Overview

Dataset statistics

Number of variables4
Number of observations153
Missing cells95
Missing cells (%)15.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory32.8 B

Variable types

Categorical1
Text3

Dataset

Description인천광역시 당구장 현황입니다.<br/>(업종,상호,시설주소(도로명),시설전화번호)<br/>ex) 당구장업,1박2일당구클럽,인천광역시 부평구 부평문화로 164 (부개동, 청오빌딩),032-201-8392<br/>
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15083689&srcSe=7661IVAWM27C61E190

Alerts

업종 has constant value ""Constant
시설전화번호 has 95 (62.1%) missing valuesMissing
시설주소(도로명) has unique valuesUnique

Reproduction

Analysis started2024-04-21 17:48:51.617655
Analysis finished2024-04-21 17:48:52.129138
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
당구장업
153 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
당구장업 153
100.0%

Length

2024-04-22T02:48:52.240811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T02:48:52.420796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당구장업 153
100.0%

상호
Text

Distinct131
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-22T02:48:53.284966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6
Min length2

Characters and Unicode

Total characters918
Distinct characters177
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

Unique120 ?
Unique (%)78.4%

Sample

1st row성실당구장
2nd row라노스당구장
3rd row맥스당구장
4th row현당구장
5th row프로당구장
ValueCountFrequency (%)
당구장 14
 
7.5%
프로당구장 8
 
4.3%
당구클럽 8
 
4.3%
sbs당구장 6
 
3.2%
sbs 3
 
1.6%
클럽 3
 
1.6%
에이스당구장 3
 
1.6%
프로당구클럽 2
 
1.1%
가브리엘 2
 
1.1%
용당구장 2
 
1.1%
Other values (132) 136
72.7%
2024-04-22T02:48:54.403300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 148
16.1%
당 145
15.8%
장 99
 
10.8%
럽 48
 
5.2%
클 47
 
5.1%
34
 
3.7%
S 26
 
2.8%
스 22
 
2.4%
B 12
 
1.3%
이 12
 
1.3%
Other values (167) 325
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 797
86.8%
Uppercase Letter 69
 
7.5%
Space Separator 34
 
3.7%
Decimal Number 8
 
0.9%
Lowercase Letter 7
 
0.8%
Other Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 148
18.6%
당 145
18.2%
장 99
12.4%
럽 48
 
6.0%
클 47
 
5.9%
스 22
 
2.8%
이 12
 
1.5%
프 11
 
1.4%
리 11
 
1.4%
로 11
 
1.4%
Other values (129) 243
30.5%
Uppercase Letter
ValueCountFrequency (%)
S 26
37.7%
B 12
17.4%
K 4
 
5.8%
P 3
 
4.3%
L 2
 
2.9%
M 2
 
2.9%
E 2
 
2.9%
C 2
 
2.9%
I 2
 
2.9%
A 2
 
2.9%
Other values (11) 12
17.4%
Decimal Number
ValueCountFrequency (%)
2 2
25.0%
4 1
12.5%
3 1
12.5%
8 1
12.5%
7 1
12.5%
9 1
12.5%
1 1
12.5%
Lowercase Letter
ValueCountFrequency (%)
c 2
28.6%
r 1
14.3%
i 1
14.3%
b 1
14.3%
u 1
14.3%
l 1
14.3%
Space Separator
ValueCountFrequency (%)
34
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 797
86.8%
Latin 76
 
8.3%
Common 45
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 148
18.6%
당 145
18.2%
장 99
12.4%
럽 48
 
6.0%
클 47
 
5.9%
스 22
 
2.8%
이 12
 
1.5%
프 11
 
1.4%
리 11
 
1.4%
로 11
 
1.4%
Other values (129) 243
30.5%
Latin
ValueCountFrequency (%)
S 26
34.2%
B 12
15.8%
K 4
 
5.3%
P 3
 
3.9%
L 2
 
2.6%
M 2
 
2.6%
E 2
 
2.6%
C 2
 
2.6%
c 2
 
2.6%
I 2
 
2.6%
Other values (17) 19
25.0%
Common
ValueCountFrequency (%)
34
75.6%
2 2
 
4.4%
. 1
 
2.2%
4 1
 
2.2%
3 1
 
2.2%
8 1
 
2.2%
) 1
 
2.2%
( 1
 
2.2%
7 1
 
2.2%
9 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 797
86.8%
ASCII 121
 
13.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 148
18.6%
당 145
18.2%
장 99
12.4%
럽 48
 
