Overview

Dataset statistics

Number of variables12
Number of observations40
Missing cells15
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory101.3 B

Variable types

Numeric2
Categorical3
Text5
Boolean1
DateTime1

Dataset

Description서대문구에 위치한 실외흡연실 정보
Author서울특별시 서대문구
URLhttps://www.data.go.kr/data/15068923/fileData.do

Alerts

자치구 has constant value ""Constant
관리여부 has constant value ""Constant
데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 시설구분High correlation
시설구분 is highly overall correlated with 연번High correlation
설치월 has 15 (37.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:18:04.777811
Analysis finished2023-12-12 09:18:06.057747
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T18:18:06.145654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2023-12-12T18:18:06.321284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
서대문구
40 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서대문구 40
100.0%

Length

2023-12-12T18:18:06.519223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:18:06.654817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서대문구 40
100.0%

시설구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
1,000㎡이상 건축물
21 
청사
12 
대학교
4 
의료기관
 
1
학원
 
1

Length

Max length12
Median length12
Mean length7.475
Min length2

Unique

Unique3 ?
Unique (%)7.5%

Sample

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

Common Values

ValueCountFrequency (%)
1,000㎡이상 건축물 21
52.5%
청사 12
30.0%
대학교 4
 
10.0%
의료기관 1
 
2.5%
학원 1
 
2.5%
대규모점포 1
 
2.5%

Length

2023-12-12T18:18:06.774291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:18:06.896623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1,000㎡이상 21
34.4%
건축물 21
34.4%
청사 12
19.7%
대학교 4
 
6.6%
의료기관 1
 
1.6%
학원 1
 
1.6%
대규모점포 1
 
1.6%

시설형태
Categorical

Distinct4
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
개방형
28 
폐쇄형
5 
완전폐쇄형
4 
완전개방형
3 

Length

Max length5
Median length3
Mean length3.35
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row완전폐쇄형
2nd row개방형
3rd row개방형
4th row개방형
5th row개방형

Common Values

ValueCountFrequency (%)
개방형 28
70.0%
폐쇄형 5
 
12.5%
완전폐쇄형 4
 
10.0%
완전개방형 3
 
7.5%

Length

2023-12-12T18:18:07.051925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:18:07.192797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개방형 28
70.0%
폐쇄형 5
 
12.5%
완전폐쇄형 4
 
10.0%
완전개방형 3
 
7.5%

설치위치
Text

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:18:07.425070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length16.875
Min length15

Characters and Unicode

Total characters675
Distinct characters45
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

Unique33 ?
Unique (%)82.5%

Sample

1st row서울특별시 서대문구 연희로248
2nd row서울특별시 서대문구 연희로248
3rd row서울특별시 서대문구 연희로182
4th row서울특별시 서대문구 서소문로51
5th row서울특별시 서대문구 성산로20길 9
ValueCountFrequency (%)
서울특별시 40
32.3%
서대문구 40
32.3%
성산로20길 3
 
2.4%
9 3
 
2.4%
충정로60 2
 
1.6%
연희로248 2
 
1.6%
연희로407 1
 
0.8%
충정로23 1
 
0.8%
신촌로113 1
 
0.8%
신촌로183 1
 
0.8%
Other values (30) 30
24.2%
2023-12-12T18:18:07.804612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
12.4%
서 83
12.3%
문 43
 
6.4%
대 43
 
6.4%
구 40
 
5.9%
로 40
 
5.9%
시 40
 
5.9%
별 40
 
5.9%
울 40
 
5.9%
특 40
 
5.9%
Other values (35) 182
27.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 491
72.7%
Decimal Number 99
 
14.7%
Space Separator 84
 
12.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 83
16.9%
문 43
8.8%
대 43
8.8%
구 40
8.1%
로 40
8.1%
시 40
8.1%
별 40
8.1%
울 40
8.1%
특 40
8.1%
충 8
 
1.6%
Other values (23) 74
15.1%
Decimal Number
ValueCountFrequency (%)
1 19
19.2%
3 15
15.2%
2 14
14.1%
4 10
10.1%
0 9
9.1%
5 7
 
