Overview

Dataset statistics

Number of variables5
Number of observations68
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory42.9 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description전북특별자치도 김제시 체육시설업신고 현황입니다.
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=1&menuCd=DOM_000000103007001000&pListTypeStr=&pId=3080630

Alerts

연번 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
상호 has unique valuesUnique
시설주소(도로명) has unique valuesUnique

Reproduction

Analysis started2024-03-14 02:08:01.929291
Analysis finished2024-03-14 02:08:02.360834
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.5
Minimum1
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-03-14T11:08:02.416352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.35
Q117.75
median34.5
Q351.25
95-th percentile64.65
Maximum68
Range67
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation19.77372
Coefficient of variation (CV)0.5731513
Kurtosis-1.2
Mean34.5
Median Absolute Deviation (MAD)17
Skewness0
Sum2346
Variance391
MonotonicityStrictly increasing
2024-03-14T11:08:02.540595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
45 1
 
1.5%
51 1
 
1.5%
50 1
 
1.5%
49 1
 
1.5%
48 1
 
1.5%
47 1
 
1.5%
46 1
 
1.5%
44 1
 
1.5%
36 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
68 1
1.5%
67 1
1.5%
66 1
1.5%
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%

업종
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size676.0 B
당구장업
30 
체육도장업
18 
골프연습장업
10 
체력단련장업
6 
승마장업
 
3

Length

Max length6
Median length5.5
Mean length4.7352941
Min length4

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
당구장업 30
44.1%
체육도장업 18
26.5%
골프연습장업 10
 
14.7%
체력단련장업 6
 
8.8%
승마장업 3
 
4.4%
썰매장업 1
 
1.5%

Length

2024-03-14T11:08:02.667152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:08:02.780819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당구장업 30
44.1%
체육도장업 18
26.5%
골프연습장업 10
 
14.7%
체력단련장업 6
 
8.8%
승마장업 3
 
4.4%
썰매장업 1
 
1.5%

상호
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-03-14T11:08:03.058429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.8088235
Min length4

Characters and Unicode

Total characters463
Distinct characters143
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st row김제무덕관
2nd row화랑석사태권도장
3rd row정무체육관
4th row금만검도장
5th row금메달체육관
ValueCountFrequency (%)
당구장 7
 
7.6%
당구클럽 5
 
5.4%
골프 2
 
2.2%
그랑프리당구장 1
 
1.1%
영상당구장 1
 
1.1%
곰당구장 1
 
1.1%
호빈 1
 
1.1%
다저스 1
 
1.1%
천일 1
 
1.1%
화랑석사태권도장 1
 
1.1%
Other values (71) 71
77.2%
2024-03-14T11:08:03.434877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 31
 
6.7%
당 30
 
6.5%
구 30
 
6.5%
24
 
5.2%
스 15
 
3.2%
럽 14
 
3.0%
클 14
 
3.0%
태 13
 
2.8%
프 12
 
2.6%
권 12
 
2.6%
Other values (133) 268
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 423
91.4%
Space Separator 24
 
5.2%
Uppercase Letter 9
 
1.9%
Decimal Number 3
 
0.6%
Lowercase Letter 2
 
0.4%
Dash Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 31
 
7.3%
당 30
 
7.1%
구 30
 
7.1%
스 15
 
3.5%
럽 14
 
3.3%
클 14
 
3.3%
태 13
 
3.1%
프 12
 
2.8%
권 12
 
2.8%
도 12
 
2.8%
Other values (118) 240
56.7%
Uppercase Letter
ValueCountFrequency (%)
C 2
22.2%
L 1
11.1%
A 1
11.1%
B 1
11.1%
J 1
11.1%
R 1
11.1%
D 1
11.1%
G 1
11.1%
Decimal Number
ValueCountFrequency (%)
7 2
66.7%
3 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
n 1
50.0%
i 1
50.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 423
91.4%
Common 29
 
6.3%
Latin 11
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 31
 
7.3%
당 30
 
7.1%
구 30
 
7.1%
스 15
 
3.5%
럽 14
 
3.3%
클 14
 
3.3%
태 13
 
3.1%
프 12
 
2.8%
권 12
 
2.8%
도 12
 
2.8%
Other values (118) 240
56.7%
Latin
ValueCountFrequency (%)
C 2
18.2%
L 1
9.1%
A 1
9.1%
B 1
9.1%
n 1
9.1%
i 1
9.1%
J 1
9.1%
R 1
9.1%
D 1
9.1%
G 1
9.1%
Common
ValueCountFrequency (%)
24
82.8%
7 2
 
