Overview

Dataset statistics

Number of variables5
Number of observations109
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory42.2 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description대전광역시 동구 관내의 야외운동기구 설치현황으로서, 기구가 위치하고 있는 상세주소 및 설치기구 등의 항목을 포함하고 있습니다.
Author대전광역시 동구
URLhttps://www.data.go.kr/data/15060864/fileData.do

Alerts

연번 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:45:06.272991
Analysis finished2023-12-12 20:45:06.853087
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55
Minimum1
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T05:45:06.944672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.4
Q128
median55
Q382
95-th percentile103.6
Maximum109
Range108
Interquartile range (IQR)54

Descriptive statistics

Standard deviation31.609598
Coefficient of variation (CV)0.57471996
Kurtosis-1.2
Mean55
Median Absolute Deviation (MAD)27
Skewness0
Sum5995
Variance999.16667
MonotonicityStrictly increasing
2023-12-13T05:45:07.159938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
70 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%

행정동
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size1004.0 B
산내동
14 
효동
11 
대청동
10 
용전동
10 
판암1동
Other values (11)
56 

Length

Max length4
Median length3
Mean length3.0366972
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가양1동
2nd row가양1동
3rd row가양1동
4th row가양2동
5th row가양2동

Common Values

ValueCountFrequency (%)
산내동 14
12.8%
효동 11
10.1%
대청동 10
 
9.2%
용전동 10
 
9.2%
판암1동 8
 
7.3%
신인동 7
 
6.4%
홍도동 7
 
6.4%
대동 6
 
5.5%
삼성동 6
 
5.5%
가양2동 5
 
4.6%
Other values (6) 25
22.9%

Length

2023-12-13T05:45:07.343323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
산내동 14
12.8%
효동 11
10.1%
대청동 10
 
9.2%
용전동 10
 
9.2%
판암1동 8
 
7.3%
신인동 7
 
6.4%
홍도동 7
 
6.4%
대동 6
 
5.5%
삼성동 6
 
5.5%
가양2동 5
 
4.6%
Other values (6) 25
22.9%

시설명
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-13T05:45:07.603614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length11.036697
Min length4

Characters and Unicode

Total characters1203
Distinct characters191
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st row가양초등학교
2nd row동부갱이경로당
3rd row아침마을아파트 103동 앞
4th row가양큰솔아파트
5th row남간정사 뒤(등산로)
ValueCountFrequency (%)
19
 
8.2%
8
 
3.4%
6
 
2.6%
효동현대아파트 4
 
1.7%
103동 4
 
1.7%
101동 4
 
1.7%
104동 3
 
1.3%
어진마을아파트 3
 
1.3%
108동 3
 
1.3%
105동 3
 
1.3%
Other values (153) 175
75.4%
2023-12-13T05:45:08.165171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
123
 
10.2%
78
 
6.5%
54
 
4.5%
49
 
4.1%
49
 
4.1%
1 44
 
3.7%
0 35
 
2.9%
( 33
 
2.7%
) 33
 
2.7%
23
 
1.9%
Other values (181) 682
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 858
71.3%
Decimal Number 152
 
12.6%
Space Separator 123
 
10.2%
Open Punctuation 33
 
2.7%
Close Punctuation 33
 
2.7%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
78
 
9.1%
54
 
6.3%
49
 
5.7%
49
 
5.7%
23
 
2.7%
18
 
2.1%
17
 
2.0%
16
 
1.9%
15
 
1.7%
14
 
1.6%
Other values (167) 525
61.2%
Decimal Number
ValueCountFrequency (%)
1 44
28.9%
0 35
23.0%
2 17
 
11.2%
3 16
 
10.5%
4 12
 
7.9%
5 7
 
4.6%
6 7
 
4.6%
8 5
 
3.3%
9 5
 
3.3%
7 4
 
2.6%
Space Separator
ValueCountFrequency (%)
123
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 857
71.2%
Common 345
28.7%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
78
 
9.1%
54
 
6.3%
49
 
5.7%
49
 
5.7%
23
 
2.7%
18
 
2.1%
17
 
2.0%
16
 
1.9%
15
 
1.8%
14
 
1.6%
Other values (166) 524
61.1%
Common
ValueCountFrequency (%)
123
35.7%
1 44
 
12.8%
0 35
 
10.1%
( 33
 
9.6%
) 33
 
9.6%
2 17
 
4.9%
3 16
 
4.6%
4 12
 
3.5%
5 7
 
2.0%
6 7
 
2.0%
Other values (4) 18
 
5.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 857
71.2%
ASCII 345
28.7%
CJK 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
123
35.7%
1 44
 
12.8%
0 35
 
10.1%
( 33
 
9.6%
) 33
 
9.6%
2 17
 
4.9%
3 16
 
4.6%
4 12
 
3.5%
5 7
 
2.0%
6 7
 
2.0%
Other values (4) 18
 
5.2%
Hangul
ValueCountFrequency (%)
78
 
9.1%
54
 
6.3%
49
 
5.7%
49
 
5.7%
23
 
2.7%
18
 
2.1%
17
 
2.0%
16
 
1.9%
15
 
1.8%
14
 
1.6%
Other values (166) 524
61.1%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct99
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-13T05:45:08.483194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length17.944954
Min length14

