Overview

Dataset statistics

Number of variables67
Number of observations30
Missing cells127
Missing cells (%)6.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.8 KiB
Average record size in memory573.4 B

Variable types

Numeric16
Categorical32
Boolean4
Text8
DateTime6
Unsupported1

Dataset

Description샘플 데이터
Author경기도일자리재단
URLhttps://www.bigdata-region.kr/#/dataset/9a362cbc-33a7-49aa-a0b0-eeefed39bd12

Alerts

재산소득금액 has constant value ""Constant
기초공제금액 has constant value ""Constant
통합조사담당자확인명 has constant value ""Constant
시도담당자확인명 has constant value ""Constant
시도담당자확인일자 has constant value ""Constant
비고내용 has constant value ""Constant
삭제여부 has constant value ""Constant
근무소재지점수 has constant value ""Constant
사업소득금액 is highly imbalanced (73.5%)Imbalance
기타소득금액 is highly imbalanced (68.6%)Imbalance
가구특성해당여부 is highly imbalanced (64.7%)Imbalance
차량보유상태명 is highly imbalanced (64.1%)Imbalance
가구특성점수 is highly imbalanced (64.7%)Imbalance
차량보유상태점수 is highly imbalanced (64.1%)Imbalance
가산기준충족점수 is highly imbalanced (73.5%)Imbalance
주거용소득환산액 is highly imbalanced (64.1%)Imbalance
일반재산금액 is highly imbalanced (64.1%)Imbalance
일반재산소득환산액 is highly imbalanced (78.9%)Imbalance
읍면동담당자확인명 is highly imbalanced (78.9%)Imbalance
지원대상여부 is highly imbalanced (53.1%)Imbalance
결혼상태명 is highly imbalanced (51.4%)Imbalance
자동차본인명 is highly imbalanced (64.1%)Imbalance
가산기준충족명 has 28 (93.3%) missing valuesMissing
예비선발순위 has 16 (53.3%) missing valuesMissing
읍면동담당자확인일시 has 1 (3.3%) missing valuesMissing
비고내용 has 29 (96.7%) missing valuesMissing
3D업종명 has 30 (100.0%) missing valuesMissing
근무처지번상세주소 has 23 (76.7%) missing valuesMissing
선발정보번호 has unique valuesUnique
우편번호 has unique valuesUnique
근무처도로명상세주소 has unique valuesUnique
3D업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
근로소득금액 has 1 (3.3%) zerosZeros
실제소득금액 has 1 (3.3%) zerosZeros
중위소득결과값 has 1 (3.3%) zerosZeros
중위소득결과점수 has 8 (26.7%) zerosZeros
부채금액 has 18 (60.0%) zerosZeros
주거용재산금액 has 5 (16.7%) zerosZeros
자동차재산금액 has 14 (46.7%) zerosZeros
자동차재산소득환산액 has 24 (80.0%) zerosZeros
재산소득환산금액 has 24 (80.0%) zerosZeros
소득인정금액 has 1 (3.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:19:48.629873
Analysis finished2023-12-10 14:19:49.865064
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

선발정보번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.333333
Minimum4
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:49.927232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5.9
Q114.75
median26.5
Q335.5
95-th percentile49.65
Maximum52
Range48
Interquartile range (IQR)20.75

Descriptive statistics

Standard deviation14.025428
Coefficient of variation (CV)0.53261121
Kurtosis-0.87824833
Mean26.333333
Median Absolute Deviation (MAD)10
Skewness0.16725803
Sum790
Variance196.71264
MonotonicityStrictly increasing
2023-12-10T23:19:50.052619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4 1
 
3.3%
28 1
 
3.3%
52 1
 
3.3%
51 1
 
3.3%
48 1
 
3.3%
47 1
 
3.3%
43 1
 
3.3%
39 1
 
3.3%
37 1
 
3.3%
36 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
4 1
3.3%
5 1
3.3%
7 1
3.3%
8 1
3.3%
10 1
3.3%
11 1
3.3%
13 1
3.3%
14 1
3.3%
17 1
3.3%
18 1
3.3%
ValueCountFrequency (%)
52 1
3.3%
51 1
3.3%
48 1
3.3%
47 1
3.3%
43 1
3.3%
39 1
3.3%
37 1
3.3%
36 1
3.3%
34 1
3.3%
33 1
3.3%

근로소득금액
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2466527.5
Minimum0
Maximum6011728
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:50.172596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1135628.1
Q11582500
median2205666.5
Q33286069
95-th percentile4120987.9
Maximum6011728
Range6011728
Interquartile range (IQR)1703569

Descriptive statistics

Standard deviation1227067.6
Coefficient of variation (CV)0.4974879
Kurtosis1.0331547
Mean2466527.5
Median Absolute Deviation (MAD)841143
Skewness0.67222815
Sum73995826
Variance1.5056949 × 1012
MonotonicityNot monotonic
2023-12-10T23:19:50.324846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1400000 2
 
6.7%
3736315 1
 
3.3%
1666666 1
 
3.3%
1360000 1
 
3.3%
1560000 1
 
3.3%
3819231 1
 
3.3%
0 1
 
3.3%
3280279 1
 
3.3%
2468766 1
 
3.3%
1650000 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0 1
3.3%
1001142 1
3.3%
1300000 1
3.3%
1360000 1
3.3%
1369047 1
3.3%
1400000 2
6.7%
1560000 1
3.3%
1650000 1
3.3%
1666666 1
3.3%
1680000 1
3.3%
ValueCountFrequency (%)
6011728 1
3.3%
4367880 1
3.3%
3819231 1
3.3%
3736315 1
3.3%
3727619 1
3.3%
3357434 1
3.3%
3325000 1
3.3%
3287999 1
3.3%
3280279 1
3.3%
3225000 1
3.3%

사업소득금액
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
28 
125000
 
1
825000
 
1

Length

Max length6
Median length1
Mean length1.3333333
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
0 28
93.3%
125000 1
 
3.3%
825000 1
 
3.3%

Length

2023-12-10T23:19:50.488474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:50.665884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 28
93.3%
125000 1
 
3.3%
825000 1
 
3.3%

재산소득금액
Categorical

CONSTANT 

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

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 30
100.0%

Length

2023-12-10T23:19:50.828920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:50.922477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

기타소득금액
Categorical

IMBALANCE 

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
27 
869375
 
1
1304350
 
1
2555080
 
1

Length

Max length7
Median length1
Mean length1.5666667
Min length1

Unique

Unique3 ?
Unique (%)10.0%

Sample

1st row0
2nd row0
3rd row0
4th row869375
5th row0

Common Values

ValueCountFrequency (%)
0 27
90.0%
869375 1
 
3.3%
1304350 1
 
3.3%
2555080 1
 
3.3%

Length

2023-12-10T23:19:51.031227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:51.162080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 27
90.0%
869375 1
 
3.3%
1304350 1
 
3.3%
2555080 1
 
3.3%

실제소득금액
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2655821
Minimum0
Maximum6011728
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:51.285409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1135628.1
Q11657500
median2731498
Q33456371
95-th percentile4302119.7
Maximum6011728
Range6011728
Interquartile range (IQR)1798871

Descriptive statistics

Standard deviation1263184.5
Coefficient of variation (CV)0.47562863
Kurtosis0.35706221
Mean2655821
Median Absolute Deviation (MAD)963809.5
Skewness0.31852201
Sum79674631
Variance1.5956352 × 1012
MonotonicityNot monotonic
2023-12-10T23:19:51.469461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1400000 2
 
6.7%
3736315 1
 
3.3%
4221746 1
 
3.3%
3489350 1
 
3.3%
1560000 1
 
3.3%
3944231 1
 
3.3%
0 1
 
3.3%
3280279 1
 
3.3%
2468766 1
 
3.3%
1650000 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0 1
3.3%
1001142 1
3.3%
1300000 1
3.3%
1369047 1
3.3%
1400000 2
6.7%
1560000 1
3.3%
1650000 1
3.3%
1680000 1
3.3%
1800000 1
3.3%
1850000 1
3.3%
ValueCountFrequency (%)
6011728 1
3.3%
4367880 1
3.3%
4221746 1
3.3%
3944231 1
3.3%
3736315 1
3.3%
3727619 1
3.3%
3514674 1
3.3%
3489350 1
3.3%
3357434 1
3.3%
3325000 1
3.3%
Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
3640915
4467380
1652931
2814449
5293845

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row3640915
2nd row3640915
3rd row1652931
4th row2814449
5th row4467380

Common Values

ValueCountFrequency (%)
3640915 9
30.0%
4467380 9
30.0%
1652931 6
20.0%
2814449 5
16.7%
5293845 1
 
3.3%

Length

2023-12-10T23:19:51.623075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:51.724935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3640915 9
30.0%
4467380 9
30.0%
1652931 6
20.0%
2814449 5
16.7%
5293845 1
 
3.3%

가구특성해당여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
False
28 
True
 
2
ValueCountFrequency (%)
False 28
93.3%
True 2
 
6.7%
2023-12-10T23:19:51.852967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

차량보유상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
차량없음
26 
1;000cc 미만 경차
 
