Overview

Dataset statistics

Number of variables5
Number of observations256
Missing cells74
Missing cells (%)5.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.4 KiB
Average record size in memory41.5 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description서울특별시 성동구 내 건축사사무소 현황 정보 입니다. 사무소명, 도로명주소, 전화번호, 신고구분 등의 정보를 포함합니다.
Author서울특별시 성동구
URLhttps://www.data.go.kr/data/15034770/fileData.do

Alerts

전화번호 has 74 (28.9%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-14 13:49:36.518361
Analysis finished2024-01-14 13:49:37.094508
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct256
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.5
Minimum1
Maximum256
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-01-14T22:49:37.213453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.75
Q164.75
median128.5
Q3192.25
95-th percentile243.25
Maximum256
Range255
Interquartile range (IQR)127.5

Descriptive statistics

Standard deviation74.045031
Coefficient of variation (CV)0.57622592
Kurtosis-1.2
Mean128.5
Median Absolute Deviation (MAD)64
Skewness0
Sum32896
Variance5482.6667
MonotonicityStrictly increasing
2024-01-14T22:49:37.430430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
130 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
Other values (246) 246
96.1%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
256 1
0.4%
255 1
0.4%
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%
249 1
0.4%
248 1
0.4%
247 1
0.4%

사무소명
Text

Distinct255
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-01-14T22:49:37.732273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length18
Mean length12.304688
Min length7

Characters and Unicode

Total characters3150
Distinct characters250
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

Unique254 ?
Unique (%)99.2%

Sample

1st row(주)건축사사무소 아르키움
2nd row아이비전 건축사사무소
3rd row예토종합건축사사무소
4th row주성건축사사무소
5th row미루건축사사무소
ValueCountFrequency (%)
건축사사무소 79
 
19.3%
주식회사 41
 
10.0%
주)건축사사무소 5
 
1.2%
주 5
 
1.2%
종합건축사사무소 3
 
0.7%
주)종합건축사사무소 3
 
0.7%
사무소 3
 
0.7%
탑도시건축사사무소 2
 
0.5%
건축사 2
 
0.5%
주)공선건축사사무소 1
 
0.2%
Other values (265) 265
64.8%
2024-01-14T22:49:38.201345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 559
17.7%
건 273
 
8.7%
축 272
 
8.6%
소 258
 
8.2%
무 257
 
8.2%
159
 
5.0%
주 129
 
4.1%
( 82
 
2.6%
) 82
 
2.6%
이 72
 
2.3%
Other values (240) 1007
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2774
88.1%
Space Separator 159
 
5.0%
Open Punctuation 83
 
2.6%
Close Punctuation 83
 
2.6%
Uppercase Letter 40
 
1.3%
Decimal Number 5
 
0.2%
Other Punctuation 3
 
0.1%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 559
20.2%
건 273
 
9.8%
축 272
 
9.8%
소 258
 
9.3%
무 257
 
9.3%
주 129
 
4.7%
이 72
 
2.6%
회 47
 
1.7%
식 46
 
1.7%
스 45
 
1.6%
Other values (208) 816
29.4%
Uppercase Letter
ValueCountFrequency (%)
A 7
17.5%
S 5
12.5%
K 3
 
7.5%
I 3
 
7.5%
O 3
 
7.5%
C 3
 
7.5%
M 2
 
5.0%
T 2
 
5.0%
F 2
 
5.0%
H 2
 
5.0%
Other values (8) 8
20.0%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
2 1
20.0%
0 1
20.0%
7 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
33.3%
a 1
33.3%
l 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 82
98.8%
[ 1
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 82
98.8%
] 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
159
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2773
88.0%
Common 333
 
10.6%
Latin 43
 
1.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 559
20.2%
건 273
 
9.8%
축 272
 
9.8%
소 258
 
9.3%
무 257
 
9.3%
주 129
 
4.7%
이 72
 
2.6%
회 47
 
1.7%
식 46
 
1.7%
스 45
 
1.6%
Other values (207) 815
29.4%
Latin
ValueCountFrequency (%)
A 7
16.3%
S 5
11.6%
K 3
 
7.0%
I 3
 
7.0%
O 3
 
7.0%
C 3
 
7.0%
M 2
 
4.7%
T 2
 
4.7%
F 2
 
4.7%
H 2
 
4.7%
Other values (11) 11
25.6%
Common
ValueCountFrequency (%)
159
47.7%
( 82
24.6%
) 82
24.6%
1 2
 
