Overview

Dataset statistics

Number of variables6
Number of observations88
Missing cells21
Missing cells (%)4.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory50.5 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description인천광역시 남동구 골프연습장업에 대한 데이터로 연번, 업종, 상호, 시설주소, 시설전화번호, 데이터기준일자를 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15088977&srcSe=7661IVAWM27C61E190

Alerts

업종 has constant value ""Constant
데이터기준일 has constant value ""Constant
시설전화번호 has 21 (23.9%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique
시설주소(도로명) has unique valuesUnique

Reproduction

Analysis started2024-01-28 06:04:54.282841
Analysis finished2024-01-28 06:04:54.717564
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.5
Minimum1
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2024-01-28T15:04:54.778020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.35
Q122.75
median44.5
Q366.25
95-th percentile83.65
Maximum88
Range87
Interquartile range (IQR)43.5

Descriptive statistics

Standard deviation25.547342
Coefficient of variation (CV)0.57409757
Kurtosis-1.2
Mean44.5
Median Absolute Deviation (MAD)22
Skewness0
Sum3916
Variance652.66667
MonotonicityStrictly increasing
2024-01-28T15:04:54.891923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
46 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
60 1
 
1.1%
59 1
 
1.1%
Other values (78) 78
88.6%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%
81 1
1.1%
80 1
1.1%
79 1
1.1%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size836.0 B
골프연습장업
88 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
골프연습장업 88
100.0%

Length

2024-01-28T15:04:54.997499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T15:04:55.075631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
골프연습장업 88
100.0%

상호
Text

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size836.0 B
2024-01-28T15:04:55.268728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length8.3977273
Min length3

Characters and Unicode

Total characters739
Distinct characters147
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

Unique88 ?
Unique (%)100.0%

Sample

1st row노블골프랜드
2nd row두레골프클럽
3rd row우리 스크린골프
4th row성강골프랜드
5th row성강스크린골프
ValueCountFrequency (%)
스크린 16
 
9.7%
골프 14
 
8.5%
골프존파크 6
 
3.6%
스크린골프 5
 
3.0%
골프존 5
 
3.0%
인천 2
 
1.2%
앤 2
 
1.2%
필드 2
 
1.2%
gdr아카데미 2
 
1.2%
프로 2
 
1.2%
Other values (100) 109
66.1%
2024-01-28T15:04:55.662904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
 
10.4%
프 75
 
10.1%
골 71
 
9.6%
스 52
 
7.0%
크 44
 
6.0%
린 37
 
5.0%
존 18
 
2.4%
아 15
 
2.0%
미 13
 
1.8%
데 12
 
1.6%
Other values (137) 325
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 635
85.9%
Space Separator 77
 
10.4%
Uppercase Letter 19
 
2.6%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%
Decimal Number 2
 
0.3%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
프 75
 
11.8%
골 71
 
11.2%
스 52
 
8.2%
크 44
 
6.9%
린 37
 
5.8%
존 18
 
2.8%
아 15
 
2.4%
미 13
 
2.0%
데 12
 
1.9%
카 12
 
1.9%
Other values (121) 286
45.0%
Uppercase Letter
ValueCountFrequency (%)
G 5
26.3%
R 3
15.8%
D 2
 
10.5%
C 2
 
10.5%
T 2
 
10.5%
S 2
 
10.5%
M 1
 
5.3%
U 1
 
5.3%
O 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
3 1
50.0%
Space Separator
ValueCountFrequency (%)
77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 635
85.9%
Common 85
 
11.5%
Latin 19
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
프 75
 
11.8%
골 71
 
11.2%
스 52
 
8.2%
크 44
 
6.9%
린 37
 
5.8%
존 18
 
2.8%
아 15
 
2.4%
미 13
 
2.0%
데 12
 
1.9%
카 12
 
1.9%
Other values (121) 286
45.0%
Latin
ValueCountFrequency (%)
G 5
26.3%
R 3
15.8%
D 2
 
10.5%
C 2
 
10.5%
T 2
 
10.5%
S 2
 
10.5%
M 1
 
5.3%
U 1
 
5.3%
O 1
 
5.3%
Common
ValueCountFrequency (%)
77
90.6%
( 2
 
2.4%
) 2
 
2.4%
& 1
 
1.2%
2 1
 
1.2%
3 1
 
1.2%
- 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 635
85.9%
ASCII 104
 
14.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
74.0%
G 5
 
4.8%
R 3
 
2.9%
D 2
 
1.9%
C 2
 
1.9%
T 2
 
1.9%
( 2
 
1.9%
) 2
 
1.9%
S 2
 
1.9%
& 1
 
1.0%
Other values (6) 6
 
5.8%
Hangul
ValueCountFrequency (%)
프 75
 
11.8%
골 71
 
11.2%
스 52
 
8.2%
크 44
 
6.9%
린 37
 
5.8%
존 18
 
2.8%
아 15
 
2.4%
미 13
 
2.0%
데 12
 
1.9%
카 12
 
1.9%
Other values (121) 286
45.0%

시설주소(도로명)
Text

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size836.0 B
2024-01-28T15:04:55.927346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length45
Mean length37.090909
Min length24

