Overview

Dataset statistics

Number of variables13
Number of observations83
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory109.6 B

Variable types

Text3
Categorical4
Numeric4
Boolean1
DateTime1

Dataset

Description부산광역시금정구_민방위대피시설_20220405
Author부산광역시 금정구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15099709

Alerts

개방여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
관리기관전화번호 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
관리기관명 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 민방위대피시설구분 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 민방위대피시설구분 and 2 other fieldsHigh correlation
민방위대피시설면적 is highly overall correlated with 대피가능인원수High correlation
대피가능인원수 is highly overall correlated with 민방위대피시설면적High correlation
민방위대피시설구분 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
평시활용유형 is highly overall correlated with 관리기관전화번호 and 1 other fieldsHigh correlation
민방위대피시설구분 is highly imbalanced (90.6%)Imbalance
평시활용유형 is highly imbalanced (62.3%)Imbalance
민방위대피시설명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
소재지지번주소 has unique valuesUnique
위도 has unique valuesUnique
민방위대피시설면적 has unique valuesUnique
대피가능인원수 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:02:40.563535
Analysis finished2023-12-10 17:02:44.033892
Duration3.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

민방위대피시설명
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-11T02:02:44.273246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.9277108
Min length4

Characters and Unicode

Total characters658
Distinct characters164
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)100.0%

Sample

1st row동성교회
2nd row파크랜드
3rd row세웅종합병원
4th row서2동 행정복지센터
5th row삼한여명아파트
ValueCountFrequency (%)
행정복지센터 7
 
5.7%
지하 6
 
4.9%
부곡4동 5
 
4.1%
장전2동 3
 
2.5%
청룡동 3
 
2.5%
아파트 3
 
2.5%
부곡2동 3
 
2.5%
서3동 2
 
1.6%
경보아파트 2
 
1.6%
경동아파트 2
 
1.6%
Other values (82) 86
70.5%
2023-12-11T02:02:44.779728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
5.9%
동 37
 
5.6%
파 30
 
4.6%
아 29
 
4.4%
트 28
 
4.3%
지 24
 
3.6%
부 17
 
2.6%
금 17
 
2.6%
정 15
 
2.3%
하 13
 
2.0%
Other values (154) 409
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 588
89.4%
Space Separator 39
 
5.9%
Decimal Number 21
 
3.2%
Uppercase Letter 6
 
0.9%
Lowercase Letter 2
 
0.3%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 37
 
6.3%
파 30
 
5.1%
아 29
 
4.9%
트 28
 
4.8%
지 24
 
4.1%
부 17
 
2.9%
금 17
 
2.9%
정 15
 
2.6%
하 13
 
2.2%
행 11
 
1.9%
Other values (142) 367
62.4%
Decimal Number
ValueCountFrequency (%)
2 9
42.9%
1 5
23.8%
4 5
23.8%
3 2
 
9.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
50.0%
G 2
33.3%
K 1
 
16.7%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 588
89.4%
Common 62
 
9.4%
Latin 8
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 37
 
6.3%
파 30
 
5.1%
아 29
 
4.9%
트 28
 
4.8%
지 24
 
4.1%
부 17
 
2.9%
금 17
 
2.9%
정 15
 
2.6%
하 13
 
2.2%
행 11
 
1.9%
Other values (142) 367
62.4%
Common
ValueCountFrequency (%)
39
62.9%
2 9
 
14.5%
1 5
 
8.1%
4 5
 
8.1%
3 2
 
3.2%
( 1
 
1.6%
) 1
 
1.6%
Latin
ValueCountFrequency (%)
S 3
37.5%
G 2
25.0%
k 1
 
12.5%
s 1
 
12.5%
K 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 588
89.4%
ASCII 70
 
10.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
55.7%
2 9
 
12.9%
1 5
 
7.1%
4 5
 
7.1%
S 3
 
4.3%
G 2
 
2.9%
3 2
 
2.9%
k 1
 
1.4%
s 1
 
1.4%
( 1
 
1.4%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
동 37
 
6.3%
파 30
 
5.1%
아 29
 
4.9%
트 28
 
4.8%
지 24
 
4.1%
부 17
 
2.9%
금 17
 
2.9%
정 15
 
2.6%
하 13
 
2.2%
행 11
 
1.9%
Other values (142) 367
62.4%

민방위대피시설구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size796.0 B
공공용
82 
공고용
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
공공용 82
98.8%
공고용 1
 
