Overview

Dataset statistics

Number of variables13
Number of observations84
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory109.6 B

Variable types

Text3
Categorical5
Numeric4
Boolean1

Dataset

Description부산광역시금정구_민방위대피시설_20230405
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 관리기관전화번호 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 관리기관전화번호 and 1 other fieldsHigh correlation
민방위대피시설면적 is highly overall correlated with 대피가능인원수High correlation
대피가능인원수 is highly overall correlated with 민방위대피시설면적High correlation
평시활용유형 is highly overall correlated with 관리기관전화번호 and 1 other fieldsHigh correlation
민방위대피시설구분 is highly imbalanced (90.7%)Imbalance
평시활용유형 is highly imbalanced (62.6%)Imbalance
민방위대피시설명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
소재지지번주소 has unique valuesUnique
민방위대피시설면적 has unique valuesUnique
대피가능인원수 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:02:25.538603
Analysis finished2023-12-10 17:02:29.427027
Duration3.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

민방위대피시설명
Text

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-11T02:02:29.744205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18.5
Mean length16.416667
Min length10

Characters and Unicode

Total characters1379
Distinct characters166
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

Unique84 ?
Unique (%)100.0%

Sample

1st row동성교회 지하 1층
2nd row파크랜드 지하주차장 지하1층
3rd row세웅종합병원 지하주차장 1층
4th row서2동 행정복지센터 지하주차장 1층
5th row삼한여명아파트 상가동 지하주차장 1층
ValueCountFrequency (%)
1층 72
24.3%
지하주차장 55
18.6%
지하 29
 
9.8%
행정복지센터 7
 
2.4%
부곡4동 5
 
1.7%
주차장 4
 
1.4%
1~3층 4
 
1.4%
1~2층 4
 
1.4%
서3동 4
 
1.4%
새마을금고 3
 
1.0%
Other values (93) 109
36.8%
2023-12-11T02:02:30.434484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
212
 
15.4%
지 104
 
7.5%
하 93
 
6.7%
1 87
 
6.3%
층 84
 
6.1%
장 65
 
4.7%
차 62
 
4.5%
주 60
 
4.4%
동 41
 
3.0%
파 32
 
2.3%
Other values (156) 539
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1025
74.3%
Space Separator 212
 
15.4%
Decimal Number 123
 
8.9%
Math Symbol 11
 
0.8%
Uppercase Letter 4
 
0.3%
Lowercase Letter 2
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 104
 
10.1%
하 93
 
9.1%
층 84
 
8.2%
장 65
 
6.3%
차 62
 
6.0%
주 60
 
5.9%
동 41
 
4.0%
파 32
 
3.1%
트 31
 
3.0%
아 31
 
3.0%
Other values (142) 422
41.2%
Decimal Number
ValueCountFrequency (%)
1 87
70.7%
2 18
 
14.6%
3 11
 
8.9%
4 5
 
4.1%
0 2
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
S 2
50.0%
K 1
25.0%
G 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
212
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1025
74.3%
Common 348
 
25.2%
Latin 6
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 104
 
10.1%
하 93
 
9.1%
층 84
 
8.2%
장 65
 
6.3%
차 62
 
6.0%
주 60
 
5.9%
동 41
 
4.0%
파 32
 
3.1%
트 31
 
3.0%
아 31
 
3.0%
Other values (142) 422
41.2%
Common
ValueCountFrequency (%)
212
60.9%
1 87
25.0%
2 18
 
5.2%
3 11
 
3.2%
~ 11
 
3.2%
4 5
 
1.4%
0 2
 
0.6%
( 1
 
0.3%
) 1
 
0.3%
Latin
ValueCountFrequency (%)
S 2
33.3%
K 1
16.7%
G 1
16.7%
s 1
16.7%
k 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1025
74.3%
ASCII 354
 
25.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
212
59.9%
1 87
24.6%
2 18
 
5.1%
3 11
 
3.1%
~ 11
 
3.1%
4 5
 
1.4%
0 2
 
0.6%
S 2
 
0.6%
( 1
 
0.3%
) 1
 
0.3%
Other values (4) 4
 
1.1%
Hangul
ValueCountFrequency (%)
지 104
 
10.1%
하 93
 
9.1%
층 84
 
8.2%
장 65
 
6.3%
차 62
 
6.0%
주 60
 
5.9%
동 41
 
4.0%
파 32
 
3.1%
트 31
 
3.0%
아 31
 
3.0%
Other values (142) 422
41.2%

민방위대피시설구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
공공용
83 
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 83
98.8%
공고용 1
 
