Overview

Dataset statistics

Number of variables8
Number of observations71
Missing cells8
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory68.9 B

Variable types

Categorical2
Text3
Numeric3

Dataset

Description부산광역시동래구_게임장_현황_20230828
Author부산광역시 동래구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15120840

Alerts

제공게임물구분 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 시설면적 and 1 other fieldsHigh correlation
게임기수 is highly overall correlated with 시설면적High correlation
시설면적 is highly overall correlated with 게임기수 and 1 other fieldsHigh correlation
우편번호 has 7 (9.9%) missing valuesMissing
게임기수 has 1 (1.4%) missing valuesMissing

Reproduction

Analysis started2023-12-10 16:50:42.830334
Analysis finished2023-12-10 16:50:44.624418
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size700.0 B
청소년게임제공업
26 
인터넷컴퓨터게임시설제공업
25 
일반게임제공업
11 
복합유통게임제공업
9 

Length

Max length13
Median length9
Mean length9.7323944
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청소년게임제공업 26
36.6%
인터넷컴퓨터게임시설제공업 25
35.2%
일반게임제공업 11
15.5%
복합유통게임제공업 9
 
12.7%

Length

2023-12-11T01:50:44.695834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:50:44.802498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청소년게임제공업 26
36.6%
인터넷컴퓨터게임시설제공업 25
35.2%
일반게임제공업 11
15.5%
복합유통게임제공업 9
 
12.7%

상호명
Text

Distinct68
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T01:50:45.071127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length11
Mean length7.3661972
Min length2

Characters and Unicode

Total characters523
Distinct characters142
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)91.5%

Sample

1st row홀릭PC방
2nd row스페셜 PC방
3rd rowOX PC 금정시장점
4th row아이파크PC방
5th row제로스PC
ValueCountFrequency (%)
pc 7
 
6.1%
ox 6
 
5.2%
pc방 5
 
4.3%
게임랜드 4
 
3.5%
부산미남역점 2
 
1.7%
zone 2
 
1.7%
욜로pc방 2
 
1.7%
수안점 2
 
1.7%
뽑기어때 2
 
1.7%
vams 2
 
1.7%
Other values (79) 81
70.4%
2023-12-11T01:50:45.580471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
 
8.4%
P 31
 
5.9%
C 31
 
5.9%
드 19
 
3.6%
게 18
 
3.4%
방 18
 
3.4%
임 18
 
3.4%
점 15
 
2.9%
랜 15
 
2.9%
뽑 13
 
2.5%
Other values (132) 301
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 352
67.3%
Uppercase Letter 120
 
22.9%
Space Separator 44
 
8.4%
Lowercase Letter 6
 
1.1%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
드 19
 
5.4%
게 18
 
5.1%
방 18
 
5.1%
임 18
 
5.1%
점 15
 
4.3%
랜 15
 
4.3%
뽑 13
 
3.7%
기 13
 
3.7%
인 8
 
2.3%
아 7
 
2.0%
Other values (103) 208
59.1%
Uppercase Letter
ValueCountFrequency (%)
P 31
25.8%
C 31
25.8%
O 10
 
8.3%
X 6
 
5.0%
B 5
 
4.2%
V 4
 
3.3%
A 4
 
3.3%
I 3
 
2.5%
N 3
 
2.5%
E 3
 
2.5%
Other values (12) 20
16.7%
Lowercase Letter
ValueCountFrequency (%)
n 2
33.3%
e 1
16.7%
o 1
16.7%
y 1
16.7%
u 1
16.7%
Space Separator
ValueCountFrequency (%)
44
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 352
67.3%
Latin 126
 
24.1%
Common 45
 
8.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
드 19
 
5.4%
게 18
 
5.1%
방 18
 
5.1%
임 18
 
5.1%
점 15
 
4.3%
랜 15
 
4.3%
뽑 13
 
3.7%
기 13
 
3.7%
인 8
 
2.3%
아 7
 
2.0%
Other values (103) 208
59.1%
Latin
ValueCountFrequency (%)
P 31
24.6%
C 31
24.6%
O 10
 
