Overview

Dataset statistics

Number of variables6
Number of observations21
Missing cells19
Missing cells (%)15.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory55.3 B

Variable types

Text5
Numeric1

Dataset

Description목포시에서 관할 장애인복지시설에 대한 현황에 대하여 시설명,소재지,전화번호,종사원,시설유형에 대한 현황을 제공하고 있습니다.
Author전라남도 목포시
URLhttps://www.data.go.kr/data/3039917/fileData.do

Alerts

비고 has constant value ""Constant
비고 has 19 (90.5%) missing valuesMissing
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:50:46.551834
Analysis finished2023-12-12 19:50:47.076112
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T04:50:47.265508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length7.4285714
Min length3

Characters and Unicode

Total characters156
Distinct characters60
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

Unique21 ?
Unique (%)100.0%

Sample

1st row광명원
2nd row공생재활원
3rd row목포장애인요양원
4th row소망장애인복지원
5th row보담하우스
ValueCountFrequency (%)
원 2
 
7.7%
광명원 1
 
3.8%
명도단기보호센터 1
 
3.8%
명도복지관일신그룹홈 1
 
3.8%
성산정신요양원 1
 
3.8%
명 1
 
3.8%
동 1
 
3.8%
성 1
 
3.8%
진 1
 
3.8%
소망자립센터 1
 
3.8%
Other values (15) 15
57.7%
2023-12-13T04:50:47.744017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 9
 
5.8%
명 7
 
4.5%
터 7
 
4.5%
센 7
 
4.5%
성 5
 
3.2%
지 5
 
3.2%
도 5
 
3.2%
5
 
3.2%
인 4
 
2.6%
복 4
 
2.6%
Other values (50) 98
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151
96.8%
Space Separator 5
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 9
 
6.0%
명 7
 
4.6%
터 7
 
4.6%
센 7
 
4.6%
성 5
 
3.3%
지 5
 
3.3%
도 5
 
3.3%
인 4
 
2.6%
복 4
 
2.6%
장 4
 
2.6%
Other values (49) 94
62.3%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151
96.8%
Common 5
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 9
 
6.0%
명 7
 
4.6%
터 7
 
4.6%
센 7
 
4.6%
성 5
 
3.3%
지 5
 
3.3%
도 5
 
3.3%
인 4
 
2.6%
복 4
 
2.6%
장 4
 
2.6%
Other values (49) 94
62.3%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151
96.8%
ASCII 5
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 9
 
6.0%
명 7
 
4.6%
터 7
 
4.6%
센 7
 
4.6%
성 5
 
3.3%
지 5
 
3.3%
도 5
 
3.3%
인 4
 
2.6%
복 4
 
2.6%
장 4
 
2.6%
Other values (49) 94
62.3%
ASCII
ValueCountFrequency (%)
5
100.0%

소재지
Text

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T04:50:48.004722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length23
Mean length20.52381
Min length15

Characters and Unicode

Total characters431
Distinct characters57
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

Unique17 ?
Unique (%)81.0%

Sample

1st row전남 영암군 삼호읍 신호정길 43-17
2nd row전라남도 목포시 대양로 14-24
3rd row전라남도 무안군 청계면 문화리 339-5
4th row전라남도 목포시 대양산단로199번길 93-36
5th row전라남도 목포시 대양산단로199번길 93-46
ValueCountFrequency (%)
전라남도 19
21.3%
목포시 16
18.0%
무안군 4
 
4.5%
25 3
 
3.4%
대양산단로199번길 3
 
3.4%
대양로 2
 
2.2%
청계면 2
 
2.2%
전남 2
 
2.2%
유교길101 2
 
2.2%
삼향읍 2
 
2.2%
Other values (33) 34
38.2%
2023-12-13T04:50:48.411645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
68
 
15.8%
1 23
 
5.3%
전 21
 
4.9%
남 21
 
4.9%
9 19
 
4.4%
도 19
 
4.4%
라 19
 
4.4%
목 16
 
3.7%
포 16
 
3.7%
시 16
 
3.7%
Other values (47) 193
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 255
59.2%
Decimal Number 97
 
22.5%
Space Separator 68
 
15.8%
Dash Punctuation 10
 
2.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 21
 
8.2%
남 21
 
8.2%
도 19
 
7.5%
라 19
 
7.5%
목 16
 
6.3%
포 16
 
6.3%
시 16
 
6.3%
길 15
 
5.9%
로 15
 
5.9%
번 10
 
3.9%
Other values (35) 87
34.1%
Decimal Number
ValueCountFrequency (%)
1 23
23.7%
9 19
19.6%
3 15
15.5%
2 12
12.4%
6 8
 
