Overview

Dataset statistics

Number of variables5
Number of observations505
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.3 KiB
Average record size in memory41.3 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description인천광역시 내에 영업 중인 건축사사무소 현황에 대한 데이터로 건축사사무소명, 건축사사무소 주소, 대표자명을 제공합니다.
URLhttps://www.data.go.kr/data/15030048/fileData.do

Alerts

연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:09:01.364374
Analysis finished2023-12-12 15:09:01.993585
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct505
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean253
Minimum1
Maximum505
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-13T00:09:02.058638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile26.2
Q1127
median253
Q3379
95-th percentile479.8
Maximum505
Range504
Interquartile range (IQR)252

Descriptive statistics

Standard deviation145.92521
Coefficient of variation (CV)0.57677948
Kurtosis-1.2
Mean253
Median Absolute Deviation (MAD)126
Skewness0
Sum127765
Variance21294.167
MonotonicityStrictly increasing
2023-12-13T00:09:02.191891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
333 1
 
0.2%
346 1
 
0.2%
345 1
 
0.2%
344 1
 
0.2%
343 1
 
0.2%
342 1
 
0.2%
341 1
 
0.2%
340 1
 
0.2%
339 1
 
0.2%
Other values (495) 495
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
505 1
0.2%
504 1
0.2%
503 1
0.2%
502 1
0.2%
501 1
0.2%
500 1
0.2%
499 1
0.2%
498 1
0.2%
497 1
0.2%
496 1
0.2%

신고구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
개인
380 
법인
125 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 380
75.2%
법인 125
 
24.8%

Length

2023-12-13T00:09:02.300885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:09:02.386348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 380
75.2%
법인 125
 
24.8%

사무소명
Text

Distinct487
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T00:09:02.586261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length10.051485
Min length2

Characters and Unicode

Total characters5076
Distinct characters270
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

Unique471 ?
Unique (%)93.3%

Sample

1st row광장건축사사무소
2nd row신화건축사사무소(주)
3rd row건축사사무소낙원
4th row남구건축사사무소
5th row건축사사무소예지
ValueCountFrequency (%)
건축사사무소 108
 
15.9%
주식회사 33
 
4.9%
종합건축사사무소 6
 
0.9%
사무소 6
 
0.9%
주)건축사사무소 5
 
0.7%
건축사 5
 
0.7%
주)삼희건축사사무소 3
 
0.4%
주)비타그룹 3
 
0.4%
삼익건축사사무소 2
 
0.3%
그룹아키존건축사사무소 2
 
0.3%
Other values (489) 505
74.5%
2023-12-13T00:09:03.279197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 1044
20.6%
건 515
 
10.1%
소 509
 
10.0%
축 509
 
10.0%
무 507
 
10.0%
181
 
3.6%
주 129
 
2.5%
( 89
 
1.8%
) 89
 
1.8%
이 74
 
1.5%
Other values (260) 1430
28.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4642
91.4%
Space Separator 181
 
3.6%
Open Punctuation 89
 
1.8%
Close Punctuation 89
 
1.8%
Uppercase Letter 54
 
1.1%
Decimal Number 11
 
0.2%
Lowercase Letter 7
 
0.1%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1044
22.5%
건 515
11.1%
소 509
11.0%
축 509
11.0%
무 507
10.9%
주 129
 
2.8%
이 74
 
1.6%
에 52
 
1.1%
합 52
 
1.1%
종 52
 
1.1%
Other values (229) 1199
25.8%
Uppercase Letter
ValueCountFrequency (%)
A 10
18.5%
S 9
16.7%
C 7
13.0%
M 6
11.1%
T 5
9.3%
N 4
 
7.4%
P 3
 
5.6%
E 2
 
3.7%
I 2
 
3.7%
G 1
 
1.9%
Other values (5) 5
9.3%
Lowercase Letter
ValueCountFrequency (%)
i 2
28.6%
u 1
14.3%
d 1
14.3%
t 1
14.3%
s 1
14.3%
o 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 4
36.4%
1 3
27.3%
0 2
18.2%
7 1
 
9.1%
3 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
· 1
33.3%
Space Separator
ValueCountFrequency (%)
181
100.0%
Open Punctuation
ValueCountFrequency (%)
( 89
100.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4642
91.4%
Common 373
 
7.3%
Latin 61
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1044
22.5%
건 515
11.1%
소 509
11.0%
축 509
11.0%
무 507
10.9%
주 129
 
2.8%
이 74
 
1.6%
에 52
 
1.1%
합 52
 
1.1%
종 52
 
1.1%
Other values (229) 1199
25.8%
Latin
ValueCountFrequency (%)
A 10
16.4%
S 9
14.8%
C 7
11.5%
M 6
9.8%
T 5
8.2%
N 4
 