6.9%
- 1
 
3.4%
& 1
 
3.4%
3 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 423
91.4%
ASCII 40
 
8.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 31
 
7.3%
당 30
 
7.1%
구 30
 
7.1%
스 15
 
3.5%
럽 14
 
3.3%
클 14
 
3.3%
태 13
 
3.1%
프 12
 
2.8%
권 12
 
2.8%
도 12
 
2.8%
Other values (118) 240
56.7%
ASCII
ValueCountFrequency (%)
24
60.0%
C 2
 
5.0%
7 2
 
5.0%
- 1
 
2.5%
& 1
 
2.5%
L 1
 
2.5%
A 1
 
2.5%
B 1
 
2.5%
3 1
 
2.5%
n 1
 
2.5%
Other values (5) 5
 
12.5%

시설주소(도로명)
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-03-14T11:08:03.659635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length18.5
Min length15

Characters and Unicode

Total characters1258
Distinct characters85
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

Unique68 ?
Unique (%)100.0%

Sample

1st row 김제시 요촌동1길 5-4 (요촌동)
2nd row 김제시 도작로 139 (검산동)
3rd row 김제시 도작8길 68-21 (신풍동)
4th row 김제시 도작9길 14 (신풍동)
5th row 김제시 도작로 103 (검산동)
ValueCountFrequency (%)
김제시 68
24.5%
요촌동 19
 
6.9%
신풍동 15
 
5.4%
검산동 14
 
5.1%
도작로 10
 
3.6%
동서로 7
 
2.5%
도작9길 4
 
1.4%
남북로 4
 
1.4%
만경읍 4
 
1.4%
금구면 4
 
1.4%
Other values (108) 128
46.2%
2024-03-14T11:08:04.017681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
281
22.3%
제 69
 
5.5%
시 68
 
5.4%
김 68
 
5.4%
동 67
 
5.3%
( 52
 
4.1%
) 52
 
4.1%
1 41
 
3.3%
로 40
 
3.2%
2 28
 
2.2%
Other values (75) 492
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 652
51.8%
Space Separator 281
22.3%
Decimal Number 206
 
16.4%
Open Punctuation 52
 
4.1%
Close Punctuation 52
 
4.1%
Dash Punctuation 12
 
1.0%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 69
 
10.6%
시 68
 
10.4%
김 68
 
10.4%
동 67
 
10.3%
로 40
 
6.1%
길 28
 
4.3%
촌 26
 
4.0%
요 26
 
4.0%
산 24
 
3.7%
도 18
 
2.8%
Other values (60) 218
33.4%
Decimal Number
ValueCountFrequency (%)
1 41
19.9%
2 28
13.6%
3 20
9.7%
9 20
9.7%
4 19
9.2%
5 19
9.2%
0 17
8.3%
8 17
8.3%
7 15
 
7.3%
6 10
 
4.9%
Space Separator
ValueCountFrequency (%)
281
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 652
51.8%
Common 606
48.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 69
 
10.6%
시 68
 
10.4%
김 68
 
10.4%
동 67
 
10.3%
로 40
 
6.1%
길 28
 
4.3%
촌 26
 
4.0%
요 26
 
4.0%
산 24
 
3.7%
도 18
 
2.8%
Other values (60) 218
33.4%
Common
ValueCountFrequency (%)
281
46.4%
( 52
 
8.6%
) 52
 
8.6%
1 41
 
6.8%
2 28
 
4.6%
3 20
 
3.3%
9 20
 
3.3%
4 19
 
3.1%
5 19
 
3.1%
0 17
 
2.8%
Other values (5) 57
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 652
51.8%
ASCII 606
48.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
281
46.4%
( 52
 
8.6%
) 52
 
8.6%
1 41
 
6.8%
2 28
 
4.6%
3 20
 
3.3%
9 20
 
3.3%
4 19
 
3.1%
5 19
 
3.1%
0 17
 
2.8%
Other values (5) 57
 
9.4%
Hangul
ValueCountFrequency (%)
제 69
 
10.6%
시 68
 
10.4%
김 68
 
10.4%
동 67
 
10.3%
로 40
 
6.1%
길 28
 
4.3%
촌 26
 
4.0%
요 26
 
4.0%
산 24
 
3.7%
도 18
 
2.8%
Other values (60) 218
33.4%

전화번호
Text

Distinct60
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-03-14T11:08:04.224364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.338235
Min length7

Characters and Unicode

Total characters771
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)86.8%

Sample

1st row063-544-0477
2nd row063-544-0424
3rd row063-547-9939
4th row063-545-4525
5th row063-546-8485
ValueCountFrequency (%)
데이터 9
 
