Overview

Dataset statistics

Number of variables57
Number of observations30
Missing cells425
Missing cells (%)24.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.0 KiB
Average record size in memory479.4 B

Variable types

Numeric6
Categorical19
Text9
Boolean9
DateTime5
Unsupported9

Dataset

Description샘플 데이터
Author경기도일자리재단
URLhttps://www.bigdata-region.kr/#/dataset/6d97268b-e314-4197-a66d-baaf0012eba1

Alerts

지번주소 has constant value ""Constant
3D업종명 has constant value ""Constant
사용여부 has constant value ""Constant
삭제여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
자동차본인명 is highly imbalanced (58.2%)Imbalance
상가보증금액 is highly imbalanced (78.9%)Imbalance
기타금액 is highly imbalanced (78.9%)Imbalance
3D업종명 has 29 (96.7%) missing valuesMissing
근무처지번상세주소 has 26 (86.7%) missing valuesMissing
부채상환본인내용 has 19 (63.3%) missing valuesMissing
부채상환가구원내용 has 19 (63.3%) missing valuesMissing
재신청일시 has 21 (70.0%) missing valuesMissing
거절사유내용 has 23 (76.7%) missing valuesMissing
거절일자 has 18 (60.0%) missing valuesMissing
신청경로명 has 30 (100.0%) missing valuesMissing
가산점수값 has 30 (100.0%) missing valuesMissing
직업유형명 has 30 (100.0%) missing valuesMissing
기업유형명 has 30 (100.0%) missing valuesMissing
건강보험명 has 30 (100.0%) missing valuesMissing
건강보험료월1금액 has 30 (100.0%) missing valuesMissing
건강보험료월2금액 has 30 (100.0%) missing valuesMissing
건강보험료월3금액 has 30 (100.0%) missing valuesMissing
건강보험료평균금액 has 30 (100.0%) missing valuesMissing
청년통장정보번호 has unique valuesUnique
우편번호 has unique valuesUnique
근무처도로명상세주소 has unique valuesUnique
신청경로명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
가산점수값 is an unsupported type, check if it needs cleaning or further analysisUnsupported
직업유형명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기업유형명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건강보험명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건강보험료월1금액 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건강보험료월2금액 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건강보험료월3금액 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건강보험료평균금액 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부채상환본인대출금액 has 19 (63.3%) zerosZeros
부채상환가구원금액 has 19 (63.3%) zerosZeros
전세월세보증금액 has 16 (53.3%) zerosZeros

Reproduction

Analysis started2023-12-10 13:58:59.685129
Analysis finished2023-12-10 13:59:01.313858
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

청년통장정보번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:01.465896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2023-12-10T22:59:01.717773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

저축목적명
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
주거자금
13 
기타 꿈을 위한 준비자금
6 
결혼자금
6 
대출금상환
5 

Length

Max length13
Median length4
Mean length5.9666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주거자금
2nd row주거자금
3rd row기타 꿈을 위한 준비자금
4th row결혼자금
5th row결혼자금

Common Values

ValueCountFrequency (%)
주거자금 13
43.3%
기타 꿈을 위한 준비자금 6
20.0%
결혼자금 6
20.0%
대출금상환 5
 
16.7%

Length

2023-12-10T22:59:01.986161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:02.137325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주거자금 13
27.1%
기타 6
12.5%
꿈을 6
12.5%
위한 6
12.5%
준비자금 6
12.5%
결혼자금 6
12.5%
대출금상환 5
 
10.4%

연령
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
30
18 
20
10 
40
 
1
50
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row40
2nd row50
3rd row30
4th row20
5th row20

Common Values

ValueCountFrequency (%)
30 18
60.0%
20 10
33.3%
40 1
 
3.3%
50 1
 
3.3%

Length

2023-12-10T22:59:02.396660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:02.577754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 18
60.0%
20 10
33.3%
40 1
 
3.3%
50 1
 
3.3%

성별코드
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
F
22 
M
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowM
3rd rowM
4th rowF
5th rowF

Common Values

ValueCountFrequency (%)
F 22
73.3%
M 8
 
26.7%

Length

2023-12-10T22:59:02.749091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:02.939043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 22
73.3%
m 8
 
26.7%

결혼상태명
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
미혼
24 
기혼
5 
이혼
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row기혼
2nd row기혼
3rd row미혼
4th row미혼
5th row미혼

Common Values

ValueCountFrequency (%)
미혼 24
80.0%
기혼 5
 
16.7%
이혼 1
 
3.3%

Length

2023-12-10T22:59:03.143858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:03.331174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미혼 24
80.0%
기혼 5
 
16.7%
이혼 1
 
3.3%

우편번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15473.633
Minimum1022
Maximum51638
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:04.042718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1022
5-th percentile10461.8
Q112153
median15007.5
Q316692.25
95-th percentile18131.4
Maximum51638
Range50616
Interquartile range (IQR)4539.25

Descriptive statistics

Standard deviation7672.404
Coefficient of variation (CV)0.49583726
Kurtosis18.171043
Mean15473.633
Median Absolute Deviation (MAD)2220.5
Skewness3.5775686
Sum464209
Variance58865783
MonotonicityNot monotonic
2023-12-10T22:59:04.442977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
16630 1
 
3.3%
16439 1
 
3.3%
15531 1
 
3.3%
17361 1
 
3.3%
10893 1
 
3.3%
11812 1
 
3.3%
18144 1
 
3.3%
14583 1
 
3.3%
16537 1
 
3.3%
15290 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1022 1
3.3%
10109 1
3.3%
10893 1
3.3%
11175 1
3.3%
11310 1
3.3%
11341 1
3.3%
11812 1
3.3%
12127 1
3.3%
12231 1
3.3%
12920 1
3.3%
ValueCountFrequency (%)
51638 1
3.3%
18144 1
3.3%
18116 1
3.3%
17931 1
3.3%
17552 1
3.3%
17361 1
3.3%
16988 1
3.3%
16713 1
3.3%
16630 1
3.3%
16583 1
3.3%

지번주소
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
30 

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 (%)
30
100.0%

Length

2023-12-10T22:59:04.751728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:04.949723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

가구원수
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
4
11 
3
10 
2
5 
1
3 
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row4
2nd row4
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
4 11
36.7%
3 10
33.3%
2 5
16.7%
1 3
 
10.0%
5 1
 
3.3%

Length

2023-12-10T22:59:05.171141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:05.458447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 11
36.7%
3 10
33.3%
2 5
16.7%
1 3
 
10.0%
5 1
 
3.3%

경기도거주기간명
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
3년 이상 ~ 4년 미만
21 
6개월 미만
4 
2년 이상 ~ 3년 미만
3 
1년 이상 ~ 2년 미만
 
2

Length

Max length13
Median length13
Mean length12.066667
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6개월 미만
2nd row6개월 미만
3rd row6개월 미만
4th row2년 이상 ~ 3년 미만
5th row3년 이상 ~ 4년 미만

Common Values

ValueCountFrequency (%)
3년 이상 ~ 4년 미만 21
70.0%
6개월 미만 4
 
13.3%
2년 이상 ~ 3년 미만 3
 
10.0%
1년 이상 ~ 2년 미만 2
 
6.7%

Length

2023-12-10T22:59:05.731448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:06.105720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미만 30
21.7%
이상 26
18.8%
26
18.8%
3년 24
17.4%
4년 21
15.2%
2년 5
 
3.6%
6개월 4
 
2.9%
1년 2
 
1.4%

직업명
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
도매 및 소매업
18 
숙박 및 음식점업
9 
운수업
2 
제조업
 
1

Length

Max length9
Median length8
Mean length7.8
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row도매 및 소매업
2nd row숙박 및 음식점업
3rd row제조업
4th row운수업
5th row숙박 및 음식점업

