Overview

Dataset statistics

Number of variables5
Number of observations413
Missing cells168
Missing cells (%)8.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.3 KiB
Average record size in memory40.3 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description인천광역시 중구에 소재하는 미용업소에 관한 정보입니다.파일명 인천광역시 중구 미용업소 현황내용 업소명, 주소, 전화번호 등
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15006800&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일 has constant value ""Constant
영업소 주소(도로명) has 8 (1.9%) missing valuesMissing
소재지전화 has 160 (38.7%) missing valuesMissing

Reproduction

Analysis started2024-04-17 21:13:10.232083
Analysis finished2024-04-17 21:13:11.531159
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

Distinct14
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
일반미용업
165 
미용업
82 
피부미용업
51 
네일미용업
34 
종합미용업
18 
Other values (9)
63 

Length

Max length23
Median length5
Mean length6.1719128
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 165
40.0%
미용업 82
19.9%
피부미용업 51
 
12.3%
네일미용업 34
 
8.2%
종합미용업 18
 
4.4%
화장ㆍ분장 미용업 13
 
3.1%
네일미용업, 화장ㆍ분장 미용업 12
 
2.9%
피부미용업, 네일미용업, 화장ㆍ분장 미용업 10
 
2.4%
피부미용업, 네일미용업 7
 
1.7%
피부미용업, 화장ㆍ분장 미용업 6
 
1.5%
Other values (4) 15
 
3.6%

Length

2024-04-18T06:13:11.597688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 180
34.2%
미용업 132
25.0%
피부미용업 77
14.6%
네일미용업 70
 
13.3%
화장ㆍ분장 50
 
9.5%
종합미용업 18
 
3.4%

업소명
Text

Distinct410
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2024-04-18T06:13:11.791254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length24
Mean length6.5544794
Min length1

Characters and Unicode

Total characters2707
Distinct characters397
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique407 ?
Unique (%)98.5%

Sample

1st row주연미용실
2nd row주영미용실
3rd row은방울미용실
4th row수양미장원
5th row가인헤어
ValueCountFrequency (%)
헤어 22
 
3.9%
nail 9
 
1.6%
hair 8
 
1.4%
영종하늘도시점 7
 
1.2%
네일 5
 
0.9%
미용실 4
 
0.7%
3
 
0.5%
미 3
 
0.5%
더 3
 
0.5%
by 3
 
0.5%
Other values (488) 498
88.1%
2024-04-18T06:13:12.090461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
헤 159
 
5.9%
어 157
 
5.8%
152
 
5.6%
미 74
 
2.7%
스 61
 
2.3%
네 53
 
2.0%
일 52
 
1.9%
이 52
 
1.9%
) 46
 
1.7%
( 46
 
1.7%
Other values (387) 1855
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2023
74.7%
Lowercase Letter 205
 
7.6%
Uppercase Letter 191
 
7.1%
Space Separator 152
 
5.6%
Close Punctuation 46
 
1.7%
Open Punctuation 46
 
1.7%
Other Punctuation 33
 
1.2%
Decimal Number 7
 
0.3%
Dash Punctuation 2
 
0.1%
Other Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
헤 159
 
7.9%
어 157
 
7.8%
미 74
 
3.7%
스 61
 
3.0%
네 53
 
2.6%
일 52
 
2.6%
이 52
 
2.6%
용 46
 
2.3%
실 44
 
2.2%
리 35
 
1.7%
Other values (324) 1290
63.8%
Lowercase Letter
ValueCountFrequency (%)
a 29
14.1%
e 29
14.1%
i 29
14.1%
r 17
8.3%
h 13
 
6.3%
l 12
 
5.9%
o 10
 
4.9%
s 9
 
4.4%
t 9
 
4.4%
u 8
 
3.9%
Other values (13) 40
19.5%
Uppercase Letter
ValueCountFrequency (%)
A 25
13.1%
N 21
11.0%
O 16
 
8.4%
L 15
 
7.9%
H 13
 
6.8%
I 13
 
6.8%
T 11
 
5.8%
E 11
 
5.8%
R 8
 
4.2%
M 8
 
4.2%
Other values (12) 50
26.2%
Decimal Number
ValueCountFrequency (%)
3 1
14.3%
6 1
14.3%
0 1
14.3%
5 1
14.3%
9 1
14.3%
1 1
14.3%
7 1
14.3%
Other Punctuation
ValueCountFrequency (%)
& 9
27.3%
, 7
21.2%
. 6
18.2%
# 5
15.2%
' 4
12.1%
: 2
 
6.1%
Space Separator
ValueCountFrequency (%)
152
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
° 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2022
74.7%
Latin 396
 
