Overview

Dataset statistics

Number of variables12
Number of observations219
Missing cells527
Missing cells (%)20.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.9 KiB
Average record size in memory97.6 B

Variable types

Text8
Categorical3
Unsupported1

Dataset

Description사회복지이용시설현황전라북도2015
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202407

Alerts

Unnamed: 6 is highly overall correlated with Unnamed: 1 and 1 other fieldsHigh correlation
Unnamed: 7 is highly overall correlated with Unnamed: 6High correlation
Unnamed: 1 is highly overall correlated with Unnamed: 6High correlation
Unnamed: 3 has 18 (8.2%) missing valuesMissing
Unnamed: 4 has 19 (8.7%) missing valuesMissing
Unnamed: 5 has 17 (7.8%) missing valuesMissing
Unnamed: 8 has 20 (9.1%) missing valuesMissing
Unnamed: 9 has 17 (7.8%) missing valuesMissing
Unnamed: 10 has 214 (97.7%) missing valuesMissing
Unnamed: 11 has 219 (100.0%) missing valuesMissing
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:12:53.644930
Analysis finished2024-03-14 00:12:54.686364
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도 사회복지(이용)시설 현황
Text

Distinct55
Distinct (%)25.3%
Missing2
Missing (%)0.9%
Memory size1.8 KiB
2024-03-14T09:12:54.816236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.4792627
Min length1

Characters and Unicode

Total characters321
Distinct characters15
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

Unique27 ?
Unique (%)12.4%

Sample

1st row언번
2nd row총계
3rd row소계
4th row1
5th row2
ValueCountFrequency (%)
소계 14
 
6.5%
4 14
 
6.5%
1 14
 
6.5%
2 14
 
6.5%
3 14
 
6.5%
6 13
 
6.0%
5 13
 
6.0%
7 12
 
5.5%
8 11
 
5.1%
9 8
 
3.7%
Other values (45) 90
41.5%
2024-03-14T09:12:55.119020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 67
20.9%
2 49
15.3%
3 33
10.3%
4 33
10.3%
5 24
 
7.5%
6 20
 
6.2%
7 19
 
5.9%
8 17
 
5.3%
계 15
 
4.7%
소 14
 
4.4%
Other values (5) 30
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 289
90.0%
Other Letter 32
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 67
23.2%
2 49
17.0%
3 33
11.4%
4 33
11.4%
5 24
 
8.3%
6 20
 
6.9%
7 19
 
6.6%
8 17
 
5.9%
9 14
 
4.8%
0 13
 
4.5%
Other Letter
ValueCountFrequency (%)
계 15
46.9%
소 14
43.8%
언 1
 
3.1%
번 1
 
3.1%
총 1
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Common 289
90.0%
Hangul 32
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 67
23.2%
2 49
17.0%
3 33
11.4%
4 33
11.4%
5 24
 
8.3%
6 20
 
6.9%
7 19
 
6.6%
8 17
 
5.9%
9 14
 
4.8%
0 13
 
4.5%
Hangul
ValueCountFrequency (%)
계 15
46.9%
소 14
43.8%
언 1
 
3.1%
번 1
 
3.1%
총 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 289
90.0%
Hangul 32
 
10.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 67
23.2%
2 49
17.0%
3 33
11.4%
4 33
11.4%
5 24
 
8.3%
6 20
 
6.9%
7 19
 
6.6%
8 17
 
5.9%
9 14
 
4.8%
0 13
 
4.5%
Hangul
ValueCountFrequency (%)
계 15
46.9%
소 14
43.8%
언 1
 
3.1%
번 1
 
3.1%
총 1
 
3.1%

Unnamed: 1
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
장애인주간보호시설
26 
여성폭력피해보호시설
22 
지역자활센터
18 
장애인보호작업장
16 
장애인수화통역센터
15 
Other values (38)
122 

