Overview

Dataset statistics

Number of variables15
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 memory142.0 B

Variable types

Numeric13
Categorical2

Dataset

Description한국부동산원(구.한국감정원)에서 제공하는 부동산 거래 통계를 조회할 수 있는 서비스로 충남의 규모별 거래 건수 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2560

Alerts

지역명 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
지역구분 레벨 is highly overall correlated with 번호 and 7 other fieldsHigh correlation
번호 is highly overall correlated with 지역코드 and 6 other fieldsHigh correlation
지역코드 is highly overall correlated with 번호 and 6 other fieldsHigh correlation
합계_건수 is highly overall correlated with 번호 and 10 other fieldsHigh correlation
규모1_건수 is highly overall correlated with 합계_건수 and 2 other fieldsHigh correlation
규모2_건수 is highly overall correlated with 번호 and 10 other fieldsHigh correlation
규모3_건수 is highly overall correlated with 번호 and 9 other fieldsHigh correlation
규모4_건수 is highly overall correlated with 합계_건수 and 7 other fieldsHigh correlation
규모5_건수 is highly overall correlated with 합계_건수 and 7 other fieldsHigh correlation
규모6_건수 is highly overall correlated with 번호 and 9 other fieldsHigh correlation
규모7_건수 is highly overall correlated with 합계_건수 and 6 other fieldsHigh correlation
규모8_건수 is highly overall correlated with 합계_건수 and 6 other fieldsHigh correlation
지역구분 레벨 is highly imbalanced (50.8%)Imbalance
번호 has unique valuesUnique
규모1_건수 has 3003 (30.0%) zerosZeros
규모2_건수 has 343 (3.4%) zerosZeros
규모3_건수 has 180 (1.8%) zerosZeros
규모4_건수 has 201 (2.0%) zerosZeros
규모5_건수 has 1877 (18.8%) zerosZeros
규모6_건수 has 1173 (11.7%) zerosZeros
규모7_건수 has 2847 (28.5%) zerosZeros
규모8_건수 has 4840 (48.4%) zerosZeros
규모9_건수 has 7163 (71.6%) zerosZeros

Reproduction

Analysis started2024-01-09 22:41:57.352026
Analysis finished2024-01-09 22:42:16.141889
Duration18.79 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%
Mean13446.565
Minimum2
Maximum26953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:16.203076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile1350.8
Q16708.75
median13477.5
Q320071.25
95-th percentile25577.1
Maximum26953
Range26951
Interquartile range (IQR)13362.5

Descriptive statistics

Standard deviation7760.509
Coefficient of variation (CV)0.57713691
Kurtosis-1.1952649
Mean13446.565
Median Absolute Deviation (MAD)6674
Skewness0.00059468742
Sum1.3446565 × 108
Variance60225500
MonotonicityNot monotonic
2024-01-10T07:42:16.317163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25786 1
 
< 0.1%
6765 1
 
< 0.1%
14271 1
 
< 0.1%
17981 1
 
< 0.1%
4650 1
 
< 0.1%
18581 1
 
< 0.1%
12057 1
 
< 0.1%
1434 1
 
< 0.1%
11803 1
 
< 0.1%
4731 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
12 1
< 0.1%
14 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
20 1
< 0.1%
ValueCountFrequency (%)
26953 1
< 0.1%
26952 1
< 0.1%
26951 1
< 0.1%
26950 1
< 0.1%
26941 1
< 0.1%
26940 1
< 0.1%
26938 1
< 0.1%
26937 1
< 0.1%
26923 1
< 0.1%
26919 1
< 0.1%

지역코드
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44415.21
Minimum44000
Maximum44825
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:16.415730image/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 deviation305.39853
Coefficient of variation (CV)0.0068759898
Kurtosis-1.7303773
Mean44415.21
Median Absolute Deviation (MAD)100
Skewness0.30647435
Sum4.441521 × 108
Variance93268.262
MonotonicityNot monotonic
2024-01-10T07:42:16.501542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
44710 634
 
