Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory151.0 B

Variable types

Numeric14
Categorical2

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 부동산 거래 통계를 조회할 수 있는 서비스로 충남의 거래주체별 부동산 거래 건수 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2558

Alerts

지역명 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
지역구분 레벨 is highly overall correlated with 번호 and 4 other fieldsHigh correlation
번호 is highly overall correlated with 지역코드 and 5 other fieldsHigh correlation
지역코드 is highly overall correlated with 번호 and 5 other fieldsHigh correlation
거래유형 is highly overall correlated with 개인->기타_건수 and 1 other fieldsHigh correlation
합계_건수 is highly overall correlated with 번호 and 8 other fieldsHigh correlation
개인->개인_건수 is highly overall correlated with 번호 and 8 other fieldsHigh correlation
개인->법인_건수 is highly overall correlated with 합계_건수 and 7 other fieldsHigh correlation
개인->기타_건수 is highly overall correlated with 거래유형 and 7 other fieldsHigh correlation
법인->개인_건수 is highly overall correlated with 번호 and 5 other fieldsHigh correlation
법인->법인_건수 is highly overall correlated with 합계_건수 and 4 other fieldsHigh correlation
기타->개인_건수 is highly overall correlated with 거래유형 and 6 other fieldsHigh correlation
기타->법인_건수 is highly overall correlated with 개인->법인_건수 and 2 other fieldsHigh correlation
기타->기타_건수 is highly overall correlated with 개인->법인_건수 and 2 other fieldsHigh correlation
지역구분 레벨 is highly imbalanced (51.1%)Imbalance
기타->법인_건수 is highly skewed (γ1 = 21.7936476)Skewed
기타->기타_건수 is highly skewed (γ1 = 23.0315796)Skewed
번호 has unique valuesUnique
개인->법인_건수 has 2433 (24.3%) zerosZeros
개인->기타_건수 has 3808 (38.1%) zerosZeros
법인->개인_건수 has 1012 (10.1%) zerosZeros
법인->법인_건수 has 4368 (43.7%) zerosZeros
법인->기타_건수 has 7669 (76.7%) zerosZeros
기타->개인_건수 has 4429 (44.3%) zerosZeros
기타->법인_건수 has 7661 (76.6%) zerosZeros
기타->기타_건수 has 7377 (73.8%) zerosZeros

Reproduction

Analysis started2024-01-09 21:33:12.614943
Analysis finished2024-01-09 21:33:33.261859
Duration20.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12348.572
Minimum2
Maximum24793
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:33.337296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile1274.75
Q16215
median12352
Q318536.5
95-th percentile23540.15
Maximum24793
Range24791
Interquartile range (IQR)12321.5

Descriptive statistics

Standard deviation7126.5225
Coefficient of variation (CV)0.57711307
Kurtosis-1.1929339
Mean12348.572
Median Absolute Deviation (MAD)6161.5
Skewness0.013256983
Sum1.2348572 × 108
Variance50787323
MonotonicityNot monotonic
2024-01-10T06:33:33.485891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16719 1
 
< 0.1%
14443 1
 
< 0.1%
4853 1
 
< 0.1%
14787 1
 
< 0.1%
5206 1
 
< 0.1%
1235 1
 
< 0.1%
1764 1
 
< 0.1%
2894 1
 
< 0.1%
8233 1
 
< 0.1%
943 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
8 1
< 0.1%
10 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
16 1
< 0.1%
19 1
< 0.1%
22 1
< 0.1%
ValueCountFrequency (%)
24793 1
< 0.1%
24790 1
< 0.1%
24788 1
< 0.1%
24783 1
< 0.1%
24781 1
< 0.1%
24779 1
< 0.1%
24775 1
< 0.1%
24769 1
< 0.1%
24764 1
< 0.1%
24761 1
< 0.1%

지역코드
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44413.551
Minimum44000
Maximum44825
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:33.592736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44000
5-th percentile44000
Q144150
median44230
Q344770
95-th percentile44825
Maximum44825
Range825
Interquartile range (IQR)620