Common Values

ValueCountFrequency (%)
도매 및 소매업 18
60.0%
숙박 및 음식점업 9
30.0%
운수업 2
 
6.7%
제조업 1
 
3.3%

Length

2023-12-10T22:59:06.312818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:06.518626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
및 27
32.1%
도매 18
21.4%
소매업 18
21.4%
숙박 9
 
10.7%
음식점업 9
 
10.7%
운수업 2
 
2.4%
제조업 1
 
1.2%

3D업종명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing29
Missing (%)96.7%
Memory size372.0 B
2023-12-10T22:59:06.728142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters8
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

Unique1 ?
Unique (%)100.0%

Sample

1st row숙박 및 음식점업
ValueCountFrequency (%)
숙박 1
33.3%
및 1
33.3%
음식점업 1
33.3%
2023-12-10T22:59:07.173858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
22.2%
숙 1
11.1%
박 1
11.1%
및 1
11.1%
음 1
11.1%
식 1
11.1%
점 1
11.1%
업 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
77.8%
Space Separator 2
 
22.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
숙 1
14.3%
박 1
14.3%
및 1
14.3%
음 1
14.3%
식 1
14.3%
점 1
14.3%
업 1
14.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
77.8%
Common 2
 
22.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
숙 1
14.3%
박 1
14.3%
및 1
14.3%
음 1
14.3%
식 1
14.3%
점 1
14.3%
업 1
14.3%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
77.8%
ASCII 2
 
22.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
100.0%
Hangul
ValueCountFrequency (%)
숙 1
14.3%
박 1
14.3%
및 1
14.3%
음 1
14.3%
식 1
14.3%
점 1
14.3%
업 1
14.3%

제조업종명
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
22 
사무직
7 
생산직
 
1

Length

Max length4
Median length4
Mean length3.7333333
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row사무직
3rd row<NA>
4th row<NA>
5th row사무직

Common Values

ValueCountFrequency (%)
<NA> 22
73.3%
사무직 7
 
23.3%
생산직 1
 
3.3%

Length

2023-12-10T22:59:07.373023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:07.531127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
73.3%
사무직 7
 
23.3%
생산직 1
 
3.3%

근로형태명
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
상용직(정규직/무기계약직)
24 
임시직(계약직/기간제)
4 
자영업자
 
2

Length

Max length14
Median length14
Mean length13.066667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상용직(정규직/무기계약직)
2nd row상용직(정규직/무기계약직)
3rd row임시직(계약직/기간제)
4th row상용직(정규직/무기계약직)
5th row상용직(정규직/무기계약직)

Common Values

ValueCountFrequency (%)
상용직(정규직/무기계약직) 24
80.0%
임시직(계약직/기간제) 4
 
13.3%
자영업자 2
 
6.7%

Length

2023-12-10T22:59:07.717449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:07.870837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상용직(정규직/무기계약직 24
80.0%
임시직(계약직/기간제 4
 
13.3%
자영업자 2
 
6.7%

근무처경기도지역여부
Boolean

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
True
24 
False
6 
ValueCountFrequency (%)
True 24
80.0%
False 6
 
20.0%
2023-12-10T22:59:08.051917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

근무처우편번호
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12668.367
Minimum4523
Maximum18134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:08.271754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4523
5-th percentile5209.45
Q110610
median14067.5
Q315520.25
95-th percentile17892.8
Maximum18134
Range13611
Interquartile range (IQR)4910.25

Descriptive statistics

Standard deviation4201.7303
Coefficient of variation (CV)0.33167104
Kurtosis-0.63580948
Mean12668.367
Median Absolute Deviation (MAD)2664.5
Skewness-0.68727142
Sum380051
Variance17654538
MonotonicityNot monotonic
2023-12-10T22:59:08.654610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
11403 2
 
6.7%
18134 2
 
6.7%
4523 1
 
3.3%
14655 1
 
3.3%
15552 1
 
3.3%
17316 1
 
3.3%
14093 1
 
3.3%
6149 1
 
3.3%
6035 1
 
3.3%
16499 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
4523 1
3.3%
4534 1
3.3%
6035 1
3.3%
6149 1
3.3%
6198 1
3.3%
6307 1
3.3%
10109 1
3.3%
10422 1
3.3%
11174 1
3.3%
11403 2
6.7%
ValueCountFrequency (%)
18134 2
6.7%
17598 1
3.3%
17316 1
3.3%
17015 1
3.3%
16621 1
3.3%
16499 1
3.3%
15552 1
3.3%
15425 1
3.3%
14723 1
3.3%
14655 1
3.3%

근무처도로명주소
Text

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:59:09.059155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length28.633333
Min length20

Characters and Unicode

Total characters859
Distinct characters67
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)86.7%

Sample

1st row서울 중구 남대문로9길 ** ************
2nd row경기 부천시 부천로 *** ************
3rd row경기 부천시 부천로 ** *****
4th row경기 용인시 기흥구 ********* ***** ************ **
5th row경기 양주시 남면 **** ****** *****
ValueCountFrequency (%)
76
45.8%
경기 24
 
14.5%
서울 6
 
3.6%
부천시 4
 
2.4%
강남구 4
 
2.4%
남면 2
 
1.2%
안양시 2
 
1.2%
수원시 2
 
1.2%
안산시 2
 
1.2%
중구 2
 
1.2%
Other values (37) 42
25.3%
2023-12-10T22:59:09.552425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 431
50.2%
166
 
19.3%
경 27
 
3.1%
기 27
 
3.1%
시 24
 
2.8%
구 15
 
1.7%
로 15
 
1.7%
남 12
 
1.4%
안 8
 
0.9%
천 8
 
0.9%
Other values (57) 126
 
14.7%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 431
50.2%
Other Letter 251
29.2%
Space Separator 166
 
19.3%
Decimal Number 11
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 27
 
10.8%
기 27
 
10.8%
시 24
 
9.6%
구 15
 
6.0%
로 15
 
6.0%
남 12
 
4.8%
안 8
 
3.2%
천 8
 
3.2%
양 7
 
2.8%
서 7
 
2.8%
Other values (49) 101
40.2%
Decimal Number
ValueCountFrequency (%)
5 3
27.3%
1 3
27.3%
6 2
18.2%
9 1
 
9.1%
8 1
 
9.1%
4 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
* 431
100.0%
Space Separator
ValueCountFrequency (%)
166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 608
70.8%
Hangul 251
29.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 27
 
10.8%
기 27
 
10.8%
시 24
 
9.6%
구 15
 
6.0%
로 15
 
6.0%
남 12
 
4.8%
안 8
 
3.2%
천 8
 
3.2%
양 7
 
2.8%
서 7
 
2.8%
Other values (49) 101
40.2%
Common
ValueCountFrequency (%)
* 431
70.9%
166
 
27.3%
5 3
 
0.5%
1 3
 
0.5%
6 2
 
0.3%
9 1
 
0.2%
8 1
 
0.2%
4 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 608
70.8%
Hangul 251
29.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 431
70.9%
166
 
27.3%
5 3
 
0.5%
1 3
 
0.5%
6 2
 
0.3%
9 1
 
0.2%
8 1
 
0.2%
4 1
 
0.2%
Hangul
ValueCountFrequency (%)
경 27
 
10.8%
기 27
 
10.8%
시 24
 
9.6%
구 15
 
6.0%
로 15
 
6.0%
남 12
 
4.8%
안 8
 
3.2%
천 8
 
3.2%
양 7
 
2.8%
서 7
 
2.8%
Other values (49) 101
40.2%

근무처도로명상세주소
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:59:09.874553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length11
Mean length7.3666667
Min length1

Characters and Unicode

Total characters221
Distinct characters109
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row111
2nd row3층
3rd row어딘가
4th row713호 그린바이오(주)
5th row한산리
ValueCountFrequency (%)
3층 4
 
