Overview

Dataset statistics

Number of variables4
Number of observations154
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory34.9 B

Variable types

Text2
Numeric2

Dataset

Description대구광역시 동구_인터넷 컴퓨터게임시설 제공업체 현황_20201117
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=3055763&dataSetDetailId=30557631b737415d99c1&provdMethod=FILE

Alerts

시설면적 is highly overall correlated with 게임기수High correlation
게임기수 is highly overall correlated with 시설면적High correlation

Reproduction

Analysis started2024-04-19 05:17:01.809734
Analysis finished2024-04-19 05:17:02.370851
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

Distinct147
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-19T14:17:02.539309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length12
Mean length6.474026
Min length2

Characters and Unicode

Total characters997
Distinct characters203
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)92.2%

Sample

1st row컴온피씨방
2nd row점프(JUMP)
3rd rowNU PC
4th row더원피시방
5th row아우토반PC방
ValueCountFrequency (%)
pc 15
 
7.3%
pc방 8
 
3.9%
이노스페이스 4
 
1.9%
럭키pc 3
 
1.5%
곰pc방 3
 
1.5%
아쿠아 2
 
1.0%
효목점 2
 
1.0%
잭팟pc 2
 
1.0%
맘모스 2
 
1.0%
앤유(nu 2
 
1.0%
Other values (158) 163
79.1%
2024-04-19T14:17:02.934796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 127
 
12.7%
C 123
 
12.3%
방 73
 
7.3%
52
 
5.2%
스 41
 
4.1%
이 39
 
3.9%
점 25
 
2.5%
피 24
 
2.4%
( 14
 
1.4%
) 14
 
1.4%
Other values (193) 465
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 608
61.0%
Uppercase Letter 281
28.2%
Space Separator 52
 
5.2%
Lowercase Letter 24
 
2.4%
Open Punctuation 14
 
1.4%
Close Punctuation 14
 
1.4%
Decimal Number 3
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 73
 
12.0%
스 41
 
6.7%
이 39
 
6.4%
점 25
 
4.1%
피 24
 
3.9%
대 13
 
2.1%
아 13
 
2.1%
씨 11
 
1.8%
구 10
 
1.6%
시 10
 
1.6%
Other values (160) 349
57.4%
Uppercase Letter
ValueCountFrequency (%)
P 127
45.2%
C 123
43.8%
N 4
 
1.4%
U 4
 
1.4%
O 3
 
1.1%
G 3
 
1.1%
D 2
 
0.7%
E 2
 
0.7%
T 2
 
0.7%
A 2
 
0.7%
Other values (9) 9
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
n 5
20.8%
e 4
16.7%
o 4
16.7%
u 3
12.5%
c 3
12.5%
p 2
 
8.3%
s 2
 
8.3%
z 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
3 1
33.3%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 608
61.0%
Latin 305
30.6%
Common 84
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 73
 
12.0%
스 41
 
6.7%
이 39
 
6.4%
점 25
 
4.1%
피 24
 
3.9%
대 13
 
2.1%
아 13
 
2.1%
씨 11
 
1.8%
구 10
 
1.6%
시 10
 
1.6%
Other values (160) 349
57.4%
Latin
ValueCountFrequency (%)
P 127
41.6%
C 123
40.3%
n 5
 
1.6%
e 4
 
1.3%
o 4
 
1.3%
N 4
 
1.3%
U 4
 
1.3%
u 3
 
1.0%
O 3
 
1.0%
c 3
 
1.0%
Other values (17) 25
 
8.2%
Common
ValueCountFrequency (%)
52
61.9%
( 14
 
16.7%
) 14
 
16.7%
2 2
 
2.4%
3 1
 
1.2%
. 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 608
61.0%
ASCII 389
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 127
32.6%
C 123
31.6%
52
13.4%
( 14
 
3.6%
) 14
 
3.6%
n 5
 
1.3%
e 4
 
1.0%
o 4
 
1.0%
N 4
 
1.0%
U 4
 
1.0%
Other values (23) 38
 
9.8%
Hangul
ValueCountFrequency (%)
방 73
 
12.0%
스 41
 
6.7%
이 39
 
6.4%
점 25
 
4.1%
피 24
 
3.9%
대 13
 
2.1%
아 13
 
2.1%
씨 11
 
1.8%
구 10
 
1.6%
시 10
 
1.6%
Other values (160) 349
57.4%

영업소소재지(도로명)
Text

Distinct153
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-19T14:17:03.196022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length39
Mean length27.915584
Min length20

Characters and Unicode

Total characters4299
Distinct characters116
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique152 ?
Unique (%)98.7%