1
1;600cc 이상 ~ 2;000cc 미만
 
1
2;000cc 이상
 
1
1;000cc 이상 ~ 1;600cc 미만
 
1

Length

Max length23
Median length4
Mean length5.7666667
Min length4

Unique

Unique4 ?
Unique (%)13.3%

Sample

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

Common Values

ValueCountFrequency (%)
차량없음 26
86.7%
1;000cc 미만 경차 1
 
3.3%
1;600cc 이상 ~ 2;000cc 미만 1
 
3.3%
2;000cc 이상 1
 
3.3%
1;000cc 이상 ~ 1;600cc 미만 1
 
3.3%

Length

2023-12-10T23:19:52.014978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:52.146605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
차량없음 26
63.4%
미만 3
 
7.3%
이상 3
 
7.3%
1;000cc 2
 
4.9%
1;600cc 2
 
4.9%
2
 
4.9%
2;000cc 2
 
4.9%
경차 1
 
2.4%

가산기준충족명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing28
Missing (%)93.3%
Memory size372.0 B
2023-12-10T23:19:52.287362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row사회적
2nd row생산직
ValueCountFrequency (%)
사회적 1
50.0%
생산직 1
50.0%
2023-12-10T23:19:52.526329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

중위소득결과값
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105.2
Minimum0
Maximum656
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:52.662451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile38
Q161.5
median80.5
Q3108.25
95-th percentile198.55
Maximum656
Range656
Interquartile range (IQR)46.75

Descriptive statistics

Standard deviation112.03983
Coefficient of variation (CV)1.0650174
Kurtosis21.555172
Mean105.2
Median Absolute Deviation (MAD)20
Skewness4.3723909
Sum3156
Variance12552.924
MonotonicityNot monotonic
2023-12-10T23:19:52.782628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
38 2
 
6.7%
75 2
 
6.7%
72 1
 
3.3%
129 1
 
3.3%
117 1
 
3.3%
94 1
 
3.3%
115 1
 
3.3%
0 1
 
3.3%
90 1
 
3.3%
55 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0 1
3.3%
38 2
6.7%
50 1
3.3%
55 1
3.3%
58 1
3.3%
60 1
3.3%
61 1
3.3%
63 1
3.3%
64 1
3.3%
72 1
3.3%
ValueCountFrequency (%)
656 1
3.3%
226 1
3.3%
165 1
3.3%
129 1
3.3%
125 1
3.3%
117 1
3.3%
115 1
3.3%
111 1
3.3%
100 1
3.3%
98 1
3.3%

가구특성점수
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
5
28 
10
 
2

Length

Max length2
Median length1
Mean length1.0666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row10
5th row5

Common Values

ValueCountFrequency (%)
5 28
93.3%
10 2
 
6.7%

Length

2023-12-10T23:19:52.943321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:53.024646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 28
93.3%
10 2
 
6.7%
Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
15.0
22 
11.0
8.0
 
2
13.5
 
1
9.5
 
1

Length

Max length4
Median length4
Mean length3.9
Min length3

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row13.5
2nd row15.0
3rd row15.0
4th row15.0
5th row15.0

Common Values

ValueCountFrequency (%)
15.0 22
73.3%
11.0 4
 
13.3%
8.0 2
 
6.7%
13.5 1
 
3.3%
9.5 1
 
3.3%

Length

2023-12-10T23:19:53.124352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:53.219163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
15.0 22
73.3%
11.0 4
 
13.3%
8.0 2
 
6.7%
13.5 1
 
3.3%
9.5 1
 
3.3%
Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.933333
Minimum10
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:53.311633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q110
median14
Q317
95-th percentile20
Maximum25
Range15
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.2664152
Coefficient of variation (CV)0.30620205
Kurtosis-0.14455559
Mean13.933333
Median Absolute Deviation (MAD)4
Skewness0.86280592
Sum418
Variance18.202299
MonotonicityNot monotonic
2023-12-10T23:19:53.424021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
10 12
40.0%
14 7
23.3%
20 5
16.7%
17 3
 
10.0%
12 2
 
6.7%
25 1
 
3.3%
ValueCountFrequency (%)
10 12
40.0%
12 2
 
6.7%
14 7
23.3%
17 3
 
10.0%
20 5
16.7%
25 1
 
3.3%
ValueCountFrequency (%)
25 1
 
3.3%
20 5
16.7%
17 3
 
10.0%
14 7
23.3%
12 2
 
6.7%
10 12
40.0%
Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
12.0
12 
4.5
10.5
6.0
9.0
 
1

Length

Max length4
Median length4
Mean length3.5333333
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row10.5
2nd row6.0
3rd row12.0
4th row12.0
5th row9.0

Common Values

ValueCountFrequency (%)
12.0 12
40.0%
4.5 9
30.0%
10.5 4
 
13.3%
6.0 4
 
13.3%
9.0 1
 
3.3%

Length

2023-12-10T23:19:53.563560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:53.991024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12.0 12
40.0%
4.5 9
30.0%
10.5 4
 
13.3%
6.0 4
 
13.3%
9.0 1
 
3.3%

차량보유상태점수
Categorical

IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
8.0
26 
6.5
 
1
3.5
 
1
2.0
 
1
5.0
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row8.0
2nd row8.0
3rd row8.0
4th row8.0
5th row8.0

Common Values

ValueCountFrequency (%)
8.0 26
86.7%
6.5 1
 
3.3%
3.5 1
 
3.3%
2.0 1
 
3.3%
5.0 1
 
3.3%

Length

2023-12-10T23:19:54.191035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:54.313294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8.0 26
86.7%
6.5 1
 
3.3%
3.5 1
 
3.3%
2.0 1
 
3.3%
5.0 1
 
3.3%

중위소득결과점수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.266667
Minimum0
Maximum30
Zeros8
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:54.422257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.75
median22.5
Q327
95-th percentile30
Maximum30
Range30
Interquartile range (IQR)22.25

Descriptive statistics

Standard deviation11.808627
Coefficient of variation (CV)0.6464577
Kurtosis-1.0546741
Mean18.266667
Median Absolute Deviation (MAD)6
Skewness-0.77339972
Sum548
Variance139.44368
MonotonicityNot monotonic
2023-12-10T23:19:54.530149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 8
26.7%
30 7
23.3%
24 5
16.7%
19 5
16.7%
27 3
 
10.0%
21 2
 
6.7%
ValueCountFrequency (%)
0 8
26.7%
19 5
16.7%
21 2
 
6.7%
24 5
16.7%
27 3
 
10.0%
30 7
23.3%
ValueCountFrequency (%)
30 7
23.3%
27 3
 
10.0%
24 5
16.7%
21 2
 
6.7%
19 5
16.7%
0 8
26.7%

가산기준충족점수
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
28 
3
 
1
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row3
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 28
93.3%
3 1
 
3.3%
5 1
 
3.3%

Length

2023-12-10T23:19:54.662817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:54.780485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 28
93.3%
3 1
 
3.3%
5 1
 
3.3%

평가점수총점수
Real number (ℝ)

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.716667
Minimum42.5
Maximum87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:54.902175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42.5
5-th percentile42.5
Q157.125
median72
Q378.75
95-th percentile84.55
Maximum87
Range44.5
Interquartile range (IQR)21.625

Descriptive statistics

Standard deviation14.050821
Coefficient of variation (CV)0.20749428
Kurtosis-0.90681139
Mean67.716667
Median Absolute Deviation (MAD)9
Skewness-0.62187629
Sum2031.5
Variance197.42557
MonotonicityNot monotonic
2023-12-10T23:19:55.017213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
70.0 3
 
10.0%
73.5 3
 
10.0%
42.5 3
 
10.0%
81.0 2
 
6.7%
51.0 2
 
6.7%
80.0 1
 
3.3%
79.0 1
 
3.3%
47.5 1
 
3.3%
73.0 1
 
3.3%
46.5 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
42.5 3
10.0%
46.5 1
 
3.3%
47.5 1
 
3.3%
51.0 2
6.7%
56.0 1
 
3.3%
60.5 1
 
3.3%
61.5 1
 
3.3%
67.0 1
 
3.3%
70.0 3
10.0%
71.0 1
 
3.3%
ValueCountFrequency (%)
87.0 1
3.3%
85.0 1
3.3%
84.0 1
3.3%
82.5 1
3.3%
81.0 2
6.7%
80.0 1
3.3%
79.0 1
3.3%
78.0 1
3.3%
77.0 1
3.3%
74.0 1
3.3%

기초공제금액
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
85000000
30 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row85000000
2nd row85000000
3rd row85000000
4th row85000000
5th row85000000

Common Values

ValueCountFrequency (%)
85000000 30
100.0%

Length

2023-12-10T23:19:55.146396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:55.252479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
85000000 30
100.0%

부채금액
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13240793
Minimum0
Maximum1.7888889 × 108
Zeros18
Zeros (%)60.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:55.378236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q313085051
95-th percentile49522981
Maximum1.7888889 × 108
Range1.7888889 × 108
Interquartile range (IQR)13085051

Descriptive statistics

Standard deviation34386631
Coefficient of variation (CV)2.5970221
Kurtosis19.653854
Mean13240793
Median Absolute Deviation (MAD)0
Skewness4.190436
Sum3.9722378 × 108
Variance1.1824404 × 1015
MonotonicityNot monotonic
2023-12-10T23:19:55.523065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 18
60.0%
9494030 1
 
