Overview

Dataset statistics

Number of variables8
Number of observations2539
Missing cells1353
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory168.7 KiB
Average record size in memory68.1 B

Variable types

Numeric4
Categorical1
Text2
Boolean1

Dataset

Description전라남도 신안군 지구단위계획, 용도지구, 용도지역, 도시계획시설, 용도구역 결정조서현황에 대한 데이터이며, 도시계획정보시스템(upis)에서 추출한 데이터로, 결정조서유형, 결정조서유형상세, 면적기정, 면적변경, 최종면적, 비고를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15116086/fileData.do

Alerts

연번 is highly overall correlated with 결정조서유형High correlation
면적기정 is highly overall correlated with 최종면적High correlation
최종면적 is highly overall correlated with 면적기정High correlation
결정조서유형 is highly overall correlated with 연번High correlation
결정조서유형 is highly imbalanced (60.4%)Imbalance
비고 has 1353 (53.3%) missing valuesMissing
면적변경 is highly skewed (γ1 = 36.30179162)Skewed
연번 has unique valuesUnique
면적기정 has 1779 (70.1%) zerosZeros
면적변경 has 1592 (62.7%) zerosZeros
최종면적 has 1405 (55.3%) zerosZeros

Reproduction

Analysis started2023-12-12 04:30:12.861937
Analysis finished2023-12-12 04:30:15.192255
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2539
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1270
Minimum1
Maximum2539
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.4 KiB
2023-12-12T13:30:15.255060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile127.9
Q1635.5
median1270
Q31904.5
95-th percentile2412.1
Maximum2539
Range2538
Interquartile range (IQR)1269

Descriptive statistics

Standard deviation733.09049
Coefficient of variation (CV)0.57723661
Kurtosis-1.2
Mean1270
Median Absolute Deviation (MAD)635
Skewness0
Sum3224530
Variance537421.67
MonotonicityStrictly increasing
2023-12-12T13:30:15.381592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1697 1
 
< 0.1%
1690 1
 
< 0.1%
1691 1
 
< 0.1%
1692 1
 
< 0.1%
1693 1
 
< 0.1%
1694 1
 
< 0.1%
1695 1
 
< 0.1%
1696 1
 
< 0.1%
1698 1
 
< 0.1%
Other values (2529) 2529
99.6%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2539 1
< 0.1%
2538 1
< 0.1%
2537 1
< 0.1%
2536 1
< 0.1%
2535 1
< 0.1%
2534 1
< 0.1%
2533 1
< 0.1%
2532 1
< 0.1%
2531 1
< 0.1%
2530 1
< 0.1%

결정조서유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.0 KiB
도시계획시설
2006 
용도지역
439 
용도지구
 
65
지구단위계획
 
27
용도구역
 
2

Length

Max length6
Median length6
Mean length5.6014179
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도시계획시설 2006
79.0%
용도지역 439
 
17.3%
용도지구 65
 
2.6%
지구단위계획 27
 
1.1%
용도구역 2
 
0.1%

Length

2023-12-12T13:30:15.523675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:30:15.636646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도시계획시설 2006
79.0%
용도지역 439
 
17.3%
용도지구 65
 
2.6%
지구단위계획 27
 
1.1%
용도구역 2
 
0.1%

결정조서유형상세
Text

Distinct153
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size20.0 KiB
2023-12-12T13:30:15.820760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length4
Mean length4.5569122
Min length1

Characters and Unicode

Total characters11570
Distinct characters165
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)3.4%

Sample

1st row제2종지구단위계획구역/1(지도농공단지)
2nd row제2종지구단위계획구역/신안밤섬지구
3rd row1종지구단위계획구역/지도1
4th row1종지구단위계획구역/지도2
5th row제2종지구단위계획구역/2(지도축산단지)
ValueCountFrequency (%)
용도지역 439
17.3%
소로2류 344
13.5%
소로3류 269
 
