Overview

Dataset statistics

Number of variables4
Number of observations386
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.2 KiB
Average record size in memory32.3 B

Variable types

Text3
Categorical1

Dataset

Description충청남도 논산시 미용업에 대한 공공데이터입니다. 해당데이터는 업소명, 행정동, 주소, 전화번호 정보를 제공하고 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=389&beforeMenuCd=DOM_000000201001001000&publicdatapk=15054218

Alerts

행정동 is highly imbalanced (53.4%)Imbalance

Reproduction

Analysis started2024-01-09 19:55:21.391580
Analysis finished2024-01-09 19:55:21.871251
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct381
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-01-10T04:55:22.091250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length5.3523316
Min length2

Characters and Unicode

Total characters2066
Distinct characters375
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique376 ?
Unique (%)97.4%

Sample

1st row에덴미용원
2nd row스타미용실
3rd row꽃가마
4th row숙녀
5th row성모
ValueCountFrequency (%)
신신미용실 2
 
0.5%
헤어아트 2
 
0.5%
우리미용실 2
 
0.5%
현대미용실 2
 
0.5%
스타미용실 2
 
0.5%
손톱달눈썹달 2
 
0.5%
미용실 2
 
0.5%
더 2
 
0.5%
헤어샵 2
 
0.5%
피부관리실 2
 
0.5%
Other values (398) 399
95.2%
2024-01-10T04:55:23.059800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 151
 
7.3%
헤 148
 
7.2%
미 102
 
4.9%
실 77
 
3.7%
용 73
 
3.5%
스 54
 
2.6%
리 43
 
2.1%
이 38
 
1.8%
샵 35
 
1.7%
33
 
1.6%
Other values (365) 1312
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1875
90.8%
Lowercase Letter 74
 
3.6%
Uppercase Letter 34
 
1.6%
Space Separator 33
 
1.6%
Open Punctuation 14
 
0.7%
Close Punctuation 14
 
0.7%
Decimal Number 11
 
0.5%
Other Punctuation 11
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 151
 
8.1%
헤 148
 
7.9%
미 102
 
5.4%
실 77
 
4.1%
용 73
 
3.9%
스 54
 
2.9%
리 43
 
2.3%
이 38
 
2.0%
샵 35
 
1.9%
일 31
 
1.7%
Other values (317) 1123
59.9%
Lowercase Letter
ValueCountFrequency (%)
n 9
12.2%
e 9
12.2%
o 8
10.8%
i 7
9.5%
s 7
9.5%
a 5
 
6.8%
h 5
 
6.8%
g 3
 
4.1%
k 3
 
4.1%
m 3
 
4.1%
Other values (9) 15
20.3%
Uppercase Letter
ValueCountFrequency (%)
S 6
17.6%
O 4
11.8%
J 4
11.8%
N 3
8.8%
M 3
8.8%
B 3
8.8%
Y 2
 
5.9%
L 2
 
5.9%
T 2
 
5.9%
P 1
 
2.9%
Other values (4) 4
11.8%
Decimal Number
ValueCountFrequency (%)
0 4
36.4%
3 2
18.2%
9 1
 
9.1%
4 1
 
9.1%
8 1
 
9.1%
5 1
 
9.1%
1 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
# 3
27.3%
& 3
27.3%
' 2
18.2%
, 2
18.2%
. 1
 
9.1%
Space Separator
ValueCountFrequency (%)
33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1873
90.7%
Latin 108
 
5.2%
Common 83
 
4.0%
Han 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 151
 
8.1%
헤 148
 
7.9%
미 102
 
5.4%
실 77
 
4.1%
용 73
 
3.9%
스 54
 
2.9%
리 43
 
2.3%
이 38
 
2.0%
샵 35
 
1.9%
일 31
 
1.7%
Other values (315) 1121
59.9%
Latin
ValueCountFrequency (%)
n 9
 
8.3%
e 9
 
8.3%
o 8
 
7.4%
i 7
 
6.5%
s 7
 
6.5%
S 6
 
5.6%
a 5
 
4.6%
h 5
 
4.6%
O 4
 
3.7%
J 4
 
3.7%
Other values (23) 44
40.7%
Common
ValueCountFrequency (%)
33
39.8%
( 14
16.9%
) 14
16.9%
0 4
 
4.8%
# 3
 
3.6%
& 3
 
3.6%
3 2
 
2.4%
' 2
 
2.4%
, 2
 
2.4%
9 1
 
1.2%
Other values (5) 5
 
6.0%
Han
ValueCountFrequency (%)
韓 1
50.0%
美 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1873
90.7%
ASCII 191
 
