Overview

Dataset statistics

Number of variables4
Number of observations1012
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.7 KiB
Average record size in memory33.1 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description경산시 공중위생업소 현황이며 일반, 피부, 네일, 화장분장 미용업의 업종명, 업소명, 영업소주소를 포함하고 있습니다.
Author경상북도 경산시
URLhttps://www.data.go.kr/data/15006921/fileData.do

Alerts

번호 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 번호High correlation
번호 has unique valuesUnique

Reproduction

Analysis started2024-03-23 04:26:57.043981
Analysis finished2024-03-23 04:26:59.441040
Duration2.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1012
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean506.5
Minimum1
Maximum1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2024-03-23T04:26:59.731165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile51.55
Q1253.75
median506.5
Q3759.25
95-th percentile961.45
Maximum1012
Range1011
Interquartile range (IQR)505.5

Descriptive statistics

Standard deviation292.28354
Coefficient of variation (CV)0.57706523
Kurtosis-1.2
Mean506.5
Median Absolute Deviation (MAD)253
Skewness0
Sum512578
Variance85429.667
MonotonicityStrictly increasing
2024-03-23T04:27:00.251673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
682 1
 
0.1%
669 1
 
0.1%
670 1
 
0.1%
671 1
 
0.1%
672 1
 
0.1%
673 1
 
0.1%
674 1
 
0.1%
675 1
 
0.1%
676 1
 
0.1%
Other values (1002) 1002
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1012 1
0.1%
1011 1
0.1%
1010 1
0.1%
1009 1
0.1%
1008 1
0.1%
1007 1
0.1%
1006 1
0.1%
1005 1
0.1%
1004 1
0.1%
1003 1
0.1%

업종명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
일반미용업
440 
미용업
177 
피부미용업
119 
네일미용업
97 
종합미용업
48 
Other values (11)
131 

Length

Max length23
Median length5
Mean length5.9209486
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 440
43.5%
미용업 177
17.5%
피부미용업 119
 
11.8%
네일미용업 97
 
9.6%
종합미용업 48
 
4.7%
네일미용업, 화장ㆍ분장 미용업 24
 
2.4%
피부미용업, 네일미용업 19
 
1.9%
화장ㆍ분장 미용업 19
 
1.9%
피부미용업, 화장ㆍ분장 미용업 19
 
1.9%
일반미용업, 화장ㆍ분장 미용업 16
 
1.6%
Other values (6) 34
 
3.4%

Length

2024-03-23T04:27:00.714860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반미용업 482
39.0%
미용업 271
21.9%
피부미용업 177
 
14.3%
네일미용업 164
 
13.3%
화장ㆍ분장 94
 
7.6%
종합미용업 48
 
3.9%

업소명
Text

Distinct985
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-03-23T04:27:01.655132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27
Mean length6.4940711
Min length1

Characters and Unicode

Total characters6572
Distinct characters535
Distinct categories10 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique961 ?
Unique (%)95.0%

Sample

1st row노슬헤어
2nd row고운헤어
3rd row외출준비
4th row정 미용실
5th row정세은 헤어
ValueCountFrequency (%)
hair 24
 
1.9%
헤어 21
 
1.6%
네일 10
 
0.8%
미용실 10
 
0.8%
에스테틱 8
 
0.6%
beauty 6
 
0.5%
스킨앤바디 6
 
0.5%
nail 6
 
0.5%
경산점 5
 
0.4%
작헤어 5
 
0.4%
Other values (1111) 1175
92.1%
2024-03-23T04:27:03.121126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 408
 
6.2%
헤 393
 
6.0%
265
 
4.0%
미 204
 
3.1%
( 150
 
2.3%
) 150
 
2.3%
실 134
 
2.0%
스 133
 
2.0%
용 130
 
2.0%
이 119
 
1.8%
Other values (525) 4486
68.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4944
75.2%
Uppercase Letter 499
 
