Overview

Dataset statistics

Number of variables8
Number of observations715
Missing cells1456
Missing cells (%)25.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory48.3 KiB
Average record size in memory69.2 B

Variable types

Numeric2
Text3
Unsupported2
Categorical1

Dataset

Description관리번호,대피소 명칭,대피소 상세주소,면적,수용가능인원,행정동 코드,행정동 명칭,비고
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21181/S/1/datasetView.do

Alerts

수용가능인원 has constant value ""Constant
대피소 상세주소 has 26 (3.6%) missing valuesMissing
면적 has 715 (100.0%) missing valuesMissing
비고 has 715 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 01:22:58.441862
Analysis finished2024-05-11 01:23:01.343175
Duration2.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

UNIQUE 

Distinct715
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47387.315
Minimum46793
Maximum47747
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-05-11T01:23:01.571601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46793
5-th percentile47068.7
Q147211.5
median47390
Q347568.5
95-th percentile47711.3
Maximum47747
Range954
Interquartile range (IQR)357

Descriptive statistics

Standard deviation212.60527
Coefficient of variation (CV)0.0044865439
Kurtosis-0.80692679
Mean47387.315
Median Absolute Deviation (MAD)179
Skewness-0.154783
Sum33881930
Variance45201
MonotonicityNot monotonic
2024-05-11T01:23:02.022429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47359 1
 
0.1%
47136 1
 
0.1%
47116 1
 
0.1%
47117 1
 
0.1%
47118 1
 
0.1%
47119 1
 
0.1%
47120 1
 
0.1%
47121 1
 
0.1%
47122 1
 
0.1%
47123 1
 
0.1%
Other values (705) 705
98.6%
ValueCountFrequency (%)
46793 1
0.1%
46794 1
0.1%
46795 1
0.1%
46796 1
0.1%
46797 1
0.1%
46798 1
0.1%
46799 1
0.1%
46800 1
0.1%
47041 1
0.1%
47042 1
0.1%
ValueCountFrequency (%)
47747 1
0.1%
47746 1
0.1%
47745 1
0.1%
47744 1
0.1%
47743 1
0.1%
47742 1
0.1%
47741 1
0.1%
47740 1
0.1%
47739 1
0.1%
47738 1
0.1%

대피소 명칭
Text

Distinct714
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-05-11T01:23:02.547879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length6.6111888
Min length4

Characters and Unicode

Total characters4727
Distinct characters268
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

Unique713 ?
Unique (%)99.7%

Sample

1st row화촌 경로당
2nd row화곡초등학교
3rd row신길6동 주민센터
4th row구로2동 주민센터
5th row현장민원실
ValueCountFrequency (%)
주민센터 62
 
7.4%
경로당 36
 
4.3%
서울 4
 
0.5%
강당 3
 
0.4%
천호2동 2
 
0.2%
체육관 2
 
0.2%
천호초등학교 2
 
0.2%
일심 2
 
0.2%
영등포동 2
 
0.2%
초등학교 2
 
0.2%
Other values (726) 726
86.1%
2024-05-11T01:23:03.672850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 519
 
11.0%
학 428
 
9.1%
등 327
 
6.9%
초 286
 
6.1%
동 148
 
3.1%
128
 
2.7%
중 117
 
2.5%
터 94
 
2.0%
회 93
 
2.0%
센 92
 
1.9%
Other values (258) 2495
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4484
94.9%
Space Separator 128
 
2.7%
Decimal Number 89
 
1.9%
Open Punctuation 13
 
0.3%
Close Punctuation 10
 
0.2%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 519
 
11.6%
학 428
 
9.5%
등 327
 
7.3%
초 286
 
6.4%
동 148
 
3.3%
중 117
 
2.6%
터 94
 
2.1%
회 93
 
2.1%
센 92
 
2.1%
주 91
 
2.0%
Other values (246) 2289
51.0%
Decimal Number
ValueCountFrequency (%)
2 35
39.3%
1 35
39.3%
3 9
 
10.1%
4 5
 
5.6%
5 2
 
2.2%
6 2
 
2.2%
7 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
@ 1
33.3%
Space Separator
ValueCountFrequency (%)
128
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4484
94.9%
Common 243
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 519
 
11.6%
학 428
 
9.5%
등 327
 
7.3%
초 286
 
6.4%
동 148
 
3.3%
중 117
 
2.6%
터 94
 
2.1%
회 93
 
2.1%
센 92
 
2.1%
주 91
 
2.0%
Other values (246) 2289
51.0%
Common
ValueCountFrequency (%)
128
52.7%
2 35
 
14.4%
1 35
 
14.4%
( 13
 
5.3%
) 10
 
4.1%
3 9
 
3.7%
4 5
 
2.1%
5 2
 
0.8%
, 2
 
0.8%
6 2
 
0.8%
Other values (2) 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4484
94.9%
ASCII 243
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 519
 
