Overview

Dataset statistics

Number of variables13
Number of observations34
Missing cells2
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory111.9 B

Variable types

Categorical3
Text4
Numeric4
Boolean1
DateTime1

Dataset

Description부산광역시동래구_재난이재민수용시설현황_20230724
Author부산광역시 동래구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15116998

Alerts

사용여부 has constant value ""Constant
수용가능면적(제곱미터) is highly overall correlated with 수용가능인원(명)High correlation
수용가능인원(명) is highly overall correlated with 수용가능면적(제곱미터) and 1 other fieldsHigh correlation
시설구분 is highly overall correlated with 수용가능인원(명) and 1 other fieldsHigh correlation
내진설계 is highly overall correlated with 시설구분High correlation
대표전화 has 2 (5.9%) missing valuesMissing
시설명 has unique valuesUnique
상세주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:08:32.851627
Analysis finished2023-12-10 17:08:36.495065
Duration3.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역명
Categorical

Distinct9
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Memory size404.0 B
부산광역시 동래구 온천동
10 
부산광역시 동래구 명장동
7 
부산광역시 동래구 사직동
5 
부산광역시 동래구 명륜동
4 
부산광역시 동래구 안락동
4 
Other values (4)
4 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique4 ?
Unique (%)11.8%

Sample

1st row부산광역시 동래구 낙민동
2nd row부산광역시 동래구 수안동
3rd row부산광역시 동래구 복천동
4th row부산광역시 동래구 칠산동
5th row부산광역시 동래구 명륜동

Common Values

ValueCountFrequency (%)
부산광역시 동래구 온천동 10
29.4%
부산광역시 동래구 명장동 7
20.6%
부산광역시 동래구 사직동 5
14.7%
부산광역시 동래구 명륜동 4
 
11.8%
부산광역시 동래구 안락동 4
 
11.8%
부산광역시 동래구 낙민동 1
 
2.9%
부산광역시 동래구 수안동 1
 
2.9%
부산광역시 동래구 복천동 1
 
2.9%
부산광역시 동래구 칠산동 1
 
2.9%

Length

2023-12-11T02:08:36.614693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:08:36.843489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 34
33.3%
동래구 34
33.3%
온천동 10
 
9.8%
명장동 7
 
6.9%
사직동 5
 
4.9%
명륜동 4
 
3.9%
안락동 4
 
3.9%
낙민동 1
 
1.0%
수안동 1
 
1.0%
복천동 1
 
1.0%

시설구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
학교
20 
연수,숙박
10 
교회
4 

Length

Max length5
Median length2
Mean length2.8823529
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row연수,숙박
2nd row연수,숙박
3rd row학교
4th row학교
5th row교회

Common Values

ValueCountFrequency (%)
학교 20
58.8%
연수,숙박 10
29.4%
교회 4
 
11.8%

Length

2023-12-11T02:08:37.091611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:08:37.249132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학교 20
58.8%
연수,숙박 10
29.4%
교회 4
 
11.8%

시설명
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-11T02:08:37.555403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.8235294
Min length3

Characters and Unicode

Total characters198
Distinct characters68
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st row스위트모텔
2nd row화성빌
3rd row내성초등학교
4th row동래고등학교
5th row새한교회
ValueCountFrequency (%)
스위트모텔 1
 
2.8%
동남장모텔 1
 
2.8%
동신중학교 1
 
2.8%
대명여자고등학교 1
 
2.8%
혜화초등학교 1
 
2.8%
충렬중학교 1
 
2.8%
충렬고등학교 1
 
2.8%
안락초등학교 1
 
2.8%
화성빌 1
 
2.8%
안락중학교 1
 
2.8%
Other values (26) 26
72.2%
2023-12-11T02:08:38.164768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 24
 
12.1%
학 20
 
10.1%
등 17
 
8.6%
초 11
 
5.6%
고 7
 
3.5%
텔 7
 
3.5%
동 6
 
3.0%
모 5
 
2.5%
회 4
 
2.0%
락 4
 
2.0%
Other values (58) 93
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 193
97.5%
Space Separator 2
 
