Overview

Dataset statistics

Number of variables12
Number of observations141
Missing cells291
Missing cells (%)17.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.5 KiB
Average record size in memory97.9 B

Variable types

Numeric1
Text11

Dataset

Description대구광역시 중구 관내 약국 관련 정보(약국명, 대표전화, 주소, 요일별 운영현황, 공유일 운영 여부 등) 를 제공합니다
Author대구광역시 중구
URLhttps://www.data.go.kr/data/15043055/fileData.do

Alerts

토요일 운영 has 50 (35.5%) missing valuesMissing
일요일 운영 has 124 (87.9%) missing valuesMissing
공휴일 운영 has 117 (83.0%) missing valuesMissing
번호 has unique valuesUnique
약국명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:53:09.181526
Analysis finished2023-12-12 15:53:10.620692
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71
Minimum1
Maximum141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T00:53:10.760430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q136
median71
Q3106
95-th percentile134
Maximum141
Range140
Interquartile range (IQR)70

Descriptive statistics

Standard deviation40.847277
Coefficient of variation (CV)0.57531375
Kurtosis-1.2
Mean71
Median Absolute Deviation (MAD)35
Skewness0
Sum10011
Variance1668.5
MonotonicityStrictly increasing
2023-12-13T00:53:10.959967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
98 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
99 1
 
0.7%
90 1
 
0.7%
Other values (131) 131
92.9%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%

약국명
Text

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T00:53:11.377000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.5319149
Min length3

Characters and Unicode

Total characters639
Distinct characters144
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

Unique141 ?
Unique (%)100.0%

Sample

1st row장춘당약국
2nd row서문로약국
3rd row플러스약국
4th row프라자약국
5th row세명약국
ValueCountFrequency (%)
장춘당약국 1
 
0.7%
문앞약국 1
 
0.7%
제현당약국 1
 
0.7%
하은약국 1
 
0.7%
정문약국 1
 
0.7%
대학당약국 1
 
0.7%
경북제일약국 1
 
0.7%
미래약국 1
 
0.7%
삼덕약국 1
 
0.7%
영남약국 1
 
0.7%
Other values (131) 131
92.9%
2023-12-13T00:53:11.930082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
약 141
22.1%
국 141
22.1%
대 13
 
2.0%
리 11
 
1.7%
당 8
 
1.3%
문 8
 
1.3%
일 8
 
1.3%
한 8
 
1.3%
신 7
 
1.1%
온 6
 
0.9%
Other values (134) 288
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 638
99.8%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
약 141
22.1%
국 141
22.1%
대 13
 
2.0%
리 11
 
1.7%
당 8
 
1.3%
문 8
 
1.3%
일 8
 
1.3%
한 8
 
1.3%
신 7
 
1.1%
온 6
 
0.9%
Other values (133) 287
45.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 638
99.8%
Common 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
약 141
22.1%
국 141
22.1%
대 13
 
2.0%
리 11
 
1.7%
당 8
 
1.3%
문 8
 
1.3%
일 8
 
1.3%
한 8
 
1.3%
신 7
 
1.1%
온 6
 
0.9%
Other values (133) 287
45.0%
Common
ValueCountFrequency (%)
& 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 638
99.8%
ASCII 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
약 141
22.1%
국 141
22.1%
대 13
 
2.0%
리 11
 
1.7%
당 8
 
1.3%
문 8
 
1.3%
일 8
 
1.3%
한 8
 
1.3%
신 7
 
1.1%
온 6
 
0.9%
Other values (133) 287
45.0%
ASCII
ValueCountFrequency (%)
& 1
100.0%

대표전화
Text

Distinct140
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T00:53:12.198269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.007092
Min length12

Characters and Unicode

Total characters1693
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

Unique139 ?
Unique (%)98.6%

Sample

1st row053-424-9393
2nd row053-253-6223
3rd row053-257-3717
4th row053-563-8828
5th row053-255-7785
ValueCountFrequency (%)
053-212-6030 2
 