6.3%
44770 590
 
5.9%
44150 584
 
5.8%
44180 579
 
5.8%
44230 573
 
5.7%
44000 571
 
5.7%
44130 570
 
5.7%
44810 570
 
5.7%
44200 569
 
5.7%
44790 567
 
5.7%
Other values (8) 4193
41.9%
ValueCountFrequency (%)
44000 571
5.7%
44130 570
5.7%
44131 515
5.1%
44133 497
5.0%
44150 584
5.8%
44180 579
5.8%
44200 569
5.7%
44210 556
5.6%
44230 573
5.7%
44250 556
5.6%
ValueCountFrequency (%)
44825 563
5.6%
44810 570
5.7%
44800 555
5.5%
44790 567
5.7%
44770 590
5.9%
44760 555
5.5%
44710 634
6.3%
44270 396
4.0%
44250 556
5.6%
44230 573
5.7%

지역명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
금산군
 
634
서천군
 
590
공주시
 
584
보령시
 
579
논산시
 
573
Other values (13)
7040 

Length

Max length3
Median length3
Mean length2.9429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
금산군 634
 
6.3%
서천군 590
 
5.9%
공주시 584
 
5.8%
보령시 579
 
5.8%
논산시 573
 
5.7%
충남 571
 
5.7%
천안시 570
 
5.7%
예산군 570
 
5.7%
아산시 569
 
5.7%
청양군 567
 
5.7%
Other values (8) 4193
41.9%

Length

2024-01-10T07:42:16.596222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
금산군 634
 
6.3%
서천군 590
 
5.9%
공주시 584
 
5.8%
보령시 579
 
5.8%
논산시 573
 
5.7%
충남 571
 
5.7%
천안시 570
 
5.7%
예산군 570
 
5.7%
아산시 569
 
5.7%
청양군 567
 
5.7%
Other values (8) 4193
41.9%

조사분기
Real number (ℝ)

Distinct213
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201494.24
Minimum200601
Maximum202309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:16.700262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200601
5-th percentile200701
Q1201102
median201507
Q3201911
95-th percentile202212
Maximum202309
Range1708
Interquartile range (IQR)809

Descriptive statistics

Standard deviation506.59709
Coefficient of variation (CV)0.0025142013
Kurtosis-1.1763768
Mean201494.24
Median Absolute Deviation (MAD)404
Skewness-0.109007
Sum2.0149424 × 109
Variance256640.61
MonotonicityNot monotonic
2024-01-10T07:42:16.842517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202005 70
 
0.7%
202101 68
 
0.7%
202204 65
 
0.7%
201211 64
 
0.6%
201903 64
 
0.6%
201901 63
 
0.6%
202001 61
 
0.6%
202009 61
 
0.6%
202109 60
 
0.6%
202011 60
 
0.6%
Other values (203) 9364
93.6%
ValueCountFrequency (%)
200601 42
0.4%
200602 32
0.3%
200603 36
0.4%
200604 44
0.4%
200605 41
0.4%
200606 43
0.4%
200607 47
0.5%
200608 43
0.4%
200609 35
0.4%
200610 38
0.4%
ValueCountFrequency (%)
202309 47
0.5%
202308 50
0.5%
202307 49
0.5%
202306 55
0.5%
202305 56
0.6%
202304 50
0.5%
202303 55
0.5%
202302 47
0.5%
202301 48
0.5%
202212 45
0.4%

합계_건수
Real number (ℝ)

HIGH CORRELATION 

Distinct2346
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean804.7772
Minimum0
Maximum25927
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:16.990569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18
Q181
median285.5
Q3730
95-th percentile3152
Maximum25927
Range25927
Interquartile range (IQR)649

Descriptive statistics

Standard deviation1796.1586
Coefficient of variation (CV)2.2318706
Kurtosis40.452786
Mean804.7772
Median Absolute Deviation (MAD)232.5
Skewness5.6076087
Sum8047772
Variance3226185.6
MonotonicityNot monotonic
2024-01-10T07:42:17.101231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18 49
 
0.5%
54 46
 
0.5%
66 44
 
0.4%
15 43
 
0.4%
58 42
 
0.4%
64 42
 
0.4%
60 42
 
0.4%
53 41
 
0.4%
17 40
 
0.4%
72 40
 
0.4%
Other values (2336) 9571
95.7%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 17
0.2%
2 17
0.2%
3 28
0.3%
4 21
0.2%
5 32
0.3%
6 28
0.3%
7 24
0.2%
8 20
0.2%
9 23
0.2%
ValueCountFrequency (%)
25927 1
< 0.1%
23450 1
< 0.1%
21064 1
< 0.1%
20906 1
< 0.1%
20109 1
< 0.1%
19191 1
< 0.1%
18895 1
< 0.1%
18555 1
< 0.1%
18388 1
< 0.1%
18183 1
< 0.1%

