Overview

Dataset statistics

Number of variables10
Number of observations166
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.4 KiB
Average record size in memory82.8 B

Variable types

Numeric1
Categorical6
Text3

Alerts

공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번High correlation
자료출처 is highly imbalanced (94.7%)Imbalance
시설명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:42:35.236944
Analysis finished2024-03-14 00:42:35.778376
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION 

Distinct165
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.554217
Minimum1
Maximum166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-03-14T09:42:35.832705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.25
Q142.25
median83.5
Q3124.75
95-th percentile157.75
Maximum166
Range165
Interquartile range (IQR)82.5

Descriptive statistics

Standard deviation47.996023
Coefficient of variation (CV)0.5744297
Kurtosis-1.1987154
Mean83.554217
Median Absolute Deviation (MAD)41.5
Skewness0.0019729528
Sum13870
Variance2303.6183
MonotonicityIncreasing
2024-03-14T09:42:35.932873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 2
 
1.2%
1 1
 
0.6%
116 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
112 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
115 1
 
0.6%
Other values (155) 155
93.4%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
166 1
0.6%
165 1
0.6%
164 1
0.6%
163 1
0.6%
162 1
0.6%
161 1
0.6%
160 1
0.6%
159 1
0.6%
158 1
0.6%
157 1
0.6%

시군명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
전주시
34 
익산시
28 
완주군
17 
군산시
16 
정읍시
15 
Other values (9)
56 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전주시
2nd row전주시
3rd row전주시
4th row전주시
5th row전주시

Common Values

ValueCountFrequency (%)
전주시 34
20.5%
익산시 28
16.9%
완주군 17
10.2%
군산시 16
9.6%
정읍시 15
9.0%
남원시 10
 
6.0%
김제시 9
 
5.4%
장수군 7
 
4.2%
부안군 6
 
3.6%
진안군 5
 
3.0%
Other values (4) 19
11.4%

Length

2024-03-14T09:42:36.028772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 34
20.5%
익산시 28
16.9%
완주군 17
10.2%
군산시 16
9.6%
정읍시 15
9.0%
남원시 10
 
6.0%
김제시 9
 
5.4%
장수군 7
 
4.2%
부안군 6
 
3.6%
진안군 5
 
3.0%
Other values (4) 19
11.4%

시설구분
Categorical

Distinct20
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
장애인거주시설
47 
장애인주간보호시설
26 
장애인보호작업장
18 
장애인 공동생활가정
18 
장애인수어통역센터
14 
Other values (15)
43 

Length

Max length16
Median length11
Mean length8.3493976
Min length5

Unique

Unique6 ?
Unique (%)3.6%

Sample

1st row장애인주간보호시설
2nd row점자도서관
3rd row생활이동지원센터
4th row생활이동지원센터
5th row장애인주간보호시설

Common Values

ValueCountFrequency (%)
장애인거주시설 47
28.3%
장애인주간보호시설 26
15.7%
장애인보호작업장 18
 
10.8%
장애인 공동생활가정 18
 
10.8%
장애인수어통역센터 14
 
8.4%
장애인복지관 13
 
7.8%
장애인생활이동지원센터 9
 
5.4%
장애인공동생활가정 3
 
1.8%
장애인근로사업장 2
 
1.2%
장애인 단기거주시설 2
 
1.2%
Other values (10) 14
 
8.4%

Length

2024-03-14T09:42:36.122275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장애인거주시설 47
25.3%
장애인주간보호시설 26
14.0%
장애인 20
10.8%
장애인보호작업장 18
 
9.7%
공동생활가정 18
 
9.7%
장애인수어통역센터 14
 
7.5%
장애인복지관 13
 
7.0%
장애인생활이동지원센터 9
 
4.8%
장애인공동생활가정 3
 
1.6%
점자도서관 2
 
1.1%
Other values (11) 16
 
8.6%

시설명
Text

UNIQUE 

Distinct166
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-14T09:42:36.316242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length8.2108434
Min length2

Characters and Unicode

Total characters1363
Distinct characters180
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

Unique166 ?
Unique (%)100.0%

Sample

1st row정다운주간보호센터
2nd row전라북도점자도서관
3rd row전북장애인생활이동지원센터
4th row전주장애인생활이동지원센터
5th row전북장애인부모회부설주간보호센터
ValueCountFrequency (%)
장애인복지관 12
 
5.8%
부설 8
 
3.8%
주간보호센터 7
 
3.4%
4
 
1.9%
주간보호시설 3
 
1.4%
희망해 2
 
1.0%
남원장애인복지관 2
 
1.0%
공동생활가정 2
 
1.0%
장수군 2
 
1.0%
나현네집 1
 
0.5%
Other values (165) 165
79.3%
2024-03-14T09:42:36.669523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
 
4.3%
51
 
3.7%
51
 
3.7%
47
 
3.4%
45
 
3.3%
43
 
3.2%
43
 
3.2%
42
 
3.1%
41
 
3.0%
37
 
2.7%
Other values (170) 904
66.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1311
96.2%
Space Separator 42
 
3.1%
Decimal Number 10
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
59
 
4.5%
51
 
3.9%
51
 
3.9%
47
 
3.6%
45
 
3.4%
43
 
3.3%
43
 
3.3%
41
 
3.1%
37
 
2.8%
34
 
2.6%
Other values (166) 860
65.6%
Decimal Number
ValueCountFrequency (%)
1 4
40.0%
2 4
40.0%
3 2
20.0%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1311
96.2%
Common 52
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
59
 
