Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells14153
Missing cells (%)10.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory118.0 B

Variable types

Numeric5
Text2
Categorical3
DateTime1
Boolean1
Unsupported1

Dataset

Description사업명,신지번 동명,신지번 본번,신지번 부번,구지번 동명,구지번 본번,구지번 부번,변경일,비고,일련번호
Author은평구
URLhttps://data.seoul.go.kr/dataList/OA-15745/S/1/datasetView.do

Alerts

삭제여부 has constant value ""Constant
신지번 동명 is highly overall correlated with 신지번 본번 and 3 other fieldsHigh correlation
구지번 동명 is highly overall correlated with 신지번 본번 and 3 other fieldsHigh correlation
비고 is highly overall correlated with 바뀐지번 번호 and 6 other fieldsHigh correlation
바뀐지번 번호 is highly overall correlated with 신지번 본번 and 2 other fieldsHigh correlation
신지번 본번 is highly overall correlated with 바뀐지번 번호 and 4 other fieldsHigh correlation
신지번 부번 is highly overall correlated with 비고High correlation
구지번 부번 is highly overall correlated with 비고High correlation
최초등록시점 is highly overall correlated with 바뀐지번 번호 and 4 other fieldsHigh correlation
신지번 동명 is highly imbalanced (81.8%)Imbalance
구지번 동명 is highly imbalanced (81.8%)Imbalance
비고 is highly imbalanced (75.4%)Imbalance
신지번 부번 has 4149 (41.5%) missing valuesMissing
수정등록시점 has 10000 (100.0%) missing valuesMissing
바뀐지번 번호 has unique valuesUnique
수정등록시점 is an unsupported type, check if it needs cleaning or further analysisUnsupported
구지번 부번 has 189 (1.9%) zerosZeros

Reproduction

Analysis started2024-05-18 04:42:51.639838
Analysis finished2024-05-18 04:43:05.274915
Duration13.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

바뀐지번 번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean438613.59
Minimum374646
Maximum492175
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:43:05.479360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum374646
5-th percentile380536.1
Q1404850.25
median442508.5
Q3471120.5
95-th percentile487950.35
Maximum492175
Range117529
Interquartile range (IQR)66270.25

Descriptive statistics

Standard deviation36059.396
Coefficient of variation (CV)0.082212219
Kurtosis-1.3317013
Mean438613.59
Median Absolute Deviation (MAD)32232.5
Skewness-0.21359384
Sum4.3861359 × 109
Variance1.3002801 × 109
MonotonicityNot monotonic
2024-05-18T13:43:05.926438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
426797 1
 
< 0.1%
445100 1
 
< 0.1%
433551 1
 
< 0.1%
440539 1
 
< 0.1%
483517 1
 
< 0.1%
390383 1
 
< 0.1%
437800 1
 
< 0.1%
485476 1
 
< 0.1%
488603 1
 
< 0.1%
401159 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
374646 1
< 0.1%
374648 1
< 0.1%
374650 1
< 0.1%
374662 1
< 0.1%
374668 1
< 0.1%
374676 1
< 0.1%
374692 1
< 0.1%
374723 1
< 0.1%
374734 1
< 0.1%
374755 1
< 0.1%
ValueCountFrequency (%)
492175 1
< 0.1%
492159 1
< 0.1%
492154 1
< 0.1%
492152 1
< 0.1%
492147 1
< 0.1%
492132 1
< 0.1%
492127 1
< 0.1%
492121 1
< 0.1%
492120 1
< 0.1%
492115 1
< 0.1%

사업명
Text

Distinct146
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T13:43:06.626021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length17.2328
Min length8

Characters and Unicode

Total characters172328
Distinct characters44
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique143 ?
Unique (%)1.4%

Sample

1st row은평뉴타운 3-2지구 2차 준공
2nd row증산2재정비촉진구역 주택재개발정비사업
3rd row은평뉴타운 3-2지구 2차 준공
4th row은평뉴타운 3-2지구 2차 준공
5th row은평뉴타운 3-2지구 2차 준공
ValueCountFrequency (%)
은평뉴타운 9326
24.1%
3-2지구 9326
24.1%
준공 9326
24.1%
2차 9185
23.8%
주택재개발정비사업 672
 
1.7%
수색9재정비촉진구역 408
 
1.1%
증산2재정비촉진구역 264
 
0.7%
자율주택정비사업 2
 
< 0.1%
1082차 1
 
< 0.1%
1343차 1
 
< 0.1%
Other values (142) 142
 
0.4%
2024-05-18T13:43:07.654471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28653
16.6%
2 18810
 
