Overview

Dataset statistics

Number of variables15
Number of observations9721
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory134.0 B

Variable types

Numeric14
Text1

Dataset

Description한국부동산원(구.한국감정원)의 청약홈에서 제공하는 APT(아파트) 주택형별 분양정보 데이터로 공고번호, 모델번호, 주택형, 주택공급면적, 일반공급세대수, 특별공급세대수, 공급금액(분양최고금액)등의 데이터를 제공합니다.- 공급금액(분양최고금액) 단위 : 만원
Author한국부동산원
URLhttps://www.data.go.kr/data/15101047/fileData.do

Alerts

주택관리번호 is highly overall correlated with 공고번호High correlation
공고번호 is highly overall correlated with 주택관리번호High correlation
주택공급면적 is highly overall correlated with 공급금액_분양최고금액High correlation
일반공급세대수 is highly overall correlated with 특별공급세대수 and 4 other fieldsHigh correlation
특별공급세대수 is highly overall correlated with 일반공급세대수 and 5 other fieldsHigh correlation
특별공급_다자녀가구세대수 is highly overall correlated with 일반공급세대수 and 5 other fieldsHigh correlation
특별공급_신혼부부세대수 is highly overall correlated with 일반공급세대수 and 5 other fieldsHigh correlation
특별공급_생애최초세대수 is highly overall correlated with 특별공급세대수 and 4 other fieldsHigh correlation
특별공급_노부모부양세대수 is highly overall correlated with 일반공급세대수 and 5 other fieldsHigh correlation
특별공급_기관추천세대수 is highly overall correlated with 일반공급세대수 and 5 other fieldsHigh correlation
공급금액_분양최고금액 is highly overall correlated with 주택공급면적High correlation
일반공급세대수 has 162 (1.7%) zerosZeros
특별공급세대수 has 2102 (21.6%) zerosZeros
특별공급_다자녀가구세대수 has 2719 (28.0%) zerosZeros
특별공급_신혼부부세대수 has 3369 (34.7%) zerosZeros
특별공급_생애최초세대수 has 4742 (48.8%) zerosZeros
특별공급_노부모부양세대수 has 3653 (37.6%) zerosZeros
특별공급_기관추천세대수 has 3698 (38.0%) zerosZeros
특별공급_기관추천기타세대수 has 9508 (97.8%) zerosZeros
특별공급_이전기관세대수 has 9515 (97.9%) zerosZeros

Reproduction

Analysis started2024-03-16 04:16:05.384174
Analysis finished2024-03-16 04:16:49.207819
Duration43.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주택관리번호
Real number (ℝ)

HIGH CORRELATION 

Distinct1863
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.021426 × 109
Minimum2.02 × 109
Maximum2.02482 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:49.365574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.02 × 109
5-th percentile2.0200005 × 109
Q12.0200014 × 109
median2.0210009 × 109
Q32.0220008 × 109
95-th percentile2.0230007 × 109
Maximum2.02482 × 109
Range4820003
Interquartile range (IQR)1999419

Descriptive statistics

Standard deviation1154008.3
Coefficient of variation (CV)0.00057088822
Kurtosis-0.94923361
Mean2.021426 × 109
Median Absolute Deviation (MAD)999753
Skewness0.30530926
Sum1.9650282 × 1013
Variance1.3317351 × 1012
MonotonicityDecreasing
2024-03-16T13:16:49.629846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2021000540 38
 
0.4%
2021000025 28
 
0.3%
2023000633 27
 
0.3%
2021000057 27
 
0.3%
2021000516 26
 
0.3%
2021000026 26
 
0.3%
2020000415 25
 
0.3%
2020001464 22
 
0.2%
2022000092 22
 
0.2%
2023000408 22
 
0.2%
Other values (1853) 9458
97.3%
ValueCountFrequency (%)
2020000001 3
 
< 0.1%
2020000005 11
0.1%
2020000007 4
 
< 0.1%
2020000009 2
 
< 0.1%
2020000010 4
 
< 0.1%
2020000028 2
 
< 0.1%
2020000040 8
0.1%
2020000041 5
0.1%
2020000046 4
 
< 0.1%
2020000047 12
0.1%
ValueCountFrequency (%)
2024820004 1
 
< 0.1%
2024820003 1
 
< 0.1%
2024820002 1
 
< 0.1%
2024000094 3
 
< 0.1%
2024000091 6
0.1%
2024000090 3
 
< 0.1%
2024000089 7
0.1%
2024000088 11
0.1%
2024000087 12
0.1%
2024000086 7
0.1%

공고번호
Real number (ℝ)

