Overview

Dataset statistics

Number of variables9
Number of observations38
Missing cells185
Missing cells (%)54.1%
Duplicate rows1
Duplicate rows (%)2.6%
Total size in memory2.8 KiB
Average record size in memory75.5 B

Variable types

Text9

Alerts

Dataset has 1 (2.6%) duplicate rowsDuplicates
전라북도 사회복지관 현황 has 28 (73.7%) missing valuesMissing
Unnamed: 1 has 20 (52.6%) missing valuesMissing
Unnamed: 2 has 20 (52.6%) missing valuesMissing
Unnamed: 3 has 20 (52.6%) missing valuesMissing
Unnamed: 4 has 18 (47.4%) missing valuesMissing
Unnamed: 5 has 20 (52.6%) missing valuesMissing
Unnamed: 6 has 20 (52.6%) missing valuesMissing
Unnamed: 7 has 20 (52.6%) missing valuesMissing
Unnamed: 8 has 19 (50.0%) missing valuesMissing

Reproduction

Analysis started2024-03-14 01:58:54.217163
Analysis finished2024-03-14 01:58:54.868190
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도 사회복지관 현황
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing28
Missing (%)73.7%
Memory size436.0 B
2024-03-14T10:58:54.954828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.2
Min length2

Characters and Unicode

Total characters22
Distinct characters20
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

Unique10 ?
Unique (%)100.0%

Sample

1st row시군
2nd row17개소
3rd row전주
4th row군산
5th row익산
ValueCountFrequency (%)
시군 1
10.0%
17개소 1
10.0%
전주 1
10.0%
군산 1
10.0%
익산 1
10.0%
정읍 1
10.0%
남원 1
10.0%
김제 1
10.0%
고창 1
10.0%
부안 1
10.0%
2024-03-14T10:58:55.323191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 2
 
9.1%
군 2
 
9.1%
시 1
 
4.5%
읍 1
 
4.5%
부 1
 
4.5%
창 1
 
4.5%
고 1
 
4.5%
제 1
 
4.5%
김 1
 
4.5%
원 1
 
4.5%
Other values (10) 10
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20
90.9%
Decimal Number 2
 
9.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 2
 
10.0%
군 2
 
10.0%
시 1
 
5.0%
읍 1
 
5.0%
부 1
 
5.0%
창 1
 
5.0%
고 1
 
5.0%
제 1
 
5.0%
김 1
 
5.0%
원 1
 
5.0%
Other values (8) 8
40.0%
Decimal Number
ValueCountFrequency (%)
7 1
50.0%
1 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20
90.9%
Common 2
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 2
 
10.0%
군 2
 
10.0%
시 1
 
5.0%
읍 1
 
5.0%
부 1
 
5.0%
창 1
 
5.0%
고 1
 
5.0%
제 1
 
5.0%
김 1
 
5.0%
원 1
 
5.0%
Other values (8) 8
40.0%
Common
ValueCountFrequency (%)
7 1
50.0%
1 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20
90.9%
ASCII 2
 
9.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 2
 
10.0%
군 2
 
10.0%
시 1
 
5.0%
읍 1
 
5.0%
부 1
 
5.0%
창 1
 
5.0%
고 1
 
5.0%
제 1
 
5.0%
김 1
 
5.0%
원 1
 
5.0%
Other values (8) 8
40.0%
ASCII
ValueCountFrequency (%)
7 1
50.0%
1 1
50.0%

Unnamed: 1
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing20
Missing (%)52.6%
Memory size436.0 B
2024-03-14T10:58:55.527290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length8.4444444
Min length3

Characters and Unicode

Total characters152
Distinct characters40
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

Unique18 ?
Unique (%)100.0%

Sample

1st row시설명
2nd row전북종합사회복지관
3rd row전주종합사회복지관
4th row학산종합사회복지관
5th row평화사회복지관
ValueCountFrequency (%)
시설명 1
 