7.1%
9 7
 
7.1%
7 7
 
7.1%
8 6
 
6.1%
6 5
 
5.1%
Space Separator
ValueCountFrequency (%)
84
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 491
72.7%
Common 184
 
27.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 83
16.9%
문 43
8.8%
대 43
8.8%
구 40
8.1%
로 40
8.1%
시 40
8.1%
별 40
8.1%
울 40
8.1%
특 40
8.1%
충 8
 
1.6%
Other values (23) 74
15.1%
Common
ValueCountFrequency (%)
84
45.7%
1 19
 
10.3%
3 15
 
8.2%
2 14
 
7.6%
4 10
 
5.4%
0 9
 
4.9%
5 7
 
3.8%
9 7
 
3.8%
7 7
 
3.8%
8 6
 
3.3%
Other values (2) 6
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 491
72.7%
ASCII 184
 
27.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84
45.7%
1 19
 
10.3%
3 15
 
8.2%
2 14
 
7.6%
4 10
 
5.4%
0 9
 
4.9%
5 7
 
3.8%
9 7
 
3.8%
7 7
 
3.8%
8 6
 
3.3%
Other values (2) 6
 
3.3%
Hangul
ValueCountFrequency (%)
서 83
16.9%
문 43
8.8%
대 43
8.8%
구 40
8.1%
로 40
8.1%
시 40
8.1%
별 40
8.1%
울 40
8.1%
특 40
8.1%
충 8
 
1.6%
Other values (23) 74
15.1%

설치위치 상세
Text

Distinct33
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:18:08.322268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length7.875
Min length2

Characters and Unicode

Total characters315
Distinct characters100
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)80.0%

Sample

1st row옥상
2nd row1층 정자
3rd row서대문소방서 3층 테라스
4th row1층
5th row4층 테라스
ValueCountFrequency (%)
1층 16
18.8%
옥상 13
 
15.3%
테라스 4
 
4.7%
옆 3
 
3.5%
2층 3
 
3.5%
외부 3
 
3.5%
주차장 3
 
3.5%
현대백화점 2
 
2.4%
지하1층 2
 
2.4%
신촌점 2
 
2.4%
Other values (34) 34
40.0%
2023-12-12T18:18:08.722422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
45
 
14.3%
층 26
 
8.3%
1 20
 
6.3%
상 16
 
5.1%
옥 14
 
4.4%
딩 11
 
3.5%
빌 11
 
3.5%
지 7
 
2.2%
스 7
 
2.2%
장 5
 
1.6%
Other values (90) 153
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 233
74.0%
Space Separator 45
 
14.3%
Decimal Number 26
 
8.3%
Uppercase Letter 9
 
2.9%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 26
 
11.2%
상 16
 
6.9%
옥 14
 
6.0%
딩 11
 
4.7%
빌 11
 
4.7%
지 7
 
3.0%
스 7
 
3.0%
장 5
 
2.1%
대 5
 
2.1%
외 5
 
2.1%
Other values (76) 126
54.1%
Uppercase Letter
ValueCountFrequency (%)
K 3
33.3%
T 2
22.2%
M 1
 
11.1%
B 1
 
11.1%
Y 1
 
11.1%
S 1
 
11.1%
Decimal Number
ValueCountFrequency (%)
1 20
76.9%
2 3
 
11.5%
3 1
 
3.8%
4 1
 
3.8%
5 1
 
3.8%
Space Separator
ValueCountFrequency (%)
45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 233
74.0%
Common 73
 
23.2%
Latin 9
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 26
 
11.2%
상 16
 
6.9%
옥 14
 
6.0%
딩 11
 
4.7%
빌 11
 
4.7%
지 7
 
3.0%
스 7
 
3.0%
장 5
 
2.1%
대 5
 
2.1%
외 5
 
2.1%
Other values (76) 126
54.1%
Common
ValueCountFrequency (%)
45
61.6%
1 20
27.4%
2 3
 
