Overview

Dataset statistics

Number of variables6
Number of observations101
Missing cells26
Missing cells (%)4.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory50.3 B

Variable types

Text3
Numeric1
DateTime1
Categorical1

Dataset

Description김포시 어린이놀이시설 현황(공원명, 소재지지번주소,면적(제곱미터), 놀이기구 현황,설치일자,데이터 기준일자)의 데이터를 제공하고 있습니다.
Author경기도 김포시
URLhttps://www.data.go.kr/data/15064691/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant
면적(제곱미터) has 13 (12.9%) missing valuesMissing
설치일자 has 13 (12.9%) missing valuesMissing
공원명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:40:37.651266
Analysis finished2023-12-12 06:40:38.693262
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공원명
Text

UNIQUE 

Distinct101
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-12-12T15:40:38.872480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length9.8118812
Min length4

Characters and Unicode

Total characters991
Distinct characters122
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

Unique101 ?
Unique (%)100.0%

Sample

1st row사우제1어린이공원
2nd row사우제2어린이공원
3rd row사우제3어린이공원
4th row사우제4어린이공원
5th row사우제5어린이공원
ValueCountFrequency (%)
어린이공원 6
 
5.2%
모험놀이터 2
 
1.7%
사우제1어린이공원 1
 
0.9%
44호 1
 
0.9%
42호 1
 
0.9%
41호 1
 
0.9%
37호 1
 
0.9%
근린공원(새장터공원 1
 
0.9%
27호 1
 
0.9%
근린공원(선수공원 1
 
0.9%
Other values (100) 100
86.2%
2023-12-12T15:40:39.314570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 117
 
11.8%
원 117
 
11.8%
린 89
 
9.0%
이 74
 
7.5%
어 70
 
7.1%
호 48
 
4.8%
( 30
 
3.0%
제 28
 
2.8%
) 26
 
2.6%
1 24
 
2.4%
Other values (112) 368
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 810
81.7%
Decimal Number 105
 
10.6%
Open Punctuation 30
 
3.0%
Close Punctuation 26
 
2.6%
Space Separator 15
 
1.5%
Dash Punctuation 4
 
0.4%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 117
14.4%
원 117
14.4%
린 89
11.0%
이 74
 
9.1%
어 70
 
8.6%
호 48
 
5.9%
제 28
 
3.5%
근 18
 
2.2%
무 14
 
1.7%
풍 14
 
1.7%
Other values (97) 221
27.3%
Decimal Number
ValueCountFrequency (%)
1 24
22.9%
2 18
17.1%
4 17
16.2%
3 13
12.4%
6 10
9.5%
5 9
 
8.6%
0 5
 
4.8%
7 5
 
4.8%
9 2
 
1.9%
8 2
 
1.9%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 810
81.7%
Common 181
 
18.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 117
14.4%
원 117
14.4%
린 89
11.0%
이 74
 
9.1%
어 70
 
8.6%
호 48
 
5.9%
제 28
 
3.5%
근 18
 
2.2%
무 14
 
1.7%
풍 14
 
1.7%
Other values (97) 221
27.3%
Common
ValueCountFrequency (%)
( 30
16.6%
) 26
14.4%
1 24
13.3%
2 18
9.9%
4 17
9.4%
15
8.3%
3 13
7.2%
6 10
 
5.5%
5 9
 
5.0%
0 5
 
2.8%
Other values (5) 14
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 810
81.7%
ASCII 181
 
18.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 117
14.4%
원 117
14.4%
린 89
11.0%
이 74
 
9.1%
어 70
 
8.6%
호 48
 
5.9%
제 28
 
3.5%
근 18
 
2.2%
무 14
 
1.7%
풍 14
 
1.7%
Other values (97) 221
27.3%
ASCII
ValueCountFrequency (%)
( 30
16.6%
) 26
14.4%
1 24
13.3%
2 18
9.9%
4 17
9.4%
15
8.3%
3 13
7.2%
6 10
 
5.5%
5 9
 
5.0%
0 5
 
2.8%
Other values (5) 14
7.7%

소재지지번주소
Text

Distinct93
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-12-12T15:40:39.758300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length17.861386
Min length14

Characters and Unicode

Total characters1804
Distinct characters58
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

Unique86 ?
Unique (%)85.1%

Sample

1st row경기도 김포시 북변동 801
2nd row경기도 김포시 북변동 804
3rd row경기도 김포시 북변동 813
4th row경기도 김포시 사우동 910
5th row경기도 김포시 사우동 1043
ValueCountFrequency (%)
경기도 101
23.4%
김포시 101
23.4%
장기동 16
 
3.7%
풍무동 16
 
3.7%
고촌읍 11
 
2.6%
양촌읍 11
 
2.6%
운양동 10
 
2.3%
신곡리 9
 
2.1%
마산동 8
 
1.9%
사우동 7
 
1.6%
Other values (105) 141
32.7%
2023-12-12T15:40:40.275406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
352
19.5%
기 117
 
