Overview

Dataset statistics

Number of variables5
Number of observations24
Missing cells9
Missing cells (%)7.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory46.5 B

Variable types

Numeric1
Text4

Dataset

Description인천광역시 미추홀구의 코인노래방 현황에 대한 데이터로 상호명, 지번주소, 도로명주소, 전화번호 등의 정보를 제공하고 있습니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15087076&srcSe=7661IVAWM27C61E190

Alerts

전화번호 has 9 (37.5%) missing valuesMissing
연번 has unique valuesUnique
상호명 has unique valuesUnique
지번주소 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-01-28 17:55:24.157086
Analysis finished2024-01-28 17:55:24.614546
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-01-29T02:55:24.666291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2024-01-29T02:55:24.764439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

상호명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-01-29T02:55:24.959009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length10.583333
Min length5

Characters and Unicode

Total characters254
Distinct characters69
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

Unique24 ?
Unique (%)100.0%

Sample

1st row24시코인노래연습장
2nd row와쑝동전노래방
3rd row808코인노래방
4th row볼륨업코인노래연습장
5th row매드락코인노래연습장
ValueCountFrequency (%)
코인노래연습장 2
 
5.7%
인하대점 2
 
5.7%
세븐스타코인노래연습장 2
 
5.7%
24시코인노래연습장 1
 
2.9%
연습장 1
 
2.9%
슈퍼스타코인노래연습장 1
 
2.9%
노래연습장 1
 
2.9%
짱코인 1
 
2.9%
주안코인노래연습장 1
 
2.9%
락휴 1
 
2.9%
Other values (22) 22
62.9%
2024-01-29T02:55:25.288507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
9.4%
24
 
9.4%
23
 
9.1%
23
 
9.1%
18
 
7.1%
18
 
7.1%
18
 
7.1%
11
 
4.3%
6
 
2.4%
5
 
2.0%
Other values (59) 84
33.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 229
90.2%
Space Separator 11
 
4.3%
Decimal Number 7
 
2.8%
Lowercase Letter 4
 
1.6%
Uppercase Letter 2
 
0.8%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
24
 
10.5%
24
 
10.5%
23
 
10.0%
23
 
10.0%
18
 
7.9%
18
 
7.9%
18
 
7.9%
6
 
2.6%
5
 
2.2%
5
 
2.2%
Other values (47) 65
28.4%
Decimal Number
ValueCountFrequency (%)
4 2
28.6%
2 2
28.6%
8 2
28.6%
0 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
c 1
25.0%
a 1
25.0%
f 1
25.0%
e 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 229
90.2%
Common 19
 
7.5%
Latin 6
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
24
 
10.5%
24
 
10.5%
23
 
10.0%
23
 
10.0%
18
 
7.9%
18
 
7.9%
18
 
7.9%
6
 
2.6%
5
 
2.2%
5
 
2.2%
Other values (47) 65
28.4%
Common
ValueCountFrequency (%)
11
57.9%
4 2
 
10.5%
2 2
 
10.5%
8 2
 
10.5%
0 1
 
5.3%
& 1
 
5.3%
Latin
ValueCountFrequency (%)
P 1
16.7%
c 1
16.7%
a 1
16.7%
f 1
16.7%
e 1
16.7%
C 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 229
90.2%
ASCII 25
 
9.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
24
 
10.5%
24
 
10.5%
23
 
10.0%
23
 
10.0%
18
 
7.9%
18
 
7.9%
18
 
7.9%
6
 
2.6%
5
 
2.2%
5
 
2.2%
Other values (47) 65
28.4%
ASCII
ValueCountFrequency (%)
11
44.0%
4 2
 
8.0%
2 2
 
8.0%
8 2
 
8.0%
P 1
 
4.0%
0 1
 
4.0%
& 1
 
4.0%
c 1
 
4.0%
a 1
 
4.0%
f 1
 
4.0%
Other values (2) 2
 
8.0%

지번주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-01-29T02:55:25.477747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length28.5
Mean length22.916667
Min length19

