Overview

Dataset statistics

Number of variables5
Number of observations109
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory41.2 B

Variable types

Unsupported1
Categorical1
Text3

Dataset

Description파일 다운로드
Author서울시사회복지관협회
URLhttps://data.seoul.go.kr/dataList/OA-12942/F/1/datasetView.do

Alerts

Unnamed: 2 has unique valuesUnique
Unnamed: 3 has unique valuesUnique
Unnamed: 4 has unique valuesUnique
'2020 희망온돌 취약계층 위기가구지원사업' 거점기관 현황 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 09:13:17.450794
Analysis finished2023-12-11 09:13:17.780517
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

'2020 희망온돌 취약계층 위기가구지원사업' 거점기관 현황
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1004.0 B

Unnamed: 1
Categorical

Distinct26
Distinct (%)23.9%
Missing0
Missing (%)0.0%
Memory size1004.0 B
강서구
10 
송파구
 
7
노원구
 
7
동작구
 
6
성북구
 
6
Other values (21)
73 

Length

Max length4
Median length3
Mean length3.0550459
Min length2

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row자치구
2nd row강남구
3rd row강남구
4th row강남구
5th row강남구

Common Values

ValueCountFrequency (%)
강서구 10
 
9.2%
송파구 7
 
6.4%
노원구 7
 
6.4%
동작구 6
 
5.5%
성북구 6
 
5.5%
관악구 5
 
4.6%
구로구 5
 
4.6%
강남구 5
 
4.6%
양천구 5
 
4.6%
서대문구 4
 
3.7%
Other values (16) 49
45.0%

Length

2023-12-11T18:13:17.897351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서구 10
 
9.2%
노원구 7
 
6.4%
송파구 7
 
6.4%
동작구 6
 
5.5%
성북구 6
 
5.5%
관악구 5
 
4.6%
구로구 5
 
4.6%
강남구 5
 
4.6%
양천구 5
 
4.6%
도봉구 4
 
3.7%
Other values (16) 49
45.0%

Unnamed: 2
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-11T18:13:18.145875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length9
Mean length9.9449541
Min length3

Characters and Unicode

Total characters1084
Distinct characters151
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

Unique109 ?
Unique (%)100.0%

Sample

1st row기관명
2nd row강남종합사회복지관
3rd row능인종합사회복지관
4th row대청종합사회복지관
5th row수서명화종합사회복지관
ValueCountFrequency (%)
기관명 1
 
0.9%
장안종합사회복지관 1
 
0.9%
정릉종합사회복지관 1
 
0.9%
장위종합사회복지관 1
 
0.9%
월곡종합사회복지관 1
 
0.9%
성북장애인복지관 1
 
0.9%
생명의전화종합사회복지관 1
 
0.9%
길음종합사회복지관 1
 
0.9%
옥수종합사회복지관 1
 
0.9%
성수종합사회복지관 1
 
0.9%
Other values (102) 102
91.1%
2023-12-11T18:13:18.514833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 112
 
10.3%
지 112
 
10.3%
복 109
 
10.1%
종 104
 
9.6%
합 102
 
9.4%
사 96
 
8.9%
회 93
 
8.6%
동 14
 
1.3%
인 14
 
1.3%
12
 
1.1%
Other values (141) 316
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1043
96.2%
Decimal Number 20
 
1.8%
Space Separator 12
 
1.1%
Uppercase Letter 4
 
0.4%
Other Punctuation 2
 
0.2%
Open Punctuation 1
 
0.1%
Control 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 112
10.7%
지 112
10.7%
복 109
 
10.5%
종 104
 
10.0%
합 102
 
9.8%
사 96
 
9.2%
회 93
 
8.9%
동 14
 
1.3%
인 14
 
1.3%
노 9
 
0.9%
Other values (123) 278
26.7%
Decimal Number
ValueCountFrequency (%)
1 4
20.0%
2 4
20.0%
5 3
15.0%
4 2
10.0%
7 2
10.0%
0 2
10.0%
6 1
 
5.0%
9 1
 
5.0%
3 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
W 1
25.0%
A 1
25.0%
C 1
25.0%
Y 1
25.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1043
96.2%
Common 37
 
3.4%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 112
10.7%
지 112
10.7%
복 109
 
10.5%
종 104
 
10.0%
합 102
 
9.8%
사 96
 
9.2%
회 93
 
8.9%
동 14
 
1.3%
인 14
 
1.3%
노 9
 
0.9%
Other values (123) 278
26.7%
Common
ValueCountFrequency (%)
12
32.4%
1 4
 
10.8%
2 4
 
10.8%
5 3
 
8.1%
4 2
 
5.4%
7 2
 
5.4%
0 2
 
5.4%
. 2
 
5.4%
( 1
 
2.7%
1
 
2.7%
Other values (4) 4
 
10.8%
Latin
ValueCountFrequency (%)
W 1
25.0%
A 1
25.0%
C 1
25.0%
Y 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1043
96.2%
ASCII 41
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 112
10.7%
지 112
10.7%
복 109
 
