Overview

Dataset statistics

Number of variables5
Number of observations349
Missing cells150
Missing cells (%)8.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.1 KiB
Average record size in memory41.4 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description인천광역시 계양구 관내 체육시설업 현황에 대한 데이터로, 연번, 업종, 상호, 시설 주소(도로명), 전화번호 등을 제공합니다.
Author인천광역시 계양구
URLhttps://www.data.go.kr/data/15038926/fileData.do

Alerts

연번 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 연번High correlation
시설전화번호 has 150 (43.0%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-16 04:14:45.111573
Analysis finished2024-03-16 04:14:45.860077
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct349
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean175
Minimum1
Maximum349
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-03-16T13:14:45.964122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.4
Q188
median175
Q3262
95-th percentile331.6
Maximum349
Range348
Interquartile range (IQR)174

Descriptive statistics

Standard deviation100.89186
Coefficient of variation (CV)0.57652489
Kurtosis-1.2
Mean175
Median Absolute Deviation (MAD)87
Skewness0
Sum61075
Variance10179.167
MonotonicityStrictly increasing
2024-03-16T13:14:46.133090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
231 1
 
0.3%
239 1
 
0.3%
238 1
 
0.3%
237 1
 
0.3%
236 1
 
0.3%
235 1
 
0.3%
234 1
 
0.3%
233 1
 
0.3%
232 1
 
0.3%
Other values (339) 339
97.1%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
349 1
0.3%
348 1
0.3%
347 1
0.3%
346 1
0.3%
345 1
0.3%
344 1
0.3%
343 1
0.3%
342 1
0.3%
341 1
0.3%
340 1
0.3%

업종
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
당구장업
106 
체육도장업
98 
체력단련장업
67 
골프연습장업
44 
가상체험 체육시설업
15 
Other values (4)
19 

Length

Max length10
Median length6
Mean length5.2206304
Min length4

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
당구장업 106
30.4%
체육도장업 98
28.1%
체력단련장업 67
19.2%
골프연습장업 44
12.6%
가상체험 체육시설업 15
 
4.3%
체육교습업 14
 
4.0%
수영장업 3
 
0.9%
썰매장업 1
 
0.3%
인공암벽장업 1
 
0.3%

Length

2024-03-16T13:14:46.360359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T13:14:46.885072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당구장업 106
29.1%
체육도장업 98
26.9%
체력단련장업 67
18.4%
골프연습장업 44
12.1%
가상체험 15
 
4.1%
체육시설업 15
 
4.1%
체육교습업 14
 
3.8%
수영장업 3
 
0.8%
썰매장업 1
 
0.3%
인공암벽장업 1
 
0.3%

상호
Text

Distinct336
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-03-16T13:14:47.270417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length7.6590258
Min length2

Characters and Unicode

Total characters2673
Distinct characters351
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique328 ?
Unique (%)94.0%

Sample

1st row진명스포아트
2nd row블루엔키즈
3rd row하나로휘트니스힐링교육센터
4th row미동인천대태권도체육관
5th row용인대석사계산체육도장
ValueCountFrequency (%)
당구클럽 25
 
4.4%
태권도장 24
 
4.2%
당구장 18
 
3.2%
태권도 8
 
1.4%
골프존 6
 
1.1%
sbs당구장 5
 
0.9%
gym 5
 
0.9%
골프 5
 
0.9%
휘트니스 5
 
0.9%
합기도 4
 
0.7%
Other values (404) 464
81.5%
2024-03-16T13:14:47.834175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
220
 
8.2%
구 119
 
4.5%
장 113
 
4.2%
스 106
 
4.0%
당 101
 
3.8%
도 82
 
3.1%
태 69
 
2.6%
권 65
 
2.4%
프 58
 
2.2%
클 56
 
2.1%
Other values (341) 1684
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2234
83.6%
Space Separator 220
 
8.2%
Uppercase Letter 146
 
5.5%
Lowercase Letter 36
 
1.3%
Decimal Number 20
 
0.7%
Other Punctuation 6
 
0.2%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Math Symbol 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 119
 