Length

Max length16
Median length12
Mean length7.5844749
Min length3

Unique

Unique21 ?
Unique (%)9.6%

Sample

1st row<NA>
2nd row시설구분
3rd row<NA>
4th row전라북도
5th row전주시

Common Values

ValueCountFrequency (%)
장애인주간보호시설 26
11.9%
여성폭력피해보호시설 22
10.0%
지역자활센터 18
 
8.2%
장애인보호작업장 16
 
7.3%
장애인수화통역센터 15
 
6.8%
장애인심부름센터 15
 
6.8%
사회복지관 14
 
6.4%
다문화가족지원센터 14
 
6.4%
노인복지관 14
 
6.4%
장애인복지관 12
 
5.5%
Other values (33) 53
24.2%

Length

2024-03-14T09:12:55.230552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장애인주간보호시설 26
11.7%
여성폭력피해보호시설 22
 
9.9%
지역자활센터 18
 
8.1%
노인복지관 16
 
7.2%
장애인보호작업장 16
 
7.2%
장애인수화통역센터 15
 
6.7%
장애인심부름센터 15
 
6.7%
사회복지관 14
 
6.3%
다문화가족지원센터 14
 
6.3%
장애인복지관 12
 
5.4%
Other values (32) 55
24.7%

Unnamed: 2
Text

Distinct215
Distinct (%)98.6%
Missing1
Missing (%)0.5%
Memory size1.8 KiB
2024-03-14T09:12:55.409233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length9.1376147
Min length1

Characters and Unicode

Total characters1992
Distinct characters202
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique213 ?
Unique (%)97.7%

Sample

1st row시 설 일 반 현 황
2nd row시설명
3rd row201
4th row52
5th row전북종합사회복지관
ValueCountFrequency (%)
장애인복지관 11
 
4.2%
부설 7
 
2.7%
주간보호센터 6
 
2.3%
8 3
 
1.2%
주간보호시설 3
 
1.2%
익산 3
 
1.2%
가정폭력상담소 2
 
0.8%
행복한집 2
 
0.8%
장수군 2
 
0.8%
김제시 1
 
0.4%
Other values (220) 220
84.6%
2024-03-14T09:12:55.691675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 97
 
4.9%
터 86
 
4.3%
센 85
 
4.3%
복 63
 
3.2%
관 61
 
3.1%
인 60
 
3.0%
장 56
 
2.8%
주 51
 
2.6%
부 47
 
2.4%
43
 
2.2%
Other values (192) 1343
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1913
96.0%
Space Separator 43
 
2.2%
Decimal Number 26
 
1.3%
Uppercase Letter 8
 
0.4%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 97
 
5.1%
터 86
 
4.5%
센 85
 
4.4%
복 63
 
3.3%
관 61
 
3.2%
인 60
 
3.1%
장 56
 
2.9%
주 51
 
2.7%
부 47
 
2.5%
군 42
 
2.2%
Other values (176) 1265
66.1%
Decimal Number
ValueCountFrequency (%)
1 7
26.9%
2 6
23.1%
8 3
11.5%
5 2
 
7.7%
7 2
 
7.7%
0 2
 
7.7%
4 2
 
7.7%
9 1
 
3.8%
6 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 2
25.0%
C 2
25.0%
Y 2
25.0%
W 2
25.0%
Space Separator
ValueCountFrequency (%)
43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1913
96.0%
Common 71
 
3.6%
Latin 8
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 97
 
5.1%
터 86
 
4.5%
센 85
 
4.4%
복 63
 
3.3%
관 61
 
3.2%
인 60
 
3.1%
장 56
 
2.9%
주 51
 
2.7%
부 47
 
2.5%
군 42
 
2.2%
Other values (176) 1265
66.1%
Common
ValueCountFrequency (%)
43
60.6%
1 7
 
9.9%
2 6
 
8.5%
8 3
 
4.2%
5 2
 
2.8%
7 2
 
2.8%
0 2
 
2.8%
4 2
 
2.8%
9 1
 
1.4%
) 1
 
1.4%
Other values (2) 2
 
2.8%
Latin
ValueCountFrequency (%)
A 2
25.0%
C 2
25.0%
Y 2
25.0%
W 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1913
96.0%
ASCII 79
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 97
 
