Overview

Dataset statistics

Number of variables8
Number of observations187
Missing cells31
Missing cells (%)2.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.8 KiB
Average record size in memory64.7 B

Variable types

Text7
Boolean1

Dataset

Description경기도 양주시 도시계획정보시스템(UPIS) 용도지구 결정조서 현황으로 도면번호, 위치명, 지역명, 면적(기정), 면적(변경) 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15115929/fileData.do

Alerts

도면번호 has 27 (14.4%) missing valuesMissing
공간도형존재여부 has 4 (2.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 20:23:17.576151
Analysis finished2023-12-12 20:23:18.856396
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도면번호
Text

MISSING 

Distinct84
Distinct (%)52.5%
Missing27
Missing (%)14.4%
Memory size1.6 KiB
2023-12-13T05:23:19.043173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length2.39375
Min length1

Characters and Unicode

Total characters383
Distinct characters14
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

Unique56 ?
Unique (%)35.0%

Sample

1st row27
2nd row28
3rd row8
4th row16
5th row1
ValueCountFrequency (%)
1 15
 
9.2%
3 8
 
4.9%
2 7
 
4.3%
4 7
 
4.3%
5 6
 
3.7%
7 5
 
3.1%
8 4
 
2.5%
6 4
 
2.5%
9 4
 
2.5%
19일 3
 
1.8%
Other values (75) 100
61.3%
2023-12-13T05:23:19.424197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 93
24.3%
9 50
13.1%
2 44
11.5%
4 39
10.2%
- 36
 
9.4%
3 29
 
7.6%
5 28
 
7.3%
8 14
 
3.7%
6 14
 
3.7%
0 14
 
3.7%
Other values (4) 22
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 338
88.3%
Dash Punctuation 36
 
9.4%
Other Letter 6
 
1.6%
Space Separator 3
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 93
27.5%
9 50
14.8%
2 44
13.0%
4 39
11.5%
3 29
 
8.6%
5 28
 
8.3%
8 14
 
4.1%
6 14
 
4.1%
0 14
 
4.1%
7 13
 
3.8%
Other Letter
ValueCountFrequency (%)
월 3
50.0%
일 3
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 377
98.4%
Hangul 6
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 93
24.7%
9 50
13.3%
2 44
11.7%
4 39
10.3%
- 36
 
9.5%
3 29
 
7.7%
5 28
 
7.4%
8 14
 
3.7%
6 14
 
3.7%
0 14
 
3.7%
Other values (2) 16
 
4.2%
Hangul
ValueCountFrequency (%)
월 3
50.0%
일 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 377
98.4%
Hangul 6
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 93
24.7%
9 50
13.3%
2 44
11.7%
4 39
10.3%
- 36
 
9.5%
3 29
 
7.7%
5 28
 
7.4%
8 14
 
3.7%
6 14
 
3.7%
0 14
 
3.7%
Other values (2) 16
 
4.2%
Hangul
ValueCountFrequency (%)
월 3
50.0%
일 3
50.0%

위치명
Text

Distinct156
Distinct (%)83.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T05:23:19.768380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length13.791444
Min length6

Characters and Unicode

Total characters2579
Distinct characters94
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)74.3%

Sample

1st row가납리 일원
2nd row오산리 일원
3rd row방성리 87-6대 일원
4th row가납리 454-2 일원
5th row광적면 효촌리 산26 일원
ValueCountFrequency (%)
일원 161
23.8%
양주군 57
 
8.4%
경기도 23
 
3.4%
백석읍 16
 
2.4%
장흥면 15
 
2.2%
가납리 15
 
2.2%
은현면 13
 
1.9%
남면 12
 
1.8%
삼숭리 10
 
1.5%
양주읍 9
 
1.3%
Other values (176) 345
51.0%
2023-12-13T05:23:20.292632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
489
19.0%
일 170
 
6.6%
원 163
 
6.3%
리 122
 
4.7%
1 96
 
3.7%
주 84
 
3.3%
양 83
 
3.2%
- 70
 
2.7%
면 66
 
2.6%
지 62
 
2.4%
Other values (84) 1174
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1586
61.5%
Space Separator 489
 