3.3%
15012406 1
 
3.3%
56267239 1
 
3.3%
2309329 1
 
3.3%
178888890 1
 
3.3%
25440233 1
 
3.3%
17558419 1
 
3.3%
14282058 1
 
3.3%
41280000 1
 
3.3%
Other values (3) 3
 
10.0%
ValueCountFrequency (%)
0 18
60.0%
5000 1
 
3.3%
2129000 1
 
3.3%
2309329 1
 
3.3%
9494030 1
 
3.3%
14282058 1
 
3.3%
15012406 1
 
3.3%
17558419 1
 
3.3%
25440233 1
 
3.3%
34557173 1
 
3.3%
ValueCountFrequency (%)
178888890 1
3.3%
56267239 1
3.3%
41280000 1
3.3%
34557173 1
3.3%
25440233 1
3.3%
17558419 1
3.3%
15012406 1
3.3%
14282058 1
3.3%
9494030 1
3.3%
2309329 1
3.3%

주거용재산금액
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49980367
Minimum0
Maximum2.34 × 108
Zeros5
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:55.655763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16012500
median14451500
Q372500000
95-th percentile1.9075 × 108
Maximum2.34 × 108
Range2.34 × 108
Interquartile range (IQR)66487500

Descriptive statistics

Standard deviation65367731
Coefficient of variation (CV)1.3078682
Kurtosis2.0028079
Mean49980367
Median Absolute Deviation (MAD)14451500
Skewness1.6409247
Sum1.499411 × 109
Variance4.2729402 × 1015
MonotonicityNot monotonic
2023-12-10T23:19:55.817689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 5
16.7%
10000000 5
16.7%
5000000 3
 
10.0%
28908000 1
 
3.3%
13403000 1
 
3.3%
220000000 1
 
3.3%
152000000 1
 
3.3%
155000000 1
 
3.3%
113000000 1
 
3.3%
45000000 1
 
3.3%
Other values (10) 10
33.3%
ValueCountFrequency (%)
0 5
16.7%
5000000 3
10.0%
9050000 1
 
3.3%
10000000 5
16.7%
13403000 1
 
3.3%
15500000 1
 
3.3%
28908000 1
 
3.3%
36600000 1
 
3.3%
44250000 1
 
3.3%
45000000 1
 
3.3%
ValueCountFrequency (%)
234000000 1
3.3%
220000000 1
3.3%
155000000 1
3.3%
152000000 1
3.3%
113000000 1
3.3%
101000000 1
3.3%
79000000 1
3.3%
75000000 1
3.3%
65000000 1
3.3%
47700000 1
3.3%

주거용소득환산액
Categorical

IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
26 
166400
 
1
728000
 
1
696748
 
1
1404000
 
1

Length

Max length7
Median length1
Mean length1.7
Min length1

Unique

Unique4 ?
Unique (%)13.3%

Sample

1st row0
2nd row166400
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26
86.7%
166400 1
 
3.3%
728000 1
 
3.3%
696748 1
 
3.3%
1404000 1
 
3.3%

Length

2023-12-10T23:19:55.947495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:56.080999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 26
86.7%
166400 1
 
3.3%
728000 1
 
3.3%
696748 1
 
3.3%
1404000 1
 
3.3%

일반재산금액
Categorical

IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
26 
20909540
 
1
809557995
 
1
6239970
 
1
22579000
 
1

Length

Max length9
Median length1
Mean length1.9333333
Min length1

Unique

Unique4 ?
Unique (%)13.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 26
86.7%
20909540 1
 
3.3%
809557995 1
 
3.3%
6239970 1
 
3.3%
22579000 1
 
3.3%

Length

2023-12-10T23:19:56.269813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:56.396376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 26
86.7%
20909540 1
 
3.3%
809557995 1
 
3.3%
6239970 1
 
3.3%
22579000 1
 
3.3%

일반재산소득환산액
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
29 
32512201
 
1

Length

Max length8
Median length1
Mean length1.2333333
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 29
96.7%
32512201 1
 
3.3%

Length

2023-12-10T23:19:56.559309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:56.689067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 29
96.7%
32512201 1
 
3.3%

자동차재산금액
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5773169.6
Minimum0
Maximum30700000
Zeros14
Zeros (%)46.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:56.838273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2386288
Q39826825.8
95-th percentile22027701
Maximum30700000
Range30700000
Interquartile range (IQR)9826825.8

Descriptive statistics

Standard deviation8267427.5
Coefficient of variation (CV)1.4320431
Kurtosis2.0836196
Mean5773169.6
Median Absolute Deviation (MAD)2386288
Skewness1.6171957
Sum1.7319509 × 108
Variance6.8350357 × 1013
MonotonicityNot monotonic
2023-12-10T23:19:57.000125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 14
46.7%
3726904 1
 
3.3%
3240000 1
 
3.3%
25282184 1
 
3.3%
10730000 1
 
3.3%
14870000 1
 
3.3%
18050000 1
 
3.3%
2302576 1
 
3.3%
10179101 1
 
3.3%
2928829 1
 
3.3%
Other values (7) 7
23.3%
ValueCountFrequency (%)
0 14
46.7%
2302576 1
 
3.3%
2470000 1
 
3.3%
2928829 1
 
3.3%
3150000 1
 
3.3%
3240000 1
 
3.3%
3726904 1
 
3.3%
7058974 1
 
3.3%
8770000 1
 
3.3%
10179101 1
 
3.3%
ValueCountFrequency (%)
30700000 1
3.3%
25282184 1
3.3%
18050000 1
3.3%
17270000 1
3.3%
14870000 1
3.3%
12466520 1
3.3%
10730000 1
3.3%
10179101 1
3.3%
8770000 1
3.3%
7058974 1
3.3%

자동차재산소득환산액
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106264.2
Minimum0
Maximum1054267
Zeros24
Zeros (%)80.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:57.144702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile767842.95
Maximum1054267
Range1054267
Interquartile range (IQR)0

Descriptive statistics

Standard deviation276052.79
Coefficient of variation (CV)2.5977967
Kurtosis8.0351376
Mean106264.2
Median Absolute Deviation (MAD)0
Skewness2.9306483
Sum3187926
Variance7.6205144 × 1010
MonotonicityNot monotonic
2023-12-10T23:19:57.265979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 24
80.0%
155411 1
 
3.3%
1029990 1
 
3.3%
365709 1
 
3.3%
447441 1
 
3.3%
1054267 1
 
3.3%
135108 1
 
3.3%
ValueCountFrequency (%)
0 24
80.0%
135108 1
 
3.3%
155411 1
 
3.3%
365709 1
 
3.3%
447441 1
 
3.3%
1029990 1
 
3.3%
1054267 1
 
3.3%
ValueCountFrequency (%)
1054267 1
 
3.3%
1029990 1
 
3.3%
447441 1
 
3.3%
365709 1
 
3.3%
155411 1
 
3.3%
135108 1
 
3.3%
0 24
80.0%

재산소득환산금액
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1289842.5
Minimum0
Maximum32877910
Zeros24
Zeros (%)80.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:57.387239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1655656.8
Maximum32877910
Range32877910
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5985693.2
Coefficient of variation (CV)4.6406388
Kurtosis29.565051
Mean1289842.5
Median Absolute Deviation (MAD)0
Skewness5.4208777
Sum38695275
Variance3.5828523 × 1013
MonotonicityNot monotonic
2023-12-10T23:19:57.534361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 24
80.0%
321811 1
 
3.3%
1029990 1
 
3.3%
32877910 1
 
3.3%
1175441 1
 
3.3%
1751015 1
 
3.3%
1539108 1
 
3.3%
ValueCountFrequency (%)
0 24
80.0%
321811 1
 
3.3%
1029990 1
 
3.3%
1175441 1
 
3.3%
1539108 1
 
3.3%
1751015 1
 
3.3%
32877910 1
 
3.3%
ValueCountFrequency (%)
32877910 1
 
3.3%
1751015 1
 
3.3%
1539108 1
 
3.3%
1175441 1
 
3.3%
1029990 1
 
3.3%
321811 1
 
3.3%
0 24
80.0%

소득인정금액
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3945663.5
Minimum0
Maximum34727910
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:57.666664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1135628.1
Q11657500
median3097544
Q33975499.2
95-th percentile5898834.7
Maximum34727910
Range34727910
Interquartile range (IQR)2317999.2

Descriptive statistics

Standard deviation6003100
Coefficient of variation (CV)1.5214424
Kurtosis26.01131
Mean3945663.5
Median Absolute Deviation (MAD)1283940
Skewness4.9459686
Sum1.1836991 × 108
Variance3.6037209 × 1013
MonotonicityNot monotonic
2023-12-10T23:19:57.813070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1400000 2
 
6.7%
4058126 1
 
3.3%
5760854 1
 
3.3%
5240365 1
 
3.3%
1560000 1
 
3.3%
5119672 1
 
3.3%
0 1
 
3.3%
3280279 1
 
3.3%
2468766 1
 
3.3%
1650000 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0 1
3.3%
1001142 1
3.3%
1300000 1
3.3%
1369047 1
3.3%
1400000 2
6.7%
1560000 1
3.3%
1650000 1
3.3%
1680000 1
3.3%
1800000 1
3.3%
2100000 1
3.3%
ValueCountFrequency (%)
34727910 1
3.3%
6011728 1
3.3%
5760854 1
3.3%
5240365 1
3.3%
5119672 1
3.3%
4367880 1
3.3%
4317989 1
3.3%
4058126 1
3.3%
3727619 1
3.3%
3514674 1
3.3%

