Overview

Dataset statistics

Number of variables17
Number of observations46
Missing cells130
Missing cells (%)16.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory144.9 B

Variable types

Categorical4
Text6
Numeric6
DateTime1

Dataset

Description전라북도 전주시 내 장애인복지시설 현황을 제공하며 시군구, 시설명, 시설구분, 주소, 전화번호 등을 제공합니다.
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=4&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15075087

Alerts

시군구 has constant value ""Constant
데이터기준일자 has constant value ""Constant
경도 is highly overall correlated with 입소자(근로장애인)정원 and 2 other fieldsHigh correlation
입소자(근로장애인)정원 is highly overall correlated with 경도 and 5 other fieldsHigh correlation
입소자(근로장애인)현원 is highly overall correlated with 경도 and 5 other fieldsHigh correlation
종사자 정원 is highly overall correlated with 경도 and 5 other fieldsHigh correlation
종사자 현원 is highly overall correlated with 입소자(근로장애인)정원 and 4 other fieldsHigh correlation
시설대구분 is highly overall correlated with 입소자(근로장애인)정원 and 4 other fieldsHigh correlation
시설소구분 is highly overall correlated with 입소자(근로장애인)정원 and 4 other fieldsHigh correlation
법인명 has 1 (2.2%) missing valuesMissing
시설장 has 40 (87.0%) missing valuesMissing
입소자(근로장애인)정원 has 8 (17.4%) missing valuesMissing
입소자(근로장애인)현원 has 27 (58.7%) missing valuesMissing
종사자 정원 has 27 (58.7%) missing valuesMissing
종사자 현원 has 27 (58.7%) missing valuesMissing
시설명 has unique valuesUnique
입소자(근로장애인)현원 has 2 (4.3%) zerosZeros

Reproduction

Analysis started2024-03-14 01:28:16.028604
Analysis finished2024-03-14 01:28:20.070460
Duration4.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
전라북도 전주시
46 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전라북도 전주시
2nd row전라북도 전주시
3rd row전라북도 전주시
4th row전라북도 전주시
5th row전라북도 전주시

Common Values

ValueCountFrequency (%)
전라북도 전주시 46
100.0%

Length

2024-03-14T10:28:20.121053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:28:20.197193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 46
50.0%
전주시 46
50.0%

시설명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T10:28:20.381921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length9.2608696
Min length4

Characters and Unicode

Total characters426
Distinct characters130
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

Unique46 ?
Unique (%)100.0%

Sample

1st row동암재활원
2nd row소화진달네집
3rd row평안의집
4th row금선백련마을
5th row한마음단기보호센타
ValueCountFrequency (%)
주간보호센터 3
 
5.7%
전라북도 2
 
3.8%
동암재활원 1
 
1.9%
손수레주간보호센터 1
 
1.9%
전북장애인보호작업장 1
 
1.9%
희망해주간보호센터 1
 
1.9%
해냄주간보호센터 1
 
1.9%
더나눔주간보호센터 1
 
1.9%
전라북도장애인복지관 1
 
1.9%
전주어울림국민체육센터 1
 
1.9%
Other values (40) 40
75.5%
2024-03-14T10:28:20.709966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
센 24
 
5.6%
터 22
 
5.2%
주 19
 
4.5%
호 17
 
4.0%
전 15
 
3.5%
보 15
 
3.5%
간 13
 
3.1%
장 12
 
2.8%
동 10
 
2.3%
인 10
 
2.3%
Other values (120) 269
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 410
96.2%
Space Separator 7
 
1.6%
Uppercase Letter 4
 
0.9%
Decimal Number 2
 
0.5%
Close Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
센 24
 
5.9%
터 22
 
5.4%
주 19
 
4.6%
호 17
 
4.1%
전 15
 
3.7%
보 15
 
3.7%
간 13
 
3.2%
장 12
 
2.9%
동 10
 
2.4%
인 10
 
2.4%
Other values (110) 253
61.7%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
H 1
25.0%
I 1
25.0%
W 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 410
96.2%
Common 12
 