10.9%
구 9999
 
5.8%
3 9368
 
5.4%
지 9327
 
5.4%
- 9327
 
5.4%
은 9326
 
5.4%
공 9326
 
5.4%
준 9326
 
5.4%
차 9326
 
5.4%
Other values (34) 49540
28.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105379
61.2%
Decimal Number 28969
 
16.8%
Space Separator 28653
 
16.6%
Dash Punctuation 9327
 
5.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 9999
9.5%
지 9327
8.9%
은 9326
8.8%
공 9326
8.8%
준 9326
8.8%
차 9326
8.8%
운 9326
8.8%
타 9326
8.8%
뉴 9326
8.8%
평 9326
8.8%
Other values (22) 11445
10.9%
Decimal Number
ValueCountFrequency (%)
2 18810
64.9%
3 9368
32.3%
9 448
 
1.5%
1 92
 
0.3%
5 60
 
0.2%
4 50
 
0.2%
7 47
 
0.2%
6 37
 
0.1%
8 29
 
0.1%
0 28
 
0.1%
Space Separator
ValueCountFrequency (%)
28653
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9327
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105379
61.2%
Common 66949
38.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 9999
9.5%
지 9327
8.9%
은 9326
8.8%
공 9326
8.8%
준 9326
8.8%
차 9326
8.8%
운 9326
8.8%
타 9326
8.8%
뉴 9326
8.8%
평 9326
8.8%
Other values (22) 11445
10.9%
Common
ValueCountFrequency (%)
28653
42.8%
2 18810
28.1%
3 9368
 
14.0%
- 9327
 
13.9%
9 448
 
0.7%
1 92
 
0.1%
5 60
 
0.1%
4 50
 
0.1%
7 47
 
0.1%
6 37
 
0.1%
Other values (2) 57
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105379
61.2%
ASCII 66949
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28653
42.8%
2 18810
28.1%
3 9368
 
14.0%
- 9327
 
13.9%
9 448
 
0.7%
1 92
 
0.1%
5 60
 
0.1%
4 50
 
0.1%
7 47
 
0.1%
6 37
 
0.1%
Other values (2) 57
 
0.1%
Hangul
ValueCountFrequency (%)
구 9999
9.5%
지 9327
8.9%
은 9326
8.8%
공 9326
8.8%
준 9326
8.8%
차 9326
8.8%
운 9326
8.8%
타 9326
8.8%
뉴 9326
8.8%
평 9326
8.8%
Other values (22) 11445
10.9%

신지번 동명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
진관동
9326 
수색동
 
408
증산동
 
264
구산동
 
1
신사동
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row진관동
2nd row증산동
3rd row진관동
4th row진관동
5th row진관동

Common Values

ValueCountFrequency (%)
진관동 9326
93.3%
수색동 408
 
4.1%
증산동 264
 
2.6%
구산동 1
 
< 0.1%
신사동 1
 
< 0.1%

Length

2024-05-18T13:43:07.974067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:43:08.245370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진관동 9326
93.3%
수색동 408
 
4.1%
증산동 264
 
2.6%
구산동 1
 
< 0.1%
신사동 1
 
< 0.1%

신지번 본번
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148.8356
Minimum89
Maximum551
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:43:08.644382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum89
5-th percentile90
Q197
median140
Q3156
95-th percentile263
Maximum551
Range462
Interquartile range (IQR)59

Descriptive statistics

Standard deviation69.425132
Coefficient of variation (CV)0.46645515
Kurtosis6.7417029
Mean148.8356
Median Absolute Deviation (MAD)41
Skewness2.4091363
Sum1488356
Variance4819.849
MonotonicityNot monotonic
2024-05-18T13:43:09.122216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
90 1167
 
11.7%
140 869
 
8.7%
154 774
 
7.7%
156 729
 
7.3%
99 520
 
5.2%
95 475
 
4.8%
97 416
 
4.2%
418 408
 
4.1%
155 383
 
3.8%
150 322
 
3.2%
Other values (35) 3937
39.4%
ValueCountFrequency (%)
89 141
 
1.4%
90 1167
11.7%
91 94
 
0.9%
92 211
 
2.1%
94 134
 
1.3%
95 475
4.8%
96 132
 
1.3%
97 416
 
4.2%
98 171
 
1.7%
99 520
5.2%
ValueCountFrequency (%)
551 1
 
< 0.1%
418 408
4.1%
373 1
 
< 0.1%
265 40
 
0.4%
264 35
 
0.4%
263 29
 
0.3%
262 29
 
0.3%
261 27
 
0.3%
260 40
 
0.4%
259 34
 
0.3%

신지번 부번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)0.2%
Missing4149
Missing (%)41.5%
Infinite0
Infinite (%)0.0%
Mean4.0223893
Minimum0
Maximum15
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:43:09.561744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q36
95-th percentile14
Maximum15
Range15
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.8765141
Coefficient of variation (CV)0.96373419
Kurtosis1.2258856
Mean4.0223893
Median Absolute Deviation (MAD)1
Skewness1.4793876
Sum23535
Variance15.027362
MonotonicityNot monotonic
2024-05-18T13:43:09.971909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 1918
19.2%
2 1075
 