Descriptive statistics

Standard deviation305.0677
Coefficient of variation (CV)0.0068687977
Kurtosis-1.7212098
Mean44413.551
Median Absolute Deviation (MAD)100
Skewness0.32200177
Sum4.4413551 × 108
Variance93066.302
MonotonicityNot monotonic
2024-01-10T06:33:33.895189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
44250 598
 
6.0%
44200 598
 
6.0%
44180 596
 
6.0%
44710 591
 
5.9%
44790 586
 
5.9%
44150 581
 
5.8%
44760 579
 
5.8%
44810 578
 
5.8%
44210 574
 
5.7%
44825 566
 
5.7%
Other values (8) 4153
41.5%
ValueCountFrequency (%)
44000 565
5.7%
44130 562
5.6%
44131 506
5.1%
44133 499
5.0%
44150 581
5.8%
44180 596
6.0%
44200 598
6.0%
44210 574
5.7%
44230 565
5.7%
44250 598
6.0%
ValueCountFrequency (%)
44825 566
5.7%
44810 578
5.8%
44800 548
5.5%
44790 586
5.9%
44770 549
5.5%
44760 579
5.8%
44710 591
5.9%
44270 359
3.6%
44250 598
6.0%
44230 565
5.7%

지역명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
계룡시
 
598
아산시
 
598
보령시
 
596
금산군
 
591
청양군
 
586
Other values (13)
7031 

Length

Max length3
Median length3
Mean length2.9435
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부여군
2nd row부여군
3rd row태안군
4th row논산시
5th row충남

Common Values

ValueCountFrequency (%)
계룡시 598
 
6.0%
아산시 598
 
6.0%
보령시 596
 
6.0%
금산군 591
 
5.9%
청양군 586
 
5.9%
공주시 581
 
5.8%
부여군 579
 
5.8%
예산군 578
 
5.8%
서산시 574
 
5.7%
태안군 566
 
5.7%
Other values (8) 4153
41.5%

Length

2024-01-10T06:33:33.982450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계룡시 598
 
6.0%
아산시 598
 
6.0%
보령시 596
 
6.0%
금산군 591
 
5.9%
청양군 586
 
5.9%
공주시 581
 
5.8%
부여군 579
 
5.8%
예산군 578
 
5.8%
서산시 574
 
5.7%
태안군 566
 
5.7%
Other values (8) 4153
41.5%

조사일자
Real number (ℝ)

Distinct198
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201417.65
Minimum200601
Maximum202206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:34.075674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200601
5-th percentile200611
Q1201007
median201409
Q3201810
95-th percentile202110
Maximum202206
Range1605
Interquartile range (IQR)803

Descriptive statistics

Standard deviation477.52548
Coefficient of variation (CV)0.0023708224
Kurtosis-1.1915877
Mean201417.65
Median Absolute Deviation (MAD)402
Skewness-0.062645617
Sum2.0141765 × 109
Variance228030.58
MonotonicityNot monotonic
2024-01-10T06:33:34.185410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202201 72
 
0.7%
202011 69
 
0.7%
202004 68
 
0.7%
202112 65
 
0.7%
202003 64
 
0.6%
202202 64
 
0.6%
202203 63
 
0.6%
201205 62
 
0.6%
202106 62
 
0.6%
202205 62
 
0.6%
Other values (188) 9349
93.5%
ValueCountFrequency (%)
200601 54
0.5%
200602 49
0.5%
200603 42
0.4%
200604 42
0.4%
200605 40
0.4%
200606 40
0.4%
200607 43
0.4%
200608 48
0.5%
200609 47
0.5%
200610 51
0.5%
ValueCountFrequency (%)
202206 58
0.6%
202205 62
0.6%
202204 61
0.6%
202203 63
0.6%
202202 64
0.6%
202201 72
0.7%
202112 65
0.7%
202111 46
0.5%
202110 50
0.5%
202109 56
0.6%

거래유형
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1168
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:34.278954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum8
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0939905
Coefficient of variation (CV)0.50864519
Kurtosis-1.1890106
Mean4.1168
Median Absolute Deviation (MAD)2
Skewness0.036641118
Sum41168
Variance4.3847962
MonotonicityNot monotonic
2024-01-10T06:33:34.364107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 1428
14.3%
6 1399
14.0%
5 1385
13.9%
3 1380
13.8%
7 1375
13.8%
4 1365
13.7%
2 1358
13.6%
8 310
 