7.6%
Lowercase Letter 454
 
6.9%
Space Separator 265
 
4.0%
Open Punctuation 150
 
2.3%
Close Punctuation 150
 
2.3%
Other Punctuation 66
 
1.0%
Decimal Number 36
 
0.5%
Dash Punctuation 5
 
0.1%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 408
 
8.3%
헤 393
 
7.9%
미 204
 
4.1%
실 134
 
2.7%
스 133
 
2.7%
용 130
 
2.6%
이 119
 
2.4%
일 117
 
2.4%
리 113
 
2.3%
티 98
 
2.0%
Other values (454) 3095
62.6%
Uppercase Letter
ValueCountFrequency (%)
A 58
 
11.6%
I 43
 
8.6%
N 39
 
7.8%
H 36
 
7.2%
E 33
 
6.6%
O 30
 
6.0%
R 27
 
5.4%
L 26
 
5.2%
S 25
 
5.0%
B 23
 
4.6%
Other values (14) 159
31.9%
Lowercase Letter
ValueCountFrequency (%)
a 57
12.6%
i 56
12.3%
e 52
11.5%
r 40
8.8%
o 32
 
7.0%
h 30
 
6.6%
l 28
 
6.2%
t 26
 
5.7%
n 24
 
5.3%
u 23
 
5.1%
Other values (14) 86
18.9%
Other Punctuation
ValueCountFrequency (%)
. 15
22.7%
, 13
19.7%
# 13
19.7%
& 11
16.7%
' 5
 
7.6%
: 4
 
6.1%
· 2
 
3.0%
/ 1
 
1.5%
? 1
 
1.5%
＆ 1
 
1.5%
Decimal Number
ValueCountFrequency (%)
1 8
22.2%
2 8
22.2%
3 7
19.4%
0 4
11.1%
5 4
11.1%
4 2
 
5.6%
8 2
 
5.6%
9 1
 
2.8%
Space Separator
ValueCountFrequency (%)
265
100.0%
Open Punctuation
ValueCountFrequency (%)
( 150
100.0%
Close Punctuation
ValueCountFrequency (%)
) 150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4937
75.1%
Latin 953
 
14.5%
Common 675
 
10.3%
Han 4
 
0.1%
Hiragana 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 408
 
8.3%
헤 393
 
8.0%
미 204
 
4.1%
실 134
 
2.7%
스 133
 
2.7%
용 130
 
2.6%
이 119
 
2.4%
일 117
 
2.4%
리 113
 
2.3%
티 98
 
2.0%
Other values (449) 3088
62.5%
Latin
ValueCountFrequency (%)
A 58
 
6.1%
a 57
 
6.0%
i 56
 
5.9%
e 52
 
5.5%
I 43
 
4.5%
r 40
 
4.2%
N 39
 
4.1%
H 36
 
3.8%
E 33
 
3.5%
o 32
 
3.4%
Other values (38) 507
53.2%
Common
ValueCountFrequency (%)
265
39.3%
( 150
22.2%
) 150
22.2%
. 15
 
2.2%
, 13
 
1.9%
# 13
 
1.9%
& 11
 
1.6%
1 8
 
1.2%
2 8
 
1.2%
3 7
 
1.0%
Other values (13) 35
 
5.2%
Hiragana
ValueCountFrequency (%)
と 1
33.3%
も 1
33.3%
る 1
33.3%
Han
ValueCountFrequency (%)
秀 2
50.0%
美 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4937
75.1%
ASCII 1625
 
24.7%
CJK 4
 
0.1%
None 3
 
< 0.1%
Hiragana 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 408
 
8.3%
헤 393
 
8.0%
미 204
 
4.1%
실 134
 
2.7%
스 133
 
2.7%
용 130
 
2.6%
이 119
 
2.4%
일 117
 
2.4%
리 113
 
2.3%
티 98
 
2.0%
Other values (449) 3088
62.5%
ASCII
ValueCountFrequency (%)
265
 
16.3%
( 150
 
9.2%
) 150
 
9.2%
A 58
 
3.6%
a 57
 
3.5%
i 56
 
3.4%
e 52
 
3.2%
I 43
 
2.6%
r 40
 
2.5%
N 39
 
2.4%
Other values (59) 715
44.0%
CJK
ValueCountFrequency (%)
秀 2
50.0%
美 2
50.0%
None
ValueCountFrequency (%)
· 2
66.7%
＆ 1
33.3%
Hiragana
ValueCountFrequency (%)
と 1
33.3%
も 1
33.3%
る 1
33.3%