5.1%
터 86
 
4.5%
센 85
 
4.4%
복 63
 
3.3%
관 61
 
3.2%
인 60
 
3.1%
장 56
 
2.9%
주 51
 
2.7%
부 47
 
2.5%
군 42
 
2.2%
Other values (176) 1265
66.1%
ASCII
ValueCountFrequency (%)
43
54.4%
1 7
 
8.9%
2 6
 
7.6%
8 3
 
3.8%
5 2
 
2.5%
7 2
 
2.5%
0 2
 
2.5%
4 2
 
2.5%
A 2
 
2.5%
C 2
 
2.5%
Other values (6) 8
 
10.1%

Unnamed: 3
Text

MISSING 

Distinct178
Distinct (%)88.6%
Missing18
Missing (%)8.2%
Memory size1.8 KiB
2024-03-14T09:12:55.944639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length8
Mean length8.0945274
Min length5

Characters and Unicode

Total characters1627
Distinct characters20
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

Unique162 ?
Unique (%)80.6%

Sample

1st row설치신고일
2nd row88.12.27
3rd row92.12.28
4th row95.12.29
5th row04.04.01
ValueCountFrequency (%)
01.07.01 8
 
3.8%
09 3
 
1.4%
00.08.24 3
 
1.4%
00.03.29 2
 
0.9%
06 2
 
0.9%
99.04.01 2
 
0.9%
11.11.01 2
 
0.9%
05.12.09 2
 
0.9%
09.02.13 2
 
0.9%
99.2.12 2
 
0.9%
Other values (175) 184
86.8%
2024-03-14T09:12:56.364763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 402
24.7%
. 402
24.7%
1 256
15.7%
2 138
 
8.5%
9 88
 
5.4%
3 78
 
4.8%
7 57
 
3.5%
8 52
 
3.2%
5 50
 
3.1%
4 47
 
2.9%
Other values (10) 57
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1201
73.8%
Other Punctuation 402
 
24.7%
Space Separator 16
 
1.0%
Other Letter 5
 
0.3%
Control 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 402
33.5%
1 256
21.3%
2 138
 
11.5%
9 88
 
7.3%
3 78
 
6.5%
7 57
 
4.7%
8 52
 
4.3%
5 50
 
4.2%
4 47
 
3.9%
6 33
 
2.7%
Other Letter
ValueCountFrequency (%)
설 1
20.0%
치 1
20.0%
신 1
20.0%
고 1
20.0%
일 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 402
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1622
99.7%
Hangul 5
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 402
24.8%
. 402
24.8%
1 256
15.8%
2 138
 
8.5%
9 88
 
5.4%
3 78
 
4.8%
7 57
 
3.5%
8 52
 
3.2%
5 50
 
3.1%
4 47
 
2.9%
Other values (5) 52
 
3.2%
Hangul
ValueCountFrequency (%)
설 1
20.0%
치 1
20.0%
신 1
20.0%
고 1
20.0%
일 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1622
99.7%
Hangul 5
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 402
24.8%
. 402
24.8%
1 256
15.8%
2 138
 
8.5%
9 88
 
5.4%
3 78
 
4.8%
7 57
 
3.5%
8 52
 
3.2%
5 50
 
3.1%
4 47
 
2.9%
Other values (5) 52
 
3.2%
Hangul
ValueCountFrequency (%)
설 1
20.0%
치 1
20.0%
신 1
20.0%
고 1
20.0%
일 1
20.0%

Unnamed: 4
Text

MISSING 

Distinct178
Distinct (%)89.0%
Missing19
Missing (%)8.7%
Memory size1.8 KiB
2024-03-14T09:12:56.660368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.035
Min length2

Characters and Unicode

Total characters607
Distinct characters134
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

Unique161 ?
Unique (%)80.5%

Sample

1st row시설장
2nd row문정훈
3rd row정학성
4th row노영웅
5th row정식수
ValueCountFrequency (%)
손형석 3
 
1.5%
강경희 3
 
1.5%
김 3
 
1.5%
진 3
 
1.5%
이춘섭 3
 
1.5%
이영재 3
 
1.5%
강정완 2
 
1.0%
한갑수 2
 
1.0%
이순옥 2
 
1.0%
박종형 2
 
1.0%
Other values (169) 177
87.2%
2024-03-14T09:12:57.033056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 38
 
