Overview

Dataset statistics

Number of variables7
Number of observations21
Missing cells11
Missing cells (%)7.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory65.3 B

Variable types

Numeric3
DateTime1
Text2
Categorical1

Dataset

Description부산광역시_동구_PC방현황_20220711
Author부산광역시 동구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3079099

Alerts

업종명 has constant value ""Constant
우편번호 has 11 (52.4%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique
영업소소재지(도로명) has unique valuesUnique
시설면적 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:51:57.490342
Analysis finished2023-12-10 16:51:59.805234
Duration2.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T01:51:59.920075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2023-12-11T01:52:00.140058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

등록(신고)일자
Date

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2007-09-19 00:00:00
Maximum2022-03-21 00:00:00
2023-12-11T01:52:00.344517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:52:00.520093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

상호
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T01:52:00.731991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length7.8571429
Min length4

Characters and Unicode

Total characters165
Distinct characters68
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

Unique21 ?
Unique (%)100.0%

Sample

1st row놀토피시존
2nd row아이비스PC방
3rd row랜드마크 PC
4th row라이또 PC방
5th row사이버포유pc
ValueCountFrequency (%)
pc 10
23.8%
ox 4
 
9.5%
pc방 2
 
4.8%
pc토랑 1
 
2.4%
동구청점 1
 
2.4%
초량역점 1
 
2.4%
범일동점 1
 
2.4%
스포플레이 1
 
2.4%
본점 1
 
2.4%
플러스피시방 1
 
2.4%
Other values (19) 19
45.2%
2023-12-11T01:52:01.103647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
12.7%
C 18
 
10.9%
P 17
 
10.3%
이 7
 
4.2%
O 6
 
3.6%
점 6
 
3.6%
방 5
 
3.0%
X 4
 
2.4%
드 3
 
1.8%
플 3
 
1.8%
Other values (58) 75
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87
52.7%
Uppercase Letter 50
30.3%
Space Separator 21
 
12.7%
Lowercase Letter 5
 
3.0%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 7
 
8.0%
점 6
 
6.9%
방 5
 
5.7%
드 3
 
3.4%
플 3
 
3.4%
스 3
 
3.4%
피 3
 
3.4%
시 3
 
3.4%
동 2
 
2.3%
토 2
 
2.3%
Other values (43) 50
57.5%
Uppercase Letter
ValueCountFrequency (%)
C 18
36.0%
P 17
34.0%
O 6
 
12.0%
X 4
 
8.0%
K 1
 
2.0%
J 1
 
2.0%
M 1
 
2.0%
A 1
 
2.0%
I 1
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
40.0%
p 2
40.0%
n 1
20.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87
52.7%
Latin 55
33.3%
Common 23
 
13.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 7
 
8.0%
점 6
 
6.9%
방 5
 
5.7%
드 3
 
3.4%
플 3
 
3.4%
스 3
 
3.4%
피 3
 
3.4%
시 3
 
3.4%
동 2
 
2.3%
토 2
 
2.3%
Other values (43) 50
57.5%
Latin
ValueCountFrequency (%)
C 18
32.7%
P 17
30.9%
O 6
 
10.9%
X 4
 
7.3%
c 2
 
3.6%
p 2
 
3.6%
n 1
 
1.8%
K 1
 
1.8%
J 1
 
1.8%
M 1
 
1.8%
Other values (2) 2
 
3.6%
Common
ValueCountFrequency (%)
21
91.3%
( 1
 
4.3%
) 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87
52.7%
ASCII 78
47.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
26.9%
C 18
23.1%
P 17
21.8%
O 6
 
7.7%
X 4
 
5.1%
c 2
 
2.6%
p 2
 
2.6%
n 1
 
1.3%
K 1
 
1.3%
J 1
 
1.3%
Other values (5) 5
 
6.4%
Hangul
ValueCountFrequency (%)
이 7
 
8.0%
점 6
 
6.9%
방 5
 
5.7%
드 3
 
3.4%
플 3
 
3.4%
스 3
 
3.4%
피 3
 
3.4%
시 3
 
3.4%
동 2
 
2.3%
토 2
 
2.3%
Other values (43) 50
57.5%

우편번호
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)80.0%
Missing11
Missing (%)52.4%
Infinite0
Infinite (%)0.0%
Mean48784.9
Minimum48726
Maximum48816
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T01:52:01.276294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48726
5-th percentile48734.1
Q148756.5
median48791
Q348815.75
95-th percentile48816
Maximum48816
Range90
Interquartile range (IQR)59.25

