Overview

Dataset statistics

Number of variables7
Number of observations53
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory59.5 B

Variable types

Numeric1
Text4
Categorical1
DateTime1

Dataset

Description인천광역시 서구 일요일 당번 약국 현황에 대한 데이터로 약국명, 소재지, 운영시간, 주별, 연락처 등의 정보가 포함되어 있습니다.
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15090843

Alerts

데이터기준일자 has constant value ""Constant
주별 is highly imbalanced (51.4%)Imbalance
연번 has unique valuesUnique
약국명 has unique valuesUnique
소재지 has unique valuesUnique
연락처 has unique valuesUnique

Reproduction

Analysis started2024-01-28 13:41:24.399445
Analysis finished2024-01-28 13:41:24.969659
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-01-28T22:41:25.045543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q114
median27
Q340
95-th percentile50.4
Maximum53
Range52
Interquartile range (IQR)26

Descriptive statistics

Standard deviation15.443445
Coefficient of variation (CV)0.57197945
Kurtosis-1.2
Mean27
Median Absolute Deviation (MAD)13
Skewness0
Sum1431
Variance238.5
MonotonicityStrictly increasing
2024-01-28T22:41:25.159154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
41 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
53 1
1.9%
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%

약국명
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-01-28T22:41:25.366656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.6603774
Min length3

Characters and Unicode

Total characters300
Distinct characters109
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)100.0%

Sample

1st row옵티마강남약국
2nd row불로스타약국
3rd row단오약국
4th row위드팜100세약국
5th row자생약국
ValueCountFrequency (%)
옵티마강남약국 1
 
1.9%
하나온누리약국 1
 
1.9%
청라미래약국 1
 
1.9%
조은약국 1
 
1.9%
청라바다약국 1
 
1.9%
비타민약국 1
 
1.9%
에버그린약국 1
 
1.9%
가좌마트약국 1
 
1.9%
굿모닝약국 1
 
1.9%
검단마트약국 1
 
1.9%
Other values (43) 43
81.1%
2024-01-28T22:41:25.692959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
약 54
 
18.0%
국 53
 
17.7%
라 8
 
2.7%
리 7
 
2.3%
누 6
 
2.0%
온 5
 
1.7%
마 5
 
1.7%
청 5
 
1.7%
디 4
 
1.3%
한 4
 
1.3%
Other values (99) 149
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 294
98.0%
Decimal Number 6
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
약 54
 
18.4%
국 53
 
18.0%
라 8
 
2.7%
리 7
 
2.4%
누 6
 
2.0%
온 5
 
1.7%
마 5
 
1.7%
청 5
 
1.7%
디 4
 
1.4%
한 4
 
1.4%
Other values (94) 143
48.6%
Decimal Number
ValueCountFrequency (%)
0 2
33.3%
5 1
16.7%
6 1
16.7%
3 1
16.7%
1 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 294
98.0%
Common 6
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
약 54
 
18.4%
국 53
 
18.0%
라 8
 
2.7%
리 7
 
2.4%
누 6
 
2.0%
온 5
 
1.7%
마 5
 
1.7%
청 5
 
1.7%
디 4
 
1.4%
한 4
 
1.4%
Other values (94) 143
48.6%
Common
ValueCountFrequency (%)
0 2
33.3%
5 1
16.7%
6 1
16.7%
3 1
16.7%
1 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 294
98.0%
ASCII 6
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
약 54
 
18.4%
국 53
 
18.0%
라 8
 
2.7%
리 7
 
2.4%
누 6
 
2.0%
온 5
 
1.7%
마 5
 
1.7%
청 5
 
1.7%
디 4
 
1.4%
한 4
 
1.4%
Other values (94) 143
48.6%
ASCII
ValueCountFrequency (%)
0 2
33.3%
5 1
16.7%
6 1
16.7%
3 1
16.7%
1 1
16.7%

소재지
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-01-28T22:41:25.923914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length18.132075
Min length15

Characters and Unicode

Total characters961
Distinct characters80
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

Unique53 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 청라에메랄드로 84
2nd row인천광역시 서구 검단로 759
3rd row인천광역시 서구 완정로178번길 31
4th row인천광역시 서구 완정로 35
5th row인천광역시 서구 거북로 74-1
ValueCountFrequency (%)
인천광역시 53
24.1%
서구 53
24.1%
가정로 7
 