6.5%
포 108
 
6.0%
김 105
 
5.8%
경 101
 
5.6%
도 101
 
5.6%
시 101
 
5.6%
1 99
 
5.5%
동 73
 
4.0%
2 53
 
2.9%
Other values (48) 594
32.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1019
56.5%
Decimal Number 395
 
21.9%
Space Separator 352
 
19.5%
Dash Punctuation 29
 
1.6%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 117
11.5%
포 108
10.6%
김 105
10.3%
경 101
9.9%
도 101
9.9%
시 101
9.9%
동 73
 
7.2%
읍 28
 
2.7%
양 27
 
2.6%
리 27
 
2.6%
Other values (33) 231
22.7%
Decimal Number
ValueCountFrequency (%)
1 99
25.1%
2 53
13.4%
6 38
 
9.6%
3 34
 
8.6%
4 33
 
8.4%
5 32
 
8.1%
8 31
 
7.8%
9 29
 
7.3%
0 29
 
7.3%
7 17
 
4.3%
Space Separator
ValueCountFrequency (%)
352
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1019
56.5%
Common 785
43.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 117
11.5%
포 108
10.6%
김 105
10.3%
경 101
9.9%
도 101
9.9%
시 101
9.9%
동 73
 
7.2%
읍 28
 
2.7%
양 27
 
2.6%
리 27
 
2.6%
Other values (33) 231
22.7%
Common
ValueCountFrequency (%)
352
44.8%
1 99
 
12.6%
2 53
 
6.8%
6 38
 
4.8%
3 34
 
4.3%
4 33
 
4.2%
5 32
 
4.1%
8 31
 
3.9%
9 29
 
3.7%
- 29
 
3.7%
Other values (5) 55
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1019
56.5%
ASCII 785
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
352
44.8%
1 99
 
12.6%
2 53
 
6.8%
6 38
 
4.8%
3 34
 
4.3%
4 33
 
4.2%
5 32
 
4.1%
8 31
 
3.9%
9 29
 
3.7%
- 29
 
3.7%
Other values (5) 55
 
7.0%
Hangul
ValueCountFrequency (%)
기 117
11.5%
포 108
10.6%
김 105
10.3%
경 101
9.9%
도 101
9.9%
시 101
9.9%
동 73
 
7.2%
읍 28
 
2.7%
양 27
 
2.6%
리 27
 
2.6%
Other values (33) 231
22.7%

면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct84
Distinct (%)95.5%
Missing13
Missing (%)12.9%
Infinite0
Infinite (%)0.0%
Mean8024.45
Minimum104
Maximum134481
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T15:40:40.503170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104
5-th percentile559.2
Q11686.75
median2514.5
Q36699.5
95-th percentile33292.95
Maximum134481
Range134377
Interquartile range (IQR)5012.75

Descriptive statistics

Standard deviation17289.531
Coefficient of variation (CV)2.1546063
Kurtosis34.124722
Mean8024.45
Median Absolute Deviation (MAD)996
Skewness5.2778532
Sum706151.6
Variance2.9892787 × 108
MonotonicityNot monotonic
2023-12-12T15:40:41.004656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1500.0 3
 
3.0%
8874.0 2
 
2.0%
3230.0 2
 
2.0%
2384.0 1
 
1.0%
1534.0 1
 
1.0%
3322.0 1
 
1.0%
2105.0 1
 
1.0%
723.0 1
 
1.0%
2179.0 1
 
1.0%
31172.0 1
 
1.0%
Other values (74) 74
73.3%
(Missing) 13
 
12.9%
ValueCountFrequency (%)
104.0 1
 
1.0%
261.0 1
 
1.0%
294.0 1
 
1.0%
360.0 1
 
1.0%
471.0 1
 
1.0%
723.0 1
 
1.0%
755.0 1
 
1.0%
996.0 1
 
1.0%
997.0 1
 
1.0%
1500.0 3
3.0%
ValueCountFrequency (%)
134481.0 1
1.0%
65251.0 1
1.0%
42307.0 1
1.0%
40716.0 1
1.0%
34435.0 1
1.0%
31172.0 1
1.0%
29054.0 1
1.0%
25279.6 1
1.0%
20682.0 1
1.0%
17194.0 1
1.0%

놀이기구현황
Text

Distinct75
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-12-12T15:40:41.263519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length25
Mean length11.435644
Min length3

Characters and Unicode

Total characters1155
Distinct characters40
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

Unique57 ?
Unique (%)56.4%

Sample

1st row그네1+흔들4
2nd row조합1+그네1+흔들4
3rd row조합1+흔들4
4th row조합1+그네1+흔들4
5th row조합1+그네1+흔들4
ValueCountFrequency (%)
조합1 12
 
