Overview

Dataset statistics

Number of variables6
Number of observations52
Missing cells38
Missing cells (%)12.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory51.5 B

Variable types

Text2
DateTime2
Categorical1
Numeric1

Dataset

Description경상남도 창녕군의 어린이 놀이시설 현황에 대한 데이터를 포함하고 있습니다.(시설명, 주소, 설치일자, 안전검사일, 보험가입여부, 면적)
Author경상남도 창녕군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15025321

Alerts

면적(㎡) is highly overall correlated with 보험가입여부High correlation
보험가입여부 is highly overall correlated with 면적(㎡)High correlation
보험가입여부 is highly imbalanced (86.3%)Imbalance
시설명 has 1 (1.9%) missing valuesMissing
주소 has 1 (1.9%) missing valuesMissing
설치일자 has 1 (1.9%) missing valuesMissing
안전검사일 has 1 (1.9%) missing valuesMissing
면적(㎡) has 34 (65.4%) missing valuesMissing

Reproduction

Analysis started2023-12-10 23:24:32.367172
Analysis finished2023-12-10 23:24:33.200581
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

MISSING 

Distinct51
Distinct (%)100.0%
Missing1
Missing (%)1.9%
Memory size548.0 B
2023-12-11T08:24:33.411601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length13.254902
Min length4

Characters and Unicode

Total characters676
Distinct characters148
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row현대맨션1차아파트 어린이놀이시설
2nd row솔터아파트 어린이놀이시설
3rd row남지어린이집 어린이놀이시설
4th row대합교회부설어린이집 어린이놀이시설
5th row여성회관어린이집 어린이놀이시설
ValueCountFrequency (%)
놀이터 10
 
8.4%
어린이놀이시설 9
 
7.6%
놀이시설 7
 
5.9%
내 4
 
3.4%
남지 3
 
2.5%
창녕 3
 
2.5%
신우희가로아파트 3
 
2.5%
앞 3
 
2.5%
현대맨션1차아파트 2
 
1.7%
107동 2
 
1.7%
Other values (71) 73
61.3%
2023-12-11T08:24:33.829348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 74
 
10.9%
68
 
10.1%
놀 38
 
5.6%
어 31
 
4.6%
린 29
 
4.3%
아 25
 
3.7%
파 23
 
3.4%
트 23
 
3.4%
설 22
 
3.3%
시 21
 
3.1%
Other values (138) 322
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 587
86.8%
Space Separator 68
 
10.1%
Decimal Number 18
 
2.7%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 74
 
12.6%
놀 38
 
6.5%
어 31
 
5.3%
린 29
 
4.9%
아 25
 
4.3%
파 23
 
3.9%
트 23
 
3.9%
설 22
 
3.7%
시 21
 
3.6%
터 17
 
2.9%
Other values (128) 284
48.4%
Decimal Number
ValueCountFrequency (%)
1 6
33.3%
0 4
22.2%
7 3
16.7%
2 2
 
11.1%
6 2
 
11.1%
5 1
 
5.6%
Space Separator
ValueCountFrequency (%)
68
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 587
86.8%
Common 89
 
13.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 74
 
12.6%
놀 38
 
6.5%
어 31
 
5.3%
린 29
 
4.9%
아 25
 
4.3%
파 23
 
3.9%
트 23
 
3.9%
설 22
 
3.7%
시 21
 
3.6%
터 17
 
2.9%
Other values (128) 284
48.4%
Common
ValueCountFrequency (%)
68
76.4%
1 6
 
6.7%
0 4
 
4.5%
7 3
 
3.4%
2 2
 
2.2%
6 2
 
2.2%
( 1
 
1.1%
) 1
 
1.1%
, 1
 
1.1%
5 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 587
86.8%
ASCII 89
 
13.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 74
 
12.6%
놀 38
 
6.5%
어 31
 
5.3%
린 29
 
4.9%
아 25
 
4.3%
파 23
 
3.9%
트 23
 
3.9%
설 22
 
3.7%
시 21
 
3.6%
터 17
 
2.9%
Other values (128) 284
48.4%
ASCII
ValueCountFrequency (%)
68
76.4%
1 6
 
6.7%
0 4
 
4.5%
7 3
 
3.4%
2 2
 
2.2%
6 2
 
2.2%
( 1
 
1.1%
) 1
 
1.1%
, 1
 
1.1%
5 1
 
1.1%

주소
Text

MISSING 

Distinct48
Distinct (%)94.1%
Missing1
Missing (%)1.9%
Memory size548.0 B
2023-12-11T08:24:34.082708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length24.098039
Min length18

Characters and Unicode

Total characters1229
Distinct characters110
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