HIGH CORRELATION 

Distinct1863
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.021426 × 109
Minimum2.02 × 109
Maximum2.02482 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:49.855538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.02 × 109
5-th percentile2.0200005 × 109
Q12.0200014 × 109
median2.0210009 × 109
Q32.0220008 × 109
95-th percentile2.0230007 × 109
Maximum2.02482 × 109
Range4820003
Interquartile range (IQR)1999419

Descriptive statistics

Standard deviation1154008.3
Coefficient of variation (CV)0.00057088822
Kurtosis-0.94923361
Mean2.021426 × 109
Median Absolute Deviation (MAD)999753
Skewness0.30530926
Sum1.9650282 × 1013
Variance1.3317351 × 1012
MonotonicityDecreasing
2024-03-16T13:16:50.114949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2021000540 38
 
0.4%
2021000025 28
 
0.3%
2023000633 27
 
0.3%
2021000057 27
 
0.3%
2021000516 26
 
0.3%
2021000026 26
 
0.3%
2020000415 25
 
0.3%
2020001464 22
 
0.2%
2022000092 22
 
0.2%
2023000408 22
 
0.2%
Other values (1853) 9458
97.3%
ValueCountFrequency (%)
2020000001 3
 
< 0.1%
2020000005 11
0.1%
2020000007 4
 
< 0.1%
2020000009 2
 
< 0.1%
2020000010 4
 
< 0.1%
2020000028 2
 
< 0.1%
2020000040 8
0.1%
2020000041 5
0.1%
2020000046 4
 
< 0.1%
2020000047 12
0.1%
ValueCountFrequency (%)
2024820004 1
 
< 0.1%
2024820003 1
 
< 0.1%
2024820002 1
 
< 0.1%
2024000094 3
 
< 0.1%
2024000091 6
0.1%
2024000090 3
 
< 0.1%
2024000089 7
0.1%
2024000088 11
0.1%
2024000087 12
0.1%
2024000086 7
0.1%

모델번호
Real number (ℝ)

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1742619
Minimum1
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:50.399959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile10
Maximum38
Range37
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.5431322
Coefficient of variation (CV)0.84880449
Kurtosis11.520676
Mean4.1742619
Median Absolute Deviation (MAD)2
Skewness2.6410973
Sum40578
Variance12.553786
MonotonicityNot monotonic
2024-03-16T13:16:50.648007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1 1863
19.2%
2 1784
18.4%
3 1574
16.2%
4 1260
13.0%
5 916
9.4%
6 683
 
7.0%
7 462
 
4.8%
8 335
 
3.4%
9 215
 
2.2%
10 146
 
1.5%
Other values (28) 483
 
5.0%
ValueCountFrequency (%)
1 1863
19.2%
2 1784
18.4%
3 1574
16.2%
4 1260
13.0%
5 916
9.4%
6 683
 
7.0%
7 462
 
4.8%
8 335
 
3.4%
9 215
 
2.2%
10 146
 
1.5%
ValueCountFrequency (%)
38 1
< 0.1%
37 1
< 0.1%
36 1
< 0.1%
35 1
< 0.1%
34 1
< 0.1%
33 1
< 0.1%
32 1
< 0.1%
31 1
< 0.1%
30 1
< 0.1%
29 1
< 0.1%
Distinct7927
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size76.1 KiB
2024-03-16T13:16:51.086276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters87489
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6902 ?
Unique (%)71.0%

Sample

1st row055.9800A
2nd row055.0000A
3rd row056.1000A
4th row084.9556A
5th row084.9484B
ValueCountFrequency (%)
084.9900a 27
 
0.3%
084.9900b 24
 
0.2%
059.9900a 22
 
0.2%
084.9700a 18
 
0.2%
084.9800a 18
 
0.2%
084.9900c 17
 
0.2%
084.9800b 17
 
0.2%
084.9600a 16
 
0.2%
084.9600b 15
 
0.2%
059.9900b 15
 
0.2%
Other values (7917) 9532
98.1%
2024-03-16T13:16:51.711567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15761
18.0%
9 10202
11.7%
. 9721
11.1%
8 8460
9.7%
4 7708
8.8%
5 5516
 
6.3%
7 5147
 
5.9%
1 4788
 
5.5%
6 4044
 
4.6%
3 3219
 
3.7%
Other values (25) 12923
14.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68047
77.8%
Other Punctuation 9721
 
11.1%
Uppercase Letter 7547
 
8.6%
Space Separator 2174
 
2.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 2771
36.7%
B 2458
32.6%
C 1093
 
