Overview

Dataset statistics

Number of variables10
Number of observations434
Missing cells809
Missing cells (%)18.6%
Duplicate rows1
Duplicate rows (%)0.2%
Total size in memory34.9 KiB
Average record size in memory82.3 B

Variable types

Categorical2
Text5
DateTime1
Numeric2

Dataset

Description건축착공 신고현황 건축사무소별 현황(시군명, 설계사무소명, 신고일, 착공신고지도로명주소, 착공신고지지번주소, 시공사명, 착공용도, 위도, 경도,비고)입니다.
URLhttps://www.data.go.kr/data/15114531/fileData.do

Alerts

시군명 has constant value ""Constant
비고 has constant value ""Constant
Dataset has 1 (0.2%) duplicate rowsDuplicates
착공용도 is highly imbalanced (56.5%)Imbalance
착공신고지도로명주소 has 66 (15.2%) missing valuesMissing
시공사명 has 307 (70.7%) missing valuesMissing
비고 has 433 (99.8%) missing valuesMissing

Reproduction

Analysis started2023-12-12 23:31:51.521909
Analysis finished2023-12-12 23:31:52.776624
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
안양시
434 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안양시 434
100.0%

Length

2023-12-13T08:31:52.825789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:52.904210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안양시 434
100.0%

설계사무소명
Text

Distinct213
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2023-12-13T08:31:53.060362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length11.034562
Min length5

Characters and Unicode

Total characters4789
Distinct characters197
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)34.1%

Sample

1st row국제건축사사무소(주)
2nd row(주)푸름인건축사사무소
3rd row(주)좋은건축사사무소
4th row건축사사무소 대삼
5th row화인건축사사무소
ValueCountFrequency (%)
건축사사무소 98
 
17.1%
이레종합건축사사무소 19
 
3.3%
건축사사무소에스앤케이 17
 
3.0%
주)포에이그룹건축사사무소 15
 
2.6%
주)종합건축사사무소 15
 
2.6%
도움 13
 
2.3%
진원건축사사무소 13
 
2.3%
우림 13
 
2.3%
주)다우건축사사무소 10
 
1.7%
국제건축사사무소(주 7
 
1.2%
Other values (212) 354
61.7%
2023-12-13T08:31:53.364088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 876
18.3%
건 474
 
9.9%
축 462
 
9.6%
무 437
 
9.1%
소 437
 
9.1%
주 176
 
3.7%
( 166
 
3.5%
) 166
 
3.5%
140
 
2.9%
이 108
 
2.3%
Other values (187) 1347
28.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4306
89.9%
Open Punctuation 166
 
3.5%
Close Punctuation 166
 
3.5%
Space Separator 140
 
2.9%
Uppercase Letter 9
 
0.2%
Other Punctuation 1
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 876
20.3%
건 474
11.0%
축 462
10.7%
무 437
10.1%
소 437
10.1%
주 176
 
4.1%
이 108
 
2.5%
종 96
 
2.2%
합 96
 
2.2%
우 56
 
1.3%
Other values (175) 1088
25.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
22.2%
K 2
22.2%
A 1
11.1%
D 1
11.1%
S 1
11.1%
E 1
11.1%
Z 1
11.1%
Open Punctuation
ValueCountFrequency (%)
( 166
100.0%
Close Punctuation
ValueCountFrequency (%)
) 166
100.0%
Space Separator
ValueCountFrequency (%)
140
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4307
89.9%
Common 473
 
9.9%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 876
20.3%
건 474
11.0%
축 462
10.7%
무 437
10.1%
소 437
10.1%
주 176
 
4.1%
이 108
 
2.5%
종 96
 
2.2%
합 96
 
2.2%
우 56
 
1.3%
Other values (176) 1089
25.3%
Latin
ValueCountFrequency (%)
C 2
22.2%
K 2
22.2%
A 1
11.1%
D 1
11.1%
S 1
11.1%
E 1
11.1%
Z 1
11.1%
Common
ValueCountFrequency (%)
( 166
35.1%
) 166
35.1%
140
29.6%
, 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4306
89.9%
ASCII 482
 
