Overview

Dataset statistics

Number of variables14
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory119.4 B

Variable types

Numeric3
Text1
Categorical9
DateTime1

Dataset

Description객체id,현황도형 관리번호,도형 대분류코드,도형 중분류코드,도형 소분류코드,도형 속성코드,도형 조서관리 코드,결정고시관리코드,라벨명,시군구코드,도면번호,현황도형 생성일시,면적(도형),길이(도형)
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21133/S/1/datasetView.do

Alerts

도형 중분류코드 has constant value ""Constant
도형 소분류코드 has constant value ""Constant
시군구코드 has constant value ""Constant
현황도형 생성일시 has constant value ""Constant
라벨명 is highly overall correlated with 면적(도형) and 6 other fieldsHigh correlation
도형 대분류코드 is highly overall correlated with 면적(도형) and 5 other fieldsHigh correlation
도면번호 is highly overall correlated with 면적(도형) and 4 other fieldsHigh correlation
도형 속성코드 is highly overall correlated with 면적(도형) and 5 other fieldsHigh correlation
결정고시관리코드 is highly overall correlated with 면적(도형) and 6 other fieldsHigh correlation
도형 조서관리 코드 is highly overall correlated with 면적(도형) and 6 other fieldsHigh correlation
면적(도형) is highly overall correlated with 길이(도형) and 6 other fieldsHigh correlation
길이(도형) is highly overall correlated with 면적(도형) and 6 other fieldsHigh correlation
도형 대분류코드 is highly imbalanced (60.9%)Imbalance
도형 속성코드 is highly imbalanced (60.9%)Imbalance
도형 조서관리 코드 is highly imbalanced (74.3%)Imbalance
결정고시관리코드 is highly imbalanced (74.3%)Imbalance
도면번호 is highly imbalanced (82.8%)Imbalance
객체id has unique valuesUnique
현황도형 관리번호 has unique valuesUnique
면적(도형) has unique valuesUnique
길이(도형) has unique valuesUnique

Reproduction

Analysis started2024-05-10 22:47:03.693933
Analysis finished2024-05-10 22:47:08.037966
Duration4.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

객체id
Real number (ℝ)

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11203.231
Minimum10911
Maximum11237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-05-10T22:47:08.295728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10911
5-th percentile11172.1
Q111208.5
median11218
Q311227.5
95-th percentile11235.1
Maximum11237
Range326
Interquartile range (IQR)19

Descriptive statistics

Standard deviation69.515792
Coefficient of variation (CV)0.0062049772
Kurtosis15.879404
Mean11203.231
Median Absolute Deviation (MAD)10
Skewness-4.0717844
Sum436926
Variance4832.4453
MonotonicityStrictly increasing
2024-05-10T22:47:08.814942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
10911 1
 
2.6%
10912 1
 
2.6%
11221 1
 
2.6%
11222 1
 
2.6%
11223 1
 
2.6%
11224 1
 
2.6%
11225 1
 
2.6%
11226 1
 
2.6%
11227 1
 
2.6%
11228 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
10911 1
2.6%
10912 1
2.6%
11201 1
2.6%
11202 1
2.6%
11203 1
2.6%
11204 1
2.6%
11205 1
2.6%
11206 1
2.6%
11207 1
2.6%
11208 1
2.6%
ValueCountFrequency (%)
11237 1
2.6%
11236 1
2.6%
11235 1
2.6%
11234 1
2.6%
11233 1
2.6%
11232 1
2.6%
11231 1
2.6%
11230 1
2.6%
11229 1
2.6%
11228 1
2.6%

현황도형 관리번호
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-05-10T22:47:09.523918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters936
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st row11000UQ131PS201912150043
2nd row11000UQ131PS201912150044
3rd row11000UQ131PS201912150045
4th row11000UQ131PS201912150046
5th row11000UQ131PS201912150047
ValueCountFrequency (%)
11000uq131ps201912150043 1
 