19.0%
Decimal Number 430
 
16.7%
Dash Punctuation 70
 
2.7%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 170
 
10.7%
원 163
 
10.3%
리 122
 
7.7%
주 84
 
5.3%
양 83
 
5.2%
면 66
 
4.2%
지 62
 
3.9%
군 57
 
3.6%
동 56
 
3.5%
산 41
 
2.6%
Other values (71) 682
43.0%
Decimal Number
ValueCountFrequency (%)
1 96
22.3%
2 59
13.7%
4 47
10.9%
6 40
9.3%
3 39
9.1%
8 38
 
8.8%
9 33
 
7.7%
5 29
 
6.7%
7 25
 
5.8%
0 24
 
5.6%
Space Separator
ValueCountFrequency (%)
489
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1586
61.5%
Common 993
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 170
 
10.7%
원 163
 
10.3%
리 122
 
7.7%
주 84
 
5.3%
양 83
 
5.2%
면 66
 
4.2%
지 62
 
3.9%
군 57
 
3.6%
동 56
 
3.5%
산 41
 
2.6%
Other values (71) 682
43.0%
Common
ValueCountFrequency (%)
489
49.2%
1 96
 
9.7%
- 70
 
7.0%
2 59
 
5.9%
4 47
 
4.7%
6 40
 
4.0%
3 39
 
3.9%
8 38
 
3.8%
9 33
 
3.3%
5 29
 
2.9%
Other values (3) 53
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1586
61.5%
ASCII 993
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
489
49.2%
1 96
 
9.7%
- 70
 
7.0%
2 59
 
5.9%
4 47
 
4.7%
6 40
 
4.0%
3 39
 
3.9%
8 38
 
3.8%
9 33
 
3.3%
5 29
 
2.9%
Other values (3) 53
 
5.3%
Hangul
ValueCountFrequency (%)
일 170
 
10.7%
원 163
 
10.3%
리 122
 
7.7%
주 84
 
5.3%
양 83
 
5.2%
면 66
 
4.2%
지 62
 
3.9%
군 57
 
3.6%
동 56
 
3.5%
산 41
 
2.6%
Other values (71) 682
43.0%

지역명
Text

Distinct86
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T05:23:20.684749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length6.0160428
Min length4

Characters and Unicode

Total characters1125
Distinct characters100
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)24.1%

Sample

1st row가납지구
2nd row오산지구
3rd row능안지구
4th row가납4지구
5th row문화자원보존지구
ValueCountFrequency (%)
자연취락지구 17
 
9.0%
문화자원보존지구 16
 
8.5%
취락지구 12
 
6.3%
시설용지지구 6
 
3.2%
주거개발진흥지구 5
 
2.6%
방성지구 5
 
2.6%
오산지구 5
 
2.6%
산업개발진흥지구 4
 
2.1%
가납3지구 4
 
2.1%
운암지구 3
 
1.6%
Other values (76) 112
59.3%
2023-12-13T05:23:21.218595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 204
18.1%
구 184
 
16.4%
락 67
 
6.0%
취 66
 
5.9%
자 42
 
3.7%
산 22
 
2.0%
2 21
 
1.9%
연 21
 
1.9%
가 17
 
1.5%
원 16
 
1.4%
Other values (90) 465
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1040
92.4%
Decimal Number 59
 
5.2%
Uppercase Letter 18
 
1.6%
Open Punctuation 3
 
0.3%
Close Punctuation 3
 
0.3%
Space Separator 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 204
19.6%
구 184
17.7%
락 67
 
6.4%
취 66
 
6.3%
자 42
 
4.0%
산 22
 
2.1%
연 21
 
2.0%
가 17
 
1.6%
원 16
 
1.5%
보 16
 
1.5%
Other values (77) 385
37.0%
Decimal Number
ValueCountFrequency (%)
2 21
35.6%
1 16
27.1%
3 10
16.9%
5 6
 
10.2%
4 4
 
6.8%
7 1
 
1.7%
6 1
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
S 9
50.0%
G 6
33.3%
K 3
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1040
92.4%
Common 67
 