10.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 876
20.3%
건 474
11.0%
축 462
10.7%
무 437
10.1%
소 437
10.1%
주 176
 
4.1%
이 108
 
2.5%
종 96
 
2.2%
합 96
 
2.2%
우 56
 
1.3%
Other values (175) 1088
25.3%
ASCII
ValueCountFrequency (%)
( 166
34.4%
) 166
34.4%
140
29.0%
C 2
 
0.4%
K 2
 
0.4%
A 1
 
0.2%
D 1
 
0.2%
S 1
 
0.2%
E 1
 
0.2%
, 1
 
0.2%
None
ValueCountFrequency (%)
㈜ 1
100.0%

신고일
Date

Distinct312
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum2020-01-02 00:00:00
Maximum2023-02-27 00:00:00
2023-12-13T08:31:53.500830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:53.627794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공신고지도로명주소
Text

MISSING 

Distinct350
Distinct (%)95.1%
Missing66
Missing (%)15.2%
Memory size3.5 KiB
2023-12-13T08:31:53.912145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length21.649457
Min length1

Characters and Unicode

Total characters7967
Distinct characters90
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

Unique337 ?
Unique (%)91.6%

Sample

1st row경기도 안양시 만안구 장내로 30
2nd row경기도 안양시 만안구 석수동 113-8
3rd row경기도 안양시 만안구 덕천로 95
4th row경기도 안양시 만안구 안양로 151-1
5th row경기도 안양시 만안구 병목안로 408
ValueCountFrequency (%)
경기도 367
19.8%
안양시 367
19.8%
만안구 227
 
12.3%
동안구 140
 
7.6%
경수대로 20
 
1.1%
안양동 16
 
0.9%
안양로 13
 
0.7%
덕천로 12
 
0.6%
병목안로130번길 10
 
0.5%
만안로 9
 
0.5%
Other values (410) 668
36.1%
2023-12-13T08:31:54.351928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1481
18.6%
안 839
 
10.5%
양 447
 
5.6%
경 392
 
4.9%
시 380
 
4.8%
구 367
 
4.6%
도 367
 
4.6%
기 367
 
4.6%
로 336
 
4.2%
1 304
 
3.8%
Other values (80) 2687
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4939
62.0%
Space Separator 1481
 
18.6%
Decimal Number 1448
 
18.2%
Dash Punctuation 98
 
1.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 839
17.0%
양 447
9.1%
경 392
 
7.9%
시 380
 
7.7%
구 367
 
7.4%
도 367
 
7.4%
기 367
 
7.4%
로 336
 
6.8%
만 240
 
4.9%
동 185
 
3.7%
Other values (67) 1019
20.6%
Decimal Number
ValueCountFrequency (%)
1 304
21.0%
3 198
13.7%
2 176
12.2%
4 149
10.3%
5 128
8.8%
9 109
 
7.5%
0 107
 
7.4%
7 95
 
6.6%
6 93
 
6.4%
8 89
 
6.1%
Space Separator
ValueCountFrequency (%)
1481
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4939
62.0%
Common 3028
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 839
17.0%
양 447
9.1%
경 392
 
7.9%
시 380
 
7.7%
구 367
 
7.4%
도 367
 
7.4%
기 367
 
7.4%
로 336
 
6.8%
만 240
 
4.9%
동 185
 
3.7%
Other values (67) 1019
20.6%
Common
ValueCountFrequency (%)
1481
48.9%
1 304
 
10.0%
3 198
 
6.5%
2 176
 
5.8%
4 149
 
4.9%
5 128
 
4.2%
9 109
 
3.6%
0 107
 
3.5%
- 98
 
3.2%
7 95
 
3.1%
Other values (3) 183
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4939
62.0%
ASCII 3028
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1481
48.9%
1 304
 