11.6%
학 428
 
9.5%
등 327
 
7.3%
초 286
 
6.4%
동 148
 
3.3%
중 117
 
2.6%
터 94
 
2.1%
회 93
 
2.1%
센 92
 
2.1%
주 91
 
2.0%
Other values (246) 2289
51.0%
ASCII
ValueCountFrequency (%)
128
52.7%
2 35
 
14.4%
1 35
 
14.4%
( 13
 
5.3%
) 10
 
4.1%
3 9
 
3.7%
4 5
 
2.1%
5 2
 
0.8%
, 2
 
0.8%
6 2
 
0.8%
Other values (2) 2
 
0.8%

대피소 상세주소
Text

MISSING 

Distinct681
Distinct (%)98.8%
Missing26
Missing (%)3.6%
Memory size5.7 KiB
2024-05-11T01:23:04.540882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length12.552975
Min length5

Characters and Unicode

Total characters8649
Distinct characters251
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

Unique675 ?
Unique (%)98.0%

Sample

1st row화곡본동 105-382
2nd row화곡동 24-266
3rd row신길동 3741-11
4th row구로2동 704-12
5th row노량진동 10-23
ValueCountFrequency (%)
신길동 19
 
1.1%
강동구 15
 
0.9%
상도동 10
 
0.6%
대림동 10
 
0.6%
사당동 10
 
0.6%
화곡동 8
 
0.5%
미아동 8
 
0.5%
산 8
 
0.5%
구로동 8
 
0.5%
시루봉로 7
 
0.4%
Other values (1231) 1624
94.0%
2024-05-11T01:23:05.816259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1038
 
12.0%
동 680
 
7.9%
1 665
 
7.7%
2 565
 
6.5%
3 449
 
5.2%
- 434
 
5.0%
4 342
 
4.0%
5 278
 
3.2%
6 271
 
3.1%
7 238
 
2.8%
Other values (241) 3689
42.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3433
39.7%
Other Letter 3266
37.8%
Space Separator 1038
 
12.0%
Dash Punctuation 434
 
5.0%
Close Punctuation 235
 
2.7%
Open Punctuation 235
 
2.7%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 680
 
20.8%
길 199
 
6.1%
로 195
 
6.0%
신 78
 
2.4%
가 67
 
2.1%
산 61
 
1.9%
구 58
 
1.8%
화 57
 
1.7%
곡 50
 
1.5%
정 47
 
1.4%
Other values (225) 1774
54.3%
Decimal Number
ValueCountFrequency (%)
1 665
19.4%
2 565
16.5%
3 449
13.1%
4 342
10.0%
5 278
8.1%
6 271
7.9%
7 238
 
6.9%
9 211
 
6.1%
8 208
 
6.1%
0 206
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 5
62.5%
? 3
37.5%
Space Separator
ValueCountFrequency (%)
1038
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 434
100.0%
Close Punctuation
ValueCountFrequency (%)
) 235
100.0%
Open Punctuation
ValueCountFrequency (%)
( 235
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5383
62.2%
Hangul 3266
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 680
 
20.8%
길 199
 
6.1%
로 195
 
6.0%
신 78
 
2.4%
가 67
 
2.1%
산 61
 
1.9%
구 58
 
1.8%
화 57
 
1.7%
곡 50
 
1.5%
정 47
 
1.4%
Other values (225) 1774
54.3%
Common
ValueCountFrequency (%)
1038
19.3%
1 665
12.4%
2 565
10.5%
3 449
8.3%
- 434
8.1%
4 342
 
6.4%
5 278
 
5.2%
6 271
 
5.0%
7 238
 
4.4%
) 235
 
4.4%
Other values (6) 868
16.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5383
62.2%
Hangul 3266
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1038
19.3%
1 665
12.4%
2 565
10.5%
3 449
8.3%
- 434
8.1%
4 342
 
6.4%
5 278
 
5.2%
6 271
 
5.0%
7 238
 
4.4%
) 235
 
4.4%
Other values (6) 868
16.1%
Hangul
ValueCountFrequency (%)
동 680
 
20.8%
길 199
 
6.1%
로 195
 
6.0%
신 78
 
2.4%
가 67
 
2.1%
산 61
 
1.9%
구 58
 
1.8%
화 57
 
1.7%
곡 50
 
1.5%
정 47
 
1.4%
Other values (225) 1774
54.3%

면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing715
Missing (%)100.0%
Memory size6.4 KiB

수용가능인원
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
0
715 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 715
100.0%

Length

2024-05-11T01:23:06.577534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:23:06.896727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 715
100.0%

행정동 코드
Real number (ℝ)

Distinct358
Distinct (%)50.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11453172
Minimum11110515
Maximum11740700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-05-11T01:23:07.304016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110515
5-th percentile11170555
Q111290655
median11470650
Q311590540
95-th percentile11740573
Maximum11740700
Range630185
Interquartile range (IQR)299885

Descriptive statistics

Standard deviation184751.04
Coefficient of variation (CV)0.016130994
Kurtosis-1.0910758
Mean11453172
Median Absolute Deviation (MAD)150065
Skewness-0.14532859
Sum8.189018 × 109
Variance3.4132948 × 1010
MonotonicityNot monotonic
2024-05-11T01:23:08.084158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11440680 8
 