8.2%
4 6
 
6.2%
5 6
 
6.2%
0 5
 
5.2%
7 3
 
3.1%
Space Separator
ValueCountFrequency (%)
68
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 255
59.2%
Common 176
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 21
 
8.2%
남 21
 
8.2%
도 19
 
7.5%
라 19
 
7.5%
목 16
 
6.3%
포 16
 
6.3%
시 16
 
6.3%
길 15
 
5.9%
로 15
 
5.9%
번 10
 
3.9%
Other values (35) 87
34.1%
Common
ValueCountFrequency (%)
68
38.6%
1 23
 
13.1%
9 19
 
10.8%
3 15
 
8.5%
2 12
 
6.8%
- 10
 
5.7%
6 8
 
4.5%
4 6
 
3.4%
5 6
 
3.4%
0 5
 
2.8%
Other values (2) 4
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 255
59.2%
ASCII 176
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
68
38.6%
1 23
 
13.1%
9 19
 
10.8%
3 15
 
8.5%
2 12
 
6.8%
- 10
 
5.7%
6 8
 
4.5%
4 6
 
3.4%
5 6
 
3.4%
0 5
 
2.8%
Other values (2) 4
 
2.3%
Hangul
ValueCountFrequency (%)
전 21
 
8.2%
남 21
 
8.2%
도 19
 
7.5%
라 19
 
7.5%
목 16
 
6.3%
포 16
 
6.3%
시 16
 
6.3%
길 15
 
5.9%
로 15
 
5.9%
번 10
 
3.9%
Other values (35) 87
34.1%

전화번호
Text

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T04:50:48.645839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.047619
Min length12

Characters and Unicode

Total characters253
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

Unique18 ?
Unique (%)85.7%

Sample

1st row061-462-7356
2nd row061-246-2036
3rd row061-453-3726
4th row061-273-0780
5th row061-802-2711
ValueCountFrequency (%)
061-279-4879 3
 
14.3%
061-462-7356 1
 
4.8%
061-284-2879 1
 
4.8%
061-272-2335 1
 
4.8%
061-280-6530 1
 
4.8%
061-452-5514 1
 
4.8%
061-280-6510 1
 
4.8%
061-278-7222 1
 
4.8%
061-284-4879 1
 
4.8%
061-246-2400 1
 
4.8%
Other values (9) 9
42.9%
2023-12-13T04:50:49.026865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 42
16.6%
0 35
13.8%
2 35
13.8%
6 29
11.5%
1 29
11.5%
8 18
7.1%
7 17
6.7%
5 15
 
5.9%
4 14
 
5.5%
9 11
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 211
83.4%
Dash Punctuation 42
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35
16.6%
2 35
16.6%
6 29
13.7%
1 29
13.7%
8 18
8.5%
7 17
8.1%
5 15
7.1%
4 14
 
6.6%
9 11
 
5.2%
3 8
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 253
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 42
16.6%
0 35
13.8%
2 35
13.8%
6 29
11.5%
1 29
11.5%
8 18
7.1%
7 17
6.7%
5 15
 
5.9%
4 14
 
5.5%
9 11
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 42
16.6%
0 35
13.8%
2 35
13.8%
6 29
11.5%
1 29
11.5%
8 18
7.1%
7 17
6.7%
5 15
 
5.9%
4 14
 
5.5%
9 11
 
4.3%

종사원
Real number (ℝ)

Distinct16
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.428571
Minimum1
Maximum58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T04:50:49.192547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median7
Q329
95-th percentile54
Maximum58
Range57
Interquartile range (IQR)24

Descriptive statistics

Standard deviation19.627968
Coefficient of variation (CV)1.0102631
Kurtosis-0.7293519
Mean19.428571
Median Absolute Deviation (MAD)6
Skewness0.89781614
Sum408
Variance385.25714
MonotonicityNot monotonic
2023-12-13T04:50:49.371035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
5 5
23.8%
1 2
 
9.5%
7 1
 
4.8%
58 1
 
4.8%
12 1
 
4.8%
27 1
 
4.8%
3 1
 
4.8%
4 1
 
4.8%
54 1
 
4.8%
49 1
 
4.8%
Other values (6) 6
28.6%
ValueCountFrequency (%)
1 2
 
9.5%
3 1
 
4.8%
4 1
 
4.8%
5 5
23.8%
6 1
 
4.8%
7 1
 
4.8%
12 1
 
4.8%
18 1
 
4.8%
24 1
 
4.8%
27 1
 
4.8%
ValueCountFrequency (%)
58 1
4.8%
54 1
4.8%
50 1
4.8%
49 1
4.8%
40 1
4.8%
29 1
4.8%
27 1
4.8%
24 1
4.8%
18 1
4.8%
12 1
4.8%