2.6%
11000uq131ps201912150063 1
 
2.6%
11000uq131ps201912150065 1
 
2.6%
11000uq131ps201912150066 1
 
2.6%
11000uq131ps201912150067 1
 
2.6%
11000uq131ps201912150068 1
 
2.6%
11000uq131ps201912150069 1
 
2.6%
11000uq131ps201912150070 1
 
2.6%
11000uq131ps201912150071 1
 
2.6%
11000uq131ps201912150064 1
 
2.6%
Other values (29) 29
74.4%
2024-05-10T22:47:10.611880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 277
29.6%
0 240
25.6%
2 85
 
9.1%
5 52
 
5.6%
3 44
 
4.7%
9 44
 
4.7%
U 39
 
4.2%
Q 39
 
4.2%
P 39
 
4.2%
S 39
 
4.2%
Other values (4) 38
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 780
83.3%
Uppercase Letter 156
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 277
35.5%
0 240
30.8%
2 85
 
10.9%
5 52
 
6.7%
3 44
 
5.6%
9 44
 
5.6%
4 14
 
1.8%
6 13
 
1.7%
7 7
 
0.9%
8 4
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
U 39
25.0%
Q 39
25.0%
P 39
25.0%
S 39
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 780
83.3%
Latin 156
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 277
35.5%
0 240
30.8%
2 85
 
10.9%
5 52
 
6.7%
3 44
 
5.6%
9 44
 
5.6%
4 14
 
1.8%
6 13
 
1.7%
7 7
 
0.9%
8 4
 
0.5%
Latin
ValueCountFrequency (%)
U 39
25.0%
Q 39
25.0%
P 39
25.0%
S 39
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 936
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 277
29.6%
0 240
25.6%
2 85
 
9.1%
5 52
 
5.6%
3 44
 
4.7%
9 44
 
4.7%
U 39
 
4.2%
Q 39
 
4.2%
P 39
 
4.2%
S 39
 
4.2%
Other values (4) 38
 
4.1%

도형 대분류코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
UQP999
36 
UQP190
 
3

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQP999
2nd rowUQP999
3rd rowUQP999
4th rowUQP999
5th rowUQP999

Common Values

ValueCountFrequency (%)
UQP999 36
92.3%
UQP190 3
 
7.7%

Length

2024-05-10T22:47:11.052636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:47:11.355199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqp999 36
92.3%
uqp190 3
 
7.7%

도형 중분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
39 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
39
100.0%

Length

2024-05-10T22:47:11.597989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:47:11.829050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 소분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
39 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
39
100.0%

Length

2024-05-10T22:47:12.143500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:47:12.455294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 속성코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
UQP999
36 
UQP190
 
3

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQP999
2nd rowUQP999
3rd rowUQP999
4th rowUQP999
5th rowUQP999

Common Values

ValueCountFrequency (%)
UQP999 36
92.3%
UQP190 3
 
7.7%

Length

2024-05-10T22:47:12.786517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:47:13.106796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqp999 36
92.3%
uqp190 3
 
7.7%

도형 조서관리 코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size444.0 B
11000DSZ000000001311
36 
11000DSZ201807166973
 
1
11000DSZ200405201749
 
1
11000DSZ200204271502
 
1

Length

Max length20
Median length20
Mean length20
Min length20

Unique

Unique3 ?
Unique (%)7.7%

Sample

1st row11000DSZ000000001311
2nd row11000DSZ000000001311
3rd row11000DSZ000000001311
4th row11000DSZ000000001311
5th row11000DSZ000000001311

Common Values

ValueCountFrequency (%)
11000DSZ000000001311 36
92.3%
11000DSZ201807166973 1
 
2.6%
11000DSZ200405201749 1
 
2.6%
11000DSZ200204271502 1
 
2.6%

Length

2024-05-10T22:47:13.442488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:47:13.769661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11000dsz000000001311 36
92.3%
11000dsz201807166973 1
 
