Overview

Dataset statistics

Number of variables7
Number of observations72
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory59.8 B

Variable types

Categorical3
Text2
Numeric2

Dataset

Description서울특별시 용산구 흡연구역 현황(자치구명, 시설구분, 시설형태, 서울특별시 용산구 설치 위치, 위도, 경도)에 대한 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15073796/fileData.do

Alerts

자치구명 has constant value ""Constant
시설형태 is highly imbalanced (81.7%)Imbalance

Reproduction

Analysis started2023-12-12 22:40:45.275162
Analysis finished2023-12-12 22:40:46.079725
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
용산구
72 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용산구 72
100.0%

Length

2023-12-13T07:40:46.131532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:40:46.213679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용산구 72
100.0%

시설 구분
Categorical

Distinct8
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size708.0 B
연면적 1000㎡ 이상 대형건물
50 
청사
7 
대규모점포
 
5
대학교
 
4
철도역
 
2
Other values (3)
 
4

Length

Max length17
Median length17
Mean length12.833333
Min length2

Unique

Unique2 ?
Unique (%)2.8%

Sample

1st row철도역
2nd row철도역
3rd row철도역(조례)
4th row청사
5th row청사

Common Values

ValueCountFrequency (%)
연면적 1000㎡ 이상 대형건물 50
69.4%
청사 7
 
9.7%
대규모점포 5
 
6.9%
대학교 4
 
5.6%
철도역 2
 
2.8%
의료기관 2
 
2.8%
철도역(조례) 1
 
1.4%
호텔 1
 
1.4%

Length

2023-12-13T07:40:46.307630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:40:46.425465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연면적 50
22.5%
1000㎡ 50
22.5%
이상 50
22.5%
대형건물 50
22.5%
청사 7
 
3.2%
대규모점포 5
 
2.3%
대학교 4
 
1.8%
철도역 2
 
0.9%
의료기관 2
 
0.9%
철도역(조례 1
 
0.5%

시설형태
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
개방형
70 
폐쇄형
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개방형 70
97.2%
폐쇄형 2
 
2.8%

Length

2023-12-13T07:40:46.538154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:40:46.622337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개방형 70
97.2%
폐쇄형 2
 
2.8%

서울특별시 용산구 설치 위치
Text

Distinct69
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-13T07:40:46.832777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27.5
Mean length21.930556
Min length15

Characters and Unicode

Total characters1579
Distinct characters195
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

Unique68 ?
Unique (%)94.4%

Sample

1st row서울특별시 용산구 서울역 광장 15번출구
2nd row서울특별시 용산구 서울역 광장 1번출구
3rd row서울특별시 용산구 용산역 광장
4th row서울특별시 용산구 용산구청 옥상
5th row서울특별시 용산구 용산구청 2층 외부
ValueCountFrequency (%)
서울특별시 72
20.6%
용산구 72
20.6%
옥상 27
 
7.7%
1층 21
 
6.0%
외부 18
 
5.1%
주차장 15
 
4.3%
정수캠퍼스 4
 
1.1%
한국폴리텍대학 4
 
1.1%
광장 3
 
0.9%
용산구청 3
 
0.9%
Other values (93) 111
31.7%
2023-12-13T07:40:47.176164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
278
17.6%
용 84
 
5.3%
산 84
 
5.3%
서 81
 
5.1%
구 78
 
4.9%
울 78
 
4.9%
별 73
 
4.6%
시 73
 
4.6%
특 72
 
4.6%
층 31
 
2.0%
Other values (185) 647
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1226
77.6%
Space Separator 278
 
17.6%
Decimal Number 42
 
2.7%
Uppercase Letter 15
 
0.9%
Other Punctuation 8
 
0.5%
Close Punctuation 4
 
0.3%
Open Punctuation 4
 
0.3%
Other Symbol 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 84
 
6.9%
산 84
 
6.9%
서 81
 
6.6%
구 78
 
6.4%
울 78
 
6.4%
별 73
 
6.0%
시 73
 
6.0%
특 72
 
5.9%
층 31
 
2.5%
상 31
 
2.5%
Other values (158) 541
44.1%
Uppercase Letter
ValueCountFrequency (%)
C 2
13.3%
S 2
13.3%
K 1
 