9.2%
CJK 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 151
 
8.1%
헤 148
 
7.9%
미 102
 
5.4%
실 77
 
4.1%
용 73
 
3.9%
스 54
 
2.9%
리 43
 
2.3%
이 38
 
2.0%
샵 35
 
1.9%
일 31
 
1.7%
Other values (315) 1121
59.9%
ASCII
ValueCountFrequency (%)
33
17.3%
( 14
 
7.3%
) 14
 
7.3%
n 9
 
4.7%
e 9
 
4.7%
o 8
 
4.2%
i 7
 
3.7%
s 7
 
3.7%
S 6
 
3.1%
a 5
 
2.6%
Other values (38) 79
41.4%
CJK
ValueCountFrequency (%)
韓 1
50.0%
美 1
50.0%

행정동
Categorical

IMBALANCE 

Distinct13
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
취암동
259 
연무읍
43 
강경읍
39 
부창동
 
21
연산면
 
7
Other values (8)
 
17

Length

Max length4
Median length3
Mean length3.0051813
Min length3

Unique

Unique3 ?
Unique (%)0.8%

Sample

1st row연무읍
2nd row연산면
3rd row취암동
4th row취암동
5th row부창동

Common Values

ValueCountFrequency (%)
취암동 259
67.1%
연무읍 43
 
11.1%
강경읍 39
 
10.1%
부창동 21
 
5.4%
연산면 7
 
1.8%
양촌면 6
 
1.6%
성동면 2
 
0.5%
가야곡면 2
 
0.5%
광석면 2
 
0.5%
상월면 2
 
0.5%
Other values (3) 3
 
0.8%

Length

2024-01-10T04:55:23.205364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취암동 259
67.1%
연무읍 43
 
11.1%
강경읍 39
 
10.1%
부창동 21
 
5.4%
연산면 7
 
1.8%
양촌면 6
 
1.6%
성동면 2
 
0.5%
가야곡면 2
 
0.5%
광석면 2
 
0.5%
상월면 2
 
0.5%
Other values (3) 3
 
0.8%

주소
Text

Distinct377
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-01-10T04:55:23.462462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length27.023316
Min length18

Characters and Unicode

Total characters10431
Distinct characters152
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

Unique369 ?
Unique (%)95.6%

Sample

1st row충청남도 논산시 연무읍 연무로178번길 2-1
2nd row충청남도 논산시 연산면 황산벌로 1534
3rd row충청남도 논산시 해월로 229 (화지동)
4th row충청남도 논산시 대화로70번길 9-4 (화지동)
5th row충청남도 논산시 중앙로505번길 10 (대교동)
ValueCountFrequency (%)
충청남도 386
17.9%
논산시 386
17.9%
취암동 117
 
5.4%
내동 68
 
3.2%
1층 52
 
2.4%
화지동 45
 
2.1%
연무읍 43
 
2.0%
강경읍 39
 
1.8%
중앙로 38
 
1.8%
반월동 28
 
1.3%
Other values (435) 951
44.2%
2024-01-10T04:55:23.908598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1769
 
17.0%
1 467
 
4.5%
시 464
 
4.4%
산 435
 
4.2%
논 404
 
3.9%
청 391
 
3.7%
남 387
 
3.7%
충 386
 
3.7%
도 386
 
3.7%
로 380
 
3.6%
Other values (142) 4962
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5881
56.4%
Decimal Number 1910
 
18.3%
Space Separator 1769
 
17.0%
Open Punctuation 280
 
2.7%
Close Punctuation 280
 
2.7%
Other Punctuation 167
 
1.6%
Dash Punctuation 140
 
1.3%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 464
 
7.9%
산 435
 
7.4%
논 404
 
6.9%
청 391
 
6.6%
남 387
 
6.6%
충 386
 
6.6%
도 386
 
6.6%
로 380
 
6.5%
동 309
 
5.3%
번 210
 
3.6%
Other values (123) 2129
36.2%
Decimal Number
ValueCountFrequency (%)
1 467
24.5%
2 268
14.0%
3 210
11.0%
0 199
10.4%
4 181
 
9.5%
8 159
 
8.3%
9 139
 
7.3%
5 106
 
5.5%
7 92
 
4.8%
6 89
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
H 1
25.0%
L 1
25.0%
I 1
25.0%
G 1
25.0%
Space Separator
ValueCountFrequency (%)
1769
100.0%
Open Punctuation
ValueCountFrequency (%)
( 280
100.0%
Close Punctuation
ValueCountFrequency (%)
) 280
100.0%
Other Punctuation
ValueCountFrequency (%)
, 167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5881
56.4%
Common 4546
43.6%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 464
 
7.9%
산 435
 
7.4%
논 404
 
6.9%
청 391
 
6.6%
남 387
 
6.6%
충 386
 
6.6%
도 386
 
6.6%
로 380
 
6.5%
동 309
 
5.3%
번 210
 
3.6%
Other values (123) 2129
36.2%
Common
ValueCountFrequency (%)
1769
38.9%
1 467
 
10.3%
( 280
 
6.2%
) 280
 
6.2%
2 268
 
5.9%
3 210
 
4.6%
0 199
 
4.4%
4 181
 
4.0%
, 167
 
3.7%
8 159
 
3.5%
Other values (5) 566
 
12.5%
Latin
ValueCountFrequency (%)
H 1
25.0%
L 1
25.0%
I 1
25.0%
G 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5881
56.4%
ASCII 4550
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1769
38.9%
1 467
 