10.0%
3 198
 
6.5%
2 176
 
5.8%
4 149
 
4.9%
5 128
 
4.2%
9 109
 
3.6%
0 107
 
3.5%
- 98
 
3.2%
7 95
 
3.1%
Other values (3) 183
 
6.0%
Hangul
ValueCountFrequency (%)
안 839
17.0%
양 447
9.1%
경 392
 
7.9%
시 380
 
7.7%
구 367
 
7.4%
도 367
 
7.4%
기 367
 
7.4%
로 336
 
6.8%
만 240
 
4.9%
동 185
 
3.7%
Other values (67) 1019
20.6%

착공신고지지번주소
Text

Distinct417
Distinct (%)96.3%
Missing1
Missing (%)0.2%
Memory size3.5 KiB
2023-12-13T08:31:54.524942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length23.057737
Min length18

Characters and Unicode

Total characters9984
Distinct characters35
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

Unique406 ?
Unique (%)93.8%

Sample

1st row경기도 안양시 만안구 안양동 752-2 외5필지
2nd row경기도 안양시 만안구 석수동 113-8
3rd row경기도 안양시 만안구 안양동 212-11
4th row경기도 안양시 만안구 안양동 491-6
5th row경기도 안양시 만안구 안양동 1151-2 외23필지
ValueCountFrequency (%)
경기도 433
18.7%
안양시 433
18.7%
만안구 252
10.9%
동안구 181
 
7.8%
안양동 172
 
7.4%
관양동 79
 
3.4%
외1필지 72
 
3.1%
호계동 60
 
2.6%
석수동 44
 
1.9%
박달동 36
 
1.6%
Other values (431) 557
24.0%
2023-12-13T08:31:54.807933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1886
18.9%
안 1038
 
10.4%
양 684
 
6.9%
동 614
 
6.1%
1 485
 
4.9%
경 433
 
4.3%
도 433
 
4.3%
시 433
 
4.3%
구 433
 
4.3%
기 433
 
4.3%
Other values (25) 3112
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5642
56.5%
Decimal Number 2082
 
20.9%
Space Separator 1886
 
18.9%
Dash Punctuation 374
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 1038
18.4%
양 684
12.1%
동 614
10.9%
경 433
7.7%
도 433
7.7%
시 433
7.7%
구 433
7.7%
기 433
7.7%
만 252
 
4.5%
지 146
 
2.6%
Other values (13) 743
13.2%
Decimal Number
ValueCountFrequency (%)
1 485
23.3%
2 262
12.6%
9 208
10.0%
4 199
9.6%
3 194
 
9.3%
5 181
 
8.7%
8 143
 
6.9%
0 141
 
6.8%
6 137
 
6.6%
7 132
 
6.3%
Space Separator
ValueCountFrequency (%)
1886
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 374
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5642
56.5%
Common 4342
43.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 1038
18.4%
양 684
12.1%
동 614
10.9%
경 433
7.7%
도 433
7.7%
시 433
7.7%
구 433
7.7%
기 433
7.7%
만 252
 
4.5%
지 146
 
2.6%
Other values (13) 743
13.2%
Common
ValueCountFrequency (%)
1886
43.4%
1 485
 
11.2%
- 374
 
8.6%
2 262
 
6.0%
9 208
 
4.8%
4 199
 
4.6%
3 194
 
4.5%
5 181
 
4.2%
8 143
 
3.3%
0 141
 
3.2%
Other values (2) 269
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5642
56.5%
ASCII 4342
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1886
43.4%
1 485
 
11.2%
- 374
 
8.6%
2 262
 
6.0%
9 208
 
4.8%
4 199
 
4.6%
3 194
 
4.5%
5 181
 
4.2%
8 143
 
3.3%
0 141
 
3.2%
Other values (2) 269
 
6.2%
Hangul
ValueCountFrequency (%)
안 1038
18.4%
양 684
12.1%
동 614
10.9%
경 433
7.7%
도 433
7.7%
시 433
7.7%
구 433
7.7%
기 433
7.7%
만 252
 