7.9%
X 6
 
4.8%
B 5
 
4.0%
V 4
 
3.2%
A 4
 
3.2%
I 3
 
2.4%
N 3
 
2.4%
E 3
 
2.4%
Other values (17) 26
20.6%
Common
ValueCountFrequency (%)
44
97.8%
3 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 352
67.3%
ASCII 171
32.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
25.7%
P 31
18.1%
C 31
18.1%
O 10
 
5.8%
X 6
 
3.5%
B 5
 
2.9%
V 4
 
2.3%
A 4
 
2.3%
I 3
 
1.8%
N 3
 
1.8%
Other values (19) 30
17.5%
Hangul
ValueCountFrequency (%)
드 19
 
5.4%
게 18
 
5.1%
방 18
 
5.1%
임 18
 
5.1%
점 15
 
4.3%
랜 15
 
4.3%
뽑 13
 
3.7%
기 13
 
3.7%
인 8
 
2.3%
아 7
 
2.0%
Other values (103) 208
59.1%

우편번호
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)64.1%
Missing7
Missing (%)9.9%
Infinite0
Infinite (%)0.0%
Mean47812.766
Minimum47710
Maximum47900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T01:50:45.775213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47710
5-th percentile47712
Q147784.75
median47821
Q347853
95-th percentile47890.85
Maximum47900
Range190
Interquartile range (IQR)68.25

Descriptive statistics

Standard deviation52.651517
Coefficient of variation (CV)0.0011012021
Kurtosis-0.67677693
Mean47812.766
Median Absolute Deviation (MAD)36.5
Skewness-0.36275819
Sum3060017
Variance2772.1823
MonotonicityNot monotonic
2023-12-11T01:50:45.954460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
47837 7
 
9.9%
47865 3
 
4.2%
47786 3
 
4.2%
47712 3
 
4.2%
47772 3
 
4.2%
47866 3
 
4.2%
47760 2
 
2.8%
47827 2
 
2.8%
47839 2
 
2.8%
47851 2
 
2.8%
Other values (31) 34
47.9%
(Missing) 7
 
9.9%
ValueCountFrequency (%)
47710 1
 
1.4%
47711 1
 
1.4%
47712 3
4.2%
47715 1
 
1.4%
47736 1
 
1.4%
47738 1
 
1.4%
47744 1
 
1.4%
47760 2
2.8%
47761 1
 
1.4%
47772 3
4.2%
ValueCountFrequency (%)
47900 2
2.8%
47896 1
 
1.4%
47891 1
 
1.4%
47890 1
 
1.4%
47877 1
 
1.4%
47875 1
 
1.4%
47867 1
 
1.4%
47866 3
4.2%
47865 3
4.2%
47864 1
 
1.4%

영업소소재지(도로명)
Text

Distinct70
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T01:50:46.459278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length38
Mean length31.084507
Min length22

Characters and Unicode

Total characters2207
Distinct characters116
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)97.2%

Sample

1st row부산광역시 동래구 안락로 74, 2층 (안락동)
2nd row부산광역시 동래구 반송로273번길 7 (명장동,(지하1층))
3rd row부산광역시 동래구 여고북로 160, 3층 (사직동)
4th row부산광역시 동래구 중앙대로1367번길 48 (온천동,(3층)(금연구역설치)(PC대))
5th row부산광역시 동래구 사직북로 1 (사직동)
ValueCountFrequency (%)
부산광역시 71
 
16.1%
동래구 71
 
16.1%
1층 21
 
4.8%
온천동 20
 
4.5%
안락동 17
 
3.9%
2층 15
 
3.4%
사직동 14
 
3.2%
3층 8
 
1.8%
명장동 8
 
1.8%
사직북로 7
 
1.6%
Other values (123) 188
42.7%
2023-12-11T01:50:47.090899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
371
 
16.8%
동 149
 
6.8%
1 78
 
3.5%
) 78
 
3.5%
시 78
 
3.5%
( 78
 
3.5%
광 72
 
3.3%
역 72
 
3.3%
래 72
 
3.3%
구 72
 
3.3%
Other values (106) 1087
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1271
57.6%
Space Separator 371
 
