Overview

Dataset statistics

Number of variables10
Number of observations40
Missing cells16
Missing cells (%)4.0%
Duplicate rows1
Duplicate rows (%)2.5%
Total size in memory3.3 KiB
Average record size in memory83.3 B

Variable types

Unsupported3
Categorical4
Text3

Dataset

Description서울특별시 중구 관내 이재민 임시주거시설 현황입니다.
Author서울특별시 중구
URLhttps://www.data.go.kr/data/3078670/fileData.do

Alerts

Dataset has 1 (2.5%) duplicate rowsDuplicates
Unnamed: 1 is highly overall correlated with Unnamed: 5 and 1 other fieldsHigh correlation
Unnamed: 9 is highly overall correlated with Unnamed: 1 and 1 other fieldsHigh correlation
Unnamed: 5 is highly overall correlated with Unnamed: 1 and 2 other fieldsHigh correlation
Unnamed: 6 is highly overall correlated with Unnamed: 5High correlation
이재민 임시주거시설 현황 has 3 (7.5%) missing valuesMissing
Unnamed: 2 has 3 (7.5%) missing valuesMissing
Unnamed: 3 has 3 (7.5%) missing valuesMissing
Unnamed: 4 has 3 (7.5%) missing valuesMissing
Unnamed: 7 has 2 (5.0%) missing valuesMissing
Unnamed: 8 has 2 (5.0%) missing valuesMissing
이재민 임시주거시설 현황 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 20:58:17.454362
Analysis finished2023-12-12 20:58:18.439218
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

이재민 임시주거시설 현황
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)7.5%
Memory size452.0 B

Unnamed: 1
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
신당동
5 
명동
3 
장충동
3 
을지로동
3 
회현동
3 
Other values (12)
23 

Length

Max length4
Median length3
Mean length3.075
Min length2

Unique

Unique3 ?
Unique (%)7.5%

Sample

1st row<NA>
2nd row행정동
3rd row<NA>
4th row<NA>
5th row소공동

Common Values

ValueCountFrequency (%)
신당동 5
12.5%
명동 3
 
7.5%
장충동 3
 
7.5%
을지로동 3
 
7.5%
회현동 3
 
7.5%
소공동 3
 
7.5%
<NA> 3
 
7.5%
청구동 2
 
5.0%
동화동 2
 
5.0%
신당5동 2
 
5.0%
Other values (7) 11
27.5%

Length

2023-12-13T05:58:18.525007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신당동 5
12.5%
장충동 3
 
7.5%
을지로동 3
 
7.5%
회현동 3
 
7.5%
소공동 3
 
7.5%
na 3
 
7.5%
명동 3
 
7.5%
약수동 2
 
5.0%
필동 2
 
5.0%
다산동 2
 
5.0%
Other values (7) 11
27.5%

Unnamed: 2
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing3
Missing (%)7.5%
Memory size452.0 B
2023-12-13T05:58:18.787317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.0540541
Min length3

Characters and Unicode

Total characters224
Distinct characters75
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row시설명
2nd row덕수초등학교
3rd row소공동주민센터
4th row창덕여자중학교
5th row회현어린이집
ValueCountFrequency (%)
남산초등학교 1
 
2.6%
다산경로당 1
 
2.6%
황학동청사 1
 
2.6%
한양공업고등학교 1
 
2.6%
신당경로당 1
 
2.6%
광희초등학교 1
 
2.6%
성동글로벌경영고등학교 1
 
2.6%
성동공업고등학교 1
 
2.6%
장충초등학교 1
 
2.6%
약수교회 1
 
2.6%
Other values (28) 28
73.7%
2023-12-13T05:58:19.225169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 16
 
7.1%
학 12
 
5.4%
로 11
 
4.9%
당 11
 
4.9%
동 10
 
4.5%
등 10
 
4.5%
경 10
 
4.5%
회 10
 
4.5%
초 6
 
2.7%
지 5
 
2.2%
Other values (65) 123
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 223
99.6%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 16
 
7.2%
학 12
 
5.4%
로 11
 
4.9%
당 11
 
4.9%
동 10
 
4.5%
등 10
 
4.5%
경 10
 
4.5%
회 10
 
4.5%
초 6
 
2.7%
지 5
 
2.2%
Other values (64) 122
54.7%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 223
99.6%
Common 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 16
 
7.2%
학 12
 
5.4%
로 11
 
4.9%
당 11
 
4.9%
동 10
 
4.5%
등 10
 
4.5%
경 10
 
4.5%
회 10
 
4.5%
초 6
 
2.7%
지 5
 
2.2%
Other values (64) 122
54.7%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 223
99.6%
ASCII 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 16
 