10.6%
근린공원 208
 
8.2%
소로1류 207
 
8.1%
중로2류 96
 
3.8%
완충녹지 96
 
3.8%
노외주차장 80
 
3.1%
경관녹지 68
 
2.7%
초등학교 57
 
2.2%
Other values (146) 680
26.7%
2023-12-12T13:30:16.181772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 1062
 
9.2%
류 1062
 
9.2%
소 888
 
7.7%
지 823
 
7.1%
도 498
 
4.3%
역 489
 
4.2%
2 480
 
4.1%
용 442
 
3.8%
공 430
 
3.7%
3 351
 
3.0%
Other values (155) 5045
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10164
87.8%
Decimal Number 1177
 
10.2%
Close Punctuation 76
 
0.7%
Open Punctuation 76
 
0.7%
Other Punctuation 72
 
0.6%
Space Separator 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 1062
 
10.4%
류 1062
 
10.4%
소 888
 
8.7%
지 823
 
8.1%
도 498
 
4.9%
역 489
 
4.8%
용 442
 
4.3%
공 430
 
4.2%
원 334
 
3.3%
린 238
 
2.3%
Other values (140) 3898
38.4%
Decimal Number
ValueCountFrequency (%)
2 480
40.8%
3 351
29.8%
1 311
26.4%
4 12
 
1.0%
5 6
 
0.5%
0 5
 
0.4%
6 3
 
0.3%
7 3
 
0.3%
8 3
 
0.3%
9 3
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 71
98.6%
· 1
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10164
87.8%
Common 1406
 
12.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 1062
 
10.4%
류 1062
 
10.4%
소 888
 
8.7%
지 823
 
8.1%
도 498
 
4.9%
역 489
 
4.8%
용 442
 
4.3%
공 430
 
4.2%
원 334
 
3.3%
린 238
 
2.3%
Other values (140) 3898
38.4%
Common
ValueCountFrequency (%)
2 480
34.1%
3 351
25.0%
1 311
22.1%
) 76
 
5.4%
( 76
 
5.4%
/ 71
 
5.0%
4 12
 
0.9%
5 6
 
0.4%
0 5
 
0.4%
5
 
0.4%
Other values (5) 13
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10164
87.8%
ASCII 1405
 
12.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 1062
 
10.4%
류 1062
 
10.4%
소 888
 
8.7%
지 823
 
8.1%
도 498
 
4.9%
역 489
 
4.8%
용 442
 
4.3%
공 430
 
4.2%
원 334
 
3.3%
린 238
 
2.3%
Other values (140) 3898
38.4%
ASCII
ValueCountFrequency (%)
2 480
34.2%
3 351
25.0%
1 311
22.1%
) 76
 
5.4%
( 76
 
5.4%
/ 71
 
5.1%
4 12
 
0.9%
5 6
 
0.4%
0 5
 
0.4%
5
 
0.4%
Other values (4) 12
 
0.9%
None
ValueCountFrequency (%)
· 1
100.0%

면적기정
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct412
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12645765
Minimum0
Maximum4.99694 × 108
Zeros1779
Zeros (%)70.1%
Negative0
Negative (%)0.0%
Memory size22.4 KiB
2023-12-12T13:30:16.320273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34078.5
95-th percentile1.0296488 × 108
Maximum4.99694 × 108
Range4.99694 × 108
Interquartile range (IQR)4078.5

Descriptive statistics

Standard deviation55930303
Coefficient of variation (CV)4.4228484
Kurtosis32.948821
Mean12645765
Median Absolute Deviation (MAD)0
Skewness5.4958227
Sum3.2107598 × 1010
Variance3.1281988 × 1015
MonotonicityNot monotonic
2023-12-12T13:30:16.469832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1779
70.1%
139700 18
 