영업소 주소(도로명)
Text

Distinct975
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2024-03-23T04:27:04.090662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length46
Mean length28.761858
Min length18

Characters and Unicode

Total characters29107
Distinct characters252
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique940 ?
Unique (%)92.9%

Sample

1st row경상북도 경산시 삼풍로2길 5 (삼풍동)
2nd row경상북도 경산시 삼성현로31길 16, 2호 (옥산동)
3rd row경상북도 경산시 압량읍 부적길 56
4th row경상북도 경산시 하양읍 금송로 41
5th row경상북도 경산시 진량읍 황제1길 86-25, 211호 (황제아파트상가)
ValueCountFrequency (%)
경상북도 1012
 
16.3%
경산시 1012
 
16.3%
1층 214
 
3.5%
하양읍 146
 
2.4%
옥산동 111
 
1.8%
사동 110
 
1.8%
2층 92
 
1.5%
진량읍 81
 
1.3%
중방동 80
 
1.3%
정평동 73
 
1.2%
Other values (971) 3261
52.7%
2024-03-23T04:27:06.179574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5184
17.8%
경 2238
 
7.7%
1 1392
 
4.8%
산 1369
 
4.7%
상 1139
 
3.9%
북 1032
 
3.5%
도 1028
 
3.5%
시 1018
 
3.5%
동 911
 
3.1%
로 899
 
3.1%
Other values (242) 12897
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16444
56.5%
Space Separator 5184
 
17.8%
Decimal Number 4958
 
17.0%
Open Punctuation 727
 
2.5%
Close Punctuation 727
 
2.5%
Other Punctuation 678
 
2.3%
Dash Punctuation 313
 
1.1%
Uppercase Letter 74
 
0.3%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 2238
 
13.6%
산 1369
 
8.3%
상 1139
 
6.9%
북 1032
 
6.3%
도 1028
 
6.3%
시 1018
 
6.2%
동 911
 
5.5%
로 899
 
5.5%
길 681
 
4.1%
층 336
 
2.0%
Other values (206) 5793
35.2%
Uppercase Letter
ValueCountFrequency (%)
R 12
16.2%
A 10
13.5%
B 8
10.8%
K 6
8.1%
I 5
6.8%
S 5
6.8%
E 5
6.8%
M 4
 
5.4%
V 4
 
5.4%
P 4
 
5.4%
Other values (7) 11
14.9%
Decimal Number
ValueCountFrequency (%)
1 1392
28.1%
2 875
17.6%
3 562
11.3%
0 462
 
9.3%
4 372
 
7.5%
5 339
 
6.8%
6 257
 
5.2%
7 253
 
5.1%
8 229
 
4.6%
9 217
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 673
99.3%
· 3
 
0.4%
& 1
 
0.1%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
5184
100.0%
Open Punctuation
ValueCountFrequency (%)
( 727
100.0%
Close Punctuation
ValueCountFrequency (%)
) 727
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 313
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16444
56.5%
Common 12587
43.2%
Latin 76
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 2238
 
13.6%
산 1369
 
8.3%
상 1139
 
6.9%
북 1032
 
6.3%
도 1028
 
6.3%
시 1018
 
6.2%
동 911
 
5.5%
로 899
 
5.5%
길 681
 
4.1%
층 336
 
2.0%
Other values (206) 5793
35.2%
Common
ValueCountFrequency (%)
5184
41.2%
1 1392
 
11.1%
2 875
 
7.0%
( 727
 
5.8%
) 727
 
5.8%
, 673
 
5.3%
3 562
 
4.5%
0 462
 
3.7%
4 372
 
3.0%
5 339
 
2.7%
Other values (8) 1274
 
10.1%
Latin
ValueCountFrequency (%)
R 12
15.8%
A 10
13.2%
B 8
10.5%
K 6
7.9%
I 5
 
6.6%
S 5
 
6.6%
E 5
 
6.6%
M 4
 
5.3%
V 4
 
5.3%
P 4
 
5.3%
Other values (8) 13
17.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16444
56.5%
ASCII 12660
43.5%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5184
40.9%
1 1392
 
