Overview

Dataset statistics

Number of variables5
Number of observations110
Missing cells38
Missing cells (%)6.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory42.2 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description인천광역시 부평구 관내에 위치한 단란주점 현황(업종명, 업소명, 소재지, 전화번호)에 관하여 입력된 데이터파일입니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15103339&srcSe=7661IVAWM27C61E190

Alerts

업종명 has constant value ""Constant
소재지전화 has 37 (33.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:10:20.894219
Analysis finished2024-03-18 05:10:21.743510
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct110
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.5
Minimum1
Maximum110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-18T14:10:21.823711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.45
Q128.25
median55.5
Q382.75
95-th percentile104.55
Maximum110
Range109
Interquartile range (IQR)54.5

Descriptive statistics

Standard deviation31.898276
Coefficient of variation (CV)0.57474371
Kurtosis-1.2
Mean55.5
Median Absolute Deviation (MAD)27.5
Skewness0
Sum6105
Variance1017.5
MonotonicityStrictly increasing
2024-03-18T14:10:21.956346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
71 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
Other values (100) 100
90.9%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1012.0 B
단란주점
110 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단란주점 110
100.0%

Length

2024-03-18T14:10:22.077753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:10:22.163954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 110
100.0%

업소명
Text

Distinct108
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2024-03-18T14:10:22.322648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12.5
Mean length6.5909091
Min length2

Characters and Unicode

Total characters725
Distinct characters202
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

Unique106 ?
Unique (%)96.4%

Sample

1st row늘푸른가요주점
2nd row7080보통사람들
3rd row팡팡단란주점
4th row추억의7080라이브
5th row별이빛나는밤에7080
ValueCountFrequency (%)
팡팡단란주점 2
 
1.8%
가요주점 2
 
1.8%
7080단란주점 2
 
1.8%
포엠 1
 
0.9%
주다단란주점 1
 
0.9%
늘푸른가요주점 1
 
0.9%
코러스노래주점 1
 
0.9%
별밤라이브클럽 1
 
0.9%
술마시는빙고 1
 
0.9%
더샵짱단란주점 1
 
0.9%
Other values (99) 99
88.4%
2024-03-18T14:10:22.666846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 64
 
8.8%
점 59
 
8.1%
0 45
 
6.2%
단 36
 
5.0%
란 35
 
4.8%
7 22
 
3.0%
래 21
 
2.9%
8 20
 
2.8%
노 18
 
2.5%
가 16
 
2.2%
Other values (192) 389
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 615
84.8%
Decimal Number 94
 
13.0%
Uppercase Letter 10
 
1.4%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Space Separator 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 64
 
10.4%
점 59
 
9.6%
단 36
 
5.9%
란 35
 
5.7%
래 21
 
3.4%
노 18
 
2.9%
가 16
 
2.6%
이 15
 
2.4%
라 14
 
2.3%
요 13
 
2.1%
Other values (172) 324
52.7%
Decimal Number
ValueCountFrequency (%)
0 45
47.9%
7 22
23.4%
8 20
21.3%
4 2
 
2.1%
2 1
 
1.1%
3 1
 
1.1%
5 1
 
1.1%
6 1
 
1.1%
9 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
F 2
20.0%
N 2
20.0%
O 1
10.0%
B 1
10.0%
C 1
10.0%
E 1
10.0%
K 1
10.0%
A 1
10.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 615
84.8%
Common 100
 
13.8%
Latin 10
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 64
 
10.4%
점 59
 
9.6%
단 36
 
5.9%
란 35
 
5.7%
래 21
 
3.4%
노 18
 
2.9%
가 16
 
2.6%
이 15
 
2.4%
라 14
 
2.3%
요 13
 
2.1%
Other values (172) 324
52.7%
Common
ValueCountFrequency (%)
0 45
45.0%
7 22
22.0%
8 20
20.0%
) 2
 
2.0%
( 2
 
2.0%
4 2
 
2.0%
2
 
2.0%
2 1
 
1.0%
3 1
 
1.0%
5 1
 
1.0%
Other values (2) 2
 
2.0%
Latin
ValueCountFrequency (%)
F 2
20.0%
N 2
20.0%
O 1
10.0%
B 1
10.0%
C 1
10.0%
E 1
10.0%
K 1
10.0%
A 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 615
84.8%
ASCII 110
 