14.6%
Common 288
 
10.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
헤 159
 
7.9%
어 157
 
7.8%
미 74
 
3.7%
스 61
 
3.0%
네 53
 
2.6%
일 52
 
2.6%
이 52
 
2.6%
용 46
 
2.3%
실 44
 
2.2%
리 35
 
1.7%
Other values (323) 1289
63.7%
Latin
ValueCountFrequency (%)
a 29
 
7.3%
e 29
 
7.3%
i 29
 
7.3%
A 25
 
6.3%
N 21
 
5.3%
r 17
 
4.3%
O 16
 
4.0%
L 15
 
3.8%
h 13
 
3.3%
H 13
 
3.3%
Other values (35) 189
47.7%
Common
ValueCountFrequency (%)
152
52.8%
) 46
 
16.0%
( 46
 
16.0%
& 9
 
3.1%
, 7
 
2.4%
. 6
 
2.1%
# 5
 
1.7%
' 4
 
1.4%
: 2
 
0.7%
- 2
 
0.7%
Other values (8) 9
 
3.1%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2022
74.7%
ASCII 682
 
25.2%
None 2
 
0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
헤 159
 
7.9%
어 157
 
7.8%
미 74
 
3.7%
스 61
 
3.0%
네 53
 
2.6%
일 52
 
2.6%
이 52
 
2.6%
용 46
 
2.3%
실 44
 
2.2%
리 35
 
1.7%
Other values (323) 1289
63.7%
ASCII
ValueCountFrequency (%)
152
22.3%
) 46
 
6.7%
( 46
 
6.7%
a 29
 
4.3%
e 29
 
4.3%
i 29
 
4.3%
A 25
 
3.7%
N 21
 
3.1%
r 17
 
2.5%
O 16
 
2.3%
Other values (52) 272
39.9%
None
ValueCountFrequency (%)
° 2
100.0%
CJK
ValueCountFrequency (%)
愛 1
100.0%

영업소 주소(도로명)
Text

MISSING 

Distinct401
Distinct (%)99.0%
Missing8
Missing (%)1.9%
Memory size3.4 KiB
2024-04-18T06:13:12.339400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length51
Mean length35.755556
Min length20

Characters and Unicode

Total characters14481
Distinct characters254
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique397 ?
Unique (%)98.0%

Sample

1st row인천광역시 중구 신포로35번길 28, 1층 (송학동2가)
2nd row인천광역시 중구 서해대로500번길 13-2, 1층 (유동)
3rd row인천광역시 중구 큰우물로 1-1, 1층 (경동)
4th row인천광역시 중구 연안부두로33번길 9-1 (항동7가)
5th row인천광역시 중구 참외전로45번길 1, 1층 (송월동1가, 정임빌라)
ValueCountFrequency (%)
인천광역시 405
 
14.1%
중구 405
 
14.1%
1층 132
 
4.6%
중산동 107
 
3.7%
운서동 106
 
3.7%
2층 77
 
2.7%
운남동 39
 
1.4%
흰바위로 36
 
1.3%
하늘달빛로 27
 
0.9%
인현동 21
 
0.7%
Other values (591) 1524
52.9%
2024-04-18T06:13:12.704949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2476
 
17.1%
1 694
 
4.8%
중 569
 
3.9%
동 465
 
3.2%
시 448
 
3.1%
, 447
 
3.1%
인 446
 
3.1%
2 435
 
3.0%
역 418
 
2.9%
천 410
 
2.8%
Other values (244) 7673
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8037
55.5%
Decimal Number 2530
 
17.5%
Space Separator 2476
 
17.1%
Other Punctuation 447
 
3.1%
Close Punctuation 410
 
2.8%
Open Punctuation 409
 
2.8%
Dash Punctuation 87
 
0.6%
Uppercase Letter 57
 
0.4%
Lowercase Letter 24
 
0.2%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 569
 
7.1%
동 465
 
5.8%
시 448
 
5.6%
인 446
 
5.5%
역 418
 
5.2%
천 410
 
5.1%
로 406
 
5.1%
광 405
 
5.0%
구 405
 
5.0%
호 265
 
3.3%
Other values (203) 3800
47.3%
Uppercase Letter
ValueCountFrequency (%)
I 12
21.1%
S 8
14.0%
B 6
10.5%
M 5
8.8%
K 5
8.8%
L 4
 
7.0%
H 4
 
7.0%
C 4
 
7.0%
W 2
 
3.5%
E 2
 
3.5%
Other values (3) 5
8.8%
Lowercase Letter
ValueCountFrequency (%)
e 5
20.8%
y 4
16.7%
t 3
12.5%
k 2
 
8.3%
l 2
 
8.3%
i 2
 
8.3%
c 2
 
8.3%
a 1
 
4.2%
o 1
 
4.2%
u 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 694
27.4%
2 435
17.2%
0 290
11.5%
3 261
 
10.3%
5 176
 
7.0%
4 167
 
6.6%
6 156
 
6.2%
7 125
 
4.9%
9 116
 
4.6%
8 110
 
4.3%
Space Separator
ValueCountFrequency (%)
2476
100.0%
Other Punctuation
ValueCountFrequency (%)
, 447
100.0%
Close Punctuation
ValueCountFrequency (%)
) 410
100.0%
Open Punctuation
ValueCountFrequency (%)
( 409
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8037
55.5%
Common 6362
43.9%
Latin 82
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 569
 