10.8%
3 816
 
8.2%
4 458
 
4.6%
7 270
 
2.7%
8 246
 
2.5%
15 200
 
2.0%
14 183
 
1.8%
10 177
 
1.8%
9 164
 
1.6%
Other values (4) 344
 
3.4%
(Missing) 4149
41.5%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 1918
19.2%
2 1075
10.8%
3 816
8.2%
4 458
 
4.6%
5 107
 
1.1%
6 122
 
1.2%
7 270
 
2.7%
8 246
 
2.5%
9 164
 
1.6%
ValueCountFrequency (%)
15 200
2.0%
14 183
 
1.8%
11 114
 
1.1%
10 177
 
1.8%
9 164
 
1.6%
8 246
2.5%
7 270
2.7%
6 122
 
1.2%
5 107
 
1.1%
4 458
4.6%

구지번 동명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
진관동
9326 
수색동
 
408
증산동
 
264
구산동
 
1
신사동
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row진관동
2nd row증산동
3rd row진관동
4th row진관동
5th row진관동

Common Values

ValueCountFrequency (%)
진관동 9326
93.3%
수색동 408
 
4.1%
증산동 264
 
2.6%
구산동 1
 
< 0.1%
신사동 1
 
< 0.1%

Length

2024-05-18T13:43:10.409096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:43:10.730172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진관동 9326
93.3%
수색동 408
 
4.1%
증산동 264
 
2.6%
구산동 1
 
< 0.1%
신사동 1
 
< 0.1%

구지번 본번
Text

Distinct95
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T13:43:11.304517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0609
Min length2

Characters and Unicode

Total characters30609
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row135
2nd row181
3rd row213
4th row산106
5th row137
ValueCountFrequency (%)
175 932
 
9.3%
134 276
 
2.8%
산105 256
 
2.6%
141 234
 
2.3%
산104 223
 
2.2%
140 222
 
2.2%
133 219
 
2.2%
156 209
 
2.1%
153 208
 
2.1%
158 207
 
2.1%
Other values (85) 7014
70.1%
2024-05-18T13:43:12.498331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 9719
31.8%
5 3658
 
12.0%
3 2965
 
9.7%
4 2836
 
9.3%
0 2539
 
8.3%
2 2533
 
8.3%
7 1797
 
5.9%
6 1369
 
4.5%
9 1299
 
4.2%
산 1016
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29593
96.7%
Other Letter 1016
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9719
32.8%
5 3658
 
12.4%
3 2965
 
10.0%
4 2836
 
9.6%
0 2539
 
8.6%
2 2533
 
8.6%
7 1797
 
6.1%
6 1369
 
4.6%
9 1299
 
4.4%
8 878
 
3.0%
Other Letter
ValueCountFrequency (%)
산 1016
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29593
96.7%
Hangul 1016
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 9719
32.8%
5 3658
 
12.4%
3 2965
 
10.0%
4 2836
 
9.6%
0 2539
 
8.6%
2 2533
 
8.6%
7 1797
 
6.1%
6 1369
 
4.6%
9 1299
 
4.4%
8 878
 
3.0%
Hangul
ValueCountFrequency (%)
산 1016
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29593
96.7%
Hangul 1016
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 9719
32.8%
5 3658
 
12.4%
3 2965
 
10.0%
4 2836
 
9.6%
0 2539
 
8.6%
2 2533
 
8.6%
7 1797
 
6.1%
6 1369
 
4.6%
9 1299
 
4.4%
8 878
 
3.0%
Hangul
ValueCountFrequency (%)
산 1016
100.0%

구지번 부번
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct265
Distinct (%)2.7%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean83.234794
Minimum0
Maximum997
Zeros189
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:43:12.998302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median23
Q337
95-th percentile585
Maximum997
Range997
Interquartile range (IQR)26

Descriptive statistics

Standard deviation205.85844
Coefficient of variation (CV)2.4732258
Kurtosis10.967158
Mean83.234794
Median Absolute Deviation (MAD)12
Skewness3.4526885
Sum832015
Variance42377.699
MonotonicityNot monotonic
2024-05-18T13:43:13.462666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 247
 