15.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 64
 
10.4%
점 59
 
9.6%
단 36
 
5.9%
란 35
 
5.7%
래 21
 
3.4%
노 18
 
2.9%
가 16
 
2.6%
이 15
 
2.4%
라 14
 
2.3%
요 13
 
2.1%
Other values (172) 324
52.7%
ASCII
ValueCountFrequency (%)
0 45
40.9%
7 22
20.0%
8 20
18.2%
F 2
 
1.8%
) 2
 
1.8%
( 2
 
1.8%
4 2
 
1.8%
2
 
1.8%
N 2
 
1.8%
O 1
 
0.9%
Other values (10) 10
 
9.1%

소재지(도로명)
Text

Distinct108
Distinct (%)99.1%
Missing1
Missing (%)0.9%
Memory size1012.0 B
2024-03-18T14:10:22.960137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length43
Mean length27.431193
Min length21

Characters and Unicode

Total characters2990
Distinct characters92
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)98.2%

Sample

1st row인천광역시 부평구 시장로 59, 3층 (부평동)
2nd row인천광역시 부평구 길주남로 90 (부평동)
3rd row인천광역시 부평구 경인로 952 (부평동)
4th row인천광역시 부평구 마장로393번길 2 (산곡동)
5th row인천광역시 부평구 평천로 328 (갈산동)
ValueCountFrequency (%)
인천광역시 109
18.5%
부평구 109
18.5%
부평동 42
 
7.1%
십정동 21
 
3.6%
청천동 10
 
1.7%
일부호 7
 
1.2%
3층 6
 
1.0%
2층 6
 
1.0%
지하1층 6
 
1.0%
갈산동 6
 
1.0%
Other values (171) 268
45.4%
2024-03-18T14:10:23.407871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
481
 
16.1%
부 195
 
6.5%
평 173
 
5.8%
천 124
 
4.1%
시 121
 
4.0%
( 116
 
3.9%
) 116
 
3.9%
동 116
 
3.9%
인 113
 
3.8%
광 112
 
3.7%
Other values (82) 1323
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1800
60.2%
Space Separator 481
 
16.1%
Decimal Number 425
 
14.2%
Open Punctuation 116
 
3.9%
Close Punctuation 116
 
3.9%
Other Punctuation 39
 
1.3%
Dash Punctuation 11
 
0.4%
Uppercase Letter 1
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 195
 
10.8%
평 173
 
9.6%
천 124
 
6.9%
시 121
 
6.7%
동 116
 
6.4%
인 113
 
6.3%
광 112
 
6.2%
로 110
 
6.1%
역 109
 
6.1%
구 109
 
6.1%
Other values (65) 518
28.8%
Decimal Number
ValueCountFrequency (%)
1 100
23.5%
3 75
17.6%
2 50
11.8%
4 48
11.3%
7 31
 
7.3%
5 30
 
7.1%
0 27
 
6.4%
6 26
 
6.1%
8 22
 
5.2%
9 16
 
3.8%
Space Separator
ValueCountFrequency (%)
481
100.0%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Other Punctuation
ValueCountFrequency (%)
, 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1800
60.2%
Common 1188
39.7%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 195
 
10.8%
평 173
 
9.6%
천 124
 
6.9%
시 121
 
6.7%
동 116
 
6.4%
인 113
 
6.3%
광 112
 
6.2%
로 110
 
6.1%
역 109
 
6.1%
구 109
 
6.1%
Other values (65) 518
28.8%
Common
ValueCountFrequency (%)
481
40.5%
( 116
 
9.8%
) 116
 
9.8%
1 100
 
8.4%
3 75
 
6.3%
2 50
 
4.2%
4 48
 
4.0%
, 39
 
3.3%
7 31
 
2.6%
5 30
 
2.5%
Other values (5) 102
 
8.6%
Latin
ValueCountFrequency (%)
B 1
50.0%
Ⅱ 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1800
60.2%
ASCII 1189
39.8%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
481
40.5%
( 116
 
9.8%
) 116
 
9.8%
1 100
 
8.4%
3 75
 
6.3%
2 50
 
4.2%
4 48
 
4.0%
, 39
 
3.3%
7 31
 
2.6%
5 30
 
2.5%
Other values (6) 103
 
8.7%
Hangul
ValueCountFrequency (%)
부 195
 
10.8%
평 173
 
9.6%
천 124
 
6.9%
시 121
 
6.7%
동 116
 
6.4%
인 113
 
6.3%
광 112
 
6.2%
로 110
 
6.1%
역 109
 
6.1%
구 109
 
6.1%
Other values (65) 518
28.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지전화
Text

MISSING 

Distinct73
Distinct (%)100.0%
Missing37
Missing (%)33.6%
Memory size1012.0 B
2024-03-18T14:10:23.635699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters876
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

