Overview

Dataset statistics

Number of variables8
Number of observations59
Missing cells29
Missing cells (%)6.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory67.2 B

Variable types

Numeric1
Text5
DateTime1
Categorical1

Dataset

Description서울특별시 서대문구에 소재하고 있는 건축사사무소의 2017년도 현황입니다.(사무소명, 사무소주소, 신고일, 전화번호 등 )
Author서울특별시 서대문구
URLhttps://www.data.go.kr/data/15047875/fileData.do

Alerts

연번 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번High correlation
신고일 has 24 (40.7%) missing valuesMissing
전화번호 has 5 (8.5%) missing valuesMissing
연번 has unique valuesUnique
신고번호 has unique valuesUnique
사무소명 has unique valuesUnique
대표자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:23:30.943529
Analysis finished2023-12-12 20:23:31.947397
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30
Minimum1
Maximum59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2023-12-13T05:23:32.356656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.9
Q115.5
median30
Q344.5
95-th percentile56.1
Maximum59
Range58
Interquartile range (IQR)29

Descriptive statistics

Standard deviation17.175564
Coefficient of variation (CV)0.5725188
Kurtosis-1.2
Mean30
Median Absolute Deviation (MAD)15
Skewness0
Sum1770
Variance295
MonotonicityStrictly increasing
2023-12-13T05:23:32.500703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.7%
2 1
 
1.7%
33 1
 
1.7%
34 1
 
1.7%
35 1
 
1.7%
36 1
 
1.7%
37 1
 
1.7%
38 1
 
1.7%
39 1
 
1.7%
40 1
 
1.7%
Other values (49) 49
83.1%
ValueCountFrequency (%)
1 1
1.7%
2 1
1.7%
3 1
1.7%
4 1
1.7%
5 1
1.7%
6 1
1.7%
7 1
1.7%
8 1
1.7%
9 1
1.7%
10 1
1.7%
ValueCountFrequency (%)
59 1
1.7%
58 1
1.7%
57 1
1.7%
56 1
1.7%
55 1
1.7%
54 1
1.7%
53 1
1.7%
52 1
1.7%
51 1
1.7%
50 1
1.7%

신고번호
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-13T05:23:32.760038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.745763
Min length18

Characters and Unicode

Total characters1165
Distinct characters21
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

Unique59 ?
Unique (%)100.0%

Sample

1st row1998-서대문구-건축사사무소-7
2nd row1985-서대문구-건축사사무소-8
3rd row1987-서대문구-건축사사무소-29
4th row1990-서대문구-건축사사무소-41
5th row1993-서대문구-건축사사무소-47
ValueCountFrequency (%)
1998-서대문구-건축사사무소-7 1
 
1.7%
2003-서대문구-건축사사무소-121 1
 
1.7%
2014-서대문구-건축사사무소-179 1
 
1.7%
2014-서대문구-건축사사무소-180 1
 
1.7%
2015-서대문구-건축사사무소-186 1
 
1.7%
2015-서대문구 1
 
1.7%
건축사사무소-187 1
 
1.7%
2016-서대문구-건축사사무소-194 1
 
1.7%
2016-서대문구-건축사사무소-195 1
 
1.7%
2017-서대문구-건축사사무소-198 1
 
1.7%
Other values (50) 50
83.3%
2023-12-13T05:23:33.135703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 176
15.1%
사 118
 
10.1%
1 94
 
8.1%
0 74
 
6.4%
2 67
 
5.8%
소 59
 
5.1%
대 59
 
5.1%
문 59
 
5.1%
구 59
 
5.1%
건 59
 
5.1%
Other values (11) 341
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 590
50.6%
Decimal Number 398
34.2%
Dash Punctuation 176
 
15.1%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 94
23.6%
0 74
18.6%
2 67
16.8%
9 44
11.1%
6 23
 
5.8%
8 23
 
5.8%
5 21
 
5.3%
7 21
 
5.3%
3 17
 
4.3%
4 14
 
3.5%
Other Letter
ValueCountFrequency (%)
사 118
20.0%
소 59
10.0%
대 59
10.0%
문 59
10.0%
구 59
10.0%
건 59
10.0%
축 59
10.0%
무 59
10.0%
서 59
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 176
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 590
50.6%
Common 575
49.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 176
30.6%
1 94
16.3%
0 74
12.9%
2 67
 