14.5%
D 440
 
5.8%
E 179
 
2.4%
P 160
 
2.1%
F 102
 
1.4%
T 101
 
1.3%
G 60
 
0.8%
H 54
 
0.7%
Other values (13) 129
 
1.7%
Decimal Number
ValueCountFrequency (%)
0 15761
23.2%
9 10202
15.0%
8 8460
12.4%
4 7708
11.3%
5 5516
 
8.1%
7 5147
 
7.6%
1 4788
 
7.0%
6 4044
 
5.9%
3 3219
 
4.7%
2 3202
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 9721
100.0%
Space Separator
ValueCountFrequency (%)
2174
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79942
91.4%
Latin 7547
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 2771
36.7%
B 2458
32.6%
C 1093
 
14.5%
D 440
 
5.8%
E 179
 
2.4%
P 160
 
2.1%
F 102
 
1.4%
T 101
 
1.3%
G 60
 
0.8%
H 54
 
0.7%
Other values (13) 129
 
1.7%
Common
ValueCountFrequency (%)
0 15761
19.7%
9 10202
12.8%
. 9721
12.2%
8 8460
10.6%
4 7708
9.6%
5 5516
 
6.9%
7 5147
 
6.4%
1 4788
 
6.0%
6 4044
 
5.1%
3 3219
 
4.0%
Other values (2) 5376
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 87489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15761
18.0%
9 10202
11.7%
. 9721
11.1%
8 8460
9.7%
4 7708
8.8%
5 5516
 
6.3%
7 5147
 
5.9%
1 4788
 
5.5%
6 4044
 
4.6%
3 3219
 
3.7%
Other values (25) 12923
14.8%

주택공급면적
Real number (ℝ)

HIGH CORRELATION 

Distinct8944
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.78663
Minimum22.348
Maximum352.1486
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:51.993578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22.348
5-th percentile70.4572
Q186.5085
median109.8121
Q3115.5746
95-th percentile167.9387
Maximum352.1486
Range329.8006
Interquartile range (IQR)29.0661

Descriptive statistics

Standard deviation33.229062
Coefficient of variation (CV)0.30266948
Kurtosis8.6544258
Mean109.78663
Median Absolute Deviation (MAD)12.1658
Skewness2.0983222
Sum1067235.8
Variance1104.1705
MonotonicityNot monotonic
2024-03-16T13:16:53.095302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
78.4955 7
 
0.1%
109.0504 5
 
0.1%
104.7567 5
 
0.1%
104.4264 5
 
0.1%
110.7176 5
 
0.1%
80.0 4
 
< 0.1%
114.0357 4
 
< 0.1%
122.5305 4
 
< 0.1%
92.6561 4
 
< 0.1%
149.2203 4
 
< 0.1%
Other values (8934) 9674
99.5%
ValueCountFrequency (%)
22.348 1
< 0.1%
23.75 1
< 0.1%
23.941 1
< 0.1%
24.05 1
< 0.1%
24.8567 1
< 0.1%
25.1982 1
< 0.1%
25.9949 1
< 0.1%
26.3273 1
< 0.1%
26.7687 1
< 0.1%
27.0238 1
< 0.1%
ValueCountFrequency (%)
352.1486 1
< 0.1%
347.9733 1
< 0.1%
343.9042 1
< 0.1%
336.0249 1
< 0.1%
334.0508 1
< 0.1%
333.8175 1
< 0.1%
332.0497 1
< 0.1%
330.9672 1
< 0.1%
329.3679 1
< 0.1%
328.4022 1
< 0.1%

일반공급세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct382
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.808044
Minimum0
Maximum936
Zeros162
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:53.366435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median24
Q363
95-th percentile176
Maximum936
Range936
Interquartile range (IQR)56

Descriptive statistics

Standard deviation66.01872
Coefficient of variation (CV)1.3809124
Kurtosis16.651478
Mean47.808044
Median Absolute Deviation (MAD)20
Skewness3.2142428
Sum464742
Variance4358.4714
MonotonicityNot monotonic
2024-03-16T13:16:53.660794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 640
 
6.6%
2 435
 
4.5%
4 290
 
3.0%
6 261
 
2.7%
3 239
 
2.5%
7 218
 
2.2%
8 216
 
2.2%
5 211
 
2.2%
10 202
 
2.1%
9 195
 
2.0%
Other values (372) 6814
70.1%
ValueCountFrequency (%)
0 162
 
1.7%
1 640
6.6%
2 435
4.5%
3 239
 
2.5%
4 290
3.0%
5 211
 
2.2%
6 261
2.7%
7 218
 
2.2%
8 216
 
2.2%
9 195
 
2.0%
ValueCountFrequency (%)
936 1
< 0.1%
759 1
< 0.1%
744 1
< 0.1%
610 1
< 0.1%
594 1
< 0.1%
563 1
< 0.1%
551 1
< 0.1%
544 1
< 0.1%
541 1
< 0.1%
532 1
< 0.1%

