Overview

Dataset statistics

Number of variables5
Number of observations107
Missing cells47
Missing cells (%)8.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory43.2 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description부산광역시_동구_화단및쌈지공원현황_20230620
Author부산광역시 동구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3078950

Alerts

연번 is highly overall correlated with 비고High correlation
비고 is highly overall correlated with 연번High correlation
위치별 has 47 (43.9%) missing valuesMissing
연번 has unique valuesUnique
명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:19:26.452401
Analysis finished2023-12-10 16:19:27.244593
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54
Minimum1
Maximum107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:19:27.356373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.3
Q127.5
median54
Q380.5
95-th percentile101.7
Maximum107
Range106
Interquartile range (IQR)53

Descriptive statistics

Standard deviation31.032241
Coefficient of variation (CV)0.57467114
Kurtosis-1.2
Mean54
Median Absolute Deviation (MAD)27
Skewness0
Sum5778
Variance963
MonotonicityStrictly increasing
2023-12-11T01:19:27.548925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
69 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%
73 1
 
0.9%
Other values (97) 97
90.7%
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 (%)
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%
99 1
0.9%
98 1
0.9%

명칭
Text

UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-11T01:19:27.800301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length19
Mean length13.327103
Min length4

Characters and Unicode

Total characters1426
Distinct characters188
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

Unique107 ?
Unique (%)100.0%

Sample

1st row윤흥신주변 쌈지공원
2nd row부산진역 쌈지공원
3rd row가구거리입구쌈지공원
4th row수정가로공원
5th row부두 화단내 쌈지공원
ValueCountFrequency (%)
쌈지공원 22
 
7.8%
화단 20
 
7.1%
앞 11
 
3.9%
범일1동 8
 
2.8%
초량2동 7
 
2.5%
옆 7
 
2.5%
초량동 7
 
2.5%
소규모공원 6
 
2.1%
초량1동 6
 
2.1%
좌천동 5
 
1.8%
Other values (148) 183
64.9%
2023-12-11T01:19:28.206132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
180
 
12.6%
동 82
 
5.8%
원 59
 
4.1%
공 58
 
4.1%
1 37
 
2.6%
초 35
 
2.5%
화 35
 
2.5%
단 33
 
2.3%
지 32
 
2.2%
량 31
 
2.2%
Other values (178) 844
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1022
71.7%
Space Separator 180
 
12.6%
Decimal Number 149
 
10.4%
Open Punctuation 28
 
2.0%
Close Punctuation 28
 
2.0%
Dash Punctuation 18
 
1.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 82
 
8.0%
원 59
 
5.8%
공 58
 
5.7%
초 35
 
3.4%
화 35
 
3.4%
단 33
 
3.2%
지 32
 
3.1%
량 31
 
3.0%
쌈 27
 
2.6%
수 26
 
2.5%
Other values (163) 604
59.1%
Decimal Number
ValueCountFrequency (%)
1 37
24.8%
2 28
18.8%
5 14
 
9.4%
0 13
 
8.7%
8 12
 
8.1%
6 11
 
7.4%
4 11
 
7.4%
9 10
 
6.7%
7 8
 
5.4%
3 5
 
3.4%
Space Separator
ValueCountFrequency (%)
180
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Lowercase Letter
ValueCountFrequency (%)
f 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1022
71.7%
Common 403
 
28.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 82
 
8.0%
원 59
 
5.8%
공 58
 
5.7%
초 35
 
3.4%
화 35
 
3.4%
단 33
 
3.2%
지 32
 
3.1%
량 31
 
3.0%
쌈 27
 
2.6%
수 26
 
2.5%
Other values (163) 604
59.1%
Common
ValueCountFrequency (%)
180
44.7%
1 37
 
9.2%
( 28
 
6.9%
) 28
 
6.9%
2 28
 
6.9%
- 18
 
4.5%
5 14
 
3.5%
0 13
 
3.2%
8 12
 
3.0%
6 11
 
2.7%
Other values (4) 34
 
8.4%
Latin
ValueCountFrequency (%)
f 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1022
71.7%
ASCII 404
 