1.0%
Open Punctuation 1
 
0.5%
Uppercase Letter 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 24
 
12.4%
학 20
 
10.4%
등 17
 
8.8%
초 11
 
5.7%
고 7
 
3.6%
텔 7
 
3.6%
동 6
 
3.1%
모 5
 
2.6%
회 4
 
2.1%
락 4
 
2.1%
Other values (54) 88
45.6%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 193
97.5%
Common 4
 
2.0%
Latin 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 24
 
12.4%
학 20
 
10.4%
등 17
 
8.8%
초 11
 
5.7%
고 7
 
3.6%
텔 7
 
3.6%
동 6
 
3.1%
모 5
 
2.6%
회 4
 
2.1%
락 4
 
2.1%
Other values (54) 88
45.6%
Common
ValueCountFrequency (%)
2
50.0%
( 1
25.0%
) 1
25.0%
Latin
ValueCountFrequency (%)
S 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 193
97.5%
ASCII 5
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 24
 
12.4%
학 20
 
10.4%
등 17
 
8.8%
초 11
 
5.7%
고 7
 
3.6%
텔 7
 
3.6%
동 6
 
3.1%
모 5
 
2.6%
회 4
 
2.1%
락 4
 
2.1%
Other values (54) 88
45.6%
ASCII
ValueCountFrequency (%)
2
40.0%
( 1
20.0%
S 1
20.0%
) 1
20.0%

상세시설명
Text

Distinct33
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-11T02:08:38.468265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12.5
Mean length8.9411765
Min length2

Characters and Unicode

Total characters304
Distinct characters69
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)94.1%

Sample

1st row2인실 27호
2nd row2인실 15호
3rd row2층 강당(참빛관)
4th row별관2층 체육관(군붕관)
5th row본관 1층
ValueCountFrequency (%)
2인실 10
 
13.7%
2층 6
 
8.2%
별관 4
 
5.5%
강당 3
 
4.1%
별관2층 3
 
4.1%
1층 3
 
4.1%
건물 2
 
2.7%
15호 2
 
2.7%
4층 2
 
2.7%
체육관 2
 
2.7%
Other values (35) 36
49.3%
2023-12-11T02:08:38.967864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
12.8%
관 27
 
8.9%
2 24
 
7.9%
층 19
 
6.2%
강 17
 
5.6%
) 17
 
5.6%
당 16
 
5.3%
( 16
 
5.3%
실 10
 
3.3%
인 10
 
3.3%
Other values (59) 109
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 181
59.5%
Decimal Number 50
 
16.4%
Space Separator 39
 
12.8%
Close Punctuation 17
 
5.6%
Open Punctuation 16
 
5.3%
Math Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 27
14.9%
층 19
 
10.5%
강 17
 
9.4%
당 16
 
8.8%
실 10
 
5.5%
인 10
 
5.5%
호 10
 
5.5%
별 9
 
5.0%
육 5
 
2.8%
체 4
 
2.2%
Other values (45) 54
29.8%
Decimal Number
ValueCountFrequency (%)
2 24
48.0%
1 7
 
14.0%
3 6
 
12.0%
4 4
 
8.0%
5 4
 
8.0%
7 1
 
2.0%
9 1
 
2.0%
6 1
 
2.0%
0 1
 
2.0%
8 1
 
2.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 181
59.5%
Common 123
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 27
14.9%
층 19
 
10.5%
강 17
 
9.4%
당 16
 
8.8%
실 10
 
5.5%
인 10
 
5.5%
호 10
 
5.5%
별 9
 
5.0%
육 5
 
2.8%
체 4
 
2.2%
Other values (45) 54
29.8%
Common
ValueCountFrequency (%)
39
31.7%
2 24
19.5%
) 17
13.8%
( 16
13.0%
1 7
 