6.0%
클 47
 
5.9%
스 22
 
2.8%
이 12
 
1.5%
프 11
 
1.4%
리 11
 
1.4%
로 11
 
1.4%
Other values (129) 243
30.5%
ASCII
ValueCountFrequency (%)
34
28.1%
S 26
21.5%
B 12
 
9.9%
K 4
 
3.3%
P 3
 
2.5%
L 2
 
1.7%
M 2
 
1.7%
E 2
 
1.7%
C 2
 
1.7%
c 2
 
1.7%
Other values (28) 32
26.4%

시설주소(도로명)
Text

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-22T02:48:55.451308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length43
Mean length29.679739
Min length21

Characters and Unicode

Total characters4541
Distinct characters147
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 부평문화로 50 (부평동)
2nd row인천광역시 부평구 원길로6번길 1 (청천동)
3rd row인천광역시 부평구 후정동로 28 (삼산동, 영진 빌딩)
4th row인천광역시 부평구 경인로1118번길 17 (일신동)
5th row인천광역시 부평구 마장로 477 (청천동, 동선빌딩)
ValueCountFrequency (%)
인천광역시 153
 
16.6%
부평구 153
 
16.6%
부평동 43
 
4.7%
십정동 26
 
2.8%
청천동 23
 
2.5%
3층 21
 
2.3%
2층 18
 
2.0%
산곡동 17
 
1.8%
삼산동 16
 
1.7%
부개동 14
 
1.5%
Other values (280) 437
47.4%
2024-04-22T02:48:56.758124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
768
 
16.9%
부 246
 
5.4%
평 222
 
4.9%
천 196
 
4.3%
동 173
 
3.8%
인 160
 
3.5%
광 159
 
3.5%
시 159
 
3.5%
로 154
 
3.4%
( 153
 
3.4%
Other values (137) 2151
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2726
60.0%
Space Separator 768
 
16.9%
Decimal Number 597
 
13.1%
Open Punctuation 153
 
3.4%
Close Punctuation 153
 
3.4%
Other Punctuation 130
 
2.9%
Dash Punctuation 7
 
0.2%
Uppercase Letter 6
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 246
 
9.0%
평 222
 
8.1%
천 196
 
7.2%
동 173
 
6.3%
인 160
 
5.9%
광 159
 
5.8%
시 159
 
5.8%
로 154
 
5.6%
구 153
 
5.6%
역 153
 
5.6%
Other values (117) 951
34.9%
Decimal Number
ValueCountFrequency (%)
1 114
19.1%
2 96
16.1%
3 93
15.6%
4 79
13.2%
7 39
 
6.5%
0 38
 
6.4%
6 38
 
6.4%
5 37
 
6.2%
8 36
 
6.0%
9 27
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
C 2
33.3%
A 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 129
99.2%
＆ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
768
100.0%
Open Punctuation
ValueCountFrequency (%)
( 153
100.0%
Close Punctuation
ValueCountFrequency (%)
) 153
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2726
60.0%
Common 1808
39.8%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 246
 
9.0%
평 222
 
8.1%
천 196
 
7.2%
동 173
 
6.3%
인 160
 
5.9%
광 159
 
5.8%
시 159
 
5.8%
로 154
 
5.6%
구 153
 
5.6%
역 153
 
5.6%
Other values (117) 951
34.9%
Common
ValueCountFrequency (%)
768
42.5%
( 153
 
8.5%
) 153
 
8.5%
, 129
 
7.1%
1 114
 
6.3%
2 96
 
5.3%
3 93
 
5.1%
4 79
 
4.4%
7 39
 
2.2%
0 38
 
2.1%
Other values (6) 146
 
8.1%
Latin
ValueCountFrequency (%)
B 3
42.9%
C 2
28.6%
A 1
 
14.3%
Ⅱ 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2726
60.0%
ASCII 1813
39.9%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
768
42.4%
( 153
 
8.4%
) 153
 
8.4%
, 129
 
7.1%
1 114
 
6.3%
2 96
 
5.3%
3 93
 
5.1%
4 79
 
4.4%
7 39
 
2.2%
0 38
 
2.1%
Other values (8) 151
 
8.3%
Hangul
ValueCountFrequency (%)
부 246
 
9.0%
평 222
 
8.1%
천 196
 
7.2%
동 173
 
6.3%
인 160
 
5.9%
광 159
 
5.8%
시 159
 
5.8%
로 154
 
5.6%
구 153
 
5.6%
역 153
 
5.6%
Other values (117) 951
34.9%
None
ValueCountFrequency (%)
＆ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