규모1_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1457
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean329.4596
Minimum0
Maximum17431
Zeros3003
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:17.217352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14
Q3186
95-th percentile1513.15
Maximum17431
Range17431
Interquartile range (IQR)186

Descriptive statistics

Standard deviation1076.0568
Coefficient of variation (CV)3.2661269
Kurtosis55.181084
Mean329.4596
Median Absolute Deviation (MAD)14
Skewness6.6212429
Sum3294596
Variance1157898.3
MonotonicityNot monotonic
2024-01-10T07:42:17.343212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3003
30.0%
1 704
 
7.0%
2 322
 
3.2%
3 212
 
2.1%
4 141
 
1.4%
5 126
 
1.3%
6 86
 
0.9%
8 74
 
0.7%
10 70
 
0.7%
7 67
 
0.7%
Other values (1447) 5195
51.9%
ValueCountFrequency (%)
0 3003
30.0%
1 704
 
7.0%
2 322
 
3.2%
3 212
 
2.1%
4 141
 
1.4%
5 126
 
1.3%
6 86
 
0.9%
7 67
 
0.7%
8 74
 
0.7%
9 59
 
0.6%
ValueCountFrequency (%)
17431 1
< 0.1%
14420 1
< 0.1%
14232 1
< 0.1%
13482 1
< 0.1%
13354 1
< 0.1%
12749 1
< 0.1%
12622 1
< 0.1%
12276 1
< 0.1%
12174 1
< 0.1%
11816 1
< 0.1%

규모2_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct736
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.9222
Minimum0
Maximum2422
Zeros343
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:17.482088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median32
Q3100
95-th percentile375.2
Maximum2422
Range2422
Interquartile range (IQR)93

Descriptive statistics

Standard deviation223.81059
Coefficient of variation (CV)2.2398485
Kurtosis32.72576
Mean99.9222
Median Absolute Deviation (MAD)29
Skewness5.2705218
Sum999222
Variance50091.181
MonotonicityNot monotonic
2024-01-10T07:42:17.629465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 355
 
3.5%
4 345
 
3.5%
0 343
 
3.4%
6 338
 
3.4%
3 330
 
3.3%
2 300
 
3.0%
7 285
 
2.9%
1 266
 
2.7%
8 263
 
2.6%
9 246
 
2.5%
Other values (726) 6929
69.3%
ValueCountFrequency (%)
0 343
3.4%
1 266
2.7%
2 300
3.0%
3 330
3.3%
4 345
3.5%
5 355
3.5%
6 338
3.4%
7 285
2.9%
8 263
2.6%
9 246
2.5%
ValueCountFrequency (%)
2422 1
< 0.1%
2420 1
< 0.1%
2217 1
< 0.1%
2201 1
< 0.1%
2195 1
< 0.1%
2178 1
< 0.1%
2092 1
< 0.1%
2062 1
< 0.1%
2052 1
< 0.1%
2025 1
< 0.1%

규모3_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct930
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.7814
Minimum0
Maximum4268
Zeros180
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:17.748869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q114
median37.5
Q379
95-th percentile640
Maximum4268
Range4268
Interquartile range (IQR)65

Descriptive statistics

Standard deviation266.46646
Coefficient of variation (CV)2.2623815
Kurtosis29.939942
Mean117.7814
Median Absolute Deviation (MAD)28.5
Skewness4.7001306
Sum1177814
Variance71004.376
MonotonicityNot monotonic
2024-01-10T07:42:17.852128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 298
 
3.0%
1 266
 
2.7%
3 264
 
2.6%
4 241
 
2.4%
5 218
 
2.2%
0 180
 
1.8%
6 174
 
1.7%
8 144
 
1.4%
7 143
 
1.4%
16 136
 
1.4%
Other values (920) 7936
79.4%
ValueCountFrequency (%)
0 180
1.8%
1 266
2.7%
2 298
3.0%
3 264
2.6%
4 241
2.4%
5 218
2.2%
6 174
1.7%
7 143
1.4%
8 144
1.4%
9 115
 
1.1%
ValueCountFrequency (%)
4268 1
< 0.1%
3055 1
< 0.1%
2912 1
< 0.1%
2847 1
< 0.1%
2839 1
< 0.1%
2796 1
< 0.1%
2734 1
< 0.1%
2644 1
< 0.1%
2630 1
< 0.1%
2591 1
< 0.1%

