Overview

Dataset statistics

Number of variables7
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory63.1 B

Variable types

Categorical2
Numeric2
Text2
DateTime1

Dataset

Description대전광역시 중구 어린이놀이터 모래소독 현황에 대한 데이터로 순번, 공원이름, 공원위치, 모래소독면적, 모래교체시기, 모래소독시기 정보를 제공합니다.
Author대전광역시 중구
URLhttps://www.data.go.kr/data/15119427/fileData.do

Alerts

22년 소독 has constant value ""Constant
구분 is highly imbalanced (53.0%)Imbalance
연번 has unique valuesUnique
공원명 has unique valuesUnique
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:09:34.213516
Analysis finished2023-12-12 15:09:35.200700
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
어린이공원
22 
어린이놀이터
3 
소공원
 
1

Length

Max length6
Median length5
Mean length5.0384615
Min length3

Unique

Unique1 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
어린이공원 22
84.6%
어린이놀이터 3
 
11.5%
소공원 1
 
3.8%

Length

2023-12-13T00:09:35.516852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:09:35.939995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이공원 22
84.6%
어린이놀이터 3
 
11.5%
소공원 1
 
3.8%

연번
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T00:09:36.185174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2023-12-13T00:09:36.382222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

공원명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T00:09:36.662828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.4615385
Min length2

Characters and Unicode

Total characters64
Distinct characters43
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

Unique26 ?
Unique (%)100.0%

Sample

1st row선화
2nd row무릉
3rd row솔밭
4th row오류
5th row평리
ValueCountFrequency (%)
선화 1
 
3.8%
무릉 1
 
3.8%
상당 1
 
3.8%
사정 1
 
3.8%
중마을 1
 
3.8%
용머리 1
 
3.8%
안영3 1
 
3.8%
안영2 1
 
3.8%
안영1 1
 
3.8%
사정3 1
 
3.8%
Other values (16) 16
61.5%
2023-12-13T00:09:37.081922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 4
 
6.2%
정 4
 
6.2%
영 3
 
4.7%
리 3
 
4.7%
안 3
 
4.7%
1 3
 
4.7%
3 2
 
3.1%
당 2
 
3.1%
대 2
 
3.1%
평 2
 
3.1%
Other values (33) 36
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57
89.1%
Decimal Number 7
 
10.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 4
 
7.0%
정 4
 
7.0%
영 3
 
5.3%
리 3
 
5.3%
안 3
 
5.3%
당 2
 
3.5%
대 2
 
3.5%
평 2
 
3.5%
마 2
 
3.5%
중 2
 
3.5%
Other values (30) 30
52.6%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
3 2
28.6%
2 2
28.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57
89.1%
Common 7
 
10.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 4
 
7.0%
정 4
 
7.0%
영 3
 
5.3%
리 3
 
5.3%
안 3
 
5.3%
당 2
 
3.5%
대 2
 
3.5%
평 2
 
3.5%
마 2
 
3.5%
중 2
 
3.5%
Other values (30) 30
52.6%
Common
ValueCountFrequency (%)
1 3
42.9%
3 2
28.6%
2 2
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57
89.1%
ASCII 7
 
10.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 4
 
7.0%
정 4
 
7.0%
영 3
 
5.3%
리 3
 
5.3%
안 3
 
5.3%
당 2
 
3.5%
대 2
 
3.5%
평 2
 
3.5%
마 2
 
3.5%
중 2
 
3.5%
Other values (30) 30
52.6%
ASCII
ValueCountFrequency (%)
1 3
42.9%
3 2
28.6%
2 2
28.6%

위치
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T00:09:37.320797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.5384615
Min length6

Characters and Unicode

Total characters222
Distinct characters33
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

Unique26 ?
Unique (%)100.0%

Sample

1st row선화1동 368-2
2nd row중촌동 85
3rd row중촌동 102-3
4th row오류동 185-1
5th row태평1동 266-3
ValueCountFrequency (%)
사정동 5
 
9.6%
문화2동 5
 
9.6%
중촌동 3
 
5.8%
안영동 3
 
5.8%
산성동 2
 
3.8%
유천1동 2
 
3.8%
118-7 1
 
1.9%
360 1
 
1.9%
407 1
 
1.9%
488 1
 
1.9%
Other values (28) 28
53.8%
2023-12-13T00:09:37.799480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 26
11.7%
26
11.7%
1 17
 
7.7%
3 15
 
6.8%
- 15
 
6.8%
6 14
 
6.3%
2 14
 
6.3%
8 12
 
5.4%
4 11
 
5.0%
5 8
 
3.6%
Other values (23) 64
28.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104
46.8%
Other Letter 77
34.7%
Space Separator 26
 
11.7%
Dash Punctuation 15
 
6.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 26
33.8%
화 6
 
7.8%
문 5
 
6.5%
사 5
 
6.5%
정 5
 
6.5%
영 3
 
3.9%
안 3
 
3.9%
중 3
 
3.9%
촌 3
 
3.9%
성 2
 
2.6%
Other values (11) 16
20.8%
Decimal Number
ValueCountFrequency (%)
1 17
16.3%
3 15
14.4%
6 14
13.5%
2 14
13.5%
8 12
11.5%
4 11
10.6%
5 8
7.7%
7 6
 
5.8%
0 5
 
4.8%
9 2
 
1.9%
Space Separator
ValueCountFrequency (%)
26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 145
65.3%
Hangul 77
34.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 26
33.8%
화 6
 
