Overview

Dataset statistics

Number of variables5
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory47.0 B

Variable types

Numeric1
Text4

Alerts

연번 has unique valuesUnique
복지관명 has unique valuesUnique
주소 has unique valuesUnique
연락처 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:21:02.975053
Analysis finished2024-03-14 00:21:03.373748
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-03-14T09:21:03.435564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q16.25
median11.5
Q316.75
95-th percentile20.95
Maximum22
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.5646597
Kurtosis-1.2
Mean11.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum253
Variance42.166667
MonotonicityStrictly increasing
2024-03-14T09:21:03.545972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 1
 
4.5%
13 1
 
4.5%
22 1
 
4.5%
21 1
 
4.5%
20 1
 
4.5%
19 1
 
4.5%
18 1
 
4.5%
17 1
 
4.5%
16 1
 
4.5%
15 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1 1
4.5%
2 1
4.5%
3 1
4.5%
4 1
4.5%
5 1
4.5%
6 1
4.5%
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 1
4.5%
ValueCountFrequency (%)
22 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
18 1
4.5%
17 1
4.5%
16 1
4.5%
15 1
4.5%
14 1
4.5%
13 1
4.5%

복지관명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-03-14T09:21:03.721112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.5
Min length7

Characters and Unicode

Total characters187
Distinct characters49
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row전라북도노인복지관
2nd row안골노인복지관
3rd row금암노인복지관
4th row서원노인복지관
5th row덕진노인복지관
ValueCountFrequency (%)
전라북도노인복지관 1
 
4.3%
정읍시노인복지관 1
 
4.3%
노인복지관 1
 
4.3%
북부권 1
 
4.3%
임실군노인복지관 1
 
4.3%
노인․장애인복지관 1
 
4.3%
무주노인종합복지관 1
 
4.3%
진안군복합노인복지타운 1
 
4.3%
김제노인종합복지관 1
 
4.3%
남원시노인복지관 1
 
4.3%
Other values (13) 13
56.5%
2024-03-14T09:21:03.989568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 23
12.3%
복 23
12.3%
지 23
12.3%
노 22
11.8%
관 21
11.2%
합 7
 
3.7%
종 6
 
3.2%
시 4
 
2.1%
군 4
 
2.1%
북 3
 
1.6%
Other values (39) 51
27.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 185
98.9%
Other Punctuation 1
 
0.5%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 23
12.4%
복 23
12.4%
지 23
12.4%
노 22
11.9%
관 21
11.4%
합 7
 
3.8%
종 6
 
3.2%
시 4
 
2.2%
군 4
 
2.2%
북 3
 
1.6%
Other values (37) 49
26.5%
Other Punctuation
ValueCountFrequency (%)
․ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 185
98.9%
Common 2
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 23
12.4%
복 23
12.4%
지 23
12.4%
노 22
11.9%
관 21
11.4%
합 7
 
3.8%
종 6
 
3.2%
시 4
 
2.2%
군 4
 
2.2%
북 3
 
1.6%
Other values (37) 49
26.5%
Common
ValueCountFrequency (%)
․ 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 185
98.9%
Punctuation 1
 
0.5%
ASCII 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 23
12.4%
복 23
12.4%
지 23
12.4%
노 22
11.9%
관 21
11.4%
합 7
 
3.8%
종 6
 
3.2%
시 4
 
2.2%
군 4
 
2.2%
북 3
 
1.6%
Other values (37) 49
26.5%
Punctuation
ValueCountFrequency (%)
․ 1
100.0%
ASCII
ValueCountFrequency (%)
1
100.0%

운영주체
Text

Distinct16
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-03-14T09:21:04.155687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9
Min length6

Characters and Unicode

Total characters198
Distinct characters54
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

Unique12 ?
Unique (%)54.5%

Sample

1st row대한노인회 전북연합회
2nd row사복) 중부복지재단
3rd row사단) 나누는 사람들
4th row사복) 금산사복지원
5th row사단) 나누는 사람들
ValueCountFrequency (%)
사복)삼동회 4
 
11.1%
사복 4
 
11.1%
나누는 2
 
5.6%
사람들 2
 
5.6%
익산시 2
 
5.6%
직영 2
 
5.6%
사복)전주가톨릭사회복지회 2
 
5.6%
유지재단 2
 
5.6%
사단 2
 
5.6%
산학협력단 1
 
2.8%
Other values (13) 13
36.1%
2024-03-14T09:21:04.457340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 22
 
