Overview

Dataset statistics

Number of variables14
Number of observations142
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.2 KiB
Average record size in memory116.9 B

Variable types

Numeric3
Text2
Categorical8
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-21140/S/1/datasetView.do

Alerts

도형 대분류코드 has constant value ""Constant
도형 중분류코드 has constant value ""Constant
도형 소분류코드 has constant value ""Constant
도형 속성코드 has constant value ""Constant
시군구코드 is highly overall correlated with 결정고시관리코드 and 1 other fieldsHigh correlation
결정고시관리코드 is highly overall correlated with 시군구코드 and 1 other fieldsHigh correlation
도면번호 is highly overall correlated with 면적(도형) and 3 other fieldsHigh correlation
면적(도형) is highly overall correlated with 길이(도형) and 1 other fieldsHigh correlation
길이(도형) is highly overall correlated with 면적(도형) and 1 other fieldsHigh correlation
라벨명 is highly imbalanced (65.7%)Imbalance
시군구코드 is highly imbalanced (92.4%)Imbalance
도면번호 is highly imbalanced (89.3%)Imbalance
객체id has unique valuesUnique
현황도형 관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-11 09:33:01.299711
Analysis finished2024-05-11 09:33:07.177457
Duration5.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

객체id
Real number (ℝ)

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11902.542
Minimum11661
Maximum11978
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T09:33:07.517373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11661
5-th percentile11844.05
Q111872.25
median11907.5
Q311942.75
95-th percentile11970.95
Maximum11978
Range317
Interquartile range (IQR)70.5

Descriptive statistics

Standard deviation56.878697
Coefficient of variation (CV)0.0047787015
Kurtosis6.813997
Mean11902.542
Median Absolute Deviation (MAD)35.5
Skewness-1.9824225
Sum1690161
Variance3235.1861
MonotonicityStrictly increasing
2024-05-11T09:33:08.163150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11661 1
 
0.7%
11935 1
 
0.7%
11929 1
 
0.7%
11930 1
 
0.7%
11931 1
 
0.7%
11932 1
 
0.7%
11933 1
 
0.7%
11934 1
 
0.7%
11936 1
 
0.7%
11927 1
 
0.7%
Other values (132) 132
93.0%
ValueCountFrequency (%)
11661 1
0.7%
11662 1
0.7%
11663 1
0.7%
11664 1
0.7%
11841 1
0.7%
11842 1
0.7%
11843 1
0.7%
11844 1
0.7%
11845 1
0.7%
11846 1
0.7%
ValueCountFrequency (%)
11978 1
0.7%
11977 1
0.7%
11976 1
0.7%
11975 1
0.7%
11974 1
0.7%
11973 1
0.7%
11972 1
0.7%
11971 1
0.7%
11970 1
0.7%
11969 1
0.7%

현황도형 관리번호
Text

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T09:33:08.938917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters3408
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

Unique142 ?
Unique (%)100.0%

Sample

1st row11000UQ124PS201912150005
2nd row11000UQ124PS201912150007
3rd row11000UQ124PS201912150015
4th row11000UQ124PS201912150016
5th row11000UQ124PS201912150134
ValueCountFrequency (%)
11000uq124ps201912150005 1
 
0.7%
11000uq124ps201912150175 1
 
0.7%
11000uq124ps201912150177 1
 
0.7%
11000uq124ps201912150170 1
 
0.7%
11000uq124ps201912150171 1
 
0.7%
11000uq124ps201912150172 1
 
0.7%
11000uq124ps201912150173 1
 
0.7%
11000uq124ps201912150174 1
 
0.7%
11000uq124ps201912150168 1
 
0.7%
11000uq124ps201912150167 1
 
0.7%
Other values (132) 132
93.0%
2024-05-11T09:33:10.250531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 981
28.8%
0 778
22.8%
2 460
13.5%
9 171
 
5.0%
4 170
 
5.0%
5 168
 
4.9%
U 142
 
4.2%
Q 142
 
4.2%
P 142
 
4.2%
S 142
 
4.2%
Other values (4) 112
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2840
83.3%
Uppercase Letter 568
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 981
34.5%
0 778
27.4%
2 460
16.2%
9 171
 