Descriptive statistics

Standard deviation34.235946
Coefficient of variation (CV)0.00070177342
Kurtosis-1.0421404
Mean48784.9
Median Absolute Deviation (MAD)25
Skewness-0.73925443
Sum487849
Variance1172.1
MonotonicityNot monotonic
2023-12-11T01:52:01.402133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
48816 3
 
14.3%
48744 1
 
4.8%
48788 1
 
4.8%
48815 1
 
4.8%
48746 1
 
4.8%
48726 1
 
4.8%
48792 1
 
4.8%
48790 1
 
4.8%
(Missing) 11
52.4%
ValueCountFrequency (%)
48726 1
 
4.8%
48744 1
 
4.8%
48746 1
 
4.8%
48788 1
 
4.8%
48790 1
 
4.8%
48792 1
 
4.8%
48815 1
 
4.8%
48816 3
14.3%
ValueCountFrequency (%)
48816 3
14.3%
48815 1
 
4.8%
48792 1
 
4.8%
48790 1
 
4.8%
48788 1
 
4.8%
48746 1
 
4.8%
48744 1
 
4.8%
48726 1
 
4.8%

영업소소재지(도로명)
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T01:52:01.666382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length27.380952
Min length22

Characters and Unicode

Total characters575
Distinct characters64
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row부산광역시 동구 초량로 9-1 (초량동)
2nd row부산광역시 동구 초량상로 84-1 (초량동)
3rd row부산광역시 동구 범일로102번길 13 (범일동)
4th row부산광역시 동구 초량상로 94 (초량동)
5th row부산광역시 동구 초량상로 90-1 (초량동,부산장우신협 3층)
ValueCountFrequency (%)
부산광역시 21
17.9%
동구 21
17.9%
초량동 9
 
7.7%
수정동 5
 
4.3%
중앙대로 4
 
3.4%
범일동 4
 
3.4%
초량상로 3
 
2.6%
범일로102번길 3
 
2.6%
2층 3
 
2.6%
3층 3
 
2.6%
Other values (35) 41
35.0%
2023-12-11T01:52:02.140462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
101
 
17.6%
동 42
 
7.3%
1 23
 
4.0%
부 22
 
3.8%
산 22
 
3.8%
) 21
 
3.7%
( 21
 
3.7%
로 21
 
3.7%
구 21
 
3.7%
시 21
 
3.7%
Other values (54) 260
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 335
58.3%
Space Separator 101
 
17.6%
Decimal Number 84
 
14.6%
Close Punctuation 21
 
3.7%
Open Punctuation 21
 
3.7%
Other Punctuation 10
 
1.7%
Dash Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 42
 
12.5%
부 22
 
6.6%
산 22
 
6.6%
로 21
 
6.3%
구 21
 
6.3%
시 21
 
6.3%
역 21
 
6.3%
광 21
 
6.3%
초 17
 
5.1%
량 17
 
5.1%
Other values (39) 110
32.8%
Decimal Number
ValueCountFrequency (%)
1 23
27.4%
2 14
16.7%
0 9
 
10.7%
3 9
 
10.7%
4 8
 
9.5%
9 7
 
8.3%
7 5
 
6.0%
8 5
 
6.0%
5 3
 
3.6%
6 1
 
1.2%
Space Separator
ValueCountFrequency (%)
101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 335
58.3%
Common 240
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 42
 
12.5%
부 22
 
6.6%
산 22
 
6.6%
로 21
 
6.3%
구 21
 
6.3%
시 21
 
6.3%
역 21
 
6.3%
광 21
 
6.3%
초 17
 
5.1%
량 17
 
5.1%
Other values (39) 110
32.8%
Common
ValueCountFrequency (%)
101
42.1%
1 23
 
9.6%
) 21
 
8.8%
( 21
 
8.8%
2 14
 
5.8%
, 10
 
4.2%
0 9
 
3.8%
3 9
 
3.8%
4 8
 
3.3%
9 7
 
2.9%
Other values (5) 17
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 335
58.3%
ASCII 240
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
101
42.1%
1 23
 