특별공급세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct396
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.287316
Minimum0
Maximum994
Zeros2102
Zeros (%)21.6%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:53.940369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median16
Q354
95-th percentile179
Maximum994
Range994
Interquartile range (IQR)52

Descriptive statistics

Standard deviation71.548876
Coefficient of variation (CV)1.6528832
Kurtosis20.120917
Mean43.287316
Median Absolute Deviation (MAD)16
Skewness3.6105755
Sum420796
Variance5119.2416
MonotonicityNot monotonic
2024-03-16T13:16:54.186438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2102
 
21.6%
1 308
 
3.2%
5 279
 
2.9%
4 220
 
2.3%
6 217
 
2.2%
2 202
 
2.1%
10 188
 
1.9%
9 183
 
1.9%
3 173
 
1.8%
8 164
 
1.7%
Other values (386) 5685
58.5%
ValueCountFrequency (%)
0 2102
21.6%
1 308
 
3.2%
2 202
 
2.1%
3 173
 
1.8%
4 220
 
2.3%
5 279
 
2.9%
6 217
 
2.2%
7 114
 
1.2%
8 164
 
1.7%
9 183
 
1.9%
ValueCountFrequency (%)
994 1
< 0.1%
825 1
< 0.1%
773 1
< 0.1%
756 1
< 0.1%
737 1
< 0.1%
715 1
< 0.1%
674 1
< 0.1%
643 1
< 0.1%
629 1
< 0.1%
626 1
< 0.1%

특별공급_다자녀가구세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct103
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3597367
Minimum0
Maximum158
Zeros2719
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:54.429406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q311
95-th percentile33
Maximum158
Range158
Interquartile range (IQR)11

Descriptive statistics

Standard deviation12.662016
Coefficient of variation (CV)1.5146429
Kurtosis15.644964
Mean8.3597367
Median Absolute Deviation (MAD)4
Skewness3.1562161
Sum81265
Variance160.32665
MonotonicityNot monotonic
2024-03-16T13:16:54.673775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2719
28.0%
2 786
 
8.1%
1 767
 
7.9%
3 529
 
5.4%
4 516
 
5.3%
5 398
 
4.1%
6 330
 
3.4%
7 319
 
3.3%
8 316
 
3.3%
10 257
 
2.6%
Other values (93) 2784
28.6%
ValueCountFrequency (%)
0 2719
28.0%
1 767
 
7.9%
2 786
 
8.1%
3 529
 
5.4%
4 516
 
5.3%
5 398
 
4.1%
6 330
 
3.4%
7 319
 
3.3%
8 316
 
3.3%
9 232
 
2.4%
ValueCountFrequency (%)
158 1
< 0.1%
151 1
< 0.1%
136 1
< 0.1%
129 1
< 0.1%
112 1
< 0.1%
111 1
< 0.1%
108 1
< 0.1%
107 1
< 0.1%
105 2
< 0.1%
100 2
< 0.1%

특별공급_신혼부부세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct186
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.357474
Minimum0
Maximum303
Zeros3369
Zeros (%)34.7%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:54.938142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q320
95-th percentile66
Maximum303
Range303
Interquartile range (IQR)20

Descriptive statistics

Standard deviation25.860962
Coefficient of variation (CV)1.6839334
Kurtosis16.39698
Mean15.357474
Median Absolute Deviation (MAD)5
Skewness3.3329984
Sum149290
Variance668.78938
MonotonicityNot monotonic
2024-03-16T13:16:55.187158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3369
34.7%
2 364
 
3.7%
3 357
 
3.7%
1 349
 
3.6%
4 339
 
3.5%
5 279
 
2.9%
6 235
 
2.4%
8 220
 
2.3%
7 219
 
2.3%
10 213
 
2.2%
Other values (176) 3777
38.9%
ValueCountFrequency (%)
0 3369
34.7%
1 349
 
3.6%
2 364
 
3.7%
3 357
 
3.7%
4 339
 
3.5%
5 279
 
2.9%
6 235
 
2.4%
7 219
 
2.3%
8 220
 
2.3%
9 182
 
1.9%
ValueCountFrequency (%)
303 1
< 0.1%
301 1
< 0.1%
268 1
< 0.1%
246 1
< 0.1%
232 1
< 0.1%
227 1
< 0.1%
225 1
< 0.1%
224 1
< 0.1%
216 1
< 0.1%
214 1
< 0.1%

