Overview

Dataset statistics

Number of variables4
Number of observations359
Missing cells2
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory33.4 B

Variable types

Categorical1
Text2
Numeric1

Dataset

Description서울특별시 중구 관내 다중이용시설 실내공기질 관리대상 자료로, 2024.2.27.기준으로 작성되었습니다.
Author서울특별시 중구
URLhttps://www.data.go.kr/data/15112386/fileData.do

Reproduction

Analysis started2024-03-14 11:16:26.438208
Analysis finished2024-03-14 11:16:27.664699
Duration1.23 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설군
Categorical

Distinct17
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
실내주차장
205 
대규모점포
48 
어린이집
27 
지하역사
23 
지하도상가
 
13
Other values (12)
43 

Length

Max length9
Median length5
Mean length4.7604457
Min length2

Unique

Unique5 ?
Unique (%)1.4%

Sample

1st rowPC영업시설
2nd rowPC영업시설
3rd rowPC영업시설
4th rowPC영업시설
5th row노인요양시설

Common Values

ValueCountFrequency (%)
실내주차장 205
57.1%
대규모점포 48
 
13.4%
어린이집 27
 
7.5%
지하역사 23
 
6.4%
지하도상가 13
 
3.6%
의료기관 10
 
2.8%
영화상영관 8
 
2.2%
목욕장 7
 
1.9%
박물관 5
 
1.4%
PC영업시설 4
 
1.1%
Other values (7) 9
 
2.5%

Length

2024-03-14T20:16:27.815689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
실내주차장 205
57.1%
대규모점포 48
 
13.4%
어린이집 27
 
7.5%
지하역사 23
 
6.4%
지하도상가 13
 
3.6%
의료기관 10
 
2.8%
영화상영관 8
 
2.2%
목욕장 7
 
1.9%
박물관 5
 
1.4%
pc영업시설 4
 
1.1%
Other values (7) 9
 
2.5%

시설명
Text

Distinct350
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-03-14T20:16:28.491166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length23
Mean length8.3844011
Min length2

Characters and Unicode

Total characters3010
Distinct characters368
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique341 ?
Unique (%)95.0%

Sample

1st row1프로 pc 아레나
2nd rowE-SPOrtS Arena
3rd rowGEEK STAR PC CAFE (긱스타 피시 카페)
4th row커몬 피씨 플렉스
5th row구립중구노인요양센터
ValueCountFrequency (%)
지하도상가 5
 
1.1%
신세계백화점 4
 
0.9%
지하상가 4
 
0.9%
주차장 4
 
0.9%
동대문 3
 
0.6%
굿모닝시티 3
 
0.6%
공영주차장 3
 
0.6%
명동 3
 
0.6%
apm 3
 
0.6%
회현 2
 
0.4%
Other values (413) 433
92.7%
2024-03-14T20:16:29.487411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 119
 
4.0%
주 112
 
3.7%
110
 
3.7%
차 103
 
3.4%
이 68
 
2.3%
동 54
 
1.8%
스 51
 
1.7%
빌 48
 
1.6%
딩 46
 
1.5%
타 45
 
1.5%
Other values (358) 2254
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2635
87.5%
Space Separator 110
 
3.7%
Uppercase Letter 106
 
3.5%
Lowercase Letter 50
 
1.7%
Close Punctuation 28
 
0.9%
Open Punctuation 28
 
0.9%
Decimal Number 19
 
0.6%
Other Number 18
 
0.6%
Other Symbol 12
 
0.4%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 119
 
4.5%
주 112
 
4.3%
차 103
 
3.9%
이 68
 
2.6%
동 54
 
2.0%
스 51
 
1.9%
빌 48
 
1.8%
딩 46
 
1.7%
타 45
 
1.7%
어 40
 
1.5%
Other values (298) 1949
74.0%
Uppercase Letter
ValueCountFrequency (%)
C 13
12.3%
A 11
10.4%
K 8
 
