Overview

Dataset statistics

Number of variables4
Number of observations229
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.4%
Total size in memory7.3 KiB
Average record size in memory32.6 B

Variable types

Categorical2
Text2

Dataset

Description경기도 포천시에서 제공하는 코로나19자가진단키드판매소현황(약국, 편의점, 영업장주소, 업업장행정동명)데이터 입니다.
Author경기도 포천시
URLhttps://www.data.go.kr/data/15105125/fileData.do

Alerts

Dataset has 1 (0.4%) duplicate rowsDuplicates

Reproduction

Analysis started2024-04-16 21:28:14.233404
Analysis finished2024-04-16 21:28:15.246757
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
편의점
171 
약국
58 

Length

Max length3
Median length3
Mean length2.7467249
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
편의점 171
74.7%
약국 58
 
25.3%

Length

2024-04-17T06:28:15.304401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:28:15.378206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
편의점 171
74.7%
약국 58
 
25.3%

영업장명칭
Text

Distinct226
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-17T06:28:15.534835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length15
Mean length8.7423581
Min length3

Characters and Unicode

Total characters2002
Distinct characters230
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique223 ?
Unique (%)97.4%

Sample

1st row녹십자약국
2nd row안녕약국
3rd row미소약국
4th row솔약국
5th row우리약국
ValueCountFrequency (%)
씨유 43
 
12.4%
세븐일레븐 26
 
7.5%
gs25 12
 
3.5%
지에스25 12
 
3.5%
cu 6
 
1.7%
이마트24 4
 
1.2%
미니스톱 3
 
0.9%
대진대 3
 
0.9%
주)이마트에브리데이 2
 
0.6%
송우영화점 2
 
0.6%
Other values (224) 234
67.4%
2024-04-17T06:28:15.806478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 166
 
8.3%
천 125
 
6.2%
포 120
 
6.0%
118
 
5.9%
유 64
 
3.2%
씨 62
 
3.1%
국 60
 
3.0%
약 58
 
2.9%
븐 56
 
2.8%
2 53
 
2.6%
Other values (220) 1120
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1667
83.3%
Space Separator 118
 
5.9%
Decimal Number 108
 
5.4%
Uppercase Letter 91
 
4.5%
Close Punctuation 8
 
0.4%
Open Punctuation 8
 
0.4%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 166
 
10.0%
천 125
 
7.5%
포 120
 
7.2%
유 64
 
3.8%
씨 62
 
3.7%
국 60
 
3.6%
약 58
 
3.5%
븐 56
 
3.4%
일 47
 
2.8%
리 38
 
2.3%
Other values (203) 871
52.2%
Uppercase Letter
ValueCountFrequency (%)
S 24
26.4%
G 24
26.4%
U 19
20.9%
C 19
20.9%
R 3
 
3.3%
K 1
 
1.1%
O 1
 
1.1%
Decimal Number
ValueCountFrequency (%)
2 53
49.1%
5 43
39.8%
4 10
 
9.3%
3 1
 
0.9%
6 1
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
g 1
50.0%
Space Separator
ValueCountFrequency (%)
118
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1667
83.3%
Common 242
 
12.1%
Latin 93
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 166
 
10.0%
천 125
 
7.5%
포 120
 
7.2%
유 64
 
3.8%
씨 62
 
3.7%
국 60
 
3.6%
약 58
 
3.5%
븐 56
 
3.4%
일 47
 
2.8%
리 38
 
2.3%
Other values (203) 871
52.2%
Latin
ValueCountFrequency (%)
S 24
25.8%
G 24
25.8%
U 19
20.4%
C 19
20.4%
R 3
 
3.2%
K 1
 
1.1%
O 1
 
1.1%
s 1
 
1.1%
g 1
 
1.1%
Common
ValueCountFrequency (%)
118
48.8%
2 53
21.9%
5 43
 
17.8%
4 10
 
4.1%
) 8
 
3.3%
( 8
 
3.3%
3 1
 
0.4%
6 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1667
83.3%
ASCII 335
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 166
 