11.7%
미집계 9
 
11.7%
063-544-3888 1
 
1.3%
063-545-3370 1
 
1.3%
063-546-7893 1
 
1.3%
063-545-4111 1
 
1.3%
063-542-8878 1
 
1.3%
063-547-5792 1
 
1.3%
063-545-2555 1
 
1.3%
063-542-7777 1
 
1.3%
Other values (51) 51
66.2%
2024-03-14T11:08:04.563998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 118
15.3%
4 94
12.2%
0 93
12.1%
5 93
12.1%
3 88
11.4%
6 82
10.6%
7 39
 
5.1%
2 30
 
3.9%
8 28
 
3.6%
9 27
 
3.5%
Other values (8) 79
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 590
76.5%
Dash Punctuation 118
 
15.3%
Other Letter 54
 
7.0%
Space Separator 9
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 94
15.9%
0 93
15.8%
5 93
15.8%
3 88
14.9%
6 82
13.9%
7 39
6.6%
2 30
 
5.1%
8 28
 
4.7%
9 27
 
4.6%
1 16
 
2.7%
Other Letter
ValueCountFrequency (%)
이 9
16.7%
계 9
16.7%
집 9
16.7%
미 9
16.7%
터 9
16.7%
데 9
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 717
93.0%
Hangul 54
 
7.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 118
16.5%
4 94
13.1%
0 93
13.0%
5 93
13.0%
3 88
12.3%
6 82
11.4%
7 39
 
5.4%
2 30
 
4.2%
8 28
 
3.9%
9 27
 
3.8%
Other values (2) 25
 
3.5%
Hangul
ValueCountFrequency (%)
이 9
16.7%
계 9
16.7%
집 9
16.7%
미 9
16.7%
터 9
16.7%
데 9
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 717
93.0%
Hangul 54
 
7.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 118
16.5%
4 94
13.1%
0 93
13.0%
5 93
13.0%
3 88
12.3%
6 82
11.4%
7 39
 
5.4%
2 30
 
4.2%
8 28
 
3.9%
9 27
 
3.8%
Other values (2) 25
 
3.5%
Hangul
ValueCountFrequency (%)
이 9
16.7%
계 9
16.7%
집 9
16.7%
미 9
16.7%
터 9
16.7%
데 9
16.7%

Interactions

2024-03-14T11:08:02.167437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:08:04.656791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종상호시설주소(도로명)전화번호
연번1.0000.8901.0001.0000.766
업종0.8901.0001.0001.0000.969
상호1.0001.0001.0001.0001.000
시설주소(도로명)1.0001.0001.0001.0001.000
전화번호0.7660.9691.0001.0001.000
2024-03-14T11:08:04.737148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.712
업종0.7121.000

Missing values

2024-03-14T11:08:02.261096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:08:02.331733image/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)전화번호
01체육도장업김제무덕관김제시 요촌동1길 5-4 (요촌동)063-544-0477
12체육도장업화랑석사태권도장김제시 도작로 139 (검산동)063-544-0424
23체육도장업정무체육관김제시 도작8길 68-21 (신풍동)063-547-9939
34체육도장업금만검도장김제시 도작9길 14 (신풍동)063-545-4525
45체육도장업금메달체육관김제시 도작로 103 (검산동)063-546-8485
56체육도장업호키태권도장김제시 요촌중3길 9 (요촌동)063-547-1470
67체육도장업석사태권도장김제시 요촌중1길 4 (요촌동)063-548-0456
78체육도장업꿈나무태권도김제시 서낭당길 47 (요촌동)063-545-2282
89체육도장업국기태권도장김제시 도작8길 75-18 (신풍동)063-547-1652
910체육도장업호원태권도체육관김제시 서낭당길 132 (요촌동)063-543-5253
연번업종상호시설주소(도로명)전화번호
5859당구장업3차 당구클럽김제시 도작로 20 (검산동)063-545-8466
5960당구장업프로 당구장김제시 검산택지5길 34 (검산동)데이터 미집계
6061당구장업길 당구장김제시 만경읍 만경로 807데이터 미집계
6162당구장업한양당구장김제시 금성로 80 (신풍동)데이터 미집계
6263당구장업승진당구장김제시 금구면 금구로 50-9, 송원상가동 2층 201호데이터 미집계
6364당구장업오투당구클럽김제시 요촌중길 146 (하동, 하동제일오투그란데)데이터 미집계
6465썰매장업모악랜드 - 모악썰매장김제시 금산면 모악로 476-39063-548-4401
6566승마장업인디안승마공원김제시 만경읍 장산2길 117-26063-544-3888
6667승마장업대원승마클럽김제시 용지면 콩쥐팥쥐로 779-35063-548-9090
6768승마장업전북말산업복합센터김제시 용지면 금백로 571-39063-547-3549