Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells37128
Missing cells (%)30.9%
Duplicate rows42
Duplicate rows (%)0.4%
Total size in memory1.0 MiB
Average record size in memory108.0 B

Variable types

Categorical2
Text5
DateTime1
Numeric4

Dataset

Description건축착공 신고 현황_건축사 사무소별
Author가평군
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=FVSTUDDOCGS7NETSTGNX27039481&infSeq=1

Alerts

Dataset has 42 (0.4%) duplicate rowsDuplicates
WGS84위도 is highly overall correlated with WGS84위도.1 and 1 other fieldsHigh correlation
WGS84위도.1 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with WGS84경도.1 and 1 other fieldsHigh correlation
WGS84경도.1 is highly overall correlated with WGS84경도 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with WGS84위도 and 3 other fieldsHigh correlation
착공 신고지 도로명주소 has 3432 (34.3%) missing valuesMissing
시공사명 has 5644 (56.4%) missing valuesMissing
WGS84위도 has 7032 (70.3%) missing valuesMissing
WGS84위도.1 has 2300 (23.0%) missing valuesMissing
WGS84경도 has 7032 (70.3%) missing valuesMissing
WGS84경도.1 has 2300 (23.0%) missing valuesMissing
비고 has 9301 (93.0%) missing valuesMissing

Reproduction

Analysis started2024-04-29 13:17:40.399111
Analysis finished2024-04-29 13:17:45.900211
Duration5.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가평군
2124 
안성시
1304 
양평군
1098 
파주시
991 
용인시
711 
Other values (26)
3772 

Length

Max length4
Median length3
Mean length3.0137
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양주시
2nd row가평군
3rd row가평군
4th row안성시
5th row고양시

Common Values

ValueCountFrequency (%)
가평군 2124
21.2%
안성시 1304
13.0%
양평군 1098
11.0%
파주시 991
9.9%
용인시 711
 
7.1%
이천시 670
 
6.7%
양주시 468
 
4.7%
수원시 323
 
3.2%
화성시 312
 
3.1%
김포시 301
 
3.0%
Other values (21) 1698
17.0%

Length

2024-04-29T22:17:45.970494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가평군 2124
21.2%
안성시 1304
13.0%
양평군 1098
11.0%
파주시 991
9.9%
용인시 711
 
7.1%
이천시 670
 
6.7%
양주시 468
 
4.7%
수원시 323
 
3.2%
화성시 312
 
3.1%
김포시 301
 
3.0%
Other values (21) 1698
17.0%

설계사무소명
Text

Distinct2557
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-29T22:17:46.171211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length9.8945
Min length1

Characters and Unicode

Total characters98945
Distinct characters510
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1445 ?
Unique (%)14.4%

Sample

1st row관건축사사무소
2nd row(유)세진건축사사무소
3rd row건승건축사사무소
4th row태림건축사사무소
5th row도우건축사사무소
ValueCountFrequency (%)
건축사사무소 1927
 
14.9%
주식회사 498
 
3.9%
태은건축사사무소 149
 
1.2%
주)삼원건축사사무소 130
 
1.0%
유)세진건축사사무소 122
 
0.9%
선우건축사사무소 114
 
0.9%
유)토담건축사사무소 109
 
0.8%
명성건축사사무소 100
 
0.8%
정풍건축사사무소 95
 
0.7%
나래건축사사무소 89
 
0.7%
Other values (2531) 9569
74.2%
2024-04-29T22:17:46.535638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 20279
20.5%
건 10187
 
10.3%
축 9983
 
10.1%
무 9792
 
9.9%
소 9748
 
9.9%
주 3084
 
3.1%
2903
 
2.9%
) 2495
 
2.5%
( 2485
 
2.5%
이 1111
 
1.1%
Other values (500) 26878
27.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90159
91.1%
Space Separator 2903
 
2.9%
Close Punctuation 2496
 
2.5%
Open Punctuation 2486
 
2.5%
Uppercase Letter 607
 
0.6%
Other Punctuation 111
 
0.1%
Lowercase Letter 106
 
0.1%
Decimal Number 65
 
0.1%
Math Symbol 6
 
< 0.1%
Other Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 20279
22.5%
건 10187
11.3%
축 9983
11.1%
무 9792
10.9%
소 9748
10.8%
주 3084
 
3.4%
이 1111
 
1.2%
우 927
 
1.0%
종 926
 
1.0%
합 919
 
1.0%
Other values (442) 23203
25.7%
Uppercase Letter
ValueCountFrequency (%)
A 87
14.3%
C 69
11.4%
E 52
 
8.6%
J 46
 
7.6%
T 38
 
6.3%
G 36
 
5.9%
S 31
 
5.1%
M 31
 
5.1%
K 29
 
4.8%
B 28
 
4.6%
Other values (12) 160
26.4%
Lowercase Letter
ValueCountFrequency (%)
p 22
20.8%
j 15
14.2%
r 11
10.4%
n 8
 
7.5%
s 7
 
6.6%
a 6
 
5.7%
e 6
 
5.7%
g 5
 
4.7%
i 5
 
4.7%
t 5
 
4.7%
Other values (7) 16
15.1%
Decimal Number
ValueCountFrequency (%)
1 41
63.1%
2 14
 
21.5%
3 5
 
7.7%
4 1
 
1.5%
6 1
 
1.5%
9 1
 
1.5%
5 1
 
1.5%
0 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
& 55
49.5%
. 51
45.9%
, 5
 