11.7%
9 44
 
7.7%
6 23
 
4.0%
8 23
 
4.0%
5 21
 
3.7%
7 21
 
3.7%
3 17
 
3.0%
Other values (2) 15
 
2.6%
Hangul
ValueCountFrequency (%)
사 118
20.0%
소 59
10.0%
대 59
10.0%
문 59
10.0%
구 59
10.0%
건 59
10.0%
축 59
10.0%
무 59
10.0%
서 59
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 590
50.6%
ASCII 575
49.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 176
30.6%
1 94
16.3%
0 74
12.9%
2 67
 
11.7%
9 44
 
7.7%
6 23
 
4.0%
8 23
 
4.0%
5 21
 
3.7%
7 21
 
3.7%
3 17
 
3.0%
Other values (2) 15
 
2.6%
Hangul
ValueCountFrequency (%)
사 118
20.0%
소 59
10.0%
대 59
10.0%
문 59
10.0%
구 59
10.0%
건 59
10.0%
축 59
10.0%
무 59
10.0%
서 59
10.0%

신고일
Date

MISSING 

Distinct34
Distinct (%)97.1%
Missing24
Missing (%)40.7%
Memory size604.0 B
Minimum1985-07-01 00:00:00
Maximum2010-09-07 00:00:00
2023-12-13T05:23:33.314933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:23:33.453177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
개인
40 
법인
19 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 40
67.8%
법인 19
32.2%

Length

2023-12-13T05:23:33.588279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:23:33.678255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 40
67.8%
법인 19
32.2%

사무소명
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-13T05:23:33.894459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length10.20339
Min length7

Characters and Unicode

Total characters602
Distinct characters115
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)100.0%

Sample

1st row국제건축사사무소
2nd row유전건축사사무소
3rd row건축사사무소서은
4th row박양춘건축사사무소
5th row건축사사무소송인
ValueCountFrequency (%)
건축사사무소 16
 
19.3%
㈜종합건축사사무소 2
 
2.4%
lim 1
 
1.2%
래안 1
 
1.2%
㈜씨앤에이건축사사무소 1
 
1.2%
㈜아키프라자건축사사무소 1
 
1.2%
㈜화영건축사사무소 1
 
1.2%
더이레건축사사무소 1
 
1.2%
보민 1
 
1.2%
림 1
 
1.2%
Other values (57) 57
68.7%
2023-12-13T05:23:34.287123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 116
19.3%
건 65
 
10.8%
축 65
 
10.8%
소 59
 
9.8%
무 58
 
9.6%
24
 
4.0%
㈜ 19
 
3.2%
이 12
 
2.0%
종 10
 
1.7%
합 9
 
1.5%
Other values (105) 165
27.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 547
90.9%
Space Separator 24
 
4.0%
Other Symbol 19
 
3.2%
Uppercase Letter 7
 
1.2%
Decimal Number 2
 
0.3%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 116
21.2%
건 65
11.9%
축 65
11.9%
소 59
10.8%
무 58
10.6%
이 12
 
2.2%
종 10
 
1.8%
합 9
 
1.6%
아 7
 
1.3%
스 5
 
0.9%
Other values (92) 141
25.8%
Uppercase Letter
ValueCountFrequency (%)
M 2
28.6%
I 1
14.3%
L 1
14.3%
A 1
14.3%
O 1
14.3%
S 1
14.3%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 566
94.0%
Common 29
 
4.8%
Latin 7
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 116
20.5%
건 65
11.5%
축 65
11.5%
소 59
10.4%
무 58
 
10.2%
㈜ 19
 
3.4%
이 12
 
2.1%
종 10
 
1.8%
합 9
 
1.6%
아 7
 
1.2%
Other values (93) 146
25.8%
Common
ValueCountFrequency (%)
24
82.8%
( 1
 
3.4%
) 1
 
3.4%
1 1
 
3.4%
2 1
 
3.4%
. 1
 
3.4%
Latin
ValueCountFrequency (%)
M 2
28.6%
I 1
14.3%
L 1
14.3%
A 1
14.3%
O 1
14.3%
S 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 547
90.9%
ASCII 36
 