6.0%
Latin 18
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 204
19.6%
구 184
17.7%
락 67
 
6.4%
취 66
 
6.3%
자 42
 
4.0%
산 22
 
2.1%
연 21
 
2.0%
가 17
 
1.6%
원 16
 
1.5%
보 16
 
1.5%
Other values (77) 385
37.0%
Common
ValueCountFrequency (%)
2 21
31.3%
1 16
23.9%
3 10
14.9%
5 6
 
9.0%
4 4
 
6.0%
( 3
 
4.5%
) 3
 
4.5%
2
 
3.0%
7 1
 
1.5%
6 1
 
1.5%
Latin
ValueCountFrequency (%)
S 9
50.0%
G 6
33.3%
K 3
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1040
92.4%
ASCII 85
 
7.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 204
19.6%
구 184
17.7%
락 67
 
6.4%
취 66
 
6.3%
자 42
 
4.0%
산 22
 
2.1%
연 21
 
2.0%
가 17
 
1.6%
원 16
 
1.5%
보 16
 
1.5%
Other values (77) 385
37.0%
ASCII
ValueCountFrequency (%)
2 21
24.7%
1 16
18.8%
3 10
11.8%
S 9
10.6%
G 6
 
7.1%
5 6
 
7.1%
4 4
 
4.7%
( 3
 
3.5%
K 3
 
3.5%
) 3
 
3.5%
Other values (3) 4
 
4.7%

면적(기정)
Text

Distinct95
Distinct (%)50.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T05:23:21.583251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.144385
Min length1

Characters and Unicode

Total characters1149
Distinct characters18
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

Unique85 ?
Unique (%)45.5%

Sample

1st row데이터 미집계
2nd row데이터 미집계
3rd row40500
4th row4100
5th row데이터 미집계
ValueCountFrequency (%)
데이터 80
30.0%
미집계 80
30.0%
232000 4
 
1.5%
0 4
 
1.5%
13252 2
 
0.7%
2190000 2
 
0.7%
1847000 2
 
0.7%
77517 2
 
0.7%
1202000 2
 
0.7%
235000 2
 
0.7%
Other values (86) 87
32.6%
2023-12-13T05:23:22.120159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 210
18.3%
집 80
 
7.0%
이 80
 
7.0%
계 80
 
7.0%
데 80
 
7.0%
미 80
 
7.0%
80
 
7.0%
터 80
 
7.0%
1 67
 
5.8%
2 62
 
5.4%
Other values (8) 250
21.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 588
51.2%
Other Letter 480
41.8%
Space Separator 80
 
7.0%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 210
35.7%
1 67
 
11.4%
2 62
 
10.5%
3 52
 
8.8%
4 39
 
6.6%
7 34
 
5.8%
5 33
 
5.6%
8 32
 
5.4%
6 30
 
5.1%
9 29
 
4.9%
Other Letter
ValueCountFrequency (%)
집 80
16.7%
이 80
16.7%
계 80
16.7%
데 80
16.7%
미 80
16.7%
터 80
16.7%
Space Separator
ValueCountFrequency (%)
80
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 669
58.2%
Hangul 480
41.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 210
31.4%
80
 
12.0%
1 67
 
10.0%
2 62
 
9.3%
3 52
 
7.8%
4 39
 
5.8%
7 34
 
5.1%
5 33
 
4.9%
8 32
 
4.8%
6 30
 
4.5%
Other values (2) 30
 
4.5%
Hangul
ValueCountFrequency (%)
집 80
16.7%
이 80
16.7%
계 80
16.7%
데 80
16.7%
미 80
16.7%
터 80
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 669
58.2%
Hangul 480
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 210
31.4%
80
 
12.0%
1 67
 
10.0%
2 62
 
9.3%
3 52
 
7.8%
4 39
 
5.8%
7 34
 
5.1%
5 33
 
4.9%
8 32
 
4.8%
6 30
 
4.5%
Other values (2) 30
 
4.5%
Hangul
ValueCountFrequency (%)
집 80
16.7%
이 80
16.7%
계 80
16.7%
데 80
16.7%
미 80
16.7%
터 80
16.7%

