Overview

Dataset statistics

Number of variables13
Number of observations54
Missing cells24
Missing cells (%)3.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory111.4 B

Variable types

Text3
Categorical3
Numeric5
DateTime2

Dataset

Description경상남도 양산시 사회복지 시설 현황에 대한 데이터로 시설명, 종류, 목적, 정원, 현원, 종사자, 소재지, 전화번호, 설립일자 등의 항목을 제공합니다.
Author경상남도 양산시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15074075

Alerts

출처 has constant value ""Constant
데이터기준일자 has constant value ""Constant
정원 is highly overall correlated with 현원 and 2 other fieldsHigh correlation
현원 is highly overall correlated with 정원 and 1 other fieldsHigh correlation
종사자 is highly overall correlated with 정원 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
종류 is highly overall correlated with 정원 and 1 other fieldsHigh correlation
목적 is highly overall correlated with 종류High correlation
정원 has 16 (29.6%) missing valuesMissing
현원 has 8 (14.8%) missing valuesMissing
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:00:16.209533
Analysis finished2023-12-11 00:00:19.402746
Duration3.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-11T09:00:19.540818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11.5
Mean length8.5740741
Min length2

Characters and Unicode

Total characters463
Distinct characters125
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

Unique54 ?
Unique (%)100.0%

Sample

1st row무궁애학원
2nd row가온들찬빛
3rd row새힘
4th row예은의집
5th row늘푸른집
ValueCountFrequency (%)
감사의집 2
 
3.3%
주간보호센터 2
 
3.3%
무궁애학원 1
 
1.7%
양산재가노인복지센터 1
 
1.7%
통도사자비원전문요양시설 1
 
1.7%
양산노인실비요양원 1
 
1.7%
원정전문요양원 1
 
1.7%
한마음요양원 1
 
1.7%
보금자리요양원 1
 
1.7%
성모요양의집 1
 
1.7%
Other values (48) 48
80.0%
2023-12-11T09:00:19.880641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 25
 
5.4%
터 24
 
5.2%
센 23
 
5.0%
원 17
 
3.7%
인 15
 
3.2%
지 14
 
3.0%
시 13
 
2.8%
복 13
 
2.8%
산 12
 
2.6%
요 11
 
2.4%
Other values (115) 296
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 455
98.3%
Space Separator 6
 
1.3%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 25
 
5.5%
터 24
 
5.3%
센 23
 
5.1%
원 17
 
3.7%
인 15
 
3.3%
지 14
 
3.1%
시 13
 
2.9%
복 13
 
2.9%
산 12
 
2.6%
요 11
 
2.4%
Other values (112) 288
63.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 455
98.3%
Common 8
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 25
 
5.5%
터 24
 
5.3%
센 23
 
5.1%
원 17
 
3.7%
인 15
 
3.3%
지 14
 
3.1%
시 13
 
2.9%
복 13
 
2.9%
산 12
 
2.6%
요 11
 
2.4%
Other values (112) 288
63.3%
Common
ValueCountFrequency (%)
6
75.0%
) 1
 
12.5%
( 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 455
98.3%
ASCII 8
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 25
 
5.5%
터 24
 
5.3%
센 23
 
5.1%
원 17
 
3.7%
인 15
 
3.3%
지 14
 
3.1%
시 13
 
2.9%
복 13
 
2.9%
산 12
 
2.6%
요 11
 
2.4%
Other values (112) 288
63.3%
ASCII
ValueCountFrequency (%)
6
75.0%
) 1
 
12.5%
( 1
 
12.5%

종류
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Memory size564.0 B
재가노인복지시설
14 
노인주거복지시설
12 
장애인지역사회재활시설
10 
장애인직업재활시설(장애인보호작업장)
5 
지적장애인시설
2 
Other values (8)
11 

Length

Max length19
Median length11
Mean length9.3518519
Min length5

Unique

Unique5 ?
Unique (%)9.3%

Sample

1st row지적장애인시설
2nd row지적장애인시설
3rd row장애인단기거주시설
4th row장애인공동생활가정
5th row중증장애인요양시설

Common Values

ValueCountFrequency (%)
재가노인복지시설 14
25.9%
노인주거복지시설 12
22.2%
장애인지역사회재활시설 10
18.5%
장애인직업재활시설(장애인보호작업장) 5
 