5.6%
전북종합사회복지관 1
 
5.6%
고창종합사회복지관 1
 
5.6%
김제제일사회복지관 1
 
5.6%
김제사회복지관 1
 
5.6%
길보른종합사회복지관 1
 
5.6%
남원사회복지관 1
 
5.6%
정읍종합사회복지관 1
 
5.6%
동산사회복지관 1
 
5.6%
부송종합사회복지관 1
 
5.6%
Other values (8) 8
44.4%
2024-03-14T10:58:55.798091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
복 17
11.2%
관 17
11.2%
사 17
11.2%
회 17
11.2%
지 17
11.2%
종 12
 
7.9%
합 12
 
7.9%
산 4
 
2.6%
제 3
 
2.0%
김 2
 
1.3%
Other values (30) 34
22.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 152
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
복 17
11.2%
관 17
11.2%
사 17
11.2%
회 17
11.2%
지 17
11.2%
종 12
 
7.9%
합 12
 
7.9%
산 4
 
2.6%
제 3
 
2.0%
김 2
 
1.3%
Other values (30) 34
22.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 152
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
복 17
11.2%
관 17
11.2%
사 17
11.2%
회 17
11.2%
지 17
11.2%
종 12
 
7.9%
합 12
 
7.9%
산 4
 
2.6%
제 3
 
2.0%
김 2
 
1.3%
Other values (30) 34
22.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 152
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
복 17
11.2%
관 17
11.2%
사 17
11.2%
회 17
11.2%
지 17
11.2%
종 12
 
7.9%
합 12
 
7.9%
산 4
 
2.6%
제 3
 
2.0%
김 2
 
1.3%
Other values (30) 34
22.4%

Unnamed: 2
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing20
Missing (%)52.6%
Memory size436.0 B
2024-03-14T10:58:55.976549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length14.222222
Min length5

Characters and Unicode

Total characters256
Distinct characters73
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

Unique18 ?
Unique (%)100.0%

Sample

1st row소 재 지
2nd row전주시 완산구 흑석로 70
3rd row전주시 완산구 덕적골 2길 10
4th row전주시 완산구 모악로 4726-1
5th row전주시 완산구 덕적골2길 25
ValueCountFrequency (%)
전주시 5
 
7.6%
완산구 5
 
7.6%
익산시 3
 
4.5%
김제시 3
 
4.5%
군산시 2
 
3.0%
소 1
 
1.5%
93 1
 
1.5%
26-1 1
 
1.5%
정읍시 1
 
1.5%
수성2로 1
 
1.5%
Other values (43) 43
65.2%
2024-03-14T10:58:56.267055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
18.8%
시 15
 
5.9%
로 14
 
5.5%
1 13
 
5.1%
산 11
 
4.3%
2 11
 
4.3%
5 7
 
2.7%
- 7
 
2.7%
4 6
 
2.3%
주 6
 
2.3%
Other values (63) 118
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142
55.5%
Decimal Number 58
22.7%
Space Separator 48
 
18.8%
Dash Punctuation 7
 
2.7%
Control 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 15
 
10.6%
로 14
 
9.9%
산 11
 
7.7%
주 6
 
4.2%
전 6
 
4.2%
구 5
 
3.5%
완 5
 
3.5%
길 5
 
3.5%
익 4
 
2.8%
군 4
 
2.8%
Other values (50) 67
47.2%
Decimal Number
ValueCountFrequency (%)
1 13
22.4%
2 11
19.0%
5 7
12.1%
4 6
10.3%
7 4
 
6.9%
9 4
 
6.9%
3 4
 
6.9%
8 3
 
5.2%
6 3
 
5.2%
0 3
 
5.2%
Space Separator
ValueCountFrequency (%)
48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142
55.5%
Common 114
44.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 15
 