특별공급_생애최초세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct134
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4175496
Minimum0
Maximum245
Zeros4742
Zeros (%)48.8%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:55.438832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q38
95-th percentile36
Maximum245
Range245
Interquartile range (IQR)8

Descriptive statistics

Standard deviation16.347594
Coefficient of variation (CV)2.2039077
Kurtosis34.376107
Mean7.4175496
Median Absolute Deviation (MAD)1
Skewness4.7332552
Sum72106
Variance267.24384
MonotonicityNot monotonic
2024-03-16T13:16:55.730708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4742
48.8%
1 628
 
6.5%
2 525
 
5.4%
3 420
 
4.3%
4 302
 
3.1%
5 248
 
2.6%
7 205
 
2.1%
6 201
 
2.1%
8 161
 
1.7%
10 152
 
1.6%
Other values (124) 2137
22.0%
ValueCountFrequency (%)
0 4742
48.8%
1 628
 
6.5%
2 525
 
5.4%
3 420
 
4.3%
4 302
 
3.1%
5 248
 
2.6%
6 201
 
2.1%
7 205
 
2.1%
8 161
 
1.7%
9 152
 
1.6%
ValueCountFrequency (%)
245 1
< 0.1%
227 1
< 0.1%
214 1
< 0.1%
210 1
< 0.1%
199 2
< 0.1%
172 1
< 0.1%
166 1
< 0.1%
164 1
< 0.1%
162 1
< 0.1%
159 2
< 0.1%

특별공급_노부모부양세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4983026
Minimum0
Maximum45
Zeros3653
Zeros (%)37.6%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:55.925488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile10
Maximum45
Range45
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.8926202
Coefficient of variation (CV)1.5581059
Kurtosis14.123834
Mean2.4983026
Median Absolute Deviation (MAD)1
Skewness3.1255321
Sum24286
Variance15.152492
MonotonicityNot monotonic
2024-03-16T13:16:56.139484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 3653
37.6%
1 1910
19.6%
2 1091
 
11.2%
3 795
 
8.2%
4 544
 
5.6%
5 415
 
4.3%
6 271
 
2.8%
7 209
 
2.1%
8 170
 
1.7%
9 122
 
1.3%
Other values (27) 541
 
5.6%
ValueCountFrequency (%)
0 3653
37.6%
1 1910
19.6%
2 1091
 
11.2%
3 795
 
8.2%
4 544
 
5.6%
5 415
 
4.3%
6 271
 
2.8%
7 209
 
2.1%
8 170
 
1.7%
9 122
 
1.3%
ValueCountFrequency (%)
45 1
 
< 0.1%
38 1
 
< 0.1%
34 2
 
< 0.1%
33 2
 
< 0.1%
32 3
< 0.1%
31 3
< 0.1%
30 2
 
< 0.1%
29 4
< 0.1%
28 5
0.1%
27 6
0.1%

특별공급_기관추천세대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct107
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.700751
Minimum0
Maximum151
Zeros3698
Zeros (%)38.0%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:56.346206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310
95-th percentile33
Maximum151
Range151
Interquartile range (IQR)10

Descriptive statistics

Standard deviation13.071993
Coefficient of variation (CV)1.6974959
Kurtosis15.61816
Mean7.700751
Median Absolute Deviation (MAD)2
Skewness3.298074
Sum74859
Variance170.877
MonotonicityNot monotonic
2024-03-16T13:16:56.540691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3698
38.0%
2 637
 
6.6%
1 629
 
6.5%
4 430
 
4.4%
3 429
 
4.4%
5 362
 
3.7%
7 296
 
3.0%
6 254
 
2.6%
8 245
 
2.5%
9 208
 
2.1%
Other values (97) 2533
26.1%
ValueCountFrequency (%)
0 3698
38.0%
1 629
 
6.5%
2 637
 
6.6%
3 429
 
4.4%
4 430
 
4.4%
5 362
 
3.7%
6 254
 
2.6%
7 296
 
3.0%
8 245
 
2.5%
9 208
 
2.1%
ValueCountFrequency (%)
151 1
< 0.1%
129 1
< 0.1%
126 1
< 0.1%
120 1
< 0.1%
116 1
< 0.1%
115 1
< 0.1%
112 1
< 0.1%
111 1
< 0.1%
108 1
< 0.1%
107 2
< 0.1%
Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.27425162
Minimum0
Maximum113
Zeros9508
Zeros (%)97.8%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:56.827091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum113
Range113
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.8537904
Coefficient of variation (CV)10.405738
Kurtosis570.83149
Mean0.27425162
Median Absolute Deviation (MAD)0
Skewness19.843789
Sum2666
Variance8.1441199
MonotonicityNot monotonic
2024-03-16T13:16:57.056037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 9508
97.8%
1 28
 