Characters and Unicode

Total characters1956
Distinct characters80
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

Unique92 ?
Unique (%)84.4%

Sample

1st row대전광역시 동구 가양로 61
2nd row대전광역시 동구 가양남로13번길 57
3rd row대전광역시 동구 우암로 192
4th row대전광역시 동구 충정로18번길 60
5th row대전광역시 동구 가양동4-15
ValueCountFrequency (%)
대전광역시 110
26.2%
동구 109
26.0%
대전로 8
 
1.9%
계족로 5
 
1.2%
646 4
 
1.0%
판암동 4
 
1.0%
삼성동 4
 
1.0%
충정로 3
 
0.7%
삼괴동 3
 
0.7%
19 3
 
0.7%
Other values (145) 167
39.8%
2023-12-13T05:45:08.940814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
312
16.0%
159
 
8.1%
136
 
7.0%
125
 
6.4%
112
 
5.7%
110
 
5.6%
110
 
5.6%
110
 
5.6%
75
 
3.8%
1 74
 
3.8%
Other values (70) 633
32.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1188
60.7%
Decimal Number 417
 
21.3%
Space Separator 312
 
16.0%
Dash Punctuation 39
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
159
13.4%
136
11.4%
125
10.5%
112
9.4%
110
9.3%
110
9.3%
110
9.3%
75
6.3%
36
 
3.0%
36
 
3.0%
Other values (58) 179
15.1%
Decimal Number
ValueCountFrequency (%)
1 74
17.7%
3 48
11.5%
4 48
11.5%
5 47
11.3%
2 47
11.3%
6 37
8.9%
7 36
8.6%
9 28
 
6.7%
0 26
 
6.2%
8 26
 
6.2%
Space Separator
ValueCountFrequency (%)
312
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1188
60.7%
Common 768
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
159
13.4%
136
11.4%
125
10.5%
112
9.4%
110
9.3%
110
9.3%
110
9.3%
75
6.3%
36
 
3.0%
36
 
3.0%
Other values (58) 179
15.1%
Common
ValueCountFrequency (%)
312
40.6%
1 74
 
9.6%
3 48
 
6.2%
4 48
 
6.2%
5 47
 
6.1%
2 47
 
6.1%
- 39
 
5.1%
6 37
 
4.8%
7 36
 
4.7%
9 28
 
3.6%
Other values (2) 52
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1188
60.7%
ASCII 768
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
312
40.6%
1 74
 
9.6%
3 48
 
6.2%
4 48
 
6.2%
5 47
 
6.1%
2 47
 
6.1%
- 39
 
5.1%
6 37
 
4.8%
7 36
 
4.7%
9 28
 
3.6%
Other values (2) 52
 
6.8%
Hangul
ValueCountFrequency (%)
159
13.4%
136
11.4%
125
10.5%
112
9.4%
110
9.3%
110
9.3%
110
9.3%
75
6.3%
36
 
3.0%
36
 
3.0%
Other values (58) 179
15.1%
Distinct108
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-13T05:45:09.195708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length26.293578
Min length8

Characters and Unicode

Total characters2866
Distinct characters123
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

Unique107 ?
Unique (%)98.2%

Sample

1st row노르딕 머신+레그 프레스+에어 서핑+에어 워킹+허리 돌리기
2nd row트위스트+마사지 롤러+워밍 쇼올더+에어서핑+
3rd row체어 웨이트+스텝 사이클+워밍암+허리 돌리기+자전거 타기
4th row워밍 쇼올더+마사지 롤러+레그 프레스+에어 워킹+
5th row에어 워킹+상체 근육 풀기+에어 서핑+트위스트+노르딕 머신
ValueCountFrequency (%)
프레스+에어 6
 
2.1%
바디 6
 
2.1%
롤러 5
 
1.7%
에어 5
 
1.7%
쇼올더+에어 5
 
1.7%
워밍 5
 
1.7%
쇼올더 5
 
1.7%
롤러+워밍 4
 
1.4%
롤러+에어 4
 
1.4%
근육 4
 
1.4%
Other values (196) 242
83.2%
2023-12-13T05:45:09.958593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 436
 
15.2%
182
 
6.4%
175
 
6.1%
126
 
4.4%
108
 
3.8%
98
 
3.4%
88
 
3.1%
84
 
2.9%
78
 
2.7%
62
 
2.2%
Other values (113) 1429
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2239
78.1%
Math Symbol 436
 
