Overview

Dataset statistics

Number of variables7
Number of observations70
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory58.9 B

Variable types

Numeric1
Text4
Boolean2

Dataset

Description휠체어 출입 가능한 음식점(업장, 화장실) 현황(2014년)입니다. 항목은 번호, 업소명, 소재지, 주메뉴, 전화번호, 영업장, 화장실입니다.
Author경상남도 창원시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15055438

Alerts

영업장 has constant value ""Constant
번호 is highly overall correlated with 화장실High correlation
화장실 is highly overall correlated with 번호High correlation
전화번호 has 1 (1.4%) missing valuesMissing
번호 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:31:42.547762
Analysis finished2023-12-10 23:31:43.243686
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.5
Minimum1
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-11T08:31:43.315044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.45
Q118.25
median35.5
Q352.75
95-th percentile66.55
Maximum70
Range69
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation20.351085
Coefficient of variation (CV)0.57327
Kurtosis-1.2
Mean35.5
Median Absolute Deviation (MAD)17.5
Skewness0
Sum2485
Variance414.16667
MonotonicityStrictly increasing
2023-12-11T08:31:43.448370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
46 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
45 1
 
1.4%
54 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%
61 1
1.4%

업소명
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-11T08:31:43.728884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length4.9
Min length2

Characters and Unicode

Total characters343
Distinct characters182
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)100.0%

Sample

1st row예담
2nd row한우별곡
3rd row뽕스패뉴
4th row통일각
5th row주촌뒷고기
ValueCountFrequency (%)
예담 1
 
1.4%
맘스터치 1
 
1.4%
명동보리밥 1
 
1.4%
치롤라로쏘 1
 
1.4%
신기소 1
 
1.4%
형제한우석쇠불고기 1
 
1.4%
전주비빔밥 1
 
1.4%
하나모리 1
 
1.4%
대박가야밀면,돈가스 1
 
1.4%
하동돼지국밥 1
 
1.4%
Other values (62) 62
86.1%
2023-12-11T08:31:44.107004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 10
 
2.9%
가 8
 
2.3%
밥 8
 
2.3%
이 8
 
2.3%
리 7
 
2.0%
기 6
 
1.7%
국 6
 
1.7%
지 5
 
1.5%
한 5
 
1.5%
일 5
 
1.5%
Other values (172) 275
80.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 335
97.7%
Other Punctuation 3
 
0.9%
Space Separator 2
 
0.6%
Uppercase Letter 2
 
0.6%
Other Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 10
 
3.0%
가 8
 
2.4%
밥 8
 
2.4%
이 8
 
2.4%
리 7
 
2.1%
기 6
 
1.8%
국 6
 
1.8%
지 5
 
1.5%
한 5
 
1.5%
일 5
 
1.5%
Other values (166) 267
79.7%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
, 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
J 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 336
98.0%
Common 5
 
1.5%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 10
 
3.0%
가 8
 
2.4%
밥 8
 
2.4%
이 8
 
2.4%
리 7
 
2.1%
기 6
 
1.8%
국 6
 
1.8%
지 5
 
1.5%
한 5
 
1.5%
일 5
 
1.5%
Other values (167) 268
79.8%
Common
ValueCountFrequency (%)
2
40.0%
& 2
40.0%
, 1
20.0%
Latin
ValueCountFrequency (%)
J 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 335
97.7%
ASCII 7
 
2.0%
None 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 10
 
3.0%
가 8
 
2.4%
밥 8
 
2.4%
이 8
 
2.4%
리 7
 
2.1%
기 6
 
1.8%
국 6
 
1.8%
지 5
 
1.5%
한 5
 
1.5%
일 5
 
1.5%
Other values (166) 267
79.7%
ASCII
ValueCountFrequency (%)
2
28.6%
& 2
28.6%
, 1
14.3%
J 1
14.3%
C 1
14.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소 재 지
Text

Distinct51
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-11T08:31:44.381261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28.5
Mean length23.428571
Min length12

Characters and Unicode

Total characters1640
Distinct characters115
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)64.3%

Sample

1st row의창구 용지로 169번길 15(용호동, 레이크벌스빌딩 101호)
2nd row의창구 용지로 169번길 13(용호동, 라이크빌 201호)
3rd row의창구 용지로 149(용호동 101호)
4th row의창구 용지로 267(용호동)
5th row성산구 대정로 36(지하층 14-15층)
ValueCountFrequency (%)
마산합포구 29
 
9.8%
성산구 16
 
5.4%
마산회원구 14
 
4.7%
251(산호동 8
 
2.7%
삼호로 8
 
2.7%
신세계백화점 8
 
2.7%
합포로 8
 
2.7%
진해구 7
 
2.4%
마산점 7
 
2.4%
홈플러스 7
 
2.4%
Other values (115) 183
62.0%
2023-12-11T08:31:44.768785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
225
 