2.6%
11000dsz200405201749 1
 
2.6%
11000dsz200204271502 1
 
2.6%

결정고시관리코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size444.0 B
36 
11000NTC201805319185
 
1
11000NTC200405206260
 
1
11000NTC200204272453
 
1

Length

Max length20
Median length1
Mean length2.4615385
Min length1

Unique

Unique3 ?
Unique (%)7.7%

Sample

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

Common Values

ValueCountFrequency (%)
36
92.3%
11000NTC201805319185 1
 
2.6%
11000NTC200405206260 1
 
2.6%
11000NTC200204272453 1
 
2.6%

Length

2024-05-10T22:47:14.187199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:47:14.556022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11000ntc201805319185 1
33.3%
11000ntc200405206260 1
33.3%
11000ntc200204272453 1
33.3%

라벨명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
주구중심
15 
분구중심
13 
지구중심
3 
기타용도지구
2 
지정제건축선
2 
Other values (4)
4 

Length

Max length9
Median length4
Mean length4.6153846
Min length4

Unique

Unique4 ?
Unique (%)10.3%

Sample

1st row주구중심
2nd row주구중심
3rd row주구중심
4th row지구중심
5th row주구중심

Common Values

ValueCountFrequency (%)
주구중심 15
38.5%
분구중심 13
33.3%
지구중심 3
 
7.7%
기타용도지구 2
 
5.1%
지정제건축선 2
 
5.1%
서초음악 문화지구 1
 
2.6%
행위허가금지대상지 1
 
2.6%
대학로문화지구 1
 
2.6%
인사동문화지구 1
 
2.6%

Length

2024-05-10T22:47:14.954294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:47:15.341741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주구중심 15
37.5%
분구중심 13
32.5%
지구중심 3
 
7.5%
기타용도지구 2
 
5.0%
지정제건축선 2
 
5.0%
서초음악 1
 
2.5%
문화지구 1
 
2.5%
행위허가금지대상지 1
 
2.5%
대학로문화지구 1
 
2.5%
인사동문화지구 1
 
2.5%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
11000
39 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11000
2nd row11000
3rd row11000
4th row11000
5th row11000

Common Values

ValueCountFrequency (%)
11000 39
100.0%

Length

2024-05-10T22:47:15.664913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:47:15.905344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11000 39
100.0%

도면번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
38 
①
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
38
97.4%
① 1
 
2.6%

Length

2024-05-10T22:47:16.209545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:47:16.490564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
① 1
100.0%

현황도형 생성일시
Date

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
Minimum2019-12-15 00:00:00
Maximum2019-12-15 00:00:00
2024-05-10T22:47:16.767987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:47:17.020146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

면적(도형)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32781.26
Minimum55.848136
Maximum446629.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-05-10T22:47:17.439366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum55.848136
5-th percentile470.71629
Q12463.8397
median7245.6594
Q310893.958
95-th percentile200078.38
Maximum446629.19
Range446573.35
Interquartile range (IQR)8430.118

Descriptive statistics

Standard deviation97309.091
Coefficient of variation (CV)2.9684366
Kurtosis13.953218
Mean32781.26
Median Absolute Deviation (MAD)4683.9981
Skewness3.8192811
Sum1278469.1
Variance9.4690591 × 109
MonotonicityNot monotonic
2024-05-10T22:47:17.854233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
6657.22393825 1
 
2.6%
11093.1462269 1
 
2.6%
2228.09691375 1
 
2.6%
7572.96693824 1
 
2.6%
3215.99771277 1
 
2.6%
1799.36835218 1
 
2.6%
1497.61835529 1
 
2.6%
999.87430501 1
 
2.6%
1082.30978495 1
 
2.6%
14758.7513637 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
55.84813607 1
2.6%
131.88959598 1
2.6%
508.36370474 1
2.6%
545.49796864 1
2.6%
999.87430501 1
2.6%
1082.30978495 1
2.6%
1497.61835529 1
2.6%
1799.36835218 1
2.6%
2228.09691375 1
2.6%
2366.01803258 1
2.6%
ValueCountFrequency (%)
446629.194811 1
2.6%
410109.244441 1
2.6%
176741.622702 1
2.6%
22874.591458 1
2.6%
20974.5253395 1
2.6%
16015.3041765 1
2.6%
14758.7513637 1
2.6%
13191.4460052 1
2.6%
12689.7087112 1
2.6%
11093.1462269 1
2.6%

