Overview

Dataset statistics

Number of variables5
Number of observations126
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory43.0 B

Variable types

Numeric2
Categorical1
Text2

Dataset

Description송파구의 도시공원 이용자 현황으로 연번, 분류, 공원명, 소재지, 연간이용자수(천명) 데이터의 정보를 제공합니다.
Author서울특별시 송파구
URLhttps://www.data.go.kr/data/15074389/fileData.do

Alerts

연번 is highly overall correlated with 연간 도시공원 이용자수 현황(천명) and 1 other fieldsHigh correlation
연간 도시공원 이용자수 현황(천명) is highly overall correlated with 연번 High correlation
분류 is highly overall correlated with 연번 High correlation
연간 도시공원 이용자수 현황(천명) has 2 (1.6%) missing valuesMissing
연번 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:56:14.943089
Analysis finished2023-12-12 20:56:15.743353
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.5
Minimum1
Maximum126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T05:56:15.854697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.25
Q132.25
median63.5
Q394.75
95-th percentile119.75
Maximum126
Range125
Interquartile range (IQR)62.5

Descriptive statistics

Standard deviation36.517119
Coefficient of variation (CV)0.57507274
Kurtosis-1.2
Mean63.5
Median Absolute Deviation (MAD)31.5
Skewness0
Sum8001
Variance1333.5
MonotonicityStrictly increasing
2023-12-13T05:56:16.052605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
81 1
 
0.8%
94 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
Other values (116) 116
92.1%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
126 1
0.8%
125 1
0.8%
124 1
0.8%
123 1
0.8%
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%

분류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
어린이공원
79 
근린공원
46 
수변공원
 
1

Length

Max length5
Median length5
Mean length4.6269841
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
어린이공원 79
62.7%
근린공원 46
36.5%
수변공원 1
 
0.8%

Length

2023-12-13T05:56:16.226753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:56:16.353944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이공원 79
62.7%
근린공원 46
36.5%
수변공원 1
 
0.8%

공원명
Text

Distinct123
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T05:56:16.721806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.6031746
Min length3

Characters and Unicode

Total characters454
Distinct characters166
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)95.2%

Sample

1st row 송파나루
2nd row 잠실
3rd row 삼전
4th row 송파
5th row 방이
ValueCountFrequency (%)
새내 2
 
1.6%
거여 2
 
1.6%
삼전 2
 
1.6%
개나리 2
 
1.6%
반딧불 1
 
0.8%
비둘기 1
 
0.8%
중대 1
 
0.8%
훙이 1
 
0.8%
개미 1
 
0.8%
송파나루 1
 
0.8%
Other values (113) 113
89.0%
2023-12-13T05:56:17.279376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
28.0%
리 9
 
2.0%
이 9
 
2.0%
나 9
 
2.0%
아 7
 
1.5%
마 6
 
1.3%
말 6
 
1.3%
무 6
 
1.3%
천 5
 
1.1%
동 5
 
1.1%
Other values (156) 265
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 327
72.0%
Space Separator 127
 
28.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 9
 
2.8%
이 9
 
2.8%
나 9
 
2.8%
아 7
 
2.1%
마 6
 
1.8%
말 6
 
1.8%
무 6
 
1.8%
천 5
 
1.5%
동 5
 
1.5%
삼 5
 
1.5%
Other values (155) 260
79.5%
Space Separator
ValueCountFrequency (%)
127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 327
72.0%
Common 127
 
28.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 9
 
2.8%
이 9
 
2.8%
나 9
 
2.8%
아 7
 
2.1%
마 6
 
1.8%
말 6
 
1.8%
무 6
 
1.8%
천 5
 
1.5%
동 5
 
1.5%
삼 5
 
1.5%
Other values (155) 260
79.5%
Common
ValueCountFrequency (%)
127
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 327
72.0%
ASCII 127
 