3.1%
ValueCountFrequency (%)
1 1428
14.3%
2 1358
13.6%
3 1380
13.8%
4 1365
13.7%
5 1385
13.9%
6 1399
14.0%
7 1375
13.8%
8 310
 
3.1%
ValueCountFrequency (%)
8 310
 
3.1%
7 1375
13.8%
6 1399
14.0%
5 1385
13.9%
4 1365
13.7%
3 1380
13.8%
2 1358
13.6%
1 1428
14.3%

합계_건수
Real number (ℝ)

HIGH CORRELATION 

Distinct2382
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean812.6284
Minimum0
Maximum23450
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:34.469727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18
Q178.75
median279
Q3742.25
95-th percentile3241.15
Maximum23450
Range23450
Interquartile range (IQR)663.5

Descriptive statistics

Standard deviation1810.0649
Coefficient of variation (CV)2.2274202
Kurtosis38.072851
Mean812.6284
Median Absolute Deviation (MAD)229
Skewness5.4780403
Sum8126284
Variance3276335
MonotonicityNot monotonic
2024-01-10T06:33:34.576809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57 48
 
0.5%
21 47
 
0.5%
72 46
 
0.5%
50 45
 
0.4%
70 44
 
0.4%
48 43
 
0.4%
53 42
 
0.4%
16 42
 
0.4%
46 41
 
0.4%
74 40
 
0.4%
Other values (2372) 9562
95.6%
ValueCountFrequency (%)
0 4
 
< 0.1%
1 12
 
0.1%
2 26
0.3%
3 14
0.1%
4 22
0.2%
5 22
0.2%
6 28
0.3%
7 24
0.2%
8 30
0.3%
9 20
0.2%
ValueCountFrequency (%)
23450 1
< 0.1%
23070 1
< 0.1%
21516 1
< 0.1%
21064 1
< 0.1%
20906 1
< 0.1%
19245 1
< 0.1%
18779 1
< 0.1%
18026 1
< 0.1%
17889 1
< 0.1%
17742 1
< 0.1%

개인->개인_건수
Real number (ℝ)

HIGH CORRELATION 

Distinct1872
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean542.5392
Minimum0
Maximum15759
Zeros10
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:34.714748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14
Q164
median190.5
Q3513
95-th percentile2126.05
Maximum15759
Range15759
Interquartile range (IQR)449

Descriptive statistics

Standard deviation1184.2734
Coefficient of variation (CV)2.1828348
Kurtosis37.796
Mean542.5392
Median Absolute Deviation (MAD)157.5
Skewness5.5121693
Sum5425392
Variance1402503.6
MonotonicityNot monotonic
2024-01-10T06:33:34.860713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 61
 
0.6%
16 58
 
0.6%
65 53
 
0.5%
64 52
 
0.5%
20 52
 
0.5%
44 51
 
0.5%
39 50
 
0.5%
56 50
 
0.5%
69 49
 
0.5%
18 49
 
0.5%
Other values (1862) 9475
94.8%
ValueCountFrequency (%)
0 10
 
0.1%
1 15
 
0.1%
2 22
0.2%
3 21
0.2%
4 25
0.2%
5 29
0.3%
6 36
0.4%
7 38
0.4%
8 48
0.5%
9 29
0.3%
ValueCountFrequency (%)
15759 1
< 0.1%
14274 1
< 0.1%
13867 1
< 0.1%
12312 1
< 0.1%
11955 1
< 0.1%
11932 1
< 0.1%
11842 1
< 0.1%
11777 1
< 0.1%
11708 1
< 0.1%
11430 1
< 0.1%

개인->법인_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct519
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.5517
Minimum0
Maximum4178
Zeros2433
Zeros (%)24.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:34.986971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q330
95-th percentile168.05
Maximum4178
Range4178
Interquartile range (IQR)29

Descriptive statistics

Standard deviation162.59485
Coefficient of variation (CV)3.5694573
Kurtosis138.74735
Mean45.5517
Median Absolute Deviation (MAD)4
Skewness9.5559382
Sum455517
Variance26437.085
MonotonicityNot monotonic
2024-01-10T06:33:35.122341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2433
24.3%
1 1087
 
