Overview

Dataset statistics

Number of variables7
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory59.4 B

Variable types

Categorical3
Text3
Numeric1

Dataset

Description동대문구의 골프연습장업 관련된 자료입니다. 관내 골프연습장업의 상호명, 주소, 전화번호 등의 정보를 담고 있습니다.
URLhttps://www.data.go.kr/data/15113516/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2023-12-12 19:19:04.942434
Analysis finished2023-12-12 19:19:05.607777
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
골프연습장업
44 
가상체험 체육시설업
10 

Length

Max length10
Median length6
Mean length6.7407407
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
골프연습장업 44
81.5%
가상체험 체육시설업 10
 
18.5%

Length

2023-12-13T04:19:05.683970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:19:05.795468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
골프연습장업 44
68.8%
가상체험 10
 
15.6%
체육시설업 10
 
15.6%

상호
Text

Distinct48
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-13T04:19:06.049342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length7.962963
Min length3

Characters and Unicode

Total characters430
Distinct characters111
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)79.6%

Sample

1st row필드로 골프연습장
2nd row동대문힐스포파크
3rd row크린골프연습장
4th row주)더해치 에이스골프
5th rowOK 스크린 골프연습장
ValueCountFrequency (%)
스크린 4
 
5.0%
골프 4
 
5.0%
엠제이골프 3
 
3.8%
골프존 3
 
3.8%
골프존파크 3
 
3.8%
골프연습장 3
 
3.8%
ed골프스튜디오 2
 
2.5%
포스빌골프 2
 
2.5%
서울시버스노동조합 2
 
2.5%
복지사업부 2
 
2.5%
Other values (50) 52
65.0%
2023-12-13T04:19:06.447946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
프 47
 
10.9%
골 46
 
10.7%
스 33
 
7.7%
크 26
 
6.0%
26
 
6.0%
린 19
 
4.4%
이 10
 
2.3%
오 9
 
2.1%
장 7
 
1.6%
존 7
 
1.6%
Other values (101) 200
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 383
89.1%
Space Separator 26
 
6.0%
Uppercase Letter 11
 
2.6%
Decimal Number 5
 
1.2%
Close Punctuation 3
 
0.7%
Open Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
프 47
 
12.3%
골 46
 
12.0%
스 33
 
8.6%
크 26
 
6.8%
린 19
 
5.0%
이 10
 
2.6%
오 9
 
2.3%
장 7
 
1.8%
존 7
 
1.8%
파 6
 
1.6%
Other values (86) 173
45.2%
Uppercase Letter
ValueCountFrequency (%)
E 3
27.3%
D 2
18.2%
J 1
 
9.1%
W 1
 
9.1%
M 1
 
9.1%
O 1
 
9.1%
K 1
 
9.1%
G 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
1 1
20.0%
3 1
20.0%
4 1
20.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 383
89.1%
Common 36
 
8.4%
Latin 11
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
프 47
 
12.3%
골 46
 
12.0%
스 33
 
8.6%
크 26
 
6.8%
린 19
 
5.0%
이 10
 
2.6%
오 9
 
2.3%
장 7
 
1.8%
존 7
 
1.8%
파 6
 
1.6%
Other values (86) 173
45.2%
Latin
ValueCountFrequency (%)
E 3
27.3%
D 2
18.2%
J 1
 
9.1%
W 1
 
9.1%
M 1
 
9.1%
O 1
 
9.1%
K 1
 
9.1%
G 1
 
9.1%
Common
ValueCountFrequency (%)
26
72.2%
) 3
 
8.3%
( 2
 
5.6%
2 2
 
5.6%
1 1
 
2.8%
3 1
 
2.8%
4 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 383
89.1%
ASCII 47
 
10.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
프 47
 
12.3%
골 46
 
12.0%
스 33
 
8.6%
크 26
 
6.8%
린 19
 
5.0%
이 10
 
2.6%
오 9
 
2.3%
장 7
 
1.8%
존 7
 
1.8%
파 6
 
1.6%
Other values (86) 173
45.2%
ASCII
ValueCountFrequency (%)
26
55.3%
) 3
 
6.4%
E 3
 
6.4%
D 2
 
4.3%
( 2
 
4.3%
2 2
 
4.3%
J 1
 
2.1%
W 1
 
2.1%
1 1
 
2.1%
3 1
 
2.1%
Other values (5) 5
 
10.6%

우편번호
Real number (ℝ)