6.0%
4 170
 
6.0%
5 168
 
5.9%
7 32
 
1.1%
6 28
 
1.0%
8 27
 
1.0%
3 25
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
U 142
25.0%
Q 142
25.0%
P 142
25.0%
S 142
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2840
83.3%
Latin 568
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 981
34.5%
0 778
27.4%
2 460
16.2%
9 171
 
6.0%
4 170
 
6.0%
5 168
 
5.9%
7 32
 
1.1%
6 28
 
1.0%
8 27
 
1.0%
3 25
 
0.9%
Latin
ValueCountFrequency (%)
U 142
25.0%
Q 142
25.0%
P 142
25.0%
S 142
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 981
28.8%
0 778
22.8%
2 460
13.5%
9 171
 
5.0%
4 170
 
5.0%
5 168
 
4.9%
U 142
 
4.2%
Q 142
 
4.2%
P 142
 
4.2%
S 142
 
4.2%
Other values (4) 112
 
3.3%

도형 대분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
UQI100
142 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQI100
2nd rowUQI100
3rd rowUQI100
4th rowUQI100
5th rowUQI100

Common Values

ValueCountFrequency (%)
UQI100 142
100.0%

Length

2024-05-11T09:33:10.886004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:33:11.438720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqi100 142
100.0%

도형 중분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
142 

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 (%)
142
100.0%

Length

2024-05-11T09:33:11.887485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:33:12.282274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 소분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
142 

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 (%)
142
100.0%

Length

2024-05-11T09:33:12.785123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:33:13.310563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 속성코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
UQI100
142 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQI100
2nd rowUQI100
3rd rowUQI100
4th rowUQI100
5th rowUQI100

Common Values

ValueCountFrequency (%)
UQI100 142
100.0%

Length

2024-05-11T09:33:13.848603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:33:14.278198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqi100 142
100.0%

도형 조서관리 코드
Text

Distinct80
Distinct (%)56.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T09:33:15.036066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters2840
Distinct characters13
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

Unique57 ?
Unique (%)40.1%

Sample

1st row11000DSZ196710251458
2nd row11000DSZ200107101491
3rd row11000DSZ196312131352
4th row11000DSZ196312131356
5th row11000DSZ000000001241
ValueCountFrequency (%)
11000dsz000000001241 41
28.9%
11000dsz196312131397 2
 
1.4%
11000dsz196312131351 2
 
1.4%
11000dsz201308066580 2
 
1.4%
11000dsz196312131419 2
 
1.4%
11000dsz196312131380 2
 
1.4%
11000dsz196402121443 2
 
1.4%
11000dsz200107101491 2
 
1.4%
11000dsz197008060685 2
 
1.4%
11000dsz197008060687 2
 
1.4%
Other values (70) 83
58.5%
2024-05-11T09:33:16.416174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 855
30.1%
1 728
25.6%
3 214
 
7.5%
2 156
 
5.5%
D 142
 
5.0%
S 142
 
5.0%
Z 142
 
5.0%
6 119
 
4.2%
9 114
 
4.0%
4 99
 
3.5%
Other values (3) 129
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2414
85.0%
Uppercase Letter 426
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 855
35.4%
1 728
30.2%
3 214
 
8.9%
2 156
 
6.5%
6 119
 
4.9%
9 114
 
4.7%
4 99
 
4.1%
7 53
 
2.2%
8 43
 
1.8%
5 33
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
D 142
33.3%
S 142
33.3%
Z 142
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2414
85.0%
Latin 426
 
15.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 855
35.4%
1 728
30.2%
3 214
 
8.9%
2 156
 
6.5%
6 119
 
4.9%
9 114
 
4.7%
4 99
 
4.1%
7 53
 
2.2%
8 43
 
1.8%
5 33
 
1.4%
Latin
ValueCountFrequency (%)
D 142
33.3%
S 142
33.3%
Z 142
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 855
30.1%
1 728
25.6%
3 214
 
7.5%
2 156
 
5.5%
D 142
 
5.0%
S 142
 
5.0%
Z 142
 
5.0%
6 119
 
4.2%
9 114
 
4.0%
4 99
 
3.5%
Other values (3) 129
 
4.5%

결정고시관리코드
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
11000NTC196312130175
70 
41 
11000NTC197008060522
 