1.4%
053-431-1011 1
 
0.7%
053-423-5989 1
 
0.7%
053-253-7003 1
 
0.7%
053-255-1554 1
 
0.7%
053-423-3239 1
 
0.7%
053-255-3989 1
 
0.7%
053-252-0936 1
 
0.7%
053-254-1985 1
 
0.7%
053-253-3900 1
 
0.7%
Other values (130) 130
92.2%
2023-12-13T00:53:12.622560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 301
17.8%
- 282
16.7%
3 222
13.1%
2 215
12.7%
0 212
12.5%
4 135
8.0%
7 75
 
4.4%
8 68
 
4.0%
1 66
 
3.9%
6 64
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1411
83.3%
Dash Punctuation 282
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 301
21.3%
3 222
15.7%
2 215
15.2%
0 212
15.0%
4 135
9.6%
7 75
 
5.3%
8 68
 
4.8%
1 66
 
4.7%
6 64
 
4.5%
9 53
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 282
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1693
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 301
17.8%
- 282
16.7%
3 222
13.1%
2 215
12.7%
0 212
12.5%
4 135
8.0%
7 75
 
4.4%
8 68
 
4.0%
1 66
 
3.9%
6 64
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1693
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 301
17.8%
- 282
16.7%
3 222
13.1%
2 215
12.7%
0 212
12.5%
4 135
8.0%
7 75
 
4.4%
8 68
 
4.0%
1 66
 
3.9%
6 64
 
3.8%

주소
Text

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T00:53:12.987204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length43
Mean length25.539007
Min length15

Characters and Unicode

Total characters3601
Distinct characters100
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

Unique141 ?
Unique (%)100.0%

Sample

1st row대구광역시 중구 경상감영길 189 (동문동)
2nd row대구광역시 중구 경상감영길 48 (서문로1가)
3rd row대구광역시 중구 공평로 20 (삼덕동2가)
4th row대구광역시 중구 국채보상로 447 (대신동)
5th row대구광역시 중구 국채보상로 468 (대신동)
ValueCountFrequency (%)
대구광역시 141
19.1%
중구 141
19.1%
달구벌대로 28
 
3.8%
국채보상로 25
 
3.4%
1층 23
 
3.1%
남산동 16
 
2.2%
중앙대로 15
 
2.0%
삼덕동2가 13
 
1.8%
동덕로 12
 
1.6%
달성로 9
 
1.2%
Other values (209) 315
42.7%
2023-12-13T00:53:13.542409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
597
16.6%
구 312
 
8.7%
대 204
 
5.7%
동 162
 
4.5%
중 157
 
4.4%
로 149
 
4.1%
역 144
 
4.0%
1 143
 
4.0%
광 141
 
3.9%
시 141
 
3.9%
Other values (90) 1451
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2085
57.9%
Decimal Number 602
 
16.7%
Space Separator 597
 
16.6%
Close Punctuation 114
 
3.2%
Open Punctuation 114
 
3.2%
Other Punctuation 64
 
1.8%
Dash Punctuation 19
 
0.5%
Uppercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 312
15.0%
대 204
 
9.8%
동 162
 
7.8%
중 157
 
7.5%
로 149
 
7.1%
역 144
 
6.9%
광 141
 
6.8%
시 141
 
6.8%
덕 51
 
2.4%
산 41
 
2.0%
Other values (72) 583
28.0%
Decimal Number
ValueCountFrequency (%)
1 143
23.8%
2 108
17.9%
3 71
11.8%
4 55
 
9.1%
0 53
 
8.8%
9 41
 
6.8%
5 40
 
6.6%
6 34
 
5.6%
8 30
 
5.0%
7 27
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
W 3
50.0%
C 2
33.3%
B 1
 