4.1%
3 1
 
1.4%
4 1
 
1.4%
5 1
 
1.4%
( 1
 
1.4%
) 1
 
1.4%
Latin
ValueCountFrequency (%)
K 3
33.3%
T 2
22.2%
M 1
 
11.1%
B 1
 
11.1%
Y 1
 
11.1%
S 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 233
74.0%
ASCII 82
 
26.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45
54.9%
1 20
24.4%
K 3
 
3.7%
2 3
 
3.7%
T 2
 
2.4%
M 1
 
1.2%
B 1
 
1.2%
Y 1
 
1.2%
S 1
 
1.2%
3 1
 
1.2%
Other values (4) 4
 
4.9%
Hangul
ValueCountFrequency (%)
층 26
 
11.2%
상 16
 
6.9%
옥 14
 
6.0%
딩 11
 
4.7%
빌 11
 
4.7%
지 7
 
3.0%
스 7
 
3.0%
장 5
 
2.1%
대 5
 
2.1%
외 5
 
2.1%
Other values (76) 126
54.1%

규모(㎡)
Real number (ℝ)

Distinct17
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19
Minimum5
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T18:18:08.877241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q19
median15
Q325
95-th percentile50
Maximum100
Range95
Interquartile range (IQR)16

Descriptive statistics

Standard deviation17.094009
Coefficient of variation (CV)0.89968466
Kurtosis12.622151
Mean19
Median Absolute Deviation (MAD)7
Skewness3.0994176
Sum760
Variance292.20513
MonotonicityNot monotonic
2023-12-12T18:18:09.039972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
15 6
15.0%
25 5
12.5%
12 3
 
7.5%
9 3
 
7.5%
5 3
 
7.5%
6 3
 
7.5%
8 2
 
5.0%
20 2
 
5.0%
50 2
 
5.0%
18 2
 
5.0%
Other values (7) 9
22.5%
ValueCountFrequency (%)
5 3
7.5%
6 3
7.5%
7 1
 
2.5%
8 2
 
5.0%
9 3
7.5%
10 2
 
5.0%
12 3
7.5%
13 1
 
2.5%
15 6
15.0%
18 2
 
5.0%
ValueCountFrequency (%)
100 1
 
2.5%
50 2
 
5.0%
35 1
 
2.5%
30 2
 
5.0%
25 5
12.5%
22 1
 
2.5%
20 2
 
5.0%
18 2
 
5.0%
15 6
15.0%
13 1
 
2.5%

설치월
Text

MISSING 

Distinct19
Distinct (%)76.0%
Missing15
Missing (%)37.5%
Memory size452.0 B
2023-12-12T18:18:09.257425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters150
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)56.0%

Sample

1st row06-Jun
2nd row15-Oct
3rd row12-Dec
4th row12-Dec
5th row12-Dec
ValueCountFrequency (%)
12-dec 3
 
12.0%
11-sep 2
 
8.0%
15-jan 2
 
8.0%
17-oct 2
 
8.0%
11-jan 2
 
8.0%
18-oct 1
 
4.0%
16-mar 1
 
4.0%
18-mar 1
 
4.0%
18-jun 1
 
4.0%
02-jan 1
 
4.0%
Other values (9) 9
36.0%
2023-12-12T18:18:09.603626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 26
17.3%
- 25
16.7%
a 12
 
8.0%
J 11
 
7.3%
n 11
 
7.3%
c 9
 
6.0%
e 6
 
4.0%
2 6
 
4.0%
O 5
 
3.3%
t 5
 
3.3%
Other values (13) 34
22.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50
33.3%
Lowercase Letter 50
33.3%
Dash Punctuation 25
16.7%
Uppercase Letter 25
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 12
24.0%
n 11
22.0%
c 9
18.0%
e 6
12.0%
t 5
10.0%
p 2
 
4.0%
u 2
 
4.0%
r 2
 
4.0%
y 1
 
2.0%
Decimal Number
ValueCountFrequency (%)
1 26
52.0%
2 6
 
12.0%
0 4
 
8.0%
4 3
 
6.0%
8 3
 
6.0%
5 3
 
6.0%
7 3
 
6.0%
6 2
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
J 11
44.0%
O 5
20.0%
D 4
 