0.7%
3720000 16
 
0.6%
62190 16
 
0.6%
53500 16
 
0.6%
373200 16
 
0.6%
29880 12
 
0.5%
109121 12
 
0.5%
154302 12
 
0.5%
63361000 12
 
0.5%
Other values (402) 630
 
24.8%
ValueCountFrequency (%)
0 1779
70.1%
43 1
 
< 0.1%
47 2
 
0.1%
54 1
 
< 0.1%
101 1
 
< 0.1%
206 2
 
0.1%
213 2
 
0.1%
256 2
 
0.1%
279 1
 
< 0.1%
307 4
 
0.2%
ValueCountFrequency (%)
499694000 3
0.1%
449694000 2
 
0.1%
436290000 1
 
< 0.1%
436280000 7
0.3%
395088000 1
 
< 0.1%
377986000 1
 
< 0.1%
377985000 1
 
< 0.1%
377266000 1
 
< 0.1%
364546000 7
0.3%
363752000 1
 
< 0.1%

면적변경
Real number (ℝ)

SKEWED  ZEROS 

Distinct666
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean355782.74
Minimum0
Maximum3.6350345 × 108
Zeros1592
Zeros (%)62.7%
Negative0
Negative (%)0.0%
Memory size22.4 KiB
2023-12-12T13:30:16.625771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32899
95-th percentile159041.1
Maximum3.6350345 × 108
Range3.6350345 × 108
Interquartile range (IQR)2899

Descriptive statistics

Standard deviation8334366
Coefficient of variation (CV)23.425437
Kurtosis1477.3451
Mean355782.74
Median Absolute Deviation (MAD)0
Skewness36.301792
Sum9.0333237 × 108
Variance6.9461657 × 1013
MonotonicityNot monotonic
2023-12-12T13:30:16.770102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1592
62.7%
162115.0 6
 
0.2%
15000.0 6
 
0.2%
8827.0 6
 
0.2%
75000.0 5
 
0.2%
3000.0 4
 
0.2%
77851.0 4
 
0.2%
6000.0 4
 
0.2%
1258.0 4
 
0.2%
307.0 4
 
0.2%
Other values (656) 904
35.6%
ValueCountFrequency (%)
0.0 1592
62.7%
5.0 1
 
< 0.1%
14.0 1
 
< 0.1%
16.0 1
 
< 0.1%
22.0 1
 
< 0.1%
34.0 1
 
< 0.1%
39.0 2
 
0.1%
43.0 2
 
0.1%
46.0 2
 
0.1%
47.0 2
 
0.1%
ValueCountFrequency (%)
363503453.0 1
< 0.1%
146412701.0 1
< 0.1%
107694972.0 1
< 0.1%
101759635.0 1
< 0.1%
13379200.0 2
0.1%
13354646.0 2
0.1%
7779824.0 1
< 0.1%
7636145.0 1
< 0.1%
6206516.0 2
0.1%
4203892.0 2
0.1%

최종면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct733
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12663346
Minimum0
Maximum4.99694 × 108
Zeros1405
Zeros (%)55.3%
Negative0
Negative (%)0.0%
Memory size22.4 KiB
2023-12-12T13:30:17.135065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q323068.5
95-th percentile1.0296497 × 108
Maximum4.99694 × 108
Range4.99694 × 108
Interquartile range (IQR)23068.5

Descriptive statistics

Standard deviation55635763
Coefficient of variation (CV)4.3934488
Kurtosis33.121833
Mean12663346
Median Absolute Deviation (MAD)0
Skewness5.4961545
Sum3.2152236 × 1010
Variance3.0953381 × 1015
MonotonicityNot monotonic
2023-12-12T13:30:17.270178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1405
55.3%
3720000.0 19
 
0.7%
139700.0 18
 
0.7%
62190.0 17
 
0.7%
53500.0 17
 
0.7%
373200.0 16
 
0.6%
29880.0 13
 
0.5%
154302.0 13
 
0.5%
109121.0 13
 
0.5%
63361000.0 12
 
0.5%
Other values (723) 996
39.2%
ValueCountFrequency (%)
0.0 1405
55.3%
34.0 1
 
< 0.1%
39.0 2
 
0.1%
43.0 1
 
< 0.1%
46.0 2
 
0.1%
47.0 2
 
0.1%
50.0 1
 
< 0.1%
53.0 1
 
< 0.1%
56.0 2
 
0.1%
57.0 1
 
< 0.1%
ValueCountFrequency (%)
499694000.0 3
0.1%
449694000.0 2
 
0.1%
436290000.0 1
 
< 0.1%
436280000.0 7
0.3%
396758000.0 1
 
< 0.1%
377986000.0 1
 
< 0.1%
377910000.0 1
 
< 0.1%
377266000.0 1
 
< 0.1%
364666000.0 2
 
0.1%
364534610.0 1
 
< 0.1%

공간도형존재여부
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
False
1778 
True
761 
ValueCountFrequency (%)
False 1778
70.0%
True 761
30.0%
2023-12-12T13:30:17.378693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

