Overview

Dataset statistics

Number of variables12
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory103.3 B

Variable types

Text4
Categorical3
Numeric3
DateTime2

Dataset

Description부산광역시중구_노인복지시설현황_20230707
Author부산광역시 중구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3072419

Alerts

시설유형 has constant value ""Constant
영업상태명 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
시설명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:01:26.216823
Analysis finished2023-12-10 17:01:28.942715
Duration2.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T02:01:29.157376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.0967742
Min length7

Characters and Unicode

Total characters282
Distinct characters70
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

Unique31 ?
Unique (%)100.0%

Sample

1st row중앙동 원로의집
2nd row동광동 원로의집
3rd row동광동할머니 원로의집
4th row대청공원 원로의집
5th row대청화목 원로의집
ValueCountFrequency (%)
원로의집 31
49.2%
영주충효 1
 
1.6%
보수대밭골 1
 
1.6%
부평동 1
 
1.6%
부평희망 1
 
1.6%
영주1동 1
 
1.6%
대명 1
 
1.6%
우남이채롬 1
 
1.6%
중앙동 1
 
1.6%
보수매화 1
 
1.6%
Other values (23) 23
36.5%
2023-12-11T02:01:29.819937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
 
11.3%
원 32
 
11.3%
로 31
 
11.0%
의 31
 
11.0%
집 31
 
11.0%
동 10
 
3.5%
보 8
 
2.8%
수 7
 
2.5%
대 7
 
2.5%
주 6
 
2.1%
Other values (60) 87
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 244
86.5%
Space Separator 32
 
11.3%
Decimal Number 6
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 32
13.1%
로 31
12.7%
의 31
12.7%
집 31
12.7%
동 10
 
4.1%
보 8
 
3.3%
수 7
 
2.9%
대 7
 
2.9%
주 6
 
2.5%
영 6
 
2.5%
Other values (56) 75
30.7%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
2 2
33.3%
9 1
 
16.7%
Space Separator
ValueCountFrequency (%)
32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 244
86.5%
Common 38
 
13.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 32
13.1%
로 31
12.7%
의 31
12.7%
집 31
12.7%
동 10
 
4.1%
보 8
 
3.3%
수 7
 
2.9%
대 7
 
2.9%
주 6
 
2.5%
영 6
 
2.5%
Other values (56) 75
30.7%
Common
ValueCountFrequency (%)
32
84.2%
1 3
 
7.9%
2 2
 
5.3%
9 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 244
86.5%
ASCII 38
 
13.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
84.2%
1 3
 
7.9%
2 2
 
5.3%
9 1
 
2.6%
Hangul
ValueCountFrequency (%)
원 32
13.1%
로 31
12.7%
의 31
12.7%
집 31
12.7%
동 10
 
4.1%
보 8
 
3.3%
수 7
 
2.9%
대 7
 
2.9%
주 6
 
2.5%
영 6
 
2.5%
Other values (56) 75
30.7%

시설유형
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
경로당
31 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경로당 31
100.0%

Length

2023-12-11T02:01:30.081502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:01:30.267477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경로당 31
100.0%

소재지도로명주소
Text

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T02:01:30.631589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length18.258065
Min length14

Characters and Unicode

Total characters566
Distinct characters45
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)87.1%

Sample

1st row부산광역시 중구 중앙대로115번길 1-6, 809호
2nd row부산광역시 중구 샘길 12
3rd row부산광역시 중구 동광길111번길 11
4th row부산광역시 중구 망양로355번길 37
5th row부산광역시 중구 대청북길 14
ValueCountFrequency (%)
부산광역시 31
24.6%
중구 31
24.6%
영주로 4
 
3.2%
6 4
 
3.2%
보수대로124번길 2
 
1.6%
21-7 2
 
1.6%
15 2
 
1.6%
법수길 2
 
1.6%
11 2
 
1.6%
망양로 2
 
1.6%
Other values (43) 44
34.9%
2023-12-11T02:01:31.351825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
17.0%
중 35
 
6.2%
구 34
 
6.0%
광 32
 
5.7%
부 31
 
5.5%
역 31
 
5.5%
시 31
 
5.5%
산 31
 
5.5%
1 28
 
4.9%
길 24
 
4.2%
Other values (35) 193
34.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 351
62.0%
Decimal Number 111
 
19.6%
Space Separator 96
 
17.0%
Dash Punctuation 6
 
1.1%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 35
10.0%
구 34
9.7%
광 32
9.1%
부 31
8.8%
역 31
8.8%
시 31
8.8%
산 31
8.8%
길 24
 
