Overview

Dataset statistics

Number of variables30
Number of observations155
Missing cells2468
Missing cells (%)53.1%
Duplicate rows1
Duplicate rows (%)0.6%
Total size in memory36.6 KiB
Average record size in memory241.9 B

Variable types

Text19
Categorical10
Unsupported1

Alerts

Unnamed: 1 has constant value ""Constant
Unnamed: 18 has constant value ""Constant
Unnamed: 25 has constant value ""Constant
Unnamed: 26 has constant value ""Constant
Unnamed: 27 has constant value ""Constant
Unnamed: 28 has constant value ""Constant
Dataset has 1 (0.6%) duplicate rowsDuplicates
Unnamed: 12 is highly imbalanced (51.9%)Imbalance
Unnamed: 13 is highly imbalanced (64.8%)Imbalance
Unnamed: 14 is highly imbalanced (69.1%)Imbalance
Unnamed: 24 is highly imbalanced (75.2%)Imbalance
사회복지법인 현황 (전라북도) has 36 (23.2%) missing valuesMissing
Unnamed: 1 has 154 (99.4%) missing valuesMissing
Unnamed: 5 has 37 (23.9%) missing valuesMissing
Unnamed: 6 has 38 (24.5%) missing valuesMissing
Unnamed: 8 has 38 (24.5%) missing valuesMissing
Unnamed: 10 has 39 (25.2%) missing valuesMissing
Unnamed: 15 has 149 (96.1%) missing valuesMissing
Unnamed: 16 has 152 (98.1%) missing valuesMissing
Unnamed: 17 has 152 (98.1%) missing valuesMissing
Unnamed: 18 has 154 (99.4%) missing valuesMissing
Unnamed: 19 has 152 (98.1%) missing valuesMissing
Unnamed: 20 has 149 (96.1%) missing valuesMissing
Unnamed: 21 has 149 (96.1%) missing valuesMissing
Unnamed: 22 has 149 (96.1%) missing valuesMissing
Unnamed: 23 has 149 (96.1%) missing valuesMissing
Unnamed: 25 has 154 (99.4%) missing valuesMissing
Unnamed: 26 has 154 (99.4%) missing valuesMissing
Unnamed: 27 has 154 (99.4%) missing valuesMissing
Unnamed: 28 has 154 (99.4%) missing valuesMissing
Unnamed: 29 has 155 (100.0%) missing valuesMissing
Unnamed: 29 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 01:17:08.524685
Analysis finished2024-03-14 01:17:09.143818
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사회복지법인 현황 (전라북도)
Text

MISSING 

Distinct119
Distinct (%)100.0%
Missing36
Missing (%)23.2%
Memory size1.3 KiB
2024-03-14T10:17:09.352628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length2
Mean length2.2184874
Min length1

Characters and Unicode

Total characters264
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)100.0%

Sample

1st row※ 2017.6월말 기준 사회복지법인
2nd row연번
3rd row총계
4th row1
5th row2
ValueCountFrequency (%)
※ 1
 
0.8%
59 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
82 1
 
0.8%
81 1
 
0.8%
80 1
 
0.8%
79 1
 
0.8%
78 1
 
0.8%
77 1
 
0.8%
Other values (112) 112
91.8%
2024-03-14T10:17:09.755397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 47
17.8%
2 23
8.7%
6 23
8.7%
0 22
8.3%
7 22
8.3%
5 22
8.3%
4 22
8.3%
3 22
8.3%
9 21
8.0%
8 21
8.0%
Other values (17) 19
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 245
92.8%
Other Letter 14
 
5.3%
Space Separator 3
 
1.1%
Other Punctuation 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 1
 
7.1%
계 1
 
7.1%
총 1
 
7.1%
번 1
 
7.1%
연 1
 
7.1%
법 1
 
7.1%
지 1
 
7.1%
복 1
 
7.1%
사 1
 
7.1%
준 1
 
7.1%
Other values (4) 4
28.6%
Decimal Number
ValueCountFrequency (%)
1 47
19.2%
2 23
9.4%
6 23
9.4%
0 22
9.0%
7 22
9.0%
5 22
9.0%
4 22
9.0%
3 22
9.0%
9 21
8.6%
8 21
8.6%
Other Punctuation
ValueCountFrequency (%)
※ 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 250
94.7%
Hangul 14
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 1
 
7.1%
계 1
 
7.1%
총 1
 
7.1%
번 1
 
7.1%
연 1
 
7.1%
법 1
 
7.1%
지 1
 
7.1%
복 1
 
7.1%
사 1
 
7.1%
준 1
 
7.1%
Other values (4) 4
28.6%
Common
ValueCountFrequency (%)
1 47
18.8%
2 23
9.2%
6 23
9.2%
0 22
8.8%
7 22
8.8%
5 22
8.8%
4 22
8.8%
3 22
8.8%
9 21
8.4%
8 21
8.4%
Other values (3) 5
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 249
94.3%
Hangul 14
 