1.2%

Length

2023-12-11T02:02:30.685263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:30.847763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 83
98.8%
공고용 1
 
1.2%

소재지도로명주소
Text

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-11T02:02:31.303165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length18.404762
Min length15

Characters and Unicode

Total characters1546
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

Unique84 ?
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 84
24.9%
금정구 84
24.9%
중앙대로 12
 
3.6%
부곡로 7
 
2.1%
금강로 6
 
1.8%
금단로 6
 
1.8%
서동로 3
 
0.9%
반송로 3
 
0.9%
30 3
 
0.9%
21 3
 
0.9%
Other values (111) 127
37.6%
2023-12-11T02:02:32.028337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
254
16.4%
금 104
 
6.7%
부 99
 
6.4%
정 89
 
5.8%
산 89
 
5.8%
구 86
 
5.6%
시 85
 
5.5%
광 84
 
5.4%
역 84
 
5.4%
로 83
 
5.4%
Other values (63) 489
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1012
65.5%
Decimal Number 267
 
17.3%
Space Separator 254
 
16.4%
Dash Punctuation 10
 
0.6%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 104
10.3%
부 99
9.8%
정 89
8.8%
산 89
8.8%
구 86
8.5%
시 85
8.4%
광 84
8.3%
역 84
8.3%
로 83
8.2%
길 20
 
2.0%
Other values (48) 189
18.7%
Decimal Number
ValueCountFrequency (%)
1 47
17.6%
2 39
14.6%
7 32
12.0%
3 31
11.6%
9 24
9.0%
5 23
8.6%
0 20
7.5%
6 20
7.5%
8 16
 
6.0%
4 15
 
5.6%
Space Separator
ValueCountFrequency (%)
254
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 1012
65.5%
Common 534
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 104
10.3%
부 99
9.8%
정 89
8.8%
산 89
8.8%
구 86
8.5%
시 85
8.4%
광 84
8.3%
역 84
8.3%
로 83
8.2%
길 20
 
2.0%
Other values (48) 189
18.7%
Common
ValueCountFrequency (%)
254
47.6%
1 47
 
8.8%
2 39
 
7.3%
7 32
 
6.0%
3 31
 
5.8%
9 24
 
4.5%
5 23
 
4.3%
0 20
 
3.7%
6 20
 
3.7%
8 16
 
3.0%
Other values (5) 28
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1012
65.5%
ASCII 534
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
254
47.6%
1 47
 
8.8%
2 39
 
7.3%
7 32
 
6.0%
3 31
 
5.8%
9 24
 
4.5%
5 23
 
4.3%
0 20
 
3.7%
6 20
 
3.7%
8 16
 
3.0%
Other values (5) 28
 
5.2%
Hangul
ValueCountFrequency (%)
금 104
10.3%
부 99
9.8%
정 89
8.8%
산 89
8.8%
구 86
8.5%
시 85
8.4%
광 84
8.3%
역 84
8.3%
로 83
8.2%
길 20
 
2.0%
Other values (48) 189
18.7%

소재지지번주소
Text

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-11T02:02:32.429441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length18.52381
Min length15

Characters and Unicode

Total characters1556
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

Unique84 ?
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 84
25.0%
금정구 84
25.0%
부곡동 20
 
6.0%
남산동 16
 
4.8%
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 (86) 86
25.6%
2023-12-11T02:02:33.017632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
252
16.2%
부 104
 
6.7%
산 100
 
6.4%
구 92
 
5.9%
금 90
 
5.8%
시 84
 
5.4%
역 84
 
5.4%
정 84
 
5.4%
광 84
 
5.4%
동 84
 
5.4%
Other values (26) 498
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 913
58.7%
Decimal Number 329
 
21.1%
Space Separator 252
 
16.2%
Dash Punctuation 62
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 104
11.4%
산 100
11.0%
구 92
10.1%
금 90
9.9%
시 84
9.2%
역 84
9.2%
정 84
9.2%
광 84
9.2%
동 84
9.2%
서 21
 
2.3%
Other values (14) 86
9.4%
Decimal Number
ValueCountFrequency (%)
1 60
18.2%
2 56
17.0%
3 46
14.0%
4 31
9.4%
5 29
8.8%
6 27
8.2%
7 25
7.6%
0 21
 
6.4%
8 18
 
5.5%
9 16
 
4.9%
Space Separator
ValueCountFrequency (%)
252
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 913
58.7%
Common 643
41.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 104
11.4%
산 100
11.0%
구 92
10.1%
금 90
9.9%
시 84
9.2%
역 84
9.2%
정 84
9.2%
광 84
9.2%
동 84
9.2%
서 21
 
