Overview

Dataset statistics

Number of variables8
Number of observations97
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory66.4 B

Variable types

Numeric1
Text2
Categorical5

Dataset

Description폭염예방을 위하여 설치된 부산광역시 부산진구 그날막에 대한 데이터로 관리번호, 종류, 설치장소 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15118142/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
연번 is highly overall correlated with 읍면동High correlation
종류 is highly overall correlated with 읍면동 and 1 other fieldsHigh correlation
읍면동 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
설치일자 is highly overall correlated with 종류High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:49:14.736064
Analysis finished2023-12-12 06:49:16.084415
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49
Minimum1
Maximum97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2023-12-12T15:49:16.178789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.8
Q125
median49
Q373
95-th percentile92.2
Maximum97
Range96
Interquartile range (IQR)48

Descriptive statistics

Standard deviation28.145456
Coefficient of variation (CV)0.57439705
Kurtosis-1.2
Mean49
Median Absolute Deviation (MAD)24
Skewness0
Sum4753
Variance792.16667
MonotonicityStrictly increasing
2023-12-12T15:49:16.334428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
74 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
66 1
 
1.0%
65 1
 
1.0%
Other values (87) 87
89.7%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%
90 1
1.0%
89 1
1.0%
88 1
1.0%

관리번호
Text

Distinct96
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2023-12-12T15:49:16.655701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.9072165
Min length6

Characters and Unicode

Total characters670
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)97.9%

Sample

1st row부산진구-2
2nd row부산진구-3
3rd row부산진구-4
4th row부산진구-6
5th row부산진구-13
ValueCountFrequency (%)
부산진구-96 2
 
2.1%
부산진구-2 1
 
1.0%
부산진구-95 1
 
1.0%
부산진구-93 1
 
1.0%
부산진구-74 1
 
1.0%
부산진구-34 1
 
1.0%
부산진구-27 1
 
1.0%
부산진구-33 1
 
1.0%
부산진구-77 1
 
1.0%
부산진구-87 1
 
1.0%
Other values (86) 86
88.7%
2023-12-12T15:49:17.149478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 97
14.5%
산 97
14.5%
진 97
14.5%
구 97
14.5%
- 97
14.5%
6 21
 
3.1%
2 20
 
3.0%
4 20
 
3.0%
3 20
 
3.0%
5 20
 
3.0%
Other values (5) 84
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 388
57.9%
Decimal Number 185
27.6%
Dash Punctuation 97
 
14.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 21
11.4%
2 20
10.8%
4 20
10.8%
3 20
10.8%
5 20
10.8%
7 20
10.8%
1 19
10.3%
9 18
9.7%
8 18
9.7%
0 9
4.9%
Other Letter
ValueCountFrequency (%)
부 97
25.0%
산 97
25.0%
진 97
25.0%
구 97
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 388
57.9%
Common 282
42.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 97
34.4%
6 21
 
7.4%
2 20
 
7.1%
4 20
 
7.1%
3 20
 
7.1%
5 20
 
7.1%
7 20
 
7.1%
1 19
 
6.7%
9 18
 
6.4%
8 18
 
6.4%
Hangul
ValueCountFrequency (%)
부 97
25.0%
산 97
25.0%
진 97
25.0%
구 97
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 388
57.9%
ASCII 282
42.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 97
25.0%
산 97
25.0%
진 97
25.0%
구 97
25.0%
ASCII
ValueCountFrequency (%)
- 97
34.4%
6 21
 
7.4%
2 20
 
7.1%
4 20
 
7.1%
3 20
 
7.1%
5 20
 
7.1%
7 20
 
7.1%
1 19
 
6.7%
9 18
 
6.4%
8 18
 
6.4%

종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
스마트
59 
고정형
33 
스마트형
 
5

Length

Max length4
Median length3
Mean length3.0515464
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고정형
2nd row고정형
3rd row고정형
4th row고정형
5th row스마트

Common Values

ValueCountFrequency (%)
스마트 59
60.8%
고정형 33
34.0%
스마트형 5
 
5.2%

Length

2023-12-12T15:49:17.323422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:49:17.424806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
스마트 59
60.8%
고정형 33
34.0%
스마트형 5
 