16.7%
Space Separator
ValueCountFrequency (%)
597
100.0%
Close Punctuation
ValueCountFrequency (%)
) 114
100.0%
Open Punctuation
ValueCountFrequency (%)
( 114
100.0%
Other Punctuation
ValueCountFrequency (%)
, 64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2085
57.9%
Common 1510
41.9%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 312
15.0%
대 204
 
9.8%
동 162
 
7.8%
중 157
 
7.5%
로 149
 
7.1%
역 144
 
6.9%
광 141
 
6.8%
시 141
 
6.8%
덕 51
 
2.4%
산 41
 
2.0%
Other values (72) 583
28.0%
Common
ValueCountFrequency (%)
597
39.5%
1 143
 
9.5%
) 114
 
7.5%
( 114
 
7.5%
2 108
 
7.2%
3 71
 
4.7%
, 64
 
4.2%
4 55
 
3.6%
0 53
 
3.5%
9 41
 
2.7%
Other values (5) 150
 
9.9%
Latin
ValueCountFrequency (%)
W 3
50.0%
C 2
33.3%
B 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2085
57.9%
ASCII 1516
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
597
39.4%
1 143
 
9.4%
) 114
 
7.5%
( 114
 
7.5%
2 108
 
7.1%
3 71
 
4.7%
, 64
 
4.2%
4 55
 
3.6%
0 53
 
3.5%
9 41
 
2.7%
Other values (8) 156
 
10.3%
Hangul
ValueCountFrequency (%)
구 312
15.0%
대 204
 
9.8%
동 162
 
7.8%
중 157
 
7.5%
로 149
 
7.1%
역 144
 
6.9%
광 141
 
6.8%
시 141
 
6.8%
덕 51
 
2.4%
산 41
 
2.0%
Other values (72) 583
28.0%

월요일 운영
Text

Distinct57
Distinct (%)40.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T00:53:13.807852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters1551
Distinct characters12
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

Unique37 ?
Unique (%)26.2%

Sample

1st row08:30~20:00
2nd row09:30~18:30
3rd row09:30~20:30
4th row08:30~19:00
5th row09:00~18:00
ValueCountFrequency (%)
09:00~18:00 20
 
14.2%
09:00~19:00 17
 
12.1%
09:00~18:30 10
 
7.1%
09:00~13:00 7
 
5.0%
09:00~17:00 6
 
4.3%
09:00~20:00 5
 
3.5%
09:30~19:00 4
 
2.8%
09:00~21:00 4
 
2.8%
08:30~19:00 4
 
2.8%
09:00~14:00 4
 
2.8%
Other values (47) 60
42.6%
2023-12-13T00:53:14.269260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 646
41.7%
: 282
18.2%
1 146
 
9.4%
~ 141
 
9.1%
9 132
 
8.5%
8 68
 
4.4%
3 68
 
4.4%
2 38
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1128
72.7%
Other Punctuation 282
 
18.2%
Math Symbol 141
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 646
57.3%
1 146
 
12.9%
9 132
 
11.7%
8 68
 
6.0%
3 68
 
6.0%
2 38
 
3.4%
7 13
 
1.2%
5 7
 
0.6%
4 6
 
0.5%
6 4
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 282
100.0%
Math Symbol
ValueCountFrequency (%)
~ 141
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1551
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 646
41.7%
: 282
18.2%
1 146
 
9.4%
~ 141
 
9.1%
9 132
 
8.5%
8 68
 
4.4%
3 68
 
4.4%
2 38
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 646
41.7%
: 282
18.2%
1 146
 
9.4%
~ 141
 
9.1%
9 132
 
8.5%
8 68
 
4.4%
3 68
 
4.4%
2 38
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

화요일 운영
Text

Distinct56
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T00:53:14.539461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters1551
Distinct characters12
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

Unique36 ?
Unique (%)25.5%

Sample

1st row08:30~20:00
2nd row09:30~18:30
3rd row09:30~20:30
4th row08:30~19:00
5th row09:00~18:00
ValueCountFrequency (%)
09:00~18:00 20
 