5
11000NTC197306051020
 
4
11000NTC201306076846
 
3
Other values (12)
19 

Length

Max length20
Median length20
Mean length14.514085
Min length1

Unique

Unique7 ?
Unique (%)4.9%

Sample

1st row11000NTC196710250315
2nd row11000NTC200107101009
3rd row11000NTC196312130175
4th row11000NTC196312130175
5th row

Common Values

ValueCountFrequency (%)
11000NTC196312130175 70
49.3%
41
28.9%
11000NTC197008060522 5
 
3.5%
11000NTC197306051020 4
 
2.8%
11000NTC201306076846 3
 
2.1%
11000NTC197308011068 3
 
2.1%
11000NTC196402120185 3
 
2.1%
11000NTC200107101009 2
 
1.4%
11000NTC196907140427 2
 
1.4%
11000NTC196710250315 2
 
1.4%
Other values (7) 7
 
4.9%

Length

2024-05-11T09:33:17.033067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11000ntc196312130175 70
69.3%
11000ntc197008060522 5
 
5.0%
11000ntc197306051020 4
 
4.0%
11000ntc201306076846 3
 
3.0%
11000ntc197308011068 3
 
3.0%
11000ntc196402120185 3
 
3.0%
11000ntc200107101009 2
 
2.0%
11000ntc196907140427 2
 
2.0%
11000ntc196710250315 2
 
2.0%
11000ntc197208140861 1
 
1.0%
Other values (6) 6
 
5.9%

라벨명
Categorical

IMBALANCE 

Distinct21
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
방화지구
115 
뉴스타상가아파트
 
2
구로시장
 
2
봉천시장
 
2
강남시장
 
2
Other values (16)
19 

Length

Max length9
Median length4
Mean length4.1619718
Min length4

Unique

Unique13 ?
Unique (%)9.2%

Sample

1st row방화지구
2nd row백범로지구
3rd row방화지구
4th row방화지구
5th row방화지구

Common Values

ValueCountFrequency (%)
방화지구 115
81.0%
뉴스타상가아파트 2
 
1.4%
구로시장 2
 
1.4%
봉천시장 2
 
1.4%
강남시장 2
 
1.4%
백범로지구 2
 
1.4%
대신시장 2
 
1.4%
아현시장 2
 
1.4%
돈암시장 1
 
0.7%
금호동시장 1
 
0.7%
Other values (11) 11
 
7.7%

Length

2024-05-11T09:33:17.590928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
방화지구 116
81.1%
면목시장 2
 
1.4%
구로시장 2
 
1.4%
봉천시장 2
 
1.4%
강남시장 2
 
1.4%
백범로지구 2
 
1.4%
대신시장 2
 
1.4%
아현시장 2
 
1.4%
뉴스타상가아파트 2
 
1.4%
만미시장 1
 
0.7%
Other values (10) 10
 
7.0%

시군구코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
11000
140 
11140
 
1
11410
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
11000 140
98.6%
11140 1
 
0.7%
11410 1
 
0.7%

Length

2024-05-11T09:33:18.063830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:33:18.533468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11000 140
98.6%
11140 1
 
0.7%
11410 1
 
0.7%

도면번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
140 
1
 
2

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 (%)
140
98.6%
1 2
 
1.4%

Length

2024-05-11T09:33:18.993318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:33:19.392866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2
100.0%

현황도형 생성일시
Date

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2019-12-15 00:00:00
Maximum2022-06-15 00:00:00
2024-05-11T09:33:19.880261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:33:20.299191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

면적(도형)
Real number (ℝ)

HIGH CORRELATION 

Distinct103
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23365.06
Minimum268.42461
Maximum630081.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T09:33:20.692945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum268.42461
5-th percentile787.52283
Q12031.1448
median4325.3316
Q324922.024
95-th percentile85334.45
Maximum630081.48
Range629813.05
Interquartile range (IQR)22890.879

Descriptive statistics

Standard deviation62173.006
Coefficient of variation (CV)2.6609392
Kurtosis66.450133
Mean23365.06
Median Absolute Deviation (MAD)3268.6408
Skewness7.3404019
Sum3317838.6
Variance3.8654826 × 109
MonotonicityNot monotonic
2024-05-11T09:33:21.174685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27431.5891341 2
 