비고
Text

MISSING 

Distinct234
Distinct (%)19.7%
Missing1353
Missing (%)53.3%
Memory size20.0 KiB
2023-12-12T13:30:17.616484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length72
Mean length7.049747
Min length2

Characters and Unicode

Total characters8361
Distinct characters258
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)11.7%

Sample

1st row지구단위계획구역의 신규지정
2nd row자연녹지지역에서 제2종일반주거지역으로 용도지역 변경
3rd row자연녹지지역에서 제2종일반주거지역으로 용도지역 변경
4th row폐지
5th row지도농공단지 확장 변경에 따른 제2종지구단위계획구역 지정
ValueCountFrequency (%)
폐지 231
 
12.7%
주거중심지구 162
 
8.9%
신안군 122
 
6.7%
총괄 122
 
6.7%
조선산업지구 96
 
5.3%
흑산면 46
 
2.5%
연결로 44
 
2.4%
진입로 30
 
1.6%
지도읍 25
 
1.4%
육지부 18
 
1.0%
Other values (401) 924
50.8%
2023-12-12T13:30:18.129888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 813
 
9.7%
634
 
7.6%
구 344
 
4.1%
도 249
 
3.0%
선 233
 
2.8%
폐 233
 
2.8%
주 188
 
2.2%
군 177
 
2.1%
거 174
 
2.1%
산 174
 
2.1%
Other values (248) 5142
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6951
83.1%
Space Separator 634
 
7.6%
Decimal Number 519
 
6.2%
Other Punctuation 188
 
2.2%
Open Punctuation 19
 
0.2%
Close Punctuation 19
 
0.2%
Other Symbol 10
 
0.1%
Math Symbol 10
 
0.1%
Lowercase Letter 7
 
0.1%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 813
 
11.7%
구 344
 
4.9%
도 249
 
3.6%
선 233
 
3.4%
폐 233
 
3.4%
주 188
 
2.7%
군 177
 
2.5%
거 174
 
2.5%
산 174
 
2.5%
중 165
 
2.4%
Other values (224) 4201
60.4%
Decimal Number
ValueCountFrequency (%)
0 97
18.7%
1 90
17.3%
2 86
16.6%
8 54
10.4%
5 49
9.4%
4 38
 
7.3%
3 35
 
6.7%
9 27
 
5.2%
7 22
 
4.2%
6 21
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 111
59.0%
: 47
25.0%
. 22
 
11.7%
% 8
 
4.3%
Math Symbol
ValueCountFrequency (%)
~ 6
60.0%
= 3
30.0%
→ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
634
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 10
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6951
83.1%
Common 1400
 
16.7%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 813
 
11.7%
구 344
 
4.9%
도 249
 
3.6%
선 233
 
3.4%
폐 233
 
3.4%
주 188
 
2.7%
군 177
 
2.5%
거 174
 
2.5%
산 174
 
2.5%
중 165
 
2.4%
Other values (224) 4201
60.4%
Common
ValueCountFrequency (%)
634
45.3%
, 111
 
7.9%
0 97
 
6.9%
1 90
 
6.4%
2 86
 
6.1%
8 54
 
3.9%
5 49
 
3.5%
: 47
 
3.4%
4 38
 
2.7%
3 35
 
2.5%
Other values (12) 159
 
11.4%
Latin
ValueCountFrequency (%)
m 7
70.0%
L 3
30.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6951
83.1%
ASCII 1399
 