16.0%
M 3
 
12.0%
S 2
 
8.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75
50.0%
Latin 75
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 12
16.0%
J 11
14.7%
n 11
14.7%
c 9
12.0%
e 6
8.0%
O 5
6.7%
t 5
6.7%
D 4
 
5.3%
M 3
 
4.0%
p 2
 
2.7%
Other values (4) 7
9.3%
Common
ValueCountFrequency (%)
1 26
34.7%
- 25
33.3%
2 6
 
8.0%
0 4
 
5.3%
4 3
 
4.0%
8 3
 
4.0%
5 3
 
4.0%
7 3
 
4.0%
6 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 26
17.3%
- 25
16.7%
a 12
 
8.0%
J 11
 
7.3%
n 11
 
7.3%
c 9
 
6.0%
e 6
 
4.0%
2 6
 
4.0%
O 5
 
3.3%
t 5
 
3.3%
Other values (13) 34
22.7%

설치주체
Text

Distinct35
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:18:09.823413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.2
Min length3

Characters and Unicode

Total characters208
Distinct characters96
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)77.5%

Sample

1st row서대문구청
2nd row서대문구청
3rd row서대문소방서
4th row상수도사업본부
5th row서대문우체국
ValueCountFrequency (%)
서대문우체국 3
 
7.5%
현대백화점 2
 
5.0%
서대문구청 2
 
5.0%
kt&g 2
 
5.0%
신촌빌딩 1
 
2.5%
골든브리지빌딩 1
 
2.5%
충정타워 1
 
2.5%
종근당 1
 
2.5%
sk리쳄블 1
 
2.5%
대림통상 1
 
2.5%
Other values (25) 25
62.5%
2023-12-12T18:18:10.220959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 14
 
6.7%
서 10
 
4.8%
딩 10
 
4.8%
빌 10
 
4.8%
문 9
 
4.3%
지 7
 
3.4%
국 5
 
2.4%
K 5
 
2.4%
T 4
 
1.9%
백 4
 
1.9%
Other values (86) 130
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191
91.8%
Uppercase Letter 15
 
7.2%
Other Punctuation 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 14
 
7.3%
서 10
 
5.2%
딩 10
 
5.2%
빌 10
 
5.2%
문 9
 
4.7%
지 7
 
3.7%
국 5
 
2.6%
백 4
 
2.1%
화 4
 
2.1%
경 3
 
1.6%
Other values (78) 115
60.2%
Uppercase Letter
ValueCountFrequency (%)
K 5
33.3%
T 4
26.7%
G 2
 
13.3%
S 1
 
6.7%
Y 1
 
6.7%
B 1
 
6.7%
M 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 191
91.8%
Latin 15
 
7.2%
Common 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 14
 
7.3%
서 10
 
5.2%
딩 10
 
5.2%
빌 10
 
5.2%
문 9
 
4.7%
지 7
 
3.7%
국 5
 
2.6%
백 4
 
2.1%
화 4
 
2.1%
경 3
 
1.6%
Other values (78) 115
60.2%
Latin
ValueCountFrequency (%)
K 5
33.3%
T 4
26.7%
G 2
 
13.3%
S 1
 
6.7%
Y 1
 
6.7%
B 1
 
6.7%
M 1
 
6.7%
Common
ValueCountFrequency (%)
& 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191
91.8%
ASCII 17
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 14
 
7.3%
서 10
 
5.2%
딩 10
 
5.2%
빌 10
 
5.2%
문 9
 
4.7%
지 7
 
3.7%
국 5
 
2.6%
백 4
 
2.1%
화 4
 
2.1%
경 3
 
1.6%
Other values (78) 115
60.2%
ASCII
ValueCountFrequency (%)
K 5
29.4%
T 4
23.5%
& 2
 
11.8%
G 2
 
11.8%
S 1
 
5.9%
Y 1
 
5.9%
B 1
 
5.9%
M 1
 
5.9%

관리여부
Boolean

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size172.0 B
True
40 
ValueCountFrequency (%)
True 40
100.0%
2023-12-12T18:18:10.345300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리기관
Text