4.5%
지 146
 
2.6%
Other values (13) 743
13.2%

시공사명
Text

MISSING 

Distinct113
Distinct (%)89.0%
Missing307
Missing (%)70.7%
Memory size3.5 KiB
2023-12-13T08:31:55.047637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.5590551
Min length4

Characters and Unicode

Total characters1087
Distinct characters140
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

Unique101 ?
Unique (%)79.5%

Sample

1st row서진토건주식회사
2nd row(주)세진에스씨엠
3rd row(주)건우종합건설
4th row도선종합건설(주)
5th row차원종합건설(주)
ValueCountFrequency (%)
주식회사 6
 
4.5%
동보종합건설(주 3
 
2.3%
주)개성건설 3
 
2.3%
신호건설(주 2
 
1.5%
도선종합건설(주 2
 
1.5%
주)담을건설 2
 
1.5%
주)미영에이티건설 2
 
1.5%
주)트래콘건설 2
 
1.5%
에스케이에코플랜트(주 2
 
1.5%
두호종합건설(주 2
 
1.5%
Other values (104) 107
80.5%
2023-12-13T08:31:55.487325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 126
 
11.6%
( 113
 
10.4%
) 113
 
10.4%
건 97
 
8.9%
설 93
 
8.6%
종 47
 
4.3%
합 47
 
4.3%
이 29
 
2.7%
에 22
 
2.0%
씨 15
 
1.4%
Other values (130) 385
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 855
78.7%
Open Punctuation 113
 
10.4%
Close Punctuation 113
 
10.4%
Space Separator 6
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 126
 
14.7%
건 97
 
11.3%
설 93
 
10.9%
종 47
 
5.5%
합 47
 
5.5%
이 29
 
3.4%
에 22
 
2.6%
씨 15
 
1.8%
사 14
 
1.6%
식 13
 
1.5%
Other values (127) 352
41.2%
Open Punctuation
ValueCountFrequency (%)
( 113
100.0%
Close Punctuation
ValueCountFrequency (%)
) 113
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 855
78.7%
Common 232
 
21.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 126
 
14.7%
건 97
 
11.3%
설 93
 
10.9%
종 47
 
5.5%
합 47
 
5.5%
이 29
 
3.4%
에 22
 
2.6%
씨 15
 
1.8%
사 14
 
1.6%
식 13
 
1.5%
Other values (127) 352
41.2%
Common
ValueCountFrequency (%)
( 113
48.7%
) 113
48.7%
6
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 855
78.7%
ASCII 232
 
21.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 126
 
14.7%
건 97
 
11.3%
설 93
 
10.9%
종 47
 
5.5%
합 47
 
5.5%
이 29
 
3.4%
에 22
 
2.6%
씨 15
 
1.8%
사 14
 
1.6%
식 13
 
1.5%
Other values (127) 352
41.2%
ASCII
ValueCountFrequency (%)
( 113
48.7%
) 113
48.7%
6
 
2.6%

착공용도
Categorical

IMBALANCE 

Distinct18
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
<NA>
301 
업무시설
52 
공장
 
21
제1종근린생활시설
 
14
공동주택
 
10
Other values (13)
36 

Length

Max length9
Median length4
Mean length4.2096774
Min length2

Unique

Unique4 ?
Unique (%)0.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 301
69.4%
업무시설 52
 
12.0%
공장 21
 
4.8%
제1종근린생활시설 14
 
3.2%
공동주택 10
 
2.3%
제2종근린생활시설 6
 
1.4%
교육연구시설 5
 
1.2%
자동차관련시설 4
 
0.9%
의료시설 4
 
0.9%
노유자시설 3
 
0.7%
Other values (8) 14
 
3.2%

Length

2023-12-13T08:31:55.727992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 301
69.4%
업무시설 52
 
12.0%
공장 21
 
4.8%
제1종근린생활시설 14
 
3.2%
공동주택 10
 
2.3%
제2종근린생활시설 6
 
1.4%
교육연구시설 5
 
1.2%
자동차관련시설 4
 
0.9%
의료시설 4
 
0.9%
숙박시설 3
 
0.7%
Other values (8) 14
 
3.2%

WGS84위도
Real number (ℝ)

