Overview

Dataset statistics

Number of variables5
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory45.3 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description인천광역시 동구 관내 중국식당 현황(업종명,업소명,소재지,소재지전화)
Author인천광역시 동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15040957&srcSe=7661IVAWM27C61E190

Alerts

업종명 has constant value ""Constant
순번 has unique valuesUnique
업소명 has unique valuesUnique
소재지(도로명) has unique valuesUnique
소재지전화 has unique valuesUnique

Reproduction

Analysis started2024-04-19 06:23:12.554466
Analysis finished2024-04-19 06:23:12.970365
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-19T15:23:13.029411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q18.5
median16
Q323.5
95-th percentile29.5
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0921211
Coefficient of variation (CV)0.56825757
Kurtosis-1.2
Mean16
Median Absolute Deviation (MAD)8
Skewness0
Sum496
Variance82.666667
MonotonicityStrictly increasing
2024-04-19T15:23:13.148311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 1
 
3.2%
2 1
 
3.2%
31 1
 
3.2%
30 1
 
3.2%
29 1
 
3.2%
28 1
 
3.2%
27 1
 
3.2%
26 1
 
3.2%
25 1
 
3.2%
24 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1 1
3.2%
2 1
3.2%
3 1
3.2%
4 1
3.2%
5 1
3.2%
6 1
3.2%
7 1
3.2%
8 1
3.2%
9 1
3.2%
10 1
3.2%
ValueCountFrequency (%)
31 1
3.2%
30 1
3.2%
29 1
3.2%
28 1
3.2%
27 1
3.2%
26 1
3.2%
25 1
3.2%
24 1
3.2%
23 1
3.2%
22 1
3.2%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
일반음식점
31 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 31
100.0%

Length

2024-04-19T15:23:13.271155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:23:13.360833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 31
100.0%

업소명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-19T15:23:13.556856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length4
Min length2

Characters and Unicode

Total characters124
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

Unique31 ?
Unique (%)100.0%

Sample

1st row화순식당
2nd row옛날장가루
3rd row문화반점
4th row태화루
5th row성림장
ValueCountFrequency (%)
화순식당 1
 
3.0%
명성각 1
 
3.0%
첸(chen 1
 
3.0%
송림점 1
 
3.0%
짬뽕타임 1
 
3.0%
송림교동짬뽕 1
 
3.0%
도원 1
 
3.0%
수문통짬뽕 1
 
3.0%
짬뽕먹을래 1
 
3.0%
짜장먹을래 1
 
3.0%
Other values (23) 23
69.7%
2024-04-19T15:23:13.900686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 7
 
5.6%
반 6
 
4.8%
장 6
 
4.8%
뽕 5
 
4.0%
짬 5
 
4.0%
각 5
 
4.0%
성 5
 
4.0%
림 4
 
3.2%
화 4
 
3.2%
문 3
 
2.4%
Other values (58) 74
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 116
93.5%
Lowercase Letter 3
 
2.4%
Space Separator 2
 
1.6%
Open Punctuation 1
 
0.8%
Uppercase Letter 1
 
0.8%
Close Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 7
 
6.0%
반 6
 
5.2%
장 6
 
5.2%
뽕 5
 
4.3%
짬 5
 
4.3%
각 5
 
4.3%
성 5
 
4.3%
림 4
 
3.4%
화 4
 
3.4%
문 3
 
2.6%
Other values (51) 66
56.9%
Lowercase Letter
ValueCountFrequency (%)
h 1
33.3%
e 1
33.3%
n 1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 116
93.5%
Common 4
 
3.2%
Latin 4
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 7
 
6.0%
반 6
 
5.2%
장 6
 
5.2%
뽕 5
 
4.3%
짬 5
 
4.3%
각 5
 
4.3%
성 5
 
4.3%
림 4
 
3.4%
화 4
 
3.4%
문 3
 
2.6%
Other values (51) 66
56.9%
Latin
ValueCountFrequency (%)
C 1
25.0%
h 1
25.0%
e 1
25.0%
n 1
25.0%
Common
ValueCountFrequency (%)
2
50.0%
( 1
25.0%
) 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 116
93.5%
ASCII 8
 