5.2%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
부산광역시
97 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 97
100.0%

Length

2023-12-12T15:49:17.540386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:49:17.644099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 97
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
부산진구
97 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산진구 97
100.0%

Length

2023-12-12T15:49:17.748721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:49:17.855350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산진구 97
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Memory size908.0 B
전포2동
16 
전포1동
11 
부전1동
10 
부암1동
9 
연지동
8 
Other values (13)
43 

Length

Max length4
Median length4
Mean length3.9072165
Min length3

Unique

Unique6 ?
Unique (%)6.2%

Sample

1st row부전1동
2nd row부전1동
3rd row부전1동
4th row부전1동
5th row부전1동

Common Values

ValueCountFrequency (%)
전포2동 16
16.5%
전포1동 11
11.3%
부전1동 10
10.3%
부암1동 9
9.3%
연지동 8
8.2%
개금1동 8
8.2%
범천2동 7
7.2%
양정1동 7
7.2%
가야1동 6
 
6.2%
가야2동 5
 
5.2%
Other values (8) 10
10.3%

Length

2023-12-12T15:49:17.975549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전포2동 16
16.5%
전포1동 11
11.3%
부전1동 10
10.3%
부암1동 9
9.3%
연지동 8
8.2%
개금1동 8
8.2%
범천2동 7
7.2%
양정1동 7
7.2%
가야1동 6
 
6.2%
가야2동 5
 
5.2%
Other values (8) 10
10.3%

설치장소명
Text

Distinct93
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size908.0 B
2023-12-12T15:49:18.185638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length11.958763
Min length6

Characters and Unicode

Total characters1160
Distinct characters213
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)92.8%

Sample

1st row시민공원 남문
2nd row시민공원 남문
3rd row시민공원 남문
4th row시민공원 입구(CU 편의점)
5th row펫월드 시민공원점
ValueCountFrequency (%)
앞 49
 
18.1%
교통섬 16
 
5.9%
횡단보도 15
 
5.6%
맞은편 11
 
4.1%
시민공원 8
 
3.0%
건너편 4
 
1.5%
옆 3
 
1.1%
남문 3
 
1.1%
서면 3
 
1.1%
삼전교차로 3
 
1.1%
Other values (130) 155
57.4%
2023-12-12T15:49:18.592823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
175
 
15.1%
앞 49
 
4.2%
교 26
 
2.2%
도 19
 
1.6%
보 19
 
1.6%
편 19
 
1.6%
은 18
 
1.6%
횡 17
 
1.5%
원 17
 
1.5%
단 17
 
1.5%
Other values (203) 784
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 926
79.8%
Space Separator 175
 
15.1%
Decimal Number 32
 
2.8%
Uppercase Letter 20
 
1.7%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%
Dash Punctuation 2
 
0.2%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 49
 
5.3%
교 26
 
2.8%
도 19
 
2.1%
보 19
 
2.1%
편 19
 
2.1%
은 18
 
1.9%
횡 17
 
1.8%
원 17
 
1.8%
단 17
 
1.8%
로 16
 
1.7%
Other values (181) 709
76.6%
Uppercase Letter
ValueCountFrequency (%)
G 5
25.0%
S 3
15.0%
C 3
15.0%
L 3
15.0%
U 2
 
10.0%
D 1
 
5.0%
B 1
 
5.0%
K 1
 
5.0%
N 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
2 10
31.2%
5 6
18.8%
1 4
 
12.5%
3 4
 
12.5%
4 3
 
9.4%
7 2
 
6.2%
0 2
 
6.2%
6 1
 
3.1%
Space Separator
ValueCountFrequency (%)
175
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 926
79.8%
Common 213
 