6.6%
P 3
 
4.9%
E 2
 
3.3%
I 2
 
3.3%
i 2
 
3.3%
Other values (11) 11
18.0%
Common
ValueCountFrequency (%)
181
48.5%
( 89
23.9%
) 89
23.9%
2 4
 
1.1%
1 3
 
0.8%
0 2
 
0.5%
. 2
 
0.5%
7 1
 
0.3%
3 1
 
0.3%
· 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4642
91.4%
ASCII 433
 
8.5%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 1044
22.5%
건 515
11.1%
소 509
11.0%
축 509
11.0%
무 507
10.9%
주 129
 
2.8%
이 74
 
1.6%
에 52
 
1.1%
합 52
 
1.1%
종 52
 
1.1%
Other values (229) 1199
25.8%
ASCII
ValueCountFrequency (%)
181
41.8%
( 89
20.6%
) 89
20.6%
A 10
 
2.3%
S 9
 
2.1%
C 7
 
1.6%
M 6
 
1.4%
T 5
 
1.2%
N 4
 
0.9%
2 4
 
0.9%
Other values (20) 29
 
6.7%
None
ValueCountFrequency (%)
· 1
100.0%

도로명주소
Text

Distinct468
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T00:09:03.641979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length41
Mean length29.948515
Min length1

Characters and Unicode

Total characters15124
Distinct characters316
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique435 ?
Unique (%)86.1%

Sample

1st row인천광역시 계양구 경명대로 1075
2nd row인천광역시 남동구 인주대로 838, 3층
3rd row인천광역시 남동구 인주대로 846, 4층 나호
4th row인천광역시 남구 독정이로 94
5th row인천광역시 계양구 주부토로472번길 30-1 (작전동)
ValueCountFrequency (%)
인천광역시 502
 
17.6%
남동구 146
 
5.1%
서구 75
 
2.6%
부평구 75
 
2.6%
연수구 60
 
2.1%
2층 45
 
1.6%
계양구 36
 
1.3%
3층 36
 
1.3%
미추홀구 32
 
1.1%
남구 26
 
0.9%
Other values (906) 1813
63.7%
2023-12-13T00:09:04.102114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2355
 
15.6%
인 564
 
3.7%
1 544
 
3.6%
구 538
 
3.6%
, 535
 
3.5%
시 518
 
3.4%
천 516
 
3.4%
광 507
 
3.4%
역 504
 
3.3%
로 503
 
3.3%
Other values (306) 8040
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8747
57.8%
Decimal Number 3012
 
19.9%
Space Separator 2355
 
15.6%
Other Punctuation 536
 
3.5%
Open Punctuation 144
 
1.0%
Close Punctuation 144
 
1.0%
Dash Punctuation 117
 
0.8%
Uppercase Letter 69
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 564
 
6.4%
구 538
 
6.2%
시 518
 
5.9%
천 516
 
5.9%
광 507
 
5.8%
역 504
 
5.8%
로 503
 
5.8%
동 363
 
4.1%
호 326
 
3.7%
남 206
 
2.4%
Other values (276) 4202
48.0%
Uppercase Letter
ValueCountFrequency (%)
B 20
29.0%
T 12
17.4%
C 11
15.9%
A 10
14.5%
I 4
 
5.8%
M 3
 
4.3%
F 2
 
2.9%
U 1
 
1.4%
R 1
 
1.4%
P 1
 
1.4%
Other values (4) 4
 
5.8%
Decimal Number
ValueCountFrequency (%)
1 544
18.1%
0 442
14.7%
2 437
14.5%
3 385
12.8%
5 257
8.5%
4 255
8.5%
6 197
 
6.5%
9 177
 
5.9%
7 166
 
5.5%
8 152
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 535
99.8%
& 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2355
100.0%
Open Punctuation
ValueCountFrequency (%)
( 144
100.0%
Close Punctuation
ValueCountFrequency (%)
) 144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 117
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8746
57.8%
Common 6308
41.7%
Latin 69
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 564
 
6.4%
구 538
 
6.2%
시 518
 
5.9%
천 516
 
5.9%
광 507
 
5.8%
역 504
 
5.8%
로 503
 
5.8%
동 363
 
4.2%
호 326
 
3.7%
남 206
 
2.4%
Other values (275) 4201
48.0%
Common
ValueCountFrequency (%)
2355
37.3%
1 544
 
