Overview

Dataset statistics

Number of variables3
Number of observations139
Missing cells122
Missing cells (%)29.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory24.9 B

Variable types

Text3

Dataset

Description전라남도 순천시 소재 PC방 현황(상호, 소재지, 전화번호)
Author전라남도 순천시
URLhttps://www.data.go.kr/data/15014729/fileData.do

Alerts

전화번호 has 122 (87.8%) missing valuesMissing
영업소소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:44:06.537456
Analysis finished2023-12-12 07:44:06.944499
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

Distinct134
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T16:44:07.182017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length6.7625899
Min length3

Characters and Unicode

Total characters940
Distinct characters215
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)92.8%

Sample

1st row칼프PC방
2nd row로그인PC방
3rd row방가방가PC방
4th row엠플러스 PC방
5th row엔젤PC방
ValueCountFrequency (%)
pc방 15
 
7.9%
pc 10
 
5.3%
갤러리pc 3
 
1.6%
zone 3
 
1.6%
lol 3
 
1.6%
강남pc 2
 
1.1%
ㅋ 2
 
1.1%
샹떼pc방 2
 
1.1%
순천조례점 2
 
1.1%
cafe 2
 
1.1%
Other values (143) 146
76.8%
2023-12-12T16:44:07.622514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 135
 
14.4%
C 134
 
14.3%
방 72
 
7.7%
51
 
5.4%
이 19
 
2.0%
스 16
 
1.7%
점 16
 
1.7%
O 14
 
1.5%
피 13
 
1.4%
아 13
 
1.4%
Other values (205) 457
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 486
51.7%
Uppercase Letter 336
35.7%
Space Separator 51
 
5.4%
Lowercase Letter 44
 
4.7%
Close Punctuation 10
 
1.1%
Open Punctuation 10
 
1.1%
Decimal Number 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 72
 
14.8%
이 19
 
3.9%
스 16
 
3.3%
점 16
 
3.3%
피 13
 
2.7%
아 13
 
2.7%
시 11
 
2.3%
리 10
 
2.1%
천 9
 
1.9%
카 7
 
1.4%
Other values (164) 300
61.7%
Uppercase Letter
ValueCountFrequency (%)
P 135
40.2%
C 134
39.9%
O 14
 
4.2%
N 8
 
2.4%
L 8
 
2.4%
E 6
 
1.8%
A 5
 
1.5%
F 4
 
1.2%
Z 4
 
1.2%
R 4
 
1.2%
Other values (10) 14
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
e 7
15.9%
o 6
13.6%
a 6
13.6%
f 5
11.4%
c 4
9.1%
n 3
6.8%
m 2
 
4.5%
p 2
 
4.5%
y 2
 
4.5%
u 2
 
4.5%
Other values (5) 5
11.4%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 486
51.7%
Latin 380
40.4%
Common 74
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 72
 
14.8%
이 19
 
3.9%
스 16
 
3.3%
점 16
 
3.3%
피 13
 
2.7%
아 13
 
2.7%
시 11
 
2.3%
리 10
 
2.1%
천 9
 
1.9%
카 7
 
1.4%
Other values (164) 300
61.7%
Latin
ValueCountFrequency (%)
P 135
35.5%
C 134
35.3%
O 14
 
3.7%
N 8
 
2.1%
L 8
 
2.1%
e 7
 
1.8%
o 6
 
1.6%
a 6
 
1.6%
E 6
 
1.6%
f 5
 
1.3%
Other values (25) 51
 
13.4%
Common
ValueCountFrequency (%)
51
68.9%
) 10
 
13.5%
( 10
 
13.5%
3 1
 
1.4%
& 1
 
1.4%
1 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 484
51.5%
ASCII 454
48.3%
Compat Jamo 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 135
29.7%
C 134
29.5%
51
 