7.5%
S 8
 
7.5%
P 8
 
7.5%
G 8
 
7.5%
E 7
 
6.6%
D 6
 
5.7%
B 5
 
4.7%
I 5
 
4.7%
Other values (11) 27
25.5%
Lowercase Letter
ValueCountFrequency (%)
s 6
12.0%
e 6
12.0%
t 5
 
10.0%
o 5
 
10.0%
l 3
 
6.0%
r 3
 
6.0%
n 3
 
6.0%
c 2
 
4.0%
h 2
 
4.0%
a 2
 
4.0%
Other values (9) 13
26.0%
Decimal Number
ValueCountFrequency (%)
2 6
31.6%
4 4
21.1%
3 4
21.1%
1 2
 
10.5%
5 2
 
10.5%
0 1
 
5.3%
Other Number
ValueCountFrequency (%)
② 5
27.8%
⑥ 3
16.7%
③ 3
16.7%
⑤ 3
16.7%
① 2
 
11.1%
④ 2
 
11.1%
Other Punctuation
ValueCountFrequency (%)
… 1
33.3%
& 1
33.3%
: 1
33.3%
Space Separator
ValueCountFrequency (%)
110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2647
87.9%
Common 207
 
6.9%
Latin 156
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 119
 
4.5%
주 112
 
4.2%
차 103
 
3.9%
이 68
 
2.6%
동 54
 
2.0%
스 51
 
1.9%
빌 48
 
1.8%
딩 46
 
1.7%
타 45
 
1.7%
어 40
 
1.5%
Other values (299) 1961
74.1%
Latin
ValueCountFrequency (%)
C 13
 
8.3%
A 11
 
7.1%
K 8
 
5.1%
S 8
 
5.1%
P 8
 
5.1%
G 8
 
5.1%
E 7
 
4.5%
s 6
 
3.8%
D 6
 
3.8%
e 6
 
3.8%
Other values (30) 75
48.1%
Common
ValueCountFrequency (%)
110
53.1%
) 28
 
13.5%
( 28
 
13.5%
2 6
 
2.9%
② 5
 
2.4%
4 4
 
1.9%
3 4
 
1.9%
⑥ 3
 
1.4%
③ 3
 
1.4%
⑤ 3
 
1.4%
Other values (9) 13
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2635
87.5%
ASCII 344
 
11.4%
Enclosed Alphanum 18
 
0.6%
None 12
 
0.4%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 119
 
4.5%
주 112
 
4.3%
차 103
 
3.9%
이 68
 
2.6%
동 54
 
2.0%
스 51
 
1.9%
빌 48
 
1.8%
딩 46
 
1.7%
타 45
 
1.7%
어 40
 
1.5%
Other values (298) 1949
74.0%
ASCII
ValueCountFrequency (%)
110
32.0%
) 28
 
8.1%
( 28
 
8.1%
C 13
 
3.8%
A 11
 
3.2%
K 8
 
2.3%
S 8
 
2.3%
P 8
 
2.3%
G 8
 
2.3%
E 7
 
2.0%
Other values (42) 115
33.4%
None
ValueCountFrequency (%)
㈜ 12
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
② 5
27.8%
⑥ 3
16.7%
③ 3
16.7%
⑤ 3
16.7%
① 2
 
11.1%
④ 2
 
11.1%
Punctuation
ValueCountFrequency (%)
… 1
100.0%

주소
Text

Distinct320
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-03-14T20:16:30.671947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length19.194986
Min length13

Characters and Unicode

Total characters6891
Distinct characters176
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique284 ?
Unique (%)79.1%

Sample

1st row서울특별시 중구 다산로 132, 우봉빌딩 3층 (신당동)
2nd row서울특별시 중구 서애로1길 11, 지하층 B201호 (충무로5가)
3rd row서울특별시 중구 퇴계로 216, 행복빌딩 지하층 (충무로4가)
4th row서울특별시 중구 동호로 180, 대승빌딩 지하1층 (신당동)
5th row서울특별시 중구 필동로 96
ValueCountFrequency (%)
중구 359
23.4%
서울특별시 356
23.2%
을지로 42
 
