Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory517.6 KiB
Average record size in memory53.0 B

Variable types

Numeric4
Categorical1

Dataset

DescriptionKCB(코리아크레딧뷰로)에서 제공한 데이터의 통계 자료로 월별, 시군별(행정동코드), 연령구간(만18세이상 ~ 104세이하를 5세단위로 구분), 월부채평균(단위 : 천원)을 확인할 수 있습니다. <성별> 1 남성, 2 여성 <연령구간> 10 : 20세미만, 21 : 25세미만, 22 : 30세미만, 31 : 35세미만, 32 : 40세미만, 41 : 45세미만, 42 : 50세미만, 51 : 55세미만, 52 : 60세미만, 61 : 65세미만, 62 : 70세미만, 70 : 70세이상 본 자료는 상업적 이용금지 및 재배포할 수 없습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2161

Alerts

연령구간 is highly overall correlated with 월대출평균잔액High correlation
월대출평균잔액 is highly overall correlated with 연령구간High correlation
월대출평균잔액 has 615 (6.2%) zerosZeros

Reproduction

Analysis started2024-01-09 21:38:18.344006
Analysis finished2024-01-09 21:38:20.343656
Duration2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준연월
Real number (ℝ)

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201638.14
Minimum201601
Maximum201712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:38:20.387048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201601
5-th percentile201601
Q1201605
median201609
Q3201702
95-th percentile201712
Maximum201712
Range111
Interquartile range (IQR)97

Descriptive statistics

Standard deviation46.745091
Coefficient of variation (CV)0.00023182663
Kurtosis-1.3383552
Mean201638.14
Median Absolute Deviation (MAD)5
Skewness0.79423191
Sum2.0163814 × 109
Variance2185.1035
MonotonicityNot monotonic
2024-01-10T06:38:20.471315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
201607 632
 
6.3%
201610 627
 
6.3%
201604 594
 
5.9%
201711 592
 
5.9%
201701 580
 
5.8%
201612 577
 
5.8%
201606 574
 
5.7%
201601 566
 
5.7%
201609 566
 
5.7%
201710 564
 
5.6%
Other values (8) 4128
41.3%
ValueCountFrequency (%)
201601 566
5.7%
201602 529
5.3%
201603 547
5.5%
201604 594
5.9%
201605 554
5.5%
201606 574
5.7%
201607 632
6.3%
201608 549
5.5%
201609 566
5.7%
201610 627
6.3%
ValueCountFrequency (%)
201712 563
5.6%
201711 592
5.9%
201710 564
5.6%
201703 303
3.0%
201702 549
5.5%
201701 580
5.8%
201612 577
5.8%
201611 534
5.3%
201610 627
6.3%
201609 566
5.7%

행정동코드
Real number (ℝ)

Distinct208
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44417172
Minimum44131250
Maximum44825360
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:38:20.567346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44131250
5-th percentile44131530
Q144180360
median44230400
Q344770267
95-th percentile44810380
Maximum44825360
Range694110
Interquartile range (IQR)589907.25

Descriptive statistics

Standard deviation289431.28
Coefficient of variation (CV)0.0065162024
Kurtosis-1.7260012
Mean44417172
Median Absolute Deviation (MAD)96870
Skewness0.4399463
Sum4.4417172 × 1011
Variance8.3770468 × 1010
MonotonicityNot monotonic
2024-01-10T06:38:20.683550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44180400 67
 
0.7%
44760330 65
 
0.7%
44790340 65
 
0.7%
44270380 64
 
0.6%
44200253 63
 
0.6%
44131540 63
 
0.6%
44131580 61
 
0.6%
44250310 61
 
0.6%
44770253 60
 
0.6%
44760250 60
 
0.6%
Other values (198) 9371
93.7%
ValueCountFrequency (%)
44131250 41
0.4%
44131310 51
0.5%
44131320 34
0.3%
44131330 58
0.6%
44131340 54
0.5%
44131350 50
0.5%
44131360 46
0.5%
44131370 44
0.4%
44131510 48
0.5%
44131520 52
0.5%
ValueCountFrequency (%)
44825360 46
0.5%
44825350 49
0.5%
44825340 53
0.5%
44825330 52
0.5%
44825320 48
0.5%
44825310 56
0.6%
44825253 48
0.5%
44825250 47
0.5%
44810400 49
0.5%
44810390 51
0.5%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5098 
2
4902 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 5098
51.0%
2 4902
49.0%

Length

2024-01-10T06:38:20.815420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:38:20.906472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5098
51.0%
2 4902
49.0%