8.2%
4층 3
 
6.1%
5층 2
 
4.1%
리더스센터 2
 
4.1%
김영모 1
 
2.0%
과자점 1
 
2.0%
부천시시설관리공단 1
 
2.0%
ㄴ 1
 
2.0%
대성빌딩 1
 
2.0%
36-27 1
 
2.0%
Other values (32) 32
65.3%
2023-12-10T22:59:10.389756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
 
9.0%
층 10
 
4.5%
스 10
 
4.5%
1 7
 
3.2%
4 7
 
3.2%
3 7
 
3.2%
호 6
 
2.7%
리 6
 
2.7%
터 5
 
2.3%
센 5
 
2.3%
Other values (99) 138
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 153
69.2%
Decimal Number 36
 
16.3%
Space Separator 20
 
9.0%
Uppercase Letter 6
 
2.7%
Close Punctuation 2
 
0.9%
Open Punctuation 2
 
0.9%
Dash Punctuation 1
 
0.5%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 10
 
6.5%
스 10
 
6.5%
호 6
 
3.9%
리 6
 
3.9%
터 5
 
3.3%
센 5
 
3.3%
성 4
 
2.6%
주 3
 
2.0%
산 3
 
2.0%
점 3
 
2.0%
Other values (80) 98
64.1%
Decimal Number
ValueCountFrequency (%)
1 7
19.4%
4 7
19.4%
3 7
19.4%
0 4
11.1%
5 3
8.3%
7 3
8.3%
2 2
 
5.6%
8 2
 
5.6%
6 1
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
F 1
16.7%
B 1
16.7%
N 1
16.7%
G 1
16.7%
Space Separator
ValueCountFrequency (%)
20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 153
69.2%
Common 62
28.1%
Latin 6
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 10
 
6.5%
스 10
 
6.5%
호 6
 
3.9%
리 6
 
3.9%
터 5
 
3.3%
센 5
 
3.3%
성 4
 
2.6%
주 3
 
2.0%
산 3
 
2.0%
점 3
 
2.0%
Other values (80) 98
64.1%
Common
ValueCountFrequency (%)
20
32.3%
1 7
 
11.3%
4 7
 
11.3%
3 7
 
11.3%
0 4
 
6.5%
5 3
 
4.8%
7 3
 
4.8%
2 2
 
3.2%
8 2
 
3.2%
) 2
 
3.2%
Other values (4) 5
 
8.1%
Latin
ValueCountFrequency (%)
C 2
33.3%
F 1
16.7%
B 1
16.7%
N 1
16.7%
G 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 152
68.8%
ASCII 68
30.8%
Compat Jamo 1
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
29.4%
1 7
 
10.3%
4 7
 
10.3%
3 7
 
10.3%
0 4
 
5.9%
5 3
 
4.4%
7 3
 
4.4%
2 2
 
2.9%
C 2
 
2.9%
8 2
 
2.9%
Other values (9) 11
16.2%
Hangul
ValueCountFrequency (%)
층 10
 
6.6%
스 10
 
6.6%
호 6
 
3.9%
리 6
 
3.9%
터 5
 
3.3%
센 5
 
3.3%
성 4
 
2.6%
주 3
 
2.0%
산 3
 
2.0%
점 3
 
2.0%
Other values (79) 97
63.8%
Compat Jamo
ValueCountFrequency (%)
ㄴ 1
100.0%

근무처지번주소
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:59:10.615561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length18.166667
Min length13

Characters and Unicode

Total characters545
Distinct characters69
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)93.3%

Sample

1st row서울 중구 을지로1가 **
2nd row경기 부천시 도당동 ****
3rd row경기 부천시 원미동 *****
4th row경기 용인시 기흥구 ** ****
5th row경기 양주시 남면 *** ***
ValueCountFrequency (%)
45
33.3%
경기 24
17.8%
서울 6
 
4.4%
강남구 4
 
3.0%
부천시 4
 
3.0%
양주시 2
 
1.5%
수원시 2
 
1.5%
오산시 2
 
1.5%
안산시 2
 
1.5%
남면 2
 
1.5%
Other values (39) 42
31.1%
2023-12-10T22:59:11.033888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 169
31.0%
135
24.8%
기 25
 
4.6%
경 24
 
4.4%
시 24
 
4.4%
동 17
 
3.1%
구 15
 
2.8%
남 9
 
1.7%
산 7
 
1.3%
안 7
 
1.3%
Other values (59) 113
20.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 239
43.9%
Other Punctuation 169
31.0%
Space Separator 135
24.8%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 25
 
10.5%
경 24
 
10.0%
시 24
 
10.0%
동 17
 
7.1%
구 15
 
6.3%
남 9
 
3.8%
산 7
 
2.9%
안 7
 
2.9%
양 7
 
2.9%
천 6
 
2.5%
Other values (56) 98
41.0%
Other Punctuation
ValueCountFrequency (%)
* 169
100.0%
Space Separator
ValueCountFrequency (%)
135
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 306
56.1%
Hangul 239
43.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 25
 
10.5%
경 24
 
10.0%
시 24
 
10.0%
동 17
 
7.1%
구 15
 
6.3%
남 9
 
3.8%
산 7
 
2.9%
안 7
 
2.9%
양 7
 
2.9%
천 6
 
2.5%
Other values (56) 98
41.0%
Common
ValueCountFrequency (%)
* 169
55.2%
135
44.1%
1 2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 306
56.1%
Hangul 239
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 169
55.2%
135
44.1%
1 2
 
0.7%
Hangul
ValueCountFrequency (%)
기 25
 
10.5%
경 24
 
10.0%
시 24
 
10.0%
동 17
 
7.1%
구 15
 
6.3%
남 9
 
3.8%
산 7
 
2.9%
안 7
 
2.9%
양 7
 
2.9%
천 6
 
2.5%
Other values (56) 98
41.0%

근무처지번상세주소
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing26
Missing (%)86.7%
Memory size372.0 B
2023-12-10T22:59:11.271935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length6.5
Mean length7
Min length2

Characters and Unicode

Total characters28
Distinct characters25
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

Unique4 ?
Unique (%)100.0%

Sample

1st row어딘가
2nd row713호 그린바이오(주)
3rd row3층 삼성서비스센터
4th row4층
ValueCountFrequency (%)
어딘가 1
16.7%
713호 1
16.7%
그린바이오(주 1
16.7%
3층 1
16.7%
삼성서비스센터 1
16.7%
4층 1
16.7%
2023-12-10T22:59:11.799378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2
 
7.1%
2
 
7.1%
층 2
 
7.1%
어 1
 
3.6%
주 1
 
3.6%
터 1
 
3.6%
센 1
 
3.6%
스 1
 
3.6%
비 1
 
3.6%
서 1
 
3.6%
Other values (15) 15
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19
67.9%
Decimal Number 5
 
17.9%
Space Separator 2
 
7.1%
Close Punctuation 1
 
3.6%
Open Punctuation 1
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 2
 
10.5%
어 1
 
5.3%
주 1
 
5.3%
터 1
 
5.3%
센 1
 
5.3%
스 1
 
5.3%
비 1
 
5.3%
서 1
 
5.3%
성 1
 
5.3%
삼 1
 
5.3%
Other values (8) 8
42.1%
Decimal Number
ValueCountFrequency (%)
3 2
40.0%
1 1
20.0%
7 1
20.0%
4 1
20.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19
67.9%
Common 9
32.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 2
 
10.5%
어 1
 
5.3%
주 1
 
5.3%
터 1
 
5.3%
센 1
 
5.3%
스 1
 
5.3%
비 1
 
5.3%
서 1
 
5.3%
성 1
 
5.3%
삼 1
 
5.3%
Other values (8) 8
42.1%
Common
ValueCountFrequency (%)
3 2
22.2%
2
22.2%
) 1
11.1%
( 1
11.1%
1 1
11.1%
7 1
11.1%
4 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19
67.9%
ASCII 9
32.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 2
22.2%
2
22.2%
) 1
11.1%
( 1
11.1%
1 1
11.1%
7 1
11.1%
4 1
11.1%
Hangul
ValueCountFrequency (%)
층 2
 