2.7%
퇴계로 29
 
1.9%
세종대로 19
 
1.2%
남대문로 18
 
1.2%
청계천로 17
 
1.1%
다산로 16
 
1.0%
장충단로 14
 
0.9%
소공로 12
 
0.8%
Other values (371) 652
42.5%
2024-03-14T20:16:32.144078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1204
17.5%
서 378
 
5.5%
로 376
 
5.5%
시 368
 
5.3%
구 363
 
5.3%
중 361
 
5.2%
울 360
 
5.2%
특 357
 
5.2%
별 356
 
5.2%
1 215
 
3.1%
Other values (166) 2553
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4398
63.8%
Space Separator 1204
 
17.5%
Decimal Number 1077
 
15.6%
Open Punctuation 70
 
1.0%
Close Punctuation 70
 
1.0%
Other Punctuation 41
 
0.6%
Uppercase Letter 18
 
0.3%
Dash Punctuation 8
 
0.1%
Lowercase Letter 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 378
 
8.6%
로 376
 
8.5%
시 368
 
8.4%
구 363
 
8.3%
중 361
 
8.2%
울 360
 
8.2%
특 357
 
8.1%
별 356
 
8.1%
지 120
 
2.7%
길 101
 
2.3%
Other values (133) 1258
28.6%
Uppercase Letter
ValueCountFrequency (%)
B 3
16.7%
D 3
16.7%
S 2
11.1%
T 2
11.1%
O 1
 
5.6%
W 1
 
5.6%
U 1
 
5.6%
C 1
 
5.6%
H 1
 
5.6%
L 1
 
5.6%
Other values (2) 2
11.1%
Decimal Number
ValueCountFrequency (%)
1 215
20.0%
2 167
15.5%
3 125
11.6%
0 101
9.4%
4 90
8.4%
5 87
8.1%
6 81
 
7.5%
7 78
 
7.2%
8 70
 
6.5%
9 63
 
5.8%
Lowercase Letter
ValueCountFrequency (%)
r 1
25.0%
w 1
25.0%
e 1
25.0%
o 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 40
97.6%
. 1
 
2.4%
Space Separator
ValueCountFrequency (%)
1204
100.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4398
63.8%
Common 2471
35.9%
Latin 22
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 378
 
8.6%
로 376
 
8.5%
시 368
 
8.4%
구 363
 
8.3%
중 361
 
8.2%
울 360
 
8.2%
특 357
 
8.1%
별 356
 
8.1%
지 120
 
2.7%
길 101
 
2.3%
Other values (133) 1258
28.6%
Common
ValueCountFrequency (%)
1204
48.7%
1 215
 
8.7%
2 167
 
6.8%
3 125
 
5.1%
0 101
 
4.1%
4 90
 
3.6%
5 87
 
3.5%
6 81
 
3.3%
7 78
 
3.2%
( 70
 
2.8%
Other values (7) 253
 
10.2%
Latin
ValueCountFrequency (%)
B 3
13.6%
D 3
13.6%
S 2
 
9.1%
T 2
 
9.1%
O 1
 
4.5%
r 1
 
4.5%
w 1
 
4.5%
W 1
 
4.5%
e 1
 
4.5%
o 1
 
4.5%
Other values (6) 6
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4398
63.8%
ASCII 2493
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1204
48.3%
1 215
 
8.6%
2 167
 
6.7%
3 125
 
5.0%
0 101
 
4.1%
4 90
 
3.6%
5 87
 
3.5%
6 81
 
3.2%
7 78
 
3.1%
( 70
 
2.8%
Other values (23) 275
 
11.0%
Hangul
ValueCountFrequency (%)
서 378
 
8.6%
로 376
 
8.5%
시 368
 
8.4%
구 363
 
8.3%
중 361
 
8.2%
울 360
 
8.2%
특 357
 
8.1%
별 356
 
8.1%
지 120
 
2.7%
길 101
 
2.3%
Other values (133) 1258
28.6%

연면적(제곱미터)
Real number (ℝ)