규모4_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1061
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.7301
Minimum0
Maximum6362
Zeros201
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:17.957955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q115
median52
Q3112
95-th percentile867
Maximum6362
Range6362
Interquartile range (IQR)97

Descriptive statistics

Standard deviation387.77532
Coefficient of variation (CV)2.3829354
Kurtosis43.989963
Mean162.7301
Median Absolute Deviation (MAD)43
Skewness5.5183357
Sum1627301
Variance150369.7
MonotonicityNot monotonic
2024-01-10T07:42:18.067259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 269
 
2.7%
2 265
 
2.6%
3 244
 
2.4%
4 205
 
2.1%
5 202
 
2.0%
0 201
 
2.0%
6 162
 
1.6%
7 161
 
1.6%
8 145
 
1.5%
11 113
 
1.1%
Other values (1051) 8033
80.3%
ValueCountFrequency (%)
0 201
2.0%
1 269
2.7%
2 265
2.6%
3 244
2.4%
4 205
2.1%
5 202
2.0%
6 162
1.6%
7 161
1.6%
8 145
1.5%
9 111
1.1%
ValueCountFrequency (%)
6362 1
< 0.1%
5809 1
< 0.1%
5359 1
< 0.1%
5335 1
< 0.1%
5178 1
< 0.1%
4691 1
< 0.1%
4645 1
< 0.1%
4579 1
< 0.1%
4545 1
< 0.1%
4212 1
< 0.1%

규모5_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct404
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.9869
Minimum0
Maximum2001
Zeros1877
Zeros (%)18.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:18.186164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median9
Q351.25
95-th percentile132
Maximum2001
Range2001
Interquartile range (IQR)50.25

Descriptive statistics

Standard deviation156.55445
Coefficient of variation (CV)3.1958431
Kurtosis61.829123
Mean48.9869
Median Absolute Deviation (MAD)9
Skewness7.4377753
Sum489869
Variance24509.295
MonotonicityNot monotonic
2024-01-10T07:42:18.307485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1877
 
18.8%
1 668
 
6.7%
2 504
 
5.0%
3 437
 
4.4%
4 358
 
3.6%
5 332
 
3.3%
6 305
 
3.0%
7 292
 
2.9%
9 237
 
2.4%
8 200
 
2.0%
Other values (394) 4790
47.9%
ValueCountFrequency (%)
0 1877
18.8%
1 668
 
6.7%
2 504
 
5.0%
3 437
 
4.4%
4 358
 
3.6%
5 332
 
3.3%
6 305
 
3.0%
7 292
 
2.9%
8 200
 
2.0%
9 237
 
2.4%
ValueCountFrequency (%)
2001 1
< 0.1%
1987 1
< 0.1%
1972 1
< 0.1%
1890 1
< 0.1%
1846 1
< 0.1%
1844 1
< 0.1%
1826 1
< 0.1%
1822 1
< 0.1%
1819 1
< 0.1%
1799 1
< 0.1%

규모6_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct413
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.0533
Minimum0
Maximum951
Zeros1173
Zeros (%)11.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:18.440446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median8
Q320
95-th percentile155
Maximum951
Range951
Interquartile range (IQR)18

Descriptive statistics

Standard deviation69.556158
Coefficient of variation (CV)2.394088
Kurtosis31.766017
Mean29.0533
Median Absolute Deviation (MAD)7
Skewness4.9774283
Sum290533
Variance4838.0591
MonotonicityNot monotonic
2024-01-10T07:42:18.551107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1173
 
11.7%
1 764
 
7.6%
2 626
 
6.3%
3 493
 
4.9%
4 489
 
4.9%
5 455
 
4.5%
6 393
 
3.9%
8 357
 
3.6%
7 355
 
3.5%
10 300
 
3.0%
Other values (403) 4595
46.0%
ValueCountFrequency (%)
0 1173
11.7%
1 764
7.6%
2 626
6.3%
3 493
4.9%
4 489
4.9%
5 455
 
4.5%
6 393
 
3.9%
7 355
 
3.5%
8 357
 
3.6%
9 270
 
2.7%
ValueCountFrequency (%)
951 1
< 0.1%
810 1
< 0.1%
804 1
< 0.1%
794 1
< 0.1%
756 1
< 0.1%
723 1
< 0.1%
715 1
< 0.1%
702 1
< 0.1%
665 1
< 0.1%
662 1
< 0.1%