28.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
100.0%
Hangul
ValueCountFrequency (%)
리 9
 
2.8%
이 9
 
2.8%
나 9
 
2.8%
아 7
 
2.1%
마 6
 
1.8%
말 6
 
1.8%
무 6
 
1.8%
천 5
 
1.5%
동 5
 
1.5%
삼 5
 
1.5%
Other values (155) 260
79.5%

소재지
Text

UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T05:56:17.604722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length20.309524
Min length15

Characters and Unicode

Total characters2559
Distinct characters75
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

Unique126 ?
Unique (%)100.0%

Sample

1st row서울특별시 송파구 잠실로 180(신천동)
2nd row서울특별시 송파구 백제고분로15길 7(잠실동)
3rd row서울특별시 송파구 백제고분로32길 6-30(삼전동)
4th row서울특별시 송파구 송파대로42길 29(송파동)
5th row서울특별시 송파구 백제고분로 489(방이동)
ValueCountFrequency (%)
서울특별시 126
25.0%
송파구 123
24.4%
오금동 8
 
1.6%
문정동 6
 
1.2%
송파동 5
 
1.0%
방이동 5
 
1.0%
잠실동 5
 
1.0%
장지동 4
 
0.8%
신천동 4
 
0.8%
거여동 4
 
0.8%
Other values (182) 214
42.5%
2023-12-13T05:56:18.121416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
404
15.8%
송 142
 
5.5%
파 139
 
5.4%
동 130
 
5.1%
서 126
 
4.9%
특 126
 
4.9%
별 126
 
4.9%
시 126
 
4.9%
구 126
 
4.9%
울 126
 
4.9%
Other values (65) 988
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1568
61.3%
Decimal Number 459
 
17.9%
Space Separator 404
 
15.8%
Dash Punctuation 52
 
2.0%
Close Punctuation 37
 
1.4%
Open Punctuation 37
 
1.4%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
송 142
 
9.1%
파 139
 
8.9%
동 130
 
8.3%
서 126
 
8.0%
특 126
 
8.0%
별 126
 
8.0%
시 126
 
8.0%
구 126
 
8.0%
울 126
 
8.0%
로 37
 
2.4%
Other values (50) 364
23.2%
Decimal Number
ValueCountFrequency (%)
1 101
22.0%
2 82
17.9%
3 52
11.3%
4 41
8.9%
5 36
 
7.8%
7 33
 
7.2%
6 33
 
7.2%
8 31
 
6.8%
0 29
 
6.3%
9 21
 
4.6%
Space Separator
ValueCountFrequency (%)
404
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1568
61.3%
Common 991
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
송 142
 
9.1%
파 139
 
8.9%
동 130
 
8.3%
서 126
 
8.0%
특 126
 
8.0%
별 126
 
8.0%
시 126
 
8.0%
구 126
 
8.0%
울 126
 
8.0%
로 37
 
2.4%
Other values (50) 364
23.2%
Common
ValueCountFrequency (%)
404
40.8%
1 101
 
10.2%
2 82
 
8.3%
- 52
 
5.2%
3 52
 
5.2%
4 41
 
4.1%
) 37
 
3.7%
( 37
 
3.7%
5 36
 
3.6%
7 33
 
3.3%
Other values (5) 116
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1568
61.3%
ASCII 991
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
404
40.8%
1 101
 
10.2%
2 82
 
8.3%
- 52
 
5.2%
3 52
 
5.2%
4 41
 
4.1%
) 37
 
3.7%
( 37
 
3.7%
5 36
 
3.6%
7 33
 
3.3%
Other values (5) 116
 
11.7%
Hangul
ValueCountFrequency (%)
송 142
 
9.1%
파 139
 
8.9%
동 130
 
8.3%
서 126
 
8.0%
특 126
 
8.0%
별 126
 
8.0%
시 126
 
8.0%
구 126
 
8.0%
울 126
 
8.0%
로 37
 
2.4%
Other values (50) 364
23.2%

연간 도시공원 이용자수 현황(천명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct21
Distinct (%)16.9%
Missing2
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean23.491935
Minimum1
Maximum1080
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T05:56:18.283352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.15
Q110
median10
Q310
95-th percentile42.75
Maximum1080
Range1079
Interquartile range (IQR)0

