Overview

Dataset statistics

Number of variables6
Number of observations26
Missing cells30
Missing cells (%)19.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory54.1 B

Variable types

Numeric1
Text4
DateTime1

Dataset

Description인천광역시 중구 관내에 위치한 문구점에 대한 데이터 입니다.
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15087847

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 8 (30.8%) missing valuesMissing
평일 영업시간 has 22 (84.6%) missing valuesMissing
연번 has unique valuesUnique
상호명 has unique valuesUnique

Reproduction

Analysis started2024-01-28 11:30:36.664479
Analysis finished2024-01-28 11:30:37.152159
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-01-28T20:30:37.198731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2024-01-28T20:30:37.297641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

상호명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-01-28T20:30:37.455315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.2692308
Min length3

Characters and Unicode

Total characters163
Distinct characters74
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row알파문구 영종도점
2nd row캐릭터라인 영종2호점
3rd row대동학생백화점 인천점
4th row알파 인천공항업무단지점
5th row대동문구
ValueCountFrequency (%)
알파문구 1
 
3.1%
영종도점 1
 
3.1%
축현문구사 1
 
3.1%
아동문구완구사 1
 
3.1%
승희문구 1
 
3.1%
숭의문구사 1
 
3.1%
도원문교사 1
 
3.1%
기호문구상사 1
 
3.1%
신광문구 1
 
3.1%
세종문구사 1
 
3.1%
Other values (22) 22
68.8%
2024-01-28T20:30:37.718923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
문 17
 
10.4%
구 17
 
10.4%
점 8
 
4.9%
사 8
 
4.9%
6
 
3.7%
동 6
 
3.7%
인 6
 
3.7%
천 5
 
3.1%
알 3
 
1.8%
호 3
 
1.8%
Other values (64) 84
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 156
95.7%
Space Separator 6
 
3.7%
Decimal Number 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
문 17
 
10.9%
구 17
 
10.9%
점 8
 
5.1%
사 8
 
5.1%
동 6
 
3.8%
인 6
 
3.8%
천 5
 
3.2%
알 3
 
1.9%
호 3
 
1.9%
종 3
 
1.9%
Other values (62) 80
51.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 156
95.7%
Common 7
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
문 17
 
10.9%
구 17
 
10.9%
점 8
 
5.1%
사 8
 
5.1%
동 6
 
3.8%
인 6
 
3.8%
천 5
 
3.2%
알 3
 
1.9%
호 3
 
1.9%
종 3
 
1.9%
Other values (62) 80
51.3%
Common
ValueCountFrequency (%)
6
85.7%
2 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 156
95.7%
ASCII 7
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
문 17
 
10.9%
구 17
 
10.9%
점 8
 
5.1%
사 8
 
5.1%
동 6
 
3.8%
인 6
 
3.8%
천 5
 
3.2%
알 3
 
1.9%
호 3
 
1.9%
종 3
 
1.9%
Other values (62) 80
51.3%
ASCII
ValueCountFrequency (%)
6
85.7%
2 1
 
14.3%

도로명주소
Text

Distinct24
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-01-28T20:30:37.892024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length23
Mean length20
Min length15

Characters and Unicode

Total characters520
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

Unique22 ?
Unique (%)84.6%

Sample

1st row인천광역시 중구 흰바위로 41 103호
2nd row인천광역시 중구 자연대로 47
3rd row인천광역시 중구 자유공원로 15
4th row인천광역시 중구 공항로424번길 50 월드게이트 1층
5th row인천광역시 중구 인현동 17-1
ValueCountFrequency (%)
인천광역시 26
23.4%
중구 26
23.4%
자유공원로 3
 
2.7%
참외전로 2
 
1.8%
제물량로 2
 
1.8%
16 2
 
1.8%
흰바위로 2
 
1.8%
인중로63번길 2
 
1.8%
개항로 2
 
1.8%
인현동 2
 
1.8%
Other values (40) 42
37.8%
2024-01-28T20:30:38.178209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
16.3%
1 33
 
