Overview

Dataset statistics

Number of variables20
Number of observations500
Missing cells1000
Missing cells (%)10.0%
Duplicate rows77
Duplicate rows (%)15.4%
Total size in memory82.2 KiB
Average record size in memory168.3 B

Variable types

Numeric2
Categorical16
Unsupported2

Dataset

Description해당 파일 데이터는 신용보증기금의 보증상담신청정보에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092840/fileData.do

Alerts

업무구분코드 has constant value ""Constant
보증신청구분코드 has constant value ""Constant
건별구분코드 has constant value ""Constant
사업장이전여부 has constant value ""Constant
O2O보증여부 has constant value ""Constant
운전자금상세코드 has constant value ""Constant
Dataset has 77 (15.4%) duplicate rowsDuplicates
홈페이지모바일구분코드 is highly overall correlated with 오전오후구분코드 and 1 other fieldsHigh correlation
상담방법구분코드 is highly overall correlated with 오전오후구분코드 and 2 other fieldsHigh correlation
오전오후구분코드 is highly overall correlated with 상담방법구분코드 and 2 other fieldsHigh correlation
신청서이전관할부점코드 is highly overall correlated with 홈페이지보증종류코드High correlation
보증신청자금용도코드 is highly overall correlated with 시설자금상세코드High correlation
홈페이지보증종류코드 is highly overall correlated with 신청서이전관할부점코드High correlation
시설자금상세코드 is highly overall correlated with 보증신청자금용도코드High correlation
1년이내대표자변경여부 is highly overall correlated with 오전오후구분코드 and 1 other fieldsHigh correlation
신청서이전관할부점코드 is highly imbalanced (89.9%)Imbalance
기업거래구분코드 is highly imbalanced (71.4%)Imbalance
홈페이지보증종류코드 is highly imbalanced (92.8%)Imbalance
시설자금상세코드 is highly imbalanced (78.9%)Imbalance
사업장주소통합ID has 500 (100.0%) missing valuesMissing
상담전화번호 has 500 (100.0%) missing valuesMissing
사업장주소통합ID is an unsupported type, check if it needs cleaning or further analysisUnsupported
상담전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 01:29:05.277838
Analysis finished2023-12-12 01:29:07.385359
Duration2.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

이력일련번호
Real number (ℝ)

Distinct11
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.194
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T10:29:07.449192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile6
Maximum13
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9088351
Coefficient of variation (CV)0.8700251
Kurtosis3.137169
Mean2.194
Median Absolute Deviation (MAD)0
Skewness1.7638556
Sum1097
Variance3.6436513
MonotonicityNot monotonic
2023-12-12T10:29:07.587011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 305
61.0%
2 52
 
10.4%
3 38
 
7.6%
5 37
 
7.4%
4 28
 
5.6%
6 21
 
4.2%
7 10
 
2.0%
8 5
 
1.0%
9 2
 
0.4%
13 1
 
0.2%
ValueCountFrequency (%)
1 305
61.0%
2 52
 
10.4%
3 38
 
7.6%
4 28
 
5.6%
5 37
 
7.4%
6 21
 
4.2%
7 10
 
2.0%
8 5
 
1.0%
9 2
 
0.4%
10 1
 
0.2%
ValueCountFrequency (%)
13 1
 
0.2%
10 1
 
0.2%
9 2
 
0.4%
8 5
 
1.0%
7 10
 
2.0%
6 21
4.2%
5 37
7.4%
4 28
5.6%
3 38
7.6%
2 52
10.4%

업무구분코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
G 500
100.0%

Length

2023-12-12T10:29:07.711656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:07.809664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 500
100.0%

신청서이전관할부점코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct14
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
480 
TAW
 