Unique46 ?
Unique (%)90.2%

Sample

1st row경상남도 창녕군 창녕읍 우포2로 1199 (현대맨션)
2nd row경상남도 창녕군 창녕읍 화왕산로 26-5 (솔터아파트)
3rd row경상남도 창녕군 남지읍 동포7길 16
4th row경상남도 창녕군 대합면 십이리1길 41
5th row경상남도 창녕군 창녕읍 창녕대로 131
ValueCountFrequency (%)
경상남도 51
19.6%
창녕군 51
19.6%
창녕읍 19
 
7.3%
남지읍 16
 
6.2%
우포2로 5
 
1.9%
영산면 5
 
1.9%
조산서재골로 4
 
1.5%
69-3 3
 
1.2%
희가로 3
 
1.2%
부곡면 3
 
1.2%
Other values (88) 100
38.5%
2023-12-11T08:24:34.461173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
209
17.0%
남 78
 
6.3%
창 73
 
5.9%
녕 73
 
5.9%
도 53
 
4.3%
상 52
 
4.2%
경 51
 
4.1%
군 51
 
4.1%
1 41
 
3.3%
읍 35
 
2.8%
Other values (100) 513
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 797
64.8%
Space Separator 209
 
17.0%
Decimal Number 173
 
14.1%
Dash Punctuation 18
 
1.5%
Open Punctuation 14
 
1.1%
Close Punctuation 14
 
1.1%
Other Punctuation 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 78
 
9.8%
창 73
 
9.2%
녕 73
 
9.2%
도 53
 
6.6%
상 52
 
6.5%
경 51
 
6.4%
군 51
 
6.4%
읍 35
 
4.4%
지 27
 
3.4%
로 26
 
3.3%
Other values (85) 278
34.9%
Decimal Number
ValueCountFrequency (%)
1 41
23.7%
2 27
15.6%
3 23
13.3%
9 18
10.4%
6 14
 
8.1%
5 14
 
8.1%
7 13
 
7.5%
8 8
 
4.6%
4 8
 
4.6%
0 7
 
4.0%
Space Separator
ValueCountFrequency (%)
209
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 797
64.8%
Common 432
35.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 78
 
9.8%
창 73
 
9.2%
녕 73
 
9.2%
도 53
 
6.6%
상 52
 
6.5%
경 51
 
6.4%
군 51
 
6.4%
읍 35
 
4.4%
지 27
 
3.4%
로 26
 
3.3%
Other values (85) 278
34.9%
Common
ValueCountFrequency (%)
209
48.4%
1 41
 
9.5%
2 27
 
6.2%
3 23
 
5.3%
9 18
 
4.2%
- 18
 
4.2%
6 14
 
3.2%
( 14
 
3.2%
) 14
 
3.2%
5 14
 
3.2%
Other values (5) 40
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 797
64.8%
ASCII 432
35.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
209
48.4%
1 41
 
9.5%
2 27
 
6.2%
3 23
 
5.3%
9 18
 
4.2%
- 18
 
4.2%
6 14
 
3.2%
( 14
 
3.2%
) 14
 
3.2%
5 14
 
3.2%
Other values (5) 40
 
9.3%
Hangul
ValueCountFrequency (%)
남 78
 
9.8%
창 73
 
9.2%
녕 73
 
9.2%
도 53
 
6.6%
상 52
 
6.5%
경 51
 
6.4%
군 51
 
6.4%
읍 35
 
4.4%
지 27
 
3.4%
로 26
 
3.3%
Other values (85) 278
34.9%

설치일자
Date

MISSING 

Distinct48
Distinct (%)94.1%
Missing1
Missing (%)1.9%
Memory size548.0 B
Minimum1992-12-24 00:00:00
Maximum2019-07-01 00:00:00
2023-12-11T08:24:34.624026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:34.757127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)

안전검사일
Date

MISSING 

Distinct39
Distinct (%)76.5%
Missing1
Missing (%)1.9%
Memory size548.0 B
Minimum2018-09-05 00:00:00
Maximum2020-07-13 00:00:00
2023-12-11T08:24:34.890257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:35.027131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)

보험가입여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
가입
51 
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0384615
Min length2

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
가입 51
98.1%
<NA> 1
 
1.9%

Length

2023-12-11T08:24:35.151447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:24:35.243026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가입 51
98.1%
na 1
 
1.9%

면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)83.3%
Missing34
Missing (%)65.4%
Infinite0
Infinite (%)0.0%
Mean442.38889
Minimum118
Maximum1996
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-11T08:24:35.321058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum118
5-th percentile118
Q1121.75
median196
Q3295.5
95-th percentile1719.75
Maximum1996
Range1878
Interquartile range (IQR)173.75