5.7%
3 6
 
4.9%
4 4
 
3.3%
5 4
 
3.3%
7 1
 
0.8%
9 1
 
0.8%
Other values (4) 4
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 181
59.5%
ASCII 123
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
31.7%
2 24
19.5%
) 17
13.8%
( 16
13.0%
1 7
 
5.7%
3 6
 
4.9%
4 4
 
3.3%
5 4
 
3.3%
7 1
 
0.8%
9 1
 
0.8%
Other values (4) 4
 
3.3%
Hangul
ValueCountFrequency (%)
관 27
14.9%
층 19
 
10.5%
강 17
 
9.4%
당 16
 
8.8%
실 10
 
5.5%
인 10
 
5.5%
호 10
 
5.5%
별 9
 
5.0%
육 5
 
2.8%
체 4
 
2.2%
Other values (45) 54
29.8%

상세주소
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-11T02:08:39.299762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length24.823529
Min length21

Characters and Unicode

Total characters844
Distinct characters57
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)100.0%

Sample

1st row부산광역시 동래구 충렬대로255번길 18(낙민동)
2nd row부산광역시 동래구 충렬대로237번가길 11(수안동)
3rd row부산광역시 동래구 동래로 173(복천동)
4th row부산광역시 동래구 충렬대로285번길 22(칠산동)
5th row부산광역시 동래구 명륜로218번길 6(명륜동)
ValueCountFrequency (%)
부산광역시 34
24.5%
동래구 34
24.5%
온천동 3
 
2.2%
금강로 2
 
1.4%
온천천로 2
 
1.4%
25(명장동 1
 
0.7%
명안로53번길 1
 
0.7%
26(명장동 1
 
0.7%
명장로106번길 1
 
0.7%
45(명장동 1
 
0.7%
Other values (59) 59
42.4%
2023-12-11T02:08:39.837229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
 
12.4%
동 70
 
8.3%
래 36
 
4.3%
1 35
 
4.1%
시 35
 
4.1%
산 35
 
4.1%
부 34
 
4.0%
) 34
 
4.0%
로 34
 
4.0%
( 34
 
4.0%
Other values (47) 392
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 535
63.4%
Decimal Number 133
 
15.8%
Space Separator 105
 
12.4%
Close Punctuation 34
 
4.0%
Open Punctuation 34
 
4.0%
Dash Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 70
13.1%
래 36
 
6.7%
시 35
 
6.5%
산 35
 
6.5%
부 34
 
6.4%
로 34
 
6.4%
구 34
 
6.4%
역 34
 
6.4%
광 34
 
6.4%
번 21
 
3.9%
Other values (33) 168
31.4%
Decimal Number
ValueCountFrequency (%)
1 35
26.3%
2 22
16.5%
3 18
13.5%
5 16
12.0%
6 10
 
7.5%
8 9
 
6.8%
4 8
 
6.0%
7 7
 
5.3%
9 6
 
4.5%
0 2
 
1.5%
Space Separator
ValueCountFrequency (%)
105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 535
63.4%
Common 309
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 70
13.1%
래 36
 
6.7%
시 35
 
6.5%
산 35
 
6.5%
부 34
 
6.4%
로 34
 
6.4%
구 34
 
6.4%
역 34
 
6.4%
광 34
 
6.4%
번 21
 
3.9%
Other values (33) 168
31.4%
Common
ValueCountFrequency (%)
105
34.0%
1 35
 
11.3%
) 34
 
11.0%
( 34
 
11.0%
2 22
 
7.1%
3 18
 
5.8%
5 16
 
5.2%
6 10
 
3.2%
8 9
 
2.9%
4 8
 
2.6%
Other values (4) 18
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 535
63.4%
ASCII 309
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
34.0%
1 35
 
11.3%
) 34
 
11.0%
( 34
 
11.0%
2 22
 
7.1%
3 18
 
5.8%
5 16
 
5.2%
6 10
 
3.2%
8 9
 
2.9%
4 8
 
2.6%
Other values (4) 18
 
5.8%
Hangul
ValueCountFrequency (%)
동 70
13.1%
래 36
 
6.7%
시 35
 
6.5%
산 35
 
6.5%
부 34
 
6.4%
로 34
 
6.4%
구 34
 
6.4%
역 34
 
6.4%
광 34
 
6.4%
번 21
 
3.9%
Other values (33) 168
31.4%

위도
Real number (ℝ)

