Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells20112
Missing cells (%)20.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory918.0 KiB
Average record size in memory94.0 B

Variable types

Text4
Numeric2
Categorical2
Unsupported2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15664/S/1/datasetView.do

Alerts

작업_일자 has constant value ""Constant
호_번호 is highly overall correlated with 층_번호High correlation
층_번호 is highly overall correlated with 호_번호High correlation
층_구분_코드 is highly imbalanced (70.4%)Imbalance
관리_건축물대장_참조 has 10000 (100.0%) missing valuesMissing
변경_구분_코드 has 10000 (100.0%) missing valuesMissing
관리_호별_명세 has unique valuesUnique
관리_건축물대장_참조 is an unsupported type, check if it needs cleaning or further analysisUnsupported
변경_구분_코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
호_번호 has 1164 (11.6%) zerosZeros

Reproduction

Analysis started2024-05-11 08:22:10.560770
Analysis finished2024-05-11 08:22:14.178420
Duration3.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리_호별_명세
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T08:22:14.729860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length11.2475
Min length7

Characters and Unicode

Total characters112475
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st row11710-25039
2nd row11545-100004323
3rd row11530-28594
4th row11215-100006841
5th row11560-100005031
ValueCountFrequency (%)
11710-25039 1
 
< 0.1%
11710-20112 1
 
< 0.1%
11710-3806 1
 
< 0.1%
11710-21602 1
 
< 0.1%
11545-12948 1
 
< 0.1%
11710-49 1
 
< 0.1%
11545-13898 1
 
< 0.1%
11380-100011380 1
 
< 0.1%
11710-2077 1
 
< 0.1%
11710-21051 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T08:22:16.008916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 31906
28.4%
0 16452
14.6%
5 13134
11.7%
- 10000
 
8.9%
4 8250
 
7.3%
7 7212
 
6.4%
2 6984
 
6.2%
3 6635
 
5.9%
6 4323
 
3.8%
8 4094
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102475
91.1%
Dash Punctuation 10000
 
8.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 31906
31.1%
0 16452
16.1%
5 13134
12.8%
4 8250
 
8.1%
7 7212
 
7.0%
2 6984
 
6.8%
3 6635
 
6.5%
6 4323
 
4.2%
8 4094
 
4.0%
9 3485
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 112475
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 31906
28.4%
0 16452
14.6%
5 13134
11.7%
- 10000
 
8.9%
4 8250
 
7.3%
7 7212
 
6.4%
2 6984
 
6.2%
3 6635
 
5.9%
6 4323
 
3.8%
8 4094
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112475
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 31906
28.4%
0 16452
14.6%
5 13134
11.7%
- 10000
 
8.9%
4 8250
 
7.3%
7 7212
 
6.4%
2 6984
 
6.2%
3 6635
 
5.9%
6 4323
 
3.8%
8 4094
 
3.6%

관리_동별_개요
Text

Distinct1196
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T08:22:16.976533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length10.7582
Min length7

Characters and Unicode

Total characters107582
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)1.0%

Sample

1st row11710-6213
2nd row11545-100005722
3rd row11530-4609
4th row11215-100015261
5th row11560-100010907
ValueCountFrequency (%)
11530-4609 912
 
9.1%
11710-1296 492
 
4.9%
11545-3205 203
 
2.0%
11545-100005722 164
 
1.6%
11545-1937 161
 
1.6%
11545-100014029 153
 
1.5%
11545-3174 139
 
1.4%
11545-2760 131
 
1.3%
11530-2968 130
 
1.3%
11710-10 118
 
1.2%
Other values (1186) 7397
74.0%
2024-05-11T08:22:19.000036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 31198
29.0%
0 16426
15.3%
5 12346
 
11.5%
- 10000
 
9.3%
4 8095
 
7.5%
7 6525
 
6.1%
2 5387
 
5.0%
3 5361
 
5.0%
6 4763
 
4.4%
9 4651
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 97582
90.7%
Dash Punctuation 10000
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 31198
32.0%
0 16426
16.8%
5 12346
 
12.7%
4 8095
 
8.3%
7 6525
 
6.7%
2 5387
 
5.5%
3 5361
 
5.5%
6 4763
 
4.9%
9 4651
 
4.8%
8 2830
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107582
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 31198
29.0%
0 16426
15.3%
5 12346
 
11.5%
- 10000
 
9.3%
4 8095
 
7.5%
7 6525
 
6.1%
2 5387
 
5.0%
3 5361
 
5.0%
6 4763
 
4.4%
9 4651
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107582
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 31198
29.0%
0 16426
15.3%
5 12346
 