14.2%
09:00~19:00 18
 
12.8%
09:00~18:30 10
 
7.1%
09:00~13:00 7
 
5.0%
09:00~17:00 6
 
4.3%
09:00~21:00 5
 
3.5%
09:30~19:00 4
 
2.8%
08:30~19:00 4
 
2.8%
09:00~14:00 4
 
2.8%
09:00~16:00 3
 
2.1%
Other values (46) 60
42.6%
2023-12-13T00:53:14.938251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 645
41.6%
: 282
18.2%
1 147
 
9.5%
~ 141
 
9.1%
9 133
 
8.6%
3 68
 
4.4%
8 67
 
4.3%
2 38
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1128
72.7%
Other Punctuation 282
 
18.2%
Math Symbol 141
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 645
57.2%
1 147
 
13.0%
9 133
 
11.8%
3 68
 
6.0%
8 67
 
5.9%
2 38
 
3.4%
7 13
 
1.2%
5 7
 
0.6%
4 6
 
0.5%
6 4
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 282
100.0%
Math Symbol
ValueCountFrequency (%)
~ 141
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1551
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 645
41.6%
: 282
18.2%
1 147
 
9.5%
~ 141
 
9.1%
9 133
 
8.6%
3 68
 
4.4%
8 67
 
4.3%
2 38
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 645
41.6%
: 282
18.2%
1 147
 
9.5%
~ 141
 
9.1%
9 133
 
8.6%
3 68
 
4.4%
8 67
 
4.3%
2 38
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

수요일 운영
Text

Distinct56
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T00:53:15.223025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters1551
Distinct characters12
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

Unique35 ?
Unique (%)24.8%

Sample

1st row08:30~20:00
2nd row09:30~18:30
3rd row09:30~20:30
4th row08:30~19:00
5th row09:00~18:00
ValueCountFrequency (%)
09:00~18:00 20
 
14.2%
09:00~19:00 17
 
12.1%
09:00~18:30 10
 
7.1%
09:00~13:00 7
 
5.0%
09:00~17:00 6
 
4.3%
09:00~21:00 4
 
2.8%
09:00~20:00 4
 
2.8%
09:30~19:00 4
 
2.8%
09:00~14:00 4
 
2.8%
08:30~19:00 4
 
2.8%
Other values (46) 61
43.3%
2023-12-13T00:53:15.865302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 645
41.6%
: 282
18.2%
1 146
 
9.4%
~ 141
 
9.1%
9 133
 
8.6%
3 69
 
4.4%
8 67
 
4.3%
2 38
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1128
72.7%
Other Punctuation 282
 
18.2%
Math Symbol 141
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 645
57.2%
1 146
 
12.9%
9 133
 
11.8%
3 69
 
6.1%
8 67
 
5.9%
2 38
 
3.4%
7 13
 
1.2%
5 7
 
0.6%
4 6
 
0.5%
6 4
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 282
100.0%
Math Symbol
ValueCountFrequency (%)
~ 141
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1551
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 645
41.6%
: 282
18.2%
1 146
 
9.4%
~ 141
 
9.1%
9 133
 
8.6%
3 69
 
4.4%
8 67
 
4.3%
2 38
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 645
41.6%
: 282
18.2%
1 146
 
9.4%
~ 141
 
9.1%
9 133
 
8.6%
3 69
 
4.4%
8 67
 
4.3%
2 38
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

목요일 운영
Text

Distinct56
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T00:53:16.191132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters1551
Distinct characters12
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

Unique36 ?
Unique (%)25.5%

Sample

1st row08:30~20:00
2nd row09:30~18:30
3rd row09:30~20:30
4th row08:30~19:00
5th row09:00~18:00
ValueCountFrequency (%)
09:00~18:00 20
 