1.2%

Length

2023-12-11T02:02:44.935609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:45.055372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 82
98.8%
공고용 1
 
1.2%

소재지도로명주소
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-11T02:02:45.384701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length18.39759
Min length15

Characters and Unicode

Total characters1527
Distinct characters73
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

Unique83 ?
Unique (%)100.0%

Sample

1st row부산광역시 금정구 서부로 72
2nd row부산광역시 금정구 반송로 365
3rd row부산광역시 금정구 서동로 162
4th row부산광역시 금정구 서동중심로 33
5th row부산광역시 금정구 중군진로 27
ValueCountFrequency (%)
부산광역시 83
24.9%
금정구 83
24.9%
중앙대로 11
 
3.3%
부곡로 7
 
2.1%
금단로 6
 
1.8%
금강로 6
 
1.8%
21 3
 
0.9%
수림로 3
 
0.9%
서동로 3
 
0.9%
반송로 3
 
0.9%
Other values (110) 126
37.7%
2023-12-11T02:02:45.914850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
251
16.4%
금 103
 
6.7%
부 98
 
6.4%
산 88
 
5.8%
정 88
 
5.8%
구 85
 
5.6%
시 84
 
5.5%
광 83
 
5.4%
역 83
 
5.4%
로 82
 
5.4%
Other values (63) 482
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1000
65.5%
Decimal Number 263
 
17.2%
Space Separator 251
 
16.4%
Dash Punctuation 10
 
0.7%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 103
10.3%
부 98
9.8%
산 88
8.8%
정 88
8.8%
구 85
8.5%
시 84
8.4%
광 83
8.3%
역 83
8.3%
로 82
8.2%
길 20
 
2.0%
Other values (48) 186
18.6%
Decimal Number
ValueCountFrequency (%)
1 46
17.5%
2 39
14.8%
7 32
12.2%
3 31
11.8%
5 23
8.7%
9 22
8.4%
6 20
7.6%
0 20
7.6%
4 15
 
5.7%
8 15
 
5.7%
Space Separator
ValueCountFrequency (%)
251
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1000
65.5%
Common 527
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 103
10.3%
부 98
9.8%
산 88
8.8%
정 88
8.8%
구 85
8.5%
시 84
8.4%
광 83
8.3%
역 83
8.3%
로 82
8.2%
길 20
 
2.0%
Other values (48) 186
18.6%
Common
ValueCountFrequency (%)
251
47.6%
1 46
 
8.7%
2 39
 
7.4%
7 32
 
6.1%
3 31
 
5.9%
5 23
 
4.4%
9 22
 
4.2%
6 20
 
3.8%
0 20
 
3.8%
4 15
 
2.8%
Other values (5) 28
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1000
65.5%
ASCII 527
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
251
47.6%
1 46
 
8.7%
2 39
 
7.4%
7 32
 
6.1%
3 31
 
5.9%
5 23
 
4.4%
9 22
 
4.2%
6 20
 
3.8%
0 20
 
3.8%
4 15
 
2.8%
Other values (5) 28
 
5.3%
Hangul
ValueCountFrequency (%)
금 103
10.3%
부 98
9.8%
산 88
8.8%
정 88
8.8%
구 85
8.5%
시 84
8.4%
광 83
8.3%
역 83
8.3%
로 82
8.2%
길 20
 
2.0%
Other values (48) 186
18.6%

소재지지번주소
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-11T02:02:46.271748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length18.53012
Min length15

Characters and Unicode

Total characters1538
Distinct characters36
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