연령구간
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.0088
Minimum10
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:38:20.975114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q122
median41
Q361
95-th percentile70
Maximum70
Range60
Interquartile range (IQR)39

Descriptive statistics

Standard deviation17.95746
Coefficient of variation (CV)0.43789284
Kurtosis-1.0939812
Mean41.0088
Median Absolute Deviation (MAD)19
Skewness-0.06001777
Sum410088
Variance322.47037
MonotonicityNot monotonic
2024-01-10T06:38:21.055020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
21 875
8.8%
10 874
8.7%
70 848
8.5%
61 847
8.5%
41 844
8.4%
32 840
8.4%
22 836
8.4%
42 834
8.3%
51 816
8.2%
62 807
8.1%
Other values (2) 1579
15.8%
ValueCountFrequency (%)
10 874
8.7%
21 875
8.8%
22 836
8.4%
31 796
8.0%
32 840
8.4%
41 844
8.4%
42 834
8.3%
51 816
8.2%
52 783
7.8%
61 847
8.5%
ValueCountFrequency (%)
70 848
8.5%
62 807
8.1%
61 847
8.5%
52 783
7.8%
51 816
8.2%
42 834
8.3%
41 844
8.4%
32 840
8.4%
31 796
8.0%
22 836
8.4%

월대출평균잔액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8922
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51021.371
Minimum0
Maximum358680
Zeros615
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:38:21.155352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126509.75
median47892
Q370779.25
95-th percentile110501.55
Maximum358680
Range358680
Interquartile range (IQR)44269.5

Descriptive statistics

Standard deviation33967.43
Coefficient of variation (CV)0.66574907
Kurtosis2.7900733
Mean51021.371
Median Absolute Deviation (MAD)22058
Skewness0.9570834
Sum5.1021371 × 108
Variance1.1537863 × 109
MonotonicityNot monotonic
2024-01-10T06:38:21.257724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 615
 
6.2%
3000 18
 
0.2%
10000 11
 
0.1%
5000 10
 
0.1%
1000 7
 
0.1%
4000 5
 
0.1%
2000 5
 
0.1%
30714 3
 
< 0.1%
34221 3
 
< 0.1%
42330 3
 
< 0.1%
Other values (8912) 9320
93.2%
ValueCountFrequency (%)
0 615
6.2%
140 1
 
< 0.1%
177 1
 
< 0.1%
200 1
 
< 0.1%
269 1
 
< 0.1%
419 1
 
< 0.1%
490 1
 
< 0.1%
495 1
 
< 0.1%
499 1
 
< 0.1%
525 1
 
< 0.1%
ValueCountFrequency (%)
358680 1
< 0.1%
338911 1
< 0.1%
298213 1
< 0.1%
291064 1
< 0.1%
269251 1
< 0.1%
254627 1
< 0.1%
254420 1
< 0.1%
246482 1
< 0.1%
240000 1
< 0.1%
239600 1
< 0.1%

Interactions

2024-01-10T06:38:19.891585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:18.734536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:19.040163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:19.359725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:19.967857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:18.806887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:19.118566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:19.430862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:20.057370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:18.886109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:19.198313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:19.511483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:20.137160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:18.962746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:19.274693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:38:19.584544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:38:21.331078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월행정동코드성별연령구간월대출평균잔액
기준연월1.0000.0000.0080.0190.057
행정동코드0.0001.0000.0000.0250.179
성별0.0080.0001.0000.0000.318
연령구간0.0190.0250.0001.0000.517
월대출평균잔액0.0570.1790.3180.5171.000
2024-01-10T06:38:21.408333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월행정동코드연령구간월대출평균잔액성별
기준연월1.0000.008-0.0050.0420.004
행정동코드0.0081.0000.003-0.0990.000
연령구간-0.0050.0031.0000.5860.000
월대출평균잔액0.042-0.0990.5861.0000.244
성별0.0040.0000.0000.2441.000

Missing values

2024-01-10T06:38:20.237708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:38:20.311215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

기준연월행정동코드성별연령구간월대출평균잔액
17782016014480035024228511
60082016104420025017061255
494912016074421033016230333
4839220160744270530141105294
294692016034413131026290676
22882016014415059022232812
148402016114421040016185050
173712016124413131013151802
562962016094420025013259029
9732016014477035026124772
기준연월행정동코드성별연령구간월대출평균잔액
161452016124423025017062682
85352016104415056025154878
219352016024477036014125494
711252017114420061022232631
621532017014413331013242378
647032017104481038013283879
503072016084413135015273290
14122016014427039023248716
131782016114413134014180287
767102017124421032014286468