0.3%
2 18
 
0.2%
12 15
 
0.2%
11 13
 
0.1%
3 13
 
0.1%
8 13
 
0.1%
6 11
 
0.1%
15 10
 
0.1%
5 8
 
0.1%
Other values (34) 84
 
0.9%
ValueCountFrequency (%)
0 9508
97.8%
1 28
 
0.3%
2 18
 
0.2%
3 13
 
0.1%
4 7
 
0.1%
5 8
 
0.1%
6 11
 
0.1%
7 7
 
0.1%
8 13
 
0.1%
9 7
 
0.1%
ValueCountFrequency (%)
113 1
< 0.1%
105 1
< 0.1%
77 1
< 0.1%
63 1
< 0.1%
46 1
< 0.1%
43 2
< 0.1%
40 1
< 0.1%
39 2
< 0.1%
36 1
< 0.1%
35 1
< 0.1%

특별공급_이전기관세대수
Real number (ℝ)

ZEROS 

Distinct67
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.54675445
Minimum0
Maximum222
Zeros9515
Zeros (%)97.9%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:57.391989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum222
Range222
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.6260984
Coefficient of variation (CV)10.289991
Kurtosis443.05219
Mean0.54675445
Median Absolute Deviation (MAD)0
Skewness17.725986
Sum5315
Variance31.652984
MonotonicityNot monotonic
2024-03-16T13:16:57.574462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9515
97.9%
2 14
 
0.1%
13 13
 
0.1%
5 10
 
0.1%
27 10
 
0.1%
17 8
 
0.1%
4 7
 
0.1%
3 7
 
0.1%
10 7
 
0.1%
15 6
 
0.1%
Other values (57) 124
 
1.3%
ValueCountFrequency (%)
0 9515
97.9%
1 5
 
0.1%
2 14
 
0.1%
3 7
 
0.1%
4 7
 
0.1%
5 10
 
0.1%
6 5
 
0.1%
7 5
 
0.1%
8 3
 
< 0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
222 1
< 0.1%
155 1
< 0.1%
127 1
< 0.1%
113 1
< 0.1%
112 1
< 0.1%
96 1
< 0.1%
95 1
< 0.1%
94 1
< 0.1%
91 1
< 0.1%
89 1
< 0.1%

공급금액_분양최고금액
Real number (ℝ)

HIGH CORRELATION 

Distinct5332
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56063.156
Minimum1761
Maximum1600000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size85.6 KiB
2024-03-16T13:16:57.798067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1761
5-th percentile22712
Q135930
median47300
Q364670
95-th percentile115300
Maximum1600000
Range1598239
Interquartile range (IQR)28740

Descriptive statistics

Standard deviation45604.359
Coefficient of variation (CV)0.81344616
Kurtosis382.21216
Mean56063.156
Median Absolute Deviation (MAD)13400
Skewness13.98686
Sum5.4498994 × 108
Variance2.0797576 × 109
MonotonicityNot monotonic
2024-03-16T13:16:58.188792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37900 23
 
0.2%
45800 19
 
0.2%
39800 18
 
0.2%
47500 18
 
0.2%
33000 18
 
0.2%
29000 17
 
0.2%
47900 16
 
0.2%
43800 16
 
0.2%
41500 16
 
0.2%
39900 16
 
0.2%
Other values (5322) 9544
98.2%
ValueCountFrequency (%)
1761 1
< 0.1%
2208 1
< 0.1%
2230 1
< 0.1%
2495 1
< 0.1%
2564 1
< 0.1%
2724 1
< 0.1%
2857 1
< 0.1%
2868 1
< 0.1%
2892 1
< 0.1%
2910 1
< 0.1%
ValueCountFrequency (%)
1600000 1
< 0.1%
1500000 1
< 0.1%
1365000 1
< 0.1%
1280000 1
< 0.1%
800000 2
< 0.1%
635000 1
< 0.1%
520000 1
< 0.1%
440000 1
< 0.1%
389650 1
< 0.1%
380900 1
< 0.1%