4.5%
Close Punctuation
ValueCountFrequency (%)
) 2495
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2485
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2903
100.0%
Math Symbol
ValueCountFrequency (%)
+ 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90158
91.1%
Common 8070
 
8.2%
Latin 713
 
0.7%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 20279
22.5%
건 10187
11.3%
축 9983
11.1%
무 9792
10.9%
소 9748
10.8%
주 3084
 
3.4%
이 1111
 
1.2%
우 927
 
1.0%
종 926
 
1.0%
합 919
 
1.0%
Other values (439) 23202
25.7%
Latin
ValueCountFrequency (%)
A 87
 
12.2%
C 69
 
9.7%
E 52
 
7.3%
J 46
 
6.5%
T 38
 
5.3%
G 36
 
5.0%
S 31
 
4.3%
M 31
 
4.3%
K 29
 
4.1%
B 28
 
3.9%
Other values (29) 266
37.3%
Common
ValueCountFrequency (%)
2903
36.0%
) 2495
30.9%
( 2485
30.8%
& 55
 
0.7%
. 51
 
0.6%
1 41
 
0.5%
2 14
 
0.2%
+ 6
 
0.1%
3 5
 
0.1%
, 5
 
0.1%
Other values (8) 10
 
0.1%
Han
ValueCountFrequency (%)
圭 1
25.0%
房 1
25.0%
樂 1
25.0%
茶 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90155
91.1%
ASCII 8783
 
8.9%
None 3
 
< 0.1%
CJK 3
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 20279
22.5%
건 10187
11.3%
축 9983
11.1%
무 9792
10.9%
소 9748
10.8%
주 3084
 
3.4%
이 1111
 
1.2%
우 927
 
1.0%
종 926
 
1.0%
합 919
 
1.0%
Other values (438) 23199
25.7%
ASCII
ValueCountFrequency (%)
2903
33.1%
) 2495
28.4%
( 2485
28.3%
A 87
 
1.0%
C 69
 
0.8%
& 55
 
0.6%
E 52
 
0.6%
. 51
 
0.6%
J 46
 
0.5%
1 41
 
0.5%
Other values (47) 499
 
5.7%
None
ValueCountFrequency (%)
㈜ 3
100.0%
CJK
ValueCountFrequency (%)
圭 1
33.3%
房 1
33.3%
茶 1
33.3%
CJK Compat Ideographs
ValueCountFrequency (%)
樂 1
100.0%

신고일
Date

Distinct2797
Distinct (%)28.0%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum1997-03-24 00:00:00
Maximum2024-06-30 00:00:00
2024-04-29T22:17:46.680222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:46.797368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공 신고지 도로명주소
Text

MISSING 

Distinct6254
Distinct (%)95.2%
Missing3432
Missing (%)34.3%
Memory size156.2 KiB
2024-04-29T22:17:47.025727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length21.452801
Min length1

Characters and Unicode

Total characters140902
Distinct characters411
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

Unique6085 ?
Unique (%)92.6%

Sample

1st row경기도 양주시 광적면 휴암로 298
2nd row경기도 가평군 조종면 세곡로 58-138
3rd row경기도 가평군 설악면 봉미산안길13번길 175
4th row경기도 안성시 양성면 가래울길 68-45
5th row경기도 고양시 일산동구 문원길120번길 107
ValueCountFrequency (%)
경기도 6471
 
20.0%
가평군 2049
 
6.3%
안성시 1137
 
3.5%
양평군 720
 
2.2%
용인시 711
 
2.2%
설악면 448
 
1.4%
처인구 437
 
1.3%
가평읍 424
 
1.3%
양주시 381
 
1.2%
상면 374
 
1.2%
Other values (6656) 19234
59.4%
2024-04-29T22:17:47.405993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25820
 
18.3%
도 6745
 
4.8%
기 6742
 
4.8%
경 6565
 
4.7%
1 5617
 
4.0%
로 4039
 
2.9%
시 3798
 
2.7%
평 3790
 
2.7%
면 3742
 
2.7%
2 3717
 
2.6%
Other values (401) 70327
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84090
59.7%
Decimal Number 27247
 
19.3%
Space Separator 25820
 
18.3%
Dash Punctuation 3712
 
2.6%
Open Punctuation 14
 
< 0.1%
Close Punctuation 14
 
< 0.1%
Other Punctuation 4
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 6745
 
8.0%
기 6742
 
8.0%
경 6565
 
7.8%
로 4039
 
4.8%
시 3798
 
4.5%
평 3790
 
4.5%
면 3742
 
4.4%
길 3370
 
4.0%
군 2904
 
3.5%
가 2705
 
3.2%
Other values (385) 39690
47.2%
Decimal Number
ValueCountFrequency (%)
1 5617
20.6%
2 3717
13.6%
3 3008
11.0%
4 2639
9.7%
5 2404
8.8%
6 2299
8.4%
7 2068
 
7.6%
8 1857
 
6.8%
0 1847
 
6.8%
9 1791
 
6.6%
Space Separator
ValueCountFrequency (%)
25820
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3712
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84090
59.7%
Common 56811
40.3%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 6745
 
8.0%
기 6742
 
8.0%
경 6565
 
7.8%
로 4039
 
4.8%
시 3798
 
4.5%
평 3790
 
4.5%
면 3742
 
4.4%
길 3370
 
4.0%
군 2904
 
3.5%
가 2705
 
3.2%
Other values (385) 39690
47.2%
Common
ValueCountFrequency (%)
25820
45.4%
1 5617
 