2.8%
Latin 4
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
센 24
 
5.9%
터 22
 
5.4%
주 19
 
4.6%
호 17
 
4.1%
전 15
 
3.7%
보 15
 
3.7%
간 13
 
3.2%
장 12
 
2.9%
동 10
 
2.4%
인 10
 
2.4%
Other values (110) 253
61.7%
Common
ValueCountFrequency (%)
7
58.3%
) 1
 
8.3%
& 1
 
8.3%
( 1
 
8.3%
2 1
 
8.3%
1 1
 
8.3%
Latin
ValueCountFrequency (%)
T 1
25.0%
H 1
25.0%
I 1
25.0%
W 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 410
96.2%
ASCII 16
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
센 24
 
5.9%
터 22
 
5.4%
주 19
 
4.6%
호 17
 
4.1%
전 15
 
3.7%
보 15
 
3.7%
간 13
 
3.2%
장 12
 
2.9%
동 10
 
2.4%
인 10
 
2.4%
Other values (110) 253
61.7%
ASCII
ValueCountFrequency (%)
7
43.8%
) 1
 
6.2%
T 1
 
6.2%
H 1
 
6.2%
& 1
 
6.2%
I 1
 
6.2%
W 1
 
6.2%
( 1
 
6.2%
2 1
 
6.2%
1 1
 
6.2%

시설대구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
장애인 지역사회 재활시설
27 
장애인거주시설
13 
장애인 직업재활시설 및 장애인생산품 판매시설
6 

Length

Max length24
Median length13
Mean length12.73913
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장애인 지역사회 재활시설 27
58.7%
장애인거주시설 13
28.3%
장애인 직업재활시설 및 장애인생산품 판매시설 6
 
13.0%

Length

2024-03-14T10:28:20.834438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:28:20.912634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장애인 33
26.6%
지역사회 27
21.8%
재활시설 27
21.8%
장애인거주시설 13
 
10.5%
직업재활시설 6
 
4.8%
및 6
 
4.8%
장애인생산품 6
 
4.8%
판매시설 6
 
4.8%

시설소구분
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Memory size500.0 B
장애인 주간보호시설
13 
장애인공동생활가정
8 
재활치료시설
5 
보호작업장
5 
지적장애인시설
2 
Other values (9)
13 

Length

Max length10
Median length9
Mean length7.9782609
Min length5

Unique

Unique5 ?
Unique (%)10.9%

Sample

1st row지체장애인시설
2nd row지적장애인시설
3rd row지적장애인시설
4th row중증장애인 거주시설
5th row장애인 단기거주시설

Common Values

ValueCountFrequency (%)
장애인 주간보호시설 13
28.3%
장애인공동생활가정 8
17.4%
재활치료시설 5
 
10.9%
보호작업장 5
 
10.9%
지적장애인시설 2
 
4.3%
장애인복지관 2
 
4.3%
장애인 체육시설 2
 
4.3%
수어통역센터 2
 
4.3%
생활이동지원센터 2
 
4.3%
지체장애인시설 1
 
2.2%
Other values (4) 4
 
8.7%

Length

2024-03-14T10:28:21.007848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장애인 16
25.4%
주간보호시설 13
20.6%
장애인공동생활가정 8
12.7%
재활치료시설 5
 
7.9%
보호작업장 5
 
7.9%
지적장애인시설 2
 
3.2%
장애인복지관 2
 
3.2%
체육시설 2
 
3.2%
수어통역센터 2
 
3.2%
생활이동지원센터 2
 
3.2%
Other values (6) 6
 
9.5%

도로명주소
Text

Distinct40
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T10:28:21.215422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length34
Mean length25.23913
Min length20

Characters and Unicode

Total characters1161
Distinct characters110
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)76.1%

Sample

1st row전라북도 전주시 완산구 천잠로 275
2nd row전라북도 전주시 완산구 우림로 595-32
3rd row전라북도 전주시 완산구 선너머2길 29-15
4th row전라북도 전주시 완산구 덕적골1길 18-3(평화동1가)
5th row전라북도 전주시 완산구 계룡산길 44-8
ValueCountFrequency (%)
전라북도 46
17.8%
전주시 46
17.8%
완산구 26
 
10.1%
덕진구 21
 
8.1%
천잠로 5
 
1.9%
277 3
 
1.2%
학산길 3
 
1.2%
백제대로 3
 
1.2%
다동 2
 
0.8%
403호 2
 
0.8%
Other values (89) 101
39.1%
2024-03-14T10:28:21.591300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
212
18.3%
전 94
 