3.2%
검단로 5
 
2.3%
완정로 4
 
1.8%
거북로 3
 
1.4%
서곶로 3
 
1.4%
청라라임로 2
 
0.9%
중봉대로 2
 
0.9%
836 2
 
0.9%
Other values (81) 86
39.1%
2024-01-28T22:41:26.258317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
167
17.4%
서 58
 
6.0%
인 53
 
5.5%
로 53
 
5.5%
광 53
 
5.5%
역 53
 
5.5%
시 53
 
5.5%
구 53
 
5.5%
천 53
 
5.5%
1 36
 
3.7%
Other values (70) 329
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 604
62.9%
Decimal Number 183
 
19.0%
Space Separator 167
 
17.4%
Dash Punctuation 7
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 58
 
9.6%
인 53
 
8.8%
로 53
 
8.8%
광 53
 
8.8%
역 53
 
8.8%
시 53
 
8.8%
구 53
 
8.8%
천 53
 
8.8%
정 13
 
2.2%
길 12
 
2.0%
Other values (58) 150
24.8%
Decimal Number
ValueCountFrequency (%)
1 36
19.7%
3 20
10.9%
7 20
10.9%
0 19
10.4%
4 16
8.7%
2 16
8.7%
8 15
8.2%
5 14
 
7.7%
9 14
 
7.7%
6 13
 
7.1%
Space Separator
ValueCountFrequency (%)
167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 604
62.9%
Common 357
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 58
 
9.6%
인 53
 
8.8%
로 53
 
8.8%
광 53
 
8.8%
역 53
 
8.8%
시 53
 
8.8%
구 53
 
8.8%
천 53
 
8.8%
정 13
 
2.2%
길 12
 
2.0%
Other values (58) 150
24.8%
Common
ValueCountFrequency (%)
167
46.8%
1 36
 
10.1%
3 20
 
5.6%
7 20
 
5.6%
0 19
 
5.3%
4 16
 
4.5%
2 16
 
4.5%
8 15
 
4.2%
5 14
 
3.9%
9 14
 
3.9%
Other values (2) 20
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 604
62.9%
ASCII 357
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
167
46.8%
1 36
 
10.1%
3 20
 
5.6%
7 20
 
5.6%
0 19
 
5.3%
4 16
 
4.5%
2 16
 
4.5%
8 15
 
4.2%
5 14
 
3.9%
9 14
 
3.9%
Other values (2) 20
 
5.6%
Hangul
ValueCountFrequency (%)
서 58
 
9.6%
인 53
 
8.8%
로 53
 
8.8%
광 53
 
8.8%
역 53
 
8.8%
시 53
 
8.8%
구 53
 
8.8%
천 53
 
8.8%
정 13
 
2.2%
길 12
 
2.0%
Other values (58) 150
24.8%

운영시간
Text

Distinct30
Distinct (%)56.6%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-01-28T22:41:26.423275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters583
Distinct characters11
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

Unique22 ?
Unique (%)41.5%

Sample

1st row11:00~20:00
2nd row14:00~22:00
3rd row09:00~21:00
4th row10:00~14:00
5th row08:00~18:00
ValueCountFrequency (%)
09:00~13:00 7
 
13.2%
09:00~19:00 6
 
11.3%
12:00~18:00 3
 
5.7%
09:00~21:00 3
 
5.7%
10:00~21:00 3
 
5.7%
09:00~14:00 3
 
5.7%
09:00~20:00 3
 
5.7%
09:00~18:00 3
 
5.7%
10:00~17:00 1
 
1.9%
13:00~21:00 1
 
1.9%
Other values (20) 20
37.7%
2024-01-28T22:41:26.681500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 250
42.9%
: 106
18.2%
1 71
 
12.2%
~ 53
 
9.1%
9 37
 
6.3%
2 30
 
5.1%
3 14
 
2.4%
8 11
 
1.9%
4 6
 
1.0%
7 3
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 424
72.7%
Other Punctuation 106
 
18.2%
Math Symbol 53
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 250
59.0%
1 71
 
16.7%
9 37
 
8.7%
2 30
 
7.1%
3 14
 
3.3%
8 11
 
2.6%
4 6
 
1.4%
7 3
 
0.7%
5 2
 
0.5%
Other Punctuation
ValueCountFrequency (%)
: 106
100.0%
Math Symbol
ValueCountFrequency (%)
~ 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 583
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 250
42.9%
: 106
18.2%
1 71
 
12.2%
~ 53
 
9.1%
9 37
 
6.3%
2 30
 
5.1%
3 14
 
2.4%
8 11
 
1.9%
4 6
 
1.0%
7 3
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 583
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 250
42.9%
: 106
18.2%
1 71
 