5.3%
Punctuation 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 47
18.9%
2 23
9.2%
6 23
9.2%
0 22
8.8%
7 22
8.8%
5 22
8.8%
4 22
8.8%
3 22
8.8%
9 21
8.4%
8 21
8.4%
Other values (2) 4
 
1.6%
Hangul
ValueCountFrequency (%)
인 1
 
7.1%
계 1
 
7.1%
총 1
 
7.1%
번 1
 
7.1%
연 1
 
7.1%
법 1
 
7.1%
지 1
 
7.1%
복 1
 
7.1%
사 1
 
7.1%
준 1
 
7.1%
Other values (4) 4
28.6%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%

Unnamed: 1
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing154
Missing (%)99.4%
Memory size1.3 KiB
2024-03-14T10:17:09.854976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row담당자
ValueCountFrequency (%)
담당자 1
100.0%
2024-03-14T10:17:10.272586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
담 1
33.3%
당 1
33.3%
자 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
담 1
33.3%
당 1
33.3%
자 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
담 1
33.3%
당 1
33.3%
자 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
담 1
33.3%
당 1
33.3%
자 1
33.3%

Unnamed: 2
Categorical

Distinct17
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
노인
46 
<NA>
38 
장애인
24 
아동
11 
사회복귀시설운영
9 
Other values (12)
27 

Length

Max length28
Median length9
Mean length3.7096774
Min length2

Unique

Unique6 ?
Unique (%)3.9%

Sample

1st row<NA>
2nd row<NA>
3rd row주요 목적사업 <노인,아동,장애인 등으로만 기재>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
노인 46
29.7%
<NA> 38
24.5%
장애인 24
15.5%
아동 11
 
7.1%
사회복귀시설운영 9
 
5.8%
보육/노인 5
 
3.2%
한부모 5
 
3.2%
사회복지 4
 
2.6%
정신요양시설운영 3
 
1.9%
사회복지 2
 
1.3%
Other values (7) 8
 
5.2%

Length

2024-03-14T10:17:10.383218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인 46
28.7%
na 38
23.8%
장애인 24
15.0%
아동 11
 
6.9%
사회복귀시설운영 9
 
5.6%
사회복지 6
 
3.8%
보육/노인 5
 
3.1%
한부모 5
 
3.1%
정신요양시설운영 3
 
1.9%
노인/보육 2
 
1.2%
Other values (11) 11
 
6.9%

Unnamed: 3
Categorical

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
전북
117 
<NA>
37 
시도
 
1

Length

Max length4
Median length2
Mean length2.4774194
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row<NA>
2nd row<NA>
3rd row시도
4th row<NA>
5th row전북

Common Values

ValueCountFrequency (%)
전북 117
75.5%
<NA> 37
 
23.9%
시도 1
 
0.6%

Length

2024-03-14T10:17:10.483574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:17:10.575143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북 117
75.5%
na 37
 
23.9%
시도 1
 
0.6%

Unnamed: 4
Categorical

Distinct15
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
38 
전주시
28 
익산시
17 
완주군
16 
군산시
14 
Other values (10)
42 

Length

Max length4
Median length3
Mean length3.2451613
Min length3

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 38
24.5%
전주시 28
18.1%
익산시 17
11.0%
완주군 16
10.3%
군산시 14
 
9.0%
남원시 10
 
6.5%
정읍시 9
 
5.8%
김제시 7
 
4.5%
고창군 4
 
2.6%
순창군 3
 
1.9%
Other values (5) 9
 
5.8%

Length

2024-03-14T10:17:10.686115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 38
24.5%
전주시 28
18.1%
익산시 17
11.0%
완주군 16
10.3%
군산시 14
 
9.0%
남원시 10
 
6.5%
정읍시 9
 
5.8%
김제시 7
 
4.5%
고창군 4
 
2.6%
순창군 3
 
1.9%
Other values (5) 9
 
5.8%

Unnamed: 5
Text

MISSING 

Distinct118
Distinct (%)100.0%
Missing37
Missing (%)23.9%
Memory size1.3 KiB
2024-03-14T10:17:10.959933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length5.6610169
Min length1

Characters and Unicode

Total characters668
Distinct characters171
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)100.0%

Sample

1st row법 인 명
2nd row116개 법인
3rd row전라북도사회복지협의회
4th row참사랑복지회
5th row천주교성가복지회
ValueCountFrequency (%)
임마누엘 1
 
0.8%
평화 1
 
0.8%
김제가나안복지재단 1
 
0.8%
유한복지재단 1
 
0.8%
햇빛 1
 
0.8%
우리원 1
 
0.8%
예닮문화복지재단 1
 
0.8%
서남행복원 1
 
0.8%
서남 1
 
0.8%
상초 1
 
0.8%
Other values (119) 119
92.2%
2024-03-14T10:17:11.297845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
복 63
 
9.4%
지 60
 
9.0%
재 43
 
6.4%
단 43
 
6.4%
원 39
 
5.8%
회 22
 
3.3%
17
 
2.5%
사 15
 
2.2%
성 11
 
1.6%
산 9
 
1.3%
Other values (161) 346
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 644
96.4%
Space Separator 17
 