13.7%
동 85
 
5.2%
산 81
 
4.9%
구 71
 
4.3%
1 68
 
4.1%
로 60
 
3.7%
마 60
 
3.7%
) 59
 
3.6%
( 59
 
3.6%
포 44
 
2.7%
Other values (105) 828
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 986
60.1%
Decimal Number 269
 
16.4%
Space Separator 225
 
13.7%
Close Punctuation 59
 
3.6%
Open Punctuation 59
 
3.6%
Other Punctuation 34
 
2.1%
Dash Punctuation 8
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 85
 
8.6%
산 81
 
8.2%
구 71
 
7.2%
로 60
 
6.1%
마 60
 
6.1%
포 44
 
4.5%
호 40
 
4.1%
합 37
 
3.8%
대 29
 
2.9%
성 21
 
2.1%
Other values (90) 458
46.5%
Decimal Number
ValueCountFrequency (%)
1 68
25.3%
2 35
13.0%
5 31
11.5%
3 31
11.5%
6 29
10.8%
4 19
 
7.1%
8 17
 
6.3%
0 16
 
5.9%
7 14
 
5.2%
9 9
 
3.3%
Space Separator
ValueCountFrequency (%)
225
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Other Punctuation
ValueCountFrequency (%)
, 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 986
60.1%
Common 654
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 85
 
8.6%
산 81
 
8.2%
구 71
 
7.2%
로 60
 
6.1%
마 60
 
6.1%
포 44
 
4.5%
호 40
 
4.1%
합 37
 
3.8%
대 29
 
2.9%
성 21
 
2.1%
Other values (90) 458
46.5%
Common
ValueCountFrequency (%)
225
34.4%
1 68
 
10.4%
) 59
 
9.0%
( 59
 
9.0%
2 35
 
5.4%
, 34
 
5.2%
5 31
 
4.7%
3 31
 
4.7%
6 29
 
4.4%
4 19
 
2.9%
Other values (5) 64
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 986
60.1%
ASCII 654
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
225
34.4%
1 68
 
10.4%
) 59
 
9.0%
( 59
 
9.0%
2 35
 
5.4%
, 34
 
5.2%
5 31
 
4.7%
3 31
 
4.7%
6 29
 
4.4%
4 19
 
2.9%
Other values (5) 64
 
9.8%
Hangul
ValueCountFrequency (%)
동 85
 
8.6%
산 81
 
8.2%
구 71
 
7.2%
로 60
 
6.1%
마 60
 
6.1%
포 44
 
4.5%
호 40
 
4.1%
합 37
 
3.8%
대 29
 
2.9%
성 21
 
2.1%
Other values (90) 458
46.5%

주메뉴
Text

Distinct49
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-11T08:31:44.972962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.5
Min length1

Characters and Unicode

Total characters245
Distinct characters96
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)51.4%

Sample

1st row등심
2nd row등심
3rd row스파케티
4th row갈비찜
5th row삼겹살
ValueCountFrequency (%)
삼겹살 6
 
8.1%
비빔밥 5
 
6.8%
보리밥 3
 
4.1%
등심 3
 
4.1%
스테이크 3
 
4.1%
짜장면 3
 
4.1%
생선초밥 2
 
2.7%
칼국수 2
 
2.7%
스시 2
 
2.7%
샤브샤브 2
 
2.7%
Other values (40) 43
58.1%
2023-12-11T08:31:45.276610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
밥 16
 
6.5%
스 10
 
4.1%
비 9
 
3.7%
살 7
 
2.9%
국 7
 
2.9%
삼 6
 
2.4%
겹 6
 
2.4%
식 6
 
2.4%
이 5
 
2.0%
브 5
 
2.0%
Other values (86) 168
68.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 236
96.3%
Other Punctuation 5
 
2.0%
Space Separator 4
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
밥 16
 
6.8%
스 10
 
4.2%
비 9
 
3.8%
살 7
 
3.0%
국 7
 
3.0%
삼 6
 
2.5%
겹 6
 
2.5%
식 6
 
2.5%
이 5
 
2.1%
브 5
 
2.1%
Other values (84) 159
67.4%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 236
96.3%
Common 9
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
밥 16
 
6.8%
스 10
 
4.2%
비 9
 
3.8%
살 7
 
3.0%
국 7
 
3.0%
삼 6
 
2.5%
겹 6
 
2.5%
식 6
 
2.5%
이 5
 
2.1%
브 5
 
2.1%
Other values (84) 159
67.4%
Common
ValueCountFrequency (%)
, 5
55.6%
4
44.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 236
96.3%
ASCII 9
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
밥 16
 
6.8%
스 10
 
4.2%
비 9
 
3.8%
살 7
 
3.0%
국 7
 
3.0%
삼 6
 
2.5%
겹 6
 
2.5%
식 6
 
2.5%
이 5
 
2.1%
브 5
 
2.1%
Other values (84) 159
67.4%
ASCII
ValueCountFrequency (%)
, 5
55.6%
4
44.4%

전화번호
Text

MISSING 

Distinct62
Distinct (%)89.9%
Missing1
Missing (%)1.4%
Memory size692.0 B
2023-12-11T08:31:45.514539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters552
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