11.5%
- 10000
 
9.3%
4 8095
 
7.5%
7 6525
 
6.1%
2 5387
 
5.0%
3 5361
 
5.0%
6 4763
 
4.4%
9 4651
 
4.3%

호_번호
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1546
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean263.8456
Minimum0
Maximum4365
Zeros1164
Zeros (%)11.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:22:19.523286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median8
Q3129.25
95-th percentile1519.05
Maximum4365
Range4365
Interquartile range (IQR)126.25

Descriptive statistics

Standard deviation714.32253
Coefficient of variation (CV)2.7073506
Kurtosis15.804887
Mean263.8456
Median Absolute Deviation (MAD)8
Skewness3.9056895
Sum2638456
Variance510256.68
MonotonicityNot monotonic
2024-05-11T08:22:20.197028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1164
 
11.6%
2 554
 
5.5%
1 533
 
5.3%
4 517
 
5.2%
5 516
 
5.2%
3 515
 
5.1%
6 485
 
4.9%
7 432
 
4.3%
8 343
 
3.4%
9 236
 
2.4%
Other values (1536) 4705
47.0%
ValueCountFrequency (%)
0 1164
11.6%
1 533
5.3%
2 554
5.5%
3 515
5.1%
4 517
5.2%
5 516
5.2%
6 485
4.9%
7 432
 
4.3%
8 343
 
3.4%
9 236
 
2.4%
ValueCountFrequency (%)
4365 1
< 0.1%
4364 1
< 0.1%
4362 1
< 0.1%
4361 1
< 0.1%
4358 1
< 0.1%
4357 1
< 0.1%
4356 1
< 0.1%
4355 1
< 0.1%
4354 1
< 0.1%
4352 1
< 0.1%

호_명칭
Text

Distinct2654
Distinct (%)26.6%
Missing15
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T08:22:21.247300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.7562344
Min length1

Characters and Unicode

Total characters37506
Distinct characters46
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2164 ?
Unique (%)21.7%

Sample

1st row402
2nd row324
3rd row지하1층094호
4th row502
5th row401
ValueCountFrequency (%)
301 598
 
6.0%
201 575
 
5.8%
202 551
 
5.5%
401 550
 
5.5%
302 528
 
5.3%
501 436
 
4.4%
402 419
 
4.2%
502 241
 
2.4%
101 221
 
2.2%
203 154
 
1.5%
Other values (2637) 5715
57.2%
2024-05-11T08:22:22.942397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8842
23.6%
1 7010
18.7%
2 5586
14.9%
3 3340
 
8.9%
4 2515
 
6.7%
5 1841
 
4.9%
호 1538
 
4.1%
6 995
 
2.7%
층 927
 
2.5%
7 883
 
2.4%
Other values (36) 4029
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32653
87.1%
Other Letter 3304
 
8.8%
Uppercase Letter 858
 
2.3%
Dash Punctuation 616
 
1.6%
Other Punctuation 54
 
0.1%
Lowercase Letter 17
 
< 0.1%
Space Separator 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 1538
46.5%
층 927
28.1%
지 165
 
5.0%
하 157
 
4.8%
오 131
 
4.0%
트 65
 
2.0%
파 65
 
2.0%
아 65
 
2.0%
텔 45
 
1.4%
스 45
 
1.4%
Other values (14) 101
 
3.1%
Decimal Number
ValueCountFrequency (%)
0 8842
27.1%
1 7010
21.5%
2 5586
17.1%
3 3340
 
10.2%
4 2515
 
7.7%
5 1841
 
5.6%
6 995
 
3.0%
7 883
 
2.7%
8 870
 
2.7%
9 771
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
B 445
51.9%
C 208
24.2%
A 184
21.4%
F 12
 
1.4%
D 8
 
0.9%
O 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/ 32
59.3%
, 22
40.7%
Dash Punctuation
ValueCountFrequency (%)
- 616
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 17
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33327
88.9%
Hangul 3304
 
8.8%
Latin 875
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 1538
46.5%
층 927
28.1%
지 165
 
5.0%
하 157
 
4.8%
오 131
 
4.0%
트 65
 
2.0%
파 65
 
2.0%
아 65
 
2.0%
텔 45
 
1.4%
스 45
 
1.4%
Other values (14) 101
 
3.1%
Common
ValueCountFrequency (%)
0 8842
26.5%
1 7010
21.0%
2 5586
16.8%
3 3340
 
10.0%
4 2515
 
7.5%
5 1841
 
5.5%
6 995
 
3.0%
7 883
 
2.6%
8 870
 
2.6%
9 771
 
2.3%
Other values (5) 674
 
2.0%
Latin
ValueCountFrequency (%)
B 445
50.9%
C 208
23.8%
A 184
21.0%
b 17
 
1.9%
F 12
 
1.4%
D 8
 
0.9%
O 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34202
91.2%
Hangul 3304
 