2.5%
Decimal Number 3
 
0.4%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
복 63
 
9.8%
지 60
 
9.3%
재 43
 
6.7%
단 43
 
6.7%
원 39
 
6.1%
회 22
 
3.4%
사 15
 
2.3%
성 11
 
1.7%
산 9
 
1.4%
의 9
 
1.4%
Other values (156) 330
51.2%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
6 1
33.3%
Space Separator
ValueCountFrequency (%)
17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 644
96.4%
Common 24
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
복 63
 
9.8%
지 60
 
9.3%
재 43
 
6.7%
단 43
 
6.7%
원 39
 
6.1%
회 22
 
3.4%
사 15
 
2.3%
성 11
 
1.7%
산 9
 
1.4%
의 9
 
1.4%
Other values (156) 330
51.2%
Common
ValueCountFrequency (%)
17
70.8%
) 2
 
8.3%
( 2
 
8.3%
1 2
 
8.3%
6 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 644
96.4%
ASCII 24
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
복 63
 
9.8%
지 60
 
9.3%
재 43
 
6.7%
단 43
 
6.7%
원 39
 
6.1%
회 22
 
3.4%
사 15
 
2.3%
성 11
 
1.7%
산 9
 
1.4%
의 9
 
1.4%
Other values (156) 330
51.2%
ASCII
ValueCountFrequency (%)
17
70.8%
) 2
 
8.3%
( 2
 
8.3%
1 2
 
8.3%
6 1
 
4.2%

Unnamed: 6
Text

MISSING 

Distinct115
Distinct (%)98.3%
Missing38
Missing (%)24.5%
Memory size1.3 KiB
2024-03-14T10:17:11.579204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.017094
Min length2

Characters and Unicode

Total characters353
Distinct characters117
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

Unique114 ?
Unique (%)97.4%

Sample

1st row대표자명
2nd row차종선
3rd row양기승
4th row이병호
5th row김정석
ValueCountFrequency (%)
이병호 3
 
2.5%
이인재 1
 
0.8%
안준언 1
 
0.8%
박춘아 1
 
0.8%
김영식 1
 
0.8%
온주현 1
 
0.8%
전유권 1
 
0.8%
최규순 1
 
0.8%
김상태 1
 
0.8%
임안희 1
 
0.8%
Other values (107) 107
89.9%
2024-03-14T10:17:11.981224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 25
 
7.1%
이 15
 
4.2%
박 15
 
4.2%
영 11
 
3.1%
정 10
 
2.8%
병 8
 
2.3%
인 7
 
2.0%
순 7
 
2.0%
최 6
 
1.7%
규 6
 
1.7%
Other values (107) 243
68.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 349
98.9%
Space Separator 4
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 25
 
7.2%
이 15
 
4.3%
박 15
 
4.3%
영 11
 
3.2%
정 10
 
2.9%
병 8
 
2.3%
인 7
 
2.0%
순 7
 
2.0%
최 6
 
1.7%
규 6
 
1.7%
Other values (106) 239
68.5%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 349
98.9%
Common 4
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 25
 
7.2%
이 15
 
4.3%
박 15
 
4.3%
영 11
 
3.2%
정 10
 
2.9%
병 8
 
2.3%
인 7
 
2.0%
순 7
 
2.0%
최 6
 
1.7%
규 6
 
1.7%
Other values (106) 239
68.5%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 349
98.9%
ASCII 4
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 25
 
7.2%
이 15
 
4.3%
박 15
 
4.3%
영 11
 
3.2%
정 10
 
2.9%
병 8
 
2.3%
인 7
 
2.0%
순 7
 
2.0%
최 6
 
1.7%
규 6
 
1.7%
Other values (106) 239
68.5%
ASCII
ValueCountFrequency (%)
4
100.0%

Unnamed: 7
Categorical

Distinct46
Distinct (%)29.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
38 
2006
14 
2004
11 
2007
9 
1999
 
7
Other values (41)
76 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique24 ?
Unique (%)15.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 38
24.5%
2006 14
 
9.0%
2004 11
 
7.1%
2007 9
 
5.8%
1999 7
 
4.5%
2005 7
 
4.5%
2016 5
 
3.2%
2003 5
 
3.2%
1997 4
 
2.6%
2000 4
 
2.6%
Other values (36) 51
32.9%

Length

2024-03-14T10:17:12.095174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 38
24.5%
2006 14
 
9.0%
2004 11
 
7.1%
2007 9
 
5.8%
1999 7
 
4.5%
2005 7
 
4.5%
2016 5
 
3.2%
2003 5
 
3.2%
2000 4
 
2.6%
1997 4
 
2.6%
Other values (36) 51
32.9%

Unnamed: 8
Text

MISSING 

Distinct117
Distinct (%)100.0%
Missing38
Missing (%)24.5%
Memory size1.3 KiB
2024-03-14T10:17:12.352091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length14.965812
Min length3

Characters and Unicode

Total characters1751
Distinct characters175
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