Unique83 ?
Unique (%)100.0%

Sample

1st row부산광역시 금정구 서동 150-12
2nd row부산광역시 금정구 서동 219-2
3rd row부산광역시 금정구 서동 199-16
4th row부산광역시 금정구 서동 297-446
5th row부산광역시 금정구 서동 228-1
ValueCountFrequency (%)
부산광역시 83
25.0%
금정구 83
25.0%
부곡동 20
 
6.0%
남산동 15
 
4.5%
서동 14
 
4.2%
장전동 12
 
3.6%
구서동 7
 
2.1%
청룡동 7
 
2.1%
금사동 4
 
1.2%
금성동 2
 
0.6%
Other values (85) 85
25.6%
2023-12-11T02:02:46.843637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
249
16.2%
부 103
 
6.7%
산 98
 
6.4%
구 91
 
5.9%
금 89
 
5.8%
광 83
 
5.4%
역 83
 
5.4%
시 83
 
5.4%
정 83
 
5.4%
동 83
 
5.4%
Other values (26) 493
32.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 902
58.6%
Decimal Number 326
 
21.2%
Space Separator 249
 
16.2%
Dash Punctuation 61
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 103
11.4%
산 98
10.9%
구 91
10.1%
금 89
9.9%
광 83
9.2%
역 83
9.2%
시 83
9.2%
정 83
9.2%
동 83
9.2%
서 21
 
2.3%
Other values (14) 85
9.4%
Decimal Number
ValueCountFrequency (%)
1 59
18.1%
2 56
17.2%
3 46
14.1%
4 31
9.5%
5 29
8.9%
6 26
8.0%
7 25
7.7%
0 21
 
6.4%
8 17
 
5.2%
9 16
 
4.9%
Space Separator
ValueCountFrequency (%)
249
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 902
58.6%
Common 636
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 103
11.4%
산 98
10.9%
구 91
10.1%
금 89
9.9%
광 83
9.2%
역 83
9.2%
시 83
9.2%
정 83
9.2%
동 83
9.2%
서 21
 
2.3%
Other values (14) 85
9.4%
Common
ValueCountFrequency (%)
249
39.2%
- 61
 
9.6%
1 59
 
9.3%
2 56
 
8.8%
3 46
 
7.2%
4 31
 
4.9%
5 29
 
4.6%
6 26
 
4.1%
7 25
 
3.9%
0 21
 
3.3%
Other values (2) 33
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 902
58.6%
ASCII 636
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
249
39.2%
- 61
 
9.6%
1 59
 
9.3%
2 56
 
8.8%
3 46
 
7.2%
4 31
 
4.9%
5 29
 
4.6%
6 26
 
4.1%
7 25
 
3.9%
0 21
 
3.3%
Other values (2) 33
 
5.2%
Hangul
ValueCountFrequency (%)
부 103
11.4%
산 98
10.9%
구 91
10.1%
금 89
9.9%
광 83
9.2%
역 83
9.2%
시 83
9.2%
정 83
9.2%
동 83
9.2%
서 21
 
2.3%
Other values (14) 85
9.4%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.238769
Minimum35.125905
Maximum35.298275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2023-12-11T02:02:47.022318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.125905
5-th percentile35.212933
Q135.220078
median35.23406
Q335.262391
95-th percentile35.275393
Maximum35.298275
Range0.17236971
Interquartile range (IQR)0.042312585

Descriptive statistics

Standard deviation0.02845814
Coefficient of variation (CV)0.00080758041
Kurtosis3.5019761
Mean35.238769
Median Absolute Deviation (MAD)0.01828777
Skewness-1.0018853
Sum2924.8179
Variance0.00080986572
MonotonicityNot monotonic
2023-12-11T02:02:47.598541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.21925623 1
 