10.5%
어 1
 
5.3%
주 1
 
5.3%
터 1
 
5.3%
센 1
 
5.3%
스 1
 
5.3%
비 1
 
5.3%
서 1
 
5.3%
성 1
 
5.3%
삼 1
 
5.3%
Other values (8) 8
42.1%

근무처명
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T22:59:12.166893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length9
Mean length6.1
Min length1

Characters and Unicode

Total characters183
Distinct characters113
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)93.3%

Sample

1st row111
2nd row경기도일자리재단
3rd rowTPLUS
4th row그린바이오(주)
5th row보이트씨앤아이
ValueCountFrequency (%)
주)오산교차로 2
 
5.9%
과자점 1
 
2.9%
gnc/천지인 1
 
2.9%
한일식품 1
 
2.9%
네오카텍 1
 
2.9%
예종세무그룹 1
 
2.9%
논노타올 1
 
2.9%
아주대학교 1
 
2.9%
에스폼알파 1
 
2.9%
에이랜드 1
 
2.9%
Other values (23) 23
67.6%
2023-12-10T22:59:13.008270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 9
 
4.9%
스 8
 
4.4%
( 5
 
2.7%
) 5
 
2.7%
이 5
 
2.7%
로 4
 
2.2%
과 4
 
2.2%
4
 
2.2%
교 4
 
2.2%
오 4
 
2.2%
Other values (103) 131
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 157
85.8%
Uppercase Letter 8
 
4.4%
Open Punctuation 5
 
2.7%
Close Punctuation 5
 
2.7%
Space Separator 4
 
2.2%
Decimal Number 3
 
1.6%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 9
 
5.7%
스 8
 
5.1%
이 5
 
3.2%
로 4
 
2.5%
과 4
 
2.5%
교 4
 
2.5%
오 4
 
2.5%
에 3
 
1.9%
시 3
 
1.9%
센 2
 
1.3%
Other values (90) 111
70.7%
Uppercase Letter
ValueCountFrequency (%)
C 1
12.5%
N 1
12.5%
G 1
12.5%
S 1
12.5%
U 1
12.5%
L 1
12.5%
P 1
12.5%
T 1
12.5%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
1 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 157
85.8%
Common 18
 
9.8%
Latin 8
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 9
 
5.7%
스 8
 
5.1%
이 5
 
3.2%
로 4
 
2.5%
과 4
 
2.5%
교 4
 
2.5%
오 4
 
2.5%
에 3
 
1.9%
시 3
 
1.9%
센 2
 
1.3%
Other values (90) 111
70.7%
Latin
ValueCountFrequency (%)
C 1
12.5%
N 1
12.5%
G 1
12.5%
S 1
12.5%
U 1
12.5%
L 1
12.5%
P 1
12.5%
T 1
12.5%
Common
ValueCountFrequency (%)
( 5
27.8%
) 5
27.8%
4
22.2%
1 3
16.7%
/ 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 156
85.2%
ASCII 26
 
14.2%
Compat Jamo 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 9
 
5.8%
스 8
 
5.1%
이 5
 
3.2%
로 4
 
2.6%
과 4
 
2.6%
교 4
 
2.6%
오 4
 
2.6%
에 3
 
1.9%
시 3
 
1.9%
센 2
 
1.3%
Other values (89) 110
70.5%
ASCII
ValueCountFrequency (%)
( 5
19.2%
) 5
19.2%
4
15.4%
1 3
11.5%
/ 1
 
3.8%
C 1
 
3.8%
N 1
 
3.8%
G 1
 
3.8%
S 1
 
3.8%
U 1
 
3.8%
Other values (3) 3
11.5%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
100.0%

근로기간명
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
6개월 미만
15 
3년 이상 ~ 4년 미만
6 
1년 이상 ~ 2년 미만
4 
2년 이상 ~ 3년 미만
2 
1년 미만
2 

Length

Max length13
Median length9.5
Mean length8.7
Min length5

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row6개월 미만
2nd row6개월 미만
3rd row6개월 미만
4th row6개월 미만
5th row2년 이상 ~ 3년 미만

Common Values

ValueCountFrequency (%)
6개월 미만 15
50.0%
3년 이상 ~ 4년 미만 6
 
20.0%
1년 이상 ~ 2년 미만 4
 
13.3%
2년 이상 ~ 3년 미만 2
 
6.7%
1년 미만 2
 
6.7%
4년 이상 1
 
3.3%

Length

2023-12-10T22:59:13.350419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:13.560182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미만 29
30.2%
6개월 15
15.6%
이상 13
13.5%
12
12.5%
3년 8
 
8.3%
4년 7
 
7.3%
1년 6
 
6.2%
2년 6
 
6.2%

거주상태명
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
자가
14 
2천만원 미만 전월세
8 
무상거주
4 
5천만원이상~1억원미만 전월세
2 
2천만원이상~5천만원미만 전월세
2 

Length

Max length17
Median length16
Mean length6.6
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자가
2nd row5천만원이상~1억원미만 전월세
3rd row자가
4th row2천만원이상~5천만원미만 전월세
5th row무상거주

Common Values

ValueCountFrequency (%)
자가 14
46.7%
2천만원 미만 전월세 8
26.7%
무상거주 4
 
13.3%
5천만원이상~1억원미만 전월세 2
 
6.7%
2천만원이상~5천만원미만 전월세 2
 
6.7%

Length

2023-12-10T22:59:13.772116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:13.984115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자가 14
28.0%
전월세 12
24.0%
2천만원 8
16.0%
미만 8
16.0%
무상거주 4
 
8.0%
5천만원이상~1억원미만 2
 
4.0%
2천만원이상~5천만원미만 2
 
4.0%

자동차본인명
Categorical

IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
차량없음
25 
1;000cc 미만 경차
 
2
1;000cc 이상 ~ 1;600cc 미만
 
1
2;000cc 이상
 
1
1;600cc 이상 ~ 2;000cc 미만
 
1

Length

Max length23
Median length4
Mean length6.0666667
Min length4

Unique

Unique3 ?
Unique (%)10.0%

Sample

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

Common Values

ValueCountFrequency (%)
차량없음 25
83.3%
1;000cc 미만 경차 2
 
6.7%
1;000cc 이상 ~ 1;600cc 미만 1
 
3.3%
2;000cc 이상 1
 
3.3%
1;600cc 이상 ~ 2;000cc 미만 1
 
3.3%

Length

2023-12-10T22:59:14.199452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:14.400937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
차량없음 25
58.1%
미만 4
 
9.3%
1;000cc 3
 
7.0%
이상 3
 
7.0%
경차 2
 
4.7%
2
 
4.7%
1;600cc 2
 
4.7%
2;000cc 2
 
4.7%

자동차가구원명
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
차량없음
16 
2;000cc 이상
5 
1;600cc 이상 ~ 2;000cc 미만
4 
1;000cc 미만 경차
3 
1;000cc 이상 ~ 1;600cc 미만
2 

Length

Max length23
Median length4
Mean length9.7
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row차량없음
2nd row차량없음
3rd row1;000cc 이상 ~ 1;600cc 미만
4th row차량없음
5th row2;000cc 이상

Common Values

ValueCountFrequency (%)
차량없음 16
53.3%
2;000cc 이상 5
 
16.7%
1;600cc 이상 ~ 2;000cc 미만 4
 
13.3%
1;000cc 미만 경차 3
 
10.0%
1;000cc 이상 ~ 1;600cc 미만 2
 
6.7%

Length

2023-12-10T22:59:14.681779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:14.865912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
차량없음 16
24.6%
이상 11
16.9%
2;000cc 9
13.8%
미만 9
13.8%
1;600cc 6
 