시설유형
Text

Distinct16
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T04:50:49.638512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length9.7142857
Min length7

Characters and Unicode

Total characters204
Distinct characters40
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

Unique12 ?
Unique (%)57.1%

Sample

1st row시각, 지적 장애인 거주시설
2nd row지적장애인 거주시설
3rd row중증장애인 거주시설
4th row지체장애인거주시설
5th row중증장애인 거주시설
ValueCountFrequency (%)
거주시설 4
13.3%
장애인주간보호시설 3
 
10.0%
지역사회재활시설 3
 
10.0%
장애인 3
 
10.0%
장애인공동생활가정 2
 
6.7%
중증장애인 2
 
6.7%
직업재활시설 1
 
3.3%
시설 1
 
3.3%
노숙인재활 1
 
3.3%
노숙인재활시설 1
 
3.3%
Other values (9) 9
30.0%
2023-12-13T04:50:50.087502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 20
 
9.8%
설 19
 
9.3%
인 18
 
8.8%
장 17
 
8.3%
애 16
 
7.8%
활 11
 
5.4%
10
 
4.9%
재 9
 
4.4%
주 8
 
3.9%
지 7
 
3.4%
Other values (30) 69
33.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191
93.6%
Space Separator 10
 
4.9%
Other Punctuation 1
 
0.5%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 20
 
10.5%
설 19
 
9.9%
인 18
 
9.4%
장 17
 
8.9%
애 16
 
8.4%
활 11
 
5.8%
재 9
 
4.7%
주 8
 
4.2%
지 7
 
3.7%
호 5
 
2.6%
Other values (26) 61
31.9%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 191
93.6%
Common 13
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 20
 
10.5%
설 19
 
9.9%
인 18
 
9.4%
장 17
 
8.9%
애 16
 
8.4%
활 11
 
5.8%
재 9
 
4.7%
주 8
 
4.2%
지 7
 
3.7%
호 5
 
2.6%
Other values (26) 61
31.9%
Common
ValueCountFrequency (%)
10
76.9%
, 1
 
7.7%
( 1
 
7.7%
) 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191
93.6%
ASCII 13
 
6.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 20
 
10.5%
설 19
 
9.9%
인 18
 
9.4%
장 17
 
8.9%
애 16
 
8.4%
활 11
 
5.8%
재 9
 
4.7%
주 8
 
4.2%
지 7
 
3.7%
호 5
 
2.6%
Other values (26) 61
31.9%
ASCII
ValueCountFrequency (%)
10
76.9%
, 1
 
7.7%
( 1
 
7.7%
) 1
 
7.7%

비고
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing19
Missing (%)90.5%
Memory size300.0 B
2023-12-13T04:50:50.245936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters10
Distinct characters5
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

Unique0 ?
Unique (%)0.0%

Sample

1st row사회복지과
2nd row사회복지과
ValueCountFrequency (%)
사회복지과 2
100.0%
2023-12-13T04:50:50.629630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 2
20.0%
회 2
20.0%
복 2
20.0%
지 2
20.0%
과 2
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 2
20.0%
회 2
20.0%
복 2
20.0%
지 2
20.0%
과 2
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 2
20.0%
회 2
20.0%
복 2
20.0%
지 2
20.0%
과 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 2
20.0%
회 2
20.0%
복 2
20.0%
지 2
20.0%
과 2
20.0%

Interactions

2023-12-13T04:50:46.783941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:50:50.768140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명소재지전화번호종사원시설유형
시설명1.0001.0001.0001.0001.000
소재지1.0001.0000.9920.9120.854
전화번호1.0000.9921.0000.6750.936
종사원1.0000.9120.6751.0000.702
시설유형1.0000.8540.9360.7021.000

Missing values

2023-12-13T04:50:46.895372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:50:47.027029image/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

시설명소재지전화번호종사원시설유형비고
0광명원전남 영암군 삼호읍 신호정길 43-17061-462-735654시각, 지적 장애인 거주시설<NA>
1공생재활원전라남도 목포시 대양로 14-24061-246-203649지적장애인 거주시설<NA>
2목포장애인요양원전라남도 무안군 청계면 문화리 339-5061-453-372650중증장애인 거주시설<NA>
3소망장애인복지원전라남도 목포시 대양산단로199번길 93-36061-273-078029지체장애인거주시설<NA>
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