9.9%
2 3717
 
6.5%
- 3712
 
6.5%
3 3008
 
5.3%
4 2639
 
4.6%
5 2404
 
4.2%
6 2299
 
4.0%
7 2068
 
3.6%
8 1857
 
3.3%
Other values (5) 3670
 
6.5%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84090
59.7%
ASCII 56812
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25820
45.4%
1 5617
 
9.9%
2 3717
 
6.5%
- 3712
 
6.5%
3 3008
 
5.3%
4 2639
 
4.6%
5 2404
 
4.2%
6 2299
 
4.0%
7 2068
 
3.6%
8 1857
 
3.3%
Other values (6) 3671
 
6.5%
Hangul
ValueCountFrequency (%)
도 6745
 
8.0%
기 6742
 
8.0%
경 6565
 
7.8%
로 4039
 
4.8%
시 3798
 
4.5%
평 3790
 
4.5%
면 3742
 
4.4%
길 3370
 
4.0%
군 2904
 
3.5%
가 2705
 
3.2%
Other values (385) 39690
47.2%

착공 신고지 지번주소
Text

Distinct9679
Distinct (%)97.6%
Missing83
Missing (%)0.8%
Memory size156.2 KiB
2024-04-29T22:17:47.709624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length40
Mean length22.207321
Min length13

Characters and Unicode

Total characters220230
Distinct characters386
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

Unique9493 ?
Unique (%)95.7%

Sample

1st row경기도 양주시 광적면 효촌리 408-1번지
2nd row경기도 가평군 조종면 신상리 648-3번지
3rd row경기도 가평군 설악면 설곡리 331-1번지
4th row경기도 안성시 양성면 추곡리 49 외5필지
5th row경기도 고양시 일산동구 설문동 82-1
ValueCountFrequency (%)
경기도 9917
 
19.7%
가평군 2115
 
4.2%
안성시 1304
 
2.6%
양평군 1099
 
2.2%
외1필지 1004
 
2.0%
파주시 991
 
2.0%
용인시 711
 
1.4%
이천시 670
 
1.3%
양주시 468
 
0.9%
설악면 468
 
0.9%
Other values (9792) 31682
62.8%
2024-04-29T22:17:48.180802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40512
 
18.4%
도 10305
 
4.7%
기 10194
 
4.6%
경 9950
 
4.5%
1 8374
 
3.8%
- 8100
 
3.7%
리 7152
 
3.2%
시 6771
 
3.1%
지 6704
 
3.0%
2 5856
 
2.7%
Other values (376) 106312
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129990
59.0%
Decimal Number 41581
 
18.9%
Space Separator 40512
 
18.4%
Dash Punctuation 8100
 
3.7%
Uppercase Letter 31
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 10305
 
7.9%
기 10194
 
7.8%
경 9950
 
7.7%
리 7152
 
5.5%
시 6771
 
5.2%
지 6704
 
5.2%
면 5209
 
4.0%
평 4649
 
3.6%
번 4354
 
3.3%
동 3587
 
2.8%
Other values (346) 61115
47.0%
Uppercase Letter
ValueCountFrequency (%)
F 5
16.1%
A 4
12.9%
T 3
9.7%
S 3
9.7%
L 3
9.7%
H 3
9.7%
R 2
 
6.5%
C 2
 
6.5%
E 2
 
6.5%
D 1
 
3.2%
Other values (3) 3
9.7%
Decimal Number
ValueCountFrequency (%)
1 8374
20.1%
2 5856
14.1%
3 4805
11.6%
4 4331
10.4%
5 3793
9.1%
6 3454
8.3%
7 3080
 
7.4%
8 2707
 
6.5%
0 2611
 
6.3%
9 2570
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
h 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
40512
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129990
59.0%
Common 90207
41.0%
Latin 33
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 10305
 
7.9%
기 10194
 
7.8%
경 9950
 
7.7%
리 7152
 
5.5%
시 6771
 
5.2%
지 6704
 
5.2%
면 5209
 
4.0%
평 4649
 
3.6%
번 4354
 
3.3%
동 3587
 
2.8%
Other values (346) 61115
47.0%
Common
ValueCountFrequency (%)
40512
44.9%
1 8374
 
9.3%
- 8100
 
9.0%
2 5856
 
6.5%
3 4805
 
5.3%
4 4331
 
4.8%
5 3793
 
4.2%
6 3454
 
3.8%
7 3080
 
3.4%
8 2707
 
3.0%
Other values (5) 5195
 
5.8%
Latin
ValueCountFrequency (%)
F 5
15.2%
A 4
12.1%
T 3
9.1%
S 3
9.1%
L 3
9.1%
H 3
9.1%
R 2
 
6.1%
C 2
 
6.1%
E 2
 
6.1%
D 1
 
3.0%
Other values (5) 5
15.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 129990
59.0%
ASCII 90240
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40512
44.9%
1 8374
 