10.6%
로 14
 
9.9%
산 11
 
7.7%
주 6
 
4.2%
전 6
 
4.2%
구 5
 
3.5%
완 5
 
3.5%
길 5
 
3.5%
익 4
 
2.8%
군 4
 
2.8%
Other values (50) 67
47.2%
Common
ValueCountFrequency (%)
48
42.1%
1 13
 
11.4%
2 11
 
9.6%
5 7
 
6.1%
- 7
 
6.1%
4 6
 
5.3%
7 4
 
3.5%
9 4
 
3.5%
3 4
 
3.5%
8 3
 
2.6%
Other values (3) 7
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 142
55.5%
ASCII 114
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
42.1%
1 13
 
11.4%
2 11
 
9.6%
5 7
 
6.1%
- 7
 
6.1%
4 6
 
5.3%
7 4
 
3.5%
9 4
 
3.5%
3 4
 
3.5%
8 3
 
2.6%
Other values (3) 7
 
6.1%
Hangul
ValueCountFrequency (%)
시 15
 
10.6%
로 14
 
9.9%
산 11
 
7.7%
주 6
 
4.2%
전 6
 
4.2%
구 5
 
3.5%
완 5
 
3.5%
길 5
 
3.5%
익 4
 
2.8%
군 4
 
2.8%
Other values (50) 67
47.2%

Unnamed: 3
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing20
Missing (%)52.6%
Memory size436.0 B
2024-03-14T10:58:56.433265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters54
Distinct characters39
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

Unique18 ?
Unique (%)100.0%

Sample

1st row시설장
2nd row문정훈
3rd row정학성
4th row노영웅
5th row성동학
ValueCountFrequency (%)
시설장 1
 
5.6%
문정훈 1
 
5.6%
손형석 1
 
5.6%
김희곤 1
 
5.6%
김준수 1
 
5.6%
권영세 1
 
5.6%
문홍근 1
 
5.6%
박진하 1
 
5.6%
박재명 1
 
5.6%
장지환 1
 
5.6%
Other values (8) 8
44.4%
2024-03-14T10:58:56.672811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 4
 
7.4%
장 3
 
5.6%
성 3
 
5.6%
김 3
 
5.6%
진 2
 
3.7%
문 2
 
3.7%
박 2
 
3.7%
학 2
 
3.7%
영 2
 
3.7%
수 2
 
3.7%
Other values (29) 29
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 4
 
7.4%
장 3
 
5.6%
성 3
 
5.6%
김 3
 
5.6%
진 2
 
3.7%
문 2
 
3.7%
박 2
 
3.7%
학 2
 
3.7%
영 2
 
3.7%
수 2
 
3.7%
Other values (29) 29
53.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 4
 
7.4%
장 3
 
5.6%
성 3
 
5.6%
김 3
 
5.6%
진 2
 
3.7%
문 2
 
3.7%
박 2
 
3.7%
학 2
 
3.7%
영 2
 
3.7%
수 2
 
3.7%
Other values (29) 29
53.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 4
 
7.4%
장 3
 
5.6%
성 3
 
5.6%
김 3
 
5.6%
진 2
 
3.7%
문 2
 
3.7%
박 2
 
3.7%
학 2
 
3.7%
영 2
 
3.7%
수 2
 
3.7%
Other values (29) 29
53.7%

Unnamed: 4
Text

MISSING 

Distinct10
Distinct (%)50.0%
Missing18
Missing (%)47.4%
Memory size436.0 B
2024-03-14T10:58:56.775629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7
Min length1

Characters and Unicode

Total characters34
Distinct characters12
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

Unique5 ?
Unique (%)25.0%

Sample

1st row종사
2nd row자수
3rd row167
4th row11
5th row10
ValueCountFrequency (%)
7 4
20.0%
11 3
15.0%
10 3
15.0%
12 3
15.0%
9 2
10.0%
종사 1
 