6.3%
이 32
 
5.3%
희 17
 
2.8%
정 17
 
2.8%
진 17
 
2.8%
성 17
 
2.8%
영 16
 
2.6%
박 14
 
2.3%
수 13
 
2.1%
경 12
 
2.0%
Other values (124) 414
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 598
98.5%
Space Separator 9
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 38
 
6.4%
이 32
 
5.4%
희 17
 
2.8%
정 17
 
2.8%
진 17
 
2.8%
성 17
 
2.8%
영 16
 
2.7%
박 14
 
2.3%
수 13
 
2.2%
경 12
 
2.0%
Other values (123) 405
67.7%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 598
98.5%
Common 9
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 38
 
6.4%
이 32
 
5.4%
희 17
 
2.8%
정 17
 
2.8%
진 17
 
2.8%
성 17
 
2.8%
영 16
 
2.7%
박 14
 
2.3%
수 13
 
2.2%
경 12
 
2.0%
Other values (123) 405
67.7%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 598
98.5%
ASCII 9
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 38
 
6.4%
이 32
 
5.4%
희 17
 
2.8%
정 17
 
2.8%
진 17
 
2.8%
성 17
 
2.8%
영 16
 
2.7%
박 14
 
2.3%
수 13
 
2.2%
경 12
 
2.0%
Other values (123) 405
67.7%
ASCII
ValueCountFrequency (%)
9
100.0%

Unnamed: 5
Text

MISSING 

Distinct180
Distinct (%)89.1%
Missing17
Missing (%)7.8%
Memory size1.8 KiB
2024-03-14T09:12:57.319958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length15.712871
Min length3

Characters and Unicode

Total characters3174
Distinct characters209
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique162 ?
Unique (%)80.2%

Sample

1st row주 소
2nd row전주시 완산구 흑석로 70
3rd row전주시 완산구 덕적골2길 10
4th row전주시 완산구 모악로 4726-1
5th row전주시 완산구 선너머로 54
ValueCountFrequency (%)
전주시 53
 
7.1%
완산구 39
 
5.2%
익산시 27
 
3.6%
군산시 20
 
2.7%
정읍시 14
 
1.9%
덕진구 14
 
1.9%
김제시 12
 
1.6%
임실읍 11
 
1.5%
남원시 11
 
1.5%
완주군 10
 
1.3%
Other values (358) 535
71.7%
2024-03-14T09:12:57.721758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
545
 
17.2%
1 150
 
4.7%
시 144
 
4.5%
로 123
 
3.9%
2 118
 
3.7%
산 109
 
3.4%
길 81
 
2.6%
주 79
 
2.5%
읍 78
 
2.5%
군 77
 
2.4%
Other values (199) 1670
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1823
57.4%
Decimal Number 683
 
21.5%
Space Separator 545
 
17.2%
Dash Punctuation 66
 
2.1%
Open Punctuation 23
 
0.7%
Close Punctuation 23
 
0.7%
Other Punctuation 8
 
0.3%
Uppercase Letter 2
 
0.1%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 144
 
7.9%
로 123
 
6.7%
산 109
 
6.0%
길 81
 
4.4%
주 79
 
4.3%
읍 78
 
4.3%
군 77
 
4.2%
전 60
 
3.3%
구 57
 
3.1%
완 49
 
2.7%
Other values (179) 966
53.0%
Decimal Number
ValueCountFrequency (%)
1 150
22.0%
2 118
17.3%
3 76
11.1%
5 64
9.4%
4 64
9.4%
7 53
 
7.8%
8 43
 
6.3%
6 42
 
6.1%
9 39
 
5.7%
0 34
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
37.5%
＠ 2
25.0%
, 2
25.0%
@ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
545
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1823
57.4%
Common 1349
42.5%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 144
 