9.3%
- 8100
 
9.0%
2 5856
 
6.5%
3 4805
 
5.3%
4 4331
 
4.8%
5 3793
 
4.2%
6 3454
 
3.8%
7 3080
 
3.4%
8 2707
 
3.0%
Other values (20) 5228
 
5.8%
Hangul
ValueCountFrequency (%)
도 10305
 
7.9%
기 10194
 
7.8%
경 9950
 
7.7%
리 7152
 
5.5%
시 6771
 
5.2%
지 6704
 
5.2%
면 5209
 
4.0%
평 4649
 
3.6%
번 4354
 
3.3%
동 3587
 
2.8%
Other values (346) 61115
47.0%

시공사명
Text

MISSING 

Distinct3065
Distinct (%)70.4%
Missing5644
Missing (%)56.4%
Memory size156.2 KiB
2024-04-29T22:17:48.435883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length7.2401286
Min length2

Characters and Unicode

Total characters31538
Distinct characters523
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2491 ?
Unique (%)57.2%

Sample

1st row건축주직영
2nd row(주)제이디종합건설
3rd row(주)유러스건설
4th row조윤심
5th row윤형귀외1명
ValueCountFrequency (%)
주식회사 179
 
3.8%
직영 117
 
2.5%
건축주 114
 
2.4%
건축주직영 101
 
2.2%
주)삼우종합건설 13
 
0.3%
서림종합건설(주 11
 
0.2%
주)하호종합건설 10
 
0.2%
주)창성종합건설 10
 
0.2%
자기공사 10
 
0.2%
지에스건설(주 10
 
0.2%
Other values (3054) 4086
87.7%
2024-04-29T22:17:48.796731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 3151
 
10.0%
건 2430
 
7.7%
) 2271
 
7.2%
( 2267
 
7.2%
설 2122
 
6.7%
종 1591
 
5.0%
합 1540
 
4.9%
이 706
 
2.2%
사 686
 
2.2%
회 670
 
2.1%
Other values (513) 14104
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26488
84.0%
Close Punctuation 2272
 
7.2%
Open Punctuation 2268
 
7.2%
Space Separator 305
 
1.0%
Decimal Number 121
 
0.4%
Other Punctuation 56
 
0.2%
Other Symbol 9
 
< 0.1%
Dash Punctuation 9
 
< 0.1%
Uppercase Letter 9
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3151
 
11.9%
건 2430
 
9.2%
설 2122
 
8.0%
종 1591
 
6.0%
합 1540
 
5.8%
이 706
 
2.7%
사 686
 
2.6%
회 670
 
2.5%
식 633
 
2.4%
영 404
 
1.5%
Other values (483) 12555
47.4%
Decimal Number
ValueCountFrequency (%)
1 67
55.4%
2 24
 
19.8%
3 11
 
9.1%
4 5
 
4.1%
5 4
 
3.3%
8 3
 
2.5%
7 3
 
2.5%
6 2
 
1.7%
9 1
 
0.8%
0 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 2
22.2%
A 2
22.2%
K 1
11.1%
H 1
11.1%
I 1
11.1%
N 1
11.1%
E 1
11.1%
Other Punctuation
ValueCountFrequency (%)
* 49
87.5%
, 3
 
5.4%
: 2
 
3.6%
& 1
 
1.8%
. 1
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 2271
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2267
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
305
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26497
84.0%
Common 5032
 
16.0%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3151
 
11.9%
건 2430
 
9.2%
설 2122
 
8.0%
종 1591
 
6.0%
합 1540
 
5.8%
이 706
 
2.7%
사 686
 
2.6%
회 670
 
2.5%
식 633
 
2.4%
영 404
 
1.5%
Other values (484) 12564
47.4%
Common
ValueCountFrequency (%)
) 2271
45.1%
( 2267
45.1%
305
 
6.1%
1 67
 
1.3%
* 49
 
1.0%
2 24
 
0.5%
3 11
 
0.2%
- 9
 
0.2%
4 5
 
0.1%
5 4
 
0.1%
Other values (12) 20
 
0.4%
Latin
ValueCountFrequency (%)
C 2
22.2%
A 2
22.2%
K 1
11.1%
H 1
11.1%
I 1
11.1%
N 1
11.1%
E 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26488
84.0%
ASCII 5041
 
16.0%
None 9
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 3151
 
11.9%
건 2430
 
9.2%
설 2122
 
8.0%
종 1591
 
6.0%
합 1540
 
5.8%
이 706
 
2.7%
사 686
 
2.6%
회 670
 
2.5%
식 633
 
2.4%
영 404
 
1.5%
Other values (483) 12555
47.4%
ASCII
ValueCountFrequency (%)
) 2271
45.1%
( 2267
45.0%
305
 
6.1%
1 67
 
1.3%
* 49
 
1.0%
2 24
 
0.5%
3 11
 
0.2%
- 9
 
0.2%
4 5
 
0.1%
5 4
 
0.1%
Other values (19) 29
 
0.6%
None
ValueCountFrequency (%)
㈜ 9
100.0%

착공 용도
Categorical

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단독주택
3953 
제2종근린생활시설
1818 
제1종근린생활시설
1211 
공장
699 
공동주택
506 
Other values (30)
1813 

Length

Max length10
Median length4
Mean length5.6659
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row단독주택
2nd row단독주택
3rd row단독주택
4th row동.식물관련시설
5th row제1종근린생활시설

Common Values

ValueCountFrequency (%)
단독주택 3953
39.5%
제2종근린생활시설 1818
18.2%
제1종근린생활시설 1211
 
12.1%
공장 699
 
7.0%
공동주택 506
 
5.1%
창고시설 391
 
3.9%
동.식물관련시설 375
 
3.8%
<NA> 211
 
2.1%
업무시설 131
 
1.3%
자동차관련시설 90
 
0.9%
Other values (25) 615
 
6.2%

Length

2024-04-29T22:17:48.948975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 3953
39.5%
제2종근린생활시설 1818
18.2%
제1종근린생활시설 1211
 