Unique117 ?
Unique (%)100.0%

Sample

1st row주소지
2nd row전주시 덕진구 전주천동로 483
3rd row전주시 완산구 바람쐬는길 152
4th row전주시 완산구 서노송동 560-6
5th row전주시 완산구 전주객사 2길 12-8
ValueCountFrequency (%)
전주시 28
 
6.4%
완산구 19
 
4.3%
완주군 16
 
3.7%
익산시 16
 
3.7%
군산시 14
 
3.2%
남원시 10
 
2.3%
덕진구 9
 
2.1%
정읍시 9
 
2.1%
김제시 7
 
1.6%
소양면 5
 
1.1%
Other values (265) 304
69.6%
2024-03-14T10:17:12.772984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
320
 
18.3%
시 84
 
4.8%
1 67
 
3.8%
산 62
 
3.5%
로 59
 
3.4%
길 59
 
3.4%
2 53
 
3.0%
주 52
 
3.0%
- 47
 
2.7%
4 44
 
2.5%
Other values (165) 904
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1009
57.6%
Decimal Number 371
 
21.2%
Space Separator 320
 
18.3%
Dash Punctuation 47
 
2.7%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 84
 
8.3%
산 62
 
6.1%
로 59
 
5.8%
길 59
 
5.8%
주 52
 
5.2%
군 43
 
4.3%
면 40
 
4.0%
완 35
 
3.5%
전 33
 
3.3%
구 33
 
3.3%
Other values (151) 509
50.4%
Decimal Number
ValueCountFrequency (%)
1 67
18.1%
2 53
14.3%
4 44
11.9%
3 39
10.5%
7 35
9.4%
6 34
9.2%
5 29
7.8%
9 29
7.8%
8 24
 
6.5%
0 17
 
4.6%
Space Separator
ValueCountFrequency (%)
320
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1009
57.6%
Common 742
42.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 84
 
8.3%
산 62
 
6.1%
로 59
 
5.8%
길 59
 
5.8%
주 52
 
5.2%
군 43
 
4.3%
면 40
 
4.0%
완 35
 
3.5%
전 33
 
3.3%
구 33
 
3.3%
Other values (151) 509
50.4%
Common
ValueCountFrequency (%)
320
43.1%
1 67
 
9.0%
2 53
 
7.1%
- 47
 
6.3%
4 44
 
5.9%
3 39
 
5.3%
7 35
 
4.7%
6 34
 
4.6%
5 29
 
3.9%
9 29
 
3.9%
Other values (4) 45
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1009
57.6%
ASCII 742
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
320
43.1%
1 67
 
9.0%
2 53
 
7.1%
- 47
 
6.3%
4 44
 
5.9%
3 39
 
5.3%
7 35
 
4.7%
6 34
 
4.6%
5 29
 
3.9%
9 29
 
3.9%
Other values (4) 45
 
6.1%
Hangul
ValueCountFrequency (%)
시 84
 
8.3%
산 62
 
6.1%
로 59
 
5.8%
길 59
 
5.8%
주 52
 
5.2%
군 43
 
4.3%
면 40
 
4.0%
완 35
 
3.5%
전 33
 
3.3%
구 33
 
3.3%
Other values (151) 509
50.4%

Unnamed: 9
Categorical

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
1
110 
<NA>
38 
2
 
6
유형 (시설 법인1 지원 법인2)
 
1

Length

Max length18
Median length1
Mean length1.8451613
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row<NA>
2nd row<NA>
3rd row유형 (시설 법인1 지원 법인2)
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
1 110
71.0%
<NA> 38
 
24.5%
2 6
 
3.9%
유형 (시설 법인1 지원 법인2) 1
 
0.6%

Length

2024-03-14T10:17:12.886835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:17:13.015926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 110
69.2%
na 38
 
23.9%
2 6
 
3.8%
유형 1
 
0.6%
시설 1
 
0.6%
법인1 1
 
0.6%
지원 1
 
0.6%
법인2 1
 
0.6%

Unnamed: 10
Text

MISSING 

Distinct113
Distinct (%)97.4%
Missing39
Missing (%)25.2%
Memory size1.3 KiB
2024-03-14T10:17:13.265631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.0258621
Min length3

Characters and Unicode

Total characters699
Distinct characters25
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)96.6%

Sample

1st row기본재산 (백만원)
2nd row 1,999
3rd row 3,520
4th row 1,422
5th row -
ValueCountFrequency (%)
4
 
3.4%
714 1
 
0.9%
927 1
 
0.9%
2,059 1
 
0.9%
483 1
 
0.9%
188 1
 
0.9%
179 1
 
0.9%
55 1
 
0.9%
101 1
 
0.9%
2,238 1
 
0.9%
Other values (104) 104
88.9%
2024-03-14T10:17:13.597953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
228
32.6%
1 72
 
10.3%
, 63
 
9.0%
2 55
 
7.9%
5 43
 
6.2%
3 41
 
5.9%
4 36
 
5.2%
9 31
 
4.4%
8 31
 
4.4%
7 29
 
4.1%
Other values (15) 70
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 392
56.1%
Space Separator 228
32.6%
Other Punctuation 63
 