1.1%
11560605 7
 
1.0%
11560620 7
 
1.0%
11500540 7
 
1.0%
11530540 6
 
0.8%
11215810 5
 
0.7%
11215830 5
 
0.7%
11740610 5
 
0.7%
11215770 5
 
0.7%
11560720 5
 
0.7%
Other values (348) 655
91.6%
ValueCountFrequency (%)
11110515 4
0.6%
11110530 2
0.3%
11110540 1
 
0.1%
11110550 1
 
0.1%
11110560 3
0.4%
11110570 2
0.3%
11110580 1
 
0.1%
11110600 2
0.3%
11110615 1
 
0.1%
11110630 1
 
0.1%
ValueCountFrequency (%)
11740700 2
 
0.3%
11740690 2
 
0.3%
11740685 5
0.7%
11740660 2
 
0.3%
11740650 4
0.6%
11740640 3
0.4%
11740620 4
0.6%
11740610 5
0.7%
11740600 4
0.6%
11740590 3
0.4%

행정동 명칭
Text

Distinct358
Distinct (%)50.1%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-05-11T01:23:09.096578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length3.7832168
Min length2

Characters and Unicode

Total characters2705
Distinct characters177
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

Unique165 ?
Unique (%)23.1%

Sample

1st row화곡본동
2nd row화곡본동
3rd row신길6동
4th row구로2동
5th row노량진1동
ValueCountFrequency (%)
합정동 8
 
1.1%
양평2동 7
 
1.0%
화곡1동 7
 
1.0%
문래동 7
 
1.0%
구로3동 6
 
0.8%
우장산동 5
 
0.7%
광장동 5
 
0.7%
천호2동 5
 
0.7%
중곡4동 5
 
0.7%
자양2동 5
 
0.7%
Other values (348) 655
91.6%
2024-05-11T01:23:10.951353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 711
26.3%
2 165
 
6.1%
1 158
 
5.8%
3 75
 
2.8%
신 71
 
2.6%
화 49
 
1.8%
곡 39
 
1.4%
4 38
 
1.4%
방 34
 
1.3%
정 33
 
1.2%
Other values (167) 1332
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2212
81.8%
Decimal Number 480
 
17.7%
Other Punctuation 13
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 711
32.1%
신 71
 
3.2%
화 49
 
2.2%
곡 39
 
1.8%
방 34
 
1.5%
정 33
 
1.5%
가 28
 
1.3%
산 26
 
1.2%
대 26
 
1.2%
성 26
 
1.2%
Other values (156) 1169
52.8%
Decimal Number
ValueCountFrequency (%)
2 165
34.4%
1 158
32.9%
3 75
15.6%
4 38
 
7.9%
5 14
 
2.9%
6 11
 
2.3%
8 9
 
1.9%
7 8
 
1.7%
9 1
 
0.2%
0 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2212
81.8%
Common 493
 
18.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 711
32.1%
신 71
 
3.2%
화 49
 
2.2%
곡 39
 
1.8%
방 34
 
1.5%
정 33
 
1.5%
가 28
 
1.3%
산 26
 
1.2%
대 26
 
1.2%
성 26
 
1.2%
Other values (156) 1169
52.8%
Common
ValueCountFrequency (%)
2 165
33.5%
1 158
32.0%
3 75
15.2%
4 38
 
7.7%
5 14
 
2.8%
. 13
 
2.6%
6 11
 
2.2%
8 9
 
1.8%
7 8
 
1.6%
9 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2212
81.8%
ASCII 493
 
18.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 711
32.1%
신 71
 
3.2%
화 49
 
2.2%
곡 39
 
1.8%
방 34
 
1.5%
정 33
 
1.5%
가 28
 
1.3%
산 26
 
1.2%
대 26
 
1.2%
성 26
 
1.2%
Other values (156) 1169
52.8%
ASCII
ValueCountFrequency (%)
2 165
33.5%
1 158
32.0%
3 75
15.2%
4 38
 
7.7%
5 14
 
2.8%
. 13
 
2.6%
6 11
 
2.2%
8 9
 
1.8%
7 8
 
1.6%
9 1
 
0.2%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing715
Missing (%)100.0%
Memory size6.4 KiB

Interactions

2024-05-11T01:22:59.988164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:22:59.364974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:23:00.303092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:22:59.593722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T01:23:11.388733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정동 코드
관리번호1.0000.217
행정동 코드0.2171.000
2024-05-11T01:23:11.691492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정동 코드
관리번호1.000-0.061
행정동 코드-0.0611.000

Missing values

2024-05-11T01:23:00.709610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T01:23:01.174123image/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

관리번호대피소 명칭대피소 상세주소면적수용가능인원행정동 코드행정동 명칭비고
047359화촌 경로당화곡본동 105-382<NA>011500590화곡본동<NA>
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