9.2%
6
 
9.2%
1;000cc 5
 
7.7%
경차 3
 
4.6%

부채상환본인대출금액
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2040918.2
Minimum0
Maximum23735972
Zeros19
Zeros (%)63.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:15.111787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32100
95-th percentile16412730
Maximum23735972
Range23735972
Interquartile range (IQR)2100

Descriptive statistics

Standard deviation5860791.8
Coefficient of variation (CV)2.8716446
Kurtosis7.7487133
Mean2040918.2
Median Absolute Deviation (MAD)0
Skewness2.9241163
Sum61227547
Variance3.4348881 × 1013
MonotonicityNot monotonic
2023-12-10T22:59:15.276000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 19
63.3%
3000 1
 
3.3%
3600 1
 
3.3%
490 1
 
3.3%
900 1
 
3.3%
15012406 1
 
3.3%
2500 1
 
3.3%
10000 1
 
3.3%
230 1
 
3.3%
23735972 1
 
3.3%
Other values (2) 2
 
6.7%
ValueCountFrequency (%)
0 19
63.3%
230 1
 
3.3%
490 1
 
3.3%
900 1
 
3.3%
2500 1
 
3.3%
3000 1
 
3.3%
3600 1
 
3.3%
10000 1
 
3.3%
4900000 1
 
3.3%
15012406 1
 
3.3%
ValueCountFrequency (%)
23735972 1
3.3%
17558449 1
3.3%
15012406 1
3.3%
4900000 1
3.3%
10000 1
3.3%
3600 1
3.3%
3000 1
3.3%
2500 1
3.3%
900 1
3.3%
490 1
3.3%

부채상환본인내용
Text

MISSING 

Distinct7
Distinct (%)63.6%
Missing19
Missing (%)63.3%
Memory size372.0 B
2023-12-10T22:59:15.503535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.6363636
Min length3

Characters and Unicode

Total characters51
Distinct characters21
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

Unique6 ?
Unique (%)54.5%

Sample

1st row테스트
2nd row생활비;이사비
3rd row학자금대출
4th row전세자금대출
5th row학자금대출
ValueCountFrequency (%)
학자금대출 5
45.5%
테스트 1
 
9.1%
생활비;이사비 1
 
9.1%
전세자금대출 1
 
9.1%
신용대출 1
 
9.1%
햇살론 1
 
9.1%
학자금 1
 
9.1%
2023-12-10T22:59:16.104141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 7
13.7%
금 7
13.7%
대 7
13.7%
출 7
13.7%
학 6
11.8%
비 2
 
3.9%
스 1
 
2.0%
트 1
 
2.0%
생 1
 
2.0%
활 1
 
2.0%
Other values (11) 11
21.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50
98.0%
Other Punctuation 1
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 7
14.0%
금 7
14.0%
대 7
14.0%
출 7
14.0%
학 6
12.0%
비 2
 
4.0%
스 1
 
2.0%
트 1
 
2.0%
생 1
 
2.0%
활 1
 
2.0%
Other values (10) 10
20.0%
Other Punctuation
ValueCountFrequency (%)
; 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50
98.0%
Common 1
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 7
14.0%
금 7
14.0%
대 7
14.0%
출 7
14.0%
학 6
12.0%
비 2
 
4.0%
스 1
 
2.0%
트 1
 
2.0%
생 1
 
2.0%
활 1
 
2.0%
Other values (10) 10
20.0%
Common
ValueCountFrequency (%)
; 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50
98.0%
ASCII 1
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 7
14.0%
금 7
14.0%
대 7
14.0%
출 7
14.0%
학 6
12.0%
비 2
 
4.0%
스 1
 
2.0%
트 1
 
2.0%
생 1
 
2.0%
활 1
 
2.0%
Other values (10) 10
20.0%
ASCII
ValueCountFrequency (%)
; 1
100.0%

부채상환본인부재여부
Boolean

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
True
19 
False
11 
ValueCountFrequency (%)
True 19
63.3%
False 11
36.7%
2023-12-10T22:59:16.411173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

부채상환가구원금액
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10246680
Minimum0
Maximum1.7888889 × 108
Zeros19
Zeros (%)63.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:16.695722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32650
95-th percentile50000000
Maximum1.7888889 × 108
Range1.7888889 × 108
Interquartile range (IQR)2650

Descriptive statistics

Standard deviation34329866
Coefficient of variation (CV)3.3503403
Kurtosis21.525819
Mean10246680
Median Absolute Deviation (MAD)0
Skewness4.4707429
Sum3.0740041 × 108
Variance1.1785397 × 1015
MonotonicityNot monotonic
2023-12-10T22:59:16.899573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 19
63.3%
50000000 2
 
6.7%
1600 1
 
3.3%
4000000 1
 
3.3%
3000 1
 
3.3%
1 1
 
3.3%
6000 1
 
3.3%
10000000 1
 
3.3%
922 1
 
3.3%
178888890 1
 
3.3%
ValueCountFrequency (%)
0 19
63.3%
1 1
 
3.3%
922 1
 
3.3%
1600 1
 
3.3%
3000 1
 
3.3%
6000 1
 
3.3%
4000000 1
 
3.3%
10000000 1
 
3.3%
14500000 1
 
3.3%
50000000 2
 
6.7%
ValueCountFrequency (%)
178888890 1
3.3%
50000000 2
6.7%
14500000 1
3.3%
10000000 1
3.3%
4000000 1
3.3%
6000 1
3.3%
3000 1
3.3%
1600 1
3.3%
922 1
3.3%
1 1
3.3%

부채상환가구원내용
Text

MISSING 

Distinct10
Distinct (%)90.9%
Missing19
Missing (%)63.3%
Memory size372.0 B
2023-12-10T22:59:17.194751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6
Min length2

Characters and Unicode

Total characters66
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)81.8%

Sample

1st row차량 구매 대출
2nd row생활안정자금대출
3rd row대출
4th row주택보증대출
5th row1000000000
ValueCountFrequency (%)
대출 3
21.4%
학자금대출 2
14.3%
차량 1
 
7.1%
구매 1
 
7.1%
생활안정자금대출 1
 
7.1%
주택보증대출 1
 
7.1%
1000000000 1
 
7.1%
집 1
 
7.1%
주택구입대출 1
 
7.1%
10000000 1
 
7.1%
2023-12-10T22:59:17.860922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
24.2%
대 9
13.6%
출 9
13.6%
금 3
 
4.5%
3
 
4.5%
자 3
 
4.5%
학 2
 
3.0%
구 2
 
3.0%
1 2
 
3.0%
주 2
 
3.0%
Other values (14) 15
22.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45
68.2%
Decimal Number 18
 
27.3%
Space Separator 3
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 9
20.0%
출 9
20.0%
금 3
 
6.7%
자 3
 
6.7%
학 2
 
4.4%
구 2
 
4.4%
주 2
 
4.4%
택 2
 
4.4%
보 1
 
2.2%
일 1
 
2.2%
Other values (11) 11
24.4%
Decimal Number
ValueCountFrequency (%)
0 16
88.9%
1 2
 
11.1%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45
68.2%
Common 21
31.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 9
20.0%
출 9
20.0%
금 3
 
6.7%
자 3
 
6.7%
학 2
 
4.4%
구 2
 
4.4%
주 2
 
4.4%
택 2
 
4.4%
보 1
 
2.2%
일 1
 
2.2%
Other values (11) 11
24.4%
Common
ValueCountFrequency (%)
0 16
76.2%
3
 
14.3%
1 2
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45
68.2%
ASCII 21
31.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16
76.2%
3
 