길이(도형)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean671.8401
Minimum43.978401
Maximum4552.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-05-10T22:47:18.422035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43.978401
5-th percentile91.55344
Q1202.951
median381.397
Q3709.905
95-th percentile2032.665
Maximum4552.75
Range4508.7716
Interquartile range (IQR)506.95399

Descriptive statistics

Standard deviation914.9234
Coefficient of variation (CV)1.3618172
Kurtosis10.489565
Mean671.8401
Median Absolute Deviation (MAD)228.369
Skewness3.1186429
Sum26201.764
Variance837084.82
MonotonicityNot monotonic
2024-05-10T22:47:18.808651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
584.25598145 1
 
2.6%
894.68798828 1
 
2.6%
189.29100037 1
 
2.6%
349.27700806 1
 
2.6%
223.47799683 1
 
2.6%
168.95500183 1
 
2.6%
153.02799988 1
 
2.6%
124.84999847 1
 
2.6%
133.68099976 1
 
2.6%
866.18499756 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
43.97840118 1
2.6%
75.57969666 1
2.6%
93.32830048 1
2.6%
97.74669647 1
2.6%
124.84999847 1
2.6%
133.68099976 1
2.6%
153.02799988 1
2.6%
168.95500183 1
2.6%
189.29100037 1
2.6%
201.32600403 1
2.6%
ValueCountFrequency (%)
4552.75 1
2.6%
3674.76000977 1
2.6%
1850.20996094 1
2.6%
1652.80004883 1
2.6%
1346.63000488 1
2.6%
894.68798828 1
2.6%
866.18499756 1
2.6%
859.08398438 1
2.6%
797.59899902 1
2.6%
762.91101074 1
2.6%

Interactions

2024-05-10T22:47:06.105668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:47:04.752658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:47:05.440397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:47:06.358869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:47:04.965926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:47:05.680530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:47:06.590084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:47:05.196587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:47:05.928888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T22:47:19.144404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id현황도형 관리번호도형 대분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명도면번호면적(도형)길이(도형)
객체id1.0001.0000.0000.0000.0000.0000.0000.0000.0000.000
현황도형 관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도형 대분류코드0.0001.0001.0000.9581.0001.0001.0000.3161.0001.000
도형 속성코드0.0001.0000.9581.0001.0001.0001.0000.3161.0001.000
도형 조서관리 코드0.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
결정고시관리코드0.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
라벨명0.0001.0001.0001.0001.0001.0001.0001.0001.0000.872
도면번호0.0001.0000.3160.3161.0001.0001.0001.0000.4351.000
면적(도형)0.0001.0001.0001.0001.0001.0001.0000.4351.0001.000
길이(도형)0.0001.0001.0001.0001.0001.0000.8721.0001.0001.000
2024-05-10T22:47:19.492838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
라벨명도형 대분류코드도면번호도형 속성코드결정고시관리코드도형 조서관리 코드
라벨명1.0000.9000.9000.9000.9260.926
도형 대분류코드0.9001.0000.2030.8140.9730.973
도면번호0.9000.2031.0000.2030.9730.973
도형 속성코드0.9000.8140.2031.0000.9730.973
결정고시관리코드0.9260.9730.9730.9731.0001.000
도형 조서관리 코드0.9260.9730.9730.9731.0001.000
2024-05-10T22:47:19.801690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id면적(도형)길이(도형)도형 대분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명도면번호
객체id1.000-0.147-0.1570.0000.0000.0000.0000.0000.000
면적(도형)-0.1471.0000.9520.9860.9860.9860.9860.9130.668
길이(도형)-0.1570.9521.0000.9300.9300.9560.9560.6890.930
도형 대분류코드0.0000.9860.9301.0000.8140.9730.9730.9000.203
도형 속성코드0.0000.9860.9300.8141.0000.9730.9730.9000.203
도형 조서관리 코드0.0000.9860.9560.9730.9731.0001.0000.9260.973
결정고시관리코드0.0000.9860.9560.9730.9731.0001.0000.9260.973
라벨명0.0000.9130.6890.9000.9000.9260.9261.0000.900
도면번호0.0000.6680.9300.2030.2030.9730.9730.9001.000