10.0%
천 125
 
7.5%
포 120
 
7.2%
유 64
 
3.8%
씨 62
 
3.7%
국 60
 
3.6%
약 58
 
3.5%
븐 56
 
3.4%
일 47
 
2.8%
리 38
 
2.3%
Other values (203) 871
52.2%
ASCII
ValueCountFrequency (%)
118
35.2%
2 53
15.8%
5 43
 
12.8%
S 24
 
7.2%
G 24
 
7.2%
U 19
 
5.7%
C 19
 
5.7%
4 10
 
3.0%
) 8
 
2.4%
( 8
 
2.4%
Other values (7) 9
 
2.7%

영업장재지(도로명)
Text

Distinct222
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-17T06:28:16.069165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length39
Mean length23.921397
Min length17

Characters and Unicode

Total characters5478
Distinct characters171
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique216 ?
Unique (%)94.3%

Sample

1st row경기도 포천시 중앙로 145(신읍동)
2nd row경기도 포천시 영북면 영북로 180
3rd row경기도 포천시 영중면 양문로 79
4th row경기도 포천시 왕방로 130, 1층 (신읍동)
5th row경기도 포천시 소흘읍 호국로 433, 1층
ValueCountFrequency (%)
경기도 229
17.6%
포천시 229
17.6%
1층 100
 
7.7%
소흘읍 67
 
5.1%
호국로 33
 
2.5%
신읍동 32
 
2.5%
선단동 19
 
1.5%
가산면 17
 
1.3%
화동로 16
 
1.2%
일동면 15
 
1.2%
Other values (314) 547
41.9%
2024-04-17T06:28:16.465709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1082
19.8%
1 302
 
5.5%
천 252
 
4.6%
포 247
 
4.5%
경 232
 
4.2%
시 230
 
4.2%
기 230
 
4.2%
도 229
 
4.2%
로 217
 
4.0%
, 126
 
2.3%
Other values (161) 2331
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3144
57.4%
Space Separator 1082
 
19.8%
Decimal Number 936
 
17.1%
Other Punctuation 126
 
2.3%
Open Punctuation 67
 
1.2%
Close Punctuation 67
 
1.2%
Dash Punctuation 48
 
0.9%
Uppercase Letter 3
 
0.1%
Lowercase Letter 3
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 252
 
8.0%
포 247
 
7.9%
경 232
 
7.4%
시 230
 
7.3%
기 230
 
7.3%
도 229
 
7.3%
로 217
 
6.9%
동 120
 
3.8%
층 103
 
3.3%
읍 101
 
3.2%
Other values (140) 1183
37.6%
Decimal Number
ValueCountFrequency (%)
1 302
32.3%
2 105
 
11.2%
3 99
 
10.6%
0 84
 
9.0%
8 69
 
7.4%
5 64
 
6.8%
4 59
 
6.3%
7 56
 
6.0%
6 52
 
5.6%
9 46
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
c 1
33.3%
u 1
33.3%
s 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
G 2
66.7%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
1082
100.0%
Other Punctuation
ValueCountFrequency (%)
, 126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3144
57.4%
Common 2328
42.5%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 252
 
8.0%
포 247
 
7.9%
경 232
 
7.4%
시 230
 
7.3%
기 230
 
7.3%
도 229
 
7.3%
로 217
 
6.9%
동 120
 
3.8%
층 103
 
3.3%
읍 101
 
3.2%
Other values (140) 1183
37.6%
Common
ValueCountFrequency (%)
1082
46.5%
1 302
 
13.0%
, 126
 
5.4%
2 105
 
4.5%
3 99
 
4.3%
0 84
 
3.6%
8 69
 
3.0%
( 67
 
2.9%
) 67
 
2.9%
5 64
 
2.7%
Other values (6) 263
 
11.3%
Latin
ValueCountFrequency (%)
G 2
33.3%
c 1
16.7%
u 1
16.7%
s 1
16.7%
S 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3144
57.4%
ASCII 2334
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1082
46.4%
1 302
 
