Overview

Dataset statistics

Number of variables3
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory28.3 B

Variable types

Numeric1
Text2

Dataset

Description서울특별시 용산구 당구장 현황에 대한 데이터로 연번, 당구장 상호, 당구장 시설 주소 항목에 대한 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/3077841/fileData.do

Alerts

업종 has unique valuesUnique
상호 has unique valuesUnique
시설주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:19:51.933396
Analysis finished2023-12-12 06:19:52.411642
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Real number (ℝ)

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
2023-12-12T15:19:52.523337image/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
2023-12-12T15:19:52.703222image/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%

상호
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T15:19:52.974709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length8
Mean length5.975
Min length2

Characters and Unicode

Total characters239
Distinct characters86
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row금강
2nd row신한당구장
3rd row새문화 당구클럽
4th row그린당구장
5th row킹당구장
ValueCountFrequency (%)
당구장 8
 
15.4%
당구클럽 2
 
3.8%
25시 2
 
3.8%
순이네당구장 1
 
1.9%
jj빌리어드 1
 
1.9%
갬블러당구장 1
 
1.9%
허리우드당구클럽 1
 
1.9%
노블 1
 
1.9%
폴리당구클럽 1
 
1.9%
롯데당구장 1
 
1.9%
Other values (33) 33
63.5%
2023-12-12T15:19:53.464625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 37
 
15.5%
당 36
 
15.1%
장 28
 
11.7%
12
 
5.0%
럽 8
 
3.3%
클 8
 
3.3%
드 5
 
2.1%
리 5
 
2.1%
2 3
 
1.3%
스 3
 
1.3%
Other values (76) 94
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 202
84.5%
Uppercase Letter 19
 
7.9%
Space Separator 12
 
5.0%
Decimal Number 6
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 37
18.3%
당 36
17.8%
장 28
13.9%
럽 8
 
4.0%
클 8
 
4.0%
드 5
 
2.5%
리 5
 
2.5%
스 3
 
1.5%
시 2
 
1.0%
비 2
 
1.0%
Other values (61) 68
33.7%
Uppercase Letter
ValueCountFrequency (%)
O 3
15.8%
M 2
10.5%
C 2
10.5%
S 2
10.5%
B 2
10.5%
J 2
10.5%
R 1
 
5.3%
U 1
 
5.3%
L 1
 
5.3%
A 1
 
5.3%
Other values (2) 2
10.5%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
5 3
50.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 202
84.5%
Latin 19
 
7.9%
Common 18
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 37
18.3%
당 36
17.8%
장 28
13.9%
럽 8
 
4.0%
클 8
 
4.0%
드 5
 
2.5%
리 5
 
2.5%
스 3
 
1.5%
시 2
 
1.0%
비 2
 
1.0%
Other values (61) 68
33.7%
Latin
ValueCountFrequency (%)
O 3
15.8%
M 2
10.5%
C 2
10.5%
S 2
10.5%
B 2
10.5%
J 2
10.5%
R 1
 
5.3%
U 1
 
5.3%
L 1
 
5.3%
A 1
 
5.3%
Other values (2) 2
10.5%
Common
ValueCountFrequency (%)
12
66.7%
2 3
 
16.7%
5 3
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 202
84.5%
ASCII 37
 
15.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 37
18.3%
당 36
17.8%
장 28
13.9%
럽 8
 
4.0%
클 8
 
4.0%
드 5
 
2.5%
리 5
 
2.5%
스 3
 
1.5%
시 2
 
1.0%
비 2
 
1.0%
Other values (61) 68
33.7%
ASCII
ValueCountFrequency (%)
12
32.4%
2 3
 
8.1%
5 3
 
8.1%
O 3
 
8.1%
M 2
 
5.4%
C 2
 
5.4%
S 2
 
5.4%
B 2
 
5.4%
J 2
 
5.4%
R 1
 
2.7%
Other values (5) 5
13.5%

시설주소
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T15:19:53.780547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length23.325
Min length19

Characters and Unicode

Total characters933
Distinct characters65
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row서울특별시 용산구 한강로1가 197
2nd row서울특별시 용산구 서계동 264-15 지상2층
3rd row서울특별시 용산구 갈월동 87-14
4th row서울특별시 용산구 한강로3가 40-152 지상3층
5th row서울특별시 용산구 동자동 12 벽산빌딩 지하2층
ValueCountFrequency (%)
서울특별시 40
21.4%
용산구 40
21.4%
3층 5
 