28.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180
44.6%
1 37
 
9.2%
( 28
 
6.9%
) 28
 
6.9%
2 28
 
6.9%
- 18
 
4.5%
5 14
 
3.5%
0 13
 
3.2%
8 12
 
3.0%
6 11
 
2.7%
Other values (5) 35
 
8.7%
Hangul
ValueCountFrequency (%)
동 82
 
8.0%
원 59
 
5.8%
공 58
 
5.7%
초 35
 
3.4%
화 35
 
3.4%
단 33
 
3.2%
지 32
 
3.1%
량 31
 
3.0%
쌈 27
 
2.6%
수 26
 
2.5%
Other values (163) 604
59.1%

위치별
Text

MISSING 

Distinct60
Distinct (%)100.0%
Missing47
Missing (%)43.9%
Memory size988.0 B
2023-12-11T01:19:28.523162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11.05
Min length5

Characters and Unicode

Total characters663
Distinct characters31
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

Unique60 ?
Unique (%)100.0%

Sample

1st row초량동 1170번지
2nd row수정동 79-711번지
3rd row좌천동 242-1번지
4th row좌천동 1164-2번지
5th row좌천동 1116-26번지
ValueCountFrequency (%)
초량동 23
18.3%
범일동 15
 
11.9%
수정동 11
 
8.7%
좌천동 9
 
7.1%
일원 7
 
5.6%
1058-31 1
 
0.8%
970-104 1
 
0.8%
980-18 1
 
0.8%
771-1 1
 
0.8%
859-46 1
 
0.8%
Other values (56) 56
44.4%
2023-12-11T01:19:28.954301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 72
 
10.9%
66
 
10.0%
동 59
 
8.9%
- 54
 
8.1%
4 39
 
5.9%
8 28
 
4.2%
5 27
 
4.1%
지 26
 
3.9%
3 26
 
3.9%
번 26
 
3.9%
Other values (21) 240
36.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 288
43.4%
Other Letter 255
38.5%
Space Separator 66
 
10.0%
Dash Punctuation 54
 
8.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 59
23.1%
지 26
10.2%
번 26
10.2%
일 25
9.8%
량 23
 
9.0%
초 23
 
9.0%
범 16
 
6.3%
수 11
 
4.3%
정 11
 
4.3%
천 9
 
3.5%
Other values (9) 26
10.2%
Decimal Number
ValueCountFrequency (%)
1 72
25.0%
4 39
13.5%
8 28
 
9.7%
5 27
 
9.4%
3 26
 
9.0%
9 26
 
9.0%
0 21
 
7.3%
7 19
 
6.6%
2 17
 
5.9%
6 13
 
4.5%
Space Separator
ValueCountFrequency (%)
66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 408
61.5%
Hangul 255
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 59
23.1%
지 26
10.2%
번 26
10.2%
일 25
9.8%
량 23
 
9.0%
초 23
 
9.0%
범 16
 
6.3%
수 11
 
4.3%
정 11
 
4.3%
천 9
 
3.5%
Other values (9) 26
10.2%
Common
ValueCountFrequency (%)
1 72
17.6%
66
16.2%
- 54
13.2%
4 39
9.6%
8 28
 
6.9%
5 27
 
6.6%
3 26
 
6.4%
9 26
 
6.4%
0 21
 
5.1%
7 19
 
4.7%
Other values (2) 30
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 408
61.5%
Hangul 255
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 72
17.6%
66
16.2%
- 54
13.2%
4 39
9.6%
8 28
 
6.9%
5 27
 
6.6%
3 26
 
6.4%
9 26
 
6.4%
0 21
 
5.1%
7 19
 
4.7%
Other values (2) 30
7.4%
Hangul
ValueCountFrequency (%)
동 59
23.1%
지 26
10.2%
번 26
10.2%
일 25
9.8%
량 23
 
9.0%
초 23
 
9.0%
범 16
 
6.3%
수 11
 
4.3%
정 11
 
4.3%
천 9
 
3.5%
Other values (9) 26
10.2%

면적(제곱미터)
Real number (ℝ)