6.8%
로 23
 
6.6%
번 16
 
4.6%
Other values (22) 63
17.9%
Decimal Number
ValueCountFrequency (%)
1 28
25.2%
3 15
13.5%
2 15
13.5%
5 11
 
9.9%
7 11
 
9.9%
6 9
 
8.1%
9 8
 
7.2%
4 8
 
7.2%
0 3
 
2.7%
8 3
 
2.7%
Space Separator
ValueCountFrequency (%)
96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 351
62.0%
Common 215
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 35
10.0%
구 34
9.7%
광 32
9.1%
부 31
8.8%
역 31
8.8%
시 31
8.8%
산 31
8.8%
길 24
 
6.8%
로 23
 
6.6%
번 16
 
4.6%
Other values (22) 63
17.9%
Common
ValueCountFrequency (%)
96
44.7%
1 28
 
13.0%
3 15
 
7.0%
2 15
 
7.0%
5 11
 
5.1%
7 11
 
5.1%
6 9
 
4.2%
9 8
 
3.7%
4 8
 
3.7%
- 6
 
2.8%
Other values (3) 8
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 351
62.0%
ASCII 215
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
44.7%
1 28
 
13.0%
3 15
 
7.0%
2 15
 
7.0%
5 11
 
5.1%
7 11
 
5.1%
6 9
 
4.2%
9 8
 
3.7%
4 8
 
3.7%
- 6
 
2.8%
Other values (3) 8
 
3.7%
Hangul
ValueCountFrequency (%)
중 35
10.0%
구 34
9.7%
광 32
9.1%
부 31
8.8%
역 31
8.8%
시 31
8.8%
산 31
8.8%
길 24
 
6.8%
로 23
 
6.6%
번 16
 
4.6%
Other values (22) 63
17.9%

소재지지번주소
Text

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T02:01:31.699004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length19.129032
Min length15

Characters and Unicode

Total characters593
Distinct characters29
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

Unique25 ?
Unique (%)80.6%

Sample

1st row부산광역시 중구 대창동1가 54-67
2nd row부산광역시 중구 대청동1가 6-27
3rd row부산광역시 중구 동광동5가 3-306
4th row부산광역시 중구 대청동4가 75-329
5th row부산광역시 중구 대청동4가 75-167
ValueCountFrequency (%)
부산광역시 31
24.8%
중구 31
24.8%
보수동1가 8
 
6.4%
영주2동 8
 
6.4%
대청동4가 4
 
3.2%
영주1동 3
 
2.4%
86-1 2
 
1.6%
160 2
 
1.6%
보수동2가 2
 
1.6%
61-1 2
 
1.6%
Other values (32) 32
25.6%
2023-12-11T02:01:32.354663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
15.9%
1 41
 
6.9%
부 33
 
5.6%
산 32
 
5.4%
광 32
 
5.4%
동 32
 
5.4%
역 31
 
5.2%
중 31
 
5.2%
구 31
 
5.2%
시 31
 
5.2%
Other values (19) 205
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 331
55.8%
Decimal Number 142
23.9%
Space Separator 94
 
15.9%
Dash Punctuation 26
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 33
10.0%
산 32
9.7%
광 32
9.7%
동 32
9.7%
역 31
9.4%
중 31
9.4%
구 31
9.4%
시 31
9.4%
가 20
6.0%
영 11
 
3.3%
Other values (7) 47
14.2%
Decimal Number
ValueCountFrequency (%)
1 41
28.9%
2 25
17.6%
6 17
12.0%
4 13
 
9.2%
7 11
 
7.7%
3 9
 
6.3%
5 8
 
5.6%
8 7
 
4.9%
0 6
 
4.2%
9 5
 
3.5%
Space Separator
ValueCountFrequency (%)
94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 331
55.8%
Common 262
44.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 33
10.0%
산 32
9.7%
광 32
9.7%
동 32
9.7%
역 31
9.4%
중 31
9.4%
구 31
9.4%
시 31
9.4%
가 20
6.0%
영 11
 
3.3%
Other values (7) 47
14.2%
Common
ValueCountFrequency (%)
94
35.9%
1 41
15.6%
- 26
 
9.9%
2 25
 
9.5%
6 17
 
6.5%
4 13
 
5.0%
7 11
 
4.2%
3 9
 
3.4%
5 8
 
3.1%
8 7
 
2.7%
Other values (2) 11
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 331
55.8%
ASCII 262
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
35.9%
1 41
15.6%
- 26
 