5.0%
자수 1
 
5.0%
167 1
 
5.0%
14 1
 
5.0%
8 1
 
5.0%
2024-03-14T10:58:57.234073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
41.2%
7 5
 
14.7%
0 3
 
8.8%
2 3
 
8.8%
9 2
 
5.9%
종 1
 
2.9%
사 1
 
2.9%
자 1
 
2.9%
수 1
 
2.9%
6 1
 
2.9%
Other values (2) 2
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
88.2%
Other Letter 4
 
11.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
46.7%
7 5
 
16.7%
0 3
 
10.0%
2 3
 
10.0%
9 2
 
6.7%
6 1
 
3.3%
4 1
 
3.3%
8 1
 
3.3%
Other Letter
ValueCountFrequency (%)
종 1
25.0%
사 1
25.0%
자 1
25.0%
수 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30
88.2%
Hangul 4
 
11.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
46.7%
7 5
 
16.7%
0 3
 
10.0%
2 3
 
10.0%
9 2
 
6.7%
6 1
 
3.3%
4 1
 
3.3%
8 1
 
3.3%
Hangul
ValueCountFrequency (%)
종 1
25.0%
사 1
25.0%
자 1
25.0%
수 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30
88.2%
Hangul 4
 
11.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
46.7%
7 5
 
16.7%
0 3
 
10.0%
2 3
 
10.0%
9 2
 
6.7%
6 1
 
3.3%
4 1
 
3.3%
8 1
 
3.3%
Hangul
ValueCountFrequency (%)
종 1
25.0%
사 1
25.0%
자 1
25.0%
수 1
25.0%

Unnamed: 5
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing20
Missing (%)52.6%
Memory size436.0 B
2024-03-14T10:58:57.470912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.7222222
Min length3

Characters and Unicode

Total characters139
Distinct characters14
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

Unique18 ?
Unique (%)100.0%

Sample

1st row개관일
2nd row88.12.27
3rd row92.12.28
4th row95.12.29
5th row92.01.13
ValueCountFrequency (%)
개관일 1
 
5.6%
88.12.27 1
 
5.6%
07.11.29 1
 
5.6%
95.03.03 1
 
5.6%
94.12.23 1
 
5.6%
91.03.13 1
 
5.6%
96.02.01 1
 
5.6%
95.01.18 1
 
5.6%
93.09.09 1
 
5.6%
93.07.30 1
 
5.6%
Other values (8) 8
44.4%
2024-03-14T10:58:57.782195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 34
24.5%
0 23
16.5%
9 18
12.9%
1 16
11.5%
2 16
11.5%
3 12
 
8.6%
8 5
 
3.6%
7 3
 
2.2%
5 3
 
2.2%
4 3
 
2.2%
Other values (4) 6
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102
73.4%
Other Punctuation 34
 
24.5%
Other Letter 3
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23
22.5%
9 18
17.6%
1 16
15.7%
2 16
15.7%
3 12
11.8%
8 5
 
4.9%
7 3
 
2.9%
5 3
 
2.9%
4 3
 
2.9%
6 3
 
2.9%
Other Letter
ValueCountFrequency (%)
개 1
33.3%
관 1
33.3%
일 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 136
97.8%
Hangul 3
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 34
25.0%
0 23
16.9%
9 18
13.2%
1 16
11.8%
2 16
11.8%
3 12
 
8.8%
8 5
 
3.7%
7 3
 
2.2%
5 3
 
2.2%
4 3
 
2.2%
Hangul
ValueCountFrequency (%)
개 1
33.3%
관 1
33.3%
일 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 136
97.8%
Hangul 3
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 34
25.0%
0 23
16.9%
9 18
13.2%
1 16
11.8%
2 16
11.8%
3 12
 
8.8%
8 5
 
3.7%
7 3
 
2.2%
5 3
 
2.2%
4 3
 
2.2%
Hangul
ValueCountFrequency (%)
개 1
33.3%
관 1
33.3%
일 1
33.3%

Unnamed: 6
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing20
Missing (%)52.6%
Memory size436.0 B
2024-03-14T10:58:57.971266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length18.444444
Min length9