6.3%
인 32
 
6.2%
중 28
 
5.4%
천 28
 
5.4%
광 26
 
5.0%
역 26
 
5.0%
시 26
 
5.0%
구 26
 
5.0%
로 24
 
4.6%
Other values (58) 186
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 320
61.5%
Decimal Number 100
 
19.2%
Space Separator 85
 
16.3%
Dash Punctuation 13
 
2.5%
Uppercase Letter 1
 
0.2%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 32
 
10.0%
중 28
 
8.8%
천 28
 
8.8%
광 26
 
8.1%
역 26
 
8.1%
시 26
 
8.1%
구 26
 
8.1%
로 24
 
7.5%
길 9
 
2.8%
번 9
 
2.8%
Other values (44) 86
26.9%
Decimal Number
ValueCountFrequency (%)
1 33
33.0%
3 10
 
10.0%
7 10
 
10.0%
2 10
 
10.0%
5 8
 
8.0%
4 8
 
8.0%
6 7
 
7.0%
0 5
 
5.0%
9 5
 
5.0%
8 4
 
4.0%
Space Separator
ValueCountFrequency (%)
85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 320
61.5%
Common 199
38.3%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 32
 
10.0%
중 28
 
8.8%
천 28
 
8.8%
광 26
 
8.1%
역 26
 
8.1%
시 26
 
8.1%
구 26
 
8.1%
로 24
 
7.5%
길 9
 
2.8%
번 9
 
2.8%
Other values (44) 86
26.9%
Common
ValueCountFrequency (%)
85
42.7%
1 33
 
16.6%
- 13
 
6.5%
3 10
 
5.0%
7 10
 
5.0%
2 10
 
5.0%
5 8
 
4.0%
4 8
 
4.0%
6 7
 
3.5%
0 5
 
2.5%
Other values (3) 10
 
5.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 320
61.5%
ASCII 200
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
85
42.5%
1 33
 
16.5%
- 13
 
6.5%
3 10
 
5.0%
7 10
 
5.0%
2 10
 
5.0%
5 8
 
4.0%
4 8
 
4.0%
6 7
 
3.5%
0 5
 
2.5%
Other values (4) 11
 
5.5%
Hangul
ValueCountFrequency (%)
인 32
 
10.0%
중 28
 
8.8%
천 28
 
8.8%
광 26
 
8.1%
역 26
 
8.1%
시 26
 
8.1%
구 26
 
8.1%
로 24
 
7.5%
길 9
 
2.8%
번 9
 
2.8%
Other values (44) 86
26.9%

전화번호
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing8
Missing (%)30.8%
Memory size340.0 B
2024-01-28T20:30:38.340463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters216
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

Unique18 ?
Unique (%)100.0%

Sample

1st row032-746-0488
2nd row032-751-7727
3rd row032-763-0121
4th row032-743-8585
5th row032-773-0121
ValueCountFrequency (%)
032-743-4412 1
 
5.6%
032-763-0121 1
 
5.6%
032-885-2057 1
 
5.6%
032-772-9354 1
 
5.6%
032-765-2571 1
 
5.6%
032-883-0759 1
 
5.6%
032-882-8076 1
 
5.6%
032-763-0653 1
 
5.6%
032-885-1394 1
 
5.6%
032-746-0488 1
 
5.6%
Other values (8) 8
44.4%
2024-01-28T20:30:38.586649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 36
16.7%
2 32
14.8%
0 29
13.4%
3 28
13.0%
7 24
11.1%
8 16
7.4%
5 14
 
6.5%
4 13
 
6.0%
6 11
 
5.1%
1 9
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 180
83.3%
Dash Punctuation 36
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 32
17.8%
0 29
16.1%
3 28
15.6%
7 24
13.3%
8 16
8.9%
5 14
7.8%
4 13
7.2%
6 11
 
6.1%
1 9
 
5.0%
9 4
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 216
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 36
16.7%
2 32
14.8%
0 29
13.4%
3 28
13.0%
7 24
11.1%
8 16
7.4%
5 14
 
6.5%
4 13
 
6.0%
6 11
 
5.1%
1 9
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 36
16.7%
2 32
14.8%
0 29
13.4%
3 28
13.0%
7 24
11.1%
8 16
7.4%
5 14
 