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.205255
Minimum35.191446
Maximum35.222957
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T02:08:40.018852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.191446
5-th percentile35.195076
Q135.200846
median35.203011
Q335.210699
95-th percentile35.219011
Maximum35.222957
Range0.03151084
Interquartile range (IQR)0.009853445

Descriptive statistics

Standard deviation0.0075067938
Coefficient of variation (CV)0.00021322935
Kurtosis-0.094649117
Mean35.205255
Median Absolute Deviation (MAD)0.0033171
Skewness0.58621992
Sum1196.9787
Variance5.6351953 × 10-5
MonotonicityNot monotonic
2023-12-11T02:08:40.148148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
35.20137428 1
 
2.9%
35.19144632 1
 
2.9%
35.19570734 1
 
2.9%
35.20047538 1
 
2.9%
35.19790721 1
 
2.9%
35.19934354 1
 
2.9%
35.19468277 1
 
2.9%
35.19528744 1
 
2.9%
35.20199789 1
 
2.9%
35.20083075 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
35.19144632 1
2.9%
35.19468277 1
2.9%
35.19528744 1
2.9%
35.19570734 1
2.9%
35.19790721 1
2.9%
35.19934354 1
2.9%
35.20047538 1
2.9%
35.20081401 1
2.9%
35.20083075 1
2.9%
35.20089022 1
2.9%
ValueCountFrequency (%)
35.22295716 1
2.9%
35.21996261 1
2.9%
35.21849864 1
2.9%
35.2151854 1
2.9%
35.21491533 1
2.9%
35.21332638 1
2.9%
35.21268222 1
2.9%
35.21254481 1
2.9%
35.21152805 1
2.9%
35.2082121 1
2.9%

경도
Real number (ℝ)

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.08479
Minimum129.0541
Maximum129.11333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T02:08:40.278067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.0541
5-th percentile129.05912
Q1129.07405
median129.08258
Q3129.09741
95-th percentile129.10957
Maximum129.11333
Range0.0592327
Interquartile range (IQR)0.023360025

Descriptive statistics

Standard deviation0.016062901
Coefficient of variation (CV)0.00012443682
Kurtosis-0.78978322
Mean129.08479
Median Absolute Deviation (MAD)0.0126335
Skewness-0.0063890316
Sum4388.8828
Variance0.00025801678
MonotonicityNot monotonic
2023-12-11T02:08:40.412106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
129.0881812 1
 
2.9%
129.1095221 1
 
2.9%
129.057469 1
 
2.9%
129.0784338 1
 
2.9%
129.0695563 1
 
2.9%
129.0985242 1
 
2.9%
129.0993835 1
 
2.9%
129.1060929 1
 
2.9%
129.1032665 1
 
2.9%
129.0624269 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
129.0541011 1
2.9%
129.057469 1
2.9%
129.0600152 1
2.9%
129.0624269 1
2.9%
129.0645117 1
2.9%
129.0695563 1
2.9%
129.070337 1
2.9%
129.0733436 1
2.9%
129.0737556 1
2.9%
129.0749169 1
2.9%
ValueCountFrequency (%)
129.1133338 1
2.9%
129.109663 1
2.9%
129.1095221 1
2.9%
129.1083192 1
2.9%
129.1060929 1
2.9%
129.1032665 1
2.9%
129.0993835 1
2.9%
129.0985242 1
2.9%
129.0977115 1
2.9%
129.0964893 1
2.9%

수용가능면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean966.46
Minimum165
Maximum2987
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T02:08:40.546162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum165
5-th percentile319.7
Q1692.25
median845.625
Q3988.4825
95-th percentile2010.2155
Maximum2987
Range2822
Interquartile range (IQR)296.2325