11.1%
복 20
 
10.1%
) 17
 
8.6%
15
 
7.6%
회 12
 
6.1%
단 12
 
6.1%
재 9
 
4.5%
지 8
 
4.0%
삼 6
 
3.0%
산 4
 
2.0%
Other values (44) 73
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166
83.8%
Close Punctuation 17
 
8.6%
Space Separator 15
 
7.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 22
 
13.3%
복 20
 
12.0%
회 12
 
7.2%
단 12
 
7.2%
재 9
 
5.4%
지 8
 
4.8%
삼 6
 
3.6%
산 4
 
2.4%
동 4
 
2.4%
대 4
 
2.4%
Other values (42) 65
39.2%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 166
83.8%
Common 32
 
16.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 22
 
13.3%
복 20
 
12.0%
회 12
 
7.2%
단 12
 
7.2%
재 9
 
5.4%
지 8
 
4.8%
삼 6
 
3.6%
산 4
 
2.4%
동 4
 
2.4%
대 4
 
2.4%
Other values (42) 65
39.2%
Common
ValueCountFrequency (%)
) 17
53.1%
15
46.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166
83.8%
ASCII 32
 
16.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 22
 
13.3%
복 20
 
12.0%
회 12
 
7.2%
단 12
 
7.2%
재 9
 
5.4%
지 8
 
4.8%
삼 6
 
3.6%
산 4
 
2.4%
동 4
 
2.4%
대 4
 
2.4%
Other values (42) 65
39.2%
ASCII
ValueCountFrequency (%)
) 17
53.1%
15
46.9%

주소
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-03-14T09:21:04.635140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length13.227273
Min length9

Characters and Unicode

Total characters291
Distinct characters83
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

Unique22 ?
Unique (%)100.0%

Sample

1st row전주시완산구 감나무4길29
2nd row전주시덕진구 안골1길 11
3rd row전주시덕진구 삼송5길 12
4th row전주시완산구 따박골5길 36
5th row전주시덕진구송천중앙로 36
ValueCountFrequency (%)
전주시완산구 4
 
7.1%
전주시덕진구 2
 
3.6%
36 2
 
3.6%
425 1
 
1.8%
남원시금동로 1
 
1.8%
50 1
 
1.8%
김제시 1
 
1.8%
하동1길 1
 
1.8%
79 1
 
1.8%
진안군진안읍 1
 
1.8%
Other values (41) 41
73.2%
2024-03-14T09:21:04.974450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34
 
11.7%
시 16
 
5.5%
1 14
 
4.8%
산 11
 
3.8%
길 11
 
3.8%
로 10
 
3.4%
2 10
 
3.4%
주 9
 
3.1%
읍 8
 
2.7%
군 8
 
2.7%
Other values (73) 160
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 189
64.9%
Decimal Number 65
 
22.3%
Space Separator 34
 
11.7%
Dash Punctuation 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 16
 
8.5%
산 11
 
5.8%
길 11
 
5.8%
로 10
 
5.3%
주 9
 
4.8%
읍 8
 
4.2%
군 8
 
4.2%
전 7
 
3.7%
구 7
 
3.7%
진 5
 
2.6%
Other values (61) 97
51.3%
Decimal Number
ValueCountFrequency (%)
1 14
21.5%
2 10
15.4%
4 8
12.3%
3 8
12.3%
5 8
12.3%
6 5
 
7.7%
7 4
 
6.2%
9 3
 
4.6%
0 3
 
4.6%
8 2
 
3.1%
Space Separator
ValueCountFrequency (%)
34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 189
64.9%
Common 102
35.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 16
 
8.5%
산 11
 
5.8%
길 11
 
5.8%
로 10
 
5.3%
주 9
 
4.8%
읍 8
 
4.2%
군 8
 
4.2%
전 7
 
3.7%
구 7
 
3.7%
진 5
 
2.6%
Other values (61) 97
51.3%
Common
ValueCountFrequency (%)
34
33.3%
1 14
13.7%
2 10
 
9.8%
4 8
 
7.8%
3 8
 
7.8%
5 8
 
7.8%
6 5
 
4.9%
7 4
 
3.9%
- 3
 
2.9%
9 3
 
2.9%
Other values (2) 5
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 189
64.9%
ASCII 102
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34
33.3%
1 14
13.7%
2 10
 