14.3%
1 2
 
9.5%
Hangul
ValueCountFrequency (%)
대 9
20.0%
출 9
20.0%
금 3
 
6.7%
자 3
 
6.7%
학 2
 
4.4%
구 2
 
4.4%
주 2
 
4.4%
택 2
 
4.4%
보 1
 
2.2%
일 1
 
2.2%
Other values (11) 11
24.4%

부채상환가구원부재여부
Boolean

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
True
19 
False
11 
ValueCountFrequency (%)
True 19
63.3%
False 11
36.7%
2023-12-10T22:59:18.202260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

전세월세보증금액
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9686933.5
Minimum0
Maximum70000000
Zeros16
Zeros (%)53.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T22:59:18.498251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q310000000
95-th percentile47412500
Maximum70000000
Range70000000
Interquartile range (IQR)10000000

Descriptive statistics

Standard deviation17533315
Coefficient of variation (CV)1.8099964
Kurtosis4.6338706
Mean9686933.5
Median Absolute Deviation (MAD)0
Skewness2.2343796
Sum2.90608 × 108
Variance3.0741714 × 1014
MonotonicityNot monotonic
2023-12-10T22:59:18.856558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 16
53.3%
5000000 3
 
10.0%
10000000 3
 
10.0%
50000000 1
 
3.3%
5 1
 
3.3%
28908000 1
 
3.3%
30000000 1
 
3.3%
70000000 1
 
3.3%
44250000 1
 
3.3%
9050000 1
 
3.3%
ValueCountFrequency (%)
0 16
53.3%
5 1
 
3.3%
5000000 3
 
10.0%
9050000 1
 
3.3%
10000000 3
 
10.0%
13400000 1
 
3.3%
28908000 1
 
3.3%
30000000 1
 
3.3%
44250000 1
 
3.3%
50000000 1
 
3.3%
ValueCountFrequency (%)
70000000 1
 
3.3%
50000000 1
 
3.3%
44250000 1
 
3.3%
30000000 1
 
3.3%
28908000 1
 
3.3%
13400000 1
 
3.3%
10000000 3
10.0%
9050000 1
 
3.3%
5000000 3
10.0%
5 1
 
3.3%

상가보증금액
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
29 
6
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row0
2nd row0
3rd row6
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 29
96.7%
6 1
 
3.3%

Length

2023-12-10T22:59:19.260880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:19.558956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 29
96.7%
6 1
 
3.3%

기타금액
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
29 
7
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row0
2nd row0
3rd row7
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 29
96.7%
7 1
 
3.3%

Length

2023-12-10T22:59:19.807765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:20.048500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 29
96.7%
7 1
 
3.3%

단계1동의여부
Boolean

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
True
16 
False
14 
ValueCountFrequency (%)
True 16
53.3%
False 14
46.7%
2023-12-10T22:59:20.279428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

단계2동의여부
Boolean

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
True
16 
False
14 
ValueCountFrequency (%)
True 16
53.3%
False 14
46.7%
2023-12-10T22:59:20.556514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

단계3동의여부
Boolean

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
False
16 
True
14 
ValueCountFrequency (%)
False 16
53.3%
True 14
46.7%
2023-12-10T22:59:20.761287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

개인정보사용동의여부
Boolean

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
False
16 
True
14 
ValueCountFrequency (%)
False 16
53.3%
True 14
46.7%
2023-12-10T22:59:20.974893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

개인정보사용동의일시
Date

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-04-12 16:16:00
Maximum2017-04-21 14:39:00
2023-12-10T22:59:21.117884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:21.311450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

신청상태명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
미선발
21 
선발
9 

Length

Max length3
Median length3
Mean length2.7
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미선발
2nd row미선발
3rd row미선발
4th row선발
5th row미선발

Common Values

ValueCountFrequency (%)
미선발 21
70.0%
선발 9
30.0%

Length

2023-12-10T22:59:21.885146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:22.073669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미선발 21
70.0%
선발 9
30.0%

신청일시
Date

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-04-10 07:45:00
Maximum2017-04-21 18:36:00
2023-12-10T22:59:22.246217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:22.476848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

재신청일시
Date

MISSING 

Distinct9
Distinct (%)100.0%
Missing21
Missing (%)70.0%
Memory size372.0 B
Minimum2017-04-11 11:51:00
Maximum2017-04-24 15:56:00
2023-12-10T22:59:22.662358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:22.838381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

거절사유내용
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing23
Missing (%)76.7%
Memory size372.0 B
2023-12-10T22:59:23.158083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length29
Mean length32.428571
Min length9

Characters and Unicode

Total characters227
Distinct characters110
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st row운영 반려 테스트
2nd row주민등록초본(주소변경내역 포함)필요
3rd row신청인 요청(1인 가구 소득인정액 초과/조부;조모 가구원수 불산입)
4th row고용임금확인서에 사업주분의 서명이나 날인이 기재되어 있지 않습니다.
5th row신청취하|(시부모님과 동일주소지 세대분리로 4인가구로 변경 신청 대상이며; 본인 요청에 따라 신청 취하 및 반려처리함.)
ValueCountFrequency (%)
신청 2
 
4.7%
및 2
 
4.7%
운영 1
 
2.3%
세대분리로 1
 
2.3%
변경 1
 
2.3%
대상이며 1
 
2.3%
본인 1
 
2.3%
요청에 1
 
2.3%
따라 1
 
2.3%
취하 1
 
2.3%
Other values (31) 31
72.1%
2023-12-10T22:59:23.739475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
 
16.7%
인 7
 
3.1%
부 6
 
2.6%
청 6
 
2.6%
( 4
 
1.8%
구 4
 
1.8%
가 4
 
1.8%
주 4
 
1.8%
신 4
 
1.8%
) 4
 
1.8%
Other values (100) 146
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 171
75.3%
Space Separator 38
 
16.7%
Other Punctuation 6
 
2.6%
Open Punctuation 4
 
1.8%
Close Punctuation 4
 
1.8%
Decimal Number 3
 
1.3%
Math Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 7
 
4.1%
부 6
 
3.5%
청 6
 
3.5%
구 4
 
2.3%
가 4
 
2.3%
주 4
 
2.3%
신 4
 
2.3%
지 4
 
2.3%
대 3
 
1.8%
요 3
 
1.8%
Other values (90) 126
73.7%
Other Punctuation
ValueCountFrequency (%)
. 3
50.0%
; 2
33.3%
/ 1
 
16.7%
Decimal Number
ValueCountFrequency (%)
4 1
33.3%
1 1
33.3%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
| 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 171
75.3%
Common 56
 
24.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 7
 
4.1%
부 6
 
3.5%
청 6
 
3.5%
구 4
 
2.3%
가 4
 
2.3%
주 4
 
2.3%
신 4
 
2.3%
지 4
 
2.3%
대 3
 
1.8%
요 3
 
1.8%
Other values (90) 126
73.7%
Common
ValueCountFrequency (%)
38
67.9%
( 4
 
7.1%
) 4
 
7.1%
. 3
 
5.4%
; 2
 
3.6%
4 1
 
1.8%
/ 1
 
1.8%
1 1
 
1.8%
| 1
 
1.8%
2 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 171
75.3%
ASCII 56
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38
67.9%
( 4
 
7.1%
) 4
 
7.1%
. 3
 
5.4%
; 2
 
3.6%
4 1
 
1.8%
/ 1
 
1.8%
1 1
 
1.8%
| 1
 
1.8%
2 1
 
1.8%
Hangul
ValueCountFrequency (%)
인 7
 
4.1%
부 6
 
3.5%
청 6
 
3.5%
구 4
 
2.3%
가 4
 
2.3%
주 4
 
2.3%
신 4
 
2.3%
지 4
 
2.3%
대 3
 
1.8%
요 3
 
1.8%
Other values (90) 126
73.7%

거절일자
Date

MISSING 

Distinct9
Distinct (%)75.0%
Missing18
Missing (%)60.0%
Memory size372.0 B
Minimum2017-04-11 00:00:00
Maximum2017-04-27 00:00:00
2023-12-10T22:59:23.928090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:24.102609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