0.6%
& 2
 
0.6%
2 1
 
0.3%
0 1
 
0.3%
7 1
 
0.3%
] 1
 
0.3%
[ 1
 
0.3%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2773
88.0%
ASCII 376
 
11.9%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 559
20.2%
건 273
 
9.8%
축 272
 
9.8%
소 258
 
9.3%
무 257
 
9.3%
주 129
 
4.7%
이 72
 
2.6%
회 47
 
1.7%
식 46
 
1.7%
스 45
 
1.6%
Other values (207) 815
29.4%
ASCII
ValueCountFrequency (%)
159
42.3%
( 82
21.8%
) 82
21.8%
A 7
 
1.9%
S 5
 
1.3%
K 3
 
0.8%
I 3
 
0.8%
O 3
 
0.8%
C 3
 
0.8%
M 2
 
0.5%
Other values (22) 27
 
7.2%
CJK
ValueCountFrequency (%)
家 1
100.0%

사무소도로명주소
Text

Distinct243
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-01-14T22:49:38.541944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length41.5
Mean length31.105469
Min length17

Characters and Unicode

Total characters7963
Distinct characters216
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique231 ?
Unique (%)90.2%

Sample

1st row서울특별시 성동구 상원12길 21, 6층
2nd row서울특별시 성동구 고산자로 269, 1506호 (도선동, 신한넥스텔)
3rd row서울특별시 성동구 고산자로 269, 신한넥스텔 304호
4th row서울특별시 성동구 고산자로 269, 신한넥스텔 1214호
5th row서울특별시 성동구 고산자로 269, 신한넥스텔 311호
ValueCountFrequency (%)
서울특별시 256
 
17.0%
성동구 256
 
17.0%
아차산로 27
 
1.8%
성수일로 19
 
1.3%
2층 19
 
1.3%
48 19
 
1.3%
아차산로17길 17
 
1.1%
25 15
 
1.0%
3층 15
 
1.0%
왕십리로 15
 
1.0%
Other values (447) 849
56.3%
2024-01-14T22:49:39.087931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1255
 
15.8%
1 434
 
5.5%
성 365
 
4.6%
동 328
 
4.1%
, 300
 
3.8%
서 296
 
3.7%
울 295
 
3.7%
시 262
 
3.3%
특 256
 
3.2%
별 256
 
3.2%
Other values (206) 3916
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4556
57.2%
Decimal Number 1677
 
21.1%
Space Separator 1255
 
15.8%
Other Punctuation 303
 
3.8%
Open Punctuation 48
 
0.6%
Close Punctuation 48
 
0.6%
Uppercase Letter 42
 
0.5%
Dash Punctuation 27
 
0.3%
Lowercase Letter 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 365
 
8.0%
동 328
 
7.2%
서 296
 
6.5%
울 295
 
6.5%
시 262
 
5.8%
특 256
 
5.6%
별 256
 
5.6%
구 256
 
5.6%
호 210
 
4.6%
로 197
 
4.3%
Other values (167) 1835
40.3%
Uppercase Letter
ValueCountFrequency (%)
A 7
16.7%
K 6
14.3%
T 5
11.9%
S 4
9.5%
I 4
9.5%
B 3
7.1%
V 2
 
4.8%
R 2
 
4.8%
M 2
 
4.8%
C 1
 
2.4%
Other values (6) 6
14.3%
Decimal Number
ValueCountFrequency (%)
1 434
25.9%
2 232
13.8%
0 225
13.4%
3 154
 
9.2%
4 146
 
8.7%
5 140
 
8.3%
8 101
 
6.0%
6 97
 
5.8%
7 82
 
4.9%
9 66
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
t 2
28.6%
v 1
14.3%
c 1
14.3%
i 1
14.3%
s 1
14.3%
k 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 300
99.0%
. 2
 
0.7%
· 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1255
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4556
57.2%
Common 3358
42.2%
Latin 49
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 365
 
8.0%
동 328
 
7.2%
서 296
 
6.5%
울 295
 
6.5%
시 262
 
5.8%
특 256
 
5.6%
별 256
 
5.6%
구 256
 
5.6%
호 210
 
4.6%
로 197
 
4.3%
Other values (167) 1835
40.3%
Latin
ValueCountFrequency (%)
A 7
14.3%
K 6
12.2%
T 5
10.2%
S 4
 