8.6%
, 535
 
8.5%
0 442
 
7.0%
2 437
 
6.9%
3 385
 
6.1%
5 257
 
4.1%
4 255
 
4.0%
6 197
 
3.1%
9 177
 
2.8%
Other values (6) 724
 
11.5%
Latin
ValueCountFrequency (%)
B 20
29.0%
T 12
17.4%
C 11
15.9%
A 10
14.5%
I 4
 
5.8%
M 3
 
4.3%
F 2
 
2.9%
U 1
 
1.4%
R 1
 
1.4%
P 1
 
1.4%
Other values (4) 4
 
5.8%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8746
57.8%
ASCII 6377
42.2%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2355
36.9%
1 544
 
8.5%
, 535
 
8.4%
0 442
 
6.9%
2 437
 
6.9%
3 385
 
6.0%
5 257
 
4.0%
4 255
 
4.0%
6 197
 
3.1%
9 177
 
2.8%
Other values (20) 793
 
12.4%
Hangul
ValueCountFrequency (%)
인 564
 
6.4%
구 538
 
6.2%
시 518
 
5.9%
천 516
 
5.9%
광 507
 
5.8%
역 504
 
5.8%
로 503
 
5.8%
동 363
 
4.2%
호 326
 
3.7%
남 206
 
2.4%
Other values (275) 4201
48.0%
CJK
ValueCountFrequency (%)
內 1
100.0%

신고건축사
Text

Distinct497
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-13T00:09:04.412408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9940594
Min length2

Characters and Unicode

Total characters1512
Distinct characters164
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique489 ?
Unique (%)96.8%

Sample

1st row김장균
2nd row김봉섭
3rd row이익수
4th row이광남
5th row박순종
ValueCountFrequency (%)
김영민 2
 
0.4%
한기용 2
 
0.4%
이영철 2
 
0.4%
노태현 2
 
0.4%
김종래 2
 
0.4%
김학성 2
 
0.4%
김경진 2
 
0.4%
김동근 2
 
0.4%
최기철 1
 
0.2%
정아 1
 
0.2%
Other values (487) 487
96.4%
2023-12-13T00:09:04.841295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 96
 
6.3%
이 69
 
4.6%
정 48
 
3.2%
영 44
 
2.9%
성 40
 
2.6%
진 35
 
2.3%
박 34
 
2.2%
호 33
 
2.2%
최 28
 
1.9%
용 27
 
1.8%
Other values (154) 1058
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1512
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 96
 
6.3%
이 69
 
4.6%
정 48
 
3.2%
영 44
 
2.9%
성 40
 
2.6%
진 35
 
2.3%
박 34
 
2.2%
호 33
 
2.2%
최 28
 
1.9%
용 27
 
1.8%
Other values (154) 1058
70.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1512
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 96
 
6.3%
이 69
 
4.6%
정 48
 
3.2%
영 44
 
2.9%
성 40
 
2.6%
진 35
 
2.3%
박 34
 
2.2%
호 33
 
2.2%
최 28
 
1.9%
용 27
 
1.8%
Other values (154) 1058
70.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1512
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 96
 
6.3%
이 69
 
4.6%
정 48
 
3.2%
영 44
 
2.9%
성 40
 
2.6%
진 35
 
2.3%
박 34
 
2.2%
호 33
 
2.2%
최 28
 
1.9%
용 27
 
1.8%
Other values (154) 1058
70.0%

Interactions

2023-12-13T00:09:01.754326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:09:04.924972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번신고구분
연번1.0000.164
신고구분0.1641.000
2023-12-13T00:09:04.993181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번신고구분
연번1.0000.125
신고구분0.1251.000

Missing values

2023-12-13T00:09:01.862860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:09:01.958479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번신고구분사무소명도로명주소신고건축사
01개인광장건축사사무소인천광역시 계양구 경명대로 1075김장균
12법인신화건축사사무소(주)인천광역시 남동구 인주대로 838, 3층김봉섭
23개인건축사사무소낙원인천광역시 남동구 인주대로 846, 4층 나호이익수
34개인남구건축사사무소인천광역시 남구 독정이로 94이광남
45개인건축사사무소예지인천광역시 계양구 주부토로472번길 30-1 (작전동)박순종
56개인유성건축사사무소인천광역시 계양구 주부토로472번길 30-1유복성
67개인양명건축사사무소인천광역시 남동구 인주대로 846, 4층 나호홍양기
78개인남도건축사사무소인천광역시 남동구 하촌로60번길 3김상욱
89개인동산건축사사무소인천광역시 부평구 열우물로 271-1김정환
910법인(주)티씨엠씨건축사사무소인천광역시 남동구 문화로 141김태영
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