2.3%
Other values (14) 86
9.4%
Common
ValueCountFrequency (%)
252
39.2%
- 62
 
9.6%
1 60
 
9.3%
2 56
 
8.7%
3 46
 
7.2%
4 31
 
4.8%
5 29
 
4.5%
6 27
 
4.2%
7 25
 
3.9%
0 21
 
3.3%
Other values (2) 34
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 913
58.7%
ASCII 643
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
252
39.2%
- 62
 
9.6%
1 60
 
9.3%
2 56
 
8.7%
3 46
 
7.2%
4 31
 
4.8%
5 29
 
4.5%
6 27
 
4.2%
7 25
 
3.9%
0 21
 
3.3%
Other values (2) 34
 
5.3%
Hangul
ValueCountFrequency (%)
부 104
11.4%
산 100
11.0%
구 92
10.1%
금 90
9.9%
시 84
9.2%
역 84
9.2%
정 84
9.2%
광 84
9.2%
동 84
9.2%
서 21
 
2.3%
Other values (14) 86
9.4%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct82
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.142678
Minimum35.123993
Maximum35.17538
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2023-12-11T02:02:33.250112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.123993
5-th percentile35.124725
Q135.131406
median35.140729
Q335.154449
95-th percentile35.163138
Maximum35.17538
Range0.051387
Interquartile range (IQR)0.02304375

Descriptive statistics

Standard deviation0.013867747
Coefficient of variation (CV)0.0003946127
Kurtosis-1.2162369
Mean35.142678
Median Absolute Deviation (MAD)0.0103935
Skewness0.3565558
Sum2951.985
Variance0.00019231441
MonotonicityNot monotonic
2023-12-11T02:02:33.823915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.124686 2
 
2.4%
35.125905 2
 
2.4%
35.130932 1
 
1.2%
35.162141 1
 
1.2%
35.160532 1
 
1.2%
35.154637 1
 
1.2%
35.161265 1
 
1.2%
35.160765 1
 
1.2%
35.155496 1
 
1.2%
35.163092 1
 
1.2%
Other values (72) 72
85.7%
ValueCountFrequency (%)
35.123993 1
1.2%
35.124626 1
1.2%
35.124686 2
2.4%
35.124722 1
1.2%
35.124744 1
1.2%
35.125201 1
1.2%
35.125246 1
1.2%
35.125296 1
1.2%
35.125492 1
1.2%
35.125684 1
1.2%
ValueCountFrequency (%)
35.17538 1
1.2%
35.165624 1
1.2%
35.165018 1
1.2%
35.164402 1
1.2%
35.163146 1
1.2%
35.163092 1
1.2%
35.162727 1
1.2%
35.162327 1
1.2%
35.162141 1
1.2%
35.161807 1
1.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct83
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.05343
Minimum129.0247
Maximum129.06545
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2023-12-11T02:02:34.026987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.0247
5-th percentile129.04516
Q1129.05194
median129.05293
Q3129.05441
95-th percentile129.06343
Maximum129.06545
Range0.040746
Interquartile range (IQR)0.0024715

Descriptive statistics

Standard deviation0.0063325915
Coefficient of variation (CV)4.9069533 × 10-5
Kurtosis5.4290661
Mean129.05343
Median Absolute Deviation (MAD)0.0012345
Skewness-1.1598148
Sum10840.488
Variance4.0101715 × 10-5
MonotonicityNot monotonic
2023-12-11T02:02:34.298022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.052914 2
 
2.4%
129.050741 1
 
1.2%
129.05353 1
 
1.2%
129.053082 1
 
1.2%
129.053485 1
 
1.2%
129.0533 1
 
1.2%
129.052353 1
 
1.2%
129.051137 1
 
1.2%
129.052367 1
 
1.2%
129.054625 1
 
1.2%
Other values (73) 73
86.9%
ValueCountFrequency (%)
129.024701 1
1.2%
129.032246 1
1.2%
129.043348 1
1.2%
129.044523 1
1.2%
129.045149 1
1.2%
129.045248 1
1.2%
129.045313 1
1.2%
129.045362 1
1.2%
129.045609 1
1.2%
129.050118 1
1.2%
ValueCountFrequency (%)
129.065447 1
1.2%
129.064916 1
1.2%
129.064801 1
1.2%
129.064071 1
1.2%
129.063479 1
1.2%
129.063174 1
1.2%
129.063 1
1.2%
129.062738 1
1.2%
129.062679 1
1.2%
129.062025 1
1.2%