7.9%
로 123
 
6.7%
산 109
 
6.0%
길 81
 
4.4%
주 79
 
4.3%
읍 78
 
4.3%
군 77
 
4.2%
전 60
 
3.3%
구 57
 
3.1%
완 49
 
2.7%
Other values (179) 966
53.0%
Common
ValueCountFrequency (%)
545
40.4%
1 150
 
11.1%
2 118
 
8.7%
3 76
 
5.6%
- 66
 
4.9%
5 64
 
4.7%
4 64
 
4.7%
7 53
 
3.9%
8 43
 
3.2%
6 42
 
3.1%
Other values (9) 128
 
9.5%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1823
57.4%
ASCII 1349
42.5%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
545
40.4%
1 150
 
11.1%
2 118
 
8.7%
3 76
 
5.6%
- 66
 
4.9%
5 64
 
4.7%
4 64
 
4.7%
7 53
 
3.9%
8 43
 
3.2%
6 42
 
3.1%
Other values (9) 128
 
9.5%
Hangul
ValueCountFrequency (%)
시 144
 
7.9%
로 123
 
6.7%
산 109
 
6.0%
길 81
 
4.4%
주 79
 
4.3%
읍 78
 
4.3%
군 77
 
4.2%
전 60
 
3.3%
구 57
 
3.1%
완 49
 
2.7%
Other values (179) 966
53.0%
None
ValueCountFrequency (%)
＠ 2
100.0%

Unnamed: 6
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3
55 
6
23 
4
21 
<NA>
15 
5
10 
Other values (38)
95 

Length

Max length7
Median length3
Mean length3.1232877
Min length1

Unique

Unique16 ?
Unique (%)7.3%

Sample

1st row<NA>
2nd row종사자
3rd row정원
4th row 1,515
5th row<NA>

Common Values

ValueCountFrequency (%)
3 55
25.1%
6 23
 
10.5%
4 21
 
9.6%
<NA> 15
 
6.8%
5 10
 
4.6%
7 10
 
4.6%
1 7
 
3.2%
10 6
 
2.7%
12 5
 
2.3%
14 4
 
1.8%
Other values (33) 63
28.8%

Length

2024-03-14T09:12:57.841981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3 56
25.6%
6 23
10.5%
4 21
 
9.6%
na 15
 
6.8%
7 14
 
6.4%
5 10
 
4.6%
1 10
 
4.6%
12 7
 
3.2%
2 7
 
3.2%
11 7
 
3.2%
Other values (24) 49
22.4%

Unnamed: 7
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3
42 
6
25 
4
25 
<NA>
16 
5
14 
Other values (40)
97 

Length

Max length7
Median length3
Mean length3.1324201
Min length1

Unique

Unique19 ?
Unique (%)8.7%

Sample

1st row<NA>
2nd row<NA>
3rd row현원
4th row 1,501
5th row<NA>

Common Values

ValueCountFrequency (%)
3 42
19.2%
6 25
11.4%
4 25
11.4%
<NA> 16
 
7.3%
5 14
 
6.4%
1 9
 
4.1%
2 8
 
3.7%
7 7
 
3.2%
10 6
 
2.7%
12 5
 
2.3%
Other values (35) 62
28.3%

Length

2024-03-14T09:12:57.941143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3 43
19.6%
6 26
11.9%
4 25
11.4%
na 16
 
7.3%
5 16
 
7.3%
1 12
 
5.5%
2 11
 
5.0%
7 8
 
3.7%
11 8
 
3.7%
12 7
 
3.2%
Other values (23) 47
21.5%

Unnamed: 8
Text

MISSING 

Distinct134
Distinct (%)67.3%
Missing20
Missing (%)9.1%
Memory size1.8 KiB
2024-03-14T09:12:58.186126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.879397
Min length2

Characters and Unicode

Total characters971
Distinct characters21
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

Unique102 ?
Unique (%)51.3%

Sample

1st row월평균 이용인원
2nd row 446,157
3rd row 7,220
4th row 11,000
5th row 9,160
ValueCountFrequency (%)
30 6
 
3.0%
20 6
 
3.0%
10 5
 
2.5%
4 5
 
2.5%
300 5
 
2.5%
200 5
 
2.5%
80 4
 
2.0%
150 4
 
2.0%
21 4
 
2.0%
42 4
 
2.0%
Other values (121) 152
76.0%
2024-03-14T09:12:58.619092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
356
36.7%
0 163
16.8%
1 93
 