9.3%
지적장애인시설 2
 
3.7%
사회복지관 2
 
3.7%
노인복지관 2
 
3.7%
노인일자리지원기관 2
 
3.7%
장애인단기거주시설 1
 
1.9%
장애인공동생활가정 1
 
1.9%
Other values (3) 3
 
5.6%

Length

2023-12-11T09:00:20.038162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재가노인복지시설 14
25.9%
노인주거복지시설 12
22.2%
장애인지역사회재활시설 10
18.5%
장애인직업재활시설(장애인보호작업장 5
 
9.3%
지적장애인시설 2
 
3.7%
사회복지관 2
 
3.7%
노인복지관 2
 
3.7%
노인일자리지원기관 2
 
3.7%
장애인단기거주시설 1
 
1.9%
장애인공동생활가정 1
 
1.9%
Other values (3) 3
 
5.6%

목적
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
이용시설
34 
생활시설
16 
생활시설(부산시법인)
 
3
이용시설(부산시법인)
 
1

Length

Max length11
Median length4
Mean length4.5185185
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row생활시설
2nd row생활시설(부산시법인)
3rd row생활시설
4th row생활시설
5th row생활시설

Common Values

ValueCountFrequency (%)
이용시설 34
63.0%
생활시설 16
29.6%
생활시설(부산시법인) 3
 
5.6%
이용시설(부산시법인) 1
 
1.9%

Length

2023-12-11T09:00:20.179951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:00:20.298527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용시설 34
63.0%
생활시설 16
29.6%
생활시설(부산시법인 3
 
5.6%
이용시설(부산시법인 1
 
1.9%

정원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct28
Distinct (%)73.7%
Missing16
Missing (%)29.6%
Infinite0
Infinite (%)0.0%
Mean36.368421
Minimum1
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T09:00:20.426129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.7
Q110
median29.5
Q348.5
95-th percentile91.65
Maximum150
Range149
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation31.33638
Coefficient of variation (CV)0.86163707
Kurtosis3.5931084
Mean36.368421
Median Absolute Deviation (MAD)19.5
Skewness1.6689719
Sum1382
Variance981.96871
MonotonicityNot monotonic
2023-12-11T09:00:20.574621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
9 4
 
7.4%
10 3
 
5.6%
30 3
 
5.6%
8 2
 
3.7%
50 2
 
3.7%
29 2
 
3.7%
52 1
 
1.9%
1 1
 
1.9%
35 1
 
1.9%
26 1
 
1.9%
Other values (18) 18
33.3%
(Missing) 16
29.6%
ValueCountFrequency (%)
1 1
 
1.9%
6 1
 
1.9%
8 2
3.7%
9 4
7.4%
10 3
5.6%
14 1
 
1.9%
15 1
 
1.9%
20 1
 
1.9%
24 1
 
1.9%
25 1
 
1.9%
ValueCountFrequency (%)
150 1
1.9%
101 1
1.9%
90 1
1.9%
80 1
1.9%
74 1
1.9%
72 1
1.9%
52 1
1.9%
50 2
3.7%
49 1
1.9%
47 1
1.9%

현원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct35
Distinct (%)76.1%
Missing8
Missing (%)14.8%
Infinite0
Infinite (%)0.0%
Mean255.6087
Minimum3
Maximum5021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T09:00:20.696751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4.25
Q110
median27
Q365.75
95-th percentile593.25
Maximum5021
Range5018
Interquartile range (IQR)55.75

Descriptive statistics

Standard deviation917.81871
Coefficient of variation (CV)3.5907178
Kurtosis21.174617
Mean255.6087
Median Absolute Deviation (MAD)18.5
Skewness4.6267641
Sum11758
Variance842391.18
MonotonicityNot monotonic
2023-12-11T09:00:20.819100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
8 4
 