3
TQA
 
2
TQL
 
2
TCE
 
2
Other values (9)
 
11

Length

Max length3
Median length1
Mean length1.08
Min length1

Unique

Unique7 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
480
96.0%
TAW 3
 
0.6%
TQA 2
 
0.4%
TQL 2
 
0.4%
TCE 2
 
0.4%
TBK 2
 
0.4%
TPI 2
 
0.4%
TPP 1
 
0.2%
TAH 1
 
0.2%
THO 1
 
0.2%
Other values (4) 4
 
0.8%

Length

2023-12-12T10:29:07.936020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
taw 3
15.0%
tqa 2
10.0%
tql 2
10.0%
tce 2
10.0%
tbk 2
10.0%
tpi 2
10.0%
tpp 1
 
5.0%
tah 1
 
5.0%
tho 1
 
5.0%
thu 1
 
5.0%
Other values (3) 3
15.0%

신청서배정팀코드
Categorical

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
166 
2
127 
94 
3
74 
4
25 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row3
3rd row1
4th row3
5th row2

Common Values

ValueCountFrequency (%)
1 166
33.2%
2 127
25.4%
94
18.8%
3 74
14.8%
4 25
 
5.0%
9 14
 
2.8%

Length

2023-12-12T10:29:08.066295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:08.175027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 166
40.9%
2 127
31.3%
3 74
18.2%
4 25
 
6.2%
9 14
 
3.4%

기업거래구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
475 
2
 
25

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 (%)
1 475
95.0%
2 25
 
5.0%

Length

2023-12-12T10:29:08.282354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:08.390280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 475
95.0%
2 25
 
5.0%

보증신청구분코드
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

2023-12-12T10:29:08.486063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:08.581964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

신청서진행상태코드
Real number (ℝ)

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.734
Minimum1
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T10:29:08.658999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q38
95-th percentile90
Maximum90
Range89
Interquartile range (IQR)5

Descriptive statistics

Standard deviation26.148551
Coefficient of variation (CV)1.9039283
Kurtosis4.6339559
Mean13.734
Median Absolute Deviation (MAD)3
Skewness2.5499603
Sum6867
Variance683.74674
MonotonicityNot monotonic
2023-12-12T10:29:08.764717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
8 167
33.4%
3 99
19.8%
1 98
19.6%
6 70
14.0%
90 52
 
10.4%
2 10
 
2.0%
4 4
 
0.8%
ValueCountFrequency (%)
1 98
19.6%
2 10
 
2.0%
3 99
19.8%
4 4
 
0.8%
6 70
14.0%
8 167
33.4%
90 52
 
10.4%
ValueCountFrequency (%)
90 52
 
10.4%
8 167
33.4%
6 70
14.0%
4 4
 
0.8%
3 99
19.8%
2 10
 
2.0%
1 98
19.6%

건별구분코드
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

2023-12-12T10:29:08.875388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:08.980298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

보증신청자금용도코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
374 
85 
2
41 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 374
74.8%
85
 
17.0%
2 41
 
8.2%

Length

2023-12-12T10:29:09.087934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:09.192017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 374
90.1%
2 41
 
9.9%

홈페이지보증종류코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
493 
5
 
6
8
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 493
98.6%
5 6
 
1.2%
8 1
 
0.2%

Length

2023-12-12T10:29:09.307146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:09.466968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 493
98.6%
5 6
 
1.2%
8 1
 
0.2%

사업장주소통합ID
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

사업장이전여부
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

2023-12-12T10:29:09.608742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:09.739023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

오전오후구분코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
362 
1
138 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
362
72.4%
1 138
 
27.6%

Length

2023-12-12T10:29:09.855804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:09.969133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 138
100.0%

상담방법구분코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
362 
2
138 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
362
72.4%
2 138
 
27.6%

Length

2023-12-12T10:29:10.093858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:10.207481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 138
100.0%

상담전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

O2O보증여부
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

2023-12-12T10:29:10.322697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:10.430570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

운전자금상세코드
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

2023-12-12T10:29:10.551996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:10.677933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

시설자금상세코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
462 
202
 
12
205
 
12
201
 
7
203
 
6

Length

Max length3
Median length1
Mean length1.152
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
462
92.4%
202 12
 