8.1%
시 48
 
4.1%
구 48
 
4.1%
주 47
 
4.0%
도 46
 
4.0%
북 46
 
4.0%
라 46
 
4.0%
1 42
 
3.6%
산 35
 
3.0%
Other values (100) 497
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 695
59.9%
Space Separator 212
 
18.3%
Decimal Number 202
 
17.4%
Dash Punctuation 23
 
2.0%
Other Punctuation 19
 
1.6%
Open Punctuation 4
 
0.3%
Close Punctuation 4
 
0.3%
Uppercase Letter 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 94
13.5%
시 48
 
6.9%
구 48
 
6.9%
주 47
 
6.8%
도 46
 
6.6%
북 46
 
6.6%
라 46
 
6.6%
산 35
 
5.0%
완 28
 
4.0%
길 26
 
3.7%
Other values (82) 231
33.2%
Decimal Number
ValueCountFrequency (%)
1 42
20.8%
2 32
15.8%
7 22
10.9%
3 20
9.9%
0 20
9.9%
4 18
8.9%
5 17
8.4%
8 13
 
6.4%
6 13
 
6.4%
9 5
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 18
94.7%
: 1
 
5.3%
Space Separator
ValueCountFrequency (%)
212
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 695
59.9%
Common 465
40.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 94
13.5%
시 48
 
6.9%
구 48
 
6.9%
주 47
 
6.8%
도 46
 
6.6%
북 46
 
6.6%
라 46
 
6.6%
산 35
 
5.0%
완 28
 
4.0%
길 26
 
3.7%
Other values (82) 231
33.2%
Common
ValueCountFrequency (%)
212
45.6%
1 42
 
9.0%
2 32
 
6.9%
- 23
 
4.9%
7 22
 
4.7%
3 20
 
4.3%
0 20
 
4.3%
4 18
 
3.9%
, 18
 
3.9%
5 17
 
3.7%
Other values (7) 41
 
8.8%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 695
59.9%
ASCII 466
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
212
45.5%
1 42
 
9.0%
2 32
 
6.9%
- 23
 
4.9%
7 22
 
4.7%
3 20
 
4.3%
0 20
 
4.3%
4 18
 
3.9%
, 18
 
3.9%
5 17
 
3.6%
Other values (8) 42
 
9.0%
Hangul
ValueCountFrequency (%)
전 94
13.5%
시 48
 
6.9%
구 48
 
6.9%
주 47
 
6.8%
도 46
 
6.6%
북 46
 
6.6%
라 46
 
6.6%
산 35
 
5.0%
완 28
 
4.0%
길 26
 
3.7%
Other values (82) 231
33.2%

지번주소
Text

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T10:28:21.817912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length24.217391
Min length20

Characters and Unicode

Total characters1114
Distinct characters50
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

Unique33 ?
Unique (%)71.7%

Sample

1st row전라북도 전주시 완산구 효자동3가 1215-5
2nd row전라북도 전주시 완산구 용복동 533-1
3rd row전라북도 전주시 완산구 중화산동2가 153-8
4th row전라북도 전주시 완산구 평화동1가 569-3
5th row전라북도 전주시 완산구 삼천동2가 225-1
ValueCountFrequency (%)
전라북도 46
20.0%
전주시 46
20.0%
완산구 26
 
11.3%
덕진구 20
 
8.7%
효자동3가 5
 
2.2%
평화동1가 4
 
1.7%
인후동1가 4
 
1.7%
서완산동2가 3
 
1.3%
팔복동2가 3
 
1.3%
1215-21 3
 
1.3%
Other values (60) 70
30.4%
2024-03-14T10:28:22.121608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
184
16.5%
전 93
 
8.3%
1 59
 
5.3%
동 47
 
4.2%
라 46
 
4.1%
2 46
 
4.1%
구 46
 
4.1%
시 46
 
4.1%
주 46
 
4.1%
도 46
 
4.1%
Other values (40) 455
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 643
57.7%
Decimal Number 244
 
21.9%
Space Separator 184
 
16.5%
Dash Punctuation 43
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 93
14.5%
동 47
 