6.7%
I 1
 
6.7%
L 1
 
6.7%
T 1
 
6.7%
A 1
 
6.7%
B 1
 
6.7%
O 1
 
6.7%
P 1
 
6.7%
Other values (3) 3
20.0%
Decimal Number
ValueCountFrequency (%)
1 27
64.3%
5 6
 
14.3%
2 4
 
9.5%
4 2
 
4.8%
0 1
 
2.4%
8 1
 
2.4%
6 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 6
75.0%
. 2
 
25.0%
Space Separator
ValueCountFrequency (%)
278
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1227
77.7%
Common 336
 
21.3%
Latin 16
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 84
 
6.8%
산 84
 
6.8%
서 81
 
6.6%
구 78
 
6.4%
울 78
 
6.4%
별 73
 
5.9%
시 73
 
5.9%
특 72
 
5.9%
층 31
 
2.5%
상 31
 
2.5%
Other values (159) 542
44.2%
Latin
ValueCountFrequency (%)
C 2
12.5%
S 2
12.5%
K 1
 
6.2%
I 1
 
6.2%
L 1
 
6.2%
T 1
 
6.2%
e 1
 
6.2%
A 1
 
6.2%
B 1
 
6.2%
O 1
 
6.2%
Other values (4) 4
25.0%
Common
ValueCountFrequency (%)
278
82.7%
1 27
 
8.0%
, 6
 
1.8%
5 6
 
1.8%
2 4
 
1.2%
) 4
 
1.2%
( 4
 
1.2%
. 2
 
0.6%
4 2
 
0.6%
0 1
 
0.3%
Other values (2) 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1226
77.6%
ASCII 352
 
22.3%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
278
79.0%
1 27
 
7.7%
, 6
 
1.7%
5 6
 
1.7%
2 4
 
1.1%
) 4
 
1.1%
( 4
 
1.1%
. 2
 
0.6%
C 2
 
0.6%
4 2
 
0.6%
Other values (16) 17
 
4.8%
Hangul
ValueCountFrequency (%)
용 84
 
6.9%
산 84
 
6.9%
서 81
 
6.6%
구 78
 
6.4%
울 78
 
6.4%
별 73
 
6.0%
시 73
 
6.0%
특 72
 
5.9%
층 31
 
2.5%
상 31
 
2.5%
Other values (158) 541
44.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

설치 주체
Text

Distinct60
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-13T07:40:47.391686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length5.6527778
Min length3

Characters and Unicode

Total characters407
Distinct characters153
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)72.2%

Sample

1st row한국철도공사
2nd row한국철도공사
3rd row현대아이파크몰
4th row용산구청
5th row용산구청
ValueCountFrequency (%)
한국폴리텍대학 4
 
5.3%
현대아이파크몰 4
 
5.3%
순천향대학교병원 2
 
2.6%
미성상사 2
 
2.6%
선인상가 2
 
2.6%
한국철도공사 2
 
2.6%
용산구청 2
 
2.6%
오리온제과 2
 
2.6%
비비안 1
 
1.3%
한화빌딩 1
 
1.3%
Other values (54) 54
71.1%
2023-12-13T07:40:47.748737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
빌 19
 
4.7%
대 19
 
4.7%
딩 18
 
4.4%
한 13
 
3.2%
리 10
 
2.5%
아 9
 
2.2%
이 9
 
2.2%
산 9
 
2.2%
용 8
 
2.0%
스 8
 
2.0%
Other values (143) 285
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 392
96.3%
Uppercase Letter 10
 
2.5%
Space Separator 4
 
1.0%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
빌 19
 
4.8%
대 19
 
4.8%
딩 18
 
4.6%
한 13
 
3.3%
리 10
 
2.6%
아 9
 
2.3%
이 9
 
2.3%
산 9
 
2.3%
용 8
 
2.0%
스 8
 
2.0%
Other values (133) 270
68.9%
Uppercase Letter
ValueCountFrequency (%)
G 2
20.0%
C 2
20.0%
H 1
10.0%
N 1
10.0%
T 1
10.0%
I 1
10.0%
K 1
10.0%
S 1
10.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 393
96.6%
Latin 10
 