Distinct36
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2556.2963
Minimum2436
Maximum2645
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-13T04:19:06.912441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2436
5-th percentile2436
Q12523
median2566
Q32621.5
95-th percentile2639
Maximum2645
Range209
Interquartile range (IQR)98.5

Descriptive statistics

Standard deviation65.71081
Coefficient of variation (CV)0.025705475
Kurtosis-0.82412717
Mean2556.2963
Median Absolute Deviation (MAD)50.5
Skewness-0.42244432
Sum138040
Variance4317.9106
MonotonicityNot monotonic
2023-12-13T04:19:07.048727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2638 4
 
7.4%
2436 4
 
7.4%
2566 3
 
5.6%
2532 3
 
5.6%
2582 3
 
5.6%
2624 2
 
3.7%
2639 2
 
3.7%
2535 2
 
3.7%
2523 2
 
3.7%
2541 2
 
3.7%
Other values (26) 27
50.0%
ValueCountFrequency (%)
2436 4
7.4%
2439 1
 
1.9%
2440 1
 
1.9%
2446 1
 
1.9%
2461 1
 
1.9%
2479 1
 
1.9%
2496 1
 
1.9%
2509 1
 
1.9%
2511 1
 
1.9%
2516 1
 
1.9%
ValueCountFrequency (%)
2645 1
 
1.9%
2641 1
 
1.9%
2639 2
3.7%
2638 4
7.4%
2633 1
 
1.9%
2631 1
 
1.9%
2629 1
 
1.9%
2624 2
3.7%
2623 1
 
1.9%
2617 1
 
1.9%

도로명 주소
Text

Distinct42
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-13T04:19:07.282786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length18.611111
Min length16

Characters and Unicode

Total characters1005
Distinct characters52
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

Unique33 ?
Unique (%)61.1%

Sample

1st row서울특별시 동대문구 망우로16길 20
2nd row서울특별시 동대문구 답십리로 209
3rd row서울특별시 동대문구 한천로 264
4th row서울특별시 동대문구 장한로24길 46
5th row서울특별시 동대문구 장한로18길 82-9
ValueCountFrequency (%)
서울특별시 54
25.0%
동대문구 54
25.0%
사가정로 6
 
2.8%
한천로 5
 
2.3%
망우로 5
 
2.3%
장한로 5
 
2.3%
장안벚꽃로 4
 
1.9%
107 4
 
1.9%
답십리로 4
 
1.9%
왕산로 4
 
1.9%
Other values (54) 71
32.9%
2023-12-13T04:19:07.651171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
16.1%
대 58
 
5.8%
문 57
 
5.7%
시 56
 
5.6%
서 55
 
5.5%
울 55
 
5.5%
로 54
 
5.4%
특 54
 
5.4%
별 54
 
5.4%
동 54
 
5.4%
Other values (42) 346
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 688
68.5%
Space Separator 162
 
16.1%
Decimal Number 153
 
15.2%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 58
8.4%
문 57
8.3%
시 56
8.1%
서 55
8.0%
울 55
8.0%
로 54
 
7.8%
특 54
 
7.8%
별 54
 
7.8%
동 54
 
7.8%
구 54
 
7.8%
Other values (30) 137
19.9%
Decimal Number
ValueCountFrequency (%)
1 30
19.6%
2 25
16.3%
0 19
12.4%
4 17
11.1%
3 15
9.8%
8 11
 