5.3%
장 113
 
5.1%
스 106
 
4.7%
당 101
 
4.5%
도 82
 
3.7%
태 69
 
3.1%
권 65
 
2.9%
프 58
 
2.6%
클 56
 
2.5%
럽 55
 
2.5%
Other values (287) 1410
63.1%
Uppercase Letter
ValueCountFrequency (%)
S 22
15.1%
T 20
13.7%
G 15
10.3%
P 12
 
8.2%
M 11
 
7.5%
B 9
 
6.2%
Y 8
 
5.5%
O 7
 
4.8%
J 6
 
4.1%
C 5
 
3.4%
Other values (12) 31
21.2%
Lowercase Letter
ValueCountFrequency (%)
o 6
16.7%
m 4
11.1%
u 4
11.1%
i 3
8.3%
t 3
8.3%
s 2
 
5.6%
d 2
 
5.6%
n 2
 
5.6%
g 2
 
5.6%
r 1
 
2.8%
Other values (7) 7
19.4%
Decimal Number
ValueCountFrequency (%)
2 4
20.0%
4 4
20.0%
1 4
20.0%
0 3
15.0%
3 2
10.0%
7 2
10.0%
9 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
& 4
66.7%
: 1
 
16.7%
. 1
 
16.7%
Space Separator
ValueCountFrequency (%)
220
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2234
83.6%
Common 257
 
9.6%
Latin 182
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 119
 
5.3%
장 113
 
5.1%
스 106
 
4.7%
당 101
 
4.5%
도 82
 
3.7%
태 69
 
3.1%
권 65
 
2.9%
프 58
 
2.6%
클 56
 
2.5%
럽 55
 
2.5%
Other values (287) 1410
63.1%
Latin
ValueCountFrequency (%)
S 22
 
12.1%
T 20
 
11.0%
G 15
 
8.2%
P 12
 
6.6%
M 11
 
6.0%
B 9
 
4.9%
Y 8
 
4.4%
O 7
 
3.8%
J 6
 
3.3%
o 6
 
3.3%
Other values (29) 66
36.3%
Common
ValueCountFrequency (%)
220
85.6%
) 4
 
1.6%
( 4
 
1.6%
2 4
 
1.6%
4 4
 
1.6%
& 4
 
1.6%
1 4
 
1.6%
0 3
 
1.2%
3 2
 
0.8%
+ 2
 
0.8%
Other values (5) 6
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2234
83.6%
ASCII 439
 
16.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
220
50.1%
S 22
 
5.0%
T 20
 
4.6%
G 15
 
3.4%
P 12
 
2.7%
M 11
 
2.5%
B 9
 
2.1%
Y 8
 
1.8%
O 7
 
1.6%
J 6
 
1.4%
Other values (44) 109
24.8%
Hangul
ValueCountFrequency (%)
구 119
 
5.3%
장 113
 
5.1%
스 106
 
4.7%
당 101
 
4.5%
도 82
 
3.7%
태 69
 
3.1%
권 65
 
2.9%
프 58
 
2.6%
클 56
 
2.5%
럽 55
 
2.5%
Other values (287) 1410
63.1%

시설주소(도로명)
Text

Distinct344
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-03-16T13:14:48.227550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length45
Mean length31.82235
Min length22

Characters and Unicode

Total characters11106
Distinct characters208
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

Unique339 ?
Unique (%)97.1%

Sample

1st row인천광역시 계양구 계양대로 37, 지2층 (작전동, 진명스포아트)
2nd row인천광역시 계양구 용종로 23, 은행마을태산아파트 상가동 지층 B01,B19호 (계산동)
3rd row인천광역시 계양구 안남로 612, 경인교육대학교 부설초등학교 (효성동)
4th row인천광역시 계양구 주부토로 368 (작전동)
5th row인천광역시 계양구 계양대로163번길 14-1 (계산동)
ValueCountFrequency (%)
인천광역시 349
 
15.6%
계양구 349
 
15.6%
계산동 101
 
4.5%
작전동 92
 
4.1%
2층 65
 
2.9%
3층 62
 
2.8%
효성동 56
 
2.5%
4층 39
 
1.7%
장제로 37
 
1.7%
용종동 23
 
1.0%
Other values (480) 1061
47.5%
2024-03-16T13:14:48.785280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1885
 