10.3%
( 280
 
6.2%
) 280
 
6.2%
2 268
 
5.9%
3 210
 
4.6%
0 199
 
4.4%
4 181
 
4.0%
, 167
 
3.7%
8 159
 
3.5%
Other values (9) 570
 
12.5%
Hangul
ValueCountFrequency (%)
시 464
 
7.9%
산 435
 
7.4%
논 404
 
6.9%
청 391
 
6.6%
남 387
 
6.6%
충 386
 
6.6%
도 386
 
6.6%
로 380
 
6.5%
동 309
 
5.3%
번 210
 
3.6%
Other values (123) 2129
36.2%

전화번호
Text

Distinct261
Distinct (%)67.6%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-01-10T04:55:24.218333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.010363
Min length12

Characters and Unicode

Total characters4636
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

Unique259 ?
Unique (%)67.1%

Sample

1st row041-741-7890
2nd row041-735-0006
3rd row000-000-0000
4th row041-735-3089
5th row041-733-0450
ValueCountFrequency (%)
000-000-0000 125
32.4%
041-734-6474 2
 
0.5%
041-7333-442 1
 
0.3%
041-980-8020 1
 
0.3%
041-733-3536 1
 
0.3%
041-745-5669 1
 
0.3%
041-732-6602 1
 
0.3%
041-735-5440 1
 
0.3%
041-742-0025 1
 
0.3%
041-745-7833 1
 
0.3%
Other values (251) 251
65.0%
2024-01-10T04:55:24.638574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1661
35.8%
- 772
16.7%
4 449
 
9.7%
1 374
 
8.1%
7 371
 
8.0%
3 314
 
6.8%
5 218
 
4.7%
2 154
 
3.3%
6 131
 
2.8%
8 101
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3864
83.3%
Dash Punctuation 772
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1661
43.0%
4 449
 
11.6%
1 374
 
9.7%
7 371
 
9.6%
3 314
 
8.1%
5 218
 
5.6%
2 154
 
4.0%
6 131
 
3.4%
8 101
 
2.6%
9 91
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 772
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4636
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1661
35.8%
- 772
16.7%
4 449
 
9.7%
1 374
 
8.1%
7 371
 
8.0%
3 314
 
6.8%
5 218
 
4.7%
2 154
 
3.3%
6 131
 
2.8%
8 101
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4636
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1661
35.8%
- 772
16.7%
4 449
 
9.7%
1 374
 
8.1%
7 371
 
8.0%
3 314
 
6.8%
5 218
 
4.7%
2 154
 
3.3%
6 131
 
2.8%
8 101
 
2.2%

Missing values

2024-01-10T04:55:21.724061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T04:55:21.830792image/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

업소명행정동주소전화번호
0에덴미용원연무읍충청남도 논산시 연무읍 연무로178번길 2-1041-741-7890
1스타미용실연산면충청남도 논산시 연산면 황산벌로 1534041-735-0006
2꽃가마취암동충청남도 논산시 해월로 229 (화지동)000-000-0000
3숙녀취암동충청남도 논산시 대화로70번길 9-4 (화지동)041-735-3089
4성모부창동충청남도 논산시 중앙로505번길 10 (대교동)041-733-0450
5중앙취암동충청남도 논산시 해월로 170 (반월동)041-735-8227
6귀희강경읍충청남도 논산시 강경읍 대흥로 13041-745-0482
7은지헤어라인강경읍충청남도 논산시 강경읍 대흥로 14041-745-7790
8수정미용실취암동충청남도 논산시 중앙로 498-10 (화지동)041-735-6826
9은희취암동충청남도 논산시 해월로 222 (반월동)041-735-2668
업소명행정동주소전화번호
376차르르헤어(차르르hair)취암동충청남도 논산시 중앙로480번길 34-1, 1층 (반월동)000-000-0000
377두희헤어양촌면충청남도 논산시 양촌면 매죽헌로 1684, 1층041-742-1278
378보니샵(BONNY)#취암동충청남도 논산시 중앙로384번길 68, 1층 102호 (취암동)041-732-2357
379롱고네일(Longgonail)취암동충청남도 논산시 부창로82번길 13-5, 1층 (취암동)000-000-0000
380The,꼼꼼skin취암동충청남도 논산시 중앙로384번길 15-9 (취암동)000-000-0000
381단비살롱취암동충청남도 논산시 시민로 320, 남양아파트 1층 (취암동)000-000-0000
382센스헤어취암동충청남도 논산시 중앙로 235, 놀뫼아파트 1층 105호 (내동)000-000-0000
383예쁘다skin&body취암동충청남도 논산시 중앙로 448, 104호 (반월동, 논산 휴드림)070-4045-6250
384904네일취암동충청남도 논산시 중앙로410번길 29-3, 1층 (취암동)000-000-0000
385머리해봄취암동충청남도 논산시 논산대로 269-24, 1층 (내동)000-000-0000