Distinct415
Distinct (%)95.8%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean37.396414
Minimum37.362223
Maximum37.428133
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-13T08:31:55.880346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.362223
5-th percentile37.37254
Q137.387968
median37.396499
Q337.404589
95-th percentile37.419204
Maximum37.428133
Range0.0659105
Interquartile range (IQR)0.01662179

Descriptive statistics

Standard deviation0.013285223
Coefficient of variation (CV)0.00035525392
Kurtosis-0.19015769
Mean37.396414
Median Absolute Deviation (MAD)0.00822433
Skewness0.012280736
Sum16192.647
Variance0.00017649714
MonotonicityNot monotonic
2023-12-13T08:31:56.058971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.37825425 5
 
1.2%
37.39598374 3
 
0.7%
37.37981684 3
 
0.7%
37.40576823 2
 
0.5%
37.39912336 2
 
0.5%
37.38791527 2
 
0.5%
37.3885524 2
 
0.5%
37.39904714 2
 
0.5%
37.40002546 2
 
0.5%
37.36990533 2
 
0.5%
Other values (405) 408
94.0%
ValueCountFrequency (%)
37.36222258 1
0.2%
37.36675211 1
0.2%
37.36686019 1
0.2%
37.36703129 1
0.2%
37.36721321 1
0.2%
37.36806219 1
0.2%
37.36844748 1
0.2%
37.36854019 1
0.2%
37.36892309 1
0.2%
37.36965318 1
0.2%
ValueCountFrequency (%)
37.42813308 1
0.2%
37.42765191 2
0.5%
37.42755198 1
0.2%
37.42712786 1
0.2%
37.42677566 1
0.2%
37.42677209 1
0.2%
37.42587439 1
0.2%
37.42535954 1
0.2%
37.42501488 1
0.2%
37.42486679 1
0.2%

WGS84경도
Real number (ℝ)

Distinct415
Distinct (%)95.8%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean126.93459
Minimum126.88198
Maximum126.97829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-13T08:31:56.225313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.88198
5-th percentile126.89475
Q1126.91442
median126.93232
Q3126.957
95-th percentile126.97339
Maximum126.97829
Range0.0963139
Interquartile range (IQR)0.0425751

Descriptive statistics

Standard deviation0.024496308
Coefficient of variation (CV)0.00019298371
Kurtosis-0.92713819
Mean126.93459
Median Absolute Deviation (MAD)0.0192193
Skewness0.048497395
Sum54962.676
Variance0.00060006909
MonotonicityNot monotonic
2023-12-13T08:31:56.382487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8858221 5
 
1.2%
126.9607565 3
 
0.7%
126.9251905 3
 
0.7%
126.8859312 2
 
0.5%
126.9419451 2
 
0.5%
126.9353972 2
 
0.5%
126.9423963 2
 
0.5%
126.9204792 2
 
0.5%
126.9326287 2
 
0.5%
126.9486669 2
 
0.5%
Other values (405) 408
94.0%
ValueCountFrequency (%)
126.8819764 1
 
0.2%
126.8823756 1
 
0.2%
126.8845327 1
 
0.2%
126.8847648 1
 
0.2%
126.8848691 1
 
0.2%
126.8851013 1
 
0.2%
126.8853837 1
 
0.2%
126.8857078 1
 
0.2%
126.8857206 1
 
0.2%
126.8858221 5
1.2%
ValueCountFrequency (%)
126.9782903 1
0.2%
126.9780355 1
0.2%
126.9779238 1
0.2%
126.9778099 1
0.2%
126.9776293 1
0.2%
126.9775739 1
0.2%
126.9772486 1
0.2%
126.9769762 1
0.2%
126.9761714 1
0.2%
126.976096 1
0.2%