14.2%
09:00~19:00 18
 
12.8%
09:00~18:30 10
 
7.1%
09:00~13:00 7
 
5.0%
09:00~17:00 6
 
4.3%
09:00~20:00 4
 
2.8%
09:30~19:00 4
 
2.8%
08:30~19:00 4
 
2.8%
09:00~21:00 4
 
2.8%
09:00~14:00 4
 
2.8%
Other values (46) 60
42.6%
2023-12-13T00:53:16.625772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 645
41.6%
: 282
18.2%
1 147
 
9.5%
~ 141
 
9.1%
9 134
 
8.6%
3 68
 
4.4%
8 67
 
4.3%
2 37
 
2.4%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1128
72.7%
Other Punctuation 282
 
18.2%
Math Symbol 141
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 645
57.2%
1 147
 
13.0%
9 134
 
11.9%
3 68
 
6.0%
8 67
 
5.9%
2 37
 
3.3%
7 13
 
1.2%
5 7
 
0.6%
4 6
 
0.5%
6 4
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 282
100.0%
Math Symbol
ValueCountFrequency (%)
~ 141
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1551
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 645
41.6%
: 282
18.2%
1 147
 
9.5%
~ 141
 
9.1%
9 134
 
8.6%
3 68
 
4.4%
8 67
 
4.3%
2 37
 
2.4%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 645
41.6%
: 282
18.2%
1 147
 
9.5%
~ 141
 
9.1%
9 134
 
8.6%
3 68
 
4.4%
8 67
 
4.3%
2 37
 
2.4%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

금요일 운영
Text

Distinct56
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T00:53:16.911654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters1551
Distinct characters12
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

Unique34 ?
Unique (%)24.1%

Sample

1st row08:30~20:00
2nd row09:30~18:30
3rd row09:30~20:30
4th row08:30~19:00
5th row09:00~18:00
ValueCountFrequency (%)
09:00~18:00 19
 
13.5%
09:00~19:00 18
 
12.8%
09:00~18:30 10
 
7.1%
09:00~13:00 7
 
5.0%
09:00~17:00 6
 
4.3%
09:00~21:00 5
 
3.5%
08:30~19:00 4
 
2.8%
09:30~19:00 4
 
2.8%
09:00~14:00 4
 
2.8%
09:00~16:00 3
 
2.1%
Other values (46) 61
43.3%
2023-12-13T00:53:17.297770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 644
41.5%
: 282
18.2%
1 147
 
9.5%
~ 141
 
9.1%
9 133
 
8.6%
3 69
 
4.4%
8 66
 
4.3%
2 39
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1128
72.7%
Other Punctuation 282
 
18.2%
Math Symbol 141
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 644
57.1%
1 147
 
13.0%
9 133
 
11.8%
3 69
 
6.1%
8 66
 
5.9%
2 39
 
3.5%
7 13
 
1.2%
5 7
 
0.6%
4 6
 
0.5%
6 4
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 282
100.0%
Math Symbol
ValueCountFrequency (%)
~ 141
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1551
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 644
41.5%
: 282
18.2%
1 147
 
9.5%
~ 141
 
9.1%
9 133
 
8.6%
3 69
 
4.4%
8 66
 
4.3%
2 39
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 644
41.5%
: 282
18.2%
1 147
 
9.5%
~ 141
 
9.1%
9 133
 
8.6%
3 69
 
4.4%
8 66
 
4.3%
2 39
 
2.5%
7 13
 
0.8%
5 7
 
0.5%
Other values (2) 10
 
0.6%

토요일 운영
Text

MISSING 

Distinct47
Distinct (%)51.6%
Missing50
Missing (%)35.5%
Memory size1.2 KiB
2023-12-13T00:53:17.638082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters1001
Distinct characters12
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

Unique32 ?
Unique (%)35.2%

Sample

1st row09:00~20:00
2nd row09:30~14:00
3rd row09:30~18:30
4th row08:30~19:00
5th row08:30~13:00
ValueCountFrequency (%)
09:00~13:00 10
 