등록일시
Categorical

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2017-04-10 08:52
9 
2017-04-10 08:51
8 
2017-04-10 08:49
4 
2017-04-10 08:48
3 
2017-04-10 08:47
2 
Other values (3)
4 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row2017-04-10 07:45
2nd row2017-04-10 08:27
3rd row2017-04-10 08:47
4th row2017-04-10 08:47
5th row2017-04-10 08:48

Common Values

ValueCountFrequency (%)
2017-04-10 08:52 9
30.0%
2017-04-10 08:51 8
26.7%
2017-04-10 08:49 4
13.3%
2017-04-10 08:48 3
 
10.0%
2017-04-10 08:47 2
 
6.7%
2017-04-10 08:50 2
 
6.7%
2017-04-10 07:45 1
 
3.3%
2017-04-10 08:27 1
 
3.3%

Length

2023-12-10T22:59:24.436122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:24.644214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017-04-10 30
50.0%
08:52 9
 
15.0%
08:51 8
 
13.3%
08:49 4
 
6.7%
08:48 3
 
5.0%
08:47 2
 
3.3%
08:50 2
 
3.3%
07:45 1
 
1.7%
08:27 1
 
1.7%

수정일시
Date

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-04-10 08:51:00
Maximum2021-01-20 17:43:00
2023-12-10T22:59:24.837095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:59:25.033474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size162.0 B
True
30 
ValueCountFrequency (%)
True 30
100.0%
2023-12-10T22:59:25.203764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size162.0 B
False
30 
ValueCountFrequency (%)
False 30
100.0%
2023-12-10T22:59:25.324388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

신청경로명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

가산점수값
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

직업유형명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

기업유형명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

건강보험명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

건강보험료월1금액
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

건강보험료월2금액
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

건강보험료월3금액
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

건강보험료평균금액
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2017-04-10
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017-04-10
2nd row2017-04-10
3rd row2017-04-10
4th row2017-04-10
5th row2017-04-10

Common Values

ValueCountFrequency (%)
2017-04-10 30
100.0%

Length

2023-12-10T22:59:25.509440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:59:25.689926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017-04-10 30
100.0%