9.6%
2 72
 
7.4%
3 59
 
6.1%
4 55
 
5.7%
, 36
 
3.7%
5 34
 
3.5%
6 28
 
2.9%
9 24
 
2.5%
Other values (11) 51
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 569
58.6%
Space Separator 356
36.7%
Other Punctuation 36
 
3.7%
Other Letter 7
 
0.7%
Dash Punctuation 2
 
0.2%
Control 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 163
28.6%
1 93
16.3%
2 72
12.7%
3 59
 
10.4%
4 55
 
9.7%
5 34
 
6.0%
6 28
 
4.9%
9 24
 
4.2%
7 22
 
3.9%
8 19
 
3.3%
Other Letter
ValueCountFrequency (%)
월 1
14.3%
평 1
14.3%
균 1
14.3%
이 1
14.3%
용 1
14.3%
인 1
14.3%
원 1
14.3%
Space Separator
ValueCountFrequency (%)
356
100.0%
Other Punctuation
ValueCountFrequency (%)
, 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 964
99.3%
Hangul 7
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
356
36.9%
0 163
16.9%
1 93
 
9.6%
2 72
 
7.5%
3 59
 
6.1%
4 55
 
5.7%
, 36
 
3.7%
5 34
 
3.5%
6 28
 
2.9%
9 24
 
2.5%
Other values (4) 44
 
4.6%
Hangul
ValueCountFrequency (%)
월 1
14.3%
평 1
14.3%
균 1
14.3%
이 1
14.3%
용 1
14.3%
인 1
14.3%
원 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 964
99.3%
Hangul 7
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
356
36.9%
0 163
16.9%
1 93
 
9.6%
2 72
 
7.5%
3 59
 
6.1%
4 55
 
5.7%
, 36
 
3.7%
5 34
 
3.5%
6 28
 
2.9%
9 24
 
2.5%
Other values (4) 44
 
4.6%
Hangul
ValueCountFrequency (%)
월 1
14.3%
평 1
14.3%
균 1
14.3%
이 1
14.3%
용 1
14.3%
인 1
14.3%
원 1
14.3%

Unnamed: 9
Text

MISSING 

Distinct160
Distinct (%)79.2%
Missing17
Missing (%)7.8%
Memory size1.8 KiB
2024-03-14T09:12:58.811578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length9.950495
Min length2

Characters and Unicode

Total characters2010
Distinct characters191
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

Unique136 ?
Unique (%)67.3%

Sample

1st row2015년 6월말 현재
2nd row운영주체(법인명)
3rd row 어린이재단
4th row 삼동회
5th row한기장복지재단
ValueCountFrequency (%)
사 12
 
4.6%
삼동회 12
 
4.6%
사복 8
 
3.1%
사회복지법인 7
 
2.7%
개인 7
 
2.7%
한기장복지재단 7
 
2.7%
사단법인 5
 
1.9%
한국장애인부모회 4
 
1.5%
사복.자광복지재단 3
 
1.1%
산학협력단 3
 
1.1%
Other values (164) 194
74.0%
2024-03-14T09:12:59.093588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 159
 
7.9%
사 116
 
5.8%
지 105
 
5.2%
인 89
 
4.4%
복 77
 
3.8%
70
 
3.5%
. 69
 
3.4%
전 59
 
2.9%
단 57
 
2.8%
장 53
 
2.6%
Other values (181) 1156
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1827
90.9%
Space Separator 70
 
3.5%
Other Punctuation 69
 
3.4%
Close Punctuation 15
 
0.7%
Uppercase Letter 12
 
0.6%
Open Punctuation 11
 
0.5%
Decimal Number 5
 
0.2%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 159
 
8.7%
사 116
 
6.3%
지 105
 
5.7%
인 89
 
4.9%
복 77
 
4.2%
전 59
 
3.2%
단 57
 
3.1%
장 53
 
2.9%
재 48
 
2.6%
한 48
 
2.6%
Other values (166) 1016
55.6%
Uppercase Letter
ValueCountFrequency (%)
A 3
25.0%
C 3
25.0%
Y 3
25.0%
W 2
16.7%
M 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 1
20.0%
1 1
20.0%
5 1
20.0%
6 1
20.0%
0 1
20.0%
Space Separator
ValueCountFrequency (%)
70
100.0%
Other Punctuation
ValueCountFrequency (%)
. 69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1827
90.9%
Common 171
 