10.9%
2 672
 
6.7%
3 487
 
4.9%
4 337
 
3.4%
5 284
 
2.8%
7 189
 
1.9%
6 189
 
1.9%
8 163
 
1.6%
9 157
 
1.6%
Other values (509) 4002
40.0%
ValueCountFrequency (%)
0 2433
24.3%
1 1087
10.9%
2 672
 
6.7%
3 487
 
4.9%
4 337
 
3.4%
5 284
 
2.8%
6 189
 
1.9%
7 189
 
1.9%
8 163
 
1.6%
9 157
 
1.6%
ValueCountFrequency (%)
4178 1
< 0.1%
3450 1
< 0.1%
3422 1
< 0.1%
3145 1
< 0.1%
2886 1
< 0.1%
2085 1
< 0.1%
2027 2
< 0.1%
1961 1
< 0.1%
1898 1
< 0.1%
1855 1
< 0.1%

개인->기타_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct260
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.3393
Minimum0
Maximum1319
Zeros3808
Zeros (%)38.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:35.257120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36
95-th percentile50
Maximum1319
Range1319
Interquartile range (IQR)6

Descriptive statistics

Standard deviation48.711609
Coefficient of variation (CV)3.9476801
Kurtosis140.10239
Mean12.3393
Median Absolute Deviation (MAD)1
Skewness9.8207374
Sum123393
Variance2372.8209
MonotonicityNot monotonic
2024-01-10T06:33:35.399042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3808
38.1%
1 1532
15.3%
2 826
 
8.3%
3 539
 
5.4%
4 364
 
3.6%
5 288
 
2.9%
6 249
 
2.5%
7 190
 
1.9%
8 165
 
1.7%
9 130
 
1.3%
Other values (250) 1909
19.1%
ValueCountFrequency (%)
0 3808
38.1%
1 1532
15.3%
2 826
 
8.3%
3 539
 
5.4%
4 364
 
3.6%
5 288
 
2.9%
6 249
 
2.5%
7 190
 
1.9%
8 165
 
1.7%
9 130
 
1.3%
ValueCountFrequency (%)
1319 1
< 0.1%
1050 1
< 0.1%
848 1
< 0.1%
755 1
< 0.1%
743 1
< 0.1%
717 1
< 0.1%
628 1
< 0.1%
603 1
< 0.1%
590 1
< 0.1%
585 1
< 0.1%

법인->개인_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1137
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.5363
Minimum0
Maximum5671
Zeros1012
Zeros (%)10.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:35.534246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median20
Q3105
95-th percentile857.05
Maximum5671
Range5671
Interquartile range (IQR)101

Descriptive statistics

Standard deviation422.73599
Coefficient of variation (CV)2.6008712
Kurtosis36.108364
Mean162.5363
Median Absolute Deviation (MAD)19
Skewness5.1931005
Sum1625363
Variance178705.72
MonotonicityNot monotonic
2024-01-10T06:33:35.644686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1012
 
10.1%
1 569
 
5.7%
2 497
 
5.0%
3 319
 
3.2%
5 293
 
2.9%
4 262
 
2.6%
6 255
 
2.5%
7 202
 
2.0%
9 186
 
1.9%
8 185
 
1.8%
Other values (1127) 6220
62.2%
ValueCountFrequency (%)
0 1012
10.1%
1 569
5.7%
2 497
5.0%
3 319
 
3.2%
4 262
 
2.6%
5 293
 
2.9%
6 255
 
2.5%
7 202
 
2.0%
8 185
 
1.8%
9 186
 
1.9%
ValueCountFrequency (%)
5671 1
< 0.1%
5395 1
< 0.1%
5127 1
< 0.1%
4884 1
< 0.1%
4763 1
< 0.1%
4718 1
< 0.1%
4697 1
< 0.1%
4634 1
< 0.1%
4605 1
< 0.1%
4524 1
< 0.1%

법인->법인_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct433
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.5288
Minimum0
Maximum1427
Zeros4368
Zeros (%)43.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:35.780228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q312
95-th percentile144.05
Maximum1427
Range1427
Interquartile range (IQR)12