Sample

1st row대구광역시 동구 동촌로 223, 2층 (방촌동)
2nd row대구광역시 동구 신암로 98, 지하1층 (신암동)
3rd row대구광역시 동구 아양로 46, 3층 (신암동)
4th row대구광역시 동구 화랑로 77, 3층 (효목동)
5th row대구광역시 동구 팔공로101길 39, 5층 (지묘동, 대영빌딩)
ValueCountFrequency (%)
대구광역시 154
 
16.5%
동구 154
 
16.5%
1층 45
 
4.8%
2층 36
 
3.9%
효목동 31
 
3.3%
신암동 27
 
2.9%
3층 20
 
2.1%
신천동 19
 
2.0%
4층 16
 
1.7%
방촌동 15
 
1.6%
Other values (220) 416
44.6%
2024-04-19T14:17:03.588449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
792
18.4%
동 365
 
8.5%
구 308
 
7.2%
대 165
 
3.8%
1 163
 
3.8%
역 158
 
3.7%
로 157
 
3.7%
시 155
 
3.6%
( 154
 
3.6%
광 154
 
3.6%
Other values (106) 1728
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2347
54.6%
Space Separator 792
 
18.4%
Decimal Number 687
 
16.0%
Open Punctuation 154
 
3.6%
Close Punctuation 154
 
3.6%
Other Punctuation 144
 
3.3%
Dash Punctuation 19
 
0.4%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 365
15.6%
구 308
13.1%
대 165
 
7.0%
역 158
 
6.7%
로 157
 
6.7%
시 155
 
6.6%
광 154
 
6.6%
층 128
 
5.5%
신 73
 
3.1%
길 63
 
2.7%
Other values (88) 621
26.5%
Decimal Number
ValueCountFrequency (%)
1 163
23.7%
2 122
17.8%
3 89
13.0%
4 68
9.9%
0 65
 
9.5%
5 49
 
7.1%
6 43
 
6.3%
7 33
 
4.8%
9 31
 
4.5%
8 24
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 143
99.3%
. 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
H 1
50.0%
Space Separator
ValueCountFrequency (%)
792
100.0%
Open Punctuation
ValueCountFrequency (%)
( 154
100.0%
Close Punctuation
ValueCountFrequency (%)
) 154
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2347
54.6%
Common 1950
45.4%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 365
15.6%
구 308
13.1%
대 165
 
7.0%
역 158
 
6.7%
로 157
 
6.7%
시 155
 
6.6%
광 154
 
6.6%
층 128
 
5.5%
신 73
 
3.1%
길 63
 
2.7%
Other values (88) 621
26.5%
Common
ValueCountFrequency (%)
792
40.6%
1 163
 
8.4%
( 154
 
7.9%
) 154
 
7.9%
, 143
 
7.3%
2 122
 
6.3%
3 89
 
4.6%
4 68
 
3.5%
0 65
 
3.3%
5 49
 
2.5%
Other values (6) 151
 
7.7%
Latin
ValueCountFrequency (%)
D 1
50.0%
H 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2347
54.6%
ASCII 1952
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
792
40.6%
1 163
 
8.4%
( 154
 
7.9%
) 154
 
7.9%
, 143
 
7.3%
2 122
 
6.2%
3 89
 
4.6%
4 68
 
3.5%
0 65
 
3.3%
5 49
 
2.5%
Other values (8) 153
 
7.8%
Hangul
ValueCountFrequency (%)
동 365
15.6%
구 308
13.1%
대 165
 
7.0%
역 158
 
6.7%
로 157
 
6.7%
시 155
 
6.6%
광 154
 
6.6%
층 128
 
5.5%
신 73
 
3.1%
길 63
 
2.7%
Other values (88) 621
26.5%

시설면적
Real number (ℝ)

HIGH CORRELATION 

Distinct141
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean154.43071
Minimum17.5
Maximum439.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-19T14:17:03.731717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17.5
5-th percentile25.2545
Q150.015
median163.145
Q3242.28
95-th percentile303.432
Maximum439.29
Range421.79
Interquartile range (IQR)192.265

Descriptive statistics

Standard deviation101.98229
Coefficient of variation (CV)0.66037567
Kurtosis-0.99175636
Mean154.43071
Median Absolute Deviation (MAD)99.09
Skewness0.22235326
Sum23782.33
Variance10400.387
MonotonicityNot monotonic
2024-04-19T14:17:03.857448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 7
 