6.0%
None 19
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 116
21.2%
건 65
11.9%
축 65
11.9%
소 59
10.8%
무 58
10.6%
이 12
 
2.2%
종 10
 
1.8%
합 9
 
1.6%
아 7
 
1.3%
스 5
 
0.9%
Other values (92) 141
25.8%
ASCII
ValueCountFrequency (%)
24
66.7%
M 2
 
5.6%
I 1
 
2.8%
( 1
 
2.8%
L 1
 
2.8%
) 1
 
2.8%
A 1
 
2.8%
O 1
 
2.8%
1 1
 
2.8%
2 1
 
2.8%
Other values (2) 2
 
5.6%
None
ValueCountFrequency (%)
㈜ 19
100.0%

사무소주소
Text

Distinct56
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-13T05:23:34.559875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length17.881356
Min length9

Characters and Unicode

Total characters1055
Distinct characters108
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)89.8%

Sample

1st row연희로 245(연희동 아취빌딩)
2nd row연희로 245(연희동 아취빌딩)
3rd row연희로 263(홍은동 봉산빌딩)
4th row연희로36길 10(연희동)
5th row연희로26길 14 2층(연희동 경보빌딩)
ValueCountFrequency (%)
연희동 10
 
5.1%
연희로 6
 
3.1%
4층 5
 
2.6%
응암로 4
 
2.1%
북가좌동 3
 
1.5%
3층 3
 
1.5%
창천동 3
 
1.5%
증가로 3
 
1.5%
2층(연희동 3
 
1.5%
성산로 3
 
1.5%
Other values (134) 152
77.9%
2023-12-13T05:23:35.032311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155
 
14.7%
1 73
 
6.9%
2 56
 
5.3%
동 53
 
5.0%
연 45
 
4.3%
희 44
 
4.2%
로 41
 
3.9%
3 40
 
3.8%
4 36
 
3.4%
) 32
 
3.0%
Other values (98) 480
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 489
46.4%
Decimal Number 314
29.8%
Space Separator 155
 
14.7%
Close Punctuation 32
 
3.0%
Open Punctuation 32
 
3.0%
Dash Punctuation 29
 
2.7%
Uppercase Letter 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 53
 
10.8%
연 45
 
9.2%
희 44
 
9.0%
로 41
 
8.4%
호 30
 
6.1%
가 25
 
5.1%
층 20
 
4.1%
빌 16
 
3.3%
딩 15
 
3.1%
좌 13
 
2.7%
Other values (82) 187
38.2%
Decimal Number
ValueCountFrequency (%)
1 73
23.2%
2 56
17.8%
3 40
12.7%
4 36
11.5%
5 31
9.9%
0 29
 
9.2%
9 16
 
5.1%
8 12
 
3.8%
7 11
 
3.5%
6 10
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
75.0%
A 1
 
25.0%
Space Separator
ValueCountFrequency (%)
155
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 562
53.3%
Hangul 489
46.4%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 53
 
10.8%
연 45
 
9.2%
희 44
 
9.0%
로 41
 
8.4%
호 30
 
6.1%
가 25
 
5.1%
층 20
 
4.1%
빌 16
 
3.3%
딩 15
 
3.1%
좌 13
 
2.7%
Other values (82) 187
38.2%
Common
ValueCountFrequency (%)
155
27.6%
1 73
13.0%
2 56
 
10.0%
3 40
 
7.1%
4 36
 
6.4%
) 32
 
5.7%
( 32
 
5.7%
5 31
 
5.5%
- 29
 
5.2%
0 29
 
5.2%
Other values (4) 49
 
8.7%
Latin
ValueCountFrequency (%)
B 3
75.0%
A 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 566
53.6%
Hangul 489
46.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
27.4%
1 73
12.9%
2 56
 
9.9%
3 40
 
7.1%
4 36
 
6.4%
) 32
 
5.7%
( 32
 
5.7%
5 31
 
5.5%
- 29
 
5.1%
0 29
 
5.1%
Other values (6) 53
 
9.4%
Hangul
ValueCountFrequency (%)
동 53
 
10.8%
연 45
 
9.2%
희 44
 
9.0%
로 41
 
8.4%
호 30
 
6.1%
가 25
 
5.1%
층 20
 
4.1%
빌 16
 
3.3%
딩 15
 
3.1%
좌 13
 
2.7%
Other values (82) 187
38.2%

전화번호
Text

MISSING 

Distinct53
Distinct (%)98.1%
Missing5
Missing (%)8.5%
Memory size604.0 B
2023-12-13T05:23:35.288857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.296296
Min length11