Descriptive statistics

Standard deviation89.375247
Coefficient of variation (CV)3.2466089
Kurtosis61.761963
Mean27.5288
Median Absolute Deviation (MAD)1
Skewness6.7247569
Sum275288
Variance7987.9348
MonotonicityNot monotonic
2024-01-10T06:33:35.915885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4368
43.7%
1 942
 
9.4%
2 509
 
5.1%
3 336
 
3.4%
4 272
 
2.7%
5 212
 
2.1%
6 197
 
2.0%
7 147
 
1.5%
9 144
 
1.4%
8 143
 
1.4%
Other values (423) 2730
27.3%
ValueCountFrequency (%)
0 4368
43.7%
1 942
 
9.4%
2 509
 
5.1%
3 336
 
3.4%
4 272
 
2.7%
5 212
 
2.1%
6 197
 
2.0%
7 147
 
1.5%
8 143
 
1.4%
9 144
 
1.4%
ValueCountFrequency (%)
1427 1
< 0.1%
1375 1
< 0.1%
1309 1
< 0.1%
1306 1
< 0.1%
1303 1
< 0.1%
1221 1
< 0.1%
1209 1
< 0.1%
1119 1
< 0.1%
1077 1
< 0.1%
1032 1
< 0.1%

법인->기타_건수
Real number (ℝ)

ZEROS 

Distinct98
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0178
Minimum0
Maximum227
Zeros7669
Zeros (%)76.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:36.059996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum227
Range227
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.228619
Coefficient of variation (CV)5.5647831
Kurtosis195.22253
Mean2.0178
Median Absolute Deviation (MAD)0
Skewness12.585633
Sum20178
Variance126.08189
MonotonicityNot monotonic
2024-01-10T06:33:36.193957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7669
76.7%
1 792
 
7.9%
2 390
 
3.9%
3 240
 
2.4%
4 135
 
1.4%
5 124
 
1.2%
6 90
 
0.9%
7 56
 
0.6%
8 48
 
0.5%
10 36
 
0.4%
Other values (88) 420
 
4.2%
ValueCountFrequency (%)
0 7669
76.7%
1 792
 
7.9%
2 390
 
3.9%
3 240
 
2.4%
4 135
 
1.4%
5 124
 
1.2%
6 90
 
0.9%
7 56
 
0.6%
8 48
 
0.5%
9 32
 
0.3%
ValueCountFrequency (%)
227 1
 
< 0.1%
217 1
 
< 0.1%
214 1
 
< 0.1%
212 1
 
< 0.1%
211 4
< 0.1%
201 1
 
< 0.1%
194 1
 
< 0.1%
193 1
 
< 0.1%
191 1
 
< 0.1%
187 1
 
< 0.1%

기타->개인_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct303
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.8465
Minimum0
Maximum1444
Zeros4429
Zeros (%)44.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:36.324488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q37
95-th percentile53
Maximum1444
Range1444
Interquartile range (IQR)7

Descriptive statistics

Standard deviation63.539415
Coefficient of variation (CV)4.2797572
Kurtosis136.30289
Mean14.8465
Median Absolute Deviation (MAD)1
Skewness9.9954955
Sum148465
Variance4037.2573
MonotonicityNot monotonic
2024-01-10T06:33:36.461927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4429
44.3%
1 1157
 
11.6%
2 605
 
6.0%
3 344
 
3.4%
4 265
 
2.6%
6 259
 
2.6%
5 251
 
2.5%
7 192
 
1.9%
8 187
 
1.9%
9 183
 
1.8%
Other values (293) 2128
21.3%
ValueCountFrequency (%)
0 4429
44.3%
1 1157
 
11.6%
2 605
 
6.0%
3 344
 
3.4%
4 265
 
2.6%
5 251
 
2.5%
6 259
 
2.6%
7 192
 
1.9%
8 187
 
1.9%
9 183
 
1.8%
ValueCountFrequency (%)
1444 1
< 0.1%
1331 1
< 0.1%
1329 1
< 0.1%
1107 1
< 0.1%
968 1
< 0.1%
934 1
< 0.1%
900 1
< 0.1%
882 1
< 0.1%
876 1
< 0.1%
870 1
< 0.1%