2.7%
지하1층 4
 
2.1%
갈월동 4
 
2.1%
동자동 4
 
2.1%
2층 3
 
1.6%
한강로1가 3
 
1.6%
한강로3가 3
 
1.6%
보광동 3
 
1.6%
Other values (68) 78
41.7%
2023-12-12T15:19:54.242011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
187
20.0%
산 43
 
4.6%
용 43
 
4.6%
서 42
 
4.5%
구 41
 
4.4%
1 41
 
4.4%
시 40
 
4.3%
별 40
 
4.3%
울 40
 
4.3%
특 40
 
4.3%
Other values (55) 376
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 522
55.9%
Space Separator 187
 
20.0%
Decimal Number 186
 
19.9%
Dash Punctuation 36
 
3.9%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 43
 
8.2%
용 43
 
8.2%
서 42
 
8.0%
구 41
 
7.9%
시 40
 
7.7%
별 40
 
7.7%
울 40
 
7.7%
특 40
 
7.7%
동 33
 
6.3%
층 20
 
3.8%
Other values (41) 140
26.8%
Decimal Number
ValueCountFrequency (%)
1 41
22.0%
2 31
16.7%
3 31
16.7%
4 18
9.7%
6 16
 
8.6%
5 16
 
8.6%
9 14
 
7.5%
8 8
 
4.3%
0 7
 
3.8%
7 4
 
2.2%
Space Separator
ValueCountFrequency (%)
187
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 522
55.9%
Common 411
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 43
 
8.2%
용 43
 
8.2%
서 42
 
8.0%
구 41
 
7.9%
시 40
 
7.7%
별 40
 
7.7%
울 40
 
7.7%
특 40
 
7.7%
동 33
 
6.3%
층 20
 
3.8%
Other values (41) 140
26.8%
Common
ValueCountFrequency (%)
187
45.5%
1 41
 
10.0%
- 36
 
8.8%
2 31
 
7.5%
3 31
 
7.5%
4 18
 
4.4%
6 16
 
3.9%
5 16
 
3.9%
9 14
 
3.4%
8 8
 
1.9%
Other values (4) 13
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 522
55.9%
ASCII 411
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
187
45.5%
1 41
 
10.0%
- 36
 
8.8%
2 31
 
7.5%
3 31
 
7.5%
4 18
 
4.4%
6 16
 
3.9%
5 16
 
3.9%
9 14
 
3.4%
8 8
 
1.9%
Other values (4) 13
 
3.2%
Hangul
ValueCountFrequency (%)
산 43
 
8.2%
용 43
 
8.2%
서 42
 
8.0%
구 41
 
7.9%
시 40
 
7.7%
별 40
 
7.7%
울 40
 
7.7%
특 40
 
7.7%
동 33
 
6.3%
층 20
 
3.8%
Other values (41) 140
26.8%

Interactions

2023-12-12T15:19:52.123955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:19:54.356399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종상호시설주소
업종1.0001.0001.000
상호1.0001.0001.000
시설주소1.0001.0001.000

Missing values

2023-12-12T15:19:52.261004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:19:52.370789image/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

업종상호시설주소
01금강서울특별시 용산구 한강로1가 197
12신한당구장서울특별시 용산구 서계동 264-15 지상2층
23새문화 당구클럽서울특별시 용산구 갈월동 87-14
34그린당구장서울특별시 용산구 한강로3가 40-152 지상3층
45킹당구장서울특별시 용산구 동자동 12 벽산빌딩 지하2층
5625시 당구클럽서울특별시 용산구 원효로2가 96-8 지하1층
67비비엠25당구장서울특별시 용산구 갈월동 93-36
78큐당구장서울특별시 용산구 동자동 43-59 지하1층
89준 당구장서울특별시 용산구 보광동 260-3
910타워당구장서울특별시 용산구 청파동3가 111-9
업종상호시설주소
303125시 당구장서울특별시 용산구 한남동 631-5
3132순이네당구장서울특별시 용산구 보광동 259-1
3233원 당구장서울특별시 용산구 후암동 105-3
3334버드당구장서울특별시 용산구 용산동2가 1-531
3435테라스당구클럽서울특별시 용산구 한남동 633-3 제일빌딩
3536GOON CAROM CLUB서울특별시 용산구 효창동 5-116
3637삼거리당구장서울특별시 용산구 이태원동 225-1 혜천상가 5층
3738매니아당구장서울특별시 용산구 동자동 19-33 여명빌딩
3839마이빌리어즈카페서울특별시 용산구 용산동2가 1-206
3940드래곤 당구장서울특별시 용산구 한강로3가 40-141 3층