7.2%
6 10
 
6.5%
9 10
 
6.5%
7 9
 
5.9%
5 7
 
4.6%
Space Separator
ValueCountFrequency (%)
162
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 688
68.5%
Common 317
31.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 58
8.4%
문 57
8.3%
시 56
8.1%
서 55
8.0%
울 55
8.0%
로 54
 
7.8%
특 54
 
7.8%
별 54
 
7.8%
동 54
 
7.8%
구 54
 
7.8%
Other values (30) 137
19.9%
Common
ValueCountFrequency (%)
162
51.1%
1 30
 
9.5%
2 25
 
7.9%
0 19
 
6.0%
4 17
 
5.4%
3 15
 
4.7%
8 11
 
3.5%
6 10
 
3.2%
9 10
 
3.2%
7 9
 
2.8%
Other values (2) 9
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 688
68.5%
ASCII 317
31.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
51.1%
1 30
 
9.5%
2 25
 
7.9%
0 19
 
6.0%
4 17
 
5.4%
3 15
 
4.7%
8 11
 
3.5%
6 10
 
3.2%
9 10
 
3.2%
7 9
 
2.8%
Other values (2) 9
 
2.8%
Hangul
ValueCountFrequency (%)
대 58
8.4%
문 57
8.3%
시 56
8.1%
서 55
8.0%
울 55
8.0%
로 54
 
7.8%
특 54
 
7.8%
별 54
 
7.8%
동 54
 
7.8%
구 54
 
7.8%
Other values (30) 137
19.9%

전화번호
Text

Distinct27
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-13T04:19:07.839533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.833333
Min length11

Characters and Unicode

Total characters639
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

Unique26 ?
Unique (%)48.1%

Sample

1st row02-2216-3003
2nd row02-2214-5200
3rd row02-2245-5558
4th row02-0000-0000
5th row02-0000-0000
ValueCountFrequency (%)
02-0000-0000 28
51.9%
02-2216-3003 1
 
1.9%
02-2216-0010 1
 
1.9%
02-2212-1875 1
 
1.9%
02-967-7006 1
 
1.9%
02-962-0753 1
 
1.9%
02-2217-0787 1
 
1.9%
02-774-5444 1
 
1.9%
02-928-4535 1
 
1.9%
02-929-8278 1
 
1.9%
Other values (17) 17
31.5%
2023-12-13T04:19:08.178645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 306
47.9%
- 108
 
16.9%
2 97
 
15.2%
7 24
 
3.8%
4 22
 
3.4%
1 17
 
2.7%
5 16
 
2.5%
9 16
 
2.5%
6 13
 
2.0%
8 11
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 531
83.1%
Dash Punctuation 108
 
16.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 306
57.6%
2 97
 
18.3%
7 24
 
4.5%
4 22
 
4.1%
1 17
 
3.2%
5 16
 
3.0%
9 16
 
3.0%
6 13
 
2.4%
8 11
 
2.1%
3 9
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 639
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 306
47.9%
- 108
 
16.9%
2 97
 
15.2%
7 24
 
3.8%
4 22
 
3.4%
1 17
 
2.7%
5 16
 
2.5%
9 16
 
2.5%
6 13
 
2.0%
8 11
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 639
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 306
47.9%
- 108
 
16.9%
2 97
 
15.2%
7 24
 
3.8%
4 22
 
3.4%
1 17
 
2.7%
5 16
 
2.5%
9 16
 
2.5%
6 13
 
2.0%
8 11
 
1.7%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
서울특별시 동대문구청
54 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 동대문구청
2nd row서울특별시 동대문구청
3rd row서울특별시 동대문구청
4th row서울특별시 동대문구청
5th row서울특별시 동대문구청

Common Values

ValueCountFrequency (%)
서울특별시 동대문구청 54
100.0%

Length

2023-12-13T04:19:08.316084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:19:08.406202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 54
50.0%
동대문구청 54
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-04-25
54 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-04-25
2nd row2023-04-25
3rd row2023-04-25
4th row2023-04-25
5th row2023-04-25