8.5%
Latin 12
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 159
 
8.7%
사 116
 
6.3%
지 105
 
5.7%
인 89
 
4.9%
복 77
 
4.2%
전 59
 
3.2%
단 57
 
3.1%
장 53
 
2.9%
재 48
 
2.6%
한 48
 
2.6%
Other values (166) 1016
55.6%
Common
ValueCountFrequency (%)
70
40.9%
. 69
40.4%
) 15
 
8.8%
( 11
 
6.4%
2 1
 
0.6%
1 1
 
0.6%
5 1
 
0.6%
6 1
 
0.6%
0 1
 
0.6%
1
 
0.6%
Latin
ValueCountFrequency (%)
A 3
25.0%
C 3
25.0%
Y 3
25.0%
W 2
16.7%
M 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1827
90.9%
ASCII 183
 
9.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 159
 
8.7%
사 116
 
6.3%
지 105
 
5.7%
인 89
 
4.9%
복 77
 
4.2%
전 59
 
3.2%
단 57
 
3.1%
장 53
 
2.9%
재 48
 
2.6%
한 48
 
2.6%
Other values (166) 1016
55.6%
ASCII
ValueCountFrequency (%)
70
38.3%
. 69
37.7%
) 15
 
8.2%
( 11
 
6.0%
A 3
 
1.6%
C 3
 
1.6%
Y 3
 
1.6%
W 2
 
1.1%
2 1
 
0.5%
1 1
 
0.5%
Other values (5) 5
 
2.7%

Unnamed: 10
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing214
Missing (%)97.7%
Memory size1.8 KiB
2024-03-14T09:12:59.258275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length6
Mean length5.6
Min length2

Characters and Unicode

Total characters28
Distinct characters24
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

Unique5 ?
Unique (%)100.0%

Sample

1st row비고
2nd row상담 월10명 교육 월25명
3rd row전라북도소관
4th row재지정
5th row휴지
ValueCountFrequency (%)
비고 1
12.5%
상담 1
12.5%
월10명 1
12.5%
교육 1
12.5%
월25명 1
12.5%
전라북도소관 1
12.5%
재지정 1
12.5%
휴지 1
12.5%
2024-03-14T09:12:59.511578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 2
 
7.1%
2
 
7.1%
월 2
 
7.1%
명 2
 
7.1%
비 1
 
3.6%
전 1
 
3.6%
정 1
 
3.6%
재 1
 
3.6%
관 1
 
3.6%
소 1
 
3.6%
Other values (14) 14
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21
75.0%
Decimal Number 4
 
14.3%
Space Separator 2
 
7.1%
Control 1
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 2
 
9.5%
월 2
 
9.5%
명 2
 
9.5%
비 1
 
4.8%
전 1
 
4.8%
정 1
 
4.8%
재 1
 
4.8%
관 1
 
4.8%
소 1
 
4.8%
도 1
 
4.8%
Other values (8) 8
38.1%
Decimal Number
ValueCountFrequency (%)
2 1
25.0%
5 1
25.0%
0 1
25.0%
1 1
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21
75.0%
Common 7
 
25.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 2
 
9.5%
월 2
 
9.5%
명 2
 
9.5%
비 1
 
4.8%
전 1
 
4.8%
정 1
 
4.8%
재 1
 
4.8%
관 1
 
4.8%
소 1
 
4.8%
도 1
 
4.8%
Other values (8) 8
38.1%
Common
ValueCountFrequency (%)
2
28.6%
2 1
14.3%
5 1
14.3%
1
14.3%
0 1
14.3%
1 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21
75.0%
ASCII 7
 
25.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 2
 
9.5%
월 2
 
9.5%
명 2
 
9.5%
비 1
 
4.8%
전 1
 
4.8%
정 1
 
4.8%
재 1
 
4.8%
관 1
 
4.8%
소 1
 
4.8%
도 1
 
4.8%
Other values (8) 8
38.1%
ASCII
ValueCountFrequency (%)
2
28.6%
2 1
14.3%
5 1
14.3%
1
14.3%
0 1
14.3%
1 1
14.3%