7.4%
10 3
 
5.6%
9 2
 
3.7%
39 2
 
3.7%
12 2
 
3.7%
28 2
 
3.7%
30 2
 
3.7%
3 2
 
3.7%
87 1
 
1.9%
21 1
 
1.9%
Other values (25) 25
46.3%
(Missing) 8
 
14.8%
ValueCountFrequency (%)
3 2
3.7%
4 1
 
1.9%
5 1
 
1.9%
7 1
 
1.9%
8 4
7.4%
9 2
3.7%
10 3
5.6%
11 1
 
1.9%
12 2
3.7%
15 1
 
1.9%
ValueCountFrequency (%)
5021 1
1.9%
3843 1
1.9%
600 1
1.9%
573 1
1.9%
400 1
1.9%
151 1
1.9%
106 1
1.9%
88 1
1.9%
87 1
1.9%
80 1
1.9%

종사자
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.925926
Minimum2
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T09:00:20.939499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.65
Q14
median7.5
Q315.75
95-th percentile47
Maximum69
Range67
Interquartile range (IQR)11.75

Descriptive statistics

Standard deviation15.178003
Coefficient of variation (CV)1.0899098
Kurtosis3.1006296
Mean13.925926
Median Absolute Deviation (MAD)3.5
Skewness1.8917868
Sum752
Variance230.37177
MonotonicityNot monotonic
2023-12-11T09:00:21.061100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
4 10
18.5%
5 6
 
11.1%
11 4
 
7.4%
3 3
 
5.6%
2 3
 
5.6%
9 3
 
5.6%
7 3
 
5.6%
16 2
 
3.7%
8 2
 
3.7%
12 2
 
3.7%
Other values (13) 16
29.6%
ValueCountFrequency (%)
2 3
 
5.6%
3 3
 
5.6%
4 10
18.5%
5 6
11.1%
6 2
 
3.7%
7 3
 
5.6%
8 2
 
3.7%
9 3
 
5.6%
11 4
 
7.4%
12 2
 
3.7%
ValueCountFrequency (%)
69 1
1.9%
51 1
1.9%
47 2
3.7%
46 1
1.9%
43 1
1.9%
34 1
1.9%
28 1
1.9%
27 1
1.9%
25 1
1.9%
23 1
1.9%

소재지
Text

Distinct46
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-11T09:00:21.309080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length18.425926
Min length15

Characters and Unicode

Total characters995
Distinct characters66
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

Unique41 ?
Unique (%)75.9%

Sample

1st row경상남도 양산시 물금읍 청룡로 69
2nd row경상남도 양산시 신명3길 125
3rd row경상남도 양산시 물금읍 화산1길 6
4th row경상남도 양산시 신명로 73
5th row경상남도 양산시 상북면 수서로 349-94
ValueCountFrequency (%)
경상남도 54
22.9%
양산시 54
22.9%
물금읍 8
 
3.4%
하북면 8
 
3.4%
북안남5길 6
 
2.5%
15 5
 
2.1%
양산대로 4
 
1.7%
월평1길 4
 
1.7%
덕계7길 3
 
1.3%
상북면 3
 
1.3%
Other values (70) 87
36.9%
2023-12-11T09:00:22.165722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
191
19.2%
남 65
 
6.5%
산 61
 
6.1%
양 59
 
5.9%
상 59
 
5.9%
경 54
 
5.4%
도 54
 
5.4%
시 54
 
5.4%
길 36
 
3.6%
1 36
 
3.6%
Other values (56) 326
32.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 627
63.0%
Space Separator 191
 
19.2%
Decimal Number 166
 
16.7%
Dash Punctuation 11
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 65
10.4%
산 61
9.7%
양 59
9.4%
상 59
9.4%
경 54
 
8.6%
도 54
 
8.6%
시 54
 
8.6%
길 36
 
5.7%
북 22
 
3.5%
로 18
 
2.9%
Other values (44) 145
23.1%
Decimal Number
ValueCountFrequency (%)
1 36
21.7%
5 24
14.5%
2 22
13.3%
7 19
11.4%
6 14
 
8.4%
8 14
 
8.4%
3 13
 
7.8%
4 9
 
5.4%
0 8
 
4.8%
9 7
 
4.2%
Space Separator
ValueCountFrequency (%)
191
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 627
63.0%
Common 368
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 65
10.4%
산 61
9.7%
양 59
9.4%
상 59
9.4%
경 54
 