면적(변경)
Text

Distinct154
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T05:23:22.520201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.026738
Min length1

Characters and Unicode

Total characters940
Distinct characters18
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

Unique138 ?
Unique (%)73.8%

Sample

1st row41999
2nd row36063
3rd row40500
4th row4100
5th row5285
ValueCountFrequency (%)
데이터 14
 
7.0%
미집계 14
 
7.0%
31000 7
 
3.5%
28119 2
 
1.0%
48000 2
 
1.0%
26170 2
 
1.0%
32340 2
 
1.0%
18000 2
 
1.0%
24000 2
 
1.0%
7366 2
 
1.0%
Other values (145) 152
75.6%
2023-12-13T05:23:23.132569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 219
23.3%
2 94
10.0%
1 90
9.6%
3 86
 
9.1%
4 69
 
7.3%
7 64
 
6.8%
5 61
 
6.5%
8 53
 
5.6%
6 53
 
5.6%
9 47
 
5.0%
Other values (8) 104
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 836
88.9%
Other Letter 84
 
8.9%
Space Separator 14
 
1.5%
Other Punctuation 6
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 219
26.2%
2 94
11.2%
1 90
10.8%
3 86
 
10.3%
4 69
 
8.3%
7 64
 
7.7%
5 61
 
7.3%
8 53
 
6.3%
6 53
 
6.3%
9 47
 
5.6%
Other Letter
ValueCountFrequency (%)
데 14
16.7%
이 14
16.7%
계 14
16.7%
집 14
16.7%
미 14
16.7%
터 14
16.7%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 856
91.1%
Hangul 84
 
8.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 219
25.6%
2 94
11.0%
1 90
10.5%
3 86
 
10.0%
4 69
 
8.1%
7 64
 
7.5%
5 61
 
7.1%
8 53
 
6.2%
6 53
 
6.2%
9 47
 
5.5%
Other values (2) 20
 
2.3%
Hangul
ValueCountFrequency (%)
데 14
16.7%
이 14
16.7%
계 14
16.7%
집 14
16.7%
미 14
16.7%
터 14
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 856
91.1%
Hangul 84
 
8.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 219
25.6%
2 94
11.0%
1 90
10.5%
3 86
 
10.0%
4 69
 
8.1%
7 64
 
7.5%
5 61
 
7.1%
8 53
 
6.2%
6 53
 
6.2%
9 47
 
5.5%
Other values (2) 20
 
2.3%
Hangul
ValueCountFrequency (%)
데 14
16.7%
이 14
16.7%
계 14
16.7%
집 14
16.7%
미 14
16.7%
터 14
16.7%

면적(변경후)
Text

Distinct175
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T05:23:23.556491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.4491979
Min length1

Characters and Unicode

Total characters1019
Distinct characters18
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

Unique169 ?
Unique (%)90.4%

Sample

1st row41999
2nd row36063
3rd row데이터 미집계
4th row데이터 미집계
5th row5285
ValueCountFrequency (%)
데이터 7
 
3.6%
미집계 7
 
3.6%
0 3
 
1.5%
46982 2
 
1.0%
232000 2
 
1.0%
4269000 2
 
1.0%
31000 2
 
1.0%
1226000 1
 
0.5%
363000 1
 
0.5%
1183000 1
 
0.5%
Other values (166) 166
85.6%
2023-12-13T05:23:24.209949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 244
23.9%
2 113
11.1%
1 112
11.0%
3 88
 
8.6%
4 77
 
7.6%
8 70
 
6.9%
5 69
 
6.8%
7 66
 
6.5%
6 64
 
6.3%
9 62
 
6.1%
Other values (8) 54
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 965
94.7%
Other Letter 42
 
4.1%
Space Separator 7
 
0.7%
Other Punctuation 5
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 244
25.3%
2 113
11.7%
1 112
11.6%
3 88
 