Descriptive statistics

Standard deviation599.11652
Coefficient of variation (CV)1.3542757
Kurtosis2.5365079
Mean442.38889
Median Absolute Deviation (MAD)76
Skewness1.9958019
Sum7963
Variance358940.6
MonotonicityNot monotonic
2023-12-11T08:24:35.414260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
120 3
 
5.8%
118 2
 
3.8%
216 1
 
1.9%
229 1
 
1.9%
150 1
 
1.9%
176 1
 
1.9%
304 1
 
1.9%
222 1
 
1.9%
335 1
 
1.9%
1501 1
 
1.9%
Other values (5) 5
 
9.6%
(Missing) 34
65.4%
ValueCountFrequency (%)
118 2
3.8%
120 3
5.8%
127 1
 
1.9%
150 1
 
1.9%
170 1
 
1.9%
176 1
 
1.9%
216 1
 
1.9%
222 1
 
1.9%
229 1
 
1.9%
270 1
 
1.9%
ValueCountFrequency (%)
1996 1
1.9%
1671 1
1.9%
1501 1
1.9%
335 1
1.9%
304 1
1.9%
270 1
1.9%
229 1
1.9%
222 1
1.9%
216 1
1.9%
176 1
1.9%

Interactions

2023-12-11T08:24:32.724298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:24:35.487093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명주소설치일자안전검사일면적(㎡)
시설명1.0001.0001.0001.0001.000
주소1.0001.0000.9991.0001.000
설치일자1.0000.9991.0000.9980.000
안전검사일1.0001.0000.9981.0000.000
면적(㎡)1.0001.0000.0000.0001.000
2023-12-11T08:24:35.574485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(㎡)보험가입여부
면적(㎡)1.0001.000
보험가입여부1.0001.000

Missing values

2023-12-11T08:24:32.842464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:24:32.979809image/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.
2023-12-11T08:24:33.102990image/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

시설명주소설치일자안전검사일보험가입여부면적(㎡)
0현대맨션1차아파트 어린이놀이시설경상남도 창녕군 창녕읍 우포2로 1199 (현대맨션)1992-12-242018-10-11가입216
1솔터아파트 어린이놀이시설경상남도 창녕군 창녕읍 화왕산로 26-5 (솔터아파트)2000-08-072019-11-29가입229
2남지어린이집 어린이놀이시설경상남도 창녕군 남지읍 동포7길 162004-07-132019-05-16가입150
3대합교회부설어린이집 어린이놀이시설경상남도 창녕군 대합면 십이리1길 411996-11-222019-02-25가입120
4여성회관어린이집 어린이놀이시설경상남도 창녕군 창녕읍 창녕대로 1311996-03-062019-05-16가입176
5예술의전당어린이집 어린이놀이시설경상남도 창녕군 고암면 상대2길 162007-12-102019-05-15가입304
6남지푸른마을아파트 어린이놀이시설경상남도 창녕군 남지읍 동포로 46 (푸른마을아파트)2005-03-162020-06-09가입118
7동보하이빌아파트 어린이놀이시설경상남도 창녕군 우포2로 1162(대지면, 동보하이빌)2003-11-242020-05-29가입222
8삼호아파트 어린이놀이시설경상남도 창녕군 도천면 영산도천로 542001-03-132019-06-26가입335
9남지 덕진7차 봄아파트 놀이터경상남도 창녕군 남지읍 남지중앙1길 102010-03-092020-06-09가입<NA>
시설명주소설치일자안전검사일보험가입여부면적(㎡)
42남지문화의 집 남지어린이놀이터경상남도 창녕군 남지읍 남지강변길 130남지문화의집2017-02-172019-02-22가입<NA>
43화왕산 자연휴양림경상남도 창녕군 고암면 청간길 128-1262017-08-072019-08-16가입<NA>
44남지생태놀이터경상남도 창녕군 남지읍 남지리970-32017-12-262020-03-09가입<NA>
45사우곰탕 내 실내놀이터경상남도 창녕군 대지면 우포2로 11381층 사우곰탕2017-12-202020-04-10가입<NA>
46함박산농촌테마공원경상남도 창녕군 영산면 교리3982018-04-022020-03-09가입270
47우포늪 생태체험장 자연놀이터경상남도 창녕군 대합면 우포2로 3702019-05-292019-05-20가입<NA>
48코아루아파트 어린이놀이터경상남도 창녕군 창녕읍 말흘리375-12019-04-082019-04-26가입<NA>
49고기굽는마을 내 정글짐 놀이시설경상남도 창녕군 창녕읍 우포1대로 15612019-06-252019-07-16가입<NA>
50홍포어린이공원 물놀이장경상남도 창녕군 남지읍 마산리1003-52019-07-012019-08-19가입<NA>
51<NA><NA><NA><NA><NA><NA>