7.3%
라 46
 
7.2%
구 46
 
7.2%
시 46
 
7.2%
주 46
 
7.2%
도 46
 
7.2%
북 46
 
7.2%
가 39
 
6.1%
산 31
 
4.8%
Other values (28) 157
24.4%
Decimal Number
ValueCountFrequency (%)
1 59
24.2%
2 46
18.9%
3 24
9.8%
5 24
9.8%
4 23
 
9.4%
9 19
 
7.8%
8 15
 
6.1%
6 14
 
5.7%
7 11
 
4.5%
0 9
 
3.7%
Space Separator
ValueCountFrequency (%)
184
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 643
57.7%
Common 471
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 93
14.5%
동 47
 
7.3%
라 46
 
7.2%
구 46
 
7.2%
시 46
 
7.2%
주 46
 
7.2%
도 46
 
7.2%
북 46
 
7.2%
가 39
 
6.1%
산 31
 
4.8%
Other values (28) 157
24.4%
Common
ValueCountFrequency (%)
184
39.1%
1 59
 
12.5%
2 46
 
9.8%
- 43
 
9.1%
3 24
 
5.1%
5 24
 
5.1%
4 23
 
4.9%
9 19
 
4.0%
8 15
 
3.2%
6 14
 
3.0%
Other values (2) 20
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 643
57.7%
ASCII 471
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
184
39.1%
1 59
 
12.5%
2 46
 
9.8%
- 43
 
9.1%
3 24
 
5.1%
5 24
 
5.1%
4 23
 
4.9%
9 19
 
4.0%
8 15
 
3.2%
6 14
 
3.0%
Other values (2) 20
 
4.2%
Hangul
ValueCountFrequency (%)
전 93
14.5%
동 47
 
7.3%
라 46
 
7.2%
구 46
 
7.2%
시 46
 
7.2%
주 46
 
7.2%
도 46
 
7.2%
북 46
 
7.2%
가 39
 
6.1%
산 31
 
4.8%
Other values (28) 157
24.4%

위도
Real number (ℝ)

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.823504
Minimum35.761307
Maximum35.890497
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-14T10:28:22.242918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.761307
5-th percentile35.790384
Q135.806004
median35.813016
Q335.845628
95-th percentile35.873072
Maximum35.890497
Range0.12919043
Interquartile range (IQR)0.039623777

Descriptive statistics

Standard deviation0.028397929
Coefficient of variation (CV)0.0007927178
Kurtosis-0.41833663
Mean35.823504
Median Absolute Deviation (MAD)0.0173513
Skewness0.40666152
Sum1647.8812
Variance0.00080644239
MonotonicityNot monotonic
2024-03-14T10:28:22.351150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
35.81176139 3
 
6.5%
35.81051203 2
 
4.3%
35.79057537 2
 
4.3%
35.81014394 2
 
4.3%
35.85529467 2
 
4.3%
35.79753744 2
 
4.3%
35.85501829 1
 
2.2%
35.81488365 1
 
2.2%
35.80544999 1
 
2.2%
35.8091884 1
 
2.2%
Other values (29) 29
63.0%
ValueCountFrequency (%)
35.761307 1
2.2%
35.78851865 1
2.2%
35.7903196 1
2.2%
35.79057537 2
4.3%
35.79119477 1
2.2%
35.79541133 1
2.2%
35.79591715 1
2.2%
35.79753744 2
4.3%
35.80291082 1
2.2%
35.80544999 1
2.2%
ValueCountFrequency (%)
35.89049743 1
2.2%
35.87647017 1
2.2%
35.87524058 1
2.2%
35.86656728 1
2.2%
35.86333293 1
2.2%
35.85618286 1
2.2%
35.85538728 1
2.2%
35.85529467 2
4.3%
35.85501829 1
2.2%
35.85181005 1
2.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.1236
Minimum127.05801
Maximum127.19252
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-14T10:28:22.455578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.05801
5-th percentile127.07489
Q1127.09548
median127.12984
Q3127.14081
95-th percentile127.16473
Maximum127.19252
Range0.1345105
Interquartile range (IQR)0.045333325

Descriptive statistics

Standard deviation0.030128282
Coefficient of variation (CV)0.00023699992
Kurtosis-0.36155936
Mean127.1236
Median Absolute Deviation (MAD)0.02478125
Skewness-0.13457318
Sum5847.6854
Variance0.0009077134
MonotonicityNot monotonic
2024-03-14T10:28:22.567315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
127.0926189 3
 