기타->법인_건수
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct123
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0024
Minimum0
Maximum844
Zeros7661
Zeros (%)76.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:36.605671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum844
Range844
Interquartile range (IQR)0

Descriptive statistics

Standard deviation19.985498
Coefficient of variation (CV)6.6565075
Kurtosis708.62053
Mean3.0024
Median Absolute Deviation (MAD)0
Skewness21.793648
Sum30024
Variance399.42014
MonotonicityNot monotonic
2024-01-10T06:33:36.739799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7661
76.6%
1 733
 
7.3%
2 359
 
3.6%
3 248
 
2.5%
4 156
 
1.6%
5 111
 
1.1%
6 67
 
0.7%
7 60
 
0.6%
8 48
 
0.5%
9 39
 
0.4%
Other values (113) 518
 
5.2%
ValueCountFrequency (%)
0 7661
76.6%
1 733
 
7.3%
2 359
 
3.6%
3 248
 
2.5%
4 156
 
1.6%
5 111
 
1.1%
6 67
 
0.7%
7 60
 
0.6%
8 48
 
0.5%
9 39
 
0.4%
ValueCountFrequency (%)
844 1
 
< 0.1%
762 1
 
< 0.1%
664 1
 
< 0.1%
422 2
 
< 0.1%
266 1
 
< 0.1%
225 2
 
< 0.1%
223 2
 
< 0.1%
222 1
 
< 0.1%
221 5
0.1%
220 3
< 0.1%

기타->기타_건수
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct109
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2664
Minimum0
Maximum595
Zeros7377
Zeros (%)73.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:33:36.871191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile8
Maximum595
Range595
Interquartile range (IQR)1

Descriptive statistics

Standard deviation13.680166
Coefficient of variation (CV)6.0360775
Kurtosis799.71957
Mean2.2664
Median Absolute Deviation (MAD)0
Skewness23.03158
Sum22664
Variance187.14695
MonotonicityNot monotonic
2024-01-10T06:33:36.980353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7377
73.8%
1 951
 
9.5%
2 422
 
4.2%
3 239
 
2.4%
4 167
 
1.7%
5 135
 
1.4%
6 84
 
0.8%
7 75
 
0.8%
8 59
 
0.6%
10 40
 
0.4%
Other values (99) 451
 
4.5%
ValueCountFrequency (%)
0 7377
73.8%
1 951
 
9.5%
2 422
 
4.2%
3 239
 
2.4%
4 167
 
1.7%
5 135
 
1.4%
6 84
 
0.8%
7 75
 
0.8%
8 59
 
0.6%
9 24
 
0.2%
ValueCountFrequency (%)
595 1
< 0.1%
561 1
< 0.1%
432 1
< 0.1%
345 1
< 0.1%
238 1
< 0.1%
209 1
< 0.1%
184 1
< 0.1%
179 1
< 0.1%
165 1
< 0.1%
154 1
< 0.1%

지역구분 레벨
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8430 
2
1005 
0
 
565

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
1 8430
84.3%
2 1005
 
10.1%
0 565
 
5.7%

Length

2024-01-10T06:33:37.077392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:33:37.147369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8430
84.3%
2 1005
 