적격상태명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
적격
22 
부적격

Length

Max length3
Median length2
Mean length2.2666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row적격
2nd row부적격
3rd row적격
4th row부적격
5th row적격

Common Values

ValueCountFrequency (%)
적격 22
73.3%
부적격 8
 
26.7%

Length

2023-12-10T23:19:57.963254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:58.108914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적격 22
73.3%
부적격 8
 
26.7%

예비선발순위
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)85.7%
Missing16
Missing (%)53.3%
Infinite0
Infinite (%)0.0%
Mean111.78571
Minimum9
Maximum513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:19:58.243463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile14.2
Q125.25
median52
Q3150.25
95-th percentile338.8
Maximum513
Range504
Interquartile range (IQR)125

Descriptive statistics

Standard deviation136.86219
Coefficient of variation (CV)1.2243263
Kurtosis5.4740314
Mean111.78571
Median Absolute Deviation (MAD)35.5
Skewness2.1985434
Sum1565
Variance18731.258
MonotonicityNot monotonic
2023-12-10T23:19:58.403185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
17 2
 
6.7%
52 2
 
6.7%
88 1
 
3.3%
513 1
 
3.3%
194 1
 
3.3%
22 1
 
3.3%
124 1
 
3.3%
35 1
 
3.3%
245 1
 
3.3%
159 1
 
3.3%
Other values (2) 2
 
6.7%
(Missing) 16
53.3%
ValueCountFrequency (%)
9 1
3.3%
17 2
6.7%
22 1
3.3%
35 1
3.3%
38 1
3.3%
52 2
6.7%
88 1
3.3%
124 1
3.3%
159 1
3.3%
194 1
3.3%
ValueCountFrequency (%)
513 1
3.3%
245 1
3.3%
194 1
3.3%
159 1
3.3%
124 1
3.3%
88 1
3.3%
52 2
6.7%
38 1
3.3%
35 1
3.3%
22 1
3.3%

읍면동담당자확인명
Categorical

IMBALANCE 

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

Length

Max length3
Median length2
Mean length2.0333333
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
확인 29
96.7%
미확인 1
 
3.3%

Length

2023-12-10T23:19:58.549387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:58.653334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
확인 29
96.7%
미확인 1
 
3.3%
Distinct28
Distinct (%)96.6%
Missing1
Missing (%)3.3%
Memory size372.0 B
Minimum2017-04-24 19:43:00
Maximum2017-05-31 14:22:00
2023-12-10T23:19:58.761785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:58.903392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

통합조사담당자확인명
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
확인 30
100.0%

Length

2023-12-10T23:19:59.086233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:59.240468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
확인 30
100.0%
Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-05-31 13:51:00
Maximum2017-10-18 18:17:00
2023-12-10T23:19:59.352065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:19:59.488321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

지원대상여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
True
27 
False
ValueCountFrequency (%)
True 27
90.0%
False 3
 
10.0%
2023-12-10T23:19:59.625089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시도담당자확인명
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
확인 30
100.0%

Length

2023-12-10T23:19:59.795420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:19:59.965176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
확인 30
100.0%
Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-06-01 00:00:00
Maximum2017-06-01 00:00:00
2023-12-10T23:20:00.087952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:20:00.224320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

비고내용
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing29
Missing (%)96.7%
Memory size372.0 B
2023-12-10T23:20:00.383331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
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

Unique1 ?
Unique (%)100.0%

Sample

1st row *시 확인함
ValueCountFrequency (%)
1
50.0%
확인함 1
50.0%
2023-12-10T23:20:00.715838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
28.6%
* 1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
57.1%
Space Separator 2
28.6%
Other Punctuation 1
 
14.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
* 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
57.1%
Common 3
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Common
ValueCountFrequency (%)
2
66.7%
* 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
57.1%
ASCII 3
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
66.7%
* 1
33.3%
Hangul
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-04-18 12:01:00
Maximum2017-05-18 17:00:00
2023-12-10T23:20:00.880112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:20:01.040401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-05-25 10:35:00
Maximum2018-03-27 13:51:00
2023-12-10T23:20:01.170549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:20:01.284878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size162.0 B
False
30 
ValueCountFrequency (%)
False 30
100.0%
2023-12-10T23:20:01.394570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

근무소재지점수
Categorical

CONSTANT 

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

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 30
100.0%

Length

2023-12-10T23:20:01.495113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:01.582997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

저축목적명
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
주거자금
12 
기타 꿈을 위한 준비자금
결혼자금
대출금상환
창업자금

Length

Max length13
Median length4
Mean length5.9666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주거자금 12
40.0%
기타 꿈을 위한 준비자금 6
20.0%
결혼자금 5
16.7%
대출금상환 5
16.7%
창업자금 2
 
6.7%

Length

2023-12-10T23:20:01.693156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:01.812601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주거자금 12
25.0%
기타 6
12.5%
꿈을 6
12.5%
위한 6
12.5%
준비자금 6
12.5%
결혼자금 5
10.4%
대출금상환 5
10.4%
창업자금 2
 
4.2%

연령
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
30
24 
20

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
30 24
80.0%
20 6
 
20.0%

Length

2023-12-10T23:20:01.955181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:02.053968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 24
80.0%
20 6
 
20.0%

성별코드
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
F
23 
M

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
F 23
76.7%
M 7
 
23.3%

Length

2023-12-10T23:20:02.174590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:02.311316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 23
76.7%
m 7
 
23.3%

결혼상태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
미혼
25 
기혼
이혼
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
미혼 25
83.3%
기혼 4
 
13.3%
이혼 1
 
3.3%

Length

2023-12-10T23:20:02.743726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:02.854941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미혼 25
83.3%
기혼 4
 
13.3%
이혼 1
 
3.3%

우편번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14654.567
Minimum10079
Maximum18302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:20:02.976683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10079
5-th percentile10577.75
Q112155.75
median14699
Q316833
95-th percentile18138.6
Maximum18302
Range8223
Interquartile range (IQR)4677.25

Descriptive statistics

Standard deviation2660.8864
Coefficient of variation (CV)0.18157387
Kurtosis-1.2660285
Mean14654.567
Median Absolute Deviation (MAD)2231.5
Skewness-0.27848398
Sum439637
Variance7080316.2
MonotonicityNot monotonic
2023-12-10T23:20:03.111615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
16988 1
 
3.3%
10893 1
 
3.3%
13623 1
 
3.3%
14921 1
 
3.3%
10337 1
 
3.3%
15853 1
 
3.3%
10872 1
 
3.3%
14673 1
 
3.3%
18132 1
 
3.3%
16678 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10079 1
3.3%
10337 1
3.3%
10872 1
3.3%
10893 1
3.3%
11175 1
3.3%
11341 1
3.3%
11812 1
3.3%
11901 1
3.3%
12920 1
3.3%
13202 1
3.3%
ValueCountFrequency (%)
18302 1
3.3%
18144 1
3.3%
18132 1
3.3%
18116 1
3.3%
17552 1
3.3%
17361 1
3.3%
16988 1
3.3%
16873 1
3.3%
16713 1
3.3%
16678 1
3.3%
Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:20:03.316938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16.5
Mean length11.966667
Min length1

Characters and Unicode

Total characters359
Distinct characters62
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

Unique23 ?
Unique (%)76.7%

Sample

1st row경기도 용인시 기흥구 **
2nd row경기도 동두천시 상패동
3rd row경기도 성남시 중원구 ****
4th row경기도 오산시 은계동
5th row경기도 하남시 풍산동
ValueCountFrequency (%)
경기도 27
30.3%
8
 
9.0%
수원시 4
 
4.5%
부천시 4
 
4.5%
영통구 3
 
3.4%
오산시 3
 
3.4%
목동동 2
 
2.2%
성남시 2
 
2.2%
파주시 2
 
2.2%
고양시 1
 
1.1%
Other values (33) 33
37.1%
2023-12-10T23:20:03.737087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
25.6%
29
 
8.1%
28
 
7.8%
28
 
7.8%
27
 
7.5%
* 23
 
6.4%
20
 
5.6%
8
 
2.2%
7
 
1.9%
7
 
1.9%
Other values (52) 90
25.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 244
68.0%
Space Separator 92
 
25.6%
Other Punctuation 23
 
6.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
29
 
11.9%
28
 
11.5%
28
 
11.5%
27
 
11.1%
20
 
8.2%
8
 
3.3%
7
 
2.9%
7
 
2.9%
6
 
2.5%
6
 
2.5%
Other values (50) 78
32.0%
Space Separator
ValueCountFrequency (%)
92
100.0%
Other Punctuation
ValueCountFrequency (%)
* 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 244
68.0%
Common 115
32.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
29
 
11.9%
28
 
11.5%
28
 
11.5%
27
 
11.1%
20
 
8.2%
8
 
3.3%
7
 
2.9%
7
 
2.9%
6
 
2.5%
6
 
2.5%
Other values (50) 78
32.0%
Common
ValueCountFrequency (%)
92
80.0%
* 23
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 244
68.0%
ASCII 115
32.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
80.0%
* 23
 