Characters and Unicode

Total characters332
Distinct characters20
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row연락처 (FAX)
2nd row282-7230 (231-6397)
3rd row284-2733 (283-4423)
4th row223-9999 (226-9001)
5th row285-4408 (287-8032)
ValueCountFrequency (%)
연락처 1
 
2.8%
fax 1
 
2.8%
842-2253 1
 
2.8%
842-2272 1
 
2.8%
533-1916 1
 
2.8%
538-3895 1
 
2.8%
632-5252 1
 
2.8%
632-5253 1
 
2.8%
545-1923 1
 
2.8%
546-1228 1
 
2.8%
Other values (26) 26
72.2%
2024-03-14T10:58:58.240937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 42
12.7%
5 35
10.5%
3 34
10.2%
- 34
10.2%
4 23
 
6.9%
0 21
 
6.3%
6 20
 
6.0%
1 20
 
6.0%
8 20
 
6.0%
) 18
 
5.4%
Other values (10) 65
19.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 238
71.7%
Dash Punctuation 34
 
10.2%
Close Punctuation 18
 
5.4%
Open Punctuation 18
 
5.4%
Control 18
 
5.4%
Other Letter 3
 
0.9%
Uppercase Letter 3
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 42
17.6%
5 35
14.7%
3 34
14.3%
4 23
9.7%
0 21
8.8%
6 20
8.4%
1 20
8.4%
8 20
8.4%
9 12
 
5.0%
7 11
 
4.6%
Other Letter
ValueCountFrequency (%)
락 1
33.3%
처 1
33.3%
연 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
X 1
33.3%
A 1
33.3%
F 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Control
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 326
98.2%
Hangul 3
 
0.9%
Latin 3
 
0.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 42
12.9%
5 35
10.7%
3 34
10.4%
- 34
10.4%
4 23
 
7.1%
0 21
 
6.4%
6 20
 
6.1%
1 20
 
6.1%
8 20
 
6.1%
) 18
 
5.5%
Other values (4) 59
18.1%
Hangul
ValueCountFrequency (%)
락 1
33.3%
처 1
33.3%
연 1
33.3%
Latin
ValueCountFrequency (%)
X 1
33.3%
A 1
33.3%
F 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 329
99.1%
Hangul 3
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 42
12.8%
5 35
10.6%
3 34
10.3%
- 34
10.3%
4 23
 
7.0%
0 21
 
6.4%
6 20
 
6.1%
1 20
 
6.1%
8 20
 
6.1%
) 18
 
5.5%
Other values (7) 62
18.8%
Hangul
ValueCountFrequency (%)
락 1
33.3%
처 1
33.3%
연 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing20
Missing (%)52.6%
Memory size436.0 B
2024-03-14T10:58:58.410055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19.5
Mean length16
Min length4

Characters and Unicode

Total characters288
Distinct characters28
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row홈페이지
2nd rowwww.childfund-jeonbuk.or.kr
3rd rowwww.bokzi.or.kr
4th rowwww.haksanc.or.kr
5th rowwww.welpeace.or.kr
ValueCountFrequency (%)
홈페이지 1
 
5.6%
www.childfund-jeonbuk.or.kr 1
 
5.6%
www.bokun.or.kr 1
 
5.6%
www.jeilwelfare.or.kr 1
 
5.6%
www.kjwelfare.or.kr 1
 
5.6%
www.kilbo.or.kr 1
 
5.6%
www.nswc.or.kr 1
 
5.6%
www.wvju.or.kr 1
 
5.6%
www.dsbokji.or.kr 1
 
5.6%
www.swb.or.kr 1
 
5.6%
Other values (8) 8
44.4%
2024-03-14T10:58:58.676238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 60
20.8%
. 51
17.7%
r 38
13.2%
k 25
8.7%
o 22
 