민방위대피시설면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2342.7024
Minimum33
Maximum8794
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2023-12-11T02:02:34.569888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile171.3
Q1314.75
median1123
Q34345.25
95-th percentile7239.6
Maximum8794
Range8761
Interquartile range (IQR)4030.5

Descriptive statistics

Standard deviation2481.7424
Coefficient of variation (CV)1.0593503
Kurtosis-0.36064454
Mean2342.7024
Median Absolute Deviation (MAD)937.5
Skewness0.95954317
Sum196787
Variance6159045.5
MonotonicityNot monotonic
2023-12-11T02:02:34.831772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
507 1
 
1.2%
105 1
 
1.2%
717 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%
Other values (74) 74
88.1%
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 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2840.3571
Minimum40
Maximum10659
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2023-12-11T02:02:35.057410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile207.45
Q1381.25
median1361
Q35266.75
95-th percentile8775.45
Maximum10659
Range10619
Interquartile range (IQR)4885.5

Descriptive statistics

Standard deviation3009.7719
Coefficient of variation (CV)1.0596456
Kurtosis-0.35724207
Mean2840.3571
Median Absolute Deviation (MAD)1136.5
Skewness0.96068517
Sum238590
Variance9058726.9
MonotonicityNot monotonic
2023-12-11T02:02:35.304263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
615 1
 
1.2%
127 1
 
1.2%
869 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%
Other values (74) 74
88.1%
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 size216.0 B
True
84 
ValueCountFrequency (%)
True 84
100.0%
2023-12-11T02:02:35.516927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

평시활용유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size804.0 B
주차장
68 
지하철 승강장
 
6
교육장
 
4
식당
 
1
독서실
 
1
Other values (4)
 
4

Length

Max length7
Median length3
Mean length3.3214286
Min length2

Unique

Unique6 ?
Unique (%)7.1%

Sample

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

Common Values

ValueCountFrequency (%)
주차장 68
81.0%
지하철 승강장 6
 
7.1%
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

2023-12-11T02:02:35.709943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:35.942995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주차장 68
75.6%
지하철 6
 
6.7%
승강장 6
 
6.7%
교육장 4
 
4.4%
식당 1
 
1.1%
독서실 1
 
1.1%
집회시설 1
 
1.1%
탁구장+문서고 1
 
1.1%
창고 1
 
1.1%
문서고 1
 
1.1%

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
051-519-5384
16 
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 16
19.0%
051-519-5302 9
10.7%
051-519-5361 8
9.5%
051-519-5124 7
8.3%
051-519-5144 6
 
7.1%
051-519-5262 6
 
7.1%
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
16.7%

Length

2023-12-11T02:02:36.224682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
051-519-5384 16
19.0%
051-519-5302 9
10.7%
051-519-5361 8
9.5%
051-519-5124 7
8.3%
051-519-5144 6
 
7.1%
051-519-5262 6
 
7.1%
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
16.7%

관리기관명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size804.0 B
남산동
16 
장전2동
9 
청룡노포동
8 
서2동
7 
구서동
7 
Other values (10)
37 

Length

Max length5
Median length3
Mean length3.5833333
Min length3

Unique

Unique2 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
남산동 16
19.0%
장전2동 9
10.7%
청룡노포동 8
9.5%
서2동 7
8.3%
구서동 7
8.3%
서3동 6
 
7.1%
부곡4동 6
 
7.1%
부곡2동 5
 
6.0%
부곡3동 5
 
6.0%
금사동 4
 
4.8%
Other values (5) 11
13.1%

Length

2023-12-11T02:02:36.454502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남산동 16
19.0%
장전2동 9
10.7%
청룡노포동 8
9.5%
서2동 7
8.3%
구서동 7
8.3%
서3동 6
 
7.1%
부곡4동 6
 
7.1%
부곡2동 5
 
6.0%
부곡3동 5
 
6.0%
금사동 4
 
4.8%
Other values (5) 11
13.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-04-05
84 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-04-05
2nd row2023-04-05
3rd row2023-04-05
4th row2023-04-05
5th row2023-04-05

Common Values

ValueCountFrequency (%)
2023-04-05 84
100.0%

Length

2023-12-11T02:02:36.669925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:36.851139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-04-05 84
100.0%