Common Values

ValueCountFrequency (%)
2023-04-25 54
100.0%

Length

2023-12-13T04:19:08.502721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:19:08.607024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-04-25 54
100.0%

Interactions

2023-12-13T04:19:05.312319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:19:08.662949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종상호우편번호도로명 주소전화번호
업종1.0000.0000.0000.0000.000
상호0.0001.0000.7250.9940.992
우편번호0.0000.7251.0001.0000.609
도로명 주소0.0000.9941.0001.0000.970
전화번호0.0000.9920.6090.9701.000
2023-12-13T04:19:08.758254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호업종
우편번호1.0000.000
업종0.0001.000

Missing values

2023-12-13T04:19:05.431809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:19:05.553354image/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

업종상호우편번호도로명 주소전화번호관리기관명데이터기준일자
0골프연습장업필드로 골프연습장2496서울특별시 동대문구 망우로16길 2002-2216-3003서울특별시 동대문구청2023-04-25
1골프연습장업동대문힐스포파크2535서울특별시 동대문구 답십리로 20902-2214-5200서울특별시 동대문구청2023-04-25
2골프연습장업크린골프연습장2511서울특별시 동대문구 한천로 26402-2245-5558서울특별시 동대문구청2023-04-25
3골프연습장업주)더해치 에이스골프2639서울특별시 동대문구 장한로24길 4602-0000-0000서울특별시 동대문구청2023-04-25
4골프연습장업OK 스크린 골프연습장2641서울특별시 동대문구 장한로18길 82-902-0000-0000서울특별시 동대문구청2023-04-25
5골프연습장업서울시버스노동조합 복지사업부2523서울특별시 동대문구 장한로28가길 4502-2216-0252서울특별시 동대문구청2023-04-25
6골프연습장업드림 스크린 골프2578서울특별시 동대문구 무학로 19702-927-9385서울특별시 동대문구청2023-04-25
7골프연습장업언더파스크린골프2532서울특별시 동대문구 사가정로 14802-432-4024서울특별시 동대문구청2023-04-25
8골프연습장업조이스크린골프2594서울특별시 동대문구 서울시립대로 3602-0000-0000서울특별시 동대문구청2023-04-25
9골프연습장업타이거골프클럽2524서울특별시 동대문구 답십리로 30902-0000-0000서울특별시 동대문구청2023-04-25
업종상호우편번호도로명 주소전화번호관리기관명데이터기준일자
44가상체험 체육시설업오름 스크린 골프2541서울특별시 동대문구 사가정로 8002-0000-0000서울특별시 동대문구청2023-04-25
45가상체험 체육시설업ED골프스튜디오2436서울특별시 동대문구 망우로 10102-2216-7120서울특별시 동대문구청2023-04-25
46가상체험 체육시설업포스빌골프2566서울특별시 동대문구 왕산로 12202-0000-0000서울특별시 동대문구청2023-04-25
47가상체험 체육시설업골프존파크 장안온천점2638서울특별시 동대문구 장안벚꽃로 10702-0000-0000서울특별시 동대문구청2023-04-25
48가상체험 체육시설업골프존2638서울특별시 동대문구 장안벚꽃로 10702-0000-0000서울특별시 동대문구청2023-04-25
49가상체험 체육시설업휘경1232436서울특별시 동대문구 망우로 12302-0000-0000서울특별시 동대문구청2023-04-25
50가상체험 체육시설업서울시버스노동조합 복지사업부2523서울특별시 동대문구 장한로28가길 4502-0000-0000서울특별시 동대문구청2023-04-25
51가상체험 체육시설업(주)더부킹골프아카데미2633서울특별시 동대문구 천호대로 40502-0000-0000서울특별시 동대문구청2023-04-25
52가상체험 체육시설업하경 골프스튜디오2540서울특별시 동대문구 전농로11길 17-402-0000-0000서울특별시 동대문구청2023-04-25
53가상체험 체육시설업골프스튜디오 곰2530서울특별시 동대문구 장한로 13702-0000-0000서울특별시 동대문구청2023-04-25