2.5%
1 245
 
2.5%
16 244
 
2.4%
21 242
 
2.4%
7 225
 
2.2%
29 222
 
2.2%
2 222
 
2.2%
12 221
 
2.2%
18 221
 
2.2%
8 221
 
2.2%
Other values (255) 7686
76.9%
ValueCountFrequency (%)
0 189
1.9%
1 245
2.5%
2 222
2.2%
3 184
1.8%
4 247
2.5%
5 212
2.1%
6 177
1.8%
7 225
2.2%
8 221
2.2%
9 205
2.1%
ValueCountFrequency (%)
997 10
0.1%
996 5
0.1%
995 5
0.1%
994 2
 
< 0.1%
993 4
 
< 0.1%
992 6
0.1%
991 8
0.1%
990 9
0.1%
989 7
0.1%
988 2
 
< 0.1%

변경일
Date

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-01-26 00:00:00
Maximum2023-10-19 00:00:00
2024-05-18T13:43:13.835680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:43:14.165580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9592 
주택재개발정비사업
 
408

Length

Max length9
Median length4
Mean length4.204
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9592
95.9%
주택재개발정비사업 408
 
4.1%

Length

2024-05-18T13:43:15.056986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T13:43:15.406334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9592
95.9%
주택재개발정비사업 408
 
4.1%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2024-05-18T13:43:15.682389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최초등록시점
Real number (ℝ)

HIGH CORRELATION 

Distinct552
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0230243 × 1013
Minimum2.023021 × 1013
Maximum2.0231024 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T13:43:16.107414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.023021 × 1013
5-th percentile2.023021 × 1013
Q12.023021 × 1013
median2.023021 × 1013
Q32.023021 × 1013
95-th percentile2.023021 × 1013
Maximum2.0231024 × 1013
Range8.140304 × 108
Interquartile range (IQR)496

Descriptive statistics

Standard deviation1.58708 × 108
Coefficient of variation (CV)7.8450863 × 10-6
Kurtosis19.475209
Mean2.0230243 × 1013
Median Absolute Deviation (MAD)226
Skewness4.6332771
Sum2.0230243 × 1017
Variance2.518823 × 1016
MonotonicityNot monotonic
2024-05-18T13:43:16.599030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230210152512 51
 
0.5%
20230210152621 50
 
0.5%
20230210152502 49
 
0.5%
20230210152500 48
 
0.5%
20230210152539 47
 
0.5%
20230210152518 47
 
0.5%
20230210152517 46
 
0.5%
20230210152508 46
 
0.5%
20230210152045 45
 
0.4%
20230210152506 44
 
0.4%
Other values (542) 9527
95.3%
ValueCountFrequency (%)
20230210141705 22
0.2%
20230210141706 23
0.2%
20230210141707 26
0.3%
20230210141708 12
0.1%
20230210141709 6
 
0.1%
20230210141710 4
 
< 0.1%
20230210141711 5
 
0.1%
20230210141712 8
 
0.1%
20230210141713 20
0.2%
20230210141714 15
0.1%
ValueCountFrequency (%)
20231024172103 1
 
< 0.1%
20231011164659 17
0.2%
20231011164658 28
0.3%
20231011164657 31
0.3%
20231011164656 21
0.2%
20231011164655 13
 