규모7_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct202
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9619
Minimum0
Maximum519
Zeros2847
Zeros (%)28.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:18.661891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q39
95-th percentile38
Maximum519
Range519
Interquartile range (IQR)9

Descriptive statistics

Standard deviation26.600718
Coefficient of variation (CV)2.6702455
Kurtosis62.794088
Mean9.9619
Median Absolute Deviation (MAD)3
Skewness6.6447171
Sum99619
Variance707.59821
MonotonicityNot monotonic
2024-01-10T07:42:19.013096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2847
28.5%
1 1140
11.4%
2 812
 
8.1%
3 629
 
6.3%
4 522
 
5.2%
5 433
 
4.3%
6 406
 
4.1%
7 344
 
3.4%
8 324
 
3.2%
10 254
 
2.5%
Other values (192) 2289
22.9%
ValueCountFrequency (%)
0 2847
28.5%
1 1140
11.4%
2 812
 
8.1%
3 629
 
6.3%
4 522
 
5.2%
5 433
 
4.3%
6 406
 
4.1%
7 344
 
3.4%
8 324
 
3.2%
9 251
 
2.5%
ValueCountFrequency (%)
519 1
< 0.1%
475 1
< 0.1%
421 1
< 0.1%
323 1
< 0.1%
315 1
< 0.1%
310 1
< 0.1%
305 1
< 0.1%
304 1
< 0.1%
303 1
< 0.1%
301 1
< 0.1%

규모8_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct86
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2378
Minimum0
Maximum177
Zeros4840
Zeros (%)48.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:19.118804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile13
Maximum177
Range177
Interquartile range (IQR)3

Descriptive statistics

Standard deviation8.8509709
Coefficient of variation (CV)2.7336373
Kurtosis63.705741
Mean3.2378
Median Absolute Deviation (MAD)1
Skewness6.4917159
Sum32378
Variance78.339685
MonotonicityNot monotonic
2024-01-10T07:42:19.234602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4840
48.4%
1 1409
 
14.1%
2 930
 
9.3%
3 690
 
6.9%
4 528
 
5.3%
5 344
 
3.4%
6 261
 
2.6%
7 169
 
1.7%
8 114
 
1.1%
9 76
 
0.8%
Other values (76) 639
 
6.4%
ValueCountFrequency (%)
0 4840
48.4%
1 1409
 
14.1%
2 930
 
9.3%
3 690
 
6.9%
4 528
 
5.3%
5 344
 
3.4%
6 261
 
2.6%
7 169
 
1.7%
8 114
 
1.1%
9 76
 
0.8%
ValueCountFrequency (%)
177 1
< 0.1%
168 1
< 0.1%
153 1
< 0.1%
105 1
< 0.1%
99 2
< 0.1%
97 1
< 0.1%
96 1
< 0.1%
94 1
< 0.1%
92 1
< 0.1%
89 1
< 0.1%

규모9_건수
Real number (ℝ)

ZEROS 

Distinct136
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6441
Minimum0
Maximum204
Zeros7163
Zeros (%)71.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T07:42:19.352604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile17
Maximum204
Range204
Interquartile range (IQR)1

Descriptive statistics

Standard deviation14.626901
Coefficient of variation (CV)4.0138583
Kurtosis65.255547
Mean3.6441
Median Absolute Deviation (MAD)0
Skewness7.408241
Sum36441
Variance213.94623
MonotonicityNot monotonic
2024-01-10T07:42:19.487121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7163
71.6%
1 519
 
5.2%
2 433
 
4.3%
3 321
 
3.2%
4 232
 
2.3%
5 150
 
1.5%
6 130
 
1.3%
7 111
 
1.1%
8 78
 
0.8%
9 64
 
0.6%
Other values (126) 799
 
8.0%
ValueCountFrequency (%)
0 7163
71.6%
1 519
 
5.2%
2 433
 
4.3%
3 321
 
3.2%
4 232
 
2.3%
5 150
 
1.5%
6 130
 
1.3%
7 111
 
1.1%
8 78
 
0.8%
9 64
 
0.6%
ValueCountFrequency (%)
204 1
< 0.1%
200 1
< 0.1%
192 1
< 0.1%
179 1
< 0.1%
175 2
< 0.1%
173 1
< 0.1%
172 1
< 0.1%
171 1
< 0.1%
169 2
< 0.1%
168 2
< 0.1%