12.1%
공장 699
 
7.0%
공동주택 506
 
5.1%
창고시설 391
 
3.9%
동.식물관련시설 375
 
3.8%
na 211
 
2.1%
업무시설 131
 
1.3%
자동차관련시설 90
 
0.9%
Other values (25) 615
 
6.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct2871
Distinct (%)96.7%
Missing7032
Missing (%)70.3%
Infinite0
Infinite (%)0.0%
Mean37.513713
Minimum37.08748
Maximum37.969129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-29T22:17:49.098946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.08748
5-th percentile37.219062
Q137.355725
median37.495657
Q337.642746
95-th percentile37.861626
Maximum37.969129
Range0.88164902
Interquartile range (IQR)0.2870206

Descriptive statistics

Standard deviation0.201196
Coefficient of variation (CV)0.0053632655
Kurtosis-0.75316969
Mean37.513713
Median Absolute Deviation (MAD)0.14419348
Skewness0.20922232
Sum111340.7
Variance0.040479832
MonotonicityNot monotonic
2024-04-29T22:17:49.232964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.47800124 27
 
0.3%
37.4033792 6
 
0.1%
37.47658349 6
 
0.1%
37.42624064 4
 
< 0.1%
37.27261356 4
 
< 0.1%
37.42993301 4
 
< 0.1%
37.39047761 3
 
< 0.1%
37.52522998 3
 
< 0.1%
37.51042866 3
 
< 0.1%
37.612381 3
 
< 0.1%
Other values (2861) 2905
29.0%
(Missing) 7032
70.3%
ValueCountFrequency (%)
37.08748029 1
< 0.1%
37.09051789 1
< 0.1%
37.09144825 1
< 0.1%
37.09265172 1
< 0.1%
37.10074987 1
< 0.1%
37.10495205 1
< 0.1%
37.10643175 1
< 0.1%
37.10764864 1
< 0.1%
37.10900937 1
< 0.1%
37.1115234 1
< 0.1%
ValueCountFrequency (%)
37.96912931 1
< 0.1%
37.96836889 1
< 0.1%
37.96289461 1
< 0.1%
37.94904478 1
< 0.1%
37.94878446 1
< 0.1%
37.94747513 1
< 0.1%
37.94248259 1
< 0.1%
37.93759917 1
< 0.1%
37.93204562 1
< 0.1%
37.93162918 1
< 0.1%

WGS84위도.1
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7423
Distinct (%)96.4%
Missing2300
Missing (%)23.0%
Infinite0
Infinite (%)0.0%
Mean37.479158
Minimum36.911764
Maximum38.049225
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-29T22:17:49.358209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.911764
5-th percentile37.003533
Q137.254932
median37.508053
Q337.73811
95-th percentile37.874137
Maximum38.049225
Range1.1374606
Interquartile range (IQR)0.48317713

Descriptive statistics

Standard deviation0.29175715
Coefficient of variation (CV)0.0077845172
Kurtosis-1.1805877
Mean37.479158
Median Absolute Deviation (MAD)0.24596651
Skewness-0.2616028
Sum288589.52
Variance0.085122235
MonotonicityNot monotonic
2024-04-29T22:17:49.502792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.47800124 27
 
0.3%
37.655203 11
 
0.1%
37.018473 8
 
0.1%
37.4033792 6
 
0.1%
37.47658349 6
 
0.1%
37.42993301 4
 
< 0.1%
37.42624064 4
 
< 0.1%
37.27261356 4
 
< 0.1%
37.701739 4
 
< 0.1%
37.0883775999 3
 
< 0.1%
Other values (7413) 7623
76.2%
(Missing) 2300
 
23.0%
ValueCountFrequency (%)
36.9117640133 1
< 0.1%
36.9120485632 1
< 0.1%
36.9121653968 1
< 0.1%
36.9129591856 1
< 0.1%
36.9138918749 1
< 0.1%
36.9141230419 1
< 0.1%
36.9147878568 1
< 0.1%
36.915146 1
< 0.1%
36.9194273882 1
< 0.1%
36.9203927818 1
< 0.1%
ValueCountFrequency (%)
38.04922458 1
< 0.1%
38.03983897 1
< 0.1%
38.0397974 1
< 0.1%
38.027277 1
< 0.1%
38.02620056 1
< 0.1%
38.0255864 1
< 0.1%
38.01937988 1
< 0.1%
37.9961817 1
< 0.1%
37.989666 1
< 0.1%
37.989391 1
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct2872
Distinct (%)96.8%
Missing7032
Missing (%)70.3%
Infinite0
Infinite (%)0.0%
Mean127.21082
Minimum126.531
Maximum127.79646
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-29T22:17:49.644675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.531
5-th percentile126.62505
Q1127.05106
median127.17697
Q3127.4525
95-th percentile127.66541
Maximum127.79646
Range1.2654614
Interquartile range (IQR)0.40144323

Descriptive statistics

Standard deviation0.29455868
Coefficient of variation (CV)0.0023155158
Kurtosis-0.50654561
Mean127.21082
Median Absolute Deviation (MAD)0.20477159
Skewness-0.23535058
Sum377561.73
Variance0.086764815
MonotonicityNot monotonic
2024-04-29T22:17:49.797528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8633879 27
 