7.1%
동 465
 
5.8%
시 448
 
5.6%
인 446
 
5.5%
역 418
 
5.2%
천 410
 
5.1%
로 406
 
5.1%
광 405
 
5.0%
구 405
 
5.0%
호 265
 
3.3%
Other values (203) 3800
47.3%
Latin
ValueCountFrequency (%)
I 12
14.6%
S 8
 
9.8%
B 6
 
7.3%
M 5
 
6.1%
K 5
 
6.1%
e 5
 
6.1%
L 4
 
4.9%
H 4
 
4.9%
C 4
 
4.9%
y 4
 
4.9%
Other values (15) 25
30.5%
Common
ValueCountFrequency (%)
2476
38.9%
1 694
 
10.9%
, 447
 
7.0%
2 435
 
6.8%
) 410
 
6.4%
( 409
 
6.4%
0 290
 
4.6%
3 261
 
4.1%
5 176
 
2.8%
4 167
 
2.6%
Other values (6) 597
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8037
55.5%
ASCII 6443
44.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2476
38.4%
1 694
 
10.8%
, 447
 
6.9%
2 435
 
6.8%
) 410
 
6.4%
( 409
 
6.3%
0 290
 
4.5%
3 261
 
4.1%
5 176
 
2.7%
4 167
 
2.6%
Other values (30) 678
 
10.5%
Hangul
ValueCountFrequency (%)
중 569
 
7.1%
동 465
 
5.8%
시 448
 
5.6%
인 446
 
5.5%
역 418
 
5.2%
천 410
 
5.1%
로 406
 
5.1%
광 405
 
5.0%
구 405
 
5.0%
호 265
 
3.3%
Other values (203) 3800
47.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

소재지전화
Text

MISSING 

Distinct249
Distinct (%)98.4%
Missing160
Missing (%)38.7%
Memory size3.4 KiB
2024-04-18T06:13:12.904959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.280632
Min length12

Characters and Unicode

Total characters3107
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

Unique245 ?
Unique (%)96.8%

Sample

1st row032-764-5058
2nd row032-764-5058
3rd row032-882-8212
4th row032-765-3582
5th row032-772-8060
ValueCountFrequency (%)
032-747-0329 2
 
0.8%
032-885-5995 2
 
0.8%
032-764-5058 2
 
0.8%
032-752-7070 2
 
0.8%
032-764-1967 1
 
0.4%
032-752-7274 1
 
0.4%
032-746-2234 1
 
0.4%
032-710-9121 1
 
0.4%
032-752-5413 1
 
0.4%
032-752-8261 1
 
0.4%
Other values (239) 239
94.5%
2024-04-18T06:13:13.216311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 506
16.3%
0 439
14.1%
2 397
12.8%
7 375
12.1%
3 358
11.5%
5 214
6.9%
1 195
 
6.3%
6 186
 
6.0%
4 185
 
6.0%
8 160
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2601
83.7%
Dash Punctuation 506
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 439
16.9%
2 397
15.3%
7 375
14.4%
3 358
13.8%
5 214
8.2%
1 195
7.5%
6 186
7.2%
4 185
7.1%
8 160
 
6.2%
9 92
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 506
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3107
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 506
16.3%
0 439
14.1%
2 397
12.8%
7 375
12.1%
3 358
11.5%
5 214
6.9%
1 195
 
6.3%
6 186
 
6.0%
4 185
 
6.0%
8 160
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3107
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 506
16.3%
0 439
14.1%
2 397
12.8%
7 375
12.1%
3 358
11.5%
5 214
6.9%
1 195
 
6.3%
6 186
 
6.0%
4 185
 
6.0%
8 160
 
5.1%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum2023-07-18 00:00:00
Maximum2023-07-18 00:00:00
2024-04-18T06:13:13.307188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T06:13:13.379509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-04-18T06:13:11.027321image/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.
2024-04-18T06:13:11.487919image/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

업종명업소명영업소 주소(도로명)소재지전화데이터기준일
0미용업주연미용실<NA>032-764-50582023-07-18
1미용업주영미용실인천광역시 중구 신포로35번길 28, 1층 (송학동2가)032-764-50582023-07-18
2미용업은방울미용실인천광역시 중구 서해대로500번길 13-2, 1층 (유동)032-882-82122023-07-18
3미용업수양미장원<NA>032-765-35822023-07-18
4미용업가인헤어인천광역시 중구 큰우물로 1-1, 1층 (경동)032-772-80602023-07-18
5미용업하림미용실<NA>032-882-57252023-07-18
6미용업샘미용실<NA>032-882-65742023-07-18
7미용업보떼리아 미용실인천광역시 중구 연안부두로33번길 9-1 (항동7가)032-883-72852023-07-18
8미용업경동미용실<NA>032-772-87672023-07-18
9미용업하얀미용실인천광역시 중구 참외전로45번길 1, 1층 (송월동1가, 정임빌라)032-762-59282023-07-18
업종명업소명영업소 주소(도로명)소재지전화데이터기준일
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