Unique73 ?
Unique (%)100.0%

Sample

1st row032-529-0826
2nd row032-505-8688
3rd row032-522-8484
4th row032-524-9305
5th row032-511-6454
ValueCountFrequency (%)
032-505-7254 1
 
1.4%
032-519-7076 1
 
1.4%
032-501-5947 1
 
1.4%
032-512-8198 1
 
1.4%
032-526-8531 1
 
1.4%
032-527-7470 1
 
1.4%
032-523-2007 1
 
1.4%
032-511-1239 1
 
1.4%
032-518-2442 1
 
1.4%
032-525-9199 1
 
1.4%
Other values (63) 63
86.3%
2024-03-18T14:10:23.971494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 146
16.7%
2 140
16.0%
0 125
14.3%
3 113
12.9%
5 96
11.0%
4 60
6.8%
1 51
 
5.8%
8 43
 
4.9%
7 38
 
4.3%
9 33
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 730
83.3%
Dash Punctuation 146
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 140
19.2%
0 125
17.1%
3 113
15.5%
5 96
13.2%
4 60
8.2%
1 51
 
7.0%
8 43
 
5.9%
7 38
 
5.2%
9 33
 
4.5%
6 31
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 876
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 146
16.7%
2 140
16.0%
0 125
14.3%
3 113
12.9%
5 96
11.0%
4 60
6.8%
1 51
 
5.8%
8 43
 
4.9%
7 38
 
4.3%
9 33
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 876
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 146
16.7%
2 140
16.0%
0 125
14.3%
3 113
12.9%
5 96
11.0%
4 60
6.8%
1 51
 
5.8%
8 43
 
4.9%
7 38
 
4.3%
9 33
 
3.8%

Interactions

2024-03-18T14:10:21.439055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:10:24.068006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재지전화
연번1.0001.000
소재지전화1.0001.000

Missing values

2024-03-18T14:10:21.528914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:10:21.613010image/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.
2024-03-18T14:10:21.697033image/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

연번업종명업소명소재지(도로명)소재지전화
01단란주점늘푸른가요주점인천광역시 부평구 시장로 59, 3층 (부평동)032-529-0826
12단란주점7080보통사람들인천광역시 부평구 길주남로 90 (부평동)032-505-8688
23단란주점팡팡단란주점인천광역시 부평구 경인로 952 (부평동)032-522-8484
34단란주점추억의7080라이브인천광역시 부평구 마장로393번길 2 (산곡동)032-524-9305
45단란주점별이빛나는밤에7080인천광역시 부평구 평천로 328 (갈산동)032-511-6454
56단란주점7080놀러와인천광역시 부평구 평천로287번길 1 (갈산동)032-526-0853
67단란주점미투로단란주점인천광역시 부평구 경인로1118번길 9 (일신동)032-502-2523
78단란주점터치단란주점인천광역시 부평구 일신로 10 (일신동)<NA>
89단란주점가요주점인천광역시 부평구 부흥로 383 (부개동)032-525-5010
910단란주점불꽃단란주점인천광역시 부평구 경인로1046번길 4 (부개동)032-525-2869
연번업종명업소명소재지(도로명)소재지전화
100101단란주점동암7080라이브인천광역시 부평구 열우물로25번길 14-9, 2층 일부호 (십정동)<NA>
101102단란주점만남7080라이브단란주점인천광역시 부평구 부평문화로 103, 2층 일부호 (부평동)032-515-1011
102103단란주점퀸가요주점인천광역시 부평구 부흥로365번길 3, 6층 일부호 (부평동)<NA>
103104단란주점3F단란주점인천광역시 부평구 경원대로 1368, 3층 (부평동)<NA>
104105단란주점단밤단란주점인천광역시 부평구 대정로 30, 지하1층 일부호 (부평동)<NA>
105106단란주점가자5060인천광역시 부평구 부평문화로105번길 5, 3층 (부평동)<NA>
106107단란주점뮤직뱅크라운딩인천광역시 부평구 대정로 72, 3층 일부호 (부평동)<NA>
107108단란주점황제트롯시대인천광역시 부평구 부흥로334번길 65, 지하1층 일부호 (부평동)<NA>
108109단란주점주다단란주점인천광역시 부평구 경원대로1403번길 21, 동강 2빌딩 3층 일부호 (부평동)<NA>
109110단란주점뷰라운지인천광역시 부평구 부평대로 24, 가나베스트빌 14층 1402호 (부평동)<NA>