8.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8842
25.9%
1 7010
20.5%
2 5586
16.3%
3 3340
 
9.8%
4 2515
 
7.4%
5 1841
 
5.4%
6 995
 
2.9%
7 883
 
2.6%
8 870
 
2.5%
9 771
 
2.3%
Other values (12) 1549
 
4.5%
Hangul
ValueCountFrequency (%)
호 1538
46.5%
층 927
28.1%
지 165
 
5.0%
하 157
 
4.8%
오 131
 
4.0%
트 65
 
2.0%
파 65
 
2.0%
아 65
 
2.0%
텔 45
 
1.4%
스 45
 
1.4%
Other values (14) 101
 
3.1%

평형_구분_명
Text

Distinct3290
Distinct (%)33.2%
Missing97
Missing (%)1.0%
Memory size156.2 KiB
2024-05-11T08:22:23.933948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length3.9301222
Min length1

Characters and Unicode

Total characters38920
Distinct characters79
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2098 ?
Unique (%)21.2%

Sample

1st row8b
2nd row131.96b
3rd row60
4th rowA
5th rowB
ValueCountFrequency (%)
1000 311
 
3.1%
19 184
 
1.9%
21 106
 
1.1%
18 79
 
0.8%
a 73
 
0.7%
b 71
 
0.7%
17a 71
 
0.7%
20 66
 
0.7%
22 64
 
0.6%
10.21a 64
 
0.6%
Other values (3199) 8846
89.0%
2024-05-11T08:22:25.486991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6057
15.6%
. 4391
11.3%
2 3951
10.2%
0 3218
8.3%
4 2636
 
6.8%
3 2612
 
6.7%
6 2367
 
6.1%
5 2317
 
6.0%
8 2241
 
5.8%
7 2143
 
5.5%
Other values (69) 6987
18.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29641
76.2%
Other Punctuation 4394
 
11.3%
Uppercase Letter 3937
 
10.1%
Lowercase Letter 677
 
1.7%
Other Letter 173
 
0.4%
Dash Punctuation 52
 
0.1%
Space Separator 32
 
0.1%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1508
38.3%
B 947
24.1%
C 492
 
12.5%
D 152
 
3.9%
Z 150
 
3.8%
R 110
 
2.8%
L 108
 
2.7%
E 108
 
2.7%
F 82
 
2.1%
W 59
 
1.5%
Other values (15) 221
 
5.6%
Other Letter
ValueCountFrequency (%)
형 49
28.3%
호 41
23.7%
평 24
13.9%
가 15
 
8.7%
층 8
 
4.6%
다 7
 
4.0%
나 5
 
2.9%
라 3
 
1.7%
축 2
 
1.2%
증 2
 
1.2%
Other values (14) 17
 
9.8%
Lowercase Letter
ValueCountFrequency (%)
a 324
47.9%
b 128
 
18.9%
o 62
 
9.2%
c 58
 
8.6%
d 39
 
5.8%
f 19
 
2.8%
e 18
 
2.7%
g 10
 
1.5%
h 8
 
1.2%
s 7
 
1.0%
Other values (4) 4
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 6057
20.4%
2 3951
13.3%
0 3218
10.9%
4 2636
8.9%
3 2612
8.8%
6 2367
 
8.0%
5 2317
 
7.8%
8 2241
 
7.6%
7 2143
 
7.2%
9 2099
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 4391
99.9%
, 3
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34133
87.7%
Latin 4614
 
11.9%
Hangul 173
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1508
32.7%
B 947
20.5%
C 492
 
10.7%
a 324
 
7.0%
D 152
 
3.3%
Z 150
 
3.3%
b 128
 
2.8%
R 110
 
2.4%
L 108
 
2.3%
E 108
 
2.3%
Other values (29) 587
 
12.7%
Hangul
ValueCountFrequency (%)
형 49
28.3%
호 41
23.7%
평 24
13.9%
가 15
 
8.7%
층 8
 
4.6%
다 7
 
4.0%
나 5
 
2.9%
라 3
 
1.7%
축 2
 
1.2%
증 2
 
1.2%
Other values (14) 17
 
9.8%
Common
ValueCountFrequency (%)
1 6057
17.7%
. 4391
12.9%
2 3951
11.6%
0 3218
9.4%
4 2636
7.7%
3 2612
7.7%
6 2367
 
6.9%
5 2317
 
6.8%
8 2241
 
6.6%
7 2143
 
6.3%
Other values (6) 2200
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38747
99.6%
Hangul 173
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6057
15.6%
. 4391
11.3%
2 3951
10.2%
0 3218
8.3%
4 2636
 
6.8%
3 2612
 
6.7%
6 2367
 
6.1%
5 2317
 
6.0%
8 2241
 
5.8%
7 2143
 
5.5%
Other values (45) 6814
17.6%
Hangul
ValueCountFrequency (%)
형 49
28.3%
호 41
23.7%
평 24
13.9%
가 15
 