16.8%
Decimal Number 321
 
14.5%
Close Punctuation 78
 
3.5%
Open Punctuation 78
 
3.5%
Other Punctuation 64
 
2.9%
Uppercase Letter 14
 
0.6%
Dash Punctuation 9
 
0.4%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 149
 
11.7%
시 78
 
6.1%
광 72
 
5.7%
역 72
 
5.7%
래 72
 
5.7%
구 72
 
5.7%
부 71
 
5.6%
산 71
 
5.6%
로 71
 
5.6%
층 61
 
4.8%
Other values (81) 482
37.9%
Decimal Number
ValueCountFrequency (%)
1 78
24.3%
2 63
19.6%
3 39
12.1%
8 29
 
9.0%
4 25
 
7.8%
0 21
 
6.5%
5 21
 
6.5%
6 19
 
5.9%
7 13
 
4.0%
9 13
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
S 3
21.4%
K 3
21.4%
A 2
14.3%
U 1
 
7.1%
H 1
 
7.1%
B 1
 
7.1%
P 1
 
7.1%
C 1
 
7.1%
Y 1
 
7.1%
Space Separator
ValueCountFrequency (%)
371
100.0%
Close Punctuation
ValueCountFrequency (%)
) 78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 78
100.0%
Other Punctuation
ValueCountFrequency (%)
, 64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1271
57.6%
Common 922
41.8%
Latin 14
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 149
 
11.7%
시 78
 
6.1%
광 72
 
5.7%
역 72
 
5.7%
래 72
 
5.7%
구 72
 
5.7%
부 71
 
5.6%
산 71
 
5.6%
로 71
 
5.6%
층 61
 
4.8%
Other values (81) 482
37.9%
Common
ValueCountFrequency (%)
371
40.2%
1 78
 
8.5%
) 78
 
8.5%
( 78
 
8.5%
, 64
 
6.9%
2 63
 
6.8%
3 39
 
4.2%
8 29
 
3.1%
4 25
 
2.7%
0 21
 
2.3%
Other values (6) 76
 
8.2%
Latin
ValueCountFrequency (%)
S 3
21.4%
K 3
21.4%
A 2
14.3%
U 1
 
7.1%
H 1
 
7.1%
B 1
 
7.1%
P 1
 
7.1%
C 1
 
7.1%
Y 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1271
57.6%
ASCII 936
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
371
39.6%
1 78
 
8.3%
) 78
 
8.3%
( 78
 
8.3%
, 64
 
6.8%
2 63
 
6.7%
3 39
 
4.2%
8 29
 
3.1%
4 25
 
2.7%
0 21
 
2.2%
Other values (15) 90
 
9.6%
Hangul
ValueCountFrequency (%)
동 149
 
11.7%
시 78
 
6.1%
광 72
 
5.7%
역 72
 
5.7%
래 72
 
5.7%
구 72
 
5.7%
부 71
 
5.6%
산 71
 
5.6%
로 71
 
5.6%
층 61
 
4.8%
Other values (81) 482
37.9%

영업소소재지(지번)
Text

Distinct68
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T01:50:47.449268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length39
Mean length22.605634
Min length18

Characters and Unicode

Total characters1605
Distinct characters89
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)91.5%

Sample

1st row부산광역시 동래구 안락동 448-2
2nd row부산광역시 동래구 명장동 29-2 (지하1층)
3rd row부산광역시 동래구 사직동 140-8
4th row부산광역시 동래구 온천동 751-24 (3층)(금연구역설치)(PC대)
5th row부산광역시 동래구 사직동 92-7
ValueCountFrequency (%)
부산광역시 71
22.7%
동래구 71
22.7%
온천동 22
 
7.0%
안락동 18
 
5.8%
사직동 14
 
4.5%
명장동 10
 
3.2%
명륜동 7
 
2.2%
파크 2
 
0.6%
1248-2 2
 
0.6%
153-8 2
 
0.6%
Other values (86) 94
30.0%
2023-12-11T01:50:48.133471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
313
19.5%
동 146
 