Sample

청년통장정보번호저축목적명연령성별코드결혼상태명우편번호지번주소가구원수경기도거주기간명직업명3D업종명제조업종명근로형태명근무처경기도지역여부근무처우편번호근무처도로명주소근무처도로명상세주소근무처지번주소근무처지번상세주소근무처명근로기간명거주상태명자동차본인명자동차가구원명부채상환본인대출금액부채상환본인내용부채상환본인부재여부부채상환가구원금액부채상환가구원내용부채상환가구원부재여부전세월세보증금액상가보증금액기타금액단계1동의여부단계2동의여부단계3동의여부개인정보사용동의여부개인정보사용동의일시신청상태명신청일시재신청일시거절사유내용거절일자등록일시수정일시사용여부삭제여부신청경로명가산점수값직업유형명기업유형명건강보험명건강보험료월1금액건강보험료월2금액건강보험료월3금액건강보험료평균금액데이터기준일자
01주거자금40M기혼1663046개월 미만도매 및 소매업<NA><NA>상용직(정규직/무기계약직)Y4523서울 중구 남대문로9길 ** ************111서울 중구 을지로1가 **<NA>1116개월 미만자가차량없음차량없음0<NA>Y0<NA>Y000YYYY2017-04-13 16:39미선발2017-04-10 07:45<NA><NA>2017-04-272017-04-10 07:452017-04-27 22:49YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
12주거자금50M기혼102246개월 미만숙박 및 음식점업<NA>사무직상용직(정규직/무기계약직)Y14480경기 부천시 부천로 *** ************3층경기 부천시 도당동 ****<NA>경기도일자리재단6개월 미만5천만원이상~1억원미만 전월세차량없음차량없음3000테스트N0<NA>Y5000000000YYYY2017-04-13 18:58미선발2017-04-10 08:27<NA><NA><NA>2017-04-10 08:272017-04-13 18:58YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
23기타 꿈을 위한 준비자금30M미혼5163836개월 미만제조업숙박 및 음식점업<NA>임시직(계약직/기간제)N14570경기 부천시 부천로 ** *****어딘가경기 부천시 원미동 *****어딘가TPLUS6개월 미만자가차량없음1;000cc 이상 ~ 1;600cc 미만0<NA>Y1600차량 구매 대출N567YYYY2017-04-18 09:38미선발2017-04-10 08:482017-04-24 11:40운영 반려 테스트2017-04-112017-04-10 08:472017-08-26 17:57YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
34결혼자금20F미혼1698832년 이상 ~ 3년 미만운수업<NA><NA>상용직(정규직/무기계약직)Y17015경기 용인시 기흥구 ********* ***** ************ **713호 그린바이오(주)경기 용인시 기흥구 ** ****713호 그린바이오(주)그린바이오(주)6개월 미만2천만원이상~5천만원미만 전월세차량없음차량없음0<NA>Y4000000생활안정자금대출N2890800000YYYY2017-04-18 09:48선발2017-04-10 09:132017-04-18 13:55<NA>2017-04-182017-04-10 08:472020-06-01 17:11YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
45결혼자금20F미혼1134133년 이상 ~ 4년 미만숙박 및 음식점업<NA>사무직상용직(정규직/무기계약직)Y11403경기 양주시 남면 **** ****** *****한산리경기 양주시 남면 *** ***<NA>보이트씨앤아이2년 이상 ~ 3년 미만무상거주차량없음2;000cc 이상0<NA>Y0<NA>Y000NNNN2017-04-12 16:16미선발2017-04-10 10:252017-04-11 11:51주민등록초본(주소변경내역 포함)필요2017-04-112017-04-10 08:482017-06-01 16:18YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
56대출금상환30F미혼1131033년 이상 ~ 4년 미만숙박 및 음식점업<NA>사무직상용직(정규직/무기계약직)Y11403경기 양주시 남면 **** ****** *****창성정밀경기 양주시 남면 *** *****<NA>창성정밀3년 이상 ~ 4년 미만2천만원이상~5천만원미만 전월세1;000cc 미만 경차차량없음0<NA>Y0<NA>Y3000000000NNNN2017-04-12 16:16미선발2017-04-10 08:48<NA>신청인 요청(1인 가구 소득인정액 초과/조부;조모 가구원수 불산입)2017-04-202017-04-10 08:482019-04-02 11:08YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
67기타 꿈을 위한 준비자금20F미혼1320213년 이상 ~ 4년 미만도매 및 소매업<NA><NA>임시직(계약직/기간제)Y10422경기 고양시 일산동구 *** **** ****************국립암센터경기 고양시 일산동구 *** ***<NA>국립암센터6개월 미만2천만원 미만 전월세차량없음차량없음0<NA>Y0<NA>Y500000000NNNN2017-04-12 16:16선발2017-04-11 09:56<NA><NA><NA>2017-04-10 08:482020-06-24 10:03YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
78대출금상환20F미혼1811623년 이상 ~ 4년 미만도매 및 소매업<NA><NA>상용직(정규직/무기계약직)Y18134경기 오산시 경기대로 *** *****리더스센터 3층경기 오산시 오산동 *****<NA>(주)오산교차로4년 이상2천만원 미만 전월세차량없음차량없음3600생활비;이사비N0<NA>Y500000000YYYY2017-04-21 14:39미선발2017-04-21 14:39<NA><NA><NA>2017-04-10 08:492017-06-01 17:48YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
89결혼자금20M미혼1658343년 이상 ~ 4년 미만숙박 및 음식점업<NA><NA>상용직(정규직/무기계약직)Y14042경기 안양시 동안구 *** ** ************504호경기 안양시 동안구 *** ***<NA>휴마시스6개월 미만자가차량없음차량없음490학자금대출N3000대출N000NNNN2017-04-12 16:16미선발2017-04-10 09:35<NA>고용임금확인서에 사업주분의 서명이나 날인이 기재되어 있지 않습니다.2017-04-202017-04-10 08:492019-03-29 17:21YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
910주거자금30F기혼1292043년 이상 ~ 4년 미만도매 및 소매업<NA><NA>상용직(정규직/무기계약직)Y13016경기 하남시 서하남로418번길 ** *****(주)파로스경기 하남시 춘궁동 ***<NA>(주)파로스3년 이상 ~ 4년 미만5천만원이상~1억원미만 전월세차량없음1;000cc 미만 경차900전세자금대출N0<NA>Y7000000000NNNN2017-04-12 16:16선발2017-04-10 09:09<NA><NA><NA>2017-04-10 08:492020-06-02 12:50YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
청년통장정보번호저축목적명연령성별코드결혼상태명우편번호지번주소가구원수경기도거주기간명직업명3D업종명제조업종명근로형태명근무처경기도지역여부근무처우편번호근무처도로명주소근무처도로명상세주소근무처지번주소근무처지번상세주소근무처명근로기간명거주상태명자동차본인명자동차가구원명부채상환본인대출금액부채상환본인내용부채상환본인부재여부부채상환가구원금액부채상환가구원내용부채상환가구원부재여부전세월세보증금액상가보증금액기타금액단계1동의여부단계2동의여부단계3동의여부개인정보사용동의여부개인정보사용동의일시신청상태명신청일시재신청일시거절사유내용거절일자등록일시수정일시사용여부삭제여부신청경로명가산점수값직업유형명기업유형명건강보험명건강보험료월1금액건강보험료월2금액건강보험료월3금액건강보험료평균금액데이터기준일자
2021주거자금30F기혼1755233년 이상 ~ 4년 미만숙박 및 음식점업<NA>사무직상용직(정규직/무기계약직)Y17598경기 안성시 미양면 *** ***** *****36-27경기 안성시 미양면 *** ******<NA>에이스팩(주)6개월 미만자가차량없음1;600cc 이상 ~ 2;000cc 미만2500신용대출N6000주택구입대출N000YYYY2017-04-18 15:45미선발2017-04-18 16:27<NA><NA><NA>2017-04-10 08:512017-06-01 17:56YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
2122기타 꿈을 위한 준비자금20M미혼1223123년 이상 ~ 4년 미만도매 및 소매업<NA><NA>자영업자N4534서울 중구 명동길 *** ******에이랜드 4층서울 중구 명동1가 ****<NA>에이랜드6개월 미만2천만원 미만 전월세1;000cc 이상 ~ 1;600cc 미만차량없음0<NA>Y1000000010000000N500000000YYYY2017-04-20 15:07미선발2017-04-20 15:082017-04-20 20:41보건복지부 추진 자산형성지원사업(희망키움2) 대상가구2017-04-212017-04-10 08:522017-04-21 12:45YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
2223결혼자금30M미혼1529033년 이상 ~ 4년 미만숙박 및 음식점업<NA>사무직상용직(정규직/무기계약직)Y15425경기 안산시 단원구 *** *** ***************에스폼알파경기 안산시 단원구 *** ****<NA>에스폼알파1년 미만자가2;000cc 이상2;000cc 이상10000햇살론N0<NA>Y000NNNN2017-04-12 16:16미선발2017-04-10 08:52<NA><NA><NA>2017-04-10 08:522017-04-10 08:52YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
2324대출금상환30F미혼1653743년 이상 ~ 4년 미만도매 및 소매업<NA><NA>임시직(계약직/기간제)Y16499경기 수원시 영통구 **** *** ***********다산관 314호경기 수원시 영통구 *** * ***<NA>아주대학교1년 미만2천만원 미만 전월세차량없음1;000cc 미만 경차230학자금대출N922학자금대출N1000000000NNNN2017-04-12 16:16미선발2017-04-10 09:02<NA><NA><NA>2017-04-10 08:522017-06-01 16:40YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
2425기타 꿈을 위한 준비자금30F미혼1458353년 이상 ~ 4년 미만도매 및 소매업<NA><NA>상용직(정규직/무기계약직)N6035서울 강남구 강남대로156길 ** *****4층서울 강남구 신사동 *****4층논노타올6개월 미만자가차량없음1;600cc 이상 ~ 2;000cc 미만0<NA>Y178888890일반대출N000YYNN2017-04-12 16:16미선발2017-04-10 09:18<NA><NA><NA>2017-04-10 08:522017-06-01 16:54YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
2526주거자금30F미혼1814413년 이상 ~ 4년 미만숙박 및 음식점업<NA>사무직상용직(정규직/무기계약직)Y18134경기 오산시 경기대로 *** *****리더스센터 오산교차로경기 오산시 오산동 *****<NA>(주)오산교차로3년 이상 ~ 4년 미만자가1;000cc 미만 경차차량없음0<NA>Y0<NA>Y000NNNN2017-04-12 16:16미선발2017-04-12 12:09<NA><NA><NA>2017-04-10 08:522017-06-01 17:48YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
2627대출금상환30F미혼1181233년 이상 ~ 4년 미만도매 및 소매업<NA><NA>상용직(정규직/무기계약직)N6149서울 강남구 선릉로 *** *************204호서울 강남구 역삼동 *****<NA>예종세무그룹2년 이상 ~ 3년 미만무상거주차량없음차량없음23735972학자금대출N14500000학자금대출N000NNNN2017-04-12 16:16선발2017-04-10 10:42<NA><NA><NA>2017-04-10 08:522020-06-02 17:49YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
2728결혼자금30M미혼1089343년 이상 ~ 4년 미만도매 및 소매업<NA><NA>상용직(정규직/무기계약직)Y14093경기 안양시 만안구 *** *** *****경기벤처연성대학센터 804호 네오카텍경기 안양시 만안구 *** *****<NA>네오카텍1년 이상 ~ 2년 미만2천만원 미만 전월세1;600cc 이상 ~ 2;000cc 미만2;000cc 이상17558449학자금대출N0<NA>Y1000000000YYYY2017-04-18 17:03선발2017-04-18 17:05<NA><NA><NA>2017-04-10 08:522020-06-22 13:59YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
2829대출금상환30M미혼1736121년 이상 ~ 2년 미만숙박 및 음식점업<NA>사무직상용직(정규직/무기계약직)Y17316경기 이천시 백사면 *** ****** *****한일식품경기 이천시 백사면 *** ***<NA>한일식품6개월 미만2천만원 미만 전월세차량없음차량없음4900000학자금N0<NA>Y1340000000YYYY2017-04-13 12:15선발2017-04-11 13:232017-04-13 12:15<NA>2017-04-132017-04-10 08:522020-06-01 14:57YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10
2930기타 꿈을 위한 준비자금20F미혼1553133년 이상 ~ 4년 미만도매 및 소매업<NA><NA>임시직(계약직/기간제)Y15552경기 안산시 상록구 *** *** *****4층 강남수내과경기 안산시 상록구 *** *****<NA>강남수내과3년 이상 ~ 4년 미만자가차량없음1;600cc 이상 ~ 2;000cc 미만0<NA>Y0<NA>Y000NNNN2017-04-12 16:16미선발2017-04-10 08:52<NA><NA><NA>2017-04-10 08:522017-04-11 11:14YN<NA><NA><NA><NA><NA><NA><NA><NA><NA>2017-04-10