Distinct351
Distinct (%)98.3%
Missing2
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean10245.053
Minimum331
Maximum122917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-03-14T20:16:32.558615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum331
5-th percentile663
Q13060
median5893
Q311025
95-th percentile31259.2
Maximum122917
Range122586
Interquartile range (IQR)7965

Descriptive statistics

Standard deviation14646.57
Coefficient of variation (CV)1.4296236
Kurtosis24.520301
Mean10245.053
Median Absolute Deviation (MAD)3406
Skewness4.3433879
Sum3657484
Variance2.1452201 × 108
MonotonicityNot monotonic
2024-03-14T20:16:33.011330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5045 2
 
0.6%
86574 2
 
0.6%
6718 2
 
0.6%
10200 2
 
0.6%
2971 2
 
0.6%
7749 2
 
0.6%
5986 1
 
0.3%
3060 1
 
0.3%
2883 1
 
0.3%
6363 1
 
0.3%
Other values (341) 341
95.0%
(Missing) 2
 
0.6%
ValueCountFrequency (%)
331 1
0.3%
338 1
0.3%
369 1
0.3%
445 1
0.3%
456 1
0.3%
466 1
0.3%
468 1
0.3%
481 1
0.3%
503 1
0.3%
517 1
0.3%
ValueCountFrequency (%)
122917 1
0.3%
118223 1
0.3%
95172 1
0.3%
86574 2
0.6%
56111 1
0.3%
53981 1
0.3%
53369 1
0.3%
51691 1
0.3%
51278 1
0.3%
49938 1
0.3%

Interactions

2024-03-14T20:16:26.919969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:16:33.271121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설군연면적(제곱미터)
시설군1.0000.299
연면적(제곱미터)0.2991.000
2024-03-14T20:16:33.502100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적(제곱미터)시설군
연면적(제곱미터)1.0000.138
시설군0.1381.000

Missing values

2024-03-14T20:16:27.260086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:16:27.551701image/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

시설군시설명주소연면적(제곱미터)
0PC영업시설1프로 pc 아레나서울특별시 중구 다산로 132, 우봉빌딩 3층 (신당동)369
1PC영업시설E-SPOrtS Arena서울특별시 중구 서애로1길 11, 지하층 B201호 (충무로5가)456
2PC영업시설GEEK STAR PC CAFE (긱스타 피시 카페)서울특별시 중구 퇴계로 216, 행복빌딩 지하층 (충무로4가)338
3PC영업시설커몬 피씨 플렉스서울특별시 중구 동호로 180, 대승빌딩 지하1층 (신당동)331
4노인요양시설구립중구노인요양센터서울특별시 중구 필동로 961655
5대규모점포(주)광희패션몰서울특별시 중구 마장로1길 21(신당동)8600
6대규모점포(주)에리어식스(벨포스트)서울특별시 중구 마장로 19(신당동)4378
7대규모점포DDP패션몰서울특별시 중구 마장로 229655
8대규모점포굳앤굳㈜서울특별시 중구 남대문로 30(남창동)9375
9대규모점포굿모닝시티 쇼핑몰서울특별시 중구 장충단로 24738183
시설군시설명주소연면적(제곱미터)
349지하역사을지로4가⑤서울특별시 중구 창경궁로 지하5111492
350지하역사을지로입구서울특별시 중구 을지로 지하4210640
351지하역사청구⑤서울특별시 중구 청구로 지하775928
352지하역사청구⑥서울특별시 중구 청구로 지하775806
353지하역사충무로③서울특별시 중구 퇴계로 지하1993860
354지하역사충무로④서울특별시 중구 퇴계로 지하19912733
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