10.1%
0 565
 
5.7%

Interactions

2024-01-10T06:33:31.936513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:16.494653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.611101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:18.859096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.110970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.206580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.207944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:23.585459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.705178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:25.972341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.050378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:28.149954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.353741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:30.753124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.010201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:16.582456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.679149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:18.935363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.188050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.275682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.293364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:23.654434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.777211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.046693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.128659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:28.217169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.437676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:30.846448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.082719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:16.651580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.745899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:19.027731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.270404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.342641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.390762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:23.721511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.858850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.134980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.206666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:28.284274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.516144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:30.938192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.162460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:16.732103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.826646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:19.119700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.355349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.422125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.497343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:23.798688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.966823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.242705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.300082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:28.359146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.628253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:31.041499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.242267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:16.811887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.905482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:19.203433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.435336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.496672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.577142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:23.873107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:25.073781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.322991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.385126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:28.434090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.733685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:31.143853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.313646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:16.879086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.974248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:19.276169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.504795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.564983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.649766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:23.940768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:25.165072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.390550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.461444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:28.714181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.827990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:31.233117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.394245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:16.968593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:18.053684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:19.365172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.587220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.640404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.730323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.036097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:25.281693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.471991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.544700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:28.790700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.935974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:31.333500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.461173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.038828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:18.125603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:19.440310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.655211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.707352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.802962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.124423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:25.372322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.537666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.617207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:28.856455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:30.034970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:31.427662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.534827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.110580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:18.198006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:19.533950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.730482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.778172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.878119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.219702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:25.466534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.615622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.692411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:28.932339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:30.135606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:31.521576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.606695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.181788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:18.268668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:19.639162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.800844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.847257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.953820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.311812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:25.563834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.687163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.765646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.000182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:30.243953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:31.590623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.681357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.280282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:18.343383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:19.748326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.880314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.924157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:23.033950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.412186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:25.664990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.763661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.845021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.072921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:30.349896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:31.664320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.749792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.372339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:18.410510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:19.851985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.953449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.989633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:23.110359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.493265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:25.751703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.831418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:27.926749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.138295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:30.450893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:31.730293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.824419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.461014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:18.717472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:19.939467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.039965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.067671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:23.205156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.567132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:25.825391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.906600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:28.004514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.210248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:30.558457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:31.802078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:32.892573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:17.532152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:18.784265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:20.023111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:21.122733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:22.136344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:23.506248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:24.631351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:25.895549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:26.975814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:28.072406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:29.276024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:30.650147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:33:31.864353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:33:37.434218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드지역명조사일자거래유형합계_건수개인->개인_건수개인->법인_건수개인->기타_건수법인->개인_건수법인->법인_건수법인->기타_건수기타->개인_건수기타->법인_건수기타->기타_건수지역구분 레벨
번호1.0000.9950.9810.2130.0650.6120.6320.2850.2590.5370.4420.2160.2970.1620.1490.868
지역코드0.9951.0001.0000.1130.0000.1740.1690.0560.0000.1480.0980.0550.0920.0900.0260.525
지역명0.9811.0001.0000.1370.0000.6200.6340.4860.4430.5290.4420.3530.4690.2290.2271.000
조사일자0.2130.1130.1371.0000.2450.0740.0540.0760.0560.0980.1310.0800.0990.0700.0660.128
거래유형0.0650.0000.0000.2451.0000.2020.2040.1530.1540.1410.1080.1080.1050.0820.0670.000
합계_건수0.6120.1740.6200.0740.2021.0000.9760.6690.6230.8480.7150.4540.5790.3880.4890.735
개인->개인_건수0.6320.1690.6340.0540.2040.9761.0000.6730.6180.7910.7300.4800.5510.3800.5650.753
개인->법인_건수0.2850.0560.4860.0760.1530.6690.6731.0000.7490.4570.4770.5250.6170.5740.4090.654
개인->기타_건수0.2590.0000.4430.0560.1540.6230.6180.7491.0000.4500.4110.6090.5980.3750.5050.607
법인->개인_건수0.5370.1480.5290.0980.1410.8480.7910.4570.4501.0000.5760.3900.4760.3240.3860.625
법인->법인_건수0.4420.0980.4420.1310.1080.7150.7300.4770.4110.5761.0000.3120.3520.3230.3390.544
법인->기타_건수0.2160.0550.3530.0800.1080.4540.4800.5250.6090.3900.3121.0000.4350.2620.2550.487
기타->개인_건수0.2970.0920.4690.0990.1050.5790.5510.6170.5980.4760.3520.4351.0000.2490.3040.626
기타->법인_건수0.1620.0900.2290.0700.0820.3880.3800.5740.3750.3240.3230.2620.2491.0000.3680.259
기타->기타_건수0.1490.0260.2270.0660.0670.4890.5650.4090.5050.3860.3390.2550.3040.3681.0000.266
지역구분 레벨0.8680.5251.0000.1280.0000.7350.7530.6540.6070.6250.5440.4870.6260.2590.2661.000
2024-01-10T06:33:37.550816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역명지역구분 레벨
지역명1.0000.999
지역구분 레벨0.9991.000
2024-01-10T06:33:37.632044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드조사일자거래유형합계_건수개인->개인_건수개인->법인_건수개인->기타_건수법인->개인_건수법인->법인_건수법인->기타_건수기타->개인_건수기타->법인_건수기타->기타_건수지역명지역구분 레벨
번호1.0000.9980.0180.011-0.604-0.614-0.436-0.324-0.530-0.471-0.303-0.298-0.248-0.2410.8990.798
지역코드0.9981.000-0.032-0.005-0.605-0.616-0.438-0.324-0.529-0.471-0.304-0.298-0.245-0.2400.9990.838
조사일자0.018-0.0321.0000.0650.1460.1660.2030.1590.0450.0730.0700.1680.0890.0770.0540.078
거래유형0.011-0.0050.0651.000-0.377-0.370-0.462-0.553-0.251-0.306-0.325-0.525-0.471-0.4550.0000.000
합계_건수-0.604-0.6050.146-0.3771.0000.9790.8300.6590.8500.7480.4950.6750.4680.4710.2920.601
개인->개인_건수-0.614-0.6160.166-0.3700.9791.0000.8300.6640.7790.7020.4660.6780.4610.4680.3020.625
개인->법인_건수-0.436-0.4380.203-0.4620.8300.8301.0000.6970.6360.6540.4710.6990.5650.5090.1810.368
개인->기타_건수-0.324-0.3240.159-0.5530.6590.6640.6971.0000.4520.5020.4580.6990.5440.5610.1620.330
법인->개인_건수-0.530-0.5290.045-0.2510.8500.7790.6360.4521.0000.6930.4660.4700.3440.3400.2330.470
법인->법인_건수-0.471-0.4710.073-0.3060.7480.7020.6540.5020.6931.0000.4570.4920.4210.3940.1860.387
법인->기타_건수-0.303-0.3040.070-0.3250.4950.4660.4710.4580.4660.4571.0000.4290.4060.4080.1240.246
기타->개인_건수-0.298-0.2980.168-0.5250.6750.6780.6990.6990.4700.4920.4291.0000.5550.5520.1740.346
기타->법인_건수-0.248-0.2450.089-0.4710.4680.4610.5650.5440.3440.4210.4060.5551.0000.4780.1040.180
기타->기타_건수-0.241-0.2400.077-0.4550.4710.4680.5090.5610.3400.3940.4080.5520.4781.0000.1030.185
지역명0.8990.9990.0540.0000.2920.3020.1810.1620.2330.1860.1240.1740.1040.1031.0000.999
지역구분 레벨0.7980.8380.0780.0000.6010.6250.3680.3300.4700.3870.2460.3460.1800.1850.9991.000