1.2%
35.27314292 1
 
1.2%
35.270197 1
 
1.2%
35.26879352 1
 
1.2%
35.265219 1
 
1.2%
35.275258 1
 
1.2%
35.28102983 1
 
1.2%
35.27540752 1
 
1.2%
35.272642 1
 
1.2%
35.27854559 1
 
1.2%
Other values (73) 73
88.0%
ValueCountFrequency (%)
35.125905 1
1.2%
35.13389 1
1.2%
35.21142353 1
1.2%
35.21287122 1
1.2%
35.21292481 1
1.2%
35.21300855 1
1.2%
35.213056 1
1.2%
35.2131853 1
1.2%
35.214444 1
1.2%
35.21452688 1
1.2%
ValueCountFrequency (%)
35.29827471 1
1.2%
35.28468657 1
1.2%
35.28102983 1
1.2%
35.27854559 1
1.2%
35.27540752 1
1.2%
35.275258 1
1.2%
35.2735519 1
1.2%
35.27314292 1
1.2%
35.272642 1
1.2%
35.271667 1
1.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct82
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.10445
Minimum129.04567
Maximum129.62738
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2023-12-11T02:02:47.845896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.04567
5-th percentile129.07984
Q1129.08864
median129.09189
Q3129.09602
95-th percentile129.11313
Maximum129.62738
Range0.5817061
Interquartile range (IQR)0.00738345

Descriptive statistics

Standard deviation0.079595522
Coefficient of variation (CV)0.00061652035
Kurtosis37.833343
Mean129.10445
Median Absolute Deviation (MAD)0.0036828
Skewness6.16728
Sum10715.67
Variance0.0063354471
MonotonicityNot monotonic
2023-12-11T02:02:48.184795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.090833 2
 
2.4%
129.0996481 1
 
1.2%
129.0851952 1
 
1.2%
129.0918945 1
 
1.2%
129.0930147 1
 
1.2%
129.0924979 1
 
1.2%
129.0898668 1
 
1.2%
129.0861996 1
 
1.2%
129.0899103 1
 
1.2%
129.096111 1
 
1.2%
Other values (72) 72
86.7%
ValueCountFrequency (%)
129.0456739 1
1.2%
129.056111 1
1.2%
129.0759656 1
1.2%
129.0793298 1
1.2%
129.0797154 1
1.2%
129.0809685 1
1.2%
129.0811551 1
1.2%
129.081243 1
1.2%
129.0818952 1
1.2%
129.0834097 1
1.2%
ValueCountFrequency (%)
129.62738 1
1.2%
129.5784 1
1.2%
129.1150895 1
1.2%
129.1138408 1
1.2%
129.113333 1
1.2%
129.1113076 1
1.2%
129.1096506 1
1.2%
129.1088163 1
1.2%
129.108333 1
1.2%
129.1074207 1
1.2%

민방위대피시설면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2348.7229
Minimum33
Maximum8794
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2023-12-11T02:02:48.522099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile171.2
Q1307.5
median962
Q34394.5
95-th percentile7244.4
Maximum8794
Range8761
Interquartile range (IQR)4087

Descriptive statistics

Standard deviation2496.2119
Coefficient of variation (CV)1.0627954
Kurtosis-0.39975466
Mean2348.7229
Median Absolute Deviation (MAD)797
Skewness0.94741949
Sum194944
Variance6231073.9
MonotonicityNot monotonic
2023-12-11T02:02:48.786012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
507 1
 
1.2%
6595 1
 
1.2%
431 1
 
1.2%
213 1
 
1.2%
4493 1
 
1.2%
173 1
 
1.2%
4527 1
 
1.2%
175 1
 
1.2%
962 1
 
1.2%
105 1
 
1.2%
Other values (73) 73
88.0%
ValueCountFrequency (%)
33 1
1.2%
105 1
1.2%
109 1
1.2%
132 1
1.2%
171 1
1.2%
173 1
1.2%
175 1
1.2%
182 1
1.2%
185 1
1.2%
193 1
1.2%
ValueCountFrequency (%)
8794 1
1.2%
7736 1
1.2%
7627 1
1.2%
7624 1
1.2%
7254 1
1.2%
7158 1
1.2%
6893 1
1.2%
6843 1
1.2%
6595 1
1.2%
6223 1
1.2%