12.2%
~ 53
 
9.1%
9 37
 
6.3%
2 30
 
5.1%
3 14
 
2.4%
8 11
 
1.9%
4 6
 
1.0%
7 3
 
0.5%

주별
Categorical

IMBALANCE 

Distinct7
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size556.0 B
매주
40 
1, 3, 5째주
5 
2, 4, 5째주
 
3
2, 4째주
 
2
1, 3째주
 
1
Other values (2)
 
2

Length

Max length12
Median length2
Mean length3.490566
Min length2

Unique

Unique3 ?
Unique (%)5.7%

Sample

1st row매주
2nd row1, 3, 5째주
3rd row매주
4th row매주
5th row매주

Common Values

ValueCountFrequency (%)
매주 40
75.5%
1, 3, 5째주 5
 
9.4%
2, 4, 5째주 3
 
5.7%
2, 4째주 2
 
3.8%
1, 3째주 1
 
1.9%
5째주 1
 
1.9%
2, 3, 4, 5째주 1
 
1.9%

Length

2024-01-28T22:41:26.791235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T22:41:26.896702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
매주 40
53.3%
5째주 10
 
13.3%
1 6
 
8.0%
3 6
 
8.0%
2 6
 
8.0%
4 4
 
5.3%
4째주 2
 
2.7%
3째주 1
 
1.3%

연락처
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-01-28T22:41:27.096695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.113208
Min length12

Characters and Unicode

Total characters642
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

Unique53 ?
Unique (%)100.0%

Sample

1st row032-865-2222
2nd row032-566-2624
3rd row032-563-3245
4th row032-565-1201
5th row032-571-6066
ValueCountFrequency (%)
032-865-2222 1
 
1.9%
032-571-6956 1
 
1.9%
032-715-6038 1
 
1.9%
032-576-7530 1
 
1.9%
032-568-3258 1
 
1.9%
032-575-8899 1
 
1.9%
032-582-7799 1
 
1.9%
032-571-6555 1
 
1.9%
032-579-7571 1
 
1.9%
032-564-7588 1
 
1.9%
Other values (43) 43
81.1%
2024-01-28T22:41:27.433180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 106
16.5%
0 80
12.5%
2 79
12.3%
5 79
12.3%
3 72
11.2%
7 56
8.7%
6 53
8.3%
8 46
7.2%
1 28
 
4.4%
9 24
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 536
83.5%
Dash Punctuation 106
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 80
14.9%
2 79
14.7%
5 79
14.7%
3 72
13.4%
7 56
10.4%
6 53
9.9%
8 46
8.6%
1 28
 
5.2%
9 24
 
4.5%
4 19
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 642
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 106
16.5%
0 80
12.5%
2 79
12.3%
5 79
12.3%
3 72
11.2%
7 56
8.7%
6 53
8.3%
8 46
7.2%
1 28
 
4.4%
9 24
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 642
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 106
16.5%
0 80
12.5%
2 79
12.3%
5 79
12.3%
3 72
11.2%
7 56
8.7%
6 53
8.3%
8 46
7.2%
1 28
 
4.4%
9 24
 
3.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2022-09-05 00:00:00
Maximum2022-09-05 00:00:00
2024-01-28T22:41:27.537452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:41:27.614253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T22:41:24.730912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T22:41:27.674919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번약국명소재지운영시간주별연락처
연번1.0001.0001.0000.0000.2421.000
약국명1.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.000
운영시간0.0001.0001.0001.0000.0001.000
주별0.2421.0001.0000.0001.0001.000
연락처1.0001.0001.0001.0001.0001.000
2024-01-28T22:41:27.755651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주별
연번1.0000.099
주별0.0991.000

Missing values

2024-01-28T22:41:24.828299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T22:41:24.929979image/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

연번약국명소재지운영시간주별연락처데이터기준일자
01옵티마강남약국인천광역시 서구 청라에메랄드로 8411:00~20:00매주032-865-22222022-09-05
12불로스타약국인천광역시 서구 검단로 75914:00~22:001, 3, 5째주032-566-26242022-09-05
23단오약국인천광역시 서구 완정로178번길 3109:00~21:00매주032-563-32452022-09-05
34위드팜100세약국인천광역시 서구 완정로 3510:00~14:00매주032-565-12012022-09-05
45자생약국인천광역시 서구 거북로 74-108:00~18:00매주032-571-60662022-09-05
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