6.5%
127.0927681 2
 
4.3%
127.1046249 2
 
4.3%
127.1351051 2
 
4.3%
127.0927658 2
 
4.3%
127.1323492 2
 
4.3%
127.1258282 1
 
2.2%
127.1055003 1
 
2.2%
127.1139624 1
 
2.2%
127.144949 1
 
2.2%
Other values (29) 29
63.0%
ValueCountFrequency (%)
127.0580071 1
 
2.2%
127.0613826 1
 
2.2%
127.0713874 1
 
2.2%
127.0853895 1
 
2.2%
127.0926189 3
6.5%
127.0927658 2
4.3%
127.0927681 2
4.3%
127.0929424 1
 
2.2%
127.1030885 1
 
2.2%
127.1046249 2
4.3%
ValueCountFrequency (%)
127.1925176 1
2.2%
127.1712778 1
2.2%
127.165313 1
2.2%
127.1629684 1
2.2%
127.1620021 1
2.2%
127.1599773 1
2.2%
127.1592708 1
2.2%
127.1581287 1
2.2%
127.1526761 1
2.2%
127.144949 1
2.2%

전화번호
Text

Distinct42
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T10:28:22.993893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.021739
Min length12

Characters and Unicode

Total characters553
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

Unique39 ?
Unique (%)84.8%

Sample

1st row063-222-4444
2nd row063-222-2786
3rd row063-282-7728
4th row063-236-0550
5th row063-224-6679
ValueCountFrequency (%)
063-901-0625 3
 
6.5%
063-222-9999 2
 
4.3%
063-224-6679 2
 
4.3%
063-244-6479 1
 
2.2%
063-283-7650 1
 
2.2%
063-227-9944 1
 
2.2%
070-8749-7575 1
 
2.2%
063-224-3242 1
 
2.2%
063-273-1955 1
 
2.2%
063-228-1804 1
 
2.2%
Other values (32) 32
69.6%
2024-03-14T10:28:23.278987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 92
16.6%
2 84
15.2%
0 80
14.5%
6 71
12.8%
3 67
12.1%
4 38
6.9%
9 33
 
6.0%
8 28
 
5.1%
7 24
 
4.3%
1 18
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 461
83.4%
Dash Punctuation 92
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 84
18.2%
0 80
17.4%
6 71
15.4%
3 67
14.5%
4 38
8.2%
9 33
 
7.2%
8 28
 
6.1%
7 24
 
5.2%
1 18
 
3.9%
5 18
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 553
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 92
16.6%
2 84
15.2%
0 80
14.5%
6 71
12.8%
3 67
12.1%
4 38
6.9%
9 33
 
6.0%
8 28
 
5.1%
7 24
 
4.3%
1 18
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 553
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 92
16.6%
2 84
15.2%
0 80
14.5%
6 71
12.8%
3 67
12.1%
4 38
6.9%
9 33
 
6.0%
8 28
 
5.1%
7 24
 
4.3%
1 18
 
3.3%

설치신고일
Date

Distinct45
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum1987-08-28 00:00:00
Maximum2021-08-26 00:00:00
2024-03-14T10:28:23.401916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:23.507987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)

법인명
Text

MISSING 

Distinct30
Distinct (%)66.7%
Missing1
Missing (%)2.2%
Memory size500.0 B
2024-03-14T10:28:23.669368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length8.4666667
Min length2

Characters and Unicode

Total characters381
Distinct characters78
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

Unique20 ?
Unique (%)44.4%

Sample

1st row사회복지법인동암
2nd row소화자매원
3rd row평안한복지
4th row사회복지법인 송광
5th row전라북도 장애인 부모회
ValueCountFrequency (%)
개인 7
 
11.3%
전라북도 6
 
9.7%
사단법인 4
 
6.5%
동암 4
 
6.5%
사회복지법인 3
 
4.8%
전주지부 2
 
3.2%
시각장애인연합회 2
 
3.2%
바른복지사무소 2
 
3.2%
중도원 2
 
3.2%
한국장애인부모회 2
 
3.2%
Other values (25) 28
45.2%
2024-03-14T10:28:24.017585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 33
 