4.5%
51
 
3.9%
51
 
3.9%
47
 
3.6%
45
 
3.4%
43
 
3.3%
43
 
3.3%
41
 
3.1%
37
 
2.8%
34
 
2.6%
Other values (166) 860
65.6%
Common
ValueCountFrequency (%)
42
80.8%
1 4
 
7.7%
2 4
 
7.7%
3 2
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1311
96.2%
ASCII 52
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
59
 
4.5%
51
 
3.9%
51
 
3.9%
47
 
3.6%
45
 
3.4%
43
 
3.3%
43
 
3.3%
41
 
3.1%
37
 
2.8%
34
 
2.6%
Other values (166) 860
65.6%
ASCII
ValueCountFrequency (%)
42
80.8%
1 4
 
7.7%
2 4
 
7.7%
3 2
 
3.8%
Distinct128
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-14T09:42:36.886064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length19.036145
Min length13

Characters and Unicode

Total characters3160
Distinct characters192
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)59.0%

Sample

1st row전주시 덕진구 기린대로 549 (덕진동2가, 샬롬빌)
2nd row전주시 덕진구 학산길 26-3 (팔복동2가)
3rd row전주시 덕진구 학산길 26-3 (팔복동2가)
4th row전주시 완산구 매곡로 27-8 (동완산동)
5th row전주시 완산구 계룡산길 44-8 (삼천동2가)
ValueCountFrequency (%)
전주시 34
 
4.8%
익산시 28
 
3.9%
완산구 24
 
3.4%
완주군 17
 
2.4%
군산시 16
 
2.2%
정읍시 15
 
2.1%
덕진구 10
 
1.4%
남원시 10
 
1.4%
김제시 9
 
1.3%
장수군 7
 
1.0%
Other values (338) 544
76.2%
2024-03-14T09:42:37.280557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
548
 
17.3%
1 146
 
4.6%
112
 
3.5%
107
 
3.4%
95
 
3.0%
95
 
3.0%
2 92
 
2.9%
81
 
2.6%
( 80
 
2.5%
) 80
 
2.5%
Other values (182) 1724
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1788
56.6%
Decimal Number 584
 
18.5%
Space Separator 548
 
17.3%
Open Punctuation 80
 
2.5%
Close Punctuation 80
 
2.5%
Dash Punctuation 66
 
2.1%
Other Punctuation 13
 
0.4%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
112
 
6.3%
107
 
6.0%
95
 
5.3%
95
 
5.3%
81
 
4.5%
73
 
4.1%
67
 
3.7%
51
 
2.9%
45
 
2.5%
42
 
2.3%
Other values (166) 1020
57.0%
Decimal Number
ValueCountFrequency (%)
1 146
25.0%
2 92
15.8%
5 60
10.3%
3 54
 
9.2%
4 48
 
8.2%
7 47
 
8.0%
8 41
 
7.0%
6 37
 
6.3%
9 34
 
5.8%
0 25
 
4.3%
Space Separator
ValueCountFrequency (%)
548
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1788
56.6%
Common 1371
43.4%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
112
 
6.3%
107
 
6.0%
95
 
5.3%
95
 
5.3%
81
 
4.5%
73
 
4.1%
67
 
3.7%
51
 
2.9%
45
 
2.5%
42
 
2.3%
Other values (166) 1020
57.0%
Common
ValueCountFrequency (%)
548
40.0%
1 146
 
10.6%
2 92
 
6.7%
( 80
 
5.8%
) 80
 
5.8%
- 66
 
4.8%
5 60
 
4.4%
3 54
 
3.9%
4 48
 
3.5%
7 47
 
3.4%
Other values (5) 150
 
10.9%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1788
56.6%
ASCII 1372
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
548
39.9%
1 146
 
10.6%
2 92
 
6.7%
( 80
 
5.8%
) 80
 
5.8%
- 66
 
4.8%
5 60
 
4.4%
3 54
 
3.9%
4 48
 
3.5%
7 47
 
3.4%
Other values (6) 151
 
11.0%
Hangul
ValueCountFrequency (%)
112
 
6.3%
107
 
6.0%
95
 
5.3%
95
 
5.3%
81
 
4.5%
73
 
4.1%
67
 
3.7%
51
 
2.9%
45
 
2.5%
42
 
2.3%
Other values (166) 1020
57.0%
Distinct144
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-14T09:42:37.479971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length12.036145
Min length12

Characters and Unicode

Total characters1998
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)75.3%

Sample

1st row063-274-0095
2nd row063-288-0046
3rd row063-282-3880
4th row063-283-7651
5th row063-224-6678
ValueCountFrequency (%)
063-452-0911 4
 
2.4%
063-636-6204 3
 
1.8%
063-223-4935 2
 
1.2%
063-532-0700 2
 
1.2%
063-261-7801 2
 
1.2%
063-581-9260 2
 
1.2%
063-901-0625 2
 
1.2%
063-653-3245 2
 
1.2%
063-432-8871 2
 
1.2%
063-542-9500 2
 
1.2%
Other values (134) 143
86.1%
2024-03-14T09:42:37.779625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/