15.2%
Space Separator 182
 
6.4%
Decimal Number 3
 
0.1%
Close Punctuation 2
 
0.1%
Other Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
175
 
7.8%
126
 
5.6%
108
 
4.8%
98
 
4.4%
88
 
3.9%
84
 
3.8%
78
 
3.5%
62
 
2.8%
56
 
2.5%
51
 
2.3%
Other values (105) 1313
58.6%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
4 1
33.3%
3 1
33.3%
Math Symbol
ValueCountFrequency (%)
+ 436
100.0%
Space Separator
ValueCountFrequency (%)
182
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2239
78.1%
Common 627
 
21.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
175
 
7.8%
126
 
5.6%
108
 
4.8%
98
 
4.4%
88
 
3.9%
84
 
3.8%
78
 
3.5%
62
 
2.8%
56
 
2.5%
51
 
2.3%
Other values (105) 1313
58.6%
Common
ValueCountFrequency (%)
+ 436
69.5%
182
29.0%
) 2
 
0.3%
. 2
 
0.3%
( 2
 
0.3%
2 1
 
0.2%
4 1
 
0.2%
3 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2239
78.1%
ASCII 627
 
21.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 436
69.5%
182
29.0%
) 2
 
0.3%
. 2
 
0.3%
( 2
 
0.3%
2 1
 
0.2%
4 1
 
0.2%
3 1
 
0.2%
Hangul
ValueCountFrequency (%)
175
 
7.8%
126
 
5.6%
108
 
4.8%
98
 
4.4%
88
 
3.9%
84
 
3.8%
78
 
3.5%
62
 
2.8%
56
 
2.5%
51
 
2.3%
Other values (105) 1313
58.6%

Interactions

2023-12-13T05:45:06.590823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:45:10.064411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동상세주소
연번1.0000.9701.000
행정동0.9701.0001.000
상세주소1.0001.0001.000
2023-12-13T05:45:10.178898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동
연번1.0000.841
행정동0.8411.000

Missing values

2023-12-13T05:45:06.706821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:45:06.810283image/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

연번행정동시설명상세주소설치기구
01가양1동가양초등학교대전광역시 동구 가양로 61노르딕 머신+레그 프레스+에어 서핑+에어 워킹+허리 돌리기
12가양1동동부갱이경로당대전광역시 동구 가양남로13번길 57트위스트+마사지 롤러+워밍 쇼올더+에어서핑+
23가양1동아침마을아파트 103동 앞대전광역시 동구 우암로 192체어 웨이트+스텝 사이클+워밍암+허리 돌리기+자전거 타기
34가양2동가양큰솔아파트대전광역시 동구 충정로18번길 60워밍 쇼올더+마사지 롤러+레그 프레스+에어 워킹+
45가양2동남간정사 뒤(등산로)대전광역시 동구 가양동4-15에어 워킹+상체 근육 풀기+에어 서핑+트위스트+노르딕 머신
56가양2동대주파크빌아파트대전광역시 동구 충정로 136바디 싯업+트위스트+에어 서핑+에어 워킹+싸이클링
67가양2동조일아파트대전광역시 동구 충정로 5역기 올리기+상체 근육 풀기+싸이클링+역기 내리기+오금 펴기
78가양2동흥룡초등학교대전광역시 동구 동대전로256번길 21크로스컨트리+체어 웨이트+트윈 트위스트+레그프레스+
89대동대동천하상 (煎 롯데마트옆 하상)대전광역시 동구 대동 162-2트위스트+에어워킹+에어서핑++
910대동대전여자고등학교대전광역시 동구 용운로1번길28-37허리 돌리기+윗몸 일으키기+허리 돌리기+허리 운동기+하늘 걷기 2
연번행정동시설명상세주소설치기구
99100효동가오동 유성아파트대전광역시 동구 대전로 470번길 25레그 프레스+에어 워킹+워밍 쇼올더+트위스트+마사지 롤러
100101효동가오주공1단지아파트 (101동)대전광역시 동구 대전로 448번길 11마사리 롤러+싸이클링+바디 싯업+스쿼트 머신+트위스트
101102효동대전맹학교대전광역시 동구 은어송로 95트위스트+바디 싯업+하늘 걷기+옆 파도타기+
102103효동우미린아파트 (502동 옆)대전광역시 동구 은어송로100바디 싯업+트위스트+마사지 롤러+레그 프레스+에어 워킹
103104효동은어송1단지 (107동 옆)대전광역시 동구 동구청로67레그 프레스+에어 워킹+마사지 롤러+에어 서핑+워밍 쇼올더
104105효동효동현대아파트 (103동 옆)대전광역시 동구 대전로 646트위스트+에어워킹+싸이클링+스쿼트 머신+에어 서핑
105106효동효동현대아파트 (105동 옆)대전광역시 동구 대전로 646바디 싯업+풀 웨이트+싸이클링+워밍 쇼올더+
106107효동효동현대아파트 (106동 옆)대전광역시 동구 대전로 646싸이클링+에어워킹+마사지 롤러++
107108효동효동현대아파트 (109동 앞)대전광역시 동구 대전로 646싸이클링+스쿼트머신+++
108109효동효천경로당대전광역시 동구 효천1길 69마사지 롤러+에어 서핑+워밍 쇼올더+마사지 롤러+