Interactions

2024-03-16T13:16:45.792673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:14.052179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:16.549510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:18.632229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:21.314583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:24.178890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:26.919024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:29.299640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:31.049376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:33.302012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:35.758108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:38.181707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:40.590182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:43.423469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:45.999151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:14.228979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:16.722020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:18.799413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:21.474565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:24.453347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:27.074021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:29.421579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:31.202188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:33.504967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:35.976382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:38.359159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:40.726930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:43.618411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:46.185928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:14.443686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:16.884007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:19.034381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:21.669257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:24.666054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:27.203784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:29.526836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:31.390617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:33.717778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:36.141842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:38.517660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:40.868497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:43.825058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:46.389585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:14.658219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:17.019041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:19.202578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:21.854715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:24.828699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:27.353594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:29.629591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:31.534063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:33.859087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:36.285120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:38.664847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:41.021456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:43.987494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:46.585433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:14.816447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:17.154060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:19.374189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:22.033222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:24.979003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:27.507907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:29.738571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:31.655717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:33.993532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:36.419683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:38.817116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:41.234246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:44.152612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:46.766119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:14.972466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:17.295163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:19.510207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:22.589764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:25.127795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:27.682020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:29.824166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:31.738104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:34.121571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:36.580834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:38.982315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:41.402324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:44.297726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:46.953665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:15.138303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:17.463764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:19.759521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:22.745347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:25.269078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:27.843633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:29.958246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:31.822251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:34.288119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:36.793519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:39.172373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:41.549277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:44.439656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:47.204412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:15.332123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:17.618835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:19.930336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:22.910253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:25.502248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:28.080861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:30.105352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:31.940862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:34.508235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:37.001378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:39.401217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:41.745393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:44.589983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:47.390409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:15.579769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:17.784889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:20.128994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:23.068281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:25.693615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:28.260923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:30.280596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:32.381611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:34.699809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:37.153826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:39.563206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:41.909373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:44.759130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:47.568846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:15.804983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:17.934115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:20.368061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:23.234668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:25.855146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:28.418955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:30.392987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:32.529843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:34.849101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:37.294274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:39.703548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:42.103667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:44.959143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:47.732242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:15.935497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:18.055828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:20.565424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:23.415284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:25.994197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:28.560225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:30.497772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:32.648392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:35.031907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:37.439299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:39.846628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:42.245847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:45.107529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:47.994889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:16.082812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:18.196540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:20.717227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:23.630451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:26.175339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:28.752506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:30.614211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:32.774994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:35.228658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:37.594290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:40.005682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:42.498961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:45.247122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:48.191586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:16.229878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:18.319298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:20.897478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:23.771418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:26.371210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:28.920661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:30.747423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:32.917324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:35.402622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:37.725618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:40.216185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:42.704230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:45.392691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:48.364896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:16.361346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:18.435924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:21.069665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:23.964835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:26.638384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:29.100225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:30.897840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:33.100231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:35.580141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:37.936408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:40.430558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:42.868107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T13:16:45.553703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:16:58.349889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주택관리번호공고번호모델번호주택공급면적일반공급세대수특별공급세대수특별공급_다자녀가구세대수특별공급_신혼부부세대수특별공급_생애최초세대수특별공급_노부모부양세대수특별공급_기관추천세대수특별공급_기관추천기타세대수특별공급_이전기관세대수공급금액_분양최고금액
주택관리번호1.0001.0000.0770.1400.0000.0610.0510.0300.0960.0110.0310.0570.0000.083
공고번호1.0001.0000.0770.1400.0000.0610.0510.0300.0960.0110.0310.0570.0000.083
모델번호0.0770.0771.0000.5160.1090.1540.1640.1770.1280.1640.1730.0000.0000.138
주택공급면적0.1400.1400.5161.0000.1350.2060.1810.2450.1620.1780.2420.0000.0000.501
일반공급세대수0.0000.0000.1090.1351.0000.7960.8850.8890.5660.9150.9140.0900.0000.000
특별공급세대수0.0610.0610.1540.2060.7961.0000.9290.9210.9090.9310.9280.5210.4430.000
특별공급_다자녀가구세대수0.0510.0510.1640.1810.8850.9291.0000.9550.8800.9700.9670.3980.2000.000
특별공급_신혼부부세대수0.0300.0300.1770.2450.8890.9210.9551.0000.8410.9740.9810.2650.2110.000
특별공급_생애최초세대수0.0960.0960.1280.1620.5660.9090.8800.8411.0000.8670.8430.4040.2800.000
특별공급_노부모부양세대수0.0110.0110.1640.1780.9150.9310.9700.9740.8671.0000.9900.2660.2020.000
특별공급_기관추천세대수0.0310.0310.1730.2420.9140.9280.9670.9810.8430.9901.0000.2230.1990.000
특별공급_기관추천기타세대수0.0570.0570.0000.0000.0900.5210.3980.2650.4040.2660.2231.0000.0000.000
특별공급_이전기관세대수0.0000.0000.0000.0000.0000.4430.2000.2110.2800.2020.1990.0001.0000.000
공급금액_분양최고금액0.0830.0830.1380.5010.0000.0000.0000.0000.0000.0000.0000.0000.0001.000
2024-03-16T13:16:58.627743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주택관리번호공고번호모델번호주택공급면적일반공급세대수특별공급세대수특별공급_다자녀가구세대수특별공급_신혼부부세대수특별공급_생애최초세대수특별공급_노부모부양세대수특별공급_기관추천세대수특별공급_기관추천기타세대수특별공급_이전기관세대수공급금액_분양최고금액
주택관리번호1.0001.000-0.0070.078-0.0630.007-0.010-0.0570.257-0.010-0.044-0.017-0.0160.306
공고번호1.0001.000-0.0070.078-0.0630.007-0.010-0.0570.257-0.010-0.044-0.017-0.0160.306
모델번호-0.007-0.0071.0000.455-0.260-0.353-0.258-0.371-0.313-0.265-0.364-0.0350.0460.390
주택공급면적0.0780.0780.4551.0000.097-0.1190.054-0.231-0.1650.041-0.2070.0470.0450.514
일반공급세대수-0.063-0.063-0.2600.0971.0000.7310.8250.6300.4390.8200.6440.0610.012-0.104
특별공급세대수0.0070.007-0.353-0.1190.7311.0000.9160.9100.7480.9050.9100.0990.099-0.245
특별공급_다자녀가구세대수-0.010-0.010-0.2580.0540.8250.9161.0000.8060.6350.9440.8140.0920.052-0.143
특별공급_신혼부부세대수-0.057-0.057-0.371-0.2310.6300.9100.8061.0000.7880.7960.9820.0540.031-0.275
특별공급_생애최초세대수0.2570.257-0.313-0.1650.4390.7480.6350.7881.0000.6280.7850.0400.063-0.187
특별공급_노부모부양세대수-0.010-0.010-0.2650.0410.8200.9050.9440.7960.6281.0000.8050.0910.056-0.147
특별공급_기관추천세대수-0.044-0.044-0.364-0.2070.6440.9100.8140.9820.7850.8051.0000.0510.031-0.257
특별공급_기관추천기타세대수-0.017-0.017-0.0350.0470.0610.0990.0920.0540.0400.0910.0511.000-0.0220.047
특별공급_이전기관세대수-0.016-0.0160.0460.0450.0120.0990.0520.0310.0630.0560.031-0.0221.000-0.095
공급금액_분양최고금액0.3060.3060.3900.514-0.104-0.245-0.143-0.275-0.187-0.147-0.2570.047-0.0951.000