11.0%
09:00~17:00 9
 
9.9%
09:00~15:00 6
 
6.6%
09:00~16:00 5
 
5.5%
09:00~14:00 4
 
4.4%
09:00~18:00 4
 
4.4%
09:30~16:00 3
 
3.3%
09:00~21:00 3
 
3.3%
09:00~20:00 3
 
3.3%
08:30~13:00 2
 
2.2%
Other values (37) 42
46.2%
2023-12-13T00:53:18.139765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 418
41.8%
: 182
18.2%
1 94
 
9.4%
~ 91
 
9.1%
9 69
 
6.9%
3 52
 
5.2%
2 26
 
2.6%
8 23
 
2.3%
7 14
 
1.4%
6 12
 
1.2%
Other values (2) 20
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 728
72.7%
Other Punctuation 182
 
18.2%
Math Symbol 91
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 418
57.4%
1 94
 
12.9%
9 69
 
9.5%
3 52
 
7.1%
2 26
 
3.6%
8 23
 
3.2%
7 14
 
1.9%
6 12
 
1.6%
5 11
 
1.5%
4 9
 
1.2%
Other Punctuation
ValueCountFrequency (%)
: 182
100.0%
Math Symbol
ValueCountFrequency (%)
~ 91
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1001
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 418
41.8%
: 182
18.2%
1 94
 
9.4%
~ 91
 
9.1%
9 69
 
6.9%
3 52
 
5.2%
2 26
 
2.6%
8 23
 
2.3%
7 14
 
1.4%
6 12
 
1.2%
Other values (2) 20
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1001
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 418
41.8%
: 182
18.2%
1 94
 
9.4%
~ 91
 
9.1%
9 69
 
6.9%
3 52
 
5.2%
2 26
 
2.6%
8 23
 
2.3%
7 14
 
1.4%
6 12
 
1.2%
Other values (2) 20
 
2.0%

일요일 운영
Text

MISSING 

Distinct16
Distinct (%)94.1%
Missing124
Missing (%)87.9%
Memory size1.2 KiB
2023-12-13T00:53:18.352973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters187
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

Unique15 ?
Unique (%)88.2%

Sample

1st row08:50~17:50
2nd row13:00~20:00
3rd row09:00~20:00
4th row09:00~21:00
5th row08:00~22:00
ValueCountFrequency (%)
09:00~13:00 2
 
11.8%
08:50~17:50 1
 
5.9%
13:00~20:00 1
 
5.9%
09:00~20:00 1
 
5.9%
09:00~21:00 1
 
5.9%
08:00~22:00 1
 
5.9%
08:30~21:00 1
 
5.9%
08:30~21:10 1
 
5.9%
11:00~24:00 1
 
5.9%
11:00~17:00 1
 
5.9%
Other values (6) 6
35.3%
2023-12-13T00:53:18.751620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72
38.5%
: 34
18.2%
1 19
 
10.2%
~ 17
 
9.1%
2 13
 
7.0%
3 11
 
5.9%
8 7
 
3.7%
9 6
 
3.2%
5 4
 
2.1%
7 3
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 136
72.7%
Other Punctuation 34
 
18.2%
Math Symbol 17
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72
52.9%
1 19
 
14.0%
2 13
 
9.6%
3 11
 
8.1%
8 7
 
5.1%
9 6
 
4.4%
5 4
 
2.9%
7 3
 
2.2%
4 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
: 34
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 187
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72
38.5%
: 34
18.2%
1 19
 
10.2%
~ 17
 
9.1%
2 13
 
7.0%
3 11
 
5.9%
8 7
 
3.7%
9 6
 
3.2%
5 4
 
2.1%
7 3
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 187
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72
38.5%
: 34
18.2%
1 19
 
10.2%
~ 17
 
9.1%
2 13
 
7.0%
3 11
 
5.9%
8 7
 
3.7%
9 6
 
3.2%
5 4
 
2.1%
7 3
 
1.6%

공휴일 운영
Text

MISSING 

Distinct21
Distinct (%)87.5%
Missing117
Missing (%)83.0%
Memory size1.2 KiB
2023-12-13T00:53:18.977503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters264
Distinct characters12
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