7.2%
학 12
 
5.4%
로 11
 
4.9%
당 11
 
4.9%
동 10
 
4.5%
등 10
 
4.5%
경 10
 
4.5%
회 10
 
4.5%
초 6
 
2.7%
지 5
 
2.2%
Other values (64) 122
54.7%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 3
Text

MISSING 

Distinct28
Distinct (%)75.7%
Missing3
Missing (%)7.5%
Memory size452.0 B
2023-12-13T05:58:19.480132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length10
Mean length4.2972973
Min length2

Characters and Unicode

Total characters159
Distinct characters41
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

Unique23 ?
Unique (%)62.2%

Sample

1st row세부시설명
2nd row2층 체육관
3rd row4층강당
4th row1층강당
5th row1층강당
ValueCountFrequency (%)
1층 6
 
15.0%
2층 3
 
7.5%
1층강당 2
 
5.0%
강당 2
 
5.0%
체육관 2
 
5.0%
4층강당 2
 
5.0%
지하1층 2
 
5.0%
교육관지하 1
 
2.5%
신관 1
 
2.5%
지하강당 1
 
2.5%
Other values (18) 18
45.0%
2023-12-13T05:58:20.202528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
층 30
18.9%
1 16
 
10.1%
강 12
 
7.5%
당 11
 
6.9%
, 9
 
5.7%
관 8
 
5.0%
2 6
 
3.8%
지 6
 
3.8%
하 6
 
3.8%
3 6
 
3.8%
Other values (31) 49
30.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109
68.6%
Decimal Number 34
 
21.4%
Other Punctuation 9
 
5.7%
Space Separator 3
 
1.9%
Close Punctuation 2
 
1.3%
Open Punctuation 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 30
27.5%
강 12
 
11.0%
당 11
 
10.1%
관 8
 
7.3%
지 6
 
5.5%
하 6
 
5.5%
동 3
 
2.8%
육 3
 
2.8%
대 2
 
1.8%
신 2
 
1.8%
Other values (22) 26
23.9%
Decimal Number
ValueCountFrequency (%)
1 16
47.1%
2 6
 
17.6%
3 6
 
17.6%
4 5
 
14.7%
5 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109
68.6%
Common 50
31.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 30
27.5%
강 12
 
11.0%
당 11
 
10.1%
관 8
 
7.3%
지 6
 
5.5%
하 6
 
5.5%
동 3
 
2.8%
육 3
 
2.8%
대 2
 
1.8%
신 2
 
1.8%
Other values (22) 26
23.9%
Common
ValueCountFrequency (%)
1 16
32.0%
, 9
18.0%
2 6
 
12.0%
3 6
 
12.0%
4 5
 
10.0%
3
 
6.0%
) 2
 
4.0%
( 2
 
4.0%
5 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109
68.6%
ASCII 50
31.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
층 30
27.5%
강 12
 
11.0%
당 11
 
10.1%
관 8
 
7.3%
지 6
 
5.5%
하 6
 
5.5%
동 3
 
2.8%
육 3
 
2.8%
대 2
 
1.8%
신 2
 
1.8%
Other values (22) 26
23.9%
ASCII
ValueCountFrequency (%)
1 16
32.0%
, 9
18.0%
2 6
 
12.0%
3 6
 
12.0%
4 5
 
10.0%
3
 
6.0%
) 2
 
4.0%
( 2
 
4.0%
5 1
 
2.0%

Unnamed: 4
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing3
Missing (%)7.5%
Memory size452.0 B
2023-12-13T05:58:20.498374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.5945946
Min length6

Characters and Unicode

Total characters318
Distinct characters42
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

Unique37 ?
Unique (%)100.0%

Sample

1st row위치(주소)
2nd row덕수궁길 140
3rd row남대문로1길 31-5
4th row정동길 22
5th row퇴계로12가길 23
ValueCountFrequency (%)
11 2
 
2.8%
23 2
 
2.8%
17 2
 
2.8%
40 2
 
2.8%
다산로 2
 
2.8%
퇴계로 2
 
2.8%
16 2
 
2.8%
퇴계로12길 2
 
2.8%
을지로 2
 
2.8%
27 1
 
1.4%
Other values (53) 53
73.6%
2023-12-13T05:58:20.979327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
11.0%
로 34
 