Interactions

2023-12-11T02:02:28.384892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:26.532873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:27.130731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:27.796092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:28.519492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:26.684666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:27.297562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:27.958988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:28.688159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:26.851259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:27.485526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:28.124176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:28.821864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:26.982725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:27.635651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:28.260112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:02:36.985650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
민방위대피시설명민방위대피시설구분소재지도로명주소소재지지번주소위도경도민방위대피시설면적대피가능인원수평시활용유형관리기관전화번호관리기관명
민방위대피시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
민방위대피시설구분1.0001.0001.0001.0000.0000.0000.0000.0000.0000.0000.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도1.0000.0001.0001.0001.0000.4860.0000.0000.7500.9140.919
경도1.0000.0001.0001.0000.4861.0000.0000.0000.6490.8580.861
민방위대피시설면적1.0000.0001.0001.0000.0000.0001.0001.0000.0000.1470.000
대피가능인원수1.0000.0001.0001.0000.0000.0001.0001.0000.0000.1470.000
평시활용유형1.0000.0001.0001.0000.7500.6490.0000.0001.0000.8410.850
관리기관전화번호1.0000.0001.0001.0000.9140.8580.1470.1470.8411.0001.000
관리기관명1.0000.0001.0001.0000.9190.8610.0000.0000.8501.0001.000
2023-12-11T02:02:37.204390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
민방위대피시설구분관리기관전화번호관리기관명평시활용유형
민방위대피시설구분1.0000.0000.0000.000
관리기관전화번호0.0001.0000.9930.526
관리기관명0.0000.9931.0000.536
평시활용유형0.0000.5260.5361.000
2023-12-11T02:02:37.380153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도민방위대피시설면적대피가능인원수민방위대피시설구분평시활용유형관리기관전화번호관리기관명
위도1.000-0.273-0.019-0.0190.0000.3280.6660.673
경도-0.2731.000-0.226-0.2250.0000.4090.5180.522
민방위대피시설면적-0.019-0.2261.0001.0000.0000.0000.0260.000
대피가능인원수-0.019-0.2251.0001.0000.0000.0000.0260.000
민방위대피시설구분0.0000.0000.0000.0001.0000.0000.0000.000
평시활용유형0.3280.4090.0000.0000.0001.0000.5260.536
관리기관전화번호0.6660.5180.0260.0260.0000.5261.0000.993
관리기관명0.6730.5220.0000.0000.0000.5360.9931.000

Missing values

2023-12-11T02:02:29.029063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:02:29.308714image/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
0동성교회 지하 1층공공용부산광역시 금정구 서부로 72부산광역시 금정구 서동 150-1235.130932129.055873507615Y식당051-519-5102서1동2023-04-05
1파크랜드 지하주차장 지하1층공공용부산광역시 금정구 반송로 365부산광역시 금정구 서동 219-235.123993129.061985198240Y독서실051-519-5124서2동2023-04-05
2세웅종합병원 지하주차장 1층공공용부산광역시 금정구 서동로 162부산광역시 금정구 서동 199-1635.125201129.061475557675Y주차장051-519-5124서2동2023-04-05
3서2동 행정복지센터 지하주차장 1층공공용부산광역시 금정구 서동중심로 33부산광역시 금정구 서동 297-44635.124626129.061625402487Y주차장051-519-5124서2동2023-04-05
4삼한여명아파트 상가동 지하주차장 1층공공용부산광역시 금정구 중군진로 27부산광역시 금정구 서동 228-135.124744129.06317419602376Y주차장051-519-5124서2동2023-04-05
5삼한아파트 지하주차장 지하 1층공공용부산광역시 금정구 명서로 76부산광역시 금정구 서동 304-15135.125246129.05527955526730Y주차장051-519-5124서2동2023-04-05
6성지아파트 지하주차장 지하 1층공공용부산광역시 금정구 명서로 94부산광역시 금정구 서동 62235.124686129.05587437054491Y주차장051-519-5124서2동2023-04-05
7서동 도시철도역 지하 1층공공용부산광역시 금정구 반송로 387부산광역시 금정구 서동 24135.124722129.06267946025578Y지하철 승강장051-519-5124서2동2023-04-05
8서3동 라이프타운 지하주차장 1층공공용부산광역시 금정구 서동로175번길 46부산광역시 금정구 서동 207-135.125492129.06330573705Y주차장051-519-5144서3동2023-04-05
9서3동 서진어패럴 지하주차장 1층공고용부산광역시 금정구 금사로 27부산광역시 금정구 서동 130번지 37호35.125905129.062738236286Y주차장051-519-5144서3동2023-04-05
민방위대피시설명민방위대피시설구분소재지도로명주소소재지지번주소위도경도민방위대피시설면적대피가능인원수개방여부평시활용유형관리기관전화번호관리기관명데이터기준일자
74수민아파트 지하주차장 1층공공용부산광역시 금정구 금단로 171부산광역시 금정구 남산동 262-435.155095129.05378816051945Y주차장051-519-5384남산동2023-04-05
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