0.3%
127.1561544 6
 
0.1%
126.8629023 6
 
0.1%
127.1019375 4
 
< 0.1%
127.1635481 4
 
< 0.1%
127.1009911 4
 
< 0.1%
126.731905 3
 
< 0.1%
127.1351311 3
 
< 0.1%
127.6101049 3
 
< 0.1%
127.4367926 3
 
< 0.1%
Other values (2862) 2905
29.0%
(Missing) 7032
70.3%
ValueCountFrequency (%)
126.530997 1
< 0.1%
126.5410968 1
< 0.1%
126.5439779 1
< 0.1%
126.5448217 1
< 0.1%
126.5467598 1
< 0.1%
126.5476291 1
< 0.1%
126.5494052 1
< 0.1%
126.5497533 1
< 0.1%
126.5510652 1
< 0.1%
126.5514463 1
< 0.1%
ValueCountFrequency (%)
127.7964584 1
< 0.1%
127.79449 1
< 0.1%
127.7936973 1
< 0.1%
127.7911709 1
< 0.1%
127.778357 1
< 0.1%
127.7781557 1
< 0.1%
127.7752281 1
< 0.1%
127.773711 1
< 0.1%
127.7703171 1
< 0.1%
127.7699097 1
< 0.1%

WGS84경도.1
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7418
Distinct (%)96.3%
Missing2300
Missing (%)23.0%
Infinite0
Infinite (%)0.0%
Mean127.24585
Minimum126.531
Maximum127.79646
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-29T22:17:49.940569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.531
5-th percentile126.7676
Q1127.06978
median127.28467
Q3127.45962
95-th percentile127.5817
Maximum127.79646
Range1.2654614
Interquartile range (IQR)0.38983473

Descriptive statistics

Standard deviation0.25880129
Coefficient of variation (CV)0.0020338683
Kurtosis-0.25884543
Mean127.24585
Median Absolute Deviation (MAD)0.19155373
Skewness-0.58152674
Sum979793.02
Variance0.066978109
MonotonicityNot monotonic
2024-04-29T22:17:50.100305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8633879 27
 
0.3%
126.8990741 11
 
0.1%
127.087145 8
 
0.1%
126.8629023 6
 
0.1%
127.1561544 6
 
0.1%
127.1635481 4
 
< 0.1%
127.543471 4
 
< 0.1%
127.1009911 4
 
< 0.1%
127.1019375 4
 
< 0.1%
127.447039 3
 
< 0.1%
Other values (7408) 7623
76.2%
(Missing) 2300
 
23.0%
ValueCountFrequency (%)
126.530997 1
< 0.1%
126.5410968 1
< 0.1%
126.5439779 1
< 0.1%
126.5448217 1
< 0.1%
126.5467598 1
< 0.1%
126.5476291 1
< 0.1%
126.5494052 1
< 0.1%
126.5497533 1
< 0.1%
126.5510652 1
< 0.1%
126.5514463 1
< 0.1%
ValueCountFrequency (%)
127.7964584 1
< 0.1%
127.79449 1
< 0.1%
127.7936973 1
< 0.1%
127.7911709 1
< 0.1%
127.778357 1
< 0.1%
127.7781557 1
< 0.1%
127.7752281 1
< 0.1%
127.773711 1
< 0.1%
127.7703171 1
< 0.1%
127.7699097 1
< 0.1%

비고
Text

MISSING 

Distinct64
Distinct (%)9.2%
Missing9301
Missing (%)93.0%
Memory size156.2 KiB
2024-04-29T22:17:50.325393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length2
Mean length3.9113019
Min length2

Characters and Unicode

Total characters2734
Distinct characters139
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

Unique58 ?
Unique (%)8.3%

Sample

1st row재축
2nd row신축
3rd row경기도 가평군 상면 항사리 285-4
4th row신축
5th row신축
ValueCountFrequency (%)
신축 512
53.4%
증축 75
 
7.8%
경기도 55
 
5.7%
대수선 41
 
4.3%
하남시 29
 
3.0%
감일동 21
 
2.2%
시흥시 11
 
1.1%
가평군 10
 
1.0%
감일지구 10
 
1.0%
상면 8
 
0.8%
Other values (129) 187
 
19.5%
2024-04-29T22:17:50.674303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
축 593
21.7%
신 513
18.8%
261
 
9.5%
증 75
 
2.7%
시 62
 
2.3%
도 60
 
2.2%
경 58
 
2.1%
기 56
 
2.0%
감 50
 
1.8%
지 48
 
1.8%
Other values (129) 958
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2221
81.2%
Space Separator 261
 
9.5%
Decimal Number 185
 
6.8%
Dash Punctuation 48
 
1.8%
Uppercase Letter 16
 
0.6%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
축 593
26.7%
신 513
23.1%
증 75
 
3.4%
시 62
 
2.8%
도 60
 
2.7%
경 58
 
2.6%
기 56
 
2.5%
감 50
 
2.3%
지 48
 
2.2%
일 46
 
2.1%
Other values (107) 660
29.7%
Decimal Number
ValueCountFrequency (%)
2 41
22.2%
1 35
18.9%
3 26
14.1%
4 18
9.7%
5 13
 
7.0%
6 12
 
6.5%
7 11
 
5.9%
8 10
 
5.4%
0 10
 
5.4%
9 9
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
D 4
25.0%
L 4
25.0%
B 4
25.0%
F 1
 