9.1%
광 72
 
4.5%
역 72
 
4.5%
구 72
 
4.5%
부 71
 
4.4%
산 71
 
4.4%
시 71
 
4.4%
래 71
 
4.4%
- 67
 
4.2%
Other values (79) 579
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 879
54.8%
Decimal Number 320
 
19.9%
Space Separator 313
 
19.5%
Dash Punctuation 67
 
4.2%
Uppercase Letter 12
 
0.7%
Close Punctuation 7
 
0.4%
Open Punctuation 7
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 146
16.6%
광 72
 
8.2%
역 72
 
8.2%
구 72
 
8.2%
부 71
 
8.1%
산 71
 
8.1%
시 71
 
8.1%
래 71
 
8.1%
천 23
 
2.6%
온 22
 
2.5%
Other values (57) 188
21.4%
Decimal Number
ValueCountFrequency (%)
1 55
17.2%
4 51
15.9%
2 37
11.6%
3 35
10.9%
5 29
9.1%
8 27
8.4%
6 26
8.1%
9 24
7.5%
7 23
7.2%
0 13
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
S 3
25.0%
K 3
25.0%
H 1
 
8.3%
U 1
 
8.3%
B 1
 
8.3%
P 1
 
8.3%
C 1
 
8.3%
Y 1
 
8.3%
Space Separator
ValueCountFrequency (%)
313
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 879
54.8%
Common 714
44.5%
Latin 12
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 146
16.6%
광 72
 
8.2%
역 72
 
8.2%
구 72
 
8.2%
부 71
 
8.1%
산 71
 
8.1%
시 71
 
8.1%
래 71
 
8.1%
천 23
 
2.6%
온 22
 
2.5%
Other values (57) 188
21.4%
Common
ValueCountFrequency (%)
313
43.8%
- 67
 
9.4%
1 55
 
7.7%
4 51
 
7.1%
2 37
 
5.2%
3 35
 
4.9%
5 29
 
4.1%
8 27
 
3.8%
6 26
 
3.6%
9 24
 
3.4%
Other values (4) 50
 
7.0%
Latin
ValueCountFrequency (%)
S 3
25.0%
K 3
25.0%
H 1
 
8.3%
U 1
 
8.3%
B 1
 
8.3%
P 1
 
8.3%
C 1
 
8.3%
Y 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 879
54.8%
ASCII 726
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
313
43.1%
- 67
 
9.2%
1 55
 
7.6%
4 51
 
7.0%
2 37
 
5.1%
3 35
 
4.8%
5 29
 
4.0%
8 27
 
3.7%
6 26
 
3.6%
9 24
 
3.3%
Other values (12) 62
 
8.5%
Hangul
ValueCountFrequency (%)
동 146
16.6%
광 72
 
8.2%
역 72
 
8.2%
구 72
 
8.2%
부 71
 
8.1%
산 71
 
8.1%
시 71
 
8.1%
래 71
 
8.1%
천 23
 
2.6%
온 22
 
2.5%
Other values (57) 188
21.4%

제공게임물구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size700.0 B
전체이용가
50 
청소년이용불가
11 
<NA>
10 

Length

Max length7
Median length5
Mean length5.1690141
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row전체이용가
3rd row전체이용가
4th row전체이용가
5th row전체이용가

Common Values

ValueCountFrequency (%)
전체이용가 50
70.4%
청소년이용불가 11
 
15.5%
<NA> 10
 
14.1%

Length

2023-12-11T01:50:48.765985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:50:48.947493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체이용가 50
70.4%
청소년이용불가 11
 
15.5%
na 10
 
14.1%

게임기수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct44
Distinct (%)62.9%
Missing1
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean63.742857
Minimum4
Maximum173
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T01:50:49.124302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9.45
Q116.25
median71
Q397.5
95-th percentile132.35
Maximum173
Range169
Interquartile range (IQR)81.25

Descriptive statistics

Standard deviation42.517068
Coefficient of variation (CV)0.66700913
Kurtosis-0.78884839
Mean63.742857
Median Absolute Deviation (MAD)32
Skewness0.22097916
Sum4462
Variance1807.701
MonotonicityNot monotonic
2023-12-11T01:50:49.337007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
80 5
 