9.9%
2 25
 
9.5%
6 17
 
6.5%
4 13
 
5.0%
7 11
 
4.2%
3 9
 
3.4%
5 8
 
3.1%
8 7
 
2.7%
Other values (2) 11
 
4.2%
Hangul
ValueCountFrequency (%)
부 33
10.0%
산 32
9.7%
광 32
9.7%
동 32
9.7%
역 31
9.4%
중 31
9.4%
구 31
9.4%
시 31
9.4%
가 20
6.0%
영 11
 
3.3%
Other values (7) 47
14.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.108056
Minimum35.100362
Maximum35.114493
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T02:01:32.600357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.100362
5-th percentile35.103059
Q135.105266
median35.107168
Q335.111716
95-th percentile35.113754
Maximum35.114493
Range0.014131006
Interquartile range (IQR)0.0064496927

Descriptive statistics

Standard deviation0.0037834716
Coefficient of variation (CV)0.00010776648
Kurtosis-0.85918392
Mean35.108056
Median Absolute Deviation (MAD)0.0026224487
Skewness0.1340302
Sum1088.3497
Variance1.4314657 × 10-5
MonotonicityNot monotonic
2023-12-11T02:01:32.850573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
35.1042226653 2
 
6.5%
35.1060440155 2
 
6.5%
35.1078467905 1
 
3.2%
35.1003620024 1
 
3.2%
35.1097901022 1
 
3.2%
35.1118638439 1
 
3.2%
35.1138551357 1
 
3.2%
35.1144930086 1
 
3.2%
35.1122445541 1
 
3.2%
35.1136527983 1
 
3.2%
Other values (19) 19
61.3%
ValueCountFrequency (%)
35.1003620024 1
3.2%
35.1018953394 1
3.2%
35.1042226653 2
6.5%
35.1045318407 1
3.2%
35.1045913935 1
3.2%
35.1048238068 1
3.2%
35.1052184117 1
3.2%
35.1053132635 1
3.2%
35.1060440155 2
6.5%
35.1062727027 1
3.2%
ValueCountFrequency (%)
35.1144930086 1
3.2%
35.1138551357 1
3.2%
35.1136527983 1
3.2%
35.1136158443 1
3.2%
35.1132148418 1
3.2%
35.1122445541 1
3.2%
35.1118638439 1
3.2%
35.1118144901 1
3.2%
35.1116165706 1
3.2%
35.1108737521 1
3.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.02912
Minimum129.02238
Maximum129.03583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T02:01:33.142533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.02238
5-th percentile129.02281
Q1129.02573
median129.02971
Q3129.03154
95-th percentile129.03513
Maximum129.03583
Range0.013455327
Interquartile range (IQR)0.0058105194

Descriptive statistics

Standard deviation0.0039169108
Coefficient of variation (CV)3.0356797 × 10-5
Kurtosis-0.93909668
Mean129.02912
Median Absolute Deviation (MAD)0.0032317319
Skewness-3.548769 × 10-5
Sum3999.9028
Variance1.534219 × 10-5
MonotonicityNot monotonic
2023-12-11T02:01:33.397603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
129.0252901597 2
 
6.5%
129.0228145519 2
 
6.5%
129.0358337725 1
 
3.2%
129.0267363677 1
 
3.2%
129.0301977833 1
 
3.2%
129.0295545923 1
 
3.2%
129.0333729719 1
 
3.2%
129.0311256196 1
 
3.2%
129.0297988388 1
 
3.2%
129.0299775556 1
 
3.2%
Other values (19) 19
61.3%
ValueCountFrequency (%)
129.0223784455 1
3.2%
129.0228145519 2
6.5%
129.0242962959 1
3.2%
129.0249967663 1
3.2%
129.0252825465 1
3.2%
129.0252901597 2
6.5%
129.0261601119 1
3.2%
129.0267363677 1
3.2%
129.0268552972 1
3.2%
129.0273274032 1
3.2%
ValueCountFrequency (%)
129.0358337725 1
3.2%
129.0352534838 1
3.2%
129.0350040536 1
3.2%
129.0347868525 1
3.2%
129.0341199298 1
3.2%
129.0333729719 1
3.2%
129.032937083 1
3.2%
129.0319456908 1
3.2%
129.0311256196 1
3.2%
129.0310528471 1
3.2%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
영업
31 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 31
100.0%

Length

2023-12-11T02:01:33.676986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:01:33.898039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 31
100.0%

전화번호
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T02:01:34.248371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters372
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row051-468-9982
2nd row051-463-1936
3rd row051-468-5226
4th row051-468-4019
5th row051-463-1535
ValueCountFrequency (%)
051-468-9982 1
 