20.0%
Hangul
ValueCountFrequency (%)
29
 
11.9%
28
 
11.5%
28
 
11.5%
27
 
11.1%
20
 
8.2%
8
 
3.3%
7
 
2.9%
7
 
2.9%
6
 
2.5%
6
 
2.5%
Other values (50) 78
32.0%

가구원수
Categorical

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row3
2nd row3
3rd row1
4th row2
5th row4

Common Values

ValueCountFrequency (%)
3 9
30.0%
4 9
30.0%
1 6
20.0%
2 5
16.7%
5 1
 
3.3%

Length

2023-12-10T23:20:03.887952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:03.999243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 9
30.0%
4 9
30.0%
1 6
20.0%
2 5
16.7%
5 1
 
3.3%
Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
3년 이상 ~ 4년 미만
22 
1년 이상 ~ 2년 미만
2년 이상 ~ 3년 미만
 
2
6개월 미만
 
2
1년 미만
 
1

Length

Max length13
Median length13
Mean length12.266667
Min length5

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
3년 이상 ~ 4년 미만 22
73.3%
1년 이상 ~ 2년 미만 3
 
10.0%
2년 이상 ~ 3년 미만 2
 
6.7%
6개월 미만 2
 
6.7%
1년 미만 1
 
3.3%

Length

2023-12-10T23:20:04.138688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:04.257056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미만 30
21.3%
이상 27
19.1%
27
19.1%
3년 24
17.0%
4년 22
15.6%
2년 5
 
3.5%
1년 4
 
2.8%
6개월 2
 
1.4%

직업명
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
해당없음
19 
개인회생 및 신용회복지원 대상자(12개월 이상 변제)
10 
사회적경제조직(종사자 포함)
 
1

Length

Max length29
Median length4
Mean length12.7
Min length4

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row사회적경제조직(종사자 포함)
2nd row개인회생 및 신용회복지원 대상자(12개월 이상 변제)
3rd row해당없음
4th row해당없음
5th row해당없음

Common Values

ValueCountFrequency (%)
해당없음 19
63.3%
개인회생 및 신용회복지원 대상자(12개월 이상 변제) 10
33.3%
사회적경제조직(종사자 포함) 1
 
3.3%

Length

2023-12-10T23:20:04.397912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:04.550013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 19
23.5%
개인회생 10
12.3%
10
12.3%
신용회복지원 10
12.3%
대상자(12개월 10
12.3%
이상 10
12.3%
변제 10
12.3%
사회적경제조직(종사자 1
 
1.2%
포함 1
 
1.2%

3D업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

제조업종명
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
20 
사무직
생산직
 
2

Length

Max length4
Median length4
Mean length3.6666667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 20
66.7%
사무직 8
 
26.7%
생산직 2
 
6.7%

Length

2023-12-10T23:20:04.686495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:04.785000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
66.7%
사무직 8
 
26.7%
생산직 2
 
6.7%

근로형태명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
생산직
26 
사무직

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생산직
2nd row생산직
3rd row사무직
4th row생산직
5th row생산직

Common Values

ValueCountFrequency (%)
생산직 26
86.7%
사무직 4
 
13.3%

Length

2023-12-10T23:20:04.877277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:04.967864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생산직 26
86.7%
사무직 4
 
13.3%
Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
True
24 
False
ValueCountFrequency (%)
True 24
80.0%
False 6
 
20.0%
2023-12-10T23:20:05.043040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

근무처우편번호
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13727.333
Minimum4513
Maximum31090
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:20:05.151914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4513
5-th percentile6086.3
Q110994.75
median14207.5
Q316916.5
95-th percentile18245.1
Maximum31090
Range26577
Interquartile range (IQR)5921.75

Descriptive statistics

Standard deviation5186.1751
Coefficient of variation (CV)0.37779916
Kurtosis3.2403828
Mean13727.333
Median Absolute Deviation (MAD)3071
Skewness0.85946272
Sum411820
Variance26896412
MonotonicityNot monotonic
2023-12-10T23:20:05.277285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
18134 2
 
6.7%
17015 1
 
3.3%
17316 1
 
3.3%
13506 1
 
3.3%
14984 1
 
3.3%
17389 1
 
3.3%
7223 1
 
3.3%
10935 1
 
3.3%
14449 1
 
3.3%
31090 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
4513 1
3.3%
6035 1
3.3%
6149 1
3.3%
6307 1
3.3%
7223 1
3.3%
10048 1
3.3%
10422 1
3.3%
10935 1
3.3%
11174 1
3.3%
11403 1
3.3%
ValueCountFrequency (%)
31090 1
3.3%
18336 1
3.3%
18134 2
6.7%
17598 1
3.3%
17389 1
3.3%
17316 1
3.3%
17015 1
3.3%
16621 1
3.3%
16499 1
3.3%
14984 1
3.3%
Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:20:05.435673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length34
Mean length29.3
Min length22

Characters and Unicode

Total characters879
Distinct characters79
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 row경기 용인시 기흥구 ********* ***** ************ **
2nd row경기 양주시 남면 **** ****** *****
3rd row경기 고양시 일산동구 *** **** ****************
4th row경기 오산시 경기대로 *** *****
5th row경기 하남시 서하남로418번길 ** *****
ValueCountFrequency (%)
78
46.4%
경기 24
 
14.3%
서울 5
 
3.0%
부천시 3
 
1.8%
강남구 3
 
1.8%
분당구 2
 
1.2%
성남시 2
 
1.2%
오산시 2
 
1.2%
수원시 2
 
1.2%
이천시 2
 
1.2%
Other values (44) 45
26.8%
2023-12-10T23:20:05.686706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 448
51.0%
168
 
19.1%
28
 
3.2%
27
 
3.1%
26
 
3.0%
13
 
1.5%
13
 
1.5%
11
 
1.3%
8
 
0.9%
7
 
0.8%
Other values (69) 130
 
14.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 448
51.0%
Other Letter 253
28.8%
Space Separator 168
 
19.1%
Decimal Number 10
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
28
 
11.1%
27
 
10.7%
26
 
10.3%
13
 
5.1%
13
 
5.1%
11
 
4.3%
8
 
3.2%
7
 
2.8%
6
 
2.4%
5
 
2.0%
Other values (61) 109
43.1%
Decimal Number
ValueCountFrequency (%)
1 3
30.0%
6 2
20.0%
5 2
20.0%
0 1
 
10.0%
8 1
 
10.0%
4 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
* 448
100.0%
Space Separator
ValueCountFrequency (%)
168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 626
71.2%
Hangul 253
28.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
28
 
11.1%
27
 
10.7%
26
 
10.3%
13
 
5.1%
13
 
5.1%
11
 
4.3%
8
 
3.2%
7
 
2.8%
6
 
2.4%
5
 
2.0%
Other values (61) 109
43.1%
Common
ValueCountFrequency (%)
* 448
71.6%
168
 
26.8%
1 3
 
0.5%
6 2
 
0.3%
5 2
 
0.3%
0 1
 
0.2%
8 1
 
0.2%
4 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 626
71.2%
Hangul 253
28.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 448
71.6%
168
 
26.8%
1 3
 
0.5%
6 2
 
0.3%
5 2
 
0.3%
0 1
 
0.2%
8 1
 
0.2%
4 1
 
0.2%
Hangul
ValueCountFrequency (%)
28
 
11.1%
27
 
10.7%
26
 
10.3%
13
 
5.1%
13
 
5.1%
11
 
4.3%
8
 
3.2%
7
 
2.8%
6
 
2.4%
5
 
2.0%
Other values (61) 109
43.1%
Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:20:05.871652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length11
Mean length7.7333333
Min length2

Characters and Unicode

Total characters232
Distinct characters108
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
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 row713호 그린바이오(주)
2nd row한산리
3rd row국립암센터
4th row리더스센터 3층
5th row(주)파로스
ValueCountFrequency (%)
리더스센터 2
 
4.2%
3층 2
 
4.2%
4층 2
 
4.2%
5층 2
 
4.2%
713호 1
 
2.1%
영업기획팀 1
 
2.1%
한일식품 1
 
2.1%
509-4호 1
 
2.1%
아주하이텍(주 1
 
2.1%
대한주철 1
 
2.1%
Other values (34) 34
70.8%
2023-12-10T23:20:06.170482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
 
8.6%
8
 
3.4%
8
 
3.4%
3 7
 
3.0%
4 7
 
3.0%
0 7
 
3.0%
7
 
3.0%
6
 
2.6%
1 5
 
2.2%
5
 
2.2%
Other values (98) 152
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 158
68.1%
Decimal Number 41
 
17.7%
Space Separator 20
 
8.6%
Uppercase Letter 5
 
2.2%
Close Punctuation 3
 
1.3%
Open Punctuation 3
 
1.3%
Dash Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8
 
5.1%
8
 
5.1%
7
 
4.4%
6
 
3.8%
5
 
3.2%
5
 
3.2%
5
 
3.2%
4
 
2.5%
4
 
2.5%
3
 
1.9%
Other values (79) 103
65.2%
Decimal Number
ValueCountFrequency (%)
3 7
17.1%
4 7
17.1%
0 7
17.1%
1 5
12.2%
2 4
9.8%
5 4
9.8%
7 3
7.3%
8 2
 
4.9%
9 1
 
2.4%
6 1
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
B 1
20.0%
K 1
20.0%
O 1
20.0%
C 1
20.0%
F 1
20.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 158
68.1%
Common 69
29.7%
Latin 5
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8
 