2.4%
205 12
 
2.4%
201 7
 
1.4%
203 6
 
1.2%
204 1
 
0.2%

Length

2023-12-12T10:29:10.851606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:10.996485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202 12
31.6%
205 12
31.6%
201 7
18.4%
203 6
15.8%
204 1
 
2.6%

1년이내대표자변경여부
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
N
242 
228 
Y
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
N 242
48.4%
228
45.6%
Y 30
 
6.0%

Length

2023-12-12T10:29:11.140860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:11.245241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
n 242
89.0%
y 30
 
11.0%

홈페이지모바일구분코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
355 
138 
2
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 355
71.0%
138
 
27.6%
2 7
 
1.4%

Length

2023-12-12T10:29:11.351444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:29:11.464406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 355
98.1%
2 7
 
1.9%

Interactions

2023-12-12T10:29:06.413066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:06.212074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:06.505816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:06.326487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:29:11.557461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이력일련번호신청서이전관할부점코드신청서배정팀코드기업거래구분코드신청서진행상태코드보증신청자금용도코드홈페이지보증종류코드오전오후구분코드상담방법구분코드시설자금상세코드1년이내대표자변경여부홈페이지모바일구분코드
이력일련번호1.0000.2850.1820.0000.1760.5100.0000.1990.1990.0000.4900.258
신청서이전관할부점코드0.2851.0000.0000.0000.2990.2150.8340.2990.2990.1790.0000.211
신청서배정팀코드0.1820.0001.0000.1310.2120.4360.4650.1790.1790.0140.2920.299
기업거래구분코드0.0000.0000.1311.0000.3590.0000.0780.1930.1930.0000.0800.080
신청서진행상태코드0.1760.2990.2120.3591.0000.0850.0860.3060.3060.0000.1870.122
보증신청자금용도코드0.5100.2150.4360.0000.0851.0000.0000.1960.1960.9270.6980.538
홈페이지보증종류코드0.0000.8340.4650.0780.0860.0001.0000.0230.0230.0000.0000.000
오전오후구분코드0.1990.2990.1790.1930.3060.1960.0231.0001.0000.2040.4311.000
상담방법구분코드0.1990.2990.1790.1930.3060.1960.0231.0001.0000.2040.4311.000
시설자금상세코드0.0000.1790.0140.0000.0000.9270.0000.2040.2041.0000.3500.197
1년이내대표자변경여부0.4900.0000.2920.0800.1870.6980.0000.4310.4310.3501.0000.812
홈페이지모바일구분코드0.2580.2110.2990.0800.1220.5380.0001.0001.0000.1970.8121.000
2023-12-12T10:29:11.784118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기업거래구분코드홈페이지보증종류코드시설자금상세코드1년이내대표자변경여부홈페이지모바일구분코드신청서배정팀코드신청서이전관할부점코드보증신청자금용도코드상담방법구분코드오전오후구분코드
기업거래구분코드1.0000.1290.0000.1330.1330.0940.0000.0000.1240.124
홈페이지보증종류코드0.1291.0000.0000.0000.0000.2160.6900.0000.0380.038
시설자금상세코드0.0000.0001.0000.1540.0820.0020.0870.6720.1460.146
1년이내대표자변경여부0.1330.0000.1541.0000.4800.1260.0000.3550.6720.672
홈페이지모바일구분코드0.1330.0000.0820.4801.0000.1290.1180.2270.9990.999
신청서배정팀코드0.0940.2160.0020.1260.1291.0000.0000.2000.1280.128
신청서이전관할부점코드0.0000.6900.0870.0000.1180.0001.0000.1200.2310.231
보증신청자금용도코드0.0000.0000.6720.3550.2270.2000.1201.0000.3210.321
상담방법구분코드0.1240.0380.1460.6720.9990.1280.2310.3211.0000.995
오전오후구분코드0.1240.0380.1460.6720.9990.1280.2310.3210.9951.000
2023-12-12T10:29:11.969488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이력일련번호신청서진행상태코드신청서이전관할부점코드신청서배정팀코드기업거래구분코드보증신청자금용도코드홈페이지보증종류코드오전오후구분코드상담방법구분코드시설자금상세코드1년이내대표자변경여부홈페이지모바일구분코드
이력일련번호1.000-0.1840.1160.0950.0000.2730.0000.1990.1990.0000.2440.118
신청서진행상태코드-0.1841.0000.2310.1520.2330.1410.1420.1980.1980.0000.3070.201
신청서이전관할부점코드0.1160.2311.0000.0000.0000.1200.6900.2310.2310.0870.0000.118
신청서배정팀코드0.0950.1520.0001.0000.0940.2000.2160.1280.1280.0020.1260.129
기업거래구분코드0.0000.2330.0000.0941.0000.0000.1290.1240.1240.0000.1330.133
보증신청자금용도코드0.2730.1410.1200.2000.0001.0000.0000.3210.3210.6720.3550.227
홈페이지보증종류코드0.0000.1420.6900.2160.1290.0001.0000.0380.0380.0000.0000.000
오전오후구분코드0.1990.1980.2310.1280.1240.3210.0381.0000.9950.1460.6720.999
상담방법구분코드0.1990.1980.2310.1280.1240.3210.0380.9951.0000.1460.6720.999
시설자금상세코드0.0000.0000.0870.0020.0000.6720.0000.1460.1461.0000.1540.082
1년이내대표자변경여부0.2440.3070.0000.1260.1330.3550.0000.6720.6720.1541.0000.480
홈페이지모바일구분코드0.1180.2010.1180.1290.1330.2270.0000.9990.9990.0820.4801.000