7.0%
100 4
 
5.6%
11 4
 
5.6%
40 4
 
5.6%
13 3
 
4.2%
91 3
 
4.2%
70 2
 
2.8%
10 2
 
2.8%
103 2
 
2.8%
16 2
 
2.8%
Other values (34) 39
54.9%
ValueCountFrequency (%)
4 1
 
1.4%
6 1
 
1.4%
8 1
 
1.4%
9 1
 
1.4%
10 2
2.8%
11 4
5.6%
13 3
4.2%
14 1
 
1.4%
15 2
2.8%
16 2
2.8%
ValueCountFrequency (%)
173 1
 
1.4%
149 1
 
1.4%
147 1
 
1.4%
140 1
 
1.4%
123 1
 
1.4%
120 1
 
1.4%
106 2
2.8%
104 2
2.8%
103 2
2.8%
100 4
5.6%

시설면적
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean195.22521
Minimum24.75
Maximum494.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T01:50:49.565341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24.75
5-th percentile29.175
Q165.785
median206.44
Q3293.83
95-th percentile373.825
Maximum494.97
Range470.22
Interquartile range (IQR)228.045

Descriptive statistics

Standard deviation121.96289
Coefficient of variation (CV)0.62472918
Kurtosis-0.808719
Mean195.22521
Median Absolute Deviation (MAD)90.86
Skewness0.11685927
Sum13860.99
Variance14874.946
MonotonicityNot monotonic
2023-12-11T01:50:49.792770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 2
 
2.8%
296.36 2
 
2.8%
261.97 2
 
2.8%
295.34 1
 
1.4%
86.9 1
 
1.4%
140.4 1
 
1.4%
28.35 1
 
1.4%
101.8 1
 
1.4%
36.6 1
 
1.4%
207.4 1
 
1.4%
Other values (58) 58
81.7%
ValueCountFrequency (%)
24.75 1
1.4%
26.21 1
1.4%
27.0 1
1.4%
28.35 1
1.4%
30.0 2
2.8%
31.95 1
1.4%
32.0 1
1.4%
32.67 1
1.4%
36.6 1
1.4%
37.0 1
1.4%
ValueCountFrequency (%)
494.97 1
1.4%
469.94 1
1.4%
396.69 1
1.4%
383.79 1
1.4%
363.86 1
1.4%
348.36 1
1.4%
344.32 1
1.4%
326.79 1
1.4%
317.83 1
1.4%
316.65 1
1.4%

Interactions

2023-12-11T01:50:44.082335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:43.497563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:43.759792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:44.168131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:43.580705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:43.881918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:44.250922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:43.671049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:43.985615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:50:50.048542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명상호명우편번호영업소소재지(도로명)영업소소재지(지번)제공게임물구분게임기수시설면적
업종명1.0000.9440.4040.6000.5691.0000.6940.713
상호명0.9441.0000.9871.0000.9981.0001.0000.987
우편번호0.4040.9871.0001.0001.0000.6360.4110.359
영업소소재지(도로명)0.6001.0001.0001.0001.0001.0001.0001.000
영업소소재지(지번)0.5690.9981.0001.0001.0001.0000.0000.920
제공게임물구분1.0001.0000.6361.0001.0001.0000.3350.515
게임기수0.6941.0000.4111.0000.0000.3351.0000.754
시설면적0.7130.9870.3591.0000.9200.5150.7541.000
2023-12-11T01:50:50.240944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제공게임물구분업종명
제공게임물구분1.0000.983
업종명0.9831.000
2023-12-11T01:50:50.429824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호게임기수시설면적업종명제공게임물구분
우편번호1.0000.0890.1260.1870.384
게임기수0.0891.0000.8390.4710.310
시설면적0.1260.8391.0000.5270.484
업종명0.1870.4710.5271.0000.983
제공게임물구분0.3840.3100.4840.9831.000