9.0%
Other Letter 9
 
1.3%
Dash Punctuation 4
 
0.6%
Control 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 72
18.4%
2 55
14.0%
5 43
11.0%
3 41
10.5%
4 36
9.2%
9 31
7.9%
8 31
7.9%
7 29
7.4%
6 27
 
6.9%
0 27
 
6.9%
Other Letter
ValueCountFrequency (%)
기 1
11.1%
본 1
11.1%
재 1
11.1%
산 1
11.1%
백 1
11.1%
만 1
11.1%
원 1
11.1%
없 1
11.1%
음 1
11.1%
Space Separator
ValueCountFrequency (%)
228
100.0%
Other Punctuation
ValueCountFrequency (%)
, 63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 690
98.7%
Hangul 9
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
228
33.0%
1 72
 
10.4%
, 63
 
9.1%
2 55
 
8.0%
5 43
 
6.2%
3 41
 
5.9%
4 36
 
5.2%
9 31
 
4.5%
8 31
 
4.5%
7 29
 
4.2%
Other values (6) 61
 
8.8%
Hangul
ValueCountFrequency (%)
기 1
11.1%
본 1
11.1%
재 1
11.1%
산 1
11.1%
백 1
11.1%
만 1
11.1%
원 1
11.1%
없 1
11.1%
음 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 690
98.7%
Hangul 9
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
228
33.0%
1 72
 
10.4%
, 63
 
9.1%
2 55
 
8.0%
5 43
 
6.2%
3 41
 
5.9%
4 36
 
5.2%
9 31
 
4.5%
8 31
 
4.5%
7 29
 
4.2%
Other values (6) 61
 
8.8%
Hangul
ValueCountFrequency (%)
기 1
11.1%
본 1
11.1%
재 1
11.1%
산 1
11.1%
백 1
11.1%
만 1
11.1%
원 1
11.1%
없 1
11.1%
음 1
11.1%

Unnamed: 11
Categorical

Distinct14
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
1
63 
<NA>
38 
2
24 
3
8 
0
 
6
Other values (9)
16 

Length

Max length11
Median length1
Mean length1.8387097
Min length1

Unique

Unique7 ?
Unique (%)4.5%

Sample

1st row<NA>
2nd row<NA>
3rd row사회복지시설 운영현황
4th row총 계
5th row<NA>

Common Values

ValueCountFrequency (%)
1 63
40.6%
<NA> 38
24.5%
2 24
 
15.5%
3 8
 
5.2%
0 6
 
3.9%
4 6
 
3.9%
5 3
 
1.9%
사회복지시설 운영현황 1
 
0.6%
총 계 1
 
0.6%
97 1
 
0.6%
Other values (4) 4
 
2.6%

Length

2024-03-14T10:17:13.713575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 63
40.1%
na 38
24.2%
2 24
 
15.3%
3 8
 
5.1%
0 6
 
3.8%
4 6
 
3.8%
5 3
 
1.9%
사회복지시설 1
 
0.6%
운영현황 1
 
0.6%
총 1
 
0.6%
Other values (6) 6
 
3.8%

Unnamed: 12
Categorical

IMBALANCE 

Distinct12
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
94 
1
38 
2
11 
4
 
3
3
 
2
Other values (7)
 
7

Length

Max length4
Median length4
Mean length2.8387097
Min length1

Unique

Unique7 ?
Unique (%)4.5%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row노 인
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 94
60.6%
1 38
24.5%
2 11
 
7.1%
4 3
 
1.9%
3 2
 
1.3%
노 인 1
 
0.6%
44 1
 
0.6%
7 1
 
0.6%
5 1
 
0.6%
6 1
 
0.6%
Other values (2) 2
 
1.3%

Length

2024-03-14T10:17:13.834653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 94
60.3%
1 38
24.4%
2 11
 
7.1%
4 3
 
1.9%
3 2
 
1.3%
노 1
 
0.6%
인 1
 
0.6%
44 1
 
0.6%
7 1
 
0.6%
5 1
 
0.6%
Other values (3) 3
 
1.9%

Unnamed: 13
Categorical

IMBALANCE 

Distinct8
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
125 
1
19 
2
 
4
3
 
3
장애인
 
1
Other values (3)
 
3

Length

Max length4
Median length4
Mean length3.4387097
Min length1

Unique

Unique4 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 125
80.6%
1 19
 
12.3%
2 4
 
2.6%
3 3
 
1.9%
장애인 1
 
0.6%
6 1
 
0.6%
4 1
 
0.6%
10 1
 
0.6%

Length

2024-03-14T10:17:13.942939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:17:14.041931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 125
80.6%
1 19
 
12.3%
2 4
 
2.6%
3 3
 
1.9%
장애인 1
 
0.6%
6 1
 
0.6%
4 1
 
0.6%
10 1
 
0.6%

Unnamed: 14
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
131 
1
19 
3
 
2
아동
 
1
25
 
1

Length

Max length4
Median length4
Mean length3.5483871
Min length1

Unique

Unique3 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 131
84.5%
1 19
 
12.3%
3 2
 
1.3%
아동 1
 
0.6%
25 1
 
0.6%
2 1
 
0.6%

Length

2024-03-14T10:17:14.140451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:17:14.236392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 131
84.5%
1 19
 