Missing values

2024-03-16T13:16:48.623282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:16:49.017295image/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

주택관리번호공고번호모델번호주택형주택공급면적일반공급세대수특별공급세대수특별공급_다자녀가구세대수특별공급_신혼부부세대수특별공급_생애최초세대수특별공급_노부모부양세대수특별공급_기관추천세대수특별공급_기관추천기타세대수특별공급_이전기관세대수공급금액_분양최고금액
0202482000420248200041055.9800A78.765901000000053058
1202482000320248200031055.0000A79.982301000000035881
2202482000220248200021056.1000A78.542101000000046619
3202400009420240000941084.9556A110.9762408401801457224800049900
4202400009420240000942084.9484B111.85961211192443217240049900
5202400009420240000943103.8578135.1244140201600400059700
6202400009120240000911084.9985A117.4969517212221131212087600
7202400009120240000912084.9048B118.2877517212221131212088300
8202400009120240000913084.9958C118.2249517212221131212088600
9202400009120240000914101.9895141.0779327120030120101600
주택관리번호공고번호모델번호주택형주택공급면적일반공급세대수특별공급세대수특별공급_다자녀가구세대수특별공급_신혼부부세대수특별공급_생애최초세대수특별공급_노부모부양세대수특별공급_기관추천세대수특별공급_기관추천기타세대수특별공급_이전기관세대수공급금액_분양최고금액
9711202000000520200000055074.9780A99.25932378510103100406100
9712202000000520200000056074.9600B99.34461960388280316100
9713202000000520200000057077.8980102.8715520133030106600
9714202000000520200000058077.7980102.747881612202096600
9715202000000520200000059084.8636A111.7368471631021216210847900
97162020000005202000000510084.9152B112.115845147919195190767900
97172020000005202000000511084.9750T111.053171512202087600
9718202000000120200000011059.0000H84.0118315431308721313052515
9719202000000120200000012084.0000H117.01223554814395243411069750
9720202000000120200000013084.0000N117.35124051510370067124