Distinct35
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:18:10.540533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.2
Min length3

Characters and Unicode

Total characters208
Distinct characters96
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)77.5%

Sample

1st row서대문구청
2nd row서대문구청
3rd row서대문소방서
4th row상수도사업본부
5th row서대문우체국
ValueCountFrequency (%)
서대문우체국 3
 
7.5%
현대백화점 2
 
5.0%
서대문구청 2
 
5.0%
kt&g 2
 
5.0%
신촌빌딩 1
 
2.5%
골든브리지빌딩 1
 
2.5%
충정타워 1
 
2.5%
종근당 1
 
2.5%
sk리쳄블 1
 
2.5%
대림통상 1
 
2.5%
Other values (25) 25
62.5%
2023-12-12T18:18:10.949421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 14
 
6.7%
서 10
 
4.8%
딩 10
 
4.8%
빌 10
 
4.8%
문 9
 
4.3%
지 7
 
3.4%
국 5
 
2.4%
K 5
 
2.4%
T 4
 
1.9%
백 4
 
1.9%
Other values (86) 130
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191
91.8%
Uppercase Letter 15
 
7.2%
Other Punctuation 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 14
 
7.3%
서 10
 
5.2%
딩 10
 
5.2%
빌 10
 
5.2%
문 9
 
4.7%
지 7
 
3.7%
국 5
 
2.6%
백 4
 
2.1%
화 4
 
2.1%
경 3
 
1.6%
Other values (78) 115
60.2%
Uppercase Letter
ValueCountFrequency (%)
K 5
33.3%
T 4
26.7%
G 2
 
13.3%
S 1
 
6.7%
Y 1
 
6.7%
B 1
 
6.7%
M 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 191
91.8%
Latin 15
 
7.2%
Common 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 14
 
7.3%
서 10
 
5.2%
딩 10
 
5.2%
빌 10
 
5.2%
문 9
 
4.7%
지 7
 
3.7%
국 5
 
2.6%
백 4
 
2.1%
화 4
 
2.1%
경 3
 
1.6%
Other values (78) 115
60.2%
Latin
ValueCountFrequency (%)
K 5
33.3%
T 4
26.7%
G 2
 
13.3%
S 1
 
6.7%
Y 1
 
6.7%
B 1
 
6.7%
M 1
 
6.7%
Common
ValueCountFrequency (%)
& 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191
91.8%
ASCII 17
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 14
 
7.3%
서 10
 
5.2%
딩 10
 
5.2%
빌 10
 
5.2%
문 9
 
4.7%
지 7
 
3.7%
국 5
 
2.6%
백 4
 
2.1%
화 4
 
2.1%
경 3
 
1.6%
Other values (78) 115
60.2%
ASCII
ValueCountFrequency (%)
K 5
29.4%
T 4
23.5%
& 2
 
11.8%
G 2
 
11.8%
S 1
 
5.9%
Y 1
 
5.9%
B 1
 
5.9%
M 1
 
5.9%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
Minimum2020-10-07 00:00:00
Maximum2020-10-07 00:00:00
2023-12-12T18:18:11.071230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:18:11.209718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T18:18:05.550066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:18:05.359898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:18:05.658983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:18:05.453895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:18:11.300394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설구분시설형태설치위치설치위치 상세규모(㎡)설치월설치주체관리기관
연번1.0000.7720.0001.0000.8590.3960.9901.0001.000
시설구분0.7721.0000.3031.0000.9700.8630.9630.8340.834
시설형태0.0000.3031.0000.9620.7590.3041.0000.9540.954
설치위치1.0001.0000.9621.0000.9720.0001.0001.0001.000
설치위치 상세0.8590.9700.7590.9721.0000.9560.9100.9520.952
규모(㎡)0.3960.8630.3040.0000.9561.0000.0000.0000.000
설치월0.9900.9631.0001.0000.9100.0001.0001.0001.000
설치주체1.0000.8340.9541.0000.9520.0001.0001.0001.000
관리기관1.0000.8340.9541.0000.9520.0001.0001.0001.000
2023-12-12T18:18:11.448365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설형태시설구분
시설형태1.0000.185
시설구분0.1851.000
2023-12-12T18:18:11.546157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번규모(㎡)시설구분시설형태
연번1.0000.0150.5110.000
규모(㎡)0.0151.0000.4870.185
시설구분0.5110.4871.0000.185
시설형태0.0000.1850.1851.000