8.2%
I 4
 
8.2%
B 3
 
6.1%
V 2
 
4.1%
t 2
 
4.1%
R 2
 
4.1%
M 2
 
4.1%
Other values (12) 12
24.5%
Common
ValueCountFrequency (%)
1255
37.4%
1 434
 
12.9%
, 300
 
8.9%
2 232
 
6.9%
0 225
 
6.7%
3 154
 
4.6%
4 146
 
4.3%
5 140
 
4.2%
8 101
 
3.0%
6 97
 
2.9%
Other values (7) 274
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4556
57.2%
ASCII 3406
42.8%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1255
36.8%
1 434
 
12.7%
, 300
 
8.8%
2 232
 
6.8%
0 225
 
6.6%
3 154
 
4.5%
4 146
 
4.3%
5 140
 
4.1%
8 101
 
3.0%
6 97
 
2.8%
Other values (28) 322
 
9.5%
Hangul
ValueCountFrequency (%)
성 365
 
8.0%
동 328
 
7.2%
서 296
 
6.5%
울 295
 
6.5%
시 262
 
5.8%
특 256
 
5.6%
별 256
 
5.6%
구 256
 
5.6%
호 210
 
4.6%
로 197
 
4.3%
Other values (167) 1835
40.3%
None
ValueCountFrequency (%)
· 1
100.0%

전화번호
Text

MISSING 

Distinct174
Distinct (%)95.6%
Missing74
Missing (%)28.9%
Memory size2.1 KiB
2024-01-14T22:49:39.506373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11.631868
Min length11

Characters and Unicode

Total characters2117
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique167 ?
Unique (%)91.8%

Sample

1st row02-2214-9852
2nd row02-2281-0909
3rd row02-2297-9633
4th row02-2291-4250
5th row02-2282-0616
ValueCountFrequency (%)
02-3444-2515 3
 
1.6%
02-540-0104 2
 
1.1%
02-512-8336 2
 
1.1%
02-334-3218 2
 
1.1%
02-512-1621 2
 
1.1%
02-2282-0616 2
 
1.1%
02-566-8170 2
 
1.1%
02-6954-1307 1
 
0.5%
02-553-8170 1
 
0.5%
02-6462-9006 1
 
0.5%
Other values (165) 165
90.2%
2024-01-14T22:49:40.075531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 363
17.1%
0 355
16.8%
2 327
15.4%
4 178
8.4%
1 164
7.7%
5 150
7.1%
6 138
 
6.5%
7 118
 
5.6%
9 110
 
5.2%
3 108
 
5.1%
Other values (2) 106
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1753
82.8%
Dash Punctuation 363
 
17.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 355
20.3%
2 327
18.7%
4 178
10.2%
1 164
9.4%
5 150
8.6%
6 138
 
7.9%
7 118
 
6.7%
9 110
 
6.3%
3 108
 
6.2%
8 105
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 363
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2117
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 363
17.1%
0 355
16.8%
2 327
15.4%
4 178
8.4%
1 164
7.7%
5 150
7.1%
6 138
 
6.5%
7 118
 
5.6%
9 110
 
5.2%
3 108
 
5.1%
Other values (2) 106
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2117
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 363
17.1%
0 355
16.8%
2 327
15.4%
4 178
8.4%
1 164
7.7%
5 150
7.1%
6 138
 
6.5%
7 118
 
5.6%
9 110
 
5.2%
3 108
 
5.1%
Other values (2) 106
 
5.0%

신고구분
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
법인
128 
개인
128 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
법인 128
50.0%
개인 128
50.0%

Length

2024-01-14T22:49:40.274658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T22:49:40.413627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 128
50.0%
개인 128
50.0%

Interactions

2024-01-14T22:49:36.834444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-14T22:49:40.496005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번신고구분
연번1.0000.125
신고구분0.1251.000
2024-01-14T22:49:40.609880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번신고구분
연번1.0000.109
신고구분0.1091.000

Missing values

2024-01-14T22:49:36.946107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-14T22:49:37.042102image/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

연번사무소명사무소도로명주소전화번호신고구분
01(주)건축사사무소 아르키움서울특별시 성동구 상원12길 21, 6층02-2214-9852법인
12아이비전 건축사사무소서울특별시 성동구 고산자로 269, 1506호 (도선동, 신한넥스텔)02-2281-0909개인
23예토종합건축사사무소서울특별시 성동구 고산자로 269, 신한넥스텔 304호02-2297-9633개인
34주성건축사사무소서울특별시 성동구 고산자로 269, 신한넥스텔 1214호02-2291-4250개인
45미루건축사사무소서울특별시 성동구 고산자로 269, 신한넥스텔 311호02-2282-0616개인
56(주)태두종합건축사사무소서울특별시 성동구 아차산로15길 52, 삼환디지털벤처타워 605호02-2024-0144법인
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