Unique19 ?
Unique (%)79.2%

Sample

1st row08:30~19:00
2nd row08:30~19:30
3rd row08:50~17:50
4th row12:00~21:00
5th row13:00~20:00
ValueCountFrequency (%)
09:00~13:00 3
 
12.5%
09:00~14:00 2
 
8.3%
09:00~16:00 1
 
4.2%
09:00~17:00 1
 
4.2%
09:00~22:30 1
 
4.2%
15:00~21:00 1
 
4.2%
08:30~13:30 1
 
4.2%
11:00~17:00 1
 
4.2%
09:30~21:30 1
 
4.2%
10:00~21:00 1
 
4.2%
Other values (11) 11
45.8%
2023-12-13T00:53:19.354472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 102
38.6%
: 48
18.2%
1 28
 
10.6%
~ 24
 
9.1%
3 16
 
6.1%
2 15
 
5.7%
9 13
 
4.9%
8 7
 
2.7%
5 4
 
1.5%
7 4
 
1.5%
Other values (2) 3
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 192
72.7%
Other Punctuation 48
 
18.2%
Math Symbol 24
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 102
53.1%
1 28
 
14.6%
3 16
 
8.3%
2 15
 
7.8%
9 13
 
6.8%
8 7
 
3.6%
5 4
 
2.1%
7 4
 
2.1%
4 2
 
1.0%
6 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
: 48
100.0%
Math Symbol
ValueCountFrequency (%)
~ 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 264
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 102
38.6%
: 48
18.2%
1 28
 
10.6%
~ 24
 
9.1%
3 16
 
6.1%
2 15
 
5.7%
9 13
 
4.9%
8 7
 
2.7%
5 4
 
1.5%
7 4
 
1.5%
Other values (2) 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 264
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 102
38.6%
: 48
18.2%
1 28
 
10.6%
~ 24
 
9.1%
3 16
 
6.1%
2 15
 
5.7%
9 13
 
4.9%
8 7
 
2.7%
5 4
 
1.5%
7 4
 
1.5%
Other values (2) 3
 
1.1%

Interactions

2023-12-13T00:53:10.003661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:53:19.493508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호월요일 운영화요일 운영수요일 운영목요일 운영금요일 운영토요일 운영일요일 운영공휴일 운영
번호1.0000.4280.3910.4900.4610.4800.6281.0000.929
월요일 운영0.4281.0001.0001.0001.0001.0000.9861.0000.983
화요일 운영0.3911.0001.0001.0001.0001.0000.9851.0000.957
수요일 운영0.4901.0001.0001.0001.0001.0000.9851.0000.958
목요일 운영0.4611.0001.0001.0001.0001.0000.9861.0000.983
금요일 운영0.4801.0001.0001.0001.0001.0000.9851.0000.900
토요일 운영0.6280.9860.9850.9850.9860.9851.0001.0000.989
일요일 운영1.0001.0001.0001.0001.0001.0001.0001.0001.000
공휴일 운영0.9290.9830.9570.9580.9830.9000.9891.0001.000

Missing values

2023-12-13T00:53:10.152145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:53:10.377950image/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.
2023-12-13T00:53:10.548640image/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