6.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 7
 
6.0%
반 6
 
5.2%
장 6
 
5.2%
뽕 5
 
4.3%
짬 5
 
4.3%
각 5
 
4.3%
성 5
 
4.3%
림 4
 
3.4%
화 4
 
3.4%
문 3
 
2.6%
Other values (51) 66
56.9%
ASCII
ValueCountFrequency (%)
2
25.0%
( 1
12.5%
C 1
12.5%
h 1
12.5%
e 1
12.5%
n 1
12.5%
) 1
12.5%

소재지(도로명)
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-19T15:23:14.163000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length32
Mean length27.645161
Min length19

Characters and Unicode

Total characters857
Distinct characters72
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

Unique31 ?
Unique (%)100.0%

Sample

1st row인천광역시 동구 만석동 2번지 -70, 71
2nd row인천광역시 동구 화도진로35번길 7-4 (송현동)
3rd row인천광역시 동구 송림동 233번지
4th row인천광역시 동구 동산로 65 (송림동)
5th row인천광역시 동구 송현로 57-3 (송현동)
ValueCountFrequency (%)
인천광역시 31
17.3%
동구 31
17.3%
송림동 12
 
6.7%
1층 11
 
6.1%
송현동 7
 
3.9%
만석동 3
 
1.7%
금곡동 3
 
1.7%
수문통로 2
 
1.1%
인천산업용품유통단지 2
 
1.1%
샛골로161번길 2
 
1.1%
Other values (68) 75
41.9%
2024-04-19T15:23:14.564274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155
18.1%
동 69
 
8.1%
1 41
 
4.8%
인 33
 
3.9%
천 33
 
3.9%
광 31
 
3.6%
역 31
 
3.6%
시 31
 
3.6%
구 31
 
3.6%
( 29
 
3.4%
Other values (62) 373
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 492
57.4%
Space Separator 155
 
18.1%
Decimal Number 117
 
13.7%
Open Punctuation 29
 
3.4%
Close Punctuation 29
 
3.4%
Other Punctuation 19
 
2.2%
Dash Punctuation 10
 
1.2%
Uppercase Letter 6
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 69
14.0%
인 33
 
6.7%
천 33
 
6.7%
광 31
 
6.3%
역 31
 
6.3%
시 31
 
6.3%
구 31
 
6.3%
송 28
 
5.7%
로 27
 
5.5%
림 15
 
3.0%
Other values (43) 163
33.1%
Decimal Number
ValueCountFrequency (%)
1 41
35.0%
3 16
 
13.7%
2 12
 
10.3%
7 11
 
9.4%
4 9
 
7.7%
0 8
 
6.8%
6 7
 
6.0%
5 7
 
6.0%
8 3
 
2.6%
9 3
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
A 1
 
16.7%
C 1
 
16.7%
F 1
 
16.7%
Space Separator
ValueCountFrequency (%)
155
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 492
57.4%
Common 359
41.9%
Latin 6
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 69
14.0%
인 33
 
6.7%
천 33
 
6.7%
광 31
 
6.3%
역 31
 
6.3%
시 31
 
6.3%
구 31
 
6.3%
송 28
 
5.7%
로 27
 
5.5%
림 15
 
3.0%
Other values (43) 163
33.1%
Common
ValueCountFrequency (%)
155
43.2%
1 41
 
11.4%
( 29
 
8.1%
) 29
 
8.1%
, 19
 
5.3%
3 16
 
4.5%
2 12
 
3.3%
7 11
 
3.1%
- 10
 
2.8%
4 9
 
2.5%
Other values (5) 28
 
7.8%
Latin
ValueCountFrequency (%)
B 3
50.0%
A 1
 
16.7%
C 1
 
16.7%
F 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 492
57.4%
ASCII 365
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
42.5%
1 41
 
11.2%
( 29
 
7.9%
) 29
 
7.9%
, 19
 
5.2%
3 16
 
4.4%
2 12
 
3.3%
7 11
 
3.0%
- 10
 
2.7%
4 9
 
2.5%
Other values (9) 34
 
9.3%
Hangul
ValueCountFrequency (%)
동 69
14.0%
인 33
 
6.7%
천 33
 
6.7%
광 31
 
6.3%
역 31
 
6.3%
시 31
 
6.3%
구 31
 
6.3%
송 28
 
5.7%
로 27
 
5.5%
림 15
 
3.0%
Other values (43) 163
33.1%

소재지전화
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-19T15:23:14.766607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters372
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