Missing values

2024-01-10T06:33:32.999636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:33:33.164137image/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

번호지역코드지역명조사일자거래유형합계_건수개인->개인_건수개인->법인_건수개인->기타_건수법인->개인_건수법인->법인_건수법인->기타_건수기타->개인_건수기타->법인_건수기타->기타_건수지역구분 레벨
167181671944760부여군20131051616000000001
168701687144760부여군200908777000000001
241062410744825태안군201404572432027000001
117671176844230논산시201410597720025000001
1243124444000충남202009477023902651563394585119210
1274127544000충남20201221350193541068401164344624256712380
1171117244000충남2019071135968765112728925524282824069980
9559956044200아산시202112410686558410131108078111
191591916044790청양군2007101139120052006061
6732673344150공주시20220441691414016512001
번호지역코드지역명조사일자거래유형합계_건수개인->개인_건수개인->법인_건수개인->기타_건수법인->개인_건수법인->법인_건수법인->기타_건수기타->개인_건수기타->법인_건수기타->기타_건수지역구분 레벨
9101910244200아산시2017026420413205000001
173571735844760부여군201906825320911317705101
204122041344790청양군202103755000000001
6730673144150공주시202204321916813820613001
8214821544200아산시2012111205599777652942639621
224672246844810예산군20110561531142130401011
7678767944180보령시2016114140132800000001
198141981544790청양군201404474360038000001
3286328744131동남구2011027545390511113800002
206292063044800홍성군2010062634340481851312202501