11.0%
2 875
 
6.9%
( 727
 
5.7%
) 727
 
5.7%
, 673
 
5.3%
3 562
 
4.4%
0 462
 
3.6%
4 372
 
2.9%
5 339
 
2.7%
Other values (25) 1347
 
10.6%
Hangul
ValueCountFrequency (%)
경 2238
 
13.6%
산 1369
 
8.3%
상 1139
 
6.9%
북 1032
 
6.3%
도 1028
 
6.3%
시 1018
 
6.2%
동 911
 
5.5%
로 899
 
5.5%
길 681
 
4.1%
층 336
 
2.0%
Other values (206) 5793
35.2%
None
ValueCountFrequency (%)
· 3
100.0%

Interactions

2024-03-23T04:26:58.334736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T04:27:06.456946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종명
번호1.0000.901
업종명0.9011.000
2024-03-23T04:27:06.692271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종명
번호1.0000.646
업종명0.6461.000

Missing values

2024-03-23T04:26:58.832593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T04:26:59.206736image/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

번호업종명업소명영업소 주소(도로명)
01미용업노슬헤어경상북도 경산시 삼풍로2길 5 (삼풍동)
12미용업고운헤어경상북도 경산시 삼성현로31길 16, 2호 (옥산동)
23미용업외출준비경상북도 경산시 압량읍 부적길 56
34미용업정 미용실경상북도 경산시 하양읍 금송로 41
45미용업정세은 헤어경상북도 경산시 진량읍 황제1길 86-25, 211호 (황제아파트상가)
56미용업헤어크리닉투경상북도 경산시 하양읍 조산천동길 26
67미용업신데렐라미용실경상북도 경산시 진량읍 봉황길 70-1, 경산4차 삼주봉황타운 상가 9동 1층 109호
78미용업이레헤어경상북도 경산시 진량읍 봉황길 29, 경산1차 삼주봉황타운 106동 115호
89미용업단발머리경상북도 경산시 성암로1길 2-4 (옥산동)
910미용업에스더헤어샵경상북도 경산시 성암로8길 11 (옥산동)
번호업종명업소명영업소 주소(도로명)
10021003일반미용업, 네일미용업, 화장ㆍ분장 미용업이쁘다 미용경상북도 경산시 경안로47길 32-17, 2층 (중방동)
10031004일반미용업, 네일미용업, 화장ㆍ분장 미용업로제머리염색＆네일경상북도 경산시 하양읍 아낙고개길 25, 1층
10041005피부미용업, 네일미용업, 화장ㆍ분장 미용업예담네일경상북도 경산시 경안로67길 13-12, 1층 (대평동)
10051006피부미용업, 네일미용업, 화장ㆍ분장 미용업뷰티마인드경상북도 경산시 진량읍 공단1로1길 33
10061007피부미용업, 네일미용업, 화장ㆍ분장 미용업린뷰티경상북도 경산시 중앙로19길 28 (중방동)
10071008피부미용업, 네일미용업, 화장ㆍ분장 미용업유뷰티(You BEAUTY)경상북도 경산시 경산로13길 33 (옥곡동)
10081009피부미용업, 네일미용업, 화장ㆍ분장 미용업렛미인/바이루미 경산점경상북도 경산시 압량읍 압독3로2길 3-12
10091010피부미용업, 네일미용업, 화장ㆍ분장 미용업요니뷰티스튜디오(YONI BEAUTY STUDIO)경상북도 경산시 하양읍 하양로 57, 4층
10101011피부미용업, 네일미용업, 화장ㆍ분장 미용업이쁘9경상북도 경산시 펜타힐즈2로 37, 205호 (중산동)
10111012피부미용업, 네일미용업, 화장ㆍ분장 미용업살롱드바미(salon de balmy)경상북도 경산시 중앙로 15, 1층 (사정동)