2.5%
Common 4
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
빌 19
 
4.8%
대 19
 
4.8%
딩 18
 
4.6%
한 13
 
3.3%
리 10
 
2.5%
아 9
 
2.3%
이 9
 
2.3%
산 9
 
2.3%
용 8
 
2.0%
스 8
 
2.0%
Other values (134) 271
69.0%
Latin
ValueCountFrequency (%)
G 2
20.0%
C 2
20.0%
H 1
10.0%
N 1
10.0%
T 1
10.0%
I 1
10.0%
K 1
10.0%
S 1
10.0%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 392
96.3%
ASCII 14
 
3.4%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
빌 19
 
4.8%
대 19
 
4.8%
딩 18
 
4.6%
한 13
 
3.3%
리 10
 
2.6%
아 9
 
2.3%
이 9
 
2.3%
산 9
 
2.3%
용 8
 
2.0%
스 8
 
2.0%
Other values (133) 270
68.9%
ASCII
ValueCountFrequency (%)
4
28.6%
G 2
14.3%
C 2
14.3%
H 1
 
7.1%
N 1
 
7.1%
T 1
 
7.1%
I 1
 
7.1%
K 1
 
7.1%
S 1
 
7.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

위도
Real number (ℝ)

Distinct67
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.536853
Minimum37.523302
Maximum37.55492
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-13T07:40:47.874347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.523302
5-th percentile37.528811
Q137.532584
median37.534816
Q337.540637
95-th percentile37.552535
Maximum37.55492
Range0.031618
Interquartile range (IQR)0.00805325

Descriptive statistics

Standard deviation0.0070356207
Coefficient of variation (CV)0.00018743235
Kurtosis0.46920612
Mean37.536853
Median Absolute Deviation (MAD)0.0039615
Skewness0.95166788
Sum2702.6534
Variance4.9499958 × 10-5
MonotonicityNot monotonic
2023-12-13T07:40:47.991367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.529492 3
 
4.2%
37.532709 2
 
2.8%
37.538839 2
 
2.8%
37.533068 2
 
2.8%
37.553149 1
 
1.4%
37.553965 1
 
1.4%
37.540529 1
 
1.4%
37.54175 1
 
1.4%
37.551185 1
 
1.4%
37.552032 1
 
1.4%
Other values (57) 57
79.2%
ValueCountFrequency (%)
37.523302 1
 
1.4%
37.528002 1
 
1.4%
37.528404 1
 
1.4%
37.52871 1
 
1.4%
37.528894 1
 
1.4%
37.52911 1
 
1.4%
37.529136 1
 
1.4%
37.529323 1
 
1.4%
37.529492 3
4.2%
37.529799 1
 
1.4%
ValueCountFrequency (%)
37.55492 1
1.4%
37.553965 1
1.4%
37.55376 1
1.4%
37.553149 1
1.4%
37.552032 1
1.4%
37.551185 1
1.4%
37.548507 1
1.4%
37.5485 1
1.4%
37.54589 1
1.4%
37.544739 1
1.4%

경도
Real number (ℝ)

Distinct66
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.97234
Minimum126.95375
Maximum127.0115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2023-12-13T07:40:48.433111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.95375
5-th percentile126.95725
Q1126.96432
median126.96884
Q3126.97326
95-th percentile126.99787
Maximum127.0115
Range0.057748
Interquartile range (IQR)0.00894525

Descriptive statistics

Standard deviation0.013242063
Coefficient of variation (CV)0.00010429093
Kurtosis0.84095387
Mean126.97234
Median Absolute Deviation (MAD)0.004525
Skewness1.258894
Sum9142.0087
Variance0.00017535224
MonotonicityNot monotonic
2023-12-13T07:40:48.566909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.964318 3
 
4.2%
126.99 2
 
2.8%
126.973179 2
 
2.8%
126.963521 2
 
2.8%
126.968402 2
 
2.8%
126.968881 1
 
1.4%
126.965964 1
 
1.4%
126.970388 1
 
1.4%
126.96922 1
 
1.4%
126.968943 1
 
1.4%
Other values (56) 56
77.8%
ValueCountFrequency (%)
126.953751 1
1.4%
126.955055 1
1.4%
126.955431 1
1.4%
126.956792 1
1.4%
126.95763 1
1.4%
126.957656 1
1.4%
126.958895 1
1.4%
126.959002 1
1.4%
126.959979 1
1.4%
126.960734 1
1.4%
ValueCountFrequency (%)
127.011499 1
1.4%
127.004585 1
1.4%
127.004334 1
1.4%
126.998616 1
1.4%
126.997264 1
1.4%
126.997224 1
1.4%
126.996498 1
1.4%
126.996483 1
1.4%
126.996226 1
1.4%
126.995976 1
1.4%