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing219
Missing (%)100.0%
Memory size2.1 KiB

Correlations

2024-03-14T09:12:59.583606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전라북도 사회복지(이용)시설 현황Unnamed: 1Unnamed: 6Unnamed: 7Unnamed: 10
전라북도 사회복지(이용)시설 현황1.0000.7820.0000.0001.000
Unnamed: 10.7821.0000.9480.9281.000
Unnamed: 60.0000.9481.0000.9981.000
Unnamed: 70.0000.9280.9981.0001.000
Unnamed: 101.0001.0001.0001.0001.000
2024-03-14T09:12:59.671772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 6Unnamed: 7Unnamed: 1
Unnamed: 61.0000.9200.513
Unnamed: 70.9201.0000.454
Unnamed: 10.5130.4541.000
2024-03-14T09:12:59.763410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 6Unnamed: 7
Unnamed: 11.0000.5130.454
Unnamed: 60.5131.0000.920
Unnamed: 70.4540.9201.000

Missing values

2024-03-14T09:12:54.297952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:12:54.433779image/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.
2024-03-14T09:12:54.575602image/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

전라북도 사회복지(이용)시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
0<NA><NA><NA><NA><NA><NA><NA><NA><NA>2015년 6월말 현재<NA><NA>
1언번시설구분시 설 일 반 현 황<NA><NA><NA>종사자<NA>월평균 이용인원운영주체(법인명)비고<NA>
2<NA><NA>시설명설치신고일시설장주 소정원현원<NA><NA><NA><NA>
3총계전라북도201<NA><NA><NA>1,5151,501446,157<NA><NA><NA>
4소계전주시52<NA><NA><NA><NA><NA><NA><NA><NA><NA>
51사회복지관전북종합사회복지관88.12.27문정훈전주시 완산구 흑석로 7011117,220어린이재단<NA><NA>
62사회복지관전주종합사회복지관92.12.28정학성전주시 완산구 덕적골2길 10101011,000삼동회<NA><NA>
73사회복지관학산종합사회복지관95.12.29노영웅전주시 완산구 모악로 4726-112129,160한기장복지재단<NA><NA>
84사회복지관선너머종합사회복지관04.04.01정식수전주시 완산구 선너머로 5412129,000전주카톨릭사회복지회<NA><NA>
95사회복지관평화사회복지관92.01.13성동학전주시 완산구 덕적골2길 11998,400삼동회<NA><NA>
전라북도 사회복지(이용)시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
209소계부안군9<NA><NA><NA><NA><NA><NA><NA><NA><NA>
2101장애인복지관부안군 장애인복지관06.05.25이춘섭부안군 부안읍 용암로 13415152,069사복.한기장복지재단<NA><NA>
2112장애인수화통역센터부안수화통역센터06.01.12문정복부안군 부안읍 소금샘길 2334106사.한국농아인협회전북협회부안군지회<NA><NA>
2123장애인심부름센터부안심부름센터05.07.06김명곤부안군 부안읍 남문안길1533204사.전북시각장애인연합회부안군지회<NA><NA>
2134장애인주간보호시설부안장애인복지관 부설 주간보호센터12.10.30이춘섭부안군 부안읍 용암로 1343410사복. 한기장복지재단<NA><NA>
2145장애인근로사업장바다의향기11.01.25조상완부안읍 봉두길 52101039부신정회<NA><NA>
2156사회복지관부안종합사회복지관06.02.23이춘섭부안군 부안읍 용암로134771,970한기장복지재단<NA><NA>
2167여성폭력피해보호시설부안성폭력상담소06.05.12김정호부안읍 당산로 75-1---사)한국청소년치유협회휴지<NA>
2178지역자활센터부안지역자활센터01.05.23장헌진부안군 행안면 월륜길56677부안제일교회<NA><NA>
2189다문화가족지원센터부안군다문화가족지원센터09.02.25<NA>부안군 부안읍 오리정로 891716102직영<NA><NA>