시설전화번호
Text

MISSING 

Distinct58
Distinct (%)100.0%
Missing95
Missing (%)62.1%
Memory size1.3 KiB
2024-04-22T02:48:57.588686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.034483
Min length12

Characters and Unicode

Total characters698
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

Unique58 ?
Unique (%)100.0%

Sample

1st row032-529-6573
2nd row032-526-8289
3rd row032-522-6359
4th row032-529-3422
5th row032-524-4228
ValueCountFrequency (%)
032-519-8599 1
 
1.7%
070-8905-3335 1
 
1.7%
070-4141-9537 1
 
1.7%
032-501-3693 1
 
1.7%
032-518-2226 1
 
1.7%
032-516-7989 1
 
1.7%
032-271-3949 1
 
1.7%
032-501-4322 1
 
1.7%
032-423-2409 1
 
1.7%
032-361-5478 1
 
1.7%
Other values (48) 48
82.8%
2024-04-22T02:48:58.651116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 116
16.6%
2 112
16.0%
3 97
13.9%
0 93
13.3%
5 71
10.2%
9 45
 
6.4%
8 41
 
5.9%
4 35
 
5.0%
1 32
 
4.6%
7 32
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 582
83.4%
Dash Punctuation 116
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 112
19.2%
3 97
16.7%
0 93
16.0%
5 71
12.2%
9 45
7.7%
8 41
 
7.0%
4 35
 
6.0%
1 32
 
5.5%
7 32
 
5.5%
6 24
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 698
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 116
16.6%
2 112
16.0%
3 97
13.9%
0 93
13.3%
5 71
10.2%
9 45
 
6.4%
8 41
 
5.9%
4 35
 
5.0%
1 32
 
4.6%
7 32
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 698
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 116
16.6%
2 112
16.0%
3 97
13.9%
0 93
13.3%
5 71
10.2%
9 45
 
6.4%
8 41
 
5.9%
4 35
 
5.0%
1 32
 
4.6%
7 32
 
4.6%

Missing values

2024-04-22T02:48:52.069934image/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

업종상호시설주소(도로명)시설전화번호
0당구장업성실당구장인천광역시 부평구 부평문화로 50 (부평동)032-529-6573
1당구장업라노스당구장인천광역시 부평구 원길로6번길 1 (청천동)032-526-8289
2당구장업맥스당구장인천광역시 부평구 후정동로 28 (삼산동, 영진 빌딩)032-522-6359
3당구장업현당구장인천광역시 부평구 경인로1118번길 17 (일신동)032-529-3422
4당구장업프로당구장인천광역시 부평구 마장로 477 (청천동, 동선빌딩)032-524-4228
5당구장업SBS 큐 클럽인천광역시 부평구 경인로 739 (십정동)032-507-9777
6당구장업포인트당구장인천광역시 부평구 부흥로 394 (부개동)032-502-5422
7당구장업쇼부당구장인천광역시 부평구 길주남로 37 (부평동)032-516-9665
8당구장업진명당구장인천광역시 부평구 평천로 286 (갈산동)032-512-0079
9당구장업당구나라인천광역시 부평구 열우물로50번길 12 (십정동, 석암빌딩)032-442-7080
업종상호시설주소(도로명)시설전화번호
143당구장업양촌리당구장인천광역시 부평구 백범로 466, 지하1층 (십정동)032-442-8592
144당구장업보스당구장인천광역시 부평구 경인로1083번길 40, 2층 (부개동)<NA>
145당구장업남부당구장인천광역시 부평구 동수북로 170, B1호 (부평동)<NA>
146당구장업오스카당구클럽인천광역시 부평구 동수천로7번길 19, 2층 (부평동, 영광그린빌)<NA>
147당구장업송학당구장인천광역시 부평구 평천로 333, 태광빌딩 2층 (갈산동)<NA>
148당구장업놀이터 당구장인천광역시 부평구 경인로1104번길 6, 3층 (부개동)032-527-3155
149당구장업A8 당구장인천광역시 부평구 부흥로328번길 4, 2층 (부평동)<NA>
150당구장업스카이 당구 대대클럽인천광역시 부평구 주부토로 231, 갈산홈프라자 201호 (갈산동)<NA>
151당구장업MA당구클럽인천광역시 부평구 청중로 73, 대우빌딩 4층 (청천동)<NA>
152당구장업SBS당구장인천광역시 부평구 세월천로 35, 명성월드프라자 2층 (청천동)<NA>