10.5%
종 104
 
10.0%
합 102
 
9.8%
사 96
 
9.2%
회 93
 
8.9%
동 14
 
1.3%
인 14
 
1.3%
노 9
 
0.9%
Other values (123) 278
26.7%
ASCII
ValueCountFrequency (%)
12
29.3%
1 4
 
9.8%
2 4
 
9.8%
5 3
 
7.3%
4 2
 
4.9%
7 2
 
4.9%
0 2
 
4.9%
. 2
 
4.9%
W 1
 
2.4%
( 1
 
2.4%
Other values (8) 8
19.5%

Unnamed: 3
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-11T18:13:18.909314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length20.036697
Min length2

Characters and Unicode

Total characters2184
Distinct characters174
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

Unique109 ?
Unique (%)100.0%

Sample

1st row주소
2nd row서울특별시 강남구 개포로 109길 5
3rd row서울특별시 강남구 양재대로 340
4th row서울특별시 강남구 양재대로55길 12
5th row서울특별시 강남구 광평로 51길 49번지
ValueCountFrequency (%)
서울특별시 94
 
19.9%
서울시 14
 
3.0%
강서구 10
 
2.1%
노원구 7
 
1.5%
송파구 7
 
1.5%
성북구 6
 
1.3%
동작구 6
 
1.3%
22 5
 
1.1%
구로구 5
 
1.1%
양천구 5
 
1.1%
Other values (230) 314
66.4%
2023-12-11T18:13:19.504262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
367
16.8%
서 129
 
5.9%
로 114
 
5.2%
구 113
 
5.2%
시 112
 
5.1%
울 108
 
4.9%
특 94
 
4.3%
별 94
 
4.3%
1 88
 
4.0%
2 72
 
3.3%
Other values (164) 893
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1370
62.7%
Decimal Number 408
 
18.7%
Space Separator 367
 
16.8%
Uppercase Letter 18
 
0.8%
Dash Punctuation 12
 
0.5%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 129
 
9.4%
로 114
 
8.3%
구 113
 
8.2%
시 112
 
8.2%
울 108
 
7.9%
특 94
 
6.9%
별 94
 
6.9%
길 72
 
5.3%
동 31
 
2.3%
강 24
 
1.8%
Other values (143) 479
35.0%
Decimal Number
ValueCountFrequency (%)
1 88
21.6%
2 72
17.6%
5 45
11.0%
3 42
10.3%
4 39
9.6%
6 33
 
8.1%
0 24
 
5.9%
8 23
 
5.6%
9 22
 
5.4%
7 20
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
T 5
27.8%
P 5
27.8%
A 5
27.8%
S 1
 
5.6%
H 1
 
5.6%
B 1
 
5.6%
Space Separator
ValueCountFrequency (%)
367
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1370
62.7%
Common 796
36.4%
Latin 18
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 129
 
9.4%
로 114
 
8.3%
구 113
 
8.2%
시 112
 
8.2%
울 108
 
7.9%
특 94
 
6.9%
별 94
 
6.9%
길 72
 
5.3%
동 31
 
2.3%
강 24
 
1.8%
Other values (143) 479
35.0%
Common
ValueCountFrequency (%)
367
46.1%
1 88
 
11.1%
2 72
 
9.0%
5 45
 
5.7%
3 42
 
5.3%
4 39
 
4.9%
6 33
 
4.1%
0 24
 
3.0%
8 23
 
2.9%
9 22
 
2.8%
Other values (5) 41
 
5.2%
Latin
ValueCountFrequency (%)
T 5
27.8%
P 5
27.8%
A 5
27.8%
S 1
 
5.6%
H 1
 
5.6%
B 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1370
62.7%
ASCII 814
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
367
45.1%
1 88
 
10.8%
2 72
 
8.8%
5 45
 
5.5%
3 42
 
5.2%
4 39
 
4.8%
6 33
 
4.1%
0 24
 
2.9%
8 23
 
2.8%
9 22
 
2.7%
Other values (11) 59
 
7.2%
Hangul
ValueCountFrequency (%)
서 129
 
9.4%
로 114
 
8.3%
구 113
 
8.2%
시 112
 
8.2%
울 108
 
7.9%
특 94
 
6.9%
별 94
 
6.9%
길 72
 
5.3%
동 31
 
2.3%
강 24
 
1.8%
Other values (143) 479
35.0%

Unnamed: 4
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-11T18:13:19.758738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length12.073394
Min length7