Characters and Unicode

Total characters550
Distinct characters50
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 주안동 146-9
2nd row인천광역시 미추홀구 주안8동 1464-46
3rd row인천광역시 미추홀구 용현동 195-24
4th row인천광역시 미추홀구 주안동 140-1
5th row인천광역시 미추홀구 도화동 998-3
ValueCountFrequency (%)
인천광역시 24
21.6%
미추홀구 24
21.6%
용현동 12
 
10.8%
주안동 7
 
6.3%
2층 3
 
2.7%
지하1층 3
 
2.7%
주안8동 2
 
1.8%
3층 2
 
1.8%
헤리움 1
 
0.9%
227-35 1
 
0.9%
Other values (32) 32
28.8%
2024-01-29T02:55:25.783350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
 
15.8%
25
 
4.5%
25
 
4.5%
25
 
4.5%
24
 
4.4%
1 24
 
4.4%
24
 
4.4%
24
 
4.4%
24
 
4.4%
24
 
4.4%
Other values (40) 244
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 321
58.4%
Decimal Number 119
 
21.6%
Space Separator 87
 
15.8%
Dash Punctuation 23
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
25
 
7.8%
25
 
7.8%
25
 
7.8%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
Other values (28) 78
24.3%
Decimal Number
ValueCountFrequency (%)
1 24
20.2%
4 15
12.6%
2 14
11.8%
9 14
11.8%
3 12
10.1%
6 12
10.1%
8 9
 
7.6%
5 7
 
5.9%
0 6
 
5.0%
7 6
 
5.0%
Space Separator
ValueCountFrequency (%)
87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 321
58.4%
Common 229
41.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
25
 
7.8%
25
 
7.8%
25
 
7.8%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
Other values (28) 78
24.3%
Common
ValueCountFrequency (%)
87
38.0%
1 24
 
10.5%
- 23
 
10.0%
4 15
 
6.6%
2 14
 
6.1%
9 14
 
6.1%
3 12
 
5.2%
6 12
 
5.2%
8 9
 
3.9%
5 7
 
3.1%
Other values (2) 12
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 321
58.4%
ASCII 229
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
38.0%
1 24
 
10.5%
- 23
 
10.0%
4 15
 
6.6%
2 14
 
6.1%
9 14
 
6.1%
3 12
 
5.2%
6 12
 
5.2%
8 9
 
3.9%
5 7
 
3.1%
Other values (2) 12
 
5.2%
Hangul
ValueCountFrequency (%)
25
 
7.8%
25
 
7.8%
25
 
7.8%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
24
 
7.5%
Other values (28) 78
24.3%

도로명주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-01-29T02:55:25.980202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length28
Mean length23.708333
Min length17

Characters and Unicode

Total characters569
Distinct characters58
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

Unique24 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 주안로104번길 29 (주안동146-9 지하)
2nd row인천광역시 미추홀구 인하로 297
3rd row인천광역시 미추홀구 인하로77번길 35
4th row인천광역시 미추홀구 주안로 102-1
5th row인천광역시 미추홀구 숙골로 93
ValueCountFrequency (%)
인천광역시 24
21.2%
미추홀구 24
21.2%
2층 4
 
3.5%
인하로 3
 
2.7%
미추홀대로 3
 
2.7%
인하로67번길 3
 
2.7%
지하1층 3
 
2.7%
주안로 2
 
1.8%
3층 2
 
1.8%
인하로77번길 2
 
1.8%
Other values (43) 43
38.1%
2024-01-29T02:55:26.587709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
 
15.6%
35
 
6.2%
28
 
4.9%
28
 
4.9%
28
 
4.9%
1 25
 
4.4%
25
 
4.4%
25
 
4.4%
24
 
4.2%
24
 
4.2%
Other values (48) 238
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 360
63.3%
Decimal Number 109
 
19.2%
Space Separator 89
 
15.6%
Dash Punctuation 9
 
1.6%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
35
 
9.7%
28
 
7.8%
28
 
7.8%
28
 
7.8%
25
 
6.9%
25
 
6.9%
24
 
6.7%
24
 
6.7%
24
 
6.7%
24
 
6.7%
Other values (34) 95
26.4%
Decimal Number
ValueCountFrequency (%)
1 25
22.9%
7 16
14.7%
2 14
12.8%
3 12
11.0%
4 11
10.1%
9 8
 