Characters and Unicode

Total characters610
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)96.3%

Sample

1st row02-332-2728
2nd row02-324-3810
3rd row02-394-3301-2
4th row02-338-2651-2
5th row02-324-0270
ValueCountFrequency (%)
02-393-1136 2
 
3.7%
02-336-6952 1
 
1.9%
02-2245-9715 1
 
1.9%
02-2069-1193 1
 
1.9%
02-532-8328 1
 
1.9%
02-363-7337 1
 
1.9%
02-722-8619 1
 
1.9%
02-525-5248 1
 
1.9%
02-3144-2567 1
 
1.9%
02-326-2217 1
 
1.9%
Other values (43) 43
79.6%
2023-12-13T05:23:35.711458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 112
18.4%
- 111
18.2%
3 91
14.9%
0 79
13.0%
1 38
 
6.2%
5 36
 
5.9%
4 33
 
5.4%
7 32
 
5.2%
6 27
 
4.4%
8 26
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 499
81.8%
Dash Punctuation 111
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 112
22.4%
3 91
18.2%
0 79
15.8%
1 38
 
7.6%
5 36
 
7.2%
4 33
 
6.6%
7 32
 
6.4%
6 27
 
5.4%
8 26
 
5.2%
9 25
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 610
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 112
18.4%
- 111
18.2%
3 91
14.9%
0 79
13.0%
1 38
 
6.2%
5 36
 
5.9%
4 33
 
5.4%
7 32
 
5.2%
6 27
 
4.4%
8 26
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 112
18.4%
- 111
18.2%
3 91
14.9%
0 79
13.0%
1 38
 
6.2%
5 36
 
5.9%
4 33
 
5.4%
7 32
 
5.2%
6 27
 
4.4%
8 26
 
4.3%

대표자
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-13T05:23:36.037075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.1355932
Min length3

Characters and Unicode

Total characters185
Distinct characters82
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)100.0%

Sample

1st row권오주
2nd row김재구
3rd row김봉호
4th row박양춘
5th row이희철
ValueCountFrequency (%)
권오주 1
 
1.6%
문광현 1
 
1.6%
김의수 1
 
1.6%
김용진 1
 
1.6%
김종대 1
 
1.6%
김한석 1
 
1.6%
노영자 1
 
1.6%
김성종 1
 
1.6%
김승욱 1
 
1.6%
이용환 1
 
1.6%
Other values (51) 51
83.6%
2023-12-13T05:23:36.572473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 17
 
9.2%
영 8
 
4.3%
이 8
 
4.3%
재 6
 
3.2%
박 5
 
2.7%
윤 5
 
2.7%
종 4
 
2.2%
기 4
 
2.2%
동 3
 
1.6%
우 3
 
1.6%
Other values (72) 122
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 183
98.9%
Space Separator 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 17
 
9.3%
영 8
 
4.4%
이 8
 
4.4%
재 6
 
3.3%
박 5
 
2.7%
윤 5
 
2.7%
종 4
 
2.2%
기 4
 
2.2%
동 3
 
1.6%
우 3
 
1.6%
Other values (71) 120
65.6%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 183
98.9%
Common 2
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 17
 
9.3%
영 8
 
4.4%
이 8
 
4.4%
재 6
 
3.3%
박 5
 
2.7%
윤 5
 
2.7%
종 4
 
2.2%
기 4
 
2.2%
동 3
 
1.6%
우 3
 
1.6%
Other values (71) 120
65.6%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 183
98.9%
ASCII 2
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 17
 