Missing values

2023-12-12T10:29:06.658308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:29:07.282130image/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

이력일련번호업무구분코드신청서이전관할부점코드신청서배정팀코드기업거래구분코드보증신청구분코드신청서진행상태코드건별구분코드보증신청자금용도코드홈페이지보증종류코드사업장주소통합ID사업장이전여부오전오후구분코드상담방법구분코드상담전화번호O2O보증여부운전자금상세코드시설자금상세코드1년이내대표자변경여부홈페이지모바일구분코드
01G111111<NA><NA>Y1
11G311811<NA>12<NA>
21G1113111<NA><NA>N1
36G3118111<NA>12<NA>
41G2118111<NA><NA>N1
53G2113111<NA><NA>N1
61G1113111<NA><NA>N1
71G1113121<NA><NA>203N1
81G111815<NA><NA>1
91G211811<NA>12<NA>
이력일련번호업무구분코드신청서이전관할부점코드신청서배정팀코드기업거래구분코드보증신청구분코드신청서진행상태코드건별구분코드보증신청자금용도코드홈페이지보증종류코드사업장주소통합ID사업장이전여부오전오후구분코드상담방법구분코드상담전화번호O2O보증여부운전자금상세코드시설자금상세코드1년이내대표자변경여부홈페이지모바일구분코드
4901G11190111<NA><NA>N1
4911G31190111<NA><NA>N1
4921G12190111<NA><NA>N1
4931G31190111<NA><NA>N1
4941G4213111<NA><NA>N1
4952G111111<NA>12<NA>
4961G111811<NA>12<NA>
4971G111111<NA>12<NA>
4981G4118111<NA>12<NA>
4995G311811<NA><NA>1

Duplicate rows

Most frequently occurring

이력일련번호업무구분코드신청서이전관할부점코드신청서배정팀코드기업거래구분코드보증신청구분코드신청서진행상태코드건별구분코드보증신청자금용도코드홈페이지보증종류코드사업장이전여부오전오후구분코드상담방법구분코드O2O보증여부운전자금상세코드시설자금상세코드1년이내대표자변경여부홈페이지모바일구분코드# duplicates
462G111111N122
01G111111N116
251G2118111N115
151G1118111N113
71G1113111N111
171G11190111N110
21G111111129
131G11181119
161G1118111129
231G211811129