비고
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing433
Missing (%)99.8%
Memory size3.5 KiB
2023-12-13T08:31:56.569527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length44
Mean length44
Min length44

Characters and Unicode

Total characters44
Distinct characters32
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

Unique1 ?
Unique (%)100.0%

Sample

1st row경기도 안양시 만안구 안양동 예술공원입구주변지구 주택재개발정비사업 18-95일원
ValueCountFrequency (%)
경기도 1
14.3%
안양시 1
14.3%
만안구 1
14.3%
안양동 1
14.3%
예술공원입구주변지구 1
14.3%
주택재개발정비사업 1
14.3%
18-95일원 1
14.3%
2023-12-13T08:31:56.877087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
13.6%
안 3
 
6.8%
구 3
 
6.8%
양 2
 
4.5%
주 2
 
4.5%
원 2
 
4.5%
경 1
 
2.3%
사 1
 
2.3%
발 1
 
2.3%
정 1
 
2.3%
Other values (22) 22
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33
75.0%
Space Separator 6
 
13.6%
Decimal Number 4
 
9.1%
Dash Punctuation 1
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 3
 
9.1%
구 3
 
9.1%
양 2
 
6.1%
주 2
 
6.1%
원 2
 
6.1%
경 1
 
3.0%
사 1
 
3.0%
발 1
 
3.0%
정 1
 
3.0%
비 1
 
3.0%
Other values (16) 16
48.5%
Decimal Number
ValueCountFrequency (%)
8 1
25.0%
1 1
25.0%
9 1
25.0%
5 1
25.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33
75.0%
Common 11
 
25.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 3
 
9.1%
구 3
 
9.1%
양 2
 
6.1%
주 2
 
6.1%
원 2
 
6.1%
경 1
 
3.0%
사 1
 
3.0%
발 1
 
3.0%
정 1
 
3.0%
비 1
 
3.0%
Other values (16) 16
48.5%
Common
ValueCountFrequency (%)
6
54.5%
8 1
 
9.1%
1 1
 
9.1%
- 1
 
9.1%
9 1
 
9.1%
5 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33
75.0%
ASCII 11
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
54.5%
8 1
 
9.1%
1 1
 
9.1%
- 1
 
9.1%
9 1
 
9.1%
5 1
 
9.1%
Hangul
ValueCountFrequency (%)
안 3
 
9.1%
구 3
 
9.1%
양 2
 
6.1%
주 2
 
6.1%
원 2
 
6.1%
경 1
 
3.0%
사 1
 
3.0%
발 1
 
3.0%
정 1
 
3.0%
비 1
 
3.0%
Other values (16) 16
48.5%

Interactions

2023-12-13T08:31:52.076433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:51.907694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:52.172734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:31:51.987263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:31:56.973963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
착공용도WGS84위도WGS84경도
착공용도1.0000.5220.560
WGS84위도0.5221.0000.744
WGS84경도0.5600.7441.000
2023-12-13T08:31:57.078111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WGS84위도WGS84경도착공용도
WGS84위도1.000-0.2800.224
WGS84경도-0.2801.0000.247
착공용도0.2240.2471.000

Missing values

2023-12-13T08:31:52.260659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:31:52.379905image/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.
2023-12-13T08:31:52.709553image/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