9.1%
4 77
 
8.0%
8 70
 
7.3%
5 69
 
7.2%
7 66
 
6.8%
6 64
 
6.6%
9 62
 
6.4%
Other Letter
ValueCountFrequency (%)
데 7
16.7%
이 7
16.7%
계 7
16.7%
집 7
16.7%
미 7
16.7%
터 7
16.7%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 977
95.9%
Hangul 42
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 244
25.0%
2 113
11.6%
1 112
11.5%
3 88
 
9.0%
4 77
 
7.9%
8 70
 
7.2%
5 69
 
7.1%
7 66
 
6.8%
6 64
 
6.6%
9 62
 
6.3%
Other values (2) 12
 
1.2%
Hangul
ValueCountFrequency (%)
데 7
16.7%
이 7
16.7%
계 7
16.7%
집 7
16.7%
미 7
16.7%
터 7
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 977
95.9%
Hangul 42
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 244
25.0%
2 113
11.6%
1 112
11.5%
3 88
 
9.0%
4 77
 
7.9%
8 70
 
7.2%
5 69
 
7.1%
7 66
 
6.8%
6 64
 
6.6%
9 62
 
6.3%
Other values (2) 12
 
1.2%
Hangul
ValueCountFrequency (%)
데 7
16.7%
이 7
16.7%
계 7
16.7%
집 7
16.7%
미 7
16.7%
터 7
16.7%

비고
Text

Distinct70
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T05:23:24.561161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length7
Mean length9.8716578
Min length2

Characters and Unicode

Total characters1846
Distinct characters143
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)34.8%

Sample

1st row데이터 미집계
2nd row데이터 미집계
3rd row백석도시
4th row광적도시, 가납3지구와통합
5th row백인걸선생묘
ValueCountFrequency (%)
데이터 105
29.2%
미집계 105
29.2%
부지조성 15
 
4.2%
공동주택건립 13
 
3.6%
공동주택(아파트 12
 
3.3%
광적도시 9
 
2.5%
백석도시 5
 
1.4%
건립 3
 
0.8%
송추c.c(운동휴양+집단묘지 2
 
0.6%
3개소 2
 
0.6%
Other values (86) 89
24.7%
2023-12-13T05:23:25.067663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
173
 
9.4%
집 107
 
5.8%
계 107
 
5.8%
이 107
 
5.8%
데 105
 
5.7%
터 105
 
5.7%
미 105
 
5.7%
0 104
 
5.6%
. 42
 
2.3%
( 41
 
2.2%
Other values (133) 850
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1197
64.8%
Decimal Number 275
 
14.9%
Space Separator 173
 
9.4%
Other Symbol 63
 
3.4%
Other Punctuation 45
 
2.4%
Open Punctuation 41
 
2.2%
Close Punctuation 41
 
2.2%
Uppercase Letter 9
 
0.5%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
집 107
 
8.9%
계 107
 
8.9%
이 107
 
8.9%
데 105
 
8.8%
터 105
 
8.8%
미 105
 
8.8%
동 36
 
3.0%
주 34
 
2.8%
공 31
 
2.6%
택 31
 
2.6%
Other values (111) 429
35.8%
Decimal Number
ValueCountFrequency (%)
0 104
37.8%
3 35
 
12.7%
1 28
 
10.2%
2 23
 
8.4%
4 21
 
7.6%
8 18
 
6.5%
7 13
 
4.7%
6 13
 
4.7%
9 11
 
4.0%
5 9
 
3.3%
Other Symbol
ValueCountFrequency (%)
㎢ 39
61.9%
㎡ 23
36.5%
㈜ 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
C 7
77.8%
M 1
 
11.1%
B 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 42
93.3%
, 3
 
6.7%
Space Separator
ValueCountFrequency (%)
173
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1198
64.9%
Common 639
34.6%
Latin 9
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
집 107
 
8.9%
계 107
 
8.9%
이 107
 
8.9%
데 105
 
8.8%
터 105
 
8.8%
미 105
 
8.8%
동 36
 
3.0%
주 34
 
2.8%
공 31
 
2.6%
택 31
 
2.6%
Other values (112) 430
35.9%
Common
ValueCountFrequency (%)
173
27.1%
0 104
16.3%
. 42
 