5.1%
8
 
5.1%
7
 
4.4%
6
 
3.8%
5
 
3.2%
5
 
3.2%
5
 
3.2%
4
 
2.5%
4
 
2.5%
3
 
1.9%
Other values (79) 103
65.2%
Common
ValueCountFrequency (%)
20
29.0%
3 7
 
10.1%
4 7
 
10.1%
0 7
 
10.1%
1 5
 
7.2%
2 4
 
5.8%
5 4
 
5.8%
7 3
 
4.3%
) 3
 
4.3%
( 3
 
4.3%
Other values (4) 6
 
8.7%
Latin
ValueCountFrequency (%)
B 1
20.0%
K 1
20.0%
O 1
20.0%
C 1
20.0%
F 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 158
68.1%
ASCII 74
31.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
27.0%
3 7
 
9.5%
4 7
 
9.5%
0 7
 
9.5%
1 5
 
6.8%
2 4
 
5.4%
5 4
 
5.4%
7 3
 
4.1%
) 3
 
4.1%
( 3
 
4.1%
Other values (9) 11
14.9%
Hangul
ValueCountFrequency (%)
8
 
5.1%
8
 
5.1%
7
 
4.4%
6
 
3.8%
5
 
3.2%
5
 
3.2%
5
 
3.2%
4
 
2.5%
4
 
2.5%
3
 
1.9%
Other values (79) 103
65.2%
Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:20:06.326613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length18.3
Min length13

Characters and Unicode

Total characters549
Distinct characters77
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 row경기 용인시 기흥구 ** ****
2nd row경기 양주시 남면 *** ***
3rd row경기 고양시 일산동구 *** ***
4th row경기 오산시 오산동 *****
5th row경기 하남시 춘궁동 ***
ValueCountFrequency (%)
47
34.3%
경기 24
17.5%
서울 5
 
3.6%
부천시 3
 
2.2%
강남구 3
 
2.2%
분당구 2
 
1.5%
성남시 2
 
1.5%
오산시 2
 
1.5%
수원시 2
 
1.5%
이천시 2
 
1.5%
Other values (44) 45
32.8%
2023-12-10T23:20:06.615754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 166
30.2%
137
25.0%
26
 
4.7%
25
 
4.6%
24
 
4.4%
14
 
2.6%
13
 
2.4%
11
 
2.0%
7
 
1.3%
6
 
1.1%
Other values (67) 120
21.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 244
44.4%
Other Punctuation 166
30.2%
Space Separator 137
25.0%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
26
 
10.7%
25
 
10.2%
24
 
9.8%
14
 
5.7%
13
 
5.3%
11
 
4.5%
7
 
2.9%
6
 
2.5%
6
 
2.5%
6
 
2.5%
Other values (63) 106
43.4%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
6 1
50.0%
Other Punctuation
ValueCountFrequency (%)
* 166
100.0%
Space Separator
ValueCountFrequency (%)
137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 305
55.6%
Hangul 244
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
26
 
10.7%
25
 
10.2%
24
 
9.8%
14
 
5.7%
13
 
5.3%
11
 
4.5%
7
 
2.9%
6
 
2.5%
6
 
2.5%
6
 
2.5%
Other values (63) 106
43.4%
Common
ValueCountFrequency (%)
* 166
54.4%
137
44.9%
4 1
 
0.3%
6 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 305
55.6%
Hangul 244
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 166
54.4%
137
44.9%
4 1
 
0.3%
6 1
 
0.3%
Hangul
ValueCountFrequency (%)
26
 
10.7%
25
 
10.2%
24
 
9.8%
14
 
5.7%
13
 
5.3%
11
 
4.5%
7
 
2.9%
6
 
2.5%
6
 
2.5%
6
 
2.5%
Other values (63) 106
43.4%
Distinct7
Distinct (%)100.0%
Missing23
Missing (%)76.7%
Memory size372.0 B
2023-12-10T23:20:06.802193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length8
Mean length8.2857143
Min length2

Characters and Unicode

Total characters58
Distinct characters43
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

Unique7 ?
Unique (%)100.0%

Sample

1st row713호 그린바이오(주)
2nd row3층 삼성서비스센터
3rd row4층
4th row4층 대한주철
5th row테크노파크 쌍용3차 301동
ValueCountFrequency (%)
4층 2
16.7%
713호 1
8.3%
그린바이오(주 1
8.3%
3층 1
8.3%
삼성서비스센터 1
8.3%
대한주철 1
8.3%
테크노파크 1
8.3%
쌍용3차 1
8.3%
301동 1
8.3%
꿈결 1
8.3%
2023-12-10T23:20:07.100992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
10.3%
3 4
 
6.9%
3
 
5.2%
4 2
 
3.4%
2
 
3.4%
1 2
 
3.4%
2
 
3.4%
2
 
3.4%
1
 
1.7%
1
 
1.7%
Other values (33) 33
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40
69.0%
Decimal Number 10
 
17.2%
Space Separator 6
 
10.3%
Open Punctuation 1
 
1.7%
Close Punctuation 1
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
7.5%
2
 
5.0%
2
 
5.0%
2
 
5.0%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
Other values (25) 25
62.5%
Decimal Number
ValueCountFrequency (%)
3 4
40.0%
4 2
20.0%
1 2
20.0%
0 1
 
10.0%
7 1
 
10.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 40
69.0%
Common 18
31.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
7.5%
2
 
5.0%
2
 
5.0%
2
 
5.0%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
Other values (25) 25
62.5%
Common
ValueCountFrequency (%)
6
33.3%
3 4
22.2%
4 2
 
11.1%
1 2
 
11.1%
0 1
 
5.6%
7 1
 
5.6%
( 1
 
5.6%
) 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 40
69.0%
ASCII 18
31.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
33.3%
3 4
22.2%
4 2
 
11.1%
1 2
 
11.1%
0 1
 
5.6%
7 1
 
5.6%
( 1
 
5.6%
) 1
 
5.6%
Hangul
ValueCountFrequency (%)
3
 
7.5%
2
 
5.0%
2
 
5.0%
2
 
5.0%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
1
 
2.5%
Other values (25) 25
62.5%
Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:20:07.333370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.3333333
Min length2

Characters and Unicode

Total characters190
Distinct characters103
Distinct categories5 ?
Distinct scripts3 ?
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 row그린바이오(주)
2nd row보이트씨앤아이
3rd row국립암센터
4th row(주)오산교차로
5th row(주)파로스
ValueCountFrequency (%)
주)오산교차로 2
 
6.1%
예종세무그룹 1
 
3.0%
아이티밥 1
 
3.0%
네오카텍 1
 
3.0%
주안에지역아동센터 1
 
3.0%
보안팀 1
 
3.0%
꿈결 1
 
3.0%
스토리인 1
 
3.0%
디자인시티커뮤니케이션 1
 
3.0%
주)로드키네마틱스 1
 
3.0%
Other values (22) 22
66.7%
2023-12-10T23:20:07.679504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
6.8%
8
 
4.2%
( 7
 
3.7%
) 7
 
3.7%
5
 
2.6%
5
 
2.6%
5
 
2.6%
4
 
2.1%
4
 
2.1%
3
 
1.6%
Other values (93) 129
67.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 171
90.0%
Open Punctuation 7
 
3.7%
Close Punctuation 7
 
3.7%
Space Separator 3
 
1.6%
Uppercase Letter 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13
 
7.6%
8
 
4.7%
5
 
2.9%
5
 
2.9%
5
 
2.9%
4
 
2.3%
4
 
2.3%
3
 
1.8%
3
 
1.8%
3
 
1.8%
Other values (88) 118
69.0%
Uppercase Letter
ValueCountFrequency (%)
O 1
50.0%
K 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 171
90.0%
Common 17
 
8.9%
Latin 2
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13
 
7.6%
8
 
4.7%
5
 
2.9%
5
 
2.9%
5
 
2.9%
4
 
2.3%
4
 
2.3%
3
 
1.8%
3
 
1.8%
3
 
1.8%
Other values (88) 118
69.0%
Common
ValueCountFrequency (%)
( 7
41.2%
) 7
41.2%
3
17.6%
Latin
ValueCountFrequency (%)
O 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 171
90.0%
ASCII 19
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
13
 
7.6%
8
 
4.7%
5
 
2.9%
5
 
2.9%
5
 
2.9%
4
 
2.3%
4
 
2.3%
3
 
1.8%
3
 
1.8%
3
 
1.8%
Other values (88) 118
69.0%
ASCII
ValueCountFrequency (%)
( 7
36.8%
) 7
36.8%
3
15.8%
O 1
 
5.3%
K 1
 
5.3%

근로기간명
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
6개월 미만
12 
1년 이상 ~ 2년 미만
3년 이상 ~ 4년 미만
2년 이상 ~ 3년 미만
1년 미만

Length

Max length13
Median length9.5
Mean length9.4
Min length5

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row6개월 미만
2nd row2년 이상 ~ 3년 미만
3rd row6개월 미만
4th row4년 이상
5th row3년 이상 ~ 4년 미만

Common Values

ValueCountFrequency (%)
6개월 미만 12
40.0%
1년 이상 ~ 2년 미만 7
23.3%
3년 이상 ~ 4년 미만 5
16.7%
2년 이상 ~ 3년 미만 3
 