10.7%
2 30
 
9.4%
길 27
 
8.5%
1 25
 
7.9%
0 17
 
5.3%
계 13
 
4.1%
퇴 12
 
3.8%
3 11
 
3.5%
9 11
 
3.5%
Other values (32) 103
32.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142
44.7%
Decimal Number 134
42.1%
Space Separator 35
 
11.0%
Dash Punctuation 5
 
1.6%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 34
23.9%
길 27
19.0%
계 13
 
9.2%
퇴 12
 
8.5%
산 7
 
4.9%
다 7
 
4.9%
동 6
 
4.2%
을 5
 
3.5%
지 5
 
3.5%
호 4
 
2.8%
Other values (18) 22
15.5%
Decimal Number
ValueCountFrequency (%)
2 30
22.4%
1 25
18.7%
0 17
12.7%
3 11
 
8.2%
9 11
 
8.2%
6 11
 
8.2%
7 10
 
7.5%
5 7
 
5.2%
8 6
 
4.5%
4 6
 
4.5%
Space Separator
ValueCountFrequency (%)
35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 176
55.3%
Hangul 142
44.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 34
23.9%
길 27
19.0%
계 13
 
9.2%
퇴 12
 
8.5%
산 7
 
4.9%
다 7
 
4.9%
동 6
 
4.2%
을 5
 
3.5%
지 5
 
3.5%
호 4
 
2.8%
Other values (18) 22
15.5%
Common
ValueCountFrequency (%)
35
19.9%
2 30
17.0%
1 25
14.2%
0 17
9.7%
3 11
 
6.2%
9 11
 
6.2%
6 11
 
6.2%
7 10
 
5.7%
5 7
 
4.0%
8 6
 
3.4%
Other values (4) 13
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 176
55.3%
Hangul 142
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
19.9%
2 30
17.0%
1 25
14.2%
0 17
9.7%
3 11
 
6.2%
9 11
 
6.2%
6 11
 
6.2%
7 10
 
5.7%
5 7
 
4.0%
8 6
 
3.4%
Other values (4) 13
 
7.4%
Hangul
ValueCountFrequency (%)
로 34
23.9%
길 27
19.0%
계 13
 
9.2%
퇴 12
 
8.5%
산 7
 
4.9%
다 7
 
4.9%
동 6
 
4.2%
을 5
 
3.5%
지 5
 
3.5%
호 4
 
2.8%
Other values (18) 22
15.5%

Unnamed: 5
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
풍수해
25 
지진 겸용
11 
<NA>
3 
시설종류
 
1

Length

Max length5
Median length3
Mean length3.65
Min length3

Unique

Unique1 ?
Unique (%)2.5%

Sample

1st row<NA>
2nd row시설종류
3rd row<NA>
4th row<NA>
5th row지진 겸용

Common Values

ValueCountFrequency (%)
풍수해 25
62.5%
지진 겸용 11
27.5%
<NA> 3
 
7.5%
시설종류 1
 
2.5%

Length

2023-12-13T05:58:21.150290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:58:21.262867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
풍수해 25
49.0%
지진 11
21.6%
겸용 11
21.6%
na 3
 
5.9%
시설종류 1
 
2.0%

Unnamed: 6
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
학교
11 
경로당
9 
기타
8 
교회
5 
<NA>
3 
Other values (2)
4 

Length

Max length4
Median length2
Mean length2.5
Min length2

Unique

Unique1 ?
Unique (%)2.5%

Sample

1st row<NA>
2nd row시설유형
3rd row<NA>
4th row<NA>
5th row학교

Common Values

ValueCountFrequency (%)
학교 11
27.5%
경로당 9
22.5%
기타 8
20.0%
교회 5
12.5%
<NA> 3
 
7.5%
관공서 3
 
7.5%
시설유형 1
 
2.5%

Length

2023-12-13T05:58:21.379041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:58:21.520142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
학교 11
27.5%
경로당 9
22.5%
기타 8
20.0%
교회 5
12.5%
na 3
 
7.5%
관공서 3
 
7.5%
시설유형 1
 
2.5%

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)5.0%
Memory size452.0 B

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)5.0%
Memory size452.0 B

Unnamed: 9
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
02-3396-6692
3 
02-3396-8422
3 
02-3396-6572
3 
02-3396-6632
3 
02-3396-6772
3 
Other values (14)
25 