대피가능인원수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2847.6627
Minimum40
Maximum10659
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2023-12-11T02:02:49.071493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile207.3
Q1372.5
median1166
Q35326.5
95-th percentile8781.3
Maximum10659
Range10619
Interquartile range (IQR)4954

Descriptive statistics

Standard deviation3027.3192
Coefficient of variation (CV)1.0630891
Kurtosis-0.39640079
Mean2847.6627
Median Absolute Deviation (MAD)966
Skewness0.94855262
Sum236356
Variance9164661.4
MonotonicityNot monotonic
2023-12-11T02:02:49.365072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
615 1
 
1.2%
7994 1
 
1.2%
522 1
 
1.2%
258 1
 
1.2%
5446 1
 
1.2%
210 1
 
1.2%
5487 1
 
1.2%
212 1
 
1.2%
1166 1
 
1.2%
127 1
 
1.2%
Other values (73) 73
88.0%
ValueCountFrequency (%)
40 1
1.2%
127 1
1.2%
132 1
1.2%
160 1
1.2%
207 1
1.2%
210 1
1.2%
212 1
1.2%
221 1
1.2%
224 1
1.2%
234 1
1.2%
ValueCountFrequency (%)
10659 1
1.2%
9377 1
1.2%
9302 1
1.2%
9245 1
1.2%
8793 1
1.2%
8676 1
1.2%
8355 1
1.2%
8295 1
1.2%
7994 1
1.2%
7543 1
1.2%

개방여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size215.0 B
True
83 
ValueCountFrequency (%)
True 83
100.0%
2023-12-11T02:02:49.566381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

평시활용유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size796.0 B
주차장
67 
지하철 승강장
 
6
교육장
 
4
식당
 
1
독서실
 
1
Other values (4)
 
4

Length

Max length8
Median length3
Mean length3.3373494
Min length2

Unique

Unique6 ?
Unique (%)7.2%

Sample

1st row식당
2nd row독서실
3rd row주차장
4th row주차장
5th row주차장

Common Values

ValueCountFrequency (%)
주차장 67
80.7%
지하철 승강장 6
 
7.2%
교육장 4
 
4.8%
식당 1
 
1.2%
독서실 1
 
1.2%
집회시설 1
 
1.2%
탁구장, 문서고 1
 
1.2%
창고 1
 
1.2%
문서고 1
 
1.2%

Length

2023-12-11T02:02:49.770904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:50.020435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주차장 67
74.4%
지하철 6
 
6.7%
승강장 6
 
6.7%
교육장 4
 
4.4%
문서고 2
 
2.2%
식당 1
 
1.1%
독서실 1
 
1.1%
집회시설 1
 
1.1%
탁구장 1
 
1.1%
창고 1
 
1.1%

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Memory size796.0 B
051-519-5384
15 
051-519-5302
9 
051-519-5361
8 
051-519-5124
7 
051-519-5144
6 
Other values (11)
38 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique2 ?
Unique (%)2.4%

Sample

1st row051-519-5102
2nd row051-519-5124
3rd row051-519-5124
4th row051-519-5124
5th row051-519-5124

Common Values

ValueCountFrequency (%)
051-519-5384 15
18.1%
051-519-5302 9
10.8%
051-519-5361 8
9.6%
051-519-5124 7
8.4%
051-519-5144 6
 
7.2%
051-519-5262 6
 
7.2%
051-519-5222 5
 
6.0%
051-519-5257 5
 
6.0%
051-519-5182 4
 
4.8%
051-519-5202 4
 
4.8%
Other values (6) 14
16.9%

Length

2023-12-11T02:02:50.284315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-519-5384 15
18.1%
051-519-5302 9
10.8%
051-519-5361 8
9.6%
051-519-5124 7
8.4%
051-519-5144 6
 
7.2%
051-519-5262 6
 
7.2%
051-519-5222 5
 
6.0%
051-519-5257 5
 
6.0%
051-519-5182 4
 
4.8%
051-519-5202 4
 
4.8%
Other values (6) 14
16.9%

관리기관명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size796.0 B
남산동
15 
장전2동
9 
청룡노포동
8 
서2동
7 
구서동
7 
Other values (10)
37 