11.2%
O 14
 
3.1%
) 10
 
2.2%
( 10
 
2.2%
N 8
 
1.8%
L 8
 
1.8%
e 7
 
1.5%
o 6
 
1.3%
Other values (31) 71
15.6%
Hangul
ValueCountFrequency (%)
방 72
 
14.9%
이 19
 
3.9%
스 16
 
3.3%
점 16
 
3.3%
피 13
 
2.7%
아 13
 
2.7%
시 11
 
2.3%
리 10
 
2.1%
천 9
 
1.9%
카 7
 
1.4%
Other values (163) 298
61.6%
Compat Jamo
ValueCountFrequency (%)
ㅋ 2
100.0%

영업소소재지(도로명)
Text

UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T16:44:08.044548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length28.546763
Min length21

Characters and Unicode

Total characters3968
Distinct characters164
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

Unique139 ?
Unique (%)100.0%

Sample

1st row전라남도 순천시 연향3로 25 (연향동 (3층))
2nd row전라남도 순천시 조례신대길 45 (조례동)
3rd row전라남도 순천시 풍덕주택길 18 (풍덕동 (2층))
4th row전라남도 순천시 도서관길 14 1층 (동외동)
5th row전라남도 순천시 왕궁길 47 지하층 (조례동)
ValueCountFrequency (%)
전라남도 139
 
15.9%
순천시 139
 
15.9%
1층 56
 
6.4%
2층 40
 
4.6%
조례동 35
 
4.0%
연향동 32
 
3.7%
3층 17
 
1.9%
장천동 12
 
1.4%
해룡면 10
 
1.1%
이수로 10
 
1.1%
Other values (220) 384
43.9%
2023-12-12T16:44:08.631141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
872
22.0%
( 170
 
4.3%
) 170
 
4.3%
천 160
 
4.0%
1 159
 
4.0%
남 154
 
3.9%
도 146
 
3.7%
순 142
 
3.6%
전 140
 
3.5%
시 140
 
3.5%
Other values (154) 1715
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2200
55.4%
Space Separator 872
 
22.0%
Decimal Number 531
 
13.4%
Open Punctuation 170
 
4.3%
Close Punctuation 170
 
4.3%
Dash Punctuation 20
 
0.5%
Uppercase Letter 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 160
 
7.3%
남 154
 
7.0%
도 146
 
6.6%
순 142
 
6.5%
전 140
 
6.4%
시 140
 
6.4%
라 139
 
6.3%
동 137
 
6.2%
층 129
 
5.9%
길 89
 
4.0%
Other values (135) 824
37.5%
Decimal Number
ValueCountFrequency (%)
1 159
29.9%
2 131
24.7%
3 60
 
11.3%
4 39
 
7.3%
5 31
 
5.8%
0 28
 
5.3%
6 26
 
4.9%
7 24
 
4.5%
8 20
 
3.8%
9 13
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
S 1
25.0%
O 1
25.0%
N 1
25.0%
Y 1
25.0%
Space Separator
ValueCountFrequency (%)
872
100.0%
Open Punctuation
ValueCountFrequency (%)
( 170
100.0%
Close Punctuation
ValueCountFrequency (%)
) 170
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2200
55.4%
Common 1764
44.5%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 160
 
7.3%
남 154
 
7.0%
도 146
 
6.6%
순 142
 
6.5%
전 140
 
6.4%
시 140
 
6.4%
라 139
 
6.3%
동 137
 
6.2%
층 129
 
5.9%
길 89
 
4.0%
Other values (135) 824
37.5%
Common
ValueCountFrequency (%)
872
49.4%
( 170
 
9.6%
) 170
 
9.6%
1 159
 
9.0%
2 131
 
7.4%
3 60
 
3.4%
4 39
 
2.2%
5 31
 
1.8%
0 28
 
1.6%
6 26
 
1.5%
Other values (5) 78
 
4.4%
Latin
ValueCountFrequency (%)
S 1
25.0%
O 1
25.0%
N 1
25.0%
Y 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2200
55.4%
ASCII 1768
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
872
49.3%
( 170
 
9.6%
) 170
 
9.6%
1 159
 
9.0%
2 131
 
7.4%
3 60
 
3.4%
4 39
 
2.2%
5 31
 
1.8%
0 28
 
1.6%
6 26
 
1.5%
Other values (9) 82
 
4.6%
Hangul
ValueCountFrequency (%)
천 160
 
7.3%
남 154
 
7.0%
도 146
 
6.6%
순 142
 
6.5%
전 140
 
6.4%
시 140
 
6.4%
라 139
 
6.3%
동 137
 
6.2%
층 129
 
5.9%
길 89
 
4.0%
Other values (135) 824
37.5%

전화번호
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing122
Missing (%)87.8%
Memory size1.2 KiB
2023-12-12T16:44:08.859734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters204
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