7.8%
문 5
 
6.5%
사 5
 
6.5%
정 5
 
6.5%
영 3
 
3.9%
안 3
 
3.9%
중 3
 
3.9%
촌 3
 
3.9%
성 2
 
2.6%
Other values (11) 16
20.8%
Common
ValueCountFrequency (%)
26
17.9%
1 17
11.7%
3 15
10.3%
- 15
10.3%
6 14
9.7%
2 14
9.7%
8 12
8.3%
4 11
7.6%
5 8
 
5.5%
7 6
 
4.1%
Other values (2) 7
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 145
65.3%
Hangul 77
34.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 26
33.8%
화 6
 
7.8%
문 5
 
6.5%
사 5
 
6.5%
정 5
 
6.5%
영 3
 
3.9%
안 3
 
3.9%
중 3
 
3.9%
촌 3
 
3.9%
성 2
 
2.6%
Other values (11) 16
20.8%
ASCII
ValueCountFrequency (%)
26
17.9%
1 17
11.7%
3 15
10.3%
- 15
10.3%
6 14
9.7%
2 14
9.7%
8 12
8.3%
4 11
7.6%
5 8
 
5.5%
7 6
 
4.1%
Other values (2) 7
 
4.8%

면적
Real number (ℝ)

Distinct24
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean230.70385
Minimum4
Maximum757
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T00:09:37.999431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile39.325
Q1132.25
median207
Q3276.75
95-th percentile475.25
Maximum757
Range753
Interquartile range (IQR)144.5

Descriptive statistics

Standard deviation159.47456
Coefficient of variation (CV)0.6912523
Kurtosis3.6673811
Mean230.70385
Median Absolute Deviation (MAD)74
Skewness1.530158
Sum5998.3
Variance25432.136
MonotonicityNot monotonic
2023-12-13T00:09:38.150409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
188.0 2
 
7.7%
226.0 2
 
7.7%
112.0 1
 
3.8%
30.0 1
 
3.8%
130.0 1
 
3.8%
104.0 1
 
3.8%
139.0 1
 
3.8%
4.0 1
 
3.8%
259.0 1
 
3.8%
373.0 1
 
3.8%
Other values (14) 14
53.8%
ValueCountFrequency (%)
4.0 1
3.8%
30.0 1
3.8%
67.3 1
3.8%
85.0 1
3.8%
104.0 1
3.8%
112.0 1
3.8%
130.0 1
3.8%
139.0 1
3.8%
150.0 1
3.8%
174.0 1
3.8%
ValueCountFrequency (%)
757.0 1
3.8%
500.0 1
3.8%
401.0 1
3.8%
373.0 1
3.8%
370.0 1
3.8%
325.0 1
3.8%
278.0 1
3.8%
273.0 1
3.8%
259.0 1
3.8%
228.0 1
3.8%

모래교체
Date

Distinct14
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2012-04-01 00:00:00
Maximum2021-10-01 00:00:00
2023-12-13T00:09:38.259870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:38.454341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

22년 소독
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
2022-10-01
26 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-10-01
2nd row2022-10-01
3rd row2022-10-01
4th row2022-10-01
5th row2022-10-01

Common Values

ValueCountFrequency (%)
2022-10-01 26
100.0%

Length

2023-12-13T00:09:38.620856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:09:38.729676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-10-01 26
100.0%

Interactions

2023-12-13T00:09:34.726537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:34.490117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:34.844223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:34.600621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:09:38.790974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분연번공원명위치면적모래교체
구분1.0000.5111.0001.0000.5000.806
연번0.5111.0001.0001.0000.0000.000
공원명1.0001.0001.0001.0001.0001.000
위치1.0001.0001.0001.0001.0001.000
면적0.5000.0001.0001.0001.0000.864
모래교체0.8060.0001.0001.0000.8641.000
2023-12-13T00:09:38.920640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적구분
연번1.000-0.3630.331
면적-0.3631.0000.308
구분0.3310.3081.000

Missing values

2023-12-13T00:09:34.994887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:09:35.149480image/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

구분연번공원명위치면적모래교체22년 소독
0어린이공원1선화선화1동 368-2112.02012-11-012022-10-01
1어린이공원2무릉중촌동 85401.02021-10-012022-10-01
2어린이공원3솔밭중촌동 102-3226.02013-12-012022-10-01
3어린이공원4오류오류동 185-1226.02016-08-012022-10-01
4어린이공원5평리태평1동 266-3757.02014-12-012022-10-01
5어린이공원6강변태평2동 368325.02014-06-012022-10-01
6어린이공원7버드내유천1동 275-567.32018-04-012022-10-01
7어린이공원8중평유천1동 315-1273.02014-12-012022-10-01
8어린이공원9천근문화2동 458-14184.02013-12-012022-10-01
9어린이공원10옥미문화2동 484-8150.02017-08-012022-10-01
구분연번공원명위치면적모래교체22년 소독
16어린이공원17사정2사정동 407174.02012-04-012022-10-01
17어린이공원18사정3사정동 488227.02013-12-012022-10-01
18어린이공원19안영1안영동 650373.02013-07-012022-10-01
19어린이공원20안영2안영동 664188.02013-12-012022-10-01
20어린이공원21안영3안영동 694259.02016-08-012022-10-01
21어린이공원22용머리용두동 162-14.02018-08-012022-10-01
22어린이놀이터23중마을중촌동 281-10139.02017-08-012022-10-01
23어린이놀이터24사정사정동 433-29104.02017-08-012022-10-01
24어린이놀이터25상당사정동 344130.02014-06-012022-10-01
25소공원26목동1목동 363-130.02021-06-012022-10-01