12.3%
3 2
 
1.3%
아동 1
 
0.6%
25 1
 
0.6%
2 1
 
0.6%

Unnamed: 15
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing149
Missing (%)96.1%
Memory size1.3 KiB
2024-03-14T10:17:14.301052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.6666667
Min length1

Characters and Unicode

Total characters10
Distinct characters6
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

Unique2 ?
Unique (%)33.3%

Sample

1st row한 부 모
2nd row1
3rd row1
4th row2
5th row1
ValueCountFrequency (%)
1 4
50.0%
한 1
 
12.5%
부 1
 
12.5%
모 1
 
12.5%
2 1
 
12.5%
2024-03-14T10:17:14.489970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
40.0%
2
20.0%
한 1
 
10.0%
부 1
 
10.0%
모 1
 
10.0%
2 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
50.0%
Other Letter 3
30.0%
Control 2
 
20.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 1
33.3%
부 1
33.3%
모 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 4
80.0%
2 1
 
20.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7
70.0%
Hangul 3
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
57.1%
2
28.6%
2 1
 
14.3%
Hangul
ValueCountFrequency (%)
한 1
33.3%
부 1
33.3%
모 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
70.0%
Hangul 3
30.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
57.1%
2
28.6%
2 1
 
14.3%
Hangul
ValueCountFrequency (%)
한 1
33.3%
부 1
33.3%
모 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing152
Missing (%)98.1%
Memory size1.3 KiB
2024-03-14T10:17:14.582988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length2.3333333
Min length1

Characters and Unicode

Total characters7
Distinct characters5
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

Unique1 ?
Unique (%)33.3%

Sample

1st row청 소 년
2nd row1
3rd row1
ValueCountFrequency (%)
1 2
40.0%
청 1
20.0%
소 1
20.0%
년 1
20.0%
2024-03-14T10:17:14.792247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
28.6%
2
28.6%
청 1
14.3%
소 1
14.3%
년 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
42.9%
Decimal Number 2
28.6%
Control 2
28.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 1
33.3%
소 1
33.3%
년 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
57.1%
Hangul 3
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 1
33.3%
소 1
33.3%
년 1
33.3%
Common
ValueCountFrequency (%)
1 2
50.0%
2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
57.1%
Hangul 3
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
50.0%
2
50.0%
Hangul
ValueCountFrequency (%)
청 1
33.3%
소 1
33.3%
년 1
33.3%

Unnamed: 17
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing152
Missing (%)98.1%
Memory size1.3 KiB
2024-03-14T10:17:14.894867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.6666667
Min length1

Characters and Unicode

Total characters5
Distinct characters4
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

Unique1 ?
Unique (%)33.3%

Sample

1st row노숙인
2nd row1
3rd row1
ValueCountFrequency (%)
1 2
66.7%
노숙인 1
33.3%
2024-03-14T10:17:15.079092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
40.0%
노 1
20.0%
숙 1
20.0%
인 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
60.0%
Decimal Number 2
40.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
노 1
33.3%
숙 1
33.3%
인 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
60.0%
Common 2
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
노 1
33.3%
숙 1
33.3%
인 1
33.3%
Common
ValueCountFrequency (%)
1 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
60.0%
ASCII 2
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
100.0%
Hangul
ValueCountFrequency (%)
노 1
33.3%
숙 1
33.3%
인 1
33.3%

Unnamed: 18
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing154
Missing (%)99.4%
Memory size1.3 KiB
2024-03-14T10:17:15.184740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row결핵한센
ValueCountFrequency (%)
결핵한센 1
100.0%
2024-03-14T10:17:15.419827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
결 1
25.0%
핵 1
25.0%
한 1
25.0%
센 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
결 1
25.0%
핵 1
25.0%
한 1
25.0%
센 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
결 1
25.0%
핵 1
25.0%
한 1
25.0%
센 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
결 1
25.0%
핵 1
25.0%
한 1
25.0%
센 1
25.0%

Unnamed: 19
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing152
Missing (%)98.1%
Memory size1.3 KiB
2024-03-14T10:17:15.517472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length1
Mean length3.3333333
Min length1

Characters and Unicode

Total characters10
Distinct characters8
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

Unique1 ?
Unique (%)33.3%

Sample

1st row지역 자활 센터
2nd row1
3rd row1
ValueCountFrequency (%)
1 2
40.0%
지역 1
20.0%
자활 1
20.0%
센터 1
20.0%
2024-03-14T10:17:15.737243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
20.0%
2
20.0%
지 1
10.0%
역 1
10.0%
자 1
10.0%
활 1
10.0%
센 1
10.0%
터 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
60.0%
Decimal Number 2
 