1.4%
2178.61424807 2
 
1.4%
949.38164591 2
 
1.4%
1317.07948504 2
 
1.4%
75095.5174464 2
 
1.4%
716.90543255 2
 
1.4%
861.78504203 2
 
1.4%
783.83914036 2
 
1.4%
3347.25533328 2
 
1.4%
3788.15617277 2
 
1.4%
Other values (93) 122
85.9%
ValueCountFrequency (%)
268.42460589 2
1.4%
294.58869487 2
1.4%
716.90543255 2
1.4%
783.83914036 2
1.4%
857.51284278 2
1.4%
861.78504203 2
1.4%
949.38164591 2
1.4%
954.37767801 1
0.7%
1015.6923411 2
1.4%
1097.68929099 1
0.7%
ValueCountFrequency (%)
630081.478076 1
0.7%
278809.791156 1
0.7%
142246.404651 1
0.7%
137132.72543872 1
0.7%
123701.846597 1
0.7%
96870.7595629 1
0.7%
92104.4846597 1
0.7%
85469.9162241 1
0.7%
82760.5908855 1
0.7%
75095.5174464 2
1.4%

길이(도형)
Real number (ℝ)

HIGH CORRELATION 

Distinct103
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1741.8469
Minimum66.8134
Maximum15503.921
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T09:33:22.146691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66.8134
5-th percentile123.34645
Q1229.71201
median442.16
Q31899.0425
95-th percentile8574.2633
Maximum15503.921
Range15437.108
Interquartile range (IQR)1669.3305

Descriptive statistics

Standard deviation2869.3703
Coefficient of variation (CV)1.6473149
Kurtosis8.2541872
Mean1741.8469
Median Absolute Deviation (MAD)284.257
Skewness2.7459493
Sum247342.26
Variance8233285.7
MonotonicityNot monotonic
2024-05-11T09:33:22.831667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4861.41015625 2
 
1.4%
192.9960022 2
 
1.4%
182.67100525 2
 
1.4%
143.59199524 2
 
1.4%
4170.41015625 2
 
1.4%
157.90299988 2
 
1.4%
124.26699829 2
 
1.4%
115.27600098 2
 
1.4%
266.44198608 2
 
1.4%
252.44500732 2
 
1.4%
Other values (93) 122
85.9%
ValueCountFrequency (%)
66.81340027 2
1.4%
90.4960022 2
1.4%
115.27600098 2
1.4%
123.29799652 2
1.4%
124.26699829 2
1.4%
140.29899597 1
0.7%
143.59199524 2
1.4%
155.10899353 1
0.7%
156.6190033 1
0.7%
157.90299988 2
1.4%
ValueCountFrequency (%)
15503.92115315 1
0.7%
15077.59960938 1
0.7%
11873.59960938 1
0.7%
11825.20019531 1
0.7%
10084.90039063 1
0.7%
9207.33984375 1
0.7%
8838.9296875 1
0.7%
8678.11035156 1
0.7%
6601.16992188 2
1.4%
4996.41992188 1
0.7%

Interactions

2024-05-11T09:33:04.707417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:33:02.487985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:33:03.595733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:33:05.114788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:33:02.810098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:33:03.957366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:33:05.530900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:33:03.200279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:33:04.341559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T09:33:23.245901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호현황도형 생성일시면적(도형)길이(도형)
객체id1.0000.2360.3160.2010.0000.0000.0000.0000.000
도형 조서관리 코드0.2361.0001.0001.0001.0001.0001.0001.0001.000
결정고시관리코드0.3161.0001.0000.8551.0001.0001.0000.7280.752
라벨명0.2011.0000.8551.0000.0000.0000.0000.0000.000
시군구코드0.0001.0001.0000.0001.0000.4511.0000.5360.748
도면번호0.0001.0001.0000.0000.4511.0000.4510.4311.000
현황도형 생성일시0.0001.0001.0000.0001.0000.4511.0000.5360.748
면적(도형)0.0001.0000.7280.0000.5360.4310.5361.0000.626
길이(도형)0.0001.0000.7520.0000.7481.0000.7480.6261.000
2024-05-11T09:33:23.734888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드결정고시관리코드도면번호라벨명
시군구코드1.0000.9480.6970.000
결정고시관리코드0.9481.0000.9450.447
도면번호0.6970.9451.0000.000
라벨명0.0000.4470.0001.000
2024-05-11T09:33:24.075106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id면적(도형)길이(도형)결정고시관리코드라벨명시군구코드도면번호
객체id1.000-0.192-0.1990.1870.0000.0000.000
면적(도형)-0.1921.0000.9090.4630.0000.4730.519
길이(도형)-0.1990.9091.0000.4070.0000.4420.975
결정고시관리코드0.1870.4630.4071.0000.4470.9480.945
라벨명0.0000.0000.0000.4471.0000.0000.000
시군구코드0.0000.4730.4420.9480.0001.0000.697
도면번호0.0000.5190.9750.9450.0000.6971.000