16.7%
CJK Compat 10
 
0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 813
 
11.7%
구 344
 
4.9%
도 249
 
3.6%
선 233
 
3.4%
폐 233
 
3.4%
주 188
 
2.7%
군 177
 
2.5%
거 174
 
2.5%
산 174
 
2.5%
중 165
 
2.4%
Other values (224) 4201
60.4%
ASCII
ValueCountFrequency (%)
634
45.3%
, 111
 
7.9%
0 97
 
6.9%
1 90
 
6.4%
2 86
 
6.1%
8 54
 
3.9%
5 49
 
3.5%
: 47
 
3.4%
4 38
 
2.7%
3 35
 
2.5%
Other values (12) 158
 
11.3%
CJK Compat
ValueCountFrequency (%)
㎡ 10
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

Interactions

2023-12-12T13:30:14.607828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:13.419602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:13.785416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:14.199201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:14.704908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:13.507698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:13.891902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:14.310473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:14.790946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:13.592836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:13.982738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:14.408092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:14.882145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:13.684577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:14.099657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:30:14.511242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:30:18.245547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번결정조서유형면적기정면적변경최종면적공간도형존재여부
연번1.0000.8680.5330.0580.5370.561
결정조서유형0.8681.0000.5930.0380.5960.167
면적기정0.5330.5931.0000.2021.0000.132
면적변경0.0580.0380.2021.0000.1860.000
최종면적0.5370.5961.0000.1861.0000.133
공간도형존재여부0.5610.1670.1320.0000.1331.000
2023-12-12T13:30:18.370829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공간도형존재여부결정조서유형
공간도형존재여부1.0000.204
결정조서유형0.2041.000
2023-12-12T13:30:18.470637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적기정면적변경최종면적결정조서유형공간도형존재여부
연번1.000-0.336-0.063-0.4840.5400.432
면적기정-0.3361.0000.1720.5900.2860.101
면적변경-0.0630.1721.0000.4630.0310.000
최종면적-0.4840.5900.4631.0000.2880.102
결정조서유형0.5400.2860.0310.2881.0000.204
공간도형존재여부0.4320.1010.0000.1020.2041.000

Missing values

2023-12-12T13:30:14.997452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:30:15.142738image/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

연번결정조서유형결정조서유형상세면적기정면적변경최종면적공간도형존재여부비고
01지구단위계획제2종지구단위계획구역/1(지도농공단지)2990000.0299000.0Y<NA>
12지구단위계획제2종지구단위계획구역/신안밤섬지구0227730.0227730.0N지구단위계획구역의 신규지정
23지구단위계획1종지구단위계획구역/지도1070432.070432.0Y자연녹지지역에서 제2종일반주거지역으로 용도지역 변경
34지구단위계획1종지구단위계획구역/지도2022450.022450.0Y자연녹지지역에서 제2종일반주거지역으로 용도지역 변경
45지구단위계획제2종지구단위계획구역/2(지도축산단지)760000.076000.0Y<NA>
56지구단위계획제2종지구단위계획구역/30220290.0220290.0Y<NA>
67지구단위계획제2종지구단위계획구역/47730000.0773000.0Y<NA>
78지구단위계획제2종지구단위계획구역/1(굴도지구)079340.079340.0Y<NA>
89지구단위계획제2종지구단위계획구역/1(도덕도)077851.077851.0Y<NA>
910지구단위계획관광휴양형지구단위계획구역/10(대단도지구)052930.052930.0N<NA>
연번결정조서유형결정조서유형상세면적기정면적변경최종면적공간도형존재여부비고
25292530도시계획시설대로3류00.00.0N<NA>
25302531도시계획시설중로2류00.00.0Y<NA>
25312532도시계획시설중로2류00.00.0N<NA>
25322533도시계획시설중로2류00.00.0Y<NA>
25332534도시계획시설중로2류00.00.0N<NA>
25342535도시계획시설중로2류00.00.0N<NA>
25352536도시계획시설중로2류00.00.0N<NA>
25362537도시계획시설중로2류00.00.0N<NA>
25372538용도구역도시계획구역03720000.03720000.0N<NA>
25382539용도구역도시계획구역37200000.03720000.0N<NA>