7.6%
e 11
 
3.8%
a 10
 
3.5%
n 10
 
3.5%
s 7
 
2.4%
b 7
 
2.4%
Other values (18) 47
16.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 232
80.6%
Other Punctuation 51
 
17.7%
Other Letter 4
 
1.4%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 60
25.9%
r 38
16.4%
k 25
10.8%
o 22
 
9.5%
e 11
 
4.7%
a 10
 
4.3%
n 10
 
4.3%
s 7
 
3.0%
b 7
 
3.0%
l 7
 
3.0%
Other values (12) 35
15.1%
Other Letter
ValueCountFrequency (%)
홈 1
25.0%
페 1
25.0%
지 1
25.0%
이 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 232
80.6%
Common 52
 
18.1%
Hangul 4
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 60
25.9%
r 38
16.4%
k 25
10.8%
o 22
 
9.5%
e 11
 
4.7%
a 10
 
4.3%
n 10
 
4.3%
s 7
 
3.0%
b 7
 
3.0%
l 7
 
3.0%
Other values (12) 35
15.1%
Hangul
ValueCountFrequency (%)
홈 1
25.0%
페 1
25.0%
지 1
25.0%
이 1
25.0%
Common
ValueCountFrequency (%)
. 51
98.1%
- 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 284
98.6%
Hangul 4
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 60
21.1%
. 51
18.0%
r 38
13.4%
k 25
8.8%
o 22
 
7.7%
e 11
 
3.9%
a 10
 
3.5%
n 10
 
3.5%
s 7
 
2.5%
b 7
 
2.5%
Other values (14) 43
15.1%
Hangul
ValueCountFrequency (%)
홈 1
25.0%
페 1
25.0%
지 1
25.0%
이 1
25.0%

Unnamed: 8
Text

MISSING 

Distinct12
Distinct (%)63.2%
Missing19
Missing (%)50.0%
Memory size436.0 B
2024-03-14T10:58:58.834260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length7.9473684
Min length4

Characters and Unicode

Total characters151
Distinct characters61
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

Unique10 ?
Unique (%)52.6%

Sample

1st row(2015년 7월 현재)
2nd row운영법인명
3rd row어린이재단
4th row삼 동 회
5th row한기장복지재단
ValueCountFrequency (%)
회 6
16.7%
삼 5
13.9%
동 5
13.9%
한기장복지재단 4
 
11.1%
월드비전 1
 
2.8%
대한불교조계종 1
 
2.8%
온 1
 
2.8%
시 1
 
2.8%
합동)유지재단 1
 
2.8%
대한예수교장로회총회 1
 
2.8%
Other values (10) 10
27.8%
2024-03-14T10:58:59.084368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
 
9.3%
회 13
 
8.6%
재 9
 
6.0%
지 8
 
5.3%
단 8
 
5.3%
한 7
 
4.6%
동 6
 
4.0%
복 6
 
4.0%
삼 5
 
3.3%
기 5
 
3.3%
Other values (51) 70
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
82.8%
Space Separator 14
 
9.3%
Decimal Number 5
 
3.3%
Control 3
 
2.0%
Open Punctuation 2
 
1.3%
Close Punctuation 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 13
 
10.4%
재 9
 
7.2%
지 8
 
6.4%
단 8
 
6.4%
한 7
 
5.6%
동 6
 
4.8%
복 6
 
4.8%
삼 5
 
4.0%
기 5
 
4.0%
장 5
 
4.0%
Other values (42) 53
42.4%
Decimal Number
ValueCountFrequency (%)
2 1
20.0%
0 1
20.0%
1 1
20.0%
5 1
20.0%
7 1
20.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
82.8%
Common 26
 