6.2%
M 1
 
6.2%
T 1
 
6.2%
V 1
 
6.2%
Space Separator
ValueCountFrequency (%)
261
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2221
81.2%
Common 497
 
18.2%
Latin 16
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
축 593
26.7%
신 513
23.1%
증 75
 
3.4%
시 62
 
2.8%
도 60
 
2.7%
경 58
 
2.6%
기 56
 
2.5%
감 50
 
2.3%
지 48
 
2.2%
일 46
 
2.1%
Other values (107) 660
29.7%
Common
ValueCountFrequency (%)
261
52.5%
- 48
 
9.7%
2 41
 
8.2%
1 35
 
7.0%
3 26
 
5.2%
4 18
 
3.6%
5 13
 
2.6%
6 12
 
2.4%
7 11
 
2.2%
8 10
 
2.0%
Other values (5) 22
 
4.4%
Latin
ValueCountFrequency (%)
D 4
25.0%
L 4
25.0%
B 4
25.0%
F 1
 
6.2%
M 1
 
6.2%
T 1
 
6.2%
V 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2221
81.2%
ASCII 513
 
18.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
축 593
26.7%
신 513
23.1%
증 75
 
3.4%
시 62
 
2.8%
도 60
 
2.7%
경 58
 
2.6%
기 56
 
2.5%
감 50
 
2.3%
지 48
 
2.2%
일 46
 
2.1%
Other values (107) 660
29.7%
ASCII
ValueCountFrequency (%)
261
50.9%
- 48
 
9.4%
2 41
 
8.0%
1 35
 
6.8%
3 26
 
5.1%
4 18
 
3.5%
5 13
 
2.5%
6 12
 
2.3%
7 11
 
2.1%
8 10
 
1.9%
Other values (12) 38
 
7.4%

Interactions

2024-04-29T22:17:44.784817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:43.576811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:44.027886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:44.399925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:44.871841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:43.732409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:44.113947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:44.496969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:44.967039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:43.813447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:44.207194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:44.596471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:45.068678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:43.913144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:44.312184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T22:17:44.687758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-29T22:17:50.781044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명착공 용도WGS84위도WGS84위도.1WGS84경도WGS84경도.1비고
시군명1.0000.5210.8740.9050.8700.9000.994
착공 용도0.5211.0000.3640.3540.4490.4320.824
WGS84위도0.8740.3641.0000.9120.8740.874NaN
WGS84위도.10.9050.3540.9121.0000.7510.7290.941
WGS84경도0.8700.4490.8740.7511.0001.000NaN
WGS84경도.10.9000.4320.8740.7291.0001.0000.948
비고0.9940.824NaN0.941NaN0.9481.000
2024-04-29T22:17:50.907398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
착공 용도시군명
착공 용도1.0000.136
시군명0.1361.000
2024-04-29T22:17:50.987296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WGS84위도WGS84위도.1WGS84경도WGS84경도.1시군명착공 용도
WGS84위도1.0001.000-0.294-0.2940.6220.137
WGS84위도.11.0001.000-0.2940.2280.6280.132
WGS84경도-0.294-0.2941.0001.0000.6140.175
WGS84경도.1-0.2940.2281.0001.0000.6160.166
시군명0.6220.6280.6140.6161.0000.136
착공 용도0.1370.1320.1750.1660.1361.000

Missing values

2024-04-29T22:17:45.214209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-29T22:17:45.374489image/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.
2024-04-29T22:17:45.768570image/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