8.6%
도 54
 
8.6%
시 54
 
8.6%
길 36
 
5.7%
북 22
 
3.5%
로 18
 
2.9%
Other values (44) 145
23.1%
Common
ValueCountFrequency (%)
191
51.9%
1 36
 
9.8%
5 24
 
6.5%
2 22
 
6.0%
7 19
 
5.2%
6 14
 
3.8%
8 14
 
3.8%
3 13
 
3.5%
- 11
 
3.0%
4 9
 
2.4%
Other values (2) 15
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 627
63.0%
ASCII 368
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
191
51.9%
1 36
 
9.8%
5 24
 
6.5%
2 22
 
6.0%
7 19
 
5.2%
6 14
 
3.8%
8 14
 
3.8%
3 13
 
3.5%
- 11
 
3.0%
4 9
 
2.4%
Other values (2) 15
 
4.1%
Hangul
ValueCountFrequency (%)
남 65
10.4%
산 61
9.7%
양 59
9.4%
상 59
9.4%
경 54
 
8.6%
도 54
 
8.6%
시 54
 
8.6%
길 36
 
5.7%
북 22
 
3.5%
로 18
 
2.9%
Other values (44) 145
23.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.379607
Minimum35.310925
Maximum35.496022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T09:00:22.345014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.310925
5-th percentile35.328317
Q135.34442
median35.368678
Q335.405118
95-th percentile35.495496
Maximum35.496022
Range0.185097
Interquartile range (IQR)0.060698

Descriptive statistics

Standard deviation0.05071197
Coefficient of variation (CV)0.0014333673
Kurtosis0.14949612
Mean35.379607
Median Absolute Deviation (MAD)0.027477
Skewness1.0486709
Sum1910.4988
Variance0.0025717039
MonotonicityNot monotonic
2023-12-11T09:00:22.536348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
35.345788 5
 
9.3%
35.374642 3
 
5.6%
35.328796 2
 
3.7%
35.43059 2
 
3.7%
35.496022 2
 
3.7%
35.349527 2
 
3.7%
35.335837 2
 
3.7%
35.453566 1
 
1.9%
35.495344 1
 
1.9%
35.347359 1
 
1.9%
Other values (33) 33
61.1%
ValueCountFrequency (%)
35.310925 1
1.9%
35.327188 1
1.9%
35.328312 1
1.9%
35.32832 1
1.9%
35.328796 2
3.7%
35.331604 1
1.9%
35.335694 1
1.9%
35.335837 2
3.7%
35.340709 1
1.9%
35.341693 1
1.9%
ValueCountFrequency (%)
35.496022 2
3.7%
35.495779 1
1.9%
35.495344 1
1.9%
35.484262 1
1.9%
35.45437 1
1.9%
35.453566 1
1.9%
35.440818 1
1.9%
35.43059 2
3.7%
35.425548 1
1.9%
35.417878 1
1.9%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)79.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.07123
Minimum128.98557
Maximum129.17469
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-11T09:00:22.739141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.98557
5-th percentile128.99627
Q1129.03708
median129.04444
Q3129.13533
95-th percentile129.17164
Maximum129.17469
Range0.189118
Interquartile range (IQR)0.0982515

Descriptive statistics

Standard deviation0.057835389
Coefficient of variation (CV)0.00044808891
Kurtosis-1.0734382
Mean129.07123
Median Absolute Deviation (MAD)0.0411745
Skewness0.47585298
Sum6969.8466
Variance0.0033449322
MonotonicityNot monotonic
2023-12-11T09:00:22.908375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
129.040314 5
 
9.3%
129.149029 3
 
5.6%
128.994938 2
 
3.7%
129.071547 2
 
3.7%
129.089578 2
 
3.7%
129.037076 2
 
3.7%
129.003267 2
 
3.7%
129.06753 1
 
1.9%
129.090342 1
 
1.9%
129.037469 1
 
1.9%
Other values (33) 33
61.1%
ValueCountFrequency (%)
128.985571 1
1.9%
128.994938 2
3.7%
128.996984 1
1.9%
129.00073 1
1.9%
129.000732 1
1.9%
129.003267 2
3.7%
129.004605 1
1.9%
129.007699 1
1.9%
129.034005 1
1.9%
129.034441 1
1.9%
ValueCountFrequency (%)
129.174689 1
 