Descriptive statistics

Standard deviation98.269126
Coefficient of variation (CV)4.1831004
Kurtosis111.1122
Mean23.491935
Median Absolute Deviation (MAD)0
Skewness10.336803
Sum2913
Variance9656.8211
MonotonicityNot monotonic
2023-12-13T05:56:18.413315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
10 74
58.7%
20 7
 
5.6%
5 7
 
5.6%
7 5
 
4.0%
30 5
 
4.0%
15 4
 
3.2%
3 4
 
3.2%
8 3
 
2.4%
25 2
 
1.6%
50 2
 
1.6%
Other values (11) 11
 
8.7%
(Missing) 2
 
1.6%
ValueCountFrequency (%)
1 1
 
0.8%
2 1
 
0.8%
3 4
 
3.2%
4 1
 
0.8%
5 7
 
5.6%
6 1
 
0.8%
7 5
 
4.0%
8 3
 
2.4%
10 74
58.7%
12 1
 
0.8%
ValueCountFrequency (%)
1080 1
 
0.8%
216 1
 
0.8%
120 1
 
0.8%
60 1
 
0.8%
50 2
 
1.6%
45 1
 
0.8%
30 5
4.0%
25 2
 
1.6%
21 1
 
0.8%
20 7
5.6%

Interactions

2023-12-13T05:56:15.351155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:56:15.168712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:56:15.459448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:56:15.265670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:56:18.503414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번분류연간 도시공원 이용자수 현황(천명)
연번1.0000.7850.346
분류0.7851.0000.250
연간 도시공원 이용자수 현황(천명)0.3460.2501.000
2023-12-13T05:56:18.923635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연간 도시공원 이용자수 현황(천명)분류
연번1.000-0.6560.650
연간 도시공원 이용자수 현황(천명)-0.6561.0000.080
분류0.6500.0801.000

Missing values

2023-12-13T05:56:15.599360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:56:15.702515image/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

연번분류공원명소재지연간 도시공원 이용자수 현황(천명)
01근린공원송파나루서울특별시 송파구 잠실로 180(신천동)1080
12근린공원잠실서울특별시 송파구 백제고분로15길 7(잠실동)30
23근린공원삼전서울특별시 송파구 백제고분로32길 6-30(삼전동)30
34근린공원송파서울특별시 송파구 송파대로42길 29(송파동)25
45근린공원방이서울특별시 송파구 백제고분로 489(방이동)20
56근린공원태양서울특별시 송파구 풍납동 389-210
67근린공원한양서울특별시 송파구 송파동 15215
78근린공원벚꽃서울특별시 송파구 잠실동 27-7<NA>
89근린공원새내서울특별시 송파구 신천동 7-7<NA>
910근린공원동산서울특별시 송파구 송파동 12010
연번분류공원명소재지연간 도시공원 이용자수 현황(천명)
116117어린이공원향나무서울특별시 송파구 거여2동 293-210
117118어린이공원모슬서울특별시 송파구 거여2동 28-73
118119어린이공원대건서울특별시 송파구 가락동 165-47
119120어린이공원도담서울특별시 송파구 마천1동 58310
120121어린이공원천상서울특별시 송파구 마천1동 61015
121122어린이공원한림서울특별시 송파구 장지동 834-25
122123어린이공원문현서울특별시 송파구 장지동 838-15
123124어린이공원솔바람서울특별시 송파구 장지동 843-15
124125어린이공원버들서울특별시 송파구 장지동 854-25
125126어린이공원거북이서울특별시 송파구 송파동 243-15