
6202919<NA>N0001-01-01 00:00:00.000000N43BATCHBATCH
7104662<NA>N0001-01-01 00:00:00.000000N224BATCHBATCH
8208610<NA>N0001-01-01 00:00:00.000000N33BATCHBATCH
9101012<NA>N0001-01-01 00:00:00.000000N180BATCHBATCH
기업형태코드기업형태앞뒤구분코드직업구분코드업종코드최종업데이트일자정정청구중여부삭제일자삭제여부최종수정수처리직원번호최초처리직원번호
490204631<NA>N0001-01-01 00:00:00.000000N107BATCHBATCH
491200<NA>N0001-01-01 00:00:00.000000N23BATCHBATCH
492109699<NA>N0001-01-01 00:00:00.000000N28BATCHBATCH
493209900<NA>N0001-01-01 00:00:00.000000N32BATCHBATCH
494207521<NA>N0001-01-01 00:00:00.000000N26BATCHBATCH
495102611<NA>N0001-01-01 00:00:00.000000N61BATCHBATCH
49600<NA>N0001-01-01 00:00:00.000000N3BATCHBATCH
49700<NA>N0001-01-01 00:00:00.000000N14BATCHBATCH
498204679<NA>N0001-01-01 00:00:00.000000N24BATCHBATCH
499204679<NA>N0001-01-01 00:00:00.000000N24BATCHBATCH

Duplicate rows

Most frequently occurring

기업형태코드기업형태앞뒤구분코드직업구분코드업종코드정정청구중여부삭제일자삭제여부최종수정수처리직원번호최초처리직원번호# duplicates
32200N0001-01-01 00:00:00.000000N1BATCHBATCH12
4100N0001-01-01 00:00:00.000000N1BATCHBATCH7
34200N0001-01-01 00:00:00.000000N3BATCHBATCH5
25109900N0001-01-01 00:00:00.000000N1BATCHBATCH4
33200N0001-01-01 00:00:00.000000N2BATCHBATCH4
38200N0001-01-01 00:00:00.000000N11BATCHBATCH4
39200N0001-01-01 00:00:00.000000N12BATCHBATCH4
84209900N0001-01-01 00:00:00.000000N14BATCHBATCH4
000N0001-01-01 00:00:00.000000N1BATCHBATCH3
6100N0001-01-01 00:00:00.000000N3BATCHBATCH3