Missing values

2023-12-12T18:18:05.801974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:18:05.990115image/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

연번자치구시설구분시설형태설치위치설치위치 상세규모(㎡)설치월설치주체관리여부관리기관데이터기준일
01서대문구청사완전폐쇄형서울특별시 서대문구 연희로248옥상35<NA>서대문구청Y서대문구청2020-10-07
12서대문구청사개방형서울특별시 서대문구 연희로2481층 정자25<NA>서대문구청Y서대문구청2020-10-07
23서대문구청사개방형서울특별시 서대문구 연희로182서대문소방서 3층 테라스2506-Jun서대문소방서Y서대문소방서2020-10-07
34서대문구청사개방형서울특별시 서대문구 서소문로511층915-Oct상수도사업본부Y상수도사업본부2020-10-07
45서대문구청사개방형서울특별시 서대문구 성산로20길 94층 테라스912-Dec서대문우체국Y서대문우체국2020-10-07
56서대문구청사개방형서울특별시 서대문구 성산로20길 92층 실외1512-Dec서대문우체국Y서대문우체국2020-10-07
67서대문구청사개방형서울특별시 서대문구 성산로20길 91층812-Dec서대문우체국Y서대문우체국2020-10-07
78서대문구청사개방형서울특별시 서대문구 통일로1131층511-Jan서대문경찰서Y서대문경찰서2020-10-07
89서대문구청사완전폐쇄형서울특별시 서대문구 통일로971층5<NA>경찰청Y경찰청2020-10-07
910서대문구청사개방형서울특별시 서대문구 충정로361층15<NA>국민연금공단Y국민연금공단2020-10-07
연번자치구시설구분시설형태설치위치설치위치 상세규모(㎡)설치월설치주체관리여부관리기관데이터기준일
3031서대문구1,000㎡이상 건축물개방형서울특별시 서대문구 서소문로45SK리쳄블 옥상914-JanSK리쳄블YSK리쳄블2020-10-07
3132서대문구1,000㎡이상 건축물개방형서울특별시 서대문구 연희로142대림통상 옥상3002-Jan대림통상Y대림통상2020-10-07
3233서대문구1,000㎡이상 건축물개방형서울특별시 서대문구 신촌로73케이스퀘어 신촌빌딩 옥상1317-Oct신촌빌딩Y신촌빌딩2020-10-07
3334서대문구1,000㎡이상 건축물완전개방형서울특별시 서대문구 연희로407백련빌딩 옥상5<NA>백련빌딩Y백련빌딩2020-10-07
3435서대문구1,000㎡이상 건축물완전개방형서울특별시 서대문구 신촌로231백상빌딩 옥상618-Jun백상빌딩Y백상빌딩2020-10-07
3536서대문구1,000㎡이상 건축물개방형서울특별시 서대문구 신촌로183유인빌딩 2층 외부717-Oct유인빌딩Y유인빌딩2020-10-07
3637서대문구1,000㎡이상 건축물완전개방형서울특별시 서대문구 신촌로113YBM옥상1518-MarYBMYYBM2020-10-07
3738서대문구1,000㎡이상 건축물폐쇄형서울특별시 서대문구 충정로23풍산빌딩 1층 화단 옆1812-Jan풍산빌딩Y풍산빌딩2020-10-07
3839서대문구1,000㎡이상 건축물개방형서울특별시 서대문구 연세로13현대백화점 유플렉스 신촌점 옥상25<NA>현대백화점Y현대백화점2020-10-07
3940서대문구대규모점포개방형서울특별시 서대문구 신촌로83현대백화점 신촌점 옥상100<NA>현대백화점Y현대백화점2020-10-07