Unique31 ?
Unique (%)100.0%

Sample

1st row032-772-1029
2nd row032-763-6500
3rd row032-773-4824
4th row032-765-1113
5th row032-772-6279
ValueCountFrequency (%)
032-772-1029 1
 
3.2%
032-572-0845 1
 
3.2%
032-772-9288 1
 
3.2%
032-766-8887 1
 
3.2%
032-589-8258 1
 
3.2%
032-589-1031 1
 
3.2%
032-772-9295 1
 
3.2%
032-777-0778 1
 
3.2%
032-772-6400 1
 
3.2%
032-777-0820 1
 
3.2%
Other values (21) 21
67.7%
2024-04-19T15:23:15.067585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 69
18.5%
- 62
16.7%
0 54
14.5%
3 50
13.4%
2 49
13.2%
6 23
 
6.2%
8 16
 
4.3%
1 15
 
4.0%
5 13
 
3.5%
9 11
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 310
83.3%
Dash Punctuation 62
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 69
22.3%
0 54
17.4%
3 50
16.1%
2 49
15.8%
6 23
 
7.4%
8 16
 
5.2%
1 15
 
4.8%
5 13
 
4.2%
9 11
 
3.5%
4 10
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 372
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 69
18.5%
- 62
16.7%
0 54
14.5%
3 50
13.4%
2 49
13.2%
6 23
 
6.2%
8 16
 
4.3%
1 15
 
4.0%
5 13
 
3.5%
9 11
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 69
18.5%
- 62
16.7%
0 54
14.5%
3 50
13.4%
2 49
13.2%
6 23
 
6.2%
8 16
 
4.3%
1 15
 
4.0%
5 13
 
3.5%
9 11
 
3.0%

Interactions

2024-04-19T15:23:12.739602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T15:23:15.165640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업소명소재지(도로명)소재지전화
순번1.0001.0001.0001.000
업소명1.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.000
소재지전화1.0001.0001.0001.000

Missing values

2024-04-19T15:23:12.847375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T15:23:12.933783image/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

순번업종명업소명소재지(도로명)소재지전화
01일반음식점화순식당인천광역시 동구 만석동 2번지 -70, 71032-772-1029
12일반음식점옛날장가루인천광역시 동구 화도진로35번길 7-4 (송현동)032-763-6500
23일반음식점문화반점인천광역시 동구 송림동 233번지032-773-4824
34일반음식점태화루인천광역시 동구 동산로 65 (송림동)032-765-1113
45일반음식점성림장인천광역시 동구 송현로 57-3 (송현동)032-772-6279
56일반음식점미성각인천광역시 동구 송현동 92번지032-773-1837
67일반음식점흑룡인천광역시 동구 제물량로 343-1 (만석동)032-772-3373
78일반음식점대성각인천광역시 동구 금곡로82번길 5 (송림동)032-763-4079
89일반음식점문성각인천광역시 동구 송미로 35, 1층 (송림동)032-777-0400
910일반음식점은혜반점인천광역시 동구 석수로 5, 1층 (만석동)032-764-5859
순번업종명업소명소재지(도로명)소재지전화
2122일반음식점신라반점인천광역시 동구 금곡로 17-1 (금곡동)032-773-6934
2223일반음식점황허장인천광역시 동구 동산로 28 (송림동)032-777-0820
2324일반음식점중국관인천광역시 동구 화도진로17번길 6-2 (송현동,(1층))032-772-6400
2425일반음식점짜장먹을래 짬뽕먹을래인천광역시 동구 솔빛로 6 (송현동, 1층)032-777-0778
2526일반음식점수문통짬뽕인천광역시 동구 수문통로 41, 1층 (송현동)032-772-9295
2627일반음식점도원인천광역시 동구 방축로 105, C동 B31호 (송림동, 인천산업용품유통단지 편익상가 )032-589-1031
2728일반음식점송림교동짬뽕인천광역시 동구 방축로83번길 23, B동 B11호 (송림동, 인천산업용품유통단지 편익상가)032-589-8258
2829일반음식점짬뽕타임 송림점인천광역시 동구 송미로 11-14, F동 1층 (송림동)032-766-8887
2930일반음식점첸(Chen)인천광역시 동구 수문통로 47, 1층 (송현동)032-772-9288
3031일반음식점홍장군짬뽕인천광역시 동구 금곡로72번길 6, 1층 (금곡동)032-766-7707