번호약국명대표전화주소월요일 운영화요일 운영수요일 운영목요일 운영금요일 운영토요일 운영일요일 운영공휴일 운영
01장춘당약국053-424-9393대구광역시 중구 경상감영길 189 (동문동)08:30~20:0008:30~20:0008:30~20:0008:30~20:0008:30~20:0009:00~20:00<NA><NA>
12서문로약국053-253-6223대구광역시 중구 경상감영길 48 (서문로1가)09:30~18:3009:30~18:3009:30~18:3009:30~18:3009:30~18:3009:30~14:00<NA><NA>
23플러스약국053-257-3717대구광역시 중구 공평로 20 (삼덕동2가)09:30~20:3009:30~20:3009:30~20:3009:30~20:3009:30~20:3009:30~18:30<NA><NA>
34프라자약국053-563-8828대구광역시 중구 국채보상로 447 (대신동)08:30~19:0008:30~19:0008:30~19:0008:30~19:0008:30~19:0008:30~19:00<NA>08:30~19:00
45세명약국053-255-7785대구광역시 중구 국채보상로 468 (대신동)09:00~18:0009:00~18:0009:00~18:0009:00~18:0009:00~18:00<NA><NA>08:30~19:30
56위드팜새동산약국053-252-6292대구광역시 중구 국채보상로 474 (동산동)08:30~19:0008:30~19:0008:30~19:0008:30~19:0008:30~19:0008:30~13:00<NA><NA>
67나사렛약국053-255-7839대구광역시 중구 국채보상로 476 (동산동)08:30~18:3008:30~18:3008:30~18:3008:30~18:3008:30~18:3009:00~14:00<NA><NA>
78문전약국053-426-9988대구광역시 중구 국채보상로 47809:00~12:0009:00~12:0009:00~12:0009:00~12:0009:00~12:00<NA><NA><NA>
89밝은미소약국053-423-3777대구광역시 중구 국채보상로 51109:00~12:0009:00~12:0009:00~12:0009:00~12:0009:00~12:00<NA><NA><NA>
910명문약국053-257-6163대구광역시 중구 국채보상로 524 (하서동)09:00~13:0009:00~13:0009:00~13:0009:00~13:0009:00~13:0009:00~15:00<NA><NA>
번호약국명대표전화주소월요일 운영화요일 운영수요일 운영목요일 운영금요일 운영토요일 운영일요일 운영공휴일 운영
131132미소약국053-252-2959대구광역시 중구 중앙대로 411 (동일동)09:30~19:0009:30~19:0009:30~19:0009:30~19:0009:30~19:0009:30~14:00<NA><NA>
132133신원약국053-425-2286대구광역시 중구 중앙대로 412-2 (남일동)10:00~20:0010:00~20:0010:00~20:0010:00~20:0010:00~20:0010:00~19:00<NA><NA>
133134대하약국053-254-8164대구광역시 중구 중앙대로 447-1 (향촌동)09:00~22:3009:00~22:3009:00~22:3009:00~22:3009:00~22:3009:00~22:0009:30~23:3009:00~22:30
134135동아약국053-424-7775대구광역시 중구 중앙대로 450-1 (화전동)08:00~21:0008:00~21:0008:00~21:0008:00~21:0008:00~21:0008:00~21:0008:00~21:00<NA>
135136마트약국053-257-1007대구광역시 중구 중앙대로66길 20, 지하2층층 (남산동, 반월당효성해링턴플레이스)10:00~22:0010:00~22:0010:00~22:0010:00~22:0010:00~22:0010:00~22:0010:00~22:0010:00~22:00
136137큰시장약국053-257-1234대구광역시 중구 큰장로 13009:00~18:5009:00~18:5009:00~18:5009:00~18:5009:00~18:5009:00~17:00<NA><NA>
137138서문약국053-255-1234대구광역시 중구 큰장로 132 (대신동)08:00~18:3008:00~18:3008:00~18:3008:00~18:3008:00~18:3008:00~18:3008:00~18:30<NA>
138139참평화약국053-256-1000대구광역시 중구 태평로 10209:00~18:3009:00~18:3009:00~18:3009:00~18:3009:00~18:3009:00~13:00<NA><NA>
139140해동약국053-424-9100대구광역시 중구 태평로 168 (태평로1가)09:00~19:0009:00~19:0009:00~19:0009:00~19:0009:00~19:0009:00~13:00<NA><NA>
140141삼행약국053-422-7868대구광역시 중구 태평로 287 (동인동3가)09:00~19:0009:00~19:0009:00~19:0009:00~19:0009:00~19:0009:00~13:00<NA><NA>