18.4%
Latin 21
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 49
 
5.3%
교 26
 
2.8%
도 19
 
2.1%
보 19
 
2.1%
편 19
 
2.1%
은 18
 
1.9%
횡 17
 
1.8%
원 17
 
1.8%
단 17
 
1.8%
로 16
 
1.7%
Other values (181) 709
76.6%
Common
ValueCountFrequency (%)
175
82.2%
2 10
 
4.7%
5 6
 
2.8%
1 4
 
1.9%
3 4
 
1.9%
4 3
 
1.4%
) 2
 
0.9%
( 2
 
0.9%
7 2
 
0.9%
- 2
 
0.9%
Other values (2) 3
 
1.4%
Latin
ValueCountFrequency (%)
G 5
23.8%
S 3
14.3%
C 3
14.3%
L 3
14.3%
U 2
 
9.5%
e 1
 
4.8%
D 1
 
4.8%
B 1
 
4.8%
K 1
 
4.8%
N 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 926
79.8%
ASCII 234
 
20.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
175
74.8%
2 10
 
4.3%
5 6
 
2.6%
G 5
 
2.1%
1 4
 
1.7%
3 4
 
1.7%
S 3
 
1.3%
C 3
 
1.3%
L 3
 
1.3%
4 3
 
1.3%
Other values (12) 18
 
7.7%
Hangul
ValueCountFrequency (%)
앞 49
 
5.3%
교 26
 
2.8%
도 19
 
2.1%
보 19
 
2.1%
편 19
 
2.1%
은 18
 
1.9%
횡 17
 
1.8%
원 17
 
1.8%
단 17
 
1.8%
로 16
 
1.7%
Other values (181) 709
76.6%

설치일자
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size908.0 B
2017-08-11
10 
2022-09-27
10 
2020-08-12
9 
2018-08-31
9 
2019-08-21
8 
Other values (16)
51 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique3 ?
Unique (%)3.1%

Sample

1st row2017-08-11
2nd row2017-08-11
3rd row2017-08-11
4th row2017-08-11
5th row2020-08-12

Common Values

ValueCountFrequency (%)
2017-08-11 10
 
10.3%
2022-09-27 10
 
10.3%
2020-08-12 9
 
9.3%
2018-08-31 9
 
9.3%
2019-08-21 8
 
8.2%
2022-08-19 6
 
6.2%
2023-06-20 5
 
5.2%
2021-07-13 5
 
5.2%
2018-09-30 5
 
5.2%
2022-11-11 4
 
4.1%
Other values (11) 26
26.8%

Length

2023-12-12T15:49:18.751588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-08-11 10
 
10.3%
2022-09-27 10
 
10.3%
2020-08-12 9
 
9.3%
2018-08-31 9
 
9.3%
2019-08-21 8
 
8.2%
2022-08-19 6
 
6.2%
2023-06-20 5
 
5.2%
2021-07-13 5
 
5.2%
2018-09-30 5
 
5.2%
2021-09-15 4
 
4.1%
Other values (11) 26
26.8%

Interactions

2023-12-12T15:49:15.688488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:49:18.851698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관리번호종류읍면동설치장소명설치일자
연번1.0000.9430.6500.9760.9600.527
관리번호0.9431.0001.0000.9870.9970.974
종류0.6501.0001.0000.8561.0000.899
읍면동0.9760.9870.8561.0000.9460.741
설치장소명0.9600.9971.0000.9461.0000.997
설치일자0.5270.9740.8990.7410.9971.000
2023-12-12T15:49:18.982402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치일자종류읍면동
설치일자1.0000.6060.305
종류0.6061.0000.556
읍면동0.3050.5561.000
2023-12-12T15:49:19.096055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종류읍면동설치일자
연번1.0000.4780.8370.204
종류0.4781.0000.5560.606
읍면동0.8370.5561.0000.305
설치일자0.2040.6060.3051.000

Missing values

2023-12-12T15:49:15.826214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:49:16.012145image/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

연번관리번호종류시도시군구읍면동설치장소명설치일자
01부산진구-2고정형부산광역시부산진구부전1동시민공원 남문2017-08-11
12부산진구-3고정형부산광역시부산진구부전1동시민공원 남문2017-08-11
23부산진구-4고정형부산광역시부산진구부전1동시민공원 남문2017-08-11
34부산진구-6고정형부산광역시부산진구부전1동시민공원 입구(CU 편의점)2017-08-11
45부산진구-13스마트부산광역시부산진구부전1동펫월드 시민공원점2020-08-12
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