12.9%
, 126
 
5.4%
2 105
 
4.5%
3 99
 
4.2%
0 84
 
3.6%
8 69
 
3.0%
( 67
 
2.9%
) 67
 
2.9%
5 64
 
2.7%
Other values (11) 269
 
11.5%
Hangul
ValueCountFrequency (%)
천 252
 
8.0%
포 247
 
7.9%
경 232
 
7.4%
시 230
 
7.3%
기 230
 
7.3%
도 229
 
7.3%
로 217
 
6.9%
동 120
 
3.8%
층 103
 
3.3%
읍 101
 
3.2%
Other values (140) 1183
37.6%

영업장행정동
Categorical

Distinct14
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
소흘읍
67 
포천동
37 
선단동
25 
가산면
17 
영북면
15 
Other values (9)
68 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique3 ?
Unique (%)1.3%

Sample

1st row포천동
2nd row영북면
3rd row영중면
4th row포천동
5th row소흘읍

Common Values

ValueCountFrequency (%)
소흘읍 67
29.3%
포천동 37
16.2%
선단동 25
 
10.9%
가산면 17
 
7.4%
영북면 15
 
6.6%
일동면 15
 
6.6%
내촌면 12
 
5.2%
군내면 11
 
4.8%
신북면 10
 
4.4%
영중면 9
 
3.9%
Other values (4) 11
 
4.8%

Length

2024-04-17T06:28:16.565844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소흘읍 67
29.3%
포천동 37
16.2%
선단동 25
 
10.9%
가산면 17
 
7.4%
영북면 15
 
6.6%
일동면 15
 
6.6%
내촌면 12
 
5.2%
군내면 11
 
4.8%
신북면 10
 
4.4%
영중면 9
 
3.9%
Other values (4) 11
 
4.8%

Correlations

2024-04-17T06:28:16.632051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분영업장행정동
구분1.0000.248
영업장행정동0.2481.000
2024-04-17T06:28:16.695052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분영업장행정동
구분1.0000.188
영업장행정동0.1881.000
2024-04-17T06:28:16.757173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분영업장행정동
구분1.0000.188
영업장행정동0.1881.000

Missing values

2024-04-17T06:28:15.126293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T06:28:15.218037image/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

구분영업장명칭영업장재지(도로명)영업장행정동
0약국녹십자약국경기도 포천시 중앙로 145(신읍동)포천동
1약국안녕약국경기도 포천시 영북면 영북로 180영북면
2약국미소약국경기도 포천시 영중면 양문로 79영중면
3약국솔약국경기도 포천시 왕방로 130, 1층 (신읍동)포천동
4약국우리약국경기도 포천시 소흘읍 호국로 433, 1층소흘읍
5약국보령약국경기도 포천시 군내면 청군로 3285군내면
6약국해든엄마약국경기도 포천시 영북면 영북로 187-5, 1층영북면
7약국365우리약국경기도 포천시 일동면 화동로 1056, 1층층일동면
8약국선교녹십자약국경기도 포천시 일동면 화동로 1068-1, 1층일동면
9약국태영약국경기도 포천시 이동면 장암1길 11이동면
구분영업장명칭영업장재지(도로명)영업장행정동
219편의점CU 포천화산점경기도 포천시 가산면 가산로 200가산면
220편의점씨유 가산본점경기도 포천시 가산면 가산로 125가산면
221편의점씨유 송우우정점경기도 포천시 소흘읍 솔모루로3번길 52-36소흘읍
222편의점(주)비지에프리테일 포천이마트점경기도 포천시 호국로 929-3 (선단동)선단동
223편의점비지에프리테일 포천고모리점경기도 포천시 소흘읍 정금로 20소흘읍
224편의점씨유 대진대 남자기숙사점경기도 포천시 호국로 1007 (선단동)선단동
225편의점씨유 대진대 학생회관점경기도 포천시 호국로 1007 (선단동)선단동
226편의점씨유 대진대 중앙도서관점경기도 포천시 호국로 1007 (선단동)선단동
227편의점씨유 송우중앙점경기도 포천시 소흘읍 호국로 243-14소흘읍
228편의점GS송우솔모루점경기도 포천시 소흘읍 솔모루로 55소흘읍

Duplicate rows

Most frequently occurring

구분영업장명칭영업장재지(도로명)영업장행정동# duplicates
0편의점세븐일레븐 운천점경기도 포천시 영북면 운천로9번길 6영북면2