Distinct69
Distinct (%)64.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean714
Minimum4
Maximum25300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T01:19:29.109114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile10
Q124
median60
Q3175
95-th percentile2285
Maximum25300
Range25296
Interquartile range (IQR)151

Descriptive statistics

Standard deviation2983.0714
Coefficient of variation (CV)4.1779711
Kurtosis50.737184
Mean714
Median Absolute Deviation (MAD)40
Skewness6.8591512
Sum76398
Variance8898714.9
MonotonicityNot monotonic
2023-12-11T01:19:29.259605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 8
 
7.5%
100 5
 
4.7%
60 4
 
3.7%
10 4
 
3.7%
40 4
 
3.7%
25 4
 
3.7%
15 3
 
2.8%
80 3
 
2.8%
50 3
 
2.8%
8 2
 
1.9%
Other values (59) 67
62.6%
ValueCountFrequency (%)
4 1
 
0.9%
7 1
 
0.9%
8 2
 
1.9%
10 4
3.7%
11 2
 
1.9%
15 3
 
2.8%
16 1
 
0.9%
17 1
 
0.9%
18 1
 
0.9%
20 8
7.5%
ValueCountFrequency (%)
25300 1
0.9%
16368 1
0.9%
6800 1
0.9%
3718 1
0.9%
2400 1
0.9%
2300 1
0.9%
2250 1
0.9%
1589 1
0.9%
1505 1
0.9%
1368 1
0.9%

비고
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size988.0 B
쌈지공원
60 
화단
47 

Length

Max length4
Median length4
Mean length3.1214953
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
쌈지공원 60
56.1%
화단 47
43.9%

Length

2023-12-11T01:19:29.415026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:19:29.526498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
쌈지공원 60
56.1%
화단 47
43.9%

Interactions

2023-12-11T01:19:26.857677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:19:26.667008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:19:26.940922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:19:26.741802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:19:29.584247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위치별면적(제곱미터)비고
연번1.0001.0000.1730.997
위치별1.0001.0001.000NaN
면적(제곱미터)0.1731.0001.0000.028
비고0.997NaN0.0281.000
2023-12-11T01:19:29.676456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적(제곱미터)비고
연번1.000-0.4540.912
면적(제곱미터)-0.4541.0000.028
비고0.9120.0281.000

Missing values

2023-12-11T01:19:27.075773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:19:27.186733image/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

연번명칭위치별면적(제곱미터)비고
01윤흥신주변 쌈지공원초량동 1170번지2400쌈지공원
12부산진역 쌈지공원수정동 79-711번지2250쌈지공원
23가구거리입구쌈지공원좌천동 242-1번지300쌈지공원
34수정가로공원좌천동 1164-2번지370쌈지공원
45부두 화단내 쌈지공원좌천동 1116-26번지1000쌈지공원
56금수사앞 쌈지공원초량동 838-32번지75쌈지공원
67동부경찰서앞쌈지공원수정동 1-4번지90쌈지공원
78초량2 파출소앞초량동 134-15번지25쌈지공원
89동구도서관앞범일동 산81-28번지260쌈지공원
910정발장군동상내 쌈지공원초량동 1147번지1505쌈지공원
연번명칭위치별면적(제곱미터)비고
9798초량2동 행복꽃밭(초량동891-4)<NA>25화단
9899초량2동 행복꽃밭(초량동906-211)<NA>17화단
99100초량2동 행복꽃밭(초량동856-56)<NA>7화단
100101초량6동 행복꽃밭(초량동827-302)<NA>15화단
101102수정2동 행복꽃밭(수정동708-63)<NA>21화단
102103수정2동 행복꽃밭(수정동787)<NA>21화단
103104수정4동 행복꽃밭(수정동997-13일원)<NA>10화단
104105수정4동 행복꽃밭(수정동974-502)<NA>4화단
105106수정5동 행복꽃밭(수정동1104-14)<NA>11화단
106107범일2동 행복꽃밭(범일동252-18)<NA>43화단