3.2%
051-248-2640 1
 
3.2%
051-462-4331 1
 
3.2%
051-462-4552 1
 
3.2%
051-463-7999 1
 
3.2%
051-441-7485 1
 
3.2%
051-468-9590 1
 
3.2%
051-468-8094 1
 
3.2%
051-469-5666 1
 
3.2%
051-469-1788 1
 
3.2%
Other values (21) 21
67.7%
2023-12-11T02:01:34.989066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 62
16.7%
5 54
14.5%
1 47
12.6%
0 43
11.6%
4 37
9.9%
6 33
8.9%
2 26
7.0%
3 25
6.7%
8 19
 
5.1%
9 18
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 310
83.3%
Dash Punctuation 62
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 54
17.4%
1 47
15.2%
0 43
13.9%
4 37
11.9%
6 33
10.6%
2 26
8.4%
3 25
8.1%
8 19
 
6.1%
9 18
 
5.8%
7 8
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 372
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 62
16.7%
5 54
14.5%
1 47
12.6%
0 43
11.6%
4 37
9.9%
6 33
8.9%
2 26
7.0%
3 25
6.7%
8 19
 
5.1%
9 18
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 62
16.7%
5 54
14.5%
1 47
12.6%
0 43
11.6%
4 37
9.9%
6 33
8.9%
2 26
7.0%
3 25
6.7%
8 19
 
5.1%
9 18
 
4.8%

건립일자
Date

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum1957-06-02 00:00:00
Maximum2020-03-05 00:00:00
2023-12-11T02:01:35.271662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:01:35.580121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

건물면적
Real number (ℝ)

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.23871
Minimum26.2
Maximum133.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T02:01:35.891771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26.2
5-th percentile39.55
Q146.7
median58.1
Q385.55
95-th percentile122.5
Maximum133.6
Range107.4
Interquartile range (IQR)38.85

Descriptive statistics

Standard deviation28.348588
Coefficient of variation (CV)0.42161113
Kurtosis0.065524439
Mean67.23871
Median Absolute Deviation (MAD)13.3
Skewness0.99750227
Sum2084.4
Variance803.64245
MonotonicityNot monotonic
2023-12-11T02:01:36.122569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
44.8 2
 
6.5%
66.1 1
 
3.2%
113.4 1
 
3.2%
53.3 1
 
3.2%
109.5 1
 
3.2%
131.6 1
 
3.2%
49.6 1
 
3.2%
48.8 1
 
3.2%
50.8 1
 
3.2%
60.8 1
 
3.2%
Other values (20) 20
64.5%
ValueCountFrequency (%)
26.2 1
3.2%
37.8 1
3.2%
41.3 1
3.2%
43.7 1
3.2%
44.8 2
6.5%
45.0 1
3.2%
45.6 1
3.2%
47.8 1
3.2%
48.8 1
3.2%
49.6 1
3.2%
ValueCountFrequency (%)
133.6 1
3.2%
131.6 1
3.2%
113.4 1
3.2%
109.5 1
3.2%
105.9 1
3.2%
94.8 1
3.2%
93.8 1
3.2%
87.7 1
3.2%
83.4 1
3.2%
73.0 1
3.2%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
부산광역시 중구청
31 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 중구청 31
100.0%

Length

2023-12-11T02:01:36.372684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:01:36.632892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 31
50.0%
중구청 31
50.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2023-07-07 00:00:00
Maximum2023-07-07 00:00:00
2023-12-11T02:01:36.817420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:01:37.018688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T02:01:27.853995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:01:26.834411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:01:27.331628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:01:28.053847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:01:26.989241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:01:27.522187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:01:28.226998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:01:27.166541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:01:27.682760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:01:37.186513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명소재지도로명주소소재지지번주소위도경도전화번호건립일자건물면적
시설명1.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0000.9720.865
소재지지번주소1.0001.0001.0001.0001.0001.0000.9680.805
위도1.0001.0001.0001.0000.4701.0000.0000.000
경도1.0001.0001.0000.4701.0001.0000.9270.443
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
건립일자1.0000.9720.9680.0000.9271.0001.0001.000
건물면적1.0000.8650.8050.0000.4431.0001.0001.000
2023-12-11T02:01:37.433173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도건물면적
위도1.0000.612-0.018
경도0.6121.000-0.053
건물면적-0.018-0.0531.000

Missing values

2023-12-11T02:01:28.459042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:01:28.819447image/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