Descriptive statistics

Standard deviation570.09433
Coefficient of variation (CV)0.58987887
Kurtosis4.0823541
Mean966.46
Median Absolute Deviation (MAD)151.5
Skewness1.7719991
Sum32859.64
Variance325007.55
MonotonicityNot monotonic
2023-12-11T02:08:40.693723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
720.0 2
 
5.9%
165.0 2
 
5.9%
924.35 1
 
2.9%
589.0 1
 
2.9%
1258.67 1
 
2.9%
588.0 1
 
2.9%
776.0 1
 
2.9%
991.0 1
 
2.9%
825.0 1
 
2.9%
980.93 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
165.0 2
5.9%
403.0 1
2.9%
471.0 1
2.9%
527.0 1
2.9%
588.0 1
2.9%
589.0 1
2.9%
616.0 1
2.9%
688.0 1
2.9%
705.0 1
2.9%
720.0 2
5.9%
ValueCountFrequency (%)
2987.0 1
2.9%
2066.33 1
2.9%
1980.0 1
2.9%
1973.0 1
2.9%
1537.0 1
2.9%
1258.67 1
2.9%
1177.02 1
2.9%
1141.66 1
2.9%
991.0 1
2.9%
980.93 1
2.9%

수용가능인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean250.08824
Minimum30
Maximum794
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T02:08:40.905035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile35.2
Q166.25
median270
Q3367
95-th percentile521.45
Maximum794
Range764
Interquartile range (IQR)300.75

Descriptive statistics

Standard deviation183.63986
Coefficient of variation (CV)0.73430027
Kurtosis0.7505589
Mean250.08824
Median Absolute Deviation (MAD)141.5
Skewness0.76410426
Sum8503
Variance33723.598
MonotonicityNot monotonic
2023-12-11T02:08:41.094903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
30 2
 
5.9%
63 2
 
5.9%
381 1
 
2.9%
226 1
 
2.9%
276 1
 
2.9%
484 1
 
2.9%
38 1
 
2.9%
298 1
 
2.9%
54 1
 
2.9%
155 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
30 2
5.9%
38 1
2.9%
40 1
2.9%
44 1
2.9%
52 1
2.9%
54 1
2.9%
63 2
5.9%
76 1
2.9%
86 1
2.9%
90 1
2.9%
ValueCountFrequency (%)
794 1
2.9%
591 1
2.9%
484 1
2.9%
452 1
2.9%
438 1
2.9%
381 1
2.9%
377 1
2.9%
376 1
2.9%
371 1
2.9%
355 1
2.9%

대표전화
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing2
Missing (%)5.9%
Memory size404.0 B
2023-12-11T02:08:41.422059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters384
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

Unique32 ?
Unique (%)100.0%

Sample

1st row051-552-9798
2nd row051-550-8606
3rd row051-555-0151
4th row051-557-5291
5th row051-558-1212
ValueCountFrequency (%)
051-790-0505 1
 
3.1%
051-550-8606 1
 
3.1%
051-500-3200 1
 
3.1%
051-500-0406 1
 
3.1%
051-559-3900 1
 
3.1%
051-590-0500 1
 
3.1%
051-522-4228 1
 
3.1%
051-520-1600 1
 
3.1%
051-552-9798 1
 
3.1%
051-502-4700 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T02:08:41.943027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 92
24.0%
5 86
22.4%
- 64
16.7%
1 46
12.0%
2 22
 
5.7%
4 15
 
3.9%
9 13
 
3.4%
3 13
 
3.4%
7 12
 
3.1%
6 12
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 320
83.3%
Dash Punctuation 64
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 92
28.7%
5 86
26.9%
1 46
14.4%
2 22
 
6.9%
4 15
 
4.7%
9 13
 
4.1%
3 13
 
4.1%
7 12
 
3.8%
6 12
 
3.8%
8 9
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 92
24.0%
5 86
22.4%
- 64
16.7%
1 46
12.0%
2 22
 