9.6%
) 21
 
8.8%
( 21
 
8.8%
2 14
 
5.8%
, 10
 
4.2%
0 9
 
3.8%
3 9
 
3.8%
4 8
 
3.3%
9 7
 
2.9%
Other values (5) 17
 
7.1%
Hangul
ValueCountFrequency (%)
동 42
 
12.5%
부 22
 
6.6%
산 22
 
6.6%
로 21
 
6.3%
구 21
 
6.3%
시 21
 
6.3%
역 21
 
6.3%
광 21
 
6.3%
초 17
 
5.1%
량 17
 
5.1%
Other values (39) 110
32.8%

시설면적
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean230.73333
Minimum61.49
Maximum422.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T01:52:02.295335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61.49
5-th percentile90.37
Q1133.31
median233
Q3286.92
95-th percentile409.01
Maximum422.72
Range361.23
Interquartile range (IQR)153.61

Descriptive statistics

Standard deviation109.12088
Coefficient of variation (CV)0.47293069
Kurtosis-0.93305372
Mean230.73333
Median Absolute Deviation (MAD)79.19
Skewness0.23603324
Sum4845.4
Variance11907.365
MonotonicityNot monotonic
2023-12-11T01:52:02.448429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
97.92 1
 
4.8%
120.44 1
 
4.8%
90.37 1
 
4.8%
422.72 1
 
4.8%
286.92 1
 
4.8%
272.09 1
 
4.8%
61.49 1
 
4.8%
233.0 1
 
4.8%
155.74 1
 
4.8%
409.01 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
61.49 1
4.8%
90.37 1
4.8%
97.92 1
4.8%
118.12 1
4.8%
120.44 1
4.8%
133.31 1
4.8%
153.81 1
4.8%
155.74 1
4.8%
216.86 1
4.8%
230.12 1
4.8%
ValueCountFrequency (%)
422.72 1
4.8%
409.01 1
4.8%
396.99 1
4.8%
355.49 1
4.8%
300.3 1
4.8%
286.92 1
4.8%
278.28 1
4.8%
278.27 1
4.8%
272.09 1
4.8%
234.15 1
4.8%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
인터넷컴퓨터게임시설제공업
21 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인터넷컴퓨터게임시설제공업 21
100.0%

Length

2023-12-11T01:52:02.620770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:52:02.745890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인터넷컴퓨터게임시설제공업 21
100.0%

Interactions

2023-12-11T01:51:58.865317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:51:57.868714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:51:58.376131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:51:59.094626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:51:58.084220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:51:58.504450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:51:59.257291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:51:58.215931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:51:58.696434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:52:02.823900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번등록(신고)일자상호우편번호영업소소재지(도로명)시설면적
연번1.0001.0001.0000.9011.0000.572
등록(신고)일자1.0001.0001.0001.0001.0000.957
상호1.0001.0001.0001.0001.0001.000
우편번호0.9011.0001.0001.0001.0000.000
영업소소재지(도로명)1.0001.0001.0001.0001.0001.000
시설면적0.5720.9571.0000.0001.0001.000
2023-12-11T01:52:02.926402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호시설면적
연번1.0000.0430.205
우편번호0.0431.000-0.227
시설면적0.205-0.2271.000

Missing values

2023-12-11T01:51:59.498390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:51:59.715299image/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

연번등록(신고)일자상호우편번호영업소소재지(도로명)시설면적업종명
012007-09-19놀토피시존<NA>부산광역시 동구 초량로 9-1 (초량동)97.92인터넷컴퓨터게임시설제공업
122008-05-20아이비스PC방<NA>부산광역시 동구 초량상로 84-1 (초량동)120.44인터넷컴퓨터게임시설제공업
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562008-07-30드레곤PC방<NA>부산광역시 동구 중앙대로371번길 9 (수정동)230.12인터넷컴퓨터게임시설제공업
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13142015-12-09꿈꾸는 PC n COOK48788부산광역시 동구 중앙대로371번길 12, 4층 (수정동)409.01인터넷컴퓨터게임시설제공업
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20212022-03-21브라보월드PC48816부산광역시 동구 대영로243번길 87, 3층 (초량동)90.37인터넷컴퓨터게임시설제공업