1.9%
129.173304 1
 
1.9%
129.172006 1
 
1.9%
129.171441 1
 
1.9%
129.167523 1
 
1.9%
129.152459 1
 
1.9%
129.149029 3
5.6%
129.147711 1
 
1.9%
129.146143 1
 
1.9%
129.1456 1
 
1.9%

전화번호
Text

Distinct50
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-11T09:00:23.166389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters648
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

Unique46 ?
Unique (%)85.2%

Sample

1st row055-382-9896
2nd row055-365-2818
3rd row055-383-6698
4th row055-362-2342
5th row055-374-6126
ValueCountFrequency (%)
055-365-2818 2
 
3.7%
055-367-7612 2
 
3.7%
055-365-9544 2
 
3.7%
055-383-7750 2
 
3.7%
055-362-6141 1
 
1.9%
055-382-9896 1
 
1.9%
055-362-5215 1
 
1.9%
055-374-5454 1
 
1.9%
055-912-2727 1
 
1.9%
055-362-5887 1
 
1.9%
Other values (40) 40
74.1%
2023-12-11T09:00:23.580293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 152
23.5%
- 108
16.7%
0 71
11.0%
3 70
10.8%
8 53
 
8.2%
6 40
 
6.2%
7 40
 
6.2%
1 35
 
5.4%
2 31
 
4.8%
9 27
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 540
83.3%
Dash Punctuation 108
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 152
28.1%
0 71
13.1%
3 70
13.0%
8 53
 
9.8%
6 40
 
7.4%
7 40
 
7.4%
1 35
 
6.5%
2 31
 
5.7%
9 27
 
5.0%
4 21
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 648
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 152
23.5%
- 108
16.7%
0 71
11.0%
3 70
10.8%
8 53
 
8.2%
6 40
 
6.2%
7 40
 
6.2%
1 35
 
5.4%
2 31
 
4.8%
9 27
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 152
23.5%
- 108
16.7%
0 71
11.0%
3 70
10.8%
8 53
 
8.2%
6 40
 
6.2%
7 40
 
6.2%
1 35
 
5.4%
2 31
 
4.8%
9 27
 
4.2%

설립일자
Date

Distinct51
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
Minimum1982-08-30 00:00:00
Maximum2020-05-27 00:00:00
2023-12-11T09:00:23.758107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:23.948890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

출처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
기본현황
54 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기본현황 54
100.0%

Length

2023-12-11T09:00:24.089808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:00:24.196009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기본현황 54
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
Minimum2020-12-01 00:00:00
Maximum2020-12-01 00:00:00
2023-12-11T09:00:24.302233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:24.415324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T09:00:18.569840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:16.818899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.293924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.699265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:18.120430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:18.654936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:16.898235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.380584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.780052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:18.203117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:18.737083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.002245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.453200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.857597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:18.285956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:18.864856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.098133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.537347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.945161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:18.384570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:18.951683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.196452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:17.621188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:18.035095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:00:18.479316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:00:24.505435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명종류목적정원현원종사자소재지위도경도전화번호설립일자
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
종류1.0001.0000.8850.8690.8210.7490.9520.6090.0000.6820.967
목적1.0000.8851.0000.8560.0000.2700.9930.6480.5210.0001.000
정원1.0000.8690.8561.000NaN0.7080.8940.2500.3260.7571.000
현원1.0000.8210.000NaN1.0000.6860.0000.2100.0000.0000.000
종사자1.0000.7490.2700.7080.6861.0000.6380.3700.1510.7750.924
소재지1.0000.9520.9930.8940.0000.6381.0001.0001.0000.9910.992
위도1.0000.6090.6480.2500.2100.3701.0001.0000.9301.0000.954
경도1.0000.0000.5210.3260.0000.1511.0000.9301.0001.0000.978
전화번호1.0000.6820.0000.7570.0000.7750.9911.0001.0001.0000.942
설립일자1.0000.9671.0001.0000.0000.9240.9920.9540.9780.9421.000
2023-12-11T09:00:24.665970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류목적
종류1.0000.678
목적0.6781.000
2023-12-11T09:00:24.781411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원현원종사자위도경도종류목적
정원1.0000.9580.8740.298-0.0310.6370.497
현원0.9581.0000.7210.1510.0320.4570.000
종사자0.8740.7211.0000.2880.0100.4330.108
위도0.2980.1510.2881.0000.6930.2940.451
경도-0.0310.0320.0100.6931.0000.0000.336
종류0.6370.4570.4330.2940.0001.0000.678
목적0.4970.0000.1080.4510.3360.6781.000