지역구분 레벨
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8417 
2
1012 
0
 
571

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 8417
84.2%
2 1012
 
10.1%
0 571
 
5.7%

Length

2024-01-10T07:42:19.604816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:42:19.686324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8417
84.2%
2 1012
 
10.1%
0 571
 
5.7%

Interactions

2024-01-10T07:42:14.556146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:00.907457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:02.186540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:03.292464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:04.558349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:05.815028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.002347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.999210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.997655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:10.147205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.484596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.479164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.500508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:14.647982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:00.979424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:02.291937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:03.391437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:04.629951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:05.898592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.084802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.075708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:09.093399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:10.482005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.565459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.553805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.582068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:14.723506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:01.053230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:02.384132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:03.474378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:04.710433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:05.977527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.157972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.152399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:09.174122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:10.555602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.641098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.631887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.662968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:14.807039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:01.132412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:02.481559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:03.567520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:04.791049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:06.060147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.238644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.230211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:09.265546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:10.636940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.720524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.715876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.748279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:14.884816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:01.213999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:02.553668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:03.669779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:04.869833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:06.139119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.312184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.304543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:09.343955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:10.716254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.796156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.790120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.831389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:14.978799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:01.300608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:02.635831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:03.776270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:05.179513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:06.219962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.390684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.386958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:09.427264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:10.801345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.876209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.871718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.919437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:15.058309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:01.377808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:02.709229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:03.879392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:05.252504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:06.302168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.464027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.473802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:09.501030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:10.880275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.950877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.943843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.995457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:15.399727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:01.454096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:02.780786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:03.974675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:05.321587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:06.396536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.532560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.541656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:09.573529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:10.955776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.018260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.016014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:14.070620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:15.475904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:01.535619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:02.873517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:04.081887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:05.399122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:06.490970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.609474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.615196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:09.667940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.039157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.095004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.092005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:14.152697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:15.563348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:01.673256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:02.956192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:04.191586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:05.482030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:06.598842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.689553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.698174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:09.772462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.133456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.176222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.180233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:14.240382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:15.640242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:01.795092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:03.027380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:04.285279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:05.570768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:06.697211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.762232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.766299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:09.866219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.220785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.244072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.263135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:14.313368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:15.717021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:01.913650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:03.100102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:04.386146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:05.645127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:06.797680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.835158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.837269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:09.961223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.299181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.319804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.337123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:14.391561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:15.798940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:02.036755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:03.186308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:04.473339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:05.724968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:06.902054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:07.913780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:08.917318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:10.054879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:11.388832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:12.396221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:13.418638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:42:14.470812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:42:19.751527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드지역명조사분기합계_건수규모1_건수규모2_건수규모3_건수규모4_건수규모5_건수규모6_건수규모7_건수규모8_건수규모9_건수지역구분 레벨
번호1.0000.9960.9810.2310.5970.4650.6220.4740.5790.4120.5940.3850.3990.4370.868
지역코드0.9961.0001.0000.1210.1550.1860.1860.1510.1300.0440.1500.0580.1060.1620.524
지역명0.9811.0001.0000.1440.6110.4850.6270.6910.5780.4380.5790.5910.5340.4321.000
조사분기0.2310.1210.1441.0000.0580.0690.0880.0640.0890.0810.0950.0510.0380.1220.121
합계_건수0.5970.1550.6110.0581.0000.9480.9090.5890.7370.8130.6850.6540.5720.4840.731
규모1_건수0.4650.1860.4850.0690.9481.0000.8420.3370.4520.7410.4500.5420.4010.0000.557
규모2_건수0.6220.1860.6270.0880.9090.8421.0000.6110.7200.8310.7080.6970.5690.5220.749
규모3_건수0.4740.1510.6910.0640.5890.3370.6111.0000.7940.5290.6390.6890.5480.5560.859
규모4_건수0.5790.1300.5780.0890.7370.4520.7200.7941.0000.7270.7920.5490.5500.6320.696
규모5_건수0.4120.0440.4380.0810.8130.7410.8310.5290.7271.0000.6980.7180.5960.3800.552
규모6_건수0.5940.1500.5790.0950.6850.4500.7080.6390.7920.6981.0000.6040.5540.6460.685
규모7_건수0.3850.0580.5910.0510.6540.5420.6970.6890.5490.7180.6041.0000.6710.4370.772
규모8_건수0.3990.1060.5340.0380.5720.4010.5690.5480.5500.5960.5540.6711.0000.5080.611
규모9_건수0.4370.1620.4320.1220.4840.0000.5220.5560.6320.3800.6460.4370.5081.0000.479
지역구분 레벨0.8680.5241.0000.1210.7310.5570.7490.8590.6960.5520.6850.7720.6110.4791.000
2024-01-10T07:42:19.870218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역명지역구분 레벨
지역명1.0000.999
지역구분 레벨0.9991.000
2024-01-10T07:42:19.951175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지역코드조사분기합계_건수규모1_건수규모2_건수규모3_건수규모4_건수규모5_건수규모6_건수규모7_건수규모8_건수규모9_건수지역명지역구분 레벨
번호1.0000.9980.030-0.595-0.282-0.570-0.515-0.484-0.330-0.511-0.442-0.381-0.2290.9030.797
지역코드0.9981.000-0.021-0.595-0.281-0.569-0.518-0.487-0.329-0.510-0.440-0.379-0.2330.9990.837
조사분기0.030-0.0211.0000.1120.1400.0800.0820.1030.1150.0380.0430.0330.0220.0560.074
합계_건수-0.595-0.5950.1121.0000.7120.9230.7390.7600.7900.7650.7460.5630.1200.2860.596
규모1_건수-0.282-0.2810.1400.7121.0000.6950.2040.2330.6990.2910.4380.304-0.2970.2080.401
규모2_건수-0.570-0.5690.0800.9230.6951.0000.6970.6920.7700.7180.7310.5570.0840.2970.619
규모3_건수-0.515-0.5180.0820.7390.2040.6971.0000.9310.6190.8630.7730.6210.3830.3020.578
규모4_건수-0.484-0.4870.1030.7600.2330.6920.9311.0000.6520.8780.7910.6290.3670.2640.552
규모5_건수-0.330-0.3290.1150.7900.6990.7700.6190.6521.0000.6590.7690.6380.0810.1830.395
규모6_건수-0.511-0.5100.0380.7650.2910.7180.8630.8780.6591.0000.8000.6220.3780.2640.538
규모7_건수-0.442-0.4400.0430.7460.4380.7310.7730.7910.7690.8001.0000.7070.2730.2360.476
규모8_건수-0.381-0.3790.0330.5630.3040.5570.6210.6290.6380.6220.7071.0000.4000.2570.480
규모9_건수-0.229-0.2330.0220.120-0.2970.0840.3830.3670.0810.3780.2730.4001.0000.1800.328
지역명0.9030.9990.0560.2860.2080.2970.3020.2640.1830.2640.2360.2570.1801.0000.999
지역구분 레벨0.7970.8370.0740.5960.4010.6190.5780.5520.3950.5380.4760.4800.3280.9991.000