8.7%
층 8
 
4.6%
다 7
 
4.0%
나 5
 
2.9%
라 3
 
1.7%
축 2
 
1.2%
증 2
 
1.2%
Other values (14) 17
 
9.8%

층_번호
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7691
Minimum0
Maximum46
Zeros13
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:22:25.911116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q36
95-th percentile17
Maximum46
Range46
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.4357849
Coefficient of variation (CV)1.1155613
Kurtosis10.870795
Mean5.7691
Median Absolute Deviation (MAD)2
Skewness3.0231883
Sum57691
Variance41.419327
MonotonicityNot monotonic
2024-05-11T08:22:26.335747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
2 1814
18.1%
3 1614
16.1%
4 1475
14.8%
1 1202
12.0%
5 1036
10.4%
6 388
 
3.9%
9 335
 
3.4%
8 322
 
3.2%
7 280
 
2.8%
12 178
 
1.8%
Other values (37) 1356
13.6%
ValueCountFrequency (%)
0 13
 
0.1%
1 1202
12.0%
2 1814
18.1%
3 1614
16.1%
4 1475
14.8%
5 1036
10.4%
6 388
 
3.9%
7 280
 
2.8%
8 322
 
3.2%
9 335
 
3.4%
ValueCountFrequency (%)
46 2
 
< 0.1%
45 7
 
0.1%
44 5
 
0.1%
43 7
 
0.1%
42 4
 
< 0.1%
41 9
 
0.1%
40 7
 
0.1%
39 7
 
0.1%
38 17
0.2%
37 24
0.2%

층_구분_코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20
9477 
10
 
523

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20
2nd row20
3rd row10
4th row20
5th row20

Common Values

ValueCountFrequency (%)
20 9477
94.8%
10 523
 
5.2%

Length

2024-05-11T08:22:26.683548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:22:26.955318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20 9477
94.8%
10 523
 
5.2%

관리_건축물대장_참조
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

변경_구분_코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

작업_일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20111227
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20111227
2nd row20111227
3rd row20111227
4th row20111227
5th row20111227

Common Values

ValueCountFrequency (%)
20111227 10000
100.0%

Length

2024-05-11T08:22:27.393724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:22:27.686213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20111227 10000
100.0%

Interactions

2024-05-11T08:22:12.240048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:22:11.683717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:22:12.587566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:22:11.933621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T08:22:27.860783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호_번호층_번호층_구분_코드
호_번호1.0000.5900.087
층_번호0.5901.0000.235
층_구분_코드0.0870.2351.000
2024-05-11T08:22:28.153826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호_번호층_번호층_구분_코드
호_번호1.0000.5650.087
층_번호0.5651.0000.180
층_구분_코드0.0870.1801.000

Missing values

2024-05-11T08:22:12.994697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T08:22:13.617534image/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.
2024-05-11T08:22:14.026057image/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

관리_호별_명세관리_동별_개요호_번호호_명칭평형_구분_명층_번호층_구분_코드관리_건축물대장_참조변경_구분_코드작업_일자
1111511710-2503911710-621364028b420<NA><NA>20111227
1348611545-10000432311545-100005722118324131.96b320<NA><NA>20111227
169811530-2859411530-460996지하1층094호60110<NA><NA>20111227
35111215-10000684111215-1000152610502A520<NA><NA>20111227
453911560-10000503111560-1000109070401B420<NA><NA>20111227
389311710-2217511710-5401630314.38b320<NA><NA>20111227
113611530-3282711530-4609432936층오12호5263620<NA><NA>20111227
1616711710-2847411710-866153027E320<NA><NA>20111227
1591911710-2677211710-69431201호16.85220<NA><NA>20111227
326511440-10000872111440-100020168010311120<NA><NA>20111227
관리_호별_명세관리_동별_개요호_번호호_명칭평형_구분_명층_번호층_구분_코드관리_건축물대장_참조변경_구분_코드작업_일자
323811530-2867311530-4609175지하1층173호92110<NA><NA>20111227
301411530-3037811530-460918805층002호75520<NA><NA>20111227
1625111710-314611710-1296527A-130426A1320<NA><NA>20111227
725811545-1323211545-3212540123.37420<NA><NA>20111227
794611545-538011545-1903530121.38320<NA><NA>20111227
1327811530-874311530-296817861919620<NA><NA>20111227
892111710-722011710-2424320314C220<NA><NA>20111227
293011530-303411530-1913653152220.43B1520<NA><NA>20111227
461811545-1239911545-2768411004301020<NA><NA>20111227
533211545-175911545-897630177.75320<NA><NA>20111227