Missing values

2023-12-11T09:00:19.078090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:00:19.239260image/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.
2023-12-11T09:00:19.357671image/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

시설명종류목적정원현원종사자소재지위도경도전화번호설립일자출처데이터기준일자
0무궁애학원지적장애인시설생활시설908851경상남도 양산시 물금읍 청룡로 6935.328796128.994938055-382-98961982-08-30기본현황2020-12-01
1가온들찬빛지적장애인시설생활시설(부산시법인)808046경상남도 양산시 신명3길 12535.389187129.139522055-365-28181986-06-25기본현황2020-12-01
2새힘장애인단기거주시설생활시설1084경상남도 양산시 물금읍 화산1길 635.310925128.985571055-383-66982016-10-11기본현황2020-12-01
3예은의집장애인공동생활가정생활시설882경상남도 양산시 신명로 7335.385499129.1456055-362-23422005-08-16기본현황2020-12-01
4늘푸른집중증장애인요양시설생활시설474734경상남도 양산시 상북면 수서로 349-9435.440818129.034441055-374-61261994-10-11기본현황2020-12-01
5미래직업재활원장애인직업재활시설(장애인보호작업장)이용시설45417경상남도 양산시 물금읍 청룡로 6935.328796128.994938055-388-23602000-06-30기본현황2020-12-01
6희망나라장애인직업재활시설(장애인보호작업장)이용시설25235경상남도 양산시 매곡4길 835.368045129.173304055-365-80552011-01-17기본현황2020-12-01
7두배일터장애인직업재활시설(장애인보호작업장)이용시설(부산시법인)30305경상남도 양산시 신명3길 13135.389188129.139521055-365-28182000-09-26기본현황2020-12-01
8양산행복한직업재활센터장애인직업재활시설(장애인보호작업장)이용시설30176경상남도 양산시 서창동5길 335.417878129.174689055-781-29512018-10-18기본현황2020-12-01
9마중물직업재활센터장애인직업재활시설(장애인보호작업장)이용시설20104경상남도 양산시 북안북2길 22-835.349898129.039322055-912-01622019-09-18기본현황2020-12-01
시설명종류목적정원현원종사자소재지위도경도전화번호설립일자출처데이터기준일자
44따스한노인주간 보호센터재가노인복지시설이용시설26219경상남도 양산시 동면 웅상대로 305-135.335694129.122747055-381-55012019-06-20기본현황2020-12-01
45양산도우누리치매전문센터재가노인복지시설이용시설35128경상남도 양산시 중앙우회로 15035.348725129.037912055-384-64002019-09-04기본현황2020-12-01
46더이로운노인주간보호센터재가노인복지시설이용시설984경상남도 양산시 양산대로 88635.349527129.037076055-785-22552020-02-24기본현황2020-12-01
47대정재가복지센터재가노인복지시설이용시설<NA>34경상남도 양산시 양산대로 88635.349527129.037076055-785-43842020-02-24기본현황2020-12-01
48꽃들재가요양센터재가노인복지시설이용시설<NA>34경상남도 양산시 물금읍 오봉로 2735.327188128.996984055-785-29292020-03-23기본현황2020-12-01
49구구팔팔어르신재가복지센터재가노인복지시설이용시설<NA>427경상남도 양산시 대운5길 735.402736129.171441055-388-38842020-02-20기본현황2020-12-01
50덕계효성의집재가노인복지시설이용시설987경상남도 양산시 덕계서로 175-235.370941129.146143055-362-88552020-04-09기본현황2020-12-01
51중앙재가복지센터재가노인복지시설이용시설1<NA>2경상남도 양산시 북안남7길 7-535.34673129.040066055-385-54782020-05-27기본현황2020-12-01
52양산시니어클럽노인일자리지원기관이용시설<NA><NA>6경상남도 양산시 남부13길 1135.340709129.038321055-372-13212008-04-04기본현황2020-12-01
53웅상시니어클럽노인일자리지원기관이용시설<NA><NA>5경상남도 양산시 덕계로 9135.375835129.152459055-366-34172020-01-01기본현황2020-12-01