Unique59 ?
Unique (%)85.5%

Sample

1st row289-8488
2nd row283-1170
3rd row285-4888
4th row285-6868
5th row283-4044
ValueCountFrequency (%)
259-8124 6
 
8.7%
224-5554 2
 
2.9%
232-1034 2
 
2.9%
545-2772 1
 
1.4%
240-6799 1
 
1.4%
240-5730 1
 
1.4%
240-6985 1
 
1.4%
222-8831 1
 
1.4%
248-6233 1
 
1.4%
222-8916 1
 
1.4%
Other values (52) 52
75.4%
2023-12-11T08:31:45.862995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 120
21.7%
- 69
12.5%
4 63
11.4%
3 48
 
8.7%
5 47
 
8.5%
1 47
 
8.5%
8 46
 
8.3%
9 33
 
6.0%
7 28
 
5.1%
6 26
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 483
87.5%
Dash Punctuation 69
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 120
24.8%
4 63
13.0%
3 48
 
9.9%
5 47
 
9.7%
1 47
 
9.7%
8 46
 
9.5%
9 33
 
6.8%
7 28
 
5.8%
6 26
 
5.4%
0 25
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 552
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 120
21.7%
- 69
12.5%
4 63
11.4%
3 48
 
8.7%
5 47
 
8.5%
1 47
 
8.5%
8 46
 
8.3%
9 33
 
6.0%
7 28
 
5.1%
6 26
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 552
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 120
21.7%
- 69
12.5%
4 63
11.4%
3 48
 
8.7%
5 47
 
8.5%
1 47
 
8.5%
8 46
 
8.3%
9 33
 
6.0%
7 28
 
5.1%
6 26
 
4.7%

영업장
Boolean

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size202.0 B
True
70 
ValueCountFrequency (%)
True 70
100.0%
2023-12-11T08:31:45.970297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

화장실
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size202.0 B
True
46 
False
24 
ValueCountFrequency (%)
True 46
65.7%
False 24
34.3%
2023-12-11T08:31:46.048496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-11T08:31:42.979470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:31:46.122241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업소명소 재 지주메뉴전화번호화장실
번호1.0001.0000.9770.8150.9870.921
업소명1.0001.0001.0001.0001.0001.000
소 재 지0.9771.0001.0000.5661.0001.000
주메뉴0.8151.0000.5661.0000.9540.707
전화번호0.9871.0001.0000.9541.0001.000
화장실0.9211.0001.0000.7071.0001.000
2023-12-11T08:31:46.217438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호화장실
번호1.0000.717
화장실0.7171.000

Missing values

2023-12-11T08:31:43.084353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:31:43.184955image/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

번호업소명소 재 지주메뉴전화번호영업장화장실
01예담의창구 용지로 169번길 15(용호동, 레이크벌스빌딩 101호)등심289-8488YN
12한우별곡의창구 용지로 169번길 13(용호동, 라이크빌 201호)등심283-1170YN
23뽕스패뉴의창구 용지로 149(용호동 101호)스파케티285-4888YN
34통일각의창구 용지로 267(용호동)갈비찜285-6868YN
45주촌뒷고기성산구 대정로 36(지하층 14-15층)삼겹살283-4044YY
56소라보리밥성산구 원이대로 883번길 15-38(가음동)보리밥285-3351YN
67동네보리밥성산구 대정로 36(지하층 33)보리밥283-5419YN
78승승장구식당성산구 가양로 124번길 15(대방동, 대암빌딩 203호)주점262-5879YN
89맘스터치성산구 가양로 124번길 15(대방동, 대암빌딩 205호)햄버거266-3232YN
910㈜설빙창원대방본점성산구 대방동 가양로 124-15 201호삼겹살284-3304YN
번호업소명소 재 지주메뉴전화번호영업장화장실
6061죽정마산회원구 삼호로 56(양덕동, 홈플러스 마산점)비빔밥259-8124YY
6162모리스시마산회원구 삼호로 56(양덕동, 홈플러스 마산점)스시259-8124YY
6263예가낙지전문점마산합포구 해안대로 331(남성동)낙지볶음246-3339YY
6364닭한마리칼국수진해구 석동로 75번길 7(석동)닭칼국수551-8222YN
6465돈&삼겹진해구 냉천로 42(석동)삼겹살543-3777YN
6566왕갈비둥지진해구 냉천로 42-1(석동)갈비551-6555YN
6667진해루진해구 중원동로 69-1(대흥동 지하)중화요리546-2643YN
6768구이세상돼랑이진해구 충장로 455번길 9가브리살542-9297YN
6869고봉민김밥진해구 진해대로 776번길 27(이동, 온메디칼 1층)김밥545-2772YY
6970쌈촌구이&샤브진해구 풍호로 45(자은동)샤브샤브543-0111YN