6.5%
4 13
 
6.0%
6 11
 
5.1%
1 9
 
4.2%

평일 영업시간
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing22
Missing (%)84.6%
Memory size340.0 B
2024-01-28T20:30:38.698783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters44
Distinct characters7
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row09:00~19:00
2nd row10:00~22:00
3rd row09:30~20:30
4th row10:00~22:00
ValueCountFrequency (%)
10:00~22:00 2
50.0%
09:00~19:00 1
25.0%
09:30~20:30 1
25.0%
2024-01-28T20:30:38.899012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19
43.2%
: 8
18.2%
2 5
 
11.4%
~ 4
 
9.1%
1 3
 
6.8%
9 3
 
6.8%
3 2
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32
72.7%
Other Punctuation 8
 
18.2%
Math Symbol 4
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19
59.4%
2 5
 
15.6%
1 3
 
9.4%
9 3
 
9.4%
3 2
 
6.2%
Other Punctuation
ValueCountFrequency (%)
: 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19
43.2%
: 8
18.2%
2 5
 
11.4%
~ 4
 
9.1%
1 3
 
6.8%
9 3
 
6.8%
3 2
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19
43.2%
: 8
18.2%
2 5
 
11.4%
~ 4
 
9.1%
1 3
 
6.8%
9 3
 
6.8%
3 2
 
4.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2021-08-05 00:00:00
Maximum2021-08-05 00:00:00
2024-01-28T20:30:38.975851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:30:39.041541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T20:30:36.881728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T20:30:39.097916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명도로명주소전화번호평일 영업시간
연번1.0001.0000.7981.0000.827
상호명1.0001.0001.0001.0001.000
도로명주소0.7981.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000
평일 영업시간0.8271.0001.0001.0001.000

Missing values

2024-01-28T20:30:36.974611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T20:30:37.053500image/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.
2024-01-28T20:30:37.118518image/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

연번상호명도로명주소전화번호평일 영업시간데이터기준일자
01알파문구 영종도점인천광역시 중구 흰바위로 41 103호032-746-048809:00~19:002021-08-05
12캐릭터라인 영종2호점인천광역시 중구 자연대로 47032-751-772710:00~22:002021-08-05
23대동학생백화점 인천점인천광역시 중구 자유공원로 15032-763-0121<NA>2021-08-05
34알파 인천공항업무단지점인천광역시 중구 공항로424번길 50 월드게이트 1층032-743-858509:30~20:302021-08-05
45대동문구인천광역시 중구 인현동 17-1032-773-0121<NA>2021-08-05
56캔버스 동인천지하상가점인천광역시 중구 참외전로 117-15 동인천지하상가 84~86<NA>10:00~22:002021-08-05
67알림짱인천광역시 중구 흰바위로 22032-746-7900<NA>2021-08-05
78동인천화방문구인천광역시 중구 자유공원로 13-2<NA><NA>2021-08-05
89코코문구인천광역시 중구 참외전로 16<NA><NA>2021-08-05
910삼성문구센터인천광역시 중구 자유공원로 11-1032-762-2552<NA>2021-08-05
연번상호명도로명주소전화번호평일 영업시간데이터기준일자
1617신세계문구사인천광역시 중구 축항대로69번길 33032-882-4127<NA>2021-08-05
1718세종문구사인천광역시 중구 도원로10번길 25-16032-885-1394<NA>2021-08-05
1819신광문구인천광역시 중구 제물량로 43<NA><NA>2021-08-05
1920기호문구상사인천광역시 중구 개항로 107-11032-763-0653<NA>2021-08-05
2021도원문교사인천광역시 중구 샛골로 57032-882-8076<NA>2021-08-05
2122숭의문구사인천광역시 중구 인중로63번길 9032-883-0759<NA>2021-08-05
2223승희문구인천광역시 중구 인중로63번길 11<NA><NA>2021-08-05
2324아동문구완구사인천광역시 중구 제물량로 132-1032-765-2571<NA>2021-08-05
2425축현문구사인천광역시 중구 인현동 17-1032-772-9354<NA>2021-08-05
2526기호의집인천광역시 중구 개항로 107-11032-764-0653<NA>2021-08-05