4.5%
30.0 3
 
1.9%
65.7 3
 
1.9%
60.0 2
 
1.3%
61.5 2
 
1.3%
35.0 2
 
1.3%
133.93 1
 
0.6%
299.47 1
 
0.6%
158.71 1
 
0.6%
62.4 1
 
0.6%
Other values (131) 131
85.1%
ValueCountFrequency (%)
17.5 1
0.6%
17.72 1
0.6%
20.16 1
0.6%
21.18 1
0.6%
22.0 1
0.6%
22.1 1
0.6%
22.44 1
0.6%
23.87 1
0.6%
26.0 1
0.6%
26.44 1
0.6%
ValueCountFrequency (%)
439.29 1
0.6%
404.32 1
0.6%
346.0 1
0.6%
335.04 1
0.6%
333.19 1
0.6%
318.09 1
0.6%
311.91 1
0.6%
310.79 1
0.6%
299.47 1
0.6%
299.08 1
0.6%

게임기수
Real number (ℝ)

HIGH CORRELATION 

Distinct62
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.928571
Minimum1
Maximum166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-19T14:17:03.974363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q16
median59.5
Q382
95-th percentile114.35
Maximum166
Range165
Interquartile range (IQR)76

Descriptive statistics

Standard deviation40.165199
Coefficient of variation (CV)0.77347014
Kurtosis-1.0388343
Mean51.928571
Median Absolute Deviation (MAD)39.5
Skewness0.19104716
Sum7997
Variance1613.2432
MonotonicityNot monotonic
2024-04-19T14:17:04.097541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 23
 
14.9%
6 11
 
7.1%
4 8
 
5.2%
60 7
 
4.5%
50 6
 
3.9%
7 6
 
3.9%
70 5
 
3.2%
99 5
 
3.2%
100 5
 
3.2%
102 4
 
2.6%
Other values (52) 74
48.1%
ValueCountFrequency (%)
1 1
 
0.6%
3 2
 
1.3%
4 8
 
5.2%
5 23
14.9%
6 11
7.1%
7 6
 
3.9%
9 1
 
0.6%
10 2
 
1.3%
22 1
 
0.6%
27 1
 
0.6%
ValueCountFrequency (%)
166 1
0.6%
141 1
0.6%
130 1
0.6%
125 1
0.6%
118 1
0.6%
117 1
0.6%
116 1
0.6%
115 1
0.6%
114 1
0.6%
106 1
0.6%

Interactions

2024-04-19T14:17:02.109040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:17:01.986451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:17:02.175147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:17:02.045206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:17:04.177955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설면적게임기수
시설면적1.0000.831
게임기수0.8311.000
2024-04-19T14:17:04.247622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설면적게임기수
시설면적1.0000.936
게임기수0.9361.000

Missing values

2024-04-19T14:17:02.268296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:17:02.339665image/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

상호영업소소재지(도로명)시설면적게임기수
0컴온피씨방대구광역시 동구 동촌로 223, 2층 (방촌동)146.1548
1점프(JUMP)대구광역시 동구 신암로 98, 지하1층 (신암동)311.91115
2NU PC대구광역시 동구 아양로 46, 3층 (신암동)439.29130
3더원피시방대구광역시 동구 화랑로 77, 3층 (효목동)251.38102
4아우토반PC방대구광역시 동구 팔공로101길 39, 5층 (지묘동, 대영빌딩)234.366
5우리동네PC방대구광역시 동구 해동로 47 (지저동,가동)132.4850
6버니PC방대구광역시 동구 효서로 23, 2층 (효목동)226.675
7아이넥스PC대구광역시 동구 아양로 170, 2층 (신암동)173.0753
8엔조이락 PC방대구광역시 동구 율하동로24길 35 (신기동,외 4필지(293-2,286-6,290.12,296))299.0877
9논스톱PC방대구광역시 동구 아양로50길 30, 2층 (효목동)160.066
상호영업소소재지(도로명)시설면적게임기수
144복돼지 PC방대구광역시 동구 율하동로17길 42, 1층 (율하동)26.954
145대박 PC대구광역시 동구 반야월로 363, 1층 (신서동)17.724
146아쿠아 PC대구광역시 동구 효목로5길 6, 1층 (효목동)37.85
147레드PC 대구신암본점대구광역시 동구 아양로 40, 유성빌딩 3층 (신암동)249.5699
148욜로 PC방대구광역시 동구 아양로 50, 4층 (신암동)219.66103
149에이스 PC대구광역시 동구 안심로 283, 천마빌딩 1층 101호 (동호동)34.376
150맘모스 피씨대구광역시 동구 효신로 28, 2층 (효목동)210.4270
151아쿠아 PC대구광역시 동구 동부로30길 81, 1층 (신천동)31.84
152킹 PC대구광역시 동구 동부로26길 5, 부띠끄시티 테라스 1층 110호 (신천동)31.15
153우승 PC대구광역시 동구 안심로41길 47, 1동 1층 (서호동)28.55