9.3%
영 8
 
4.4%
이 8
 
4.4%
재 6
 
3.3%
박 5
 
2.7%
윤 5
 
2.7%
종 4
 
2.2%
기 4
 
2.2%
동 3
 
1.6%
우 3
 
1.6%
Other values (71) 120
65.6%
ASCII
ValueCountFrequency (%)
2
100.0%

Interactions

2023-12-13T05:23:31.516585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:23:36.740649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번신고번호신고일구분사무소명사무소주소전화번호대표자
연번1.0001.0000.0000.9981.0000.9370.9471.000
신고번호1.0001.0001.0001.0001.0001.0001.0001.000
신고일0.0001.0001.0000.0001.0000.9880.9931.000
구분0.9981.0000.0001.0001.0001.0001.0001.000
사무소명1.0001.0001.0001.0001.0001.0001.0001.000
사무소주소0.9371.0000.9881.0001.0001.0000.9901.000
전화번호0.9471.0000.9931.0001.0000.9901.0001.000
대표자1.0001.0001.0001.0001.0001.0001.0001.000
2023-12-13T05:23:36.896692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분
연번1.0000.891
구분0.8911.000

Missing values

2023-12-13T05:23:31.645058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:23:31.760007image/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.
2023-12-13T05:23:31.892320image/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

연번신고번호신고일구분사무소명사무소주소전화번호대표자
011998-서대문구-건축사사무소-71998-01-13개인국제건축사사무소연희로 245(연희동 아취빌딩)02-332-2728권오주
121985-서대문구-건축사사무소-81985-07-01개인유전건축사사무소연희로 245(연희동 아취빌딩)02-324-3810김재구
231987-서대문구-건축사사무소-291987-12-03개인건축사사무소서은연희로 263(홍은동 봉산빌딩)02-394-3301-2김봉호
341990-서대문구-건축사사무소-411990-01-15개인박양춘건축사사무소연희로36길 10(연희동)02-338-2651-2박양춘
451993-서대문구-건축사사무소-471993-10-25개인건축사사무소송인연희로26길 14 2층(연희동 경보빌딩)02-324-0270이희철
561994-서대문구-건축사사무소-571994-08-20개인신세계건축사사무소연희로11가길 2(연희동)02-3143-0583이윤기
671995-서대문구-건축사사무소-651995-10-11개인종합건축사사무소신원건축연희로8길 5-12 101호(연희동 아이비하우스)02-338-5552권상운
781996-서대문구-건축사사무소-721996-09-06개인인우 건축사사무소응암로 115 4층(북가좌동)02-374-8343이문재
891998-서대문구-건축사사무소-831998-11-06개인대상건축사사무소연희동 169-402-332-5882조진호
9101999-서대문구-건축사사무소-871999-03-11개인아너스티종합건축사사무소연희로36길 10 2층(연희동)02-334-1252이광영
연번신고번호신고일구분사무소명사무소주소전화번호대표자
49502013-서대문구-건축사사무소-176<NA>법인연이종합건축사사무소㈜ 김종기연희로 241 1층(연희동)02-581-6871김종기
50512014-서대문구-건축사사무소-181<NA>법인㈜건축사사무소원오원아키텍스성산로 559(대신동)02-739-6363황선영
51522015-서대문구-건축사사무소-185<NA>법인㈜산성건축사사무소응암로 115 4층(북가좌동 333-2호)02-322-7425정재학
52532015-서대문구-건축사사무소-189<NA>법인㈜김영섭 건축문화 건축사사무소연희로32길 48 상가동 206호(연희동)02-737-3842김영섭
53542016-서대문구-건축사사무소-190<NA>법인㈜건축사사무소 건축농장연희로11나길 5 302호(연희동)<NA>조선애
54552016-서대문구-건축사사무소-191<NA>법인㈜종합건축사사무소 수내충정로11길 29 202호02-6387-8339신청수
55562016-서대문구-건축사사무소-192<NA>법인㈜맥이앤씨건축사사무소모래내로15길 34 지하층(남가좌동)02-573-2928서동혁
56572016-서대문구-건축사사무소-193<NA>법인지엔건축사사무소㈜가재울로 25 2층(남가좌동)02-303-5405엄태성
57582017-서대문구-건축사사무소-196<NA>법인㈜이노플랜종합건축사사무소거북골로18길 41 B01호(북가좌동 디엠씨이노빌)02-306-8190김영택
58592017-서대문구-건축사사무소-197<NA>법인㈜재인건축사사무소이화여대5길 15 2-2호(대현동)<NA>김성식