Characters and Unicode

Total characters1316
Distinct characters21
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

Unique109 ?
Unique (%)100.0%

Sample

1st row기관 대표번호
2nd row02-451-0051-3
3rd row02-571-2988-9
4th row02-459-6332
5th row02-459-2696~8
ValueCountFrequency (%)
기관 1
 
0.9%
02-3477-9811 1
 
0.9%
02-909-0434 1
 
0.9%
02-918-3073~5 1
 
0.9%
02-911-5511 1
 
0.9%
02-915-9200 1
 
0.9%
02-916-9193-5 1
 
0.9%
02-985-0161-4 1
 
0.9%
02-2282-1100 1
 
0.9%
02-2204-9922 1
 
0.9%
Other values (100) 100
90.9%
2023-12-11T18:13:20.170819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 239
18.2%
0 208
15.8%
2 206
15.7%
1 92
 
7.0%
6 85
 
6.5%
3 83
 
6.3%
8 82
 
6.2%
9 80
 
6.1%
4 75
 
5.7%
7 71
 
5.4%
Other values (11) 95
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1053
80.0%
Dash Punctuation 239
 
18.2%
Math Symbol 13
 
1.0%
Other Letter 6
 
0.5%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 208
19.8%
2 206
19.6%
1 92
8.7%
6 85
8.1%
3 83
 
7.9%
8 82
 
7.8%
9 80
 
7.6%
4 75
 
7.1%
7 71
 
6.7%
5 71
 
6.7%
Other Letter
ValueCountFrequency (%)
관 1
16.7%
호 1
16.7%
번 1
16.7%
표 1
16.7%
대 1
16.7%
기 1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 239
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1310
99.5%
Hangul 6
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
- 239
18.2%
0 208
15.9%
2 206
15.7%
1 92
 
7.0%
6 85
 
6.5%
3 83
 
6.3%
8 82
 
6.3%
9 80
 
6.1%
4 75
 
5.7%
7 71
 
5.4%
Other values (5) 89
 
6.8%
Hangul
ValueCountFrequency (%)
관 1
16.7%
호 1
16.7%
번 1
16.7%
표 1
16.7%
대 1
16.7%
기 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1310
99.5%
Hangul 6
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 239
18.2%
0 208
15.9%
2 206
15.7%
1 92
 
7.0%
6 85
 
6.5%
3 83
 
6.3%
8 82
 
6.3%
9 80
 
6.1%
4 75
 
5.7%
7 71
 
5.4%
Other values (5) 89
 
6.8%
Hangul
ValueCountFrequency (%)
관 1
16.7%
호 1
16.7%
번 1
16.7%
표 1
16.7%
대 1
16.7%
기 1
16.7%

Missing values

2023-12-11T18:13:17.651360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:13:17.740362image/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

'2020 희망온돌 취약계층 위기가구지원사업' 거점기관 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
0구분자치구기관명주소기관 대표번호
11강남구강남종합사회복지관서울특별시 강남구 개포로 109길 502-451-0051-3
22강남구능인종합사회복지관서울특별시 강남구 양재대로 34002-571-2988-9
33강남구대청종합사회복지관서울특별시 강남구 양재대로55길 1202-459-6332
44강남구수서명화종합사회복지관서울특별시 강남구 광평로 51길 49번지02-459-2696~8
55강남구수서종합사회복지관서울특별시 강남구 광평로 56길 1102-459-5504
66강동구강동노인종합복지관서울시 강동구 동남로 71길 32-502-442-1026
77강동구강동종합사회복지관서울특별시 강동구 진황도로23길 702-2041-7800
88강동구성내종합사회복지관서울특별시 강동구 성안로13길 5602-478-2555
99강북구구세군강북종합사회복지관서울특별시 강북구 인수봉로20가길 2402-984-5811~4
'2020 희망온돌 취약계층 위기가구지원사업' 거점기관 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
9999은평구은평종합사회복지관서울특별시 은평구 은평터널로 4802-307-1181-3
100100종로구종로노인종합복지관서울시 종로구 율곡로 19길 17-802-6247-9922
101101종로구종로종합사회복지관서울특별시 종로구 지봉로13길 8202-766-8282
102102중구신당종합사회복지관서울특별시 중구 동호로11길 2202-2231-1876~9
103103중구유락종합사회복지관서울특별시 중구 퇴계로 46002-2235-4000
104104중구중림종합사회복지관서울특별시 중구 서소문로6길16(중림동 155-1)02-362-3348~51
105105중랑구면목종합사회복지관서울특별시 중랑구 용마산로 228 도시개발단지내02-436-0500
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