Characters and Unicode

Total characters3264
Distinct characters171
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 담방로 45, 희망프라자 7층 (만수동)
2nd row인천광역시 남동구 남동대로239번길 72-20, 3층 (논현동, 두레비지니스센터)
3rd row인천광역시 남동구 은청로 16-7, 3층 (고잔동)
4th row인천광역시 남동구 논현고잔로109번길 106 (고잔동)
5th row인천광역시 남동구 논현고잔로109번길 106, 212~213호 (고잔동)
ValueCountFrequency (%)
인천광역시 88
 
14.5%
남동구 88
 
14.5%
논현동 28
 
4.6%
구월동 20
 
3.3%
2층 15
 
2.5%
고잔동 11
 
1.8%
간석동 9
 
1.5%
논고개로 9
 
1.5%
서창동 9
 
1.5%
4층 8
 
1.3%
Other values (222) 320
52.9%
2024-01-28T15:04:56.318332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
517
 
15.8%
동 184
 
5.6%
, 132
 
4.0%
1 122
 
3.7%
구 120
 
3.7%
2 105
 
3.2%
남 103
 
3.2%
인 100
 
3.1%
) 92
 
2.8%
( 92
 
2.8%
Other values (161) 1697
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1791
54.9%
Decimal Number 607
 
18.6%
Space Separator 517
 
15.8%
Other Punctuation 132
 
4.0%
Close Punctuation 92
 
2.8%
Open Punctuation 92
 
2.8%
Dash Punctuation 18
 
0.6%
Math Symbol 10
 
0.3%
Uppercase Letter 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 184
 
10.3%
구 120
 
6.7%
남 103
 
5.8%
인 100
 
5.6%
역 92
 
5.1%
로 90
 
5.0%
천 89
 
5.0%
시 88
 
4.9%
광 88
 
4.9%
층 66
 
3.7%
Other values (142) 771
43.0%
Decimal Number
ValueCountFrequency (%)
1 122
20.1%
2 105
17.3%
0 91
15.0%
3 63
10.4%
4 49
8.1%
6 42
 
6.9%
8 39
 
6.4%
5 39
 
6.4%
7 37
 
6.1%
9 20
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
A 2
40.0%
C 1
20.0%
Space Separator
ValueCountFrequency (%)
517
100.0%
Other Punctuation
ValueCountFrequency (%)
, 132
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 92
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1791
54.9%
Common 1468
45.0%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 184
 
10.3%
구 120
 
6.7%
남 103
 
5.8%
인 100
 
5.6%
역 92
 
5.1%
로 90
 
5.0%
천 89
 
5.0%
시 88
 
4.9%
광 88
 
4.9%
층 66
 
3.7%
Other values (142) 771
43.0%
Common
ValueCountFrequency (%)
517
35.2%
, 132
 
9.0%
1 122
 
8.3%
2 105
 
7.2%
) 92
 
6.3%
( 92
 
6.3%
0 91
 
6.2%
3 63
 
4.3%
4 49
 
3.3%
6 42
 
2.9%
Other values (6) 163
 
11.1%
Latin
ValueCountFrequency (%)
B 2
40.0%
A 2
40.0%
C 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1791
54.9%
ASCII 1473
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
517
35.1%
, 132
 
9.0%
1 122
 
8.3%
2 105
 
7.1%
) 92
 
6.2%
( 92
 
6.2%
0 91
 
6.2%
3 63
 
4.3%
4 49
 
3.3%
6 42
 
2.9%
Other values (9) 168
 
11.4%
Hangul
ValueCountFrequency (%)
동 184
 
10.3%
구 120
 
6.7%
남 103
 
5.8%
인 100
 
5.6%
역 92
 
5.1%
로 90
 
5.0%
천 89
 
5.0%
시 88
 
4.9%
광 88
 
4.9%
층 66
 
3.7%
Other values (142) 771
43.0%

시설전화번호
Text

MISSING 

Distinct65
Distinct (%)97.0%
Missing21
Missing (%)23.9%
Memory size836.0 B
2024-01-28T15:04:56.538070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.029851
Min length12

Characters and Unicode

Total characters806
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)94.0%

Sample

1st row032-469-0990
2nd row032-812-9017
3rd row032-814-8110
4th row032-437-0720
5th row032-473-8001
ValueCountFrequency (%)
032-431-5151 2
 
3.0%
032-469-0753 2
 
3.0%
032-433-8333 1
 
1.5%
032-428-6669 1
 
1.5%
032-429-1113 1
 
1.5%
032-851-0707 1
 
1.5%
032-469-0990 1
 
1.5%
032-472-8596 1
 
1.5%
032-472-7942 1
 
1.5%
032-437-0753 1
 
1.5%
Other values (55) 55
82.1%
2024-01-28T15:04:56.920409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 134
16.6%
0 129
16.0%
3 121
15.0%
2 116
14.4%
4 74
9.2%
7 67
8.3%
1 44
 