Length

Max length13
Median length12
Mean length11.5
Min length4

Unique

Unique4 ?
Unique (%)10.0%

Sample

1st row(2019. 9월 현재)
2nd row관리자 연락처
3rd row<NA>
4th row<NA>
5th row02-3396-6506

Common Values

ValueCountFrequency (%)
02-3396-6692 3
 
7.5%
02-3396-8422 3
 
7.5%
02-3396-6572 3
 
7.5%
02-3396-6632 3
 
7.5%
02-3396-6772 3
 
7.5%
02-3396-6506 3
 
7.5%
02-3396-6952 2
 
5.0%
02-3396-8455 2
 
5.0%
02-3396-6975 2
 
5.0%
02-3396-6784 2
 
5.0%
Other values (9) 14
35.0%

Length

2023-12-13T05:58:21.652661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02-3396-6692 3
 
7.0%
02-3396-6572 3
 
7.0%
02-3396-6632 3
 
7.0%
02-3396-6772 3
 
7.0%
02-3396-6506 3
 
7.0%
02-3396-8422 3
 
7.0%
02-3396-6665 2
 
4.7%
02-3396-6872 2
 
4.7%
na 2
 
4.7%
02-3396-6603 2
 
4.7%
Other values (12) 17
39.5%

Correlations

2023-12-13T05:58:21.726897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 9
Unnamed: 11.0001.0000.9071.0000.8320.7391.000
Unnamed: 21.0001.0001.0001.0001.0001.0001.000
Unnamed: 30.9071.0001.0001.0000.8970.9330.916
Unnamed: 41.0001.0001.0001.0001.0001.0001.000
Unnamed: 50.8321.0000.8971.0001.0000.9670.852
Unnamed: 60.7391.0000.9331.0000.9671.0000.718
Unnamed: 91.0001.0000.9161.0000.8520.7181.000
2023-12-13T05:58:21.851522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 6Unnamed: 5Unnamed: 9
Unnamed: 11.0000.3740.5290.976
Unnamed: 60.3741.0000.7420.337
Unnamed: 50.5290.7421.0000.537
Unnamed: 90.9760.3370.5371.000
2023-12-13T05:58:21.940552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 5Unnamed: 6Unnamed: 9
Unnamed: 11.0000.5290.3740.976
Unnamed: 50.5291.0000.7420.537
Unnamed: 60.3740.7421.0000.337
Unnamed: 90.9760.5370.3371.000

Missing values

2023-12-13T05:58:17.920913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:58:18.114872image/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.
2023-12-13T05:58:18.295056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

이재민 임시주거시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
0NaN<NA><NA><NA><NA><NA><NA>NaNNaN(2019. 9월 현재)
1연번행정동시설명세부시설명위치(주소)시설종류시설유형시설면적\n(㎡)수용가능인원(명)관리자 연락처
2NaN<NA><NA><NA><NA><NA><NA>NaNNaN<NA>
3NaN<NA><NA><NA><NA><NA><NA>270898208.787879<NA>
41소공동덕수초등학교2층 체육관덕수궁길 140지진 겸용학교897271.81818202-3396-6506
52소공동소공동주민센터4층강당남대문로1길 31-5풍수해관공서13540.90909102-3396-6506
63소공동창덕여자중학교1층강당정동길 22풍수해학교470142.42424202-3396-6506
74회현동회현어린이집1층강당퇴계로12가길 23풍수해기타650196.96969702-3396-8422
85회현동회현경로당2층퇴계로12길 89풍수해경로당10331.21212102-3396-8422
96회현동회현체육센터2층퇴계로12길 78지진 겸용기타701212.42424202-3396-8422
이재민 임시주거시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
3027약수동약수노인복지관3층,5층다산로6길 11풍수해기타659199.6969702-3396-6784
3128약수동약수교회지하1,2층다산로8길 32풍수해교회643194.84848502-3396-6784
3229청구동신일교회지하소예배실동호로10길 27풍수해교회500151.51515202-3396-6975
3330청구동청구동문화마당강당다산로24가길 23풍수해기타537162.72727302-3396-6975
3431신당5동성동고등학교체육관퇴계로90길 17지진 겸용학교877265.75757602-3396-8455
3532신당5동유락종합사회복지관지하1층퇴계로 460풍수해기타17853.93939402-3396-8455
3633동화동문화교회교육관지하퇴계로86길 96풍수해교회12638.18181802-3396-6872
3734동화동동화동주민센터지하강당다산로36길 100풍수해관공서391118.48484802-3396-6872
3835황학동황학동청사4층강당난계로11길 52풍수해관공서402121.81818202-3396-6911
3936중림동중림종합복지센터3층강당서소문로6길 16지진 겸용기타1986002-3396-6932

Duplicate rows

Most frequently occurring

Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 9# duplicates
0<NA><NA><NA><NA><NA><NA><NA>2