Missing values

2024-05-11T09:33:06.116645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T09:33:06.788692image/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)
01166111000UQ124PS201912150005UQI100UQI10011000DSZ19671025145811000NTC196710250315방화지구110002019-12-15 00:00:00.027431.5891344861.410156
11166211000UQ124PS201912150007UQI100UQI10011000DSZ20010710149111000NTC200107101009백범로지구110002019-12-15 00:00:00.014177.484892507.629883
21166311000UQ124PS201912150015UQI100UQI10011000DSZ19631213135211000NTC196312130175방화지구110002019-12-15 00:00:00.07402.0678791331.859985
31166411000UQ124PS201912150016UQI100UQI10011000DSZ19631213135611000NTC196312130175방화지구110002019-12-15 00:00:00.011343.86586499.507996
41184111000UQ124PS201912150134UQI100UQI10011000DSZ000000001241방화지구110002019-12-15 00:00:00.02267.474562229.712006
51184211000UQ124PS201912150135UQI100UQI10011000DSZ000000001241방화지구110002019-12-15 00:00:00.02539.879275450.153015
61184311000UQ124PS201912150136UQI100UQI10011000DSZ19631213139211000NTC196312130175금호동시장110002019-12-15 00:00:00.02632.100219232.893997
71184411000UQ124PS201912150137UQI100UQI10011000DSZ19631213139511000NTC196312130175합동시장110002019-12-15 00:00:00.029795.41134749.906982
81184511000UQ124PS201912150138UQI100UQI10011000DSZ19631213140011000NTC196312130175방화지구110002019-12-15 00:00:00.01427.446373155.108994
91184611000UQ124PS201912150139UQI100UQI10011000DSZ19631213140211000NTC196312130175방화지구110002019-12-15 00:00:00.015015.0813242672.5
객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호현황도형 생성일시면적(도형)길이(도형)
1321196911000UQ124PS201912150040UQI100UQI10011000DSZ000000001241방화지구110002019-12-15 00:00:00.0949.381646182.671005
1331197011000UQ124PS201912150041UQI100UQI10011000DSZ000000001241방화지구110002019-12-15 00:00:00.01607.106081297.503998
1341197111000UQ124PS201912150055UQI100UQI10011000DSZ19631213134411000NTC196312130175아현시장110002019-12-15 00:00:00.0857.512843123.297997
1351197211000UQ124PS201912150057UQI100UQI10011000DSZ19631213135111000NTC196312130175방화지구110002019-12-15 00:00:00.02031.144775189.082993
1361197311000UQ124PS201912150060UQI100UQI10011000DSZ19631213136711000NTC196312130175방화지구110002019-12-15 00:00:00.03788.156173252.445007
1371197411000UQ124PS201912150061UQI100UQI10011000DSZ19631213137811000NTC196312130175방화지구110002019-12-15 00:00:00.03347.255333266.441986
1381197511000UQ124PS201912150062UQI100UQI10011000DSZ19631213138111000NTC196312130175방화지구110002019-12-15 00:00:00.0783.83914115.276001
1391197611000UQ124PS201912150066UQI100UQI10011000DSZ000000001241방화지구110002019-12-15 00:00:00.02958.806185515.898987
1401197711000UQ124PS201912150047UQI100UQI10011000DSZ19700806068511000NTC197008060522봉천시장110002019-12-15 00:00:00.04687.027947319.848999
1411197811000UQ124PS201912150048UQI100UQI10011000DSZ19700806068711000NTC197008060522뉴스타상가아파트110002019-12-15 00:00:00.010211.802687535.525024