20.0%
Control 2
 
20.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1
16.7%
역 1
16.7%
자 1
16.7%
활 1
16.7%
센 1
16.7%
터 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
60.0%
Common 4
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1
16.7%
역 1
16.7%
자 1
16.7%
활 1
16.7%
센 1
16.7%
터 1
16.7%
Common
ValueCountFrequency (%)
1 2
50.0%
2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
60.0%
ASCII 4
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
50.0%
2
50.0%
Hangul
ValueCountFrequency (%)
지 1
16.7%
역 1
16.7%
자 1
16.7%
활 1
16.7%
센 1
16.7%
터 1
16.7%

Unnamed: 20
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing149
Missing (%)96.1%
Memory size1.3 KiB
2024-03-14T10:17:15.828148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.5
Min length1

Characters and Unicode

Total characters9
Distinct characters6
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

Unique2 ?
Unique (%)33.3%

Sample

1st row정신요양
2nd row1
3rd row3
4th row1
5th row1
ValueCountFrequency (%)
1 4
66.7%
정신요양 1
 
16.7%
3 1
 
16.7%
2024-03-14T10:17:16.060854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
44.4%
정 1
 
11.1%
신 1
 
11.1%
요 1
 
11.1%
양 1
 
11.1%
3 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
55.6%
Other Letter 4
44.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 1
25.0%
신 1
25.0%
요 1
25.0%
양 1
25.0%
Decimal Number
ValueCountFrequency (%)
1 4
80.0%
3 1
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
55.6%
Hangul 4
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 1
25.0%
신 1
25.0%
요 1
25.0%
양 1
25.0%
Common
ValueCountFrequency (%)
1 4
80.0%
3 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
55.6%
Hangul 4
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
80.0%
3 1
 
20.0%
Hangul
ValueCountFrequency (%)
정 1
25.0%
신 1
25.0%
요 1
25.0%
양 1
25.0%

Unnamed: 21
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing149
Missing (%)96.1%
Memory size1.3 KiB
2024-03-14T10:17:16.161522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length2.5
Min length1

Characters and Unicode

Total characters15
Distinct characters8
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

Unique2 ?
Unique (%)33.3%

Sample

1st row사 회 복 지 관
2nd row13
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 4
40.0%
사 1
 
10.0%
회 1
 
10.0%
복 1
 
10.0%
지 1
 
10.0%
관 1
 
10.0%
13 1
 
10.0%
2024-03-14T10:17:16.352019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
33.3%
4
26.7%
사 1
 
6.7%
회 1
 
6.7%
복 1
 
6.7%
지 1
 
6.7%
관 1
 
6.7%
3 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
40.0%
Other Letter 5
33.3%
Control 4
26.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1
20.0%
회 1
20.0%
복 1
20.0%
지 1
20.0%
관 1
20.0%
Decimal Number
ValueCountFrequency (%)
1 5
83.3%
3 1
 
16.7%
Control
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
66.7%
Hangul 5
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1
20.0%
회 1
20.0%
복 1
20.0%
지 1
20.0%
관 1
20.0%
Common
ValueCountFrequency (%)
1 5
50.0%
4
40.0%
3 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
66.7%
Hangul 5
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
50.0%
4
40.0%
3 1
 
10.0%
Hangul
ValueCountFrequency (%)
사 1
20.0%
회 1
20.0%
복 1
20.0%
지 1
20.0%
관 1
20.0%

Unnamed: 22
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing149
Missing (%)96.1%
Memory size1.3 KiB
2024-03-14T10:17:16.459609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.6666667
Min length1

Characters and Unicode

Total characters10
Distinct characters7
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

Unique2 ?
Unique (%)33.3%

Sample

1st row노인복지관
2nd row5
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 4
66.7%
노인복지관 1
 
16.7%
5 1
 
16.7%
2024-03-14T10:17:16.683829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
40.0%
노 1
 
10.0%
인 1
 
10.0%
복 1
 
10.0%
지 1
 
10.0%
관 1
 
10.0%
5 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
50.0%
Other Letter 5
50.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
노 1
20.0%
인 1
20.0%
복 1
20.0%
지 1
20.0%
관 1
20.0%
Decimal Number
ValueCountFrequency (%)
1 4
80.0%
5 1
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
50.0%
Hangul 5
50.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
노 1
20.0%
인 1
20.0%
복 1
20.0%
지 1
20.0%
관 1
20.0%
Common
ValueCountFrequency (%)
1 4
80.0%
5 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
50.0%
Hangul 5
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
80.0%
5 1
 
20.0%
Hangul
ValueCountFrequency (%)
노 1
20.0%
인 1
20.0%
복 1
20.0%
지 1
20.0%
관 1
20.0%

Unnamed: 23
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing149
Missing (%)96.1%
Memory size1.3 KiB
2024-03-14T10:17:16.772008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length1
Mean length1.8333333
Min length1

Characters and Unicode

Total characters11
Distinct characters8
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

Unique2 ?
Unique (%)33.3%

Sample

1st row장애인복지관
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 4
66.7%
장애인복지관 1
 