9.8%
4 8
 
7.8%
3 8
 
7.8%
5 8
 
7.8%
6 5
 
4.9%
7 4
 
3.9%
- 3
 
2.9%
9 3
 
2.9%
Other values (2) 5
 
4.9%
Hangul
ValueCountFrequency (%)
시 16
 
8.5%
산 11
 
5.8%
길 11
 
5.8%
로 10
 
5.3%
주 9
 
4.8%
읍 8
 
4.2%
군 8
 
4.2%
전 7
 
3.7%
구 7
 
3.7%
진 5
 
2.6%
Other values (61) 97
51.3%

연락처
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-03-14T09:21:05.140930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters176
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row276-2086
2nd row243-4377
3rd row253-5728
4th row227-7481
5th row271-9336
ValueCountFrequency (%)
276-2086 1
 
4.5%
243-4377 1
 
4.5%
642-3844 1
 
4.5%
644-4438 1
 
4.5%
353-8286 1
 
4.5%
322-1252 1
 
4.5%
430-2747 1
 
4.5%
542-5550 1
 
4.5%
625-9988 1
 
4.5%
571-9051 1
 
4.5%
Other values (12) 12
54.5%
2024-03-14T09:21:05.411199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 27
15.3%
- 22
12.5%
4 19
10.8%
3 19
10.8%
7 18
10.2%
0 16
9.1%
5 15
8.5%
8 13
7.4%
6 10
 
5.7%
9 10
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 154
87.5%
Dash Punctuation 22
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 27
17.5%
4 19
12.3%
3 19
12.3%
7 18
11.7%
0 16
10.4%
5 15
9.7%
8 13
8.4%
6 10
 
6.5%
9 10
 
6.5%
1 7
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 176
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 27
15.3%
- 22
12.5%
4 19
10.8%
3 19
10.8%
7 18
10.2%
0 16
9.1%
5 15
8.5%
8 13
7.4%
6 10
 
5.7%
9 10
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 176
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 27
15.3%
- 22
12.5%
4 19
10.8%
3 19
10.8%
7 18
10.2%
0 16
9.1%
5 15
8.5%
8 13
7.4%
6 10
 
5.7%
9 10
 
5.7%

Interactions

2024-03-14T09:21:03.182847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:21:05.486697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번복지관명운영주체주소연락처
연번1.0001.0000.6921.0001.000
복지관명1.0001.0001.0001.0001.000
운영주체0.6921.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.000

Missing values

2024-03-14T09:21:03.276975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:21:03.345473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번복지관명운영주체주소연락처
01전라북도노인복지관대한노인회 전북연합회전주시완산구 감나무4길29276-2086
12안골노인복지관사복) 중부복지재단전주시덕진구 안골1길 11243-4377
23금암노인복지관사단) 나누는 사람들전주시덕진구 삼송5길 12253-5728
34서원노인복지관사복) 금산사복지원전주시완산구 따박골5길 36227-7481
45덕진노인복지관사단) 나누는 사람들전주시덕진구송천중앙로 36271-9336
56양지노인복지관사복) 삼육재단전주시완산구 성지산로 55232-1000
67꽃밭정이노인복지관사복)이랜드전주시완산구 평화14길 27-53237-0770
78군산노인종합복지관사복)삼동회군산시둔배미길 29442-4227
89금강노인복지관군장대학교 산학협력단군산시백릉로 245442-0012
910익산시노인종합복지관사복) 신광복지재단익산시동서로 103837-7722
연번복지관명운영주체주소연락처
1213정읍시노인복지관사복)삼육재단정읍시금붕1길 211538-3606
1314정읍시북부노인복지관재단)대한성공회 유지재단정읍시신태인읍신태인중앙로40571-9051
1415남원시노인복지관사복)전주가톨릭사회복지회남원시금동로 50625-9988
1516김제노인종합복지관대한성공회 유지재단김제시 하동1길 79542-5550
1617진안군복합노인복지타운사복)전주가톨릭사회복지회진안군진안읍 마이산로 76430-2747
1718무주노인종합복지관사복)삼동회무주군무주읍 한풍루로 425322-1252
1819노인․장애인복지관사복)자광재단장수군장수읍 노하3길 16353-8286
1920임실군노인복지관사복)삼동회임실군임실읍운수로 33-46644-4438
2021북부권 노인복지관사복)삼동회임실군관촌면 사선1길 24642-3844
2122고창군노인복지관사복)선운사복지재단고창군고창읍 율계리 114-2563-0009