7.3%
0 7
 
6.4%
6 7
 
6.4%
5 5
 
4.6%
8 4
 
3.7%
Space Separator
ValueCountFrequency (%)
89
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 360
63.3%
Common 209
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
35
 
9.7%
28
 
7.8%
28
 
7.8%
28
 
7.8%
25
 
6.9%
25
 
6.9%
24
 
6.7%
24
 
6.7%
24
 
6.7%
24
 
6.7%
Other values (34) 95
26.4%
Common
ValueCountFrequency (%)
89
42.6%
1 25
 
12.0%
7 16
 
7.7%
2 14
 
6.7%
3 12
 
5.7%
4 11
 
5.3%
- 9
 
4.3%
9 8
 
3.8%
0 7
 
3.3%
6 7
 
3.3%
Other values (4) 11
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 360
63.3%
ASCII 209
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
42.6%
1 25
 
12.0%
7 16
 
7.7%
2 14
 
6.7%
3 12
 
5.7%
4 11
 
5.3%
- 9
 
4.3%
9 8
 
3.8%
0 7
 
3.3%
6 7
 
3.3%
Other values (4) 11
 
5.3%
Hangul
ValueCountFrequency (%)
35
 
9.7%
28
 
7.8%
28
 
7.8%
28
 
7.8%
25
 
6.9%
25
 
6.9%
24
 
6.7%
24
 
6.7%
24
 
6.7%
24
 
6.7%
Other values (34) 95
26.4%

전화번호
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing9
Missing (%)37.5%
Memory size324.0 B
2024-01-29T02:55:26.750449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.4
Min length12

Characters and Unicode

Total characters201
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st row0507-1406-2585
2nd row0507-1309-7690
3rd row032-195-0030
4th row032-833-3748
5th row0507-1327-6167
ValueCountFrequency (%)
0507-1406-2585 1
 
6.7%
0507-1309-7690 1
 
6.7%
032-195-0030 1
 
6.7%
032-833-3748 1
 
6.7%
0507-1327-6167 1
 
6.7%
0507-1406-9538 1
 
6.7%
070-8846-8476 1
 
6.7%
0507-1307-9143 1
 
6.7%
0507-1486-1569 1
 
6.7%
0507-1315-3837 1
 
6.7%
Other values (5) 5
33.3%
2024-01-29T02:55:27.055765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40
19.9%
- 30
14.9%
5 23
11.4%
7 22
10.9%
3 20
10.0%
1 17
8.5%
4 11
 
5.5%
6 11
 
5.5%
8 11
 
5.5%
2 10
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 171
85.1%
Dash Punctuation 30
 
14.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40
23.4%
5 23
13.5%
7 22
12.9%
3 20
11.7%
1 17
9.9%
4 11
 
6.4%
6 11
 
6.4%
8 11
 
6.4%
2 10
 
5.8%
9 6
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 201
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40
19.9%
- 30
14.9%
5 23
11.4%
7 22
10.9%
3 20
10.0%
1 17
8.5%
4 11
 
5.5%
6 11
 
5.5%
8 11
 
5.5%
2 10
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 201
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40
19.9%
- 30
14.9%
5 23
11.4%
7 22
10.9%
3 20
10.0%
1 17
8.5%
4 11
 
5.5%
6 11
 
5.5%
8 11
 
5.5%
2 10
 
5.0%

Interactions

2024-01-29T02:55:24.399005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:55:27.140783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명지번주소도로명주소전화번호
연번1.0001.0001.0001.0001.000
상호명1.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2024-01-29T02:55:24.499784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:55:24.582930image/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

연번상호명지번주소도로명주소전화번호
0124시코인노래연습장인천광역시 미추홀구 주안동 146-9인천광역시 미추홀구 주안로104번길 29 (주안동146-9 지하)0507-1406-2585
12와쑝동전노래방인천광역시 미추홀구 주안8동 1464-46인천광역시 미추홀구 인하로 297<NA>
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