10.0%
1년 미만 2
 
6.7%
4년 이상 1
 
3.3%

Length

2023-12-10T23:20:07.848835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:07.986786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미만 29
27.6%
이상 16
15.2%
15
14.3%
6개월 12
11.4%
2년 10
 
9.5%
1년 9
 
8.6%
3년 8
 
7.6%
4년 6
 
5.7%

거주상태명
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2천만원 미만 전월세
12 
자가
2천만원이상~5천만원미만 전월세
무상거주
5천만원이상~1억원미만 전월세
 
1

Length

Max length17
Median length16
Mean length8.3333333
Min length2

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row2천만원이상~5천만원미만 전월세
2nd row무상거주
3rd row2천만원 미만 전월세
4th row2천만원 미만 전월세
5th row5천만원이상~1억원미만 전월세

Common Values

ValueCountFrequency (%)
2천만원 미만 전월세 12
40.0%
자가 9
30.0%
2천만원이상~5천만원미만 전월세 4
 
13.3%
무상거주 4
 
13.3%
5천만원이상~1억원미만 전월세 1
 
3.3%

Length

2023-12-10T23:20:08.111605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:08.220507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전월세 17
28.8%
2천만원 12
20.3%
미만 12
20.3%
자가 9
15.3%
2천만원이상~5천만원미만 4
 
6.8%
무상거주 4
 
6.8%
5천만원이상~1억원미만 1
 
1.7%

자동차본인명
Categorical

IMBALANCE 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
차량없음
26 
1;000cc 미만 경차
 
1
1;600cc 이상 ~ 2;000cc 미만
 
1
2;000cc 이상
 
1
1;000cc 이상 ~ 1;600cc 미만
 
1

Length

Max length23
Median length4
Mean length5.7666667
Min length4

Unique

Unique4 ?
Unique (%)13.3%

Sample

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

Common Values

ValueCountFrequency (%)
차량없음 26
86.7%
1;000cc 미만 경차 1
 
3.3%
1;600cc 이상 ~ 2;000cc 미만 1
 
3.3%
2;000cc 이상 1
 
3.3%
1;000cc 이상 ~ 1;600cc 미만 1
 
3.3%

Length

2023-12-10T23:20:08.355016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:08.476640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
차량없음 26
63.4%
미만 3
 
7.3%
이상 3
 
7.3%
1;000cc 2
 
4.9%
1;600cc 2
 
4.9%
2
 
4.9%
2;000cc 2
 
4.9%
경차 1
 
2.4%
Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
차량없음
18 
1;600cc 이상 ~ 2;000cc 미만
2;000cc 이상
1;000cc 미만 경차

Length

Max length23
Median length4
Mean length9.3
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
차량없음 18
60.0%
1;600cc 이상 ~ 2;000cc 미만 6
 
20.0%
2;000cc 이상 3
 
10.0%
1;000cc 미만 경차 3
 
10.0%

Length

2023-12-10T23:20:08.611319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:20:08.723337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
차량없음 18
28.6%
이상 9
14.3%
2;000cc 9
14.3%
미만 9
14.3%
1;600cc 6
 
9.5%
6
 
9.5%
1;000cc 3
 
4.8%
경차 3
 
4.8%
Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2017-04-18 00:00:00
Maximum2017-05-18 00:00:00
2023-12-10T23:20:08.819562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:20:08.921958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