Missing values

2024-05-10T22:47:07.077068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T22:47:07.731332image/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

객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호현황도형 생성일시면적(도형)길이(도형)
01091111000UQ131PS201912150043UQP999UQP99911000DSZ000000001311주구중심110002019-12-15 00:00:00.06657.223938584.255981
11091211000UQ131PS201912150044UQP999UQP99911000DSZ000000001311주구중심110002019-12-15 00:00:00.011093.146227894.687988
21120111000UQ131PS201912150045UQP999UQP99911000DSZ000000001311주구중심110002019-12-15 00:00:00.05580.875374349.77301
31120211000UQ131PS201912150046UQP999UQP99911000DSZ000000001311지구중심110002019-12-15 00:00:00.020974.525339572.479004
41120311000UQ131PS201912150047UQP999UQP99911000DSZ000000001311주구중심110002019-12-15 00:00:00.08454.491389446.845001
51120411000UQ131PS201912150048UQP999UQP99911000DSZ000000001311분구중심110002019-12-15 00:00:00.08987.976211559.192993
61120511000UQ131PS201912150049UQP999UQP99911000DSZ000000001311지구중심110002019-12-15 00:00:00.022874.5914581652.800049
71120611000UQ131PS201912150050UQP999UQP99911000DSZ000000001311분구중심110002019-12-15 00:00:00.02366.018033201.326004
81120711000UQ131PS201912150051UQP999UQP99911000DSZ000000001311분구중심110002019-12-15 00:00:00.03319.472002232.901993
91120811000UQ131PS201912150052UQP999UQP99911000DSZ000000001311주구중심110002019-12-15 00:00:00.09313.840903611.578003
객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호현황도형 생성일시면적(도형)길이(도형)
291122811000UQ131PS201912150072UQP999UQP99911000DSZ000000001311지구중심110002019-12-15 00:00:00.014758.751364866.184998
301122911000UQ131PS201912150004UQP190UQP19011000DSZ20180716697311000NTC201805319185서초음악 문화지구11000①2019-12-15 00:00:00.0410109.2444413674.76001
311123011000UQ131PS201912150039UQP999UQP99911000DSZ000000001311기타용도지구110002019-12-15 00:00:00.02568.853042211.824997
321123111000UQ131PS201912150040UQP999UQP99911000DSZ000000001311주구중심110002019-12-15 00:00:00.07389.951671381.397003
331123211000UQ131PS201912150041UQP999UQP99911000DSZ000000001311행위허가금지대상지110002019-12-15 00:00:00.016015.304176620.844971
341123311000UQ131PS201912150042UQP999UQP99911000DSZ000000001311주구중심110002019-12-15 00:00:00.07245.659423656.898987
351123411000UQ131PS201912150027UQP190UQP19011000DSZ20040520174911000NTC200405206260대학로문화지구110002019-12-15 00:00:00.0446629.1948114552.75
361123511000UQ131PS201912150028UQP190UQP19011000DSZ20020427150211000NTC200204272453인사동문화지구110002019-12-15 00:00:00.0176741.6227021850.209961
371123611000UQ131PS201912150029UQP999UQP99911000DSZ000000001311지정제건축선110002019-12-15 00:00:00.0131.88959675.579697
381123711000UQ131PS201912150030UQP999UQP99911000DSZ000000001311지정제건축선110002019-12-15 00:00:00.055.84813643.978401