5.7%
4 15
 
3.9%
9 13
 
3.4%
3 13
 
3.4%
7 12
 
3.1%
6 12
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 92
24.0%
5 86
22.4%
- 64
16.7%
1 46
12.0%
2 22
 
5.7%
4 15
 
3.9%
9 13
 
3.4%
3 13
 
3.4%
7 12
 
3.1%
6 12
 
3.1%

내진설계
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
적용
23 
미적용
11 

Length

Max length3
Median length2
Mean length2.3235294
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미적용
2nd row미적용
3rd row미적용
4th row적용
5th row미적용

Common Values

ValueCountFrequency (%)
적용 23
67.6%
미적용 11
32.4%

Length

2023-12-11T02:08:42.148098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:08:42.323128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적용 23
67.6%
미적용 11
32.4%

사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size166.0 B
True
34 
ValueCountFrequency (%)
True 34
100.0%
2023-12-11T02:08:42.458262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

지정일자
Date

Distinct4
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
Minimum2019-01-01 00:00:00
Maximum2021-03-11 00:00:00
2023-12-11T02:08:42.584371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:42.724840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

Interactions

2023-12-11T02:08:35.375370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:33.596717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:34.212226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:34.818231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:35.541896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:33.760900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:34.367791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:34.957111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:35.678121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:33.905206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:34.514290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:35.089071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:35.811410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:34.060651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:34.657891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:08:35.211305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:08:43.266405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역명시설구분시설명상세시설명상세주소위도경도수용가능면적(제곱미터)수용가능인원(명)대표전화내진설계지정일자
지역명1.0000.5931.0000.0001.0000.4420.7610.5210.5621.0000.3730.216
시설구분0.5931.0001.0001.0001.0000.1750.6220.3860.7351.0000.3430.745
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상세시설명0.0001.0001.0001.0001.0000.9690.9260.9751.0001.0001.0001.000
상세주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도0.4420.1751.0000.9691.0001.0000.0000.0000.1341.0000.0000.292
경도0.7610.6221.0000.9261.0000.0001.0000.0000.6511.0000.5060.068
수용가능면적(제곱미터)0.5210.3861.0000.9751.0000.0000.0001.0000.8901.0000.1530.391
수용가능인원(명)0.5620.7351.0001.0001.0000.1340.6510.8901.0001.0000.5180.895
대표전화1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
내진설계0.3730.3431.0001.0001.0000.0000.5060.1530.5181.0001.0000.753
지정일자0.2160.7451.0001.0001.0000.2920.0680.3910.8951.0000.7531.000
2023-12-11T02:08:43.482386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
내진설계시설구분지역명
내진설계1.0000.5380.320
시설구분0.5381.0000.276
지역명0.3200.2761.000
2023-12-11T02:08:43.641321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도수용가능면적(제곱미터)수용가능인원(명)지역명시설구분내진설계
위도1.000-0.1870.153-0.1680.1890.0140.000
경도-0.1871.0000.1920.2350.4810.4170.351
수용가능면적(제곱미터)0.1530.1921.0000.5380.3020.0000.000
수용가능인원(명)-0.1680.2350.5381.0000.2980.5760.344
지역명0.1890.4810.3020.2981.0000.2760.320
시설구분0.0140.4170.0000.5760.2761.0000.538
내진설계0.0000.3510.0000.3440.3200.5381.000

Missing values

2023-12-11T02:08:36.059591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:08:36.371516image/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