17.0%
계 530
 
4.8%
양 437
 
3.9%
동 407
 
3.7%
, 380
 
3.4%
인 355
 
3.2%
시 352
 
3.2%
천 352
 
3.2%
광 351
 
3.2%
역 350
 
3.2%
Other values (198) 5707
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6368
57.3%
Space Separator 1885
 
17.0%
Decimal Number 1696
 
15.3%
Other Punctuation 384
 
3.5%
Open Punctuation 350
 
3.2%
Close Punctuation 350
 
3.2%
Uppercase Letter 44
 
0.4%
Dash Punctuation 15
 
0.1%
Math Symbol 14
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 530
 
8.3%
양 437
 
6.9%
동 407
 
6.4%
인 355
 
5.6%
시 352
 
5.5%
천 352
 
5.5%
광 351
 
5.5%
역 350
 
5.5%
구 349
 
5.5%
로 345
 
5.4%
Other values (165) 2540
39.9%
Uppercase Letter
ValueCountFrequency (%)
B 14
31.8%
S 4
 
9.1%
C 3
 
6.8%
E 3
 
6.8%
P 3
 
6.8%
O 3
 
6.8%
M 2
 
4.5%
H 2
 
4.5%
U 2
 
4.5%
L 2
 
4.5%
Other values (5) 6
13.6%
Decimal Number
ValueCountFrequency (%)
1 344
20.3%
2 242
14.3%
3 213
12.6%
0 191
11.3%
4 172
10.1%
5 163
9.6%
7 134
 
7.9%
6 85
 
5.0%
9 83
 
4.9%
8 69
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 380
99.0%
. 3
 
0.8%
& 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1885
100.0%
Open Punctuation
ValueCountFrequency (%)
( 350
100.0%
Close Punctuation
ValueCountFrequency (%)
) 350
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6368
57.3%
Common 4694
42.3%
Latin 44
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 530
 
8.3%
양 437
 
6.9%
동 407
 
6.4%
인 355
 
5.6%
시 352
 
5.5%
천 352
 
5.5%
광 351
 
5.5%
역 350
 
5.5%
구 349
 
5.5%
로 345
 
5.4%
Other values (165) 2540
39.9%
Common
ValueCountFrequency (%)
1885
40.2%
, 380
 
8.1%
( 350
 
7.5%
) 350
 
7.5%
1 344
 
7.3%
2 242
 
5.2%
3 213
 
4.5%
0 191
 
4.1%
4 172
 
3.7%
5 163
 
3.5%
Other values (8) 404
 
8.6%
Latin
ValueCountFrequency (%)
B 14
31.8%
S 4
 
9.1%
C 3
 
6.8%
E 3
 
6.8%
P 3
 
6.8%
O 3
 
6.8%
M 2
 
4.5%
H 2
 
4.5%
U 2
 
4.5%
L 2
 
4.5%
Other values (5) 6
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6368
57.3%
ASCII 4738
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1885
39.8%
, 380
 
8.0%
( 350
 
7.4%
) 350
 
7.4%
1 344
 
7.3%
2 242
 
5.1%
3 213
 
4.5%
0 191
 
4.0%
4 172
 
3.6%
5 163
 
3.4%
Other values (23) 448
 
9.5%
Hangul
ValueCountFrequency (%)
계 530
 
8.3%
양 437
 
6.9%
동 407
 
6.4%
인 355
 
5.6%
시 352
 
5.5%
천 352
 
5.5%
광 351
 
5.5%
역 350
 
5.5%
구 349
 
5.5%
로 345
 
5.4%
Other values (165) 2540
39.9%

시설전화번호
Text

MISSING 

Distinct196
Distinct (%)98.5%
Missing150
Missing (%)43.0%
Memory size2.9 KiB
2024-03-16T13:14:49.145906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.98995
Min length9

Characters and Unicode

Total characters2386
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

Unique194 ?
Unique (%)97.5%

Sample

1st row032-554-9500
2nd row032-710-1213
3rd row032-556-2571
4th row032-546-7076
5th row032-541-4990
ValueCountFrequency (%)
032-554-9500 3
 