6.6%
( 41
 
6.4%
) 41
 
6.4%
㎢ 39
 
6.1%
3 35
 
5.5%
1 28
 
4.4%
2 23
 
3.6%
㎡ 23
 
3.6%
Other values (8) 90
14.1%
Latin
ValueCountFrequency (%)
C 7
77.8%
M 1
 
11.1%
B 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1197
64.8%
ASCII 586
31.7%
CJK Compat 62
 
3.4%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
173
29.5%
0 104
17.7%
. 42
 
7.2%
( 41
 
7.0%
) 41
 
7.0%
3 35
 
6.0%
1 28
 
4.8%
2 23
 
3.9%
4 21
 
3.6%
8 18
 
3.1%
Other values (9) 60
 
10.2%
Hangul
ValueCountFrequency (%)
집 107
 
8.9%
계 107
 
8.9%
이 107
 
8.9%
데 105
 
8.8%
터 105
 
8.8%
미 105
 
8.8%
동 36
 
3.0%
주 34
 
2.8%
공 31
 
2.6%
택 31
 
2.6%
Other values (111) 429
35.8%
CJK Compat
ValueCountFrequency (%)
㎢ 39
62.9%
㎡ 23
37.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

공간도형존재여부
Boolean

MISSING 

Distinct2
Distinct (%)1.1%
Missing4
Missing (%)2.1%
Memory size506.0 B
True
148 
False
35 
(Missing)
 
4
ValueCountFrequency (%)
True 148
79.1%
False 35
 
18.7%
(Missing) 4
 
2.1%
2023-12-13T05:23:25.199443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:23:25.295293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도면번호지역명면적(기정)비고공간도형존재여부
도면번호1.0000.9890.8310.9770.839
지역명0.9891.0000.9840.0000.768
면적(기정)0.8310.9841.0000.9890.981
비고0.9770.0000.9891.0000.610
공간도형존재여부0.8390.7680.9810.6101.000

Missing values

2023-12-13T05:23:18.544442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:23:18.666873image/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.
2023-12-13T05:23:18.796976image/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

도면번호위치명지역명면적(기정)면적(변경)면적(변경후)비고공간도형존재여부
027가납리 일원가납지구데이터 미집계4199941999데이터 미집계Y
128오산리 일원오산지구데이터 미집계3606336063데이터 미집계Y
2<NA>방성리 87-6대 일원능안지구4050040500데이터 미집계백석도시N
3<NA>가납리 454-2 일원가납4지구41004100데이터 미집계광적도시, 가납3지구와통합N
48광적면 효촌리 산26 일원문화자원보존지구데이터 미집계52855285백인걸선생묘Y
516장흥면 삼하리 산90 일원문화자원보존지구데이터 미집계33223322이수광선생묘Y
61장흥면 석현리 일원관광휴양개발진흥지구390000데이터 미집계390000장흥관광지Y
72만송동 일원관광휴양개발진흥지구232000데이터 미집계232000MBC문화동산Y
83은현면 도하리 산41-1산업개발진흥지구66802데이터 미집계66802삼표산업Y
94남면 경신리 93-1산업개발진흥지구13252데이터 미집계13252제2종지구단위계획구역Y
도면번호위치명지역명면적(기정)면적(변경)면적(변경후)비고공간도형존재여부
177<NA>신산리 395일원신산지구3234032340데이터 미집계남면도시N
17810덕계동 산64 일원문화자원보존지구데이터 미집계879879송석최면창묘역Y
17911옥정동 627-1, 산94-1 일원문화자원보존지구데이터 미집계920920옥정리선돌Y
1807봉양동 일원봉양1지구데이터 미집계105328105328데이터 미집계Y
18110봉양동 일원봉양2지구데이터 미집계3542235422데이터 미집계Y
18211봉양동 일원봉양3지구데이터 미집계177655177655데이터 미집계Y
18312회암동 일원회암1지구데이터 미집계2112521125데이터 미집계Y
18413회암동 일원회암2지구데이터 미집계1880118801데이터 미집계Y
18514고암동 일원고암지구데이터 미집계106043106043데이터 미집계Y
18624백석읍 방성리 일원방성지구데이터 미집계130023130023데이터 미집계Y