Length

Max length5
Median length3
Mean length3.5903614
Min length3

Unique

Unique2 ?
Unique (%)2.4%

Sample

1st row서1동
2nd row서2동
3rd row서2동
4th row서2동
5th row서2동

Common Values

ValueCountFrequency (%)
남산동 15
18.1%
장전2동 9
10.8%
청룡노포동 8
9.6%
서2동 7
8.4%
구서동 7
8.4%
서3동 6
 
7.2%
부곡4동 6
 
7.2%
부곡2동 5
 
6.0%
부곡3동 5
 
6.0%
금사동 4
 
4.8%
Other values (5) 11
13.3%

Length

2023-12-11T02:02:50.538063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남산동 15
18.1%
장전2동 9
10.8%
청룡노포동 8
9.6%
서2동 7
8.4%
구서동 7
8.4%
서3동 6
 
7.2%
부곡4동 6
 
7.2%
부곡2동 5
 
6.0%
부곡3동 5
 
6.0%
금사동 4
 
4.8%
Other values (5) 11
13.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
Minimum2022-04-05 00:00:00
Maximum2022-04-05 00:00:00
2023-12-11T02:02:50.746635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:51.008027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T02:02:43.157799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:41.589889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:42.228445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:42.671425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:43.276809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:41.762865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:42.366720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:42.798084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:43.397782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:41.940108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:42.473946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:42.934300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:43.519400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:42.094554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:42.568243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:43.034453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:02:51.155409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
민방위대피시설명민방위대피시설구분소재지도로명주소소재지지번주소위도경도민방위대피시설면적대피가능인원수평시활용유형관리기관전화번호관리기관명
민방위대피시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
민방위대피시설구분1.0001.0001.0001.0000.6260.4470.0000.0000.0000.0000.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도1.0000.6261.0001.0001.0000.8180.0000.0000.7010.8630.869
경도1.0000.4471.0001.0000.8181.0000.0000.0000.3320.7330.822
민방위대피시설면적1.0000.0001.0001.0000.0000.0001.0001.0000.0000.1710.000
대피가능인원수1.0000.0001.0001.0000.0000.0001.0001.0000.0000.1710.000
평시활용유형1.0000.0001.0001.0000.7010.3320.0000.0001.0000.8400.849
관리기관전화번호1.0000.0001.0001.0000.8630.7330.1710.1710.8401.0001.000
관리기관명1.0000.0001.0001.0000.8690.8220.0000.0000.8491.0001.000
2023-12-11T02:02:51.376726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
민방위대피시설구분관리기관전화번호관리기관명평시활용유형
민방위대피시설구분1.0000.0000.0000.000
관리기관전화번호0.0001.0000.9930.523
관리기관명0.0000.9931.0000.534
평시활용유형0.0000.5230.5341.000
2023-12-11T02:02:51.543141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도민방위대피시설면적대피가능인원수민방위대피시설구분평시활용유형관리기관전화번호관리기관명
위도1.000-0.3200.0220.0220.6530.4620.5920.598
경도-0.3201.000-0.276-0.2760.6890.1530.5030.515
민방위대피시설면적0.022-0.2761.0001.0000.0000.0000.0410.000
대피가능인원수0.022-0.2761.0001.0000.0000.0000.0410.000
민방위대피시설구분0.6530.6890.0000.0001.0000.0000.0000.000
평시활용유형0.4620.1530.0000.0000.0001.0000.5230.534
관리기관전화번호0.5920.5030.0410.0410.0000.5231.0000.993
관리기관명0.5980.5150.0000.0000.0000.5340.9931.000

Missing values

2023-12-11T02:02:43.675547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:02:43.941336image/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