1.5%
032-252-6000 2
 
1.0%
032-541-6500 1
 
0.5%
032-545-5747 1
 
0.5%
032-542-2463 1
 
0.5%
070-4129-0979 1
 
0.5%
032-543-5010 1
 
0.5%
032-551-4211 1
 
0.5%
032-555-2584 1
 
0.5%
032-555-1147 1
 
0.5%
Other values (186) 186
93.5%
2024-03-16T13:14:50.587248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 404
16.9%
- 397
16.6%
0 339
14.2%
3 309
13.0%
2 295
12.4%
4 186
7.8%
7 106
 
4.4%
9 103
 
4.3%
1 100
 
4.2%
6 81
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1989
83.4%
Dash Punctuation 397
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 404
20.3%
0 339
17.0%
3 309
15.5%
2 295
14.8%
4 186
9.4%
7 106
 
5.3%
9 103
 
5.2%
1 100
 
5.0%
6 81
 
4.1%
8 66
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 397
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2386
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 404
16.9%
- 397
16.6%
0 339
14.2%
3 309
13.0%
2 295
12.4%
4 186
7.8%
7 106
 
4.4%
9 103
 
4.3%
1 100
 
4.2%
6 81
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2386
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 404
16.9%
- 397
16.6%
0 339
14.2%
3 309
13.0%
2 295
12.4%
4 186
7.8%
7 106
 
4.4%
9 103
 
4.3%
1 100
 
4.2%
6 81
 
3.4%

Interactions

2024-03-16T13:14:45.479659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T13:14:50.869546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.879
업종0.8791.000
2024-03-16T13:14:51.161355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.655
업종0.6551.000

Missing values

2024-03-16T13:14:45.644503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:14:45.798816image/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)시설전화번호
01수영장업진명스포아트인천광역시 계양구 계양대로 37, 지2층 (작전동, 진명스포아트)032-554-9500
12수영장업블루엔키즈인천광역시 계양구 용종로 23, 은행마을태산아파트 상가동 지층 B01,B19호 (계산동)032-710-1213
23수영장업하나로휘트니스힐링교육센터인천광역시 계양구 안남로 612, 경인교육대학교 부설초등학교 (효성동)032-556-2571
34체육도장업미동인천대태권도체육관인천광역시 계양구 주부토로 368 (작전동)032-546-7076
45체육도장업용인대석사계산체육도장인천광역시 계양구 계양대로163번길 14-1 (계산동)032-541-4990
56체육도장업비호체육관인천광역시 계양구 안남로573번길 21 (효성동)032-546-3811
67체육도장업고려체육도장인천광역시 계양구 안남로 491 (효성동)032-547-7205
78체육도장업한국태권도아카데미인천광역시 계양구 까치말로 20 (작전동)032-542-9909
89체육도장업최성 태권도인천광역시 계양구 효서로 380, 신현대타운 301,302,309호 (작전동)<NA>
910체육도장업영웅백호 태권도장인천광역시 계양구 장제로767번길 33, 3층 (계산동)032-541-4346
연번업종상호시설주소(도로명)시설전화번호
339340체육교습업씨엔에스 농구교실인천광역시 계양구 선주로54번길 12, 4동 (선주지동)<NA>
340341체육교습업계양구 리틀야구단인천광역시 계양구 계산로 18, 지하1층 (계산동)<NA>
341342체육교습업강서구B리틀야구단인천광역시 계양구 벌말로551번길 5-3, 2층 (상야동)<NA>
342343체육교습업계양구유소년야구단인천광역시 계양구 장제로 851, 지하1층 (임학동)<NA>
343344체육교습업김포시 리틀야구단인천광역시 계양구 이화북로 27 (이화동)<NA>
344345체육교습업계양축구센터인천광역시 계양구 주부토로532번길 43, 301호 (계산동)<NA>
345346체육교습업씨앤탑 아카데미인천광역시 계양구 벌말로573번길 8-1 (상야동)<NA>
346347체육교습업CP sports인천광역시 계양구 이화남로136번길 9, 1동 (이화동)<NA>
347348체육교습업점프윙스 줄넘기클럽인천광역시 계양구 길마로 67, 2층 (효성동)<NA>
348349인공암벽장업인천계양클라이밍센터인천광역시 계양구 경명대로 1146, 4층 (계산동)032-554-5014