Missing values

2023-12-11T01:50:44.349543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:50:44.467825image/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.
2023-12-11T01:50:44.568978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업종명상호명우편번호영업소소재지(도로명)영업소소재지(지번)제공게임물구분게임기수시설면적
0인터넷컴퓨터게임시설제공업홀릭PC방47790부산광역시 동래구 안락로 74, 2층 (안락동)부산광역시 동래구 안락동 448-2<NA>70295.34
1인터넷컴퓨터게임시설제공업스페셜 PC방<NA>부산광역시 동래구 반송로273번길 7 (명장동,(지하1층))부산광역시 동래구 명장동 29-2 (지하1층)전체이용가81315.29
2인터넷컴퓨터게임시설제공업OX PC 금정시장점47830부산광역시 동래구 여고북로 160, 3층 (사직동)부산광역시 동래구 사직동 140-8전체이용가104247.5
3인터넷컴퓨터게임시설제공업아이파크PC방<NA>부산광역시 동래구 중앙대로1367번길 48 (온천동,(3층)(금연구역설치)(PC대))부산광역시 동래구 온천동 751-24 (3층)(금연구역설치)(PC대)전체이용가79249.61
4인터넷컴퓨터게임시설제공업제로스PC47865부산광역시 동래구 사직북로 1 (사직동)부산광역시 동래구 사직동 92-7전체이용가99295.49
5인터넷컴퓨터게임시설제공업ZEN PC방47787부산광역시 동래구 충렬대로359번길 38, 3층 (안락동)부산광역시 동래구 안락동 430-61전체이용가70237.8
6인터넷컴퓨터게임시설제공업아이파크PC방47890부산광역시 동래구 충렬대로428번길 26, 2층 (안락동)부산광역시 동래구 안락동 603-75<NA>82196.67
7인터넷컴퓨터게임시설제공업PC토랑 사직점47859부산광역시 동래구 사직북로 38, 2층 (사직동)부산광역시 동래구 사직동 25-30<NA>60193.84
8인터넷컴퓨터게임시설제공업마루PC방47736부산광역시 동래구 명륜로129번길 20, 우성빌딩 4층 (명륜동)부산광역시 동래구 명륜동 553-5 우성빌딩<NA>106253.86
9인터넷컴퓨터게임시설제공업PC ON47791부산광역시 동래구 안락로 92, 3층 (안락동)부산광역시 동래구 안락동 454-28전체이용가91236.53
업종명상호명우편번호영업소소재지(도로명)영업소소재지(지번)제공게임물구분게임기수시설면적
61청소년게임제공업JD인형뽑기47896부산광역시 동래구 충렬대로428번길 69-1, 1층 (안락동)부산광역시 동래구 안락동 245-31전체이용가1537.61
62청소년게임제공업VAMS47866부산광역시 동래구 사직북로 4, 사직동 자이언츠 파크 지하 1층 (사직동)부산광역시 동래구 사직동 93-6 사직동 자이언츠 파크전체이용가25296.36
63청소년게임제공업인형뽑기세상47772부산광역시 동래구 명장로20번길 26, 1층 (명장동)부산광역시 동래구 명장동 59-5전체이용가1578.82
64청소년게임제공업조아조아뽑기샵47865부산광역시 동래구 사직북로 13, 1층 (사직동)부산광역시 동래구 사직동 78-38전체이용가1859.0
65청소년게임제공업플레이샵 인형뽑기47772부산광역시 동래구 명안로85번길 48, 1층 (명장동)부산광역시 동래구 명장동 60-13전체이용가1132.0
66청소년게임제공업픽미픽미47900부산광역시 동래구 안남로 108, 화성코아 1층 105호 (안락동)부산광역시 동래구 안락동 243-1 화성코아전체이용가1676.93
67청소년게임제공업뽑기어때47839부산광역시 동래구 여고북로 77, 1층 (온천동)부산광역시 동래구 온천동 1377-34전체이용가937.52
68청소년게임제공업VAVI인형뽑기47789부산광역시 동래구 명안로 23 (안락동)부산광역시 동래구 안락동 447-19전체이용가427.0
69청소년게임제공업뽑기어때47787부산광역시 동래구 안락로 26, 1층 (안락동)부산광역시 동래구 안락동 429-38전체이용가1454.21
70청소년게임제공업피규어 뽑기47772부산광역시 동래구 명안로85번길 33, 1층 (명장동)부산광역시 동래구 명장동 61-3전체이용가1126.21