9.4%
조합1+흔들4 4
 
3.1%
그네1 4
 
3.1%
조합1+그네1+흔들4 3
 
2.4%
공중놀이기구1 3
 
2.4%
3
 
2.4%
흔들3+조합1 2
 
1.6%
조합놀이대1+그네 2
 
1.6%
조합놀이대1 2
 
1.6%
흔들2 2
 
1.6%
Other values (73) 90
70.9%
2023-12-12T15:40:41.714912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 165
14.3%
1 162
14.0%
조 89
 
7.7%
합 89
 
7.7%
흔 69
 
6.0%
들 69
 
6.0%
기 53
 
4.6%
그 46
 
4.0%
네 46
 
4.0%
2 40
 
3.5%
Other values (30) 327
28.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 702
60.8%
Decimal Number 262
 
22.7%
Math Symbol 165
 
14.3%
Space Separator 26
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 89
12.7%
합 89
12.7%
흔 69
9.8%
들 69
9.8%
기 53
 
7.5%
그 46
 
6.6%
네 46
 
6.6%
이 30
 
4.3%
구 29
 
4.1%
놀 25
 
3.6%
Other values (21) 157
22.4%
Decimal Number
ValueCountFrequency (%)
1 162
61.8%
2 40
 
15.3%
3 31
 
11.8%
4 14
 
5.3%
5 12
 
4.6%
6 2
 
0.8%
7 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
+ 165
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 702
60.8%
Common 453
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 89
12.7%
합 89
12.7%
흔 69
9.8%
들 69
9.8%
기 53
 
7.5%
그 46
 
6.6%
네 46
 
6.6%
이 30
 
4.3%
구 29
 
4.1%
놀 25
 
3.6%
Other values (21) 157
22.4%
Common
ValueCountFrequency (%)
+ 165
36.4%
1 162
35.8%
2 40
 
8.8%
3 31
 
6.8%
26
 
5.7%
4 14
 
3.1%
5 12
 
2.6%
6 2
 
0.4%
7 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 702
60.8%
ASCII 453
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 165
36.4%
1 162
35.8%
2 40
 
8.8%
3 31
 
6.8%
26
 
5.7%
4 14
 
3.1%
5 12
 
2.6%
6 2
 
0.4%
7 1
 
0.2%
Hangul
ValueCountFrequency (%)
조 89
12.7%
합 89
12.7%
흔 69
9.8%
들 69
9.8%
기 53
 
7.5%
그 46
 
6.6%
네 46
 
6.6%
이 30
 
4.3%
구 29
 
4.1%
놀 25
 
3.6%
Other values (21) 157
22.4%

설치일자
Date

MISSING 

Distinct56
Distinct (%)63.6%
Missing13
Missing (%)12.9%
Memory size940.0 B
Minimum2001-01-01 00:00:00
Maximum2022-09-30 00:00:00
2023-12-12T15:40:41.901270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:40:42.101989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터 기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-09-18
101 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-18
2nd row2023-09-18
3rd row2023-09-18
4th row2023-09-18
5th row2023-09-18

Common Values

ValueCountFrequency (%)
2023-09-18 101
100.0%

Length

2023-12-12T15:40:42.273380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:42.388545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-18 101
100.0%

Interactions

2023-12-12T15:40:38.262055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:40:42.450676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지지번주소면적(제곱미터)놀이기구현황설치일자
소재지지번주소1.0000.6960.9470.999
면적(제곱미터)0.6961.0000.9080.860
놀이기구현황0.9470.9081.0000.945
설치일자0.9990.8600.9451.000

Missing values

2023-12-12T15:40:38.396450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:40:38.526066image/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.
2023-12-12T15:40:38.639744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

공원명소재지지번주소면적(제곱미터)놀이기구현황설치일자데이터 기준일자
0사우제1어린이공원경기도 김포시 북변동 8013479.0그네1+흔들42009-05-122023-09-18
1사우제2어린이공원경기도 김포시 북변동 8042037.0조합1+그네1+흔들42009-05-122023-09-18
2사우제3어린이공원경기도 김포시 북변동 8132282.0조합1+흔들42009-05-122023-09-18
3사우제4어린이공원경기도 김포시 사우동 9102376.0조합1+그네1+흔들42011-12-222023-09-18
4사우제5어린이공원경기도 김포시 사우동 10432521.0조합1+그네1+흔들42011-12-222023-09-18
5사우제6어린이공원경기도 김포시 사우동 9483042.0흔들32009-05-122023-09-18
6사우5통어린이공원경기도 김포시 사우동 241-11644.0조합1+흔들42007-01-012023-09-18
7사우8통어린이공원경기도 김포시 사우동 249-31701.0조합1+흔들42009-01-232023-09-18
8사우근린공원경기도 김포시 사우동 8649898.0조합1+흔들1+회전12010-06-112023-09-18
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