시군명설계사무소명신고일착공 신고지 도로명주소착공 신고지 지번주소시공사명착공 용도WGS84위도WGS84위도.1WGS84경도WGS84경도.1비고
31869양주시관건축사사무소2021-05-24경기도 양주시 광적면 휴암로 298경기도 양주시 광적면 효촌리 408-1번지<NA>단독주택37.88303337.883033126.959704126.959704<NA>
744가평군(유)세진건축사사무소2014-04-22경기도 가평군 조종면 세곡로 58-138경기도 가평군 조종면 신상리 648-3번지<NA>단독주택<NA>37.660312<NA>127.482202<NA>
4598가평군건승건축사사무소2007-06-14경기도 가평군 설악면 봉미산안길13번길 175경기도 가평군 설악면 설곡리 331-1번지<NA>단독주택<NA>37.804208<NA>127.515529<NA>
30308안성시태림건축사사무소2020-09-02경기도 안성시 양성면 가래울길 68-45경기도 안성시 양성면 추곡리 49 외5필지<NA>동.식물관련시설<NA>37.068348<NA>127.209066<NA>
13119고양시도우건축사사무소2021-11-05경기도 고양시 일산동구 문원길120번길 107경기도 고양시 일산동구 설문동 82-1건축주직영제1종근린생활시설<NA>37.720352<NA>126.8213<NA>
32476양주시라인건축사사무소2020-12-10경기도 양주시 백석읍 권율로1398번길 95경기도 양주시 백석읍 오산리 429번지<NA>동.식물관련시설37.8044237.80442126.981474126.981474<NA>
28209안성시예인건축사사무소2017-01-04경기도 안성시 보개면 보개산로 254-17경기도 안성시 보개면 북좌리 55-2번지<NA>창고시설<NA>37.04068<NA>127.334238<NA>
35960양평군BOM건축사사무소2022-03-07경기도 양평군 양평읍 충신로351번길 59-6경기도 양평군 양평읍 회현리 487-1번지<NA>단독주택37.46924837.469248127.501516127.501516<NA>
41109용인시(주)유원건축사사무소2022-08-24경기도 용인시 처인구 포곡읍 마성리 99-2 외3필지경기도 용인시 처인구 포곡읍 마성리 99-2 외3필지(주)제이디종합건설제1종근린생활시설37.2814937.28149127.197957127.197957<NA>
49155파주시(주)나무건축사사무소2021-02-17<NA>경기도 파주시 야당동 244-34(주)유러스건설공동주택<NA><NA><NA><NA><NA>
시군명설계사무소명신고일착공 신고지 도로명주소착공 신고지 지번주소시공사명착공 용도WGS84위도WGS84위도.1WGS84경도WGS84경도.1비고
29504안성시주식회사 세림건축사사무소2017-11-06경기도 안성시 원곡면 승량길 79경기도 안성시 원곡면 성은리 10번지<NA>공장<NA>37.07793<NA>127.161406<NA>
13952광명시드림종합건축사사무소2019-02-22경기도 광명시 시청로 11경기도 광명시 철산동 463-92번지(주)하호종합건설제2종근린생활시설37.47800137.478001126.863388126.863388<NA>
38113양평군송건축사사무소2020-08-24경기도 양평군 양동면 사이실1길 225경기도 양평군 양동면 석곡리 662번지<NA>단독주택37.45079837.450798127.756646127.756646<NA>
46624이천시노 건축사사무소2020-09-02<NA>경기도 이천시 창전동 423이천시장제1종근린생활시설<NA><NA><NA><NA><NA>
52000파주시부성 건축사사무소2022-01-24<NA>경기도 파주시 상지석동 190-11맹덕희제1종근린생활시설<NA><NA><NA><NA><NA>
15139김포시(주)대한종합건축사사무소2021-03-23경기도 김포시 대곶면 대곶북로 156경기도 김포시 대곶면 초원지리 600번지서림종합건설(주)제1종근린생활시설37.66183137.661831126.585339126.585339<NA>
39864양평군청남건축사사무소2022-07-07<NA>경기도 양평군 단월면 보룡리 305-18 외2필지<NA>제2종근린생활시설37.53230337.532303127.668093127.668093<NA>
43560용인시원건축사사무소2021-05-26경기도 용인시 처인구 모현읍 일산리 283-37경기도 용인시 처인구 모현읍 일산리 283-37<NA>제2종근린생활시설37.34831337.348313127.236254127.236254<NA>
38906양평군주식회사 동빈건축사사무소2021-03-18경기도 양평군 서종면 황순원로 138-10경기도 양평군 서종면 수능리 338-15번지<NA>단독주택37.59638737.596387127.380916127.380916<NA>
51383파주시남부건축사사무소2020-06-18<NA>경기도 파주시 하지석동 200-2(주)신촌종합건설공장<NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군명설계사무소명신고일착공 신고지 도로명주소착공 신고지 지번주소시공사명착공 용도WGS84위도WGS84위도.1WGS84경도WGS84경도.1비고# duplicates
16성남시(주)종합건축사사무소그룹예성2020-03-13경기도 성남시 분당구 새나리로6번길 5경기도 성남시 분당구 야탑동 129-5번지화성종합건설(주)교정및군사시설37.40337937.403379127.156154127.156154<NA>6
36용인시태성건축사사무소2021-12-06경기도 용인시 기흥구 중동 131-55경기도 용인시 기흥구 중동 131-55(주)삼우종합건설단독주택37.27261437.272614127.163548127.163548<NA>4
1가평군건축사사무소 정훈2017-10-24경기도 가평군 가평읍 태봉두밀로406번길 127-62경기도 가평군 가평읍 두밀리 144-26번지<NA>제2종근린생활시설<NA>37.822936<NA>127.447414<NA>3
9가평군한성건축사 사무소2022-05-13경기도 가평군 상면 기와집길 174-94경기도 가평군 상면 연하리 290-11번지주식회사디센트가든단독주택<NA>37.793361<NA>127.349562<NA>3
13성남시(주)나우동인건축사사무소2020-11-27경기도 성남시 수정구 대왕판교로 961경기도 성남시 수정구 고등동 601번지 판교밸리자이3단지지에스건설(주)공동주택37.42624137.426241127.101938127.101938<NA>3
14성남시(주)나우동인건축사사무소2020-11-27경기도 성남시 수정구 대왕판교로 995-경기도 성남시 수정구 고등동 582번지 판교밸리자이1단지지에스건설(주)공동주택37.42993337.429933127.100991127.100991<NA>3
15성남시(주)예인종합건축사사무소2021-01-04경기도 성남시 분당구 이매로144번길 3경기도 성남시 분당구 이매동 346-4번지(주)케이티건설공동주택37.39047837.390478127.135131127.135131<NA>3
21안성시주식회사 건축사사무소범건축2021-04-05<NA>경기도 안성시 양성면 도곡리 산 9-1<NA>단독주택<NA>37.088378<NA>127.214658<NA>3
0가평군(주)일진건축사사무소2007-11-08경기도 가평군 북면 백둔로 379경기도 가평군 북면 백둔리 342번지<NA>단독주택<NA>37.902232<NA>127.466922<NA>2
2가평군건축사사무소명성2022-09-26<NA>경기도 가평군 설악면 설곡리 595주식회사케이종합건설제2종근린생활시설<NA>37.618509<NA>127.524329<NA>2