Sample

선발정보번호근로소득금액사업소득금액재산소득금액기타소득금액실제소득금액최대소득인정금액가구특성해당여부차량보유상태명가산기준충족명중위소득결과값가구특성점수경기도거주기간점수현재직장근로기간점수거주상태점수차량보유상태점수중위소득결과점수가산기준충족점수평가점수총점수기초공제금액부채금액주거용재산금액주거용소득환산액일반재산금액일반재산소득환산액자동차재산금액자동차재산소득환산액재산소득환산금액소득인정금액적격상태명예비선발순위읍면동담당자확인명읍면동담당자확인일시통합조사담당자확인명통합조사담당자확인일시지원대상여부시도담당자확인명시도담당자확인일자비고내용등록일시수정일시삭제여부근무소재지점수저축목적명연령성별코드결혼상태명우편번호지번주소가구원수경기도거주기간명직업명3D업종명제조업종명근로형태명근무처경기도지역여부근무처우편번호근무처도로명주소근무처도로명상세주소근무처지번주소근무처지번상세주소근무처명근로기간명거주상태명자동차본인명자동차가구원명데이터기준일자
04140000000014000003640915N차량없음사회적38513.51010.58.030380.0850000000289080000000001400000적격88확인2017-04-27 14:13확인2017-05-31 17:27Y확인2017-06-01*시 확인함2017-04-18 15:552017-06-01 10:15N0결혼자금20F미혼16988경기도 용인시 기흥구 **32년 이상 ~ 3년 미만사회적경제조직(종사자 포함)<NA><NA>생산직Y17015경기 용인시 기흥구 ********* ***** ************ **713호 그린바이오(주)경기 용인시 기흥구 ** ****713호 그린바이오(주)그린바이오(주)6개월 미만2천만원이상~5천만원미만 전월세차량없음차량없음2017-04-18
15373631500037363153640915N차량없음<NA>111515.0176.08.00051.08500000001010000001664000037269041554113218114058126부적격<NA>확인2017-05-25 12:39확인2017-05-31 14:31N확인2017-06-01<NA>2017-04-18 12:012017-05-25 12:39N0결혼자금20F미혼11341경기도 동두천시 상패동33년 이상 ~ 4년 미만개인회생 및 신용회복지원 대상자(12개월 이상 변제)<NA>사무직생산직Y11403경기 양주시 남면 **** ****** *****한산리경기 양주시 남면 *** ***<NA>보이트씨앤아이2년 이상 ~ 3년 미만무상거주차량없음2;000cc 이상2017-04-18
27130000000013000001652931N차량없음<NA>79515.01012.08.024074.085000000050000000000001300000적격<NA>확인2017-04-25 09:57확인2017-05-31 13:51Y확인2017-06-01<NA>2017-04-18 12:012017-05-31 13:51N0기타 꿈을 위한 준비자금20F미혼13202경기도 성남시 중원구 ****13년 이상 ~ 4년 미만해당없음<NA><NA>사무직Y10422경기 고양시 일산동구 *** **** ****************국립암센터경기 고양시 일산동구 *** ***<NA>국립암센터6개월 미만2천만원 미만 전월세차량없음차량없음2017-04-18
3826452990086937535146742814449Y차량없음<NA>1251015.02512.08.00070.085000000050000000000003514674부적격<NA>확인2017-05-01 16:16확인2017-05-31 13:59Y확인2017-06-01<NA>2017-05-01 14:432017-05-25 10:35N0대출금상환20F미혼18116경기도 오산시 은계동23년 이상 ~ 4년 미만해당없음<NA><NA>생산직Y18134경기 오산시 경기대로 *** *****리더스센터 3층경기 오산시 오산동 *****<NA>(주)오산교차로4년 이상2천만원 미만 전월세차량없음차량없음2017-05-01
410332500000033250004467380N차량없음<NA>74515.0209.08.024081.0850000009494030650000000002470000003325000적격17확인2017-05-02 16:45확인2017-05-31 13:54Y확인2017-06-01<NA>2017-04-20 09:562018-03-27 13:51N0주거자금30F기혼12920경기도 하남시 풍산동43년 이상 ~ 4년 미만해당없음<NA><NA>생산직Y13016경기 하남시 서하남로418번길 ** *****(주)파로스경기 하남시 춘궁동 ***<NA>(주)파로스3년 이상 ~ 4년 미만5천만원이상~1억원미만 전월세차량없음1;000cc 미만 경차2017-04-20
511328799900032879994467380N차량없음<NA>97515.0104.58.019061.58500000007900000000030700000102999010299904317989적격<NA>미확인<NA>확인2017-05-31 14:29Y확인2017-06-01<NA>2017-04-24 16:052017-05-25 10:35N0주거자금20F미혼11175경기도 포천시 소흘읍43년 이상 ~ 4년 미만해당없음<NA><NA>생산직Y11174경기 포천시 소흘읍 *** *** *****우리병원경기 포천시 소흘읍 *** ******<NA>영상의학과6개월 미만자가차량없음2;000cc 이상2017-04-24
613168000000016800002814449N차량없음<NA>60515.0206.08.030084.085000000000000001680000적격52확인2017-04-28 11:36확인2017-05-31 14:25Y확인2017-06-01<NA>2017-04-20 11:532017-05-31 16:56N0주거자금30F기혼14617경기도 부천시 심곡동23년 이상 ~ 4년 미만해당없음<NA><NA>생산직Y14723경기 부천시 경인로 *** ************3층 삼성서비스센터경기 부천시 송내동 *****3층 삼성서비스센터삼성서비스센터3년 이상 ~ 4년 미만무상거주차량없음차량없음2017-04-20
714335743400033574344467380N차량없음<NA>75511.01012.08.024070.08500000001000000002090954003150000003357434적격<NA>확인2017-05-23 10:27확인2017-05-31 14:05Y확인2017-06-01<NA>2017-04-19 16:182017-05-25 10:35N0주거자금30F미혼1427543년 이상 ~ 4년 미만해당없음<NA><NA>생산직Y14322경기 광명시 하안로 ** *************C동 807호경기 광명시 소하동 ****<NA>비봉교역6개월 미만2천만원 미만 전월세차량없음1;600cc 이상 ~ 2;000cc 미만2017-04-19
817230300000023030003640915N차량없음<NA>63515.0144.58.027073.5850000000442500000000002303000적격513확인2017-04-27 14:30확인2017-05-31 14:12Y확인2017-06-01<NA>2017-04-18 12:012017-05-31 16:01N0기타 꿈을 위한 준비자금30F미혼16439경기도 수원시 팔달구 ***33년 이상 ~ 4년 미만개인회생 및 신용회복지원 대상자(12개월 이상 변제)<NA>생산직생산직Y16621경기 수원시 권선구 *** *** ******** ****B1F 김영모 과자점경기 수원시 권선구 *** ***<NA>김영모 과자점1년 이상 ~ 2년 미만자가차량없음차량없음2017-04-18
918100114200010011421652931N차량없음<NA>61511.01412.08.027077.0850000001501240690500000000001001142적격194확인2017-04-27 16:37확인2017-05-31 14:25Y확인2017-06-01<NA>2017-04-18 14:392017-05-31 16:56N0주거자금30F미혼14725경기도 부천시 송내동11년 이상 ~ 2년 미만해당없음<NA><NA>생산직Y14655경기 부천시 소사로 *** *********************부천시시설관리공단경기 부천시 춘의동 *<NA>부천시시설관리공단1년 이상 ~ 2년 미만2천만원 미만 전월세차량없음차량없음2017-04-18
선발정보번호근로소득금액사업소득금액재산소득금액기타소득금액실제소득금액최대소득인정금액가구특성해당여부차량보유상태명가산기준충족명중위소득결과값가구특성점수경기도거주기간점수현재직장근로기간점수거주상태점수차량보유상태점수중위소득결과점수가산기준충족점수평가점수총점수기초공제금액부채금액주거용재산금액주거용소득환산액일반재산금액일반재산소득환산액자동차재산금액자동차재산소득환산액재산소득환산금액소득인정금액적격상태명예비선발순위읍면동담당자확인명읍면동담당자확인일시통합조사담당자확인명통합조사담당자확인일시지원대상여부시도담당자확인명시도담당자확인일자비고내용등록일시수정일시삭제여부근무소재지점수저축목적명연령성별코드결혼상태명우편번호지번주소가구원수경기도거주기간명직업명3D업종명제조업종명근로형태명근무처경기도지역여부근무처우편번호근무처도로명주소근무처도로명상세주소근무처지번주소근무처지번상세주소근무처명근로기간명거주상태명자동차본인명자동차가구원명데이터기준일자
2033210833300021083333640915N차량없음<NA>58515.01410.58.030082.58500000041280000366000000002302576002108333적격17확인2017-05-31 14:22확인2017-05-31 14:46Y확인2017-06-01<NA>2017-04-24 13:002017-05-31 16:36N0대출금상환30F미혼1190133년 이상 ~ 4년 미만개인회생 및 신용회복지원 대상자(12개월 이상 변제)<NA>사무직생산직Y12238경기 남양주시 경춘로 *** **********4층 대한주철경기 남양주시 금곡동 *****4층 대한주철대한주철1년 이상 ~ 2년 미만2천만원이상~5천만원미만 전월세차량없음1;000cc 미만 경차2017-04-24
2134180000000018000002814449N차량없음<NA>64515.01212.08.027079.08500000001550000000018050000001800000적격38확인2017-04-25 09:58확인2017-05-31 13:54Y확인2017-06-01<NA>2017-04-20 11:122017-05-31 13:54N0기타 꿈을 위한 준비자금20F미혼10079경기도 김포시 장기동23년 이상 ~ 4년 미만개인회생 및 신용회복지원 대상자(12개월 이상 변제)<NA>사무직생산직Y10048경기 김포시 양촌읍 ******* *** *****학운4산업단지경기 김포시 양촌읍 *** ****<NA>서부이엔지1년 미만2천만원 미만 전월세차량없음차량없음2017-04-20
2236165000000016500001652931N차량없음<NA>10058.01010.58.019060.5850000000450000000000001650000적격<NA>확인2017-05-22 08:53확인2017-05-31 14:12Y확인2017-06-01<NA>2017-04-18 12:012017-05-25 10:35N0결혼자금30M미혼16678경기도 수원시 영통구 **16개월 미만해당없음<NA><NA>사무직N4513서울 중구 세종대로 ** ******************10층 OK저축은행 영업기획팀서울 중구 남대문로4가 **<NA>OK저축은행6개월 미만2천만원이상~5천만원미만 전월세차량없음차량없음2017-04-18
2337246876600024687664467380N1;000cc 이상 ~ 1;600cc 미만<NA>55515.02012.05.030087.08500000021290001000000000014870000002468766적격9확인2017-04-28 09:56확인2017-05-31 13:58Y확인2017-06-01<NA>2017-04-21 17:322017-05-31 13:59N0주거자금30F미혼18132경기도 오산시 부산동43년 이상 ~ 4년 미만해당없음<NA><NA>생산직N31090충남 천안시 서북구 **** ** **********성윤빌딩 205호충남 천안시 서북구 *** ***<NA>(주)로드키네마틱스3년 이상 ~ 4년 미만2천만원 미만 전월세1;000cc 이상 ~ 1;600cc 미만차량없음2017-04-21
2439328027900032802793640915N차량없음<NA>9059.5104.58.019056.085000000345571731130000000000003280279적격<NA>확인2017-04-26 10:48확인2017-05-31 14:25Y확인2017-06-01<NA>2017-04-20 13:232017-05-25 10:35N0기타 꿈을 위한 준비자금30F미혼14673경기도 부천시 역곡동31년 미만해당없음<NA><NA>생산직Y14449경기 부천시 석천로 *** *****************테크노파크 쌍용3차 301동경기 부천시 삼정동 ****테크노파크 쌍용3차 301동디자인시티커뮤니케이션6개월 미만자가차량없음차량없음2017-04-20
2543000001652931N차량없음생산직0511.01412.08.030585.085000000000000000적격52확인2017-04-25 17:10확인2017-10-18 18:17Y확인2017-06-01<NA>2017-04-18 12:012017-05-31 16:25N0주거자금30M미혼10872경기도 파주시 목동동11년 이상 ~ 2년 미만개인회생 및 신용회복지원 대상자(12개월 이상 변제)<NA>생산직생산직Y10935경기 파주시 조리읍 ******** **** *****스토리인경기 파주시 조리읍 *** ***<NA>스토리인1년 이상 ~ 2년 미만2천만원 미만 전월세차량없음차량없음2017-04-18
264738192311250000039442314467380N차량없음<NA>115515.0144.58.00046.5850000000155000000728000001073000044744111754415119672부적격<NA>확인2017-04-25 17:08확인2017-05-31 14:25Y확인2017-06-01<NA>2017-04-18 12:012017-05-25 10:35N0결혼자금30F미혼15853경기도 군포시 당정동43년 이상 ~ 4년 미만해당없음<NA><NA>생산직N7223서울 영등포구 당산로50길 * *************꿈결서울 영등포구 당산동6가 ***꿈결꿈결1년 이상 ~ 2년 미만자가차량없음1;600cc 이상 ~ 2;000cc 미만2017-04-18
2748156000000015600001652931N차량없음<NA>94515.01412.08.019073.085000000050000000000001560000적격<NA>확인2017-05-29 00:25확인2017-05-31 13:51Y확인2017-06-01<NA>2017-04-18 12:012017-05-31 13:51N0주거자금30M미혼10337경기도 고양시 일산동구 ***13년 이상 ~ 4년 미만해당없음<NA><NA>사무직Y17389경기 이천시 마장면 *** ** *****스태츠칩팩코리아경기 이천시 마장면 *** *****스태츠칩팩코리아보안팀1년 이상 ~ 2년 미만2천만원 미만 전월세차량없음차량없음2017-04-18
285113600008250000130435034893504467380N차량없음<NA>117515.0104.58.00042.58500000050001520000006967480025282184105426717510155240365부적격<NA>확인2017-04-25 10:10확인2017-05-31 14:00Y확인2017-06-01<NA>2017-04-21 09:442017-05-25 10:35N0기타 꿈을 위한 준비자금30F미혼14921경기도 시흥시 은행동43년 이상 ~ 4년 미만해당없음<NA><NA>생산직Y14984경기 시흥시 목감초등길 * ***********삼호가든상가 2층경기 시흥시 조남동 ***<NA>주안에지역아동센터6개월 미만자가차량없음1;600cc 이상 ~ 2;000cc 미만2017-04-21
2952166666600255508042217464467380Y차량없음<NA>1291015.0104.58.00047.5850000000220000000140400000324000013510815391085760854부적격<NA>확인2017-05-22 15:13확인2017-05-31 14:17Y확인2017-06-01<NA>2017-04-21 09:462017-05-25 10:35N0창업자금30M미혼13623경기도 성남시 분당구 ***43년 이상 ~ 4년 미만해당없음<NA><NA>생산직Y13506경기 성남시 분당구 ******** * **********5층경기 성남시 분당구 *** *****<NA>아이티밥 개발팀6개월 미만자가차량없음1;600cc 이상 ~ 2;000cc 미만2017-04-21