Missing values

2024-01-10T07:42:15.915551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:42:16.071654image/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

번호지역코드지역명조사분기합계_건수규모1_건수규모2_건수규모3_건수규모4_건수규모5_건수규모6_건수규모7_건수규모8_건수규모9_건수지역구분 레벨
257852578644825태안군201905568223724971913626001
4676467744133서북구2013101224161317304317167786182
1369137044000충남2021109307111688229351782315668164950
8577857844180보령시202006139015415111124141
191071910844760부여군20220959091423920111
7540754144180보령시2010061931542624430001
8208820944180보령시20160598093334562361
3946394744131동남구20180710320842067122234012
203412034244770서천군20190340315853386075154001
53453544000충남201107442111799141914471324188121930
번호지역코드지역명조사분기합계_건수규모1_건수규모2_건수규모3_건수규모4_건수규모5_건수규모6_건수규모7_건수규모8_건수규모9_건수지역구분 레벨
204542045544770서천군2020061961741532110001
199961999744770서천군2015016652911120001
205072050844770서천군20201148031318362121
250932509444810예산군20200554824475627472117301
4410441144131동남구202306622877161277463163132
8726872744180보령시2022031230203843383441
188051880644760부여군201905760623241353201
226762267744800홍성군20101295051962132031
129801298144230논산시20170917438487415106191
197361973744770서천군201109650118293111111