0.1%
20231011164654 13
 
0.1%
20231011164653 1
 
< 0.1%
20231011164305 9
 
0.1%
20231011164304 38
0.4%

수정등록시점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Interactions

2024-05-18T13:43:02.301492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:55.117035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:56.891982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:58.640907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:43:00.607594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:43:02.597656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:55.427756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:57.257936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:59.027112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:43:00.885634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:43:02.895122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:55.799960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:57.617343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:59.419347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:43:01.186729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:43:03.205818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:56.179159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:57.969027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:59.838986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:43:01.591978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:43:03.488634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:56.500140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:42:58.326931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:43:00.224356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T13:43:01.980965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T13:43:16.899447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
바뀐지번 번호신지번 동명신지번 본번신지번 부번구지번 동명구지번 본번구지번 부번변경일최초등록시점
바뀐지번 번호1.0000.6580.7760.6820.6580.5390.1130.6580.515
신지번 동명0.6581.0001.0000.4221.0001.0000.2481.0001.000
신지번 본번0.7761.0001.0000.7371.0000.9670.2231.0001.000
신지번 부번0.6820.4220.7371.0000.4220.2940.1220.4220.422
구지번 동명0.6581.0001.0000.4221.0001.0000.2481.0001.000
구지번 본번0.5391.0000.9670.2941.0001.0000.7561.0001.000
구지번 부번0.1130.2480.2230.1220.2480.7561.0000.2480.419
변경일0.6581.0001.0000.4221.0001.0000.2481.0001.000
최초등록시점0.5151.0001.0000.4221.0001.0000.4191.0001.000
2024-05-18T13:43:17.181952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신지번 동명구지번 동명비고
신지번 동명1.0001.0001.000
구지번 동명1.0001.0001.000
비고1.0001.0001.000
2024-05-18T13:43:17.433325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
바뀐지번 번호신지번 본번신지번 부번구지번 부번최초등록시점신지번 동명구지번 동명비고
바뀐지번 번호1.0000.9980.1870.0011.0000.3310.3311.000
신지번 본번0.9981.0000.123-0.0020.9981.0001.0001.000
신지번 부번0.1870.1231.0000.0240.1870.2140.2141.000
구지번 부번0.001-0.0020.0241.0000.0010.1450.1451.000
최초등록시점1.0000.9980.1870.0011.0001.0001.0001.000
신지번 동명0.3311.0000.2140.1451.0001.0001.0001.000
구지번 동명0.3311.0000.2140.1451.0001.0001.0001.000
비고1.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2024-05-18T13:43:03.927174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T13:43:04.675629image/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.
2024-05-18T13:43:05.088859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

바뀐지번 번호사업명신지번 동명신지번 본번신지번 부번구지번 동명구지번 본번구지번 부번변경일비고삭제여부최초등록시점수정등록시점
68619426797은평뉴타운 3-2지구 2차 준공진관동134<NA>진관동135512023-01-26<NA>N20230210152225<NA>
5265486726증산2재정비촉진구역 주택재개발정비사업증산동259<NA>증산동181232023-01-27<NA>N20230210154735<NA>
12378479867은평뉴타운 3-2지구 2차 준공진관동19415진관동21352023-01-26<NA>N20230210152622<NA>
28774470607은평뉴타운 3-2지구 2차 준공진관동1551진관동산106442023-01-26<NA>N20230210152539<NA>
33047439428은평뉴타운 3-2지구 2차 준공진관동1403진관동137232023-01-26<NA>N20230210152321<NA>
68639427077은평뉴타운 3-2지구 2차 준공진관동134<NA>진관동144362023-01-26<NA>N20230210152226<NA>
22388477364은평뉴타운 3-2지구 2차 준공진관동183<NA>진관동14272023-01-26<NA>N20230210152609<NA>
648491471수색9재정비촉진구역 주택재개발정비사업수색동4189수색동29402023-09-13주택재개발정비사업N20231011164656<NA>
51068484520은평뉴타운 3-2지구 2차 준공진관동217<NA>진관동208402023-01-26<NA>N20230210152644<NA>
44736468869은평뉴타운 3-2지구 2차 준공진관동155<NA>진관동213292023-01-26<NA>N20230210152532<NA>
바뀐지번 번호사업명신지번 동명신지번 본번신지번 부번구지번 동명구지번 본번구지번 부번변경일비고삭제여부최초등록시점수정등록시점
27835437428은평뉴타운 3-2지구 2차 준공진관동1401진관동산103122023-01-26<NA>N20230210152311<NA>
82774401353은평뉴타운 3-2지구 2차 준공진관동952진관동산108372023-01-26<NA>N20230210152030<NA>
22428464671은평뉴타운 3-2지구 2차 준공진관동1542진관동139212023-01-26<NA>N20230210152514<NA>
10283417233은평뉴타운 3-2지구 2차 준공진관동994진관동131262023-01-26<NA>N20230210152145<NA>
51552482233은평뉴타운 3-2지구 2차 준공진관동216<NA>진관동146262023-01-26<NA>N20230210152632<NA>
39216471506은평뉴타운 3-2지구 2차 준공진관동1561진관동157182023-01-26<NA>N20230210152542<NA>
9110476841은평뉴타운 3-2지구 2차 준공진관동1564진관동산10522023-01-26<NA>N20230210152607<NA>
44944478735은평뉴타운 3-2지구 2차 준공진관동19415진관동135412023-01-26<NA>N20230210152618<NA>
78886402421은평뉴타운 3-2지구 2차 준공진관동96<NA>진관동1753122023-01-26<NA>N20230210152034<NA>
39822472701은평뉴타운 3-2지구 2차 준공진관동1562진관동14402023-01-26<NA>N20230210152550<NA>