시설명시설유형소재지도로명주소소재지지번주소위도경도영업상태명전화번호건립일자건물면적관리기관명데이터기준일자
0중앙동 원로의집경로당부산광역시 중구 중앙대로115번길 1-6, 809호부산광역시 중구 대창동1가 54-6735.107847129.035834영업051-468-99822012-11-1366.1부산광역시 중구청2023-07-07
1동광동 원로의집경로당부산광역시 중구 샘길 12부산광역시 중구 대청동1가 6-2735.106433129.032937영업051-463-19361971-04-2583.4부산광역시 중구청2023-07-07
2동광동할머니 원로의집경로당부산광역시 중구 동광길111번길 11부산광역시 중구 동광동5가 3-30635.107908129.035004영업051-468-52262000-03-2526.2부산광역시 중구청2023-07-07
3대청공원 원로의집경로당부산광역시 중구 망양로355번길 37부산광역시 중구 대청동4가 75-32935.106273129.02887영업051-468-40191981-05-3045.0부산광역시 중구청2023-07-07
4대청화목 원로의집경로당부산광역시 중구 대청북길 14부산광역시 중구 대청동4가 75-16735.105313129.028792영업051-463-15351980-04-2450.5부산광역시 중구청2023-07-07
5대청만우 원로의집경로당부산광역시 중구 중구로91번안길 15부산광역시 중구 대청동4가 79-135.105218129.029732영업051-469-80701980-08-20105.9부산광역시 중구청2023-07-07
6행복 원로의집경로당부산광역시 중구 대청로99번길 22부산광역시 중구 대청동2가 1-835.104532129.031053영업051-463-99332007-12-0693.8부산광역시 중구청2023-07-07
7대청망양 원로의집경로당부산광역시 중구 망양로335번길 6부산광역시 중구 대청동4가 1-8235.107905129.029705영업051-463-33562020-03-0587.7부산광역시 중구청2023-07-07
8보수새마을 원로의집경로당부산광역시 중구 망양로319번길 24부산광역시 중구 보수동1가 산 3-14835.106383129.027327영업051-253-16761982-02-2837.8부산광역시 중구청2023-07-07
9보수죽화 원로의집경로당부산광역시 중구 보수대로144번길 15부산광역시 중구 보수동1가 2-67035.108456129.024296영업051-255-36341970-06-2845.6부산광역시 중구청2023-07-07
시설명시설유형소재지도로명주소소재지지번주소위도경도영업상태명전화번호건립일자건물면적관리기관명데이터기준일자
21대명 원로의집경로당부산광역시 중구 중구로 182-6, 303호부산광역시 중구 영주1동 671-1435.110874129.034787영업051-442-15552013-03-1141.3부산광역시 중구청2023-07-07
22우남이채롬 원로의집경로당부산광역시 중구 초량상로 13부산광역시 중구 영주1동 535.113616129.035253영업051-469-17882007-10-1843.7부산광역시 중구청2023-07-07
23영주충효 원로의집경로당부산광역시 중구 동영로73번길 3부산광역시 중구 영주2동 278-235.111814129.031946영업051-469-56662006-09-2858.3부산광역시 중구청2023-07-07
24영주금호타운 원로의집경로당부산광역시 중구 영주로 49부산광역시 중구 영주2동 16135.111617129.030506영업051-468-80941998-08-3160.8부산광역시 중구청2023-07-07
25동아 9블럭 원로의집경로당부산광역시 중구 영주로 73부산광역시 중구 영주2동 9235.113653129.029978영업051-468-95902000-07-2450.8부산광역시 중구청2023-07-07
26동아11블럭 원로의집경로당부산광역시 중구 영주로 65부산광역시 중구 영주2동 16035.112245129.029799영업051-441-74852000-10-2848.8부산광역시 중구청2023-07-07
27은하아파트 원로의집경로당부산광역시 중구 영주로 87부산광역시 중구 영주2동 91-135.114493129.031126영업051-463-79992008-12-0149.6부산광역시 중구청2023-07-07
28영주2동 원로의집경로당부산광역시 중구 영초길 103부산광역시 중구 영주2동 72-435.113855129.033373영업051-462-45521988-09-23131.6부산광역시 중구청2023-07-07
29영주아파트 원로의집경로당부산광역시 중구 망양로 396부산광역시 중구 영주2동 16035.111864129.029555영업051-462-43311977-06-20109.5부산광역시 중구청2023-07-07
30영주자유 원로의집경로당부산광역시 중구 망양로 371-3부산광역시 중구 영주2동 239-2635.10979129.030198영업051-469-22232006-09-2853.3부산광역시 중구청2023-07-07