지역명시설구분시설명상세시설명상세주소위도경도수용가능면적(제곱미터)수용가능인원(명)대표전화내진설계사용여부지정일자
0부산광역시 동래구 낙민동연수,숙박스위트모텔2인실 27호부산광역시 동래구 충렬대로255번길 18(낙민동)35.201374129.088181825.054051-552-9798미적용Y2019-08-09
1부산광역시 동래구 수안동연수,숙박화성빌2인실 15호부산광역시 동래구 충렬대로237번가길 11(수안동)35.202511129.085973471.030<NA>미적용Y2019-08-09
2부산광역시 동래구 복천동학교내성초등학교2층 강당(참빛관)부산광역시 동래구 동래로 173(복천동)35.204371129.089688527.0202051-550-8606미적용Y2019-01-01
3부산광역시 동래구 칠산동학교동래고등학교별관2층 체육관(군붕관)부산광역시 동래구 충렬대로285번길 22(칠산동)35.20089129.0927451537.0591051-555-0151적용Y2021-03-11
4부산광역시 동래구 명륜동교회새한교회본관 1층부산광역시 동래구 명륜로218번길 6(명륜동)35.212682129.08363797.0306051-557-5291미적용Y2019-01-01
5부산광역시 동래구 명륜동연수,숙박락모텔2인실 22호부산광역시 동래구 명륜로 125(명륜동)35.204826129.082205940.044051-558-1212미적용Y2019-08-09
6부산광역시 동래구 명륜동연수,숙박브이모텔2인실 43호부산광역시 동래구 명륜로112번가길 36(명륜동)35.205078129.0829561980.086051-552-3420적용Y2019-08-09
7부산광역시 동래구 명륜동학교부산중앙여자고등학교강당부산광역시 동래구 온천천로 131(명륜동)35.208118129.079629760.23292051-550-0370적용Y2021-03-11
8부산광역시 동래구 온천동연수,숙박노블래스2인실 26호부산광역시 동래구 금강공원로 41-2 (온천동)35.218499129.079909720.052<NA>미적용Y2019-08-09
9부산광역시 동래구 온천동연수,숙박동남장모텔2인실 20호부산광역시 동래구 금강로 161-3 (온천동)35.222957129.081006705.040051-550-4314미적용Y2019-08-09
지역명시설구분시설명상세시설명상세주소위도경도수용가능면적(제곱미터)수용가능인원(명)대표전화내진설계사용여부지정일자
24부산광역시 동래구 안락동학교안진초등학교3층 강당(안진관)부산광역시 동래구 안남로 63(안락동)35.194683129.099383776.0298051-520-1600적용Y2019-01-01
25부산광역시 동래구 안락동교회순복음안락교회교육관 1~3층부산광역시 동래구 연안로81번길 47(안락동)35.195287129.106093991.0381051-532-0441미적용Y2019-01-01
26부산광역시 동래구 안락동학교안락중학교동역관 3층(체육관)부산광역시 동래구 온천천로 513(안락동)35.191446129.109522924.35355051-790-0700적용Y2021-03-11
27부산광역시 동래구 명장동학교안락초등학교별관 2층 강당(안락마루)부산광역시 동래구 명안로53번길 22(명장동)35.201998129.103266980.0376051-713-8507적용Y2021-03-11
28부산광역시 동래구 명장동학교충렬고등학교별관 2층 강당(청운관)부산광역시 동래구 명장로106번길 26(명장동)35.20257129.1096631177.02452051-510-0492적용Y2021-03-11
29부산광역시 동래구 명장동학교충렬중학교별관 2층 강당(충비관)부산광역시 동래구 명장로64번길 45(명장동)35.202946129.108319965.2371051-520-3300적용Y2021-03-11
30부산광역시 동래구 명장동학교혜화초등학교도서관 건물부산광역시 동래구 명장로99번길 25(명장동)35.202262129.113334165.063051-531-1668적용Y2019-01-01
31부산광역시 동래구 명장동학교대명여자고등학교2층 강당(일석헌)부산광역시 동래구 시실로 135(명장동)35.211528129.09646688.0264051-526-3452적용Y2019-01-01
32부산광역시 동래구 명장동학교동신중학교별관2층 강당(해랑관)부산광역시 동래구 충렬사로51번길 38(명장동)35.205978129.0977121141.66438051-540-2500적용Y2021-03-11
33부산광역시 동래구 명장동학교명장초등학교별관 3층 강당(라온누리)부산광역시 동래구 복천로 121(명장동)35.208212129.0964892066.33794051-529-0646적용Y2021-03-11