Unique17 ?
Unique (%)100.0%

Sample

1st row061-725-5196
2nd row061-744-4941
3rd row061-752-3200
4th row061-752-8758
5th row061-726-5056
ValueCountFrequency (%)
061-725-5196 1
 
5.9%
061-743-5002 1
 
5.9%
061-727-2240 1
 
5.9%
061-725-5802 1
 
5.9%
061-727-6869 1
 
5.9%
061-753-1425 1
 
5.9%
061-725-1788 1
 
5.9%
061-722-4855 1
 
5.9%
061-722-5770 1
 
5.9%
061-744-4941 1
 
5.9%
Other values (7) 7
41.2%
2023-12-12T16:44:09.290159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 34
16.7%
0 29
14.2%
7 26
12.7%
6 24
11.8%
1 22
10.8%
2 21
10.3%
5 19
9.3%
4 13
 
6.4%
8 8
 
3.9%
9 5
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 170
83.3%
Dash Punctuation 34
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 29
17.1%
7 26
15.3%
6 24
14.1%
1 22
12.9%
2 21
12.4%
5 19
11.2%
4 13
7.6%
8 8
 
4.7%
9 5
 
2.9%
3 3
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 204
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 34
16.7%
0 29
14.2%
7 26
12.7%
6 24
11.8%
1 22
10.8%
2 21
10.3%
5 19
9.3%
4 13
 
6.4%
8 8
 
3.9%
9 5
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 204
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 34
16.7%
0 29
14.2%
7 26
12.7%
6 24
11.8%
1 22
10.8%
2 21
10.3%
5 19
9.3%
4 13
 
6.4%
8 8
 
3.9%
9 5
 
2.5%

Missing values

2023-12-12T16:44:06.784392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:44:06.891905image/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

상호영업소소재지(도로명)전화번호
0칼프PC방전라남도 순천시 연향3로 25 (연향동 (3층))061-725-5196
1로그인PC방전라남도 순천시 조례신대길 45 (조례동)<NA>
2방가방가PC방전라남도 순천시 풍덕주택길 18 (풍덕동 (2층))061-744-4941
3엠플러스 PC방전라남도 순천시 도서관길 14 1층 (동외동)061-752-3200
4엔젤PC방전라남도 순천시 왕궁길 47 지하층 (조례동)<NA>
5FOX PC방전라남도 순천시 중앙7길 1 2층 (중앙동)<NA>
6맬론PC방(순대점)전라남도 순천시 순천대2길 2 3층 (석현동)<NA>
7프리존PC방전라남도 순천시 옥천길 39 (영동 (2층))<NA>
8스카이블루PC방전라남도 순천시 삼산로 73 2층 (용당동)061-752-8758
9그린존PC방전라남도 순천시 장선배기길 15 1층 (조례동)061-726-5056
상호영업소소재지(도로명)전화번호
129피시프레소 PC방전라남도 순천시 팔마2길 56 3층 (연향동)<NA>
130아이피시토랑전라남도 순천시 왕궁길 25 3층 (조례동 보배약국)<NA>
131땡피씨전라남도 순천시 팔마로 176 1층 (덕암동)<NA>
132안젤리나PC전라남도 순천시 장선배기2길 5-10 1층 (조례동)<NA>
133동성PC전라남도 순천시 장자보2길 104 1층 (연향동)<NA>
134꿀PC전라남도 순천시 중앙2길 27 1층 (장천동)<NA>
135Awesome Pc Cafe(아썸PC cafe)전라남도 순천시 덕월길 2 3층 (덕월동 정풍빌딩)<NA>
136골프PC전라남도 순천시 이수로 38 1층 (장천동)<NA>
137남부PC전라남도 순천시 남산로 154-1 1층 (풍덕동)<NA>
138스타덤PC순천본점전라남도 순천시 연향3로 41 2층 (연향동)<NA>