16.7%
2 1
 
16.7%
2024-03-14T10:17:16.969357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
36.4%
장 1
 
9.1%
애 1
 
9.1%
인 1
 
9.1%
복 1
 
9.1%
지 1
 
9.1%
관 1
 
9.1%
2 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
54.5%
Decimal Number 5
45.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 1
16.7%
애 1
16.7%
인 1
16.7%
복 1
16.7%
지 1
16.7%
관 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 4
80.0%
2 1
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
54.5%
Common 5
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 1
16.7%
애 1
16.7%
인 1
16.7%
복 1
16.7%
지 1
16.7%
관 1
16.7%
Common
ValueCountFrequency (%)
1 4
80.0%
2 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
54.5%
ASCII 5
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
80.0%
2 1
 
20.0%
Hangul
ValueCountFrequency (%)
장 1
16.7%
애 1
16.7%
인 1
16.7%
복 1
16.7%
지 1
16.7%
관 1
16.7%

Unnamed: 24
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
141 
1
 
8
2
 
4
사회복귀
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.7483871
Min length1

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 141
91.0%
1 8
 
5.2%
2 4
 
2.6%
사회복귀 1
 
0.6%
3 1
 
0.6%

Length

2024-03-14T10:17:17.078127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:17:17.169973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 141
91.0%
1 8
 
5.2%
2 4
 
2.6%
사회복귀 1
 
0.6%
3 1
 
0.6%

Unnamed: 25
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing154
Missing (%)99.4%
Memory size1.3 KiB
2024-03-14T10:17:17.260785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row보육시설
ValueCountFrequency (%)
보육시설 1
100.0%
2024-03-14T10:17:17.476813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 1
25.0%
육 1
25.0%
시 1
25.0%
설 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 1
25.0%
육 1
25.0%
시 1
25.0%
설 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 1
25.0%
육 1
25.0%
시 1
25.0%
설 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 1
25.0%
육 1
25.0%
시 1
25.0%
설 1
25.0%

Unnamed: 26
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing154
Missing (%)99.4%
Memory size1.3 KiB
2024-03-14T10:17:17.597801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row다문화가족지원
ValueCountFrequency (%)
다문화가족지원 1
100.0%
2024-03-14T10:17:17.804500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
다 1
14.3%
문 1
14.3%
화 1
14.3%
가 1
14.3%
족 1
14.3%
지 1
14.3%
원 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 1
14.3%
문 1
14.3%
화 1
14.3%
가 1
14.3%
족 1
14.3%
지 1
14.3%
원 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 1
14.3%
문 1
14.3%
화 1
14.3%
가 1
14.3%
족 1
14.3%
지 1
14.3%
원 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
다 1
14.3%
문 1
14.3%
화 1
14.3%
가 1
14.3%
족 1
14.3%
지 1
14.3%
원 1
14.3%

Unnamed: 27
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing154
Missing (%)99.4%
Memory size1.3 KiB
2024-03-14T10:17:17.913603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
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

Unique1 ?
Unique (%)100.0%

Sample

1st row기 타
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%
2024-03-14T10:17:18.087346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1
33.3%
1
33.3%
타 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
66.7%
Control 1
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
66.7%
Common 1
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
66.7%
ASCII 1
33.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 28
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing154
Missing (%)99.4%
Memory size1.3 KiB
2024-03-14T10:17:18.177159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row비고
ValueCountFrequency (%)
비고 1
100.0%
2024-03-14T10:17:18.365508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Unnamed: 29
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing155
Missing (%)100.0%
Memory size1.5 KiB

Sample

사회복지법인 현황 (전라북도)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29
0※ 2017.6월말 기준 사회복지법인<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2연번담당자주요 목적사업 <노인,아동,장애인 등으로만 기재>시도시군구법 인 명대표자명설립연도주소지유형 (시설 법인1 지원 법인2)기본재산 (백만원)사회복지시설 운영현황<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>비고<NA>
3<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>총 계노 인장애인아동한 부 모청 소 년노숙인결핵한센지역 자활 센터정신요양사 회 복 지 관노인복지관장애인복지관사회복귀보육시설다문화가족지원기 타<NA><NA>
4총계<NA><NA>전북<NA>116개 법인<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51<NA>사회복지전북전주시전라북도사회복지협의회차종선1999전주시 덕진구 전주천동로 48321,9990<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
62<NA>정신요양시설운영전북전주시참사랑복지회양기승1982전주시 완산구 바람쐬는길 15213,5201<NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA><NA><NA>
73<NA>사회복지/여성전북전주시천주교성가복지회이병호1999전주시 완산구 서노송동 560-611,4221<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA><NA><NA><NA>
84<NA>사회복지전북전주시전주시사회복지협의회김정석2007전주시 완산구 전주객사 2길 12-82-0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
95<NA>사회복지전북군산시군산시사회복지협의회정윤모2006군산시 백릉안3길 122-0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
사회복지법인 현황 (전라북도)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29
145<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
146<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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148<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
149<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
150<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
151<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
152<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
153<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
154<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

사회복지법인 현황 (전라북도)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>35