시군명설계사무소명신고일착공신고지도로명주소착공신고지지번주소시공사명착공용도WGS84위도WGS84경도비고
0안양시국제건축사사무소(주)2020-01-02경기도 안양시 만안구 장내로 30경기도 안양시 만안구 안양동 752-2 외5필지<NA><NA>37.392888126.912539<NA>
1안양시(주)푸름인건축사사무소2022-12-15경기도 안양시 만안구 석수동 113-8경기도 안양시 만안구 석수동 113-8<NA><NA>37.426772126.915426<NA>
2안양시(주)좋은건축사사무소2020-01-07경기도 안양시 만안구 덕천로 95경기도 안양시 만안구 안양동 212-11<NA><NA>37.389586126.934165<NA>
3안양시건축사사무소 대삼2020-01-10경기도 안양시 만안구 안양로 151-1경기도 안양시 만안구 안양동 491-6<NA><NA>37.387782126.930247<NA>
4안양시화인건축사사무소2020-01-13경기도 안양시 만안구 병목안로 408경기도 안양시 만안구 안양동 1151-2 외23필지<NA><NA>37.370255126.905398<NA>
5안양시건축사사무소에스앤케이2020-01-16경기도 안양시 만안구 박달로560번길 29-6경기도 안양시 만안구 안양동 873-96<NA><NA>37.401094126.915131<NA>
6안양시이수 건축사사무소2020-01-17경기도 안양시 동안구 갈산로2번길 19경기도 안양시 동안구 호계동 1110-5<NA><NA>37.372951126.964106<NA>
7안양시(주)종합건축사사무소 우림2020-01-21경기도 안양시 만안구 삼막로96번길 23-22경기도 안양시 만안구 석수동 134-9<NA><NA>37.425874126.915503<NA>
8안양시매우람 건축사사무소2020-01-22경기도 안양시 동안구 관악대로 403-7경기도 안양시 동안구 관양동 1433-33<NA><NA>37.405217126.967538<NA>
9안양시(주)포에이그룹건축사사무소2020-01-23경기도 안양시 만안구 안양동 497-19경기도 안양시 만안구 안양동 497-19<NA><NA>37.387262126.926952<NA>
시군명설계사무소명신고일착공신고지도로명주소착공신고지지번주소시공사명착공용도WGS84위도WGS84경도비고
424안양시두경건축사사무소2022-11-08경기도 안양시 만안구 박달동 374 외40필지경기도 안양시 만안구 박달동 374 외40필지<NA><NA>37.38839126.884869<NA>
425안양시(주)문양종합건축사사무소2022-11-14경기도 안양시 만안구 안양동 822-1 외1필지경기도 안양시 만안구 안양동 822-1 외1필지<NA><NA>37.406776126.911903<NA>
426안양시(주)도원건축사사무소2022-11-16경기도 안양시 만안구 박달동 783 외1필지경기도 안양시 만안구 박달동 783 외1필지<NA><NA>37.405996126.885101<NA>
427안양시(주)포에이그룹건축사사무소2022-11-28경기도 안양시 만안구 안양동 1319-12경기도 안양시 만안구 안양동 1319-12<NA><NA>37.41828126.919935<NA>
428안양시신우건축사사무소2022-12-07경기도 안양시 만안구 양화로 243경기도 안양시 만안구 석수동 337-1(주)미영에이티건설공동주택37.413803126.906014<NA>
429안양시(주)한림건축씨엠종합건축사사무소2022-12-12<NA>경기도 안양시 만안구 안양동 437-2신원종합개발(주)업무시설37.390138126.930679<NA>
430안양시(주)야긴건축사사무소2022-12-14<NA>경기도 안양시 동안구 호계동 282-12 외3필지율산종합건설(주)종교시설37.382057126.948786<NA>
431안양시젬마종합건축사사무소2022-12-15경기도 안양시 동안구 평촌대로 104경기도 안양시 동안구 평촌동 923<NA><NA>37.3818126.961502<NA>
432안양시(주)건축사사무소다보건축2023-01-31<NA>경기도 안양시 동안구 관양동 1703인본산업(주)노유자시설37.408691126.973391<NA>
433안양시(주)좋은건축사사무소2023-02-27경기도 안양시 만안구 덕천로 100경기도 안양시 만안구 안양동 194-40(주)에이치디종합건설공장37.390066126.934568<NA>

Duplicate rows

Most frequently occurring

시군명설계사무소명신고일착공신고지도로명주소착공신고지지번주소시공사명착공용도WGS84위도WGS84경도비고# duplicates
0안양시(주)정우엔지니어링건축사사무소2021-10-15경기도 안양시 만안구 박달동 산 141경기도 안양시 만안구 박달동 산 141<NA><NA>37.378254126.885822<NA>5