17.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 13
 
10.4%
재 9
 
7.2%
지 8
 
6.4%
단 8
 
6.4%
한 7
 
5.6%
동 6
 
4.8%
복 6
 
4.8%
삼 5
 
4.0%
기 5
 
4.0%
장 5
 
4.0%
Other values (42) 53
42.4%
Common
ValueCountFrequency (%)
14
53.8%
3
 
11.5%
( 2
 
7.7%
) 2
 
7.7%
2 1
 
3.8%
0 1
 
3.8%
1 1
 
3.8%
5 1
 
3.8%
7 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
82.8%
ASCII 26
 
17.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
53.8%
3
 
11.5%
( 2
 
7.7%
) 2
 
7.7%
2 1
 
3.8%
0 1
 
3.8%
1 1
 
3.8%
5 1
 
3.8%
7 1
 
3.8%
Hangul
ValueCountFrequency (%)
회 13
 
10.4%
재 9
 
7.2%
지 8
 
6.4%
단 8
 
6.4%
한 7
 
5.6%
동 6
 
4.8%
복 6
 
4.8%
삼 5
 
4.0%
기 5
 
4.0%
장 5
 
4.0%
Other values (42) 53
42.4%

Correlations

2024-03-14T10:58:59.174678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전라북도 사회복지관 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
전라북도 사회복지관 현황1.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 41.0001.0001.0001.0001.0001.0001.0001.0000.000
Unnamed: 51.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 61.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 71.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 81.0001.0001.0001.0000.0001.0001.0001.0001.000

Missing values

2024-03-14T10:58:54.579102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:58:54.679238image/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.
2024-03-14T10:58:54.783132image/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 사회복지관 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
0<NA><NA><NA><NA><NA><NA><NA><NA>(2015년 7월 현재)
1시군시설명소 재 지시설장종사개관일연락처 (FAX)홈페이지운영법인명
2<NA><NA><NA><NA>자수<NA><NA><NA><NA>
317개소<NA><NA><NA>167<NA><NA><NA><NA>
4전주전북종합사회복지관전주시 완산구 흑석로 70문정훈1188.12.27282-7230 (231-6397)www.childfund-jeonbuk.or.kr어린이재단
5<NA><NA><NA><NA><NA><NA><NA><NA><NA>
6<NA>전주종합사회복지관전주시 완산구 덕적골 2길 10정학성1092.12.28284-2733 (283-4423)www.bokzi.or.kr삼 동 회
7<NA><NA><NA><NA><NA><NA><NA><NA><NA>
8<NA>학산종합사회복지관전주시 완산구 모악로 4726-1노영웅1295.12.29223-9999 (226-9001)www.haksanc.or.kr한기장복지재단
9<NA><NA><NA><NA><NA><NA><NA><NA><NA>
전라북도 사회복지관 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
28김제길보른종합사회복지관김제시 금성로 93권영세1091.03.13545-1923 (546-1228)www.kilbo.or.kr길보경애원
29<NA><NA><NA><NA><NA><NA><NA><NA><NA>
30<NA>김제사회복지관김제시 요촌북로 110김준수794.12.23543-5007 (545-5009)www.kjwelfare.or.kr대한예수교장로회총회 (합동)유지재단
31<NA><NA><NA><NA><NA><NA><NA><NA><NA>
32<NA>김제제일사회복지관김제시 동서1길 9-24김희곤795.03.03547-0431 (545-0431)www.jeilwelfare.or.kr시 온 회
33<NA><NA><NA><NA><NA><NA><NA><NA><NA>
34고창고창종합사회복지관고창군 고창읍 전봉준로 88-15손형석907.11.29563-1111 (564-1334)www.bokun.or.kr대한불교조계종 사회복지재단
35<NA><NA><NA><NA><NA><NA><NA><NA><NA>
36부안부안종합사회복지관부안군 부안읍 용암로 134이춘섭706.02.23580-7600 (580-7601)www.buan.or.kr한기장복지재단
37<NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

전라북도 사회복지관 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA>17