Interactions

2023-12-13T07:40:45.764179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:40:45.616561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:40:45.841536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:40:45.692115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:40:48.729455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설 구분시설형태서울특별시 용산구 설치 위치설치 주체위도경도
시설 구분1.0000.0001.0000.8630.4340.747
시설형태0.0001.0001.0001.0000.0000.000
서울특별시 용산구 설치 위치1.0001.0001.0001.0000.9791.000
설치 주체0.8631.0001.0001.0000.9980.998
위도0.4340.0000.9790.9981.0000.607
경도0.7470.0001.0000.9980.6071.000
2023-12-13T07:40:48.851531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설 구분시설형태
시설 구분1.0000.000
시설형태0.0001.000
2023-12-13T07:40:48.933404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도시설 구분시설형태
위도1.0000.2260.2160.000
경도0.2261.0000.4850.000
시설 구분0.2160.4851.0000.000
시설형태0.0000.0000.0001.000

Missing values

2023-12-13T07:40:45.936541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:40:46.037405image/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

자치구명시설 구분시설형태서울특별시 용산구 설치 위치설치 주체위도경도
0용산구철도역개방형서울특별시 용산구 서울역 광장 15번출구한국철도공사37.553149126.968881
1용산구철도역개방형서울특별시 용산구 서울역 광장 1번출구한국철도공사37.55376126.969662
2용산구철도역(조례)개방형서울특별시 용산구 용산역 광장현대아이파크몰37.528404126.965569
3용산구청사개방형서울특별시 용산구 용산구청 옥상용산구청37.532709126.99
4용산구청사개방형서울특별시 용산구 용산구청 2층 외부용산구청37.532709126.99
5용산구청사개방형서울특별시 용산구 용산경찰서 1층 외부용산경찰서37.541169126.96765
6용산구청사개방형서울특별시 용산구 원효지구대 방범순찰대(옛 용산구청)원효지구대 방법순찰대37.538716126.96589
7용산구청사개방형서울특별시 용산구 서울지방보훈청 실외서울지방보훈청37.534923126.974192
8용산구청사개방형서울특별시 용산구 용산세무서 1층 외부용산세무서37.523302126.96868
9용산구청사개방형서울특별시 용산구 국방부 컨벤스 1층 외부국방부37.533237126.97859
자치구명시설 구분시설형태서울특별시 용산구 설치 위치설치 주체위도경도
62용산구연면적 1000㎡ 이상 대형건물개방형서울특별시 용산구 우리빌딩 주차장우리빌딩37.54096126.973516
63용산구연면적 1000㎡ 이상 대형건물개방형서울특별시 용산구 기업은행용산지점 2층 베란다기업은행용산지점37.541995126.973179
64용산구연면적 1000㎡ 이상 대형건물개방형서울특별시 용산구 진흥빌딩 옥상진흥빌딩37.5485126.977574
65용산구연면적 1000㎡ 이상 대형건물개방형서울특별시 용산구 한치과의원 건물 주차장한치과37.54589126.976959
66용산구연면적 1000㎡ 이상 대형건물폐쇄형서울특별시 용산구 LS용산타워 주차장㈜하나은행37.528002126.967632
67용산구연면적 1000㎡ 이상 대형건물폐쇄형서울특별시 용산구 용산더프라임 업무동 지하 1층용산더프라임37.540259126.969626
68용산구대학교개방형서울특별시 용산구 한국폴리텍대학 정수캠퍼스한국폴리텍대학37.529136126.996483
69용산구대학교개방형서울특별시 용산구 한국폴리텍대학 정수캠퍼스한국폴리텍대학37.52871126.996226
70용산구대학교개방형서울특별시 용산구 한국폴리텍대학 정수캠퍼스한국폴리텍대학37.529323126.995976
71용산구대학교개방형서울특별시 용산구 한국폴리텍대학 정수캠퍼스한국폴리텍대학37.529799126.996498