5.5%
5 37
 
4.6%
9 29
 
3.6%
6 27
 
3.3%
Other values (2) 28
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 671
83.3%
Dash Punctuation 134
 
16.6%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 129
19.2%
3 121
18.0%
2 116
17.3%
4 74
11.0%
7 67
10.0%
1 44
 
6.6%
5 37
 
5.5%
9 29
 
4.3%
6 27
 
4.0%
8 27
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 806
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 134
16.6%
0 129
16.0%
3 121
15.0%
2 116
14.4%
4 74
9.2%
7 67
8.3%
1 44
 
5.5%
5 37
 
4.6%
9 29
 
3.6%
6 27
 
3.3%
Other values (2) 28
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 806
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 134
16.6%
0 129
16.0%
3 121
15.0%
2 116
14.4%
4 74
9.2%
7 67
8.3%
1 44
 
5.5%
5 37
 
4.6%
9 29
 
3.6%
6 27
 
3.3%
Other values (2) 28
 
3.5%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size836.0 B
2023-08-02
88 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-02
2nd row2023-08-02
3rd row2023-08-02
4th row2023-08-02
5th row2023-08-02

Common Values

ValueCountFrequency (%)
2023-08-02 88
100.0%

Length

2024-01-28T15:04:57.042472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T15:04:57.126487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-02 88
100.0%

Interactions

2024-01-28T15:04:54.523400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T15:04:57.183498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호시설주소(도로명)시설전화번호
연번1.0001.0001.0000.980
상호1.0001.0001.0001.000
시설주소(도로명)1.0001.0001.0001.000
시설전화번호0.9801.0001.0001.000

Missing values

2024-01-28T15:04:54.604135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T15:04:54.684179image/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

연번업종상호시설주소(도로명)시설전화번호데이터기준일
01골프연습장업노블골프랜드인천광역시 남동구 담방로 45, 희망프라자 7층 (만수동)032-469-09902023-08-02
12골프연습장업두레골프클럽인천광역시 남동구 남동대로239번길 72-20, 3층 (논현동, 두레비지니스센터)032-812-90172023-08-02
23골프연습장업우리 스크린골프인천광역시 남동구 은청로 16-7, 3층 (고잔동)032-814-81102023-08-02
34골프연습장업성강골프랜드인천광역시 남동구 논현고잔로109번길 106 (고잔동)032-437-07202023-08-02
45골프연습장업성강스크린골프인천광역시 남동구 논현고잔로109번길 106, 212~213호 (고잔동)<NA>2023-08-02
56골프연습장업구월 스크린 골프인천광역시 남동구 용천로97번길 3, 4,5층 (구월동)032-473-80012023-08-02
67골프연습장업학성 스포렉스인천광역시 남동구 논현고잔로128번길 10, 2,3층 (고잔동)<NA>2023-08-02
78골프연습장업그린실내골프연습장인천광역시 남동구 장승로 28, 7층 (만수동)032-472-71712023-08-02
89골프연습장업학성스크린골프연습장인천광역시 남동구 논현고잔로128번길 10, 2층 (고잔동)032-432-07872023-08-02
910골프연습장업골프클리닉 이븐인천광역시 남동구 논고개로123번길 45, 701호 (논현동)032-422-99662023-08-02
연번업종상호시설주소(도로명)시설전화번호데이터기준일
7879골프연습장업SG에코스크린골프 인천논현점인천광역시 남동구 논고개로 77, 에코타워 11층 1104~6호 (논현동)032-433-00772023-08-02
7980골프연습장업바로피트니스 인천논현점인천광역시 남동구 논고개로 101, 아름다운타워 11층 1~3호 (논현동)032-441-44772023-08-02
8081골프연습장업브라보 퍼블릭 스크린인천광역시 남동구 앵고개로934번길 51, 흥인빌딩 7층 701호 (논현동)<NA>2023-08-02
8182골프연습장업마스터즈 프로 골프 아카데미&스크린인천광역시 남동구 서창방산로 51, 3층 301~3호 (서창동)032-463-02202023-08-02
8283골프연습장업아라지트인천광역시 남동구 논고개로 118, 양진타워 10층 1~2호 (논현동)032-434-75532023-08-02
8384골프연습장업논현스크린 골프존인천광역시 남동구 은봉로419번길 21, 2층 (논현동)032-433-83332023-08-02
8485골프연습장업마스터골프아카데미인천광역시 남동구 청능대로595번길 13, 2층 (논현동)032-710-07592023-08-02
8586골프연습장업S2 골프존 아카데미인천광역시 남동구 경인로 611, 간석오피앙 A동 201호 (간석동)032-429-11132023-08-02
8687골프연습장업골프존스퀘어인천광역시 남동구 논현고잔로135번길 30-13, 4층 (고잔동)032-822-07772023-08-02
8788골프연습장업지이앤홀딩스인천광역시 남동구 경인로 548, 지이앤홀딩스 1,2,3층 (간석동)<NA>2023-08-02