민방위대피시설명민방위대피시설구분소재지도로명주소소재지지번주소위도경도민방위대피시설면적대피가능인원수개방여부평시활용유형관리기관전화번호관리기관명데이터기준일자
0동성교회공공용부산광역시 금정구 서부로 72부산광역시 금정구 서동 150-1235.219256129.099648507615Y식당051-519-5102서1동2022-04-05
1파크랜드공공용부산광역시 금정구 반송로 365부산광역시 금정구 서동 219-235.211424129.105661198240Y독서실051-519-5124서2동2022-04-05
2세웅종합병원공공용부산광역시 금정구 서동로 162부산광역시 금정구 서동 199-1635.214444129.104079557675Y주차장051-519-5124서2동2022-04-05
3서2동 행정복지센터공공용부산광역시 금정구 서동중심로 33부산광역시 금정구 서동 297-44635.212871129.104444402487Y주차장051-519-5124서2동2022-04-05
4삼한여명아파트공공용부산광역시 금정구 중군진로 27부산광역시 금정구 서동 228-135.213185129.10881619602376Y주차장051-519-5124서2동2022-04-05
5삼한아파트공공용부산광역시 금정구 명서로 76부산광역시 금정구 서동 304-15135.214527129.09799355526730Y주차장051-519-5124서2동2022-04-05
6성지아파트공공용부산광역시 금정구 명서로 94부산광역시 금정구 서동 62235.212925129.09954237054491Y주차장051-519-5124서2동2022-04-05
7서동 도시철도역공공용부산광역시 금정구 반송로 387부산광역시 금정구 서동 24135.213056129.10742146025578Y지하철 승강장051-519-5124서2동2022-04-05
8서동 라이프타운 지하공공용부산광역시 금정구 서동로175번길 46부산광역시 금정구 서동 207-135.215256129.10833330573705Y주차장051-519-5144서3동2022-04-05
9서3동 서진어패럴 지하공고용부산광역시 금정구 금사로 27부산광역시 금정구 서동 130번지 37호35.125905129.62738236286Y주차장051-519-5144서3동2022-04-05
민방위대피시설명민방위대피시설구분소재지도로명주소소재지지번주소위도경도민방위대피시설면적대피가능인원수개방여부평시활용유형관리기관전화번호관리기관명데이터기준일자
73수민아파트공공용부산광역시 금정구 금단로 171부산광역시 금정구 남산동 262-435.264526129.09362616051945Y주차장051-519-5384남산동2022-04-05
74구서1동 경보아파트공공용부산광역시 금정구 금단로 33-1부산광역시 금정구 구서동 26735.252858129.09300942965207Y주차장051-519-5404구서동2022-04-05
75금강부광아파트공공용부산광역시 금정구 금샘로229번길 29부산광역시 금정구 구서동 563-4035.245731129.08341879410659Y주차장051-519-5404구서동2022-04-05
76협성그린아파트공공용부산광역시 금정구 금단로 30부산광역시 금정구 구서동 266-1635.252301129.0929971588676Y주차장051-519-5404구서동2022-04-05
77두실지하철역공공용부산광역시 금정구 중앙대로 1927-1부산광역시 금정구 구서동 26235.256876129.09141242735179Y지하철 승강장051-519-5424구서동2022-04-05
78현대자동차금정사옥공공용부산광역시 금정구 중앙대로 1883부산광역시 금정구 구서동 248-1035.252468129.09093456196811Y주차장051-519-5424구서동2022-04-05
79롯데캐슬골드1단지공공용부산광역시 금정구 금강로 502부산광역시 금정구 구서동 105135.250695129.08819568438295Y주차장051-519-5424구서동2022-04-05
80롯데캐슬골드2단지공공용부산광역시 금정구 금강로 503부산광역시 금정구 구서동 104935.252682129.08649576279245Y주차장051-519-5424구서동2022-04-05
81금성동 행정복지센터공공용부산광역시 금정구 산성로 452부산광역시 금정구 금성동 554-335.250322129.0561113340Y문서고051-519-5442금성동2022-04-05
82부산시학생교육원공공용부산광역시 금정구 북문로 178부산광역시 금정구 금성동 22-235.26057129.045674603731Y교육장051-519-5442금성동2022-04-05