8.7%
회 23
 
6.0%
17
 
4.5%
전 17
 
4.5%
지 17
 
4.5%
장 16
 
4.2%
사 16
 
4.2%
애 16
 
4.2%
복 12
 
3.1%
북 11
 
2.9%
Other values (68) 203
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 356
93.4%
Space Separator 17
 
4.5%
Close Punctuation 4
 
1.0%
Open Punctuation 3
 
0.8%
Math Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 33
 
9.3%
회 23
 
6.5%
전 17
 
4.8%
지 17
 
4.8%
장 16
 
4.5%
사 16
 
4.5%
애 16
 
4.5%
복 12
 
3.4%
북 11
 
3.1%
도 11
 
3.1%
Other values (64) 184
51.7%
Space Separator
ValueCountFrequency (%)
17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 356
93.4%
Common 25
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 33
 
9.3%
회 23
 
6.5%
전 17
 
4.8%
지 17
 
4.8%
장 16
 
4.5%
사 16
 
4.5%
애 16
 
4.5%
복 12
 
3.4%
북 11
 
3.1%
도 11
 
3.1%
Other values (64) 184
51.7%
Common
ValueCountFrequency (%)
17
68.0%
) 4
 
16.0%
( 3
 
12.0%
+ 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 356
93.4%
ASCII 25
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 33
 
9.3%
회 23
 
6.5%
전 17
 
4.8%
지 17
 
4.8%
장 16
 
4.5%
사 16
 
4.5%
애 16
 
4.5%
복 12
 
3.4%
북 11
 
3.1%
도 11
 
3.1%
Other values (64) 184
51.7%
ASCII
ValueCountFrequency (%)
17
68.0%
) 4
 
16.0%
( 3
 
12.0%
+ 1
 
4.0%

시설장
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing40
Missing (%)87.0%
Memory size500.0 B
2024-03-14T10:28:24.142520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters18
Distinct characters16
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

Unique6 ?
Unique (%)100.0%

Sample

1st row김관무
2nd row정진남
3rd row최명호
4th row이정득
5th row정성일
ValueCountFrequency (%)
김관무 1
16.7%
정진남 1
16.7%
최명호 1
16.7%
이정득 1
16.7%
정성일 1
16.7%
백동훈 1
16.7%
2024-03-14T10:28:24.396059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 3
16.7%
김 1
 
5.6%
관 1
 
5.6%
무 1
 
5.6%
진 1
 
5.6%
남 1
 
5.6%
최 1
 
5.6%
명 1
 
5.6%
호 1
 
5.6%
이 1
 
5.6%
Other values (6) 6
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 3
16.7%
김 1
 
5.6%
관 1
 
5.6%
무 1
 
5.6%
진 1
 
5.6%
남 1
 
5.6%
최 1
 
5.6%
명 1
 
5.6%
호 1
 
5.6%
이 1
 
5.6%
Other values (6) 6
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 3
16.7%
김 1
 
5.6%
관 1
 
5.6%
무 1
 
5.6%
진 1
 
5.6%
남 1
 
5.6%
최 1
 
5.6%
명 1
 
5.6%
호 1
 
5.6%
이 1
 
5.6%
Other values (6) 6
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 3
16.7%
김 1
 
5.6%
관 1
 
5.6%
무 1
 
5.6%
진 1
 
5.6%
남 1
 
5.6%
최 1
 
5.6%
명 1
 
5.6%
호 1
 
5.6%
이 1
 
5.6%
Other values (6) 6
33.3%

입소자(근로장애인)정원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)39.5%
Missing8
Missing (%)17.4%
Infinite0
Infinite (%)0.0%
Mean17.5
Minimum3
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-14T10:28:24.494310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q110
median15
Q320
95-th percentile31.5
Maximum70
Range67
Interquartile range (IQR)10

Descriptive statistics

Standard deviation12.680587
Coefficient of variation (CV)0.724605
Kurtosis6.8885683
Mean17.5
Median Absolute Deviation (MAD)5
Skewness2.0355812
Sum665
Variance160.7973
MonotonicityNot monotonic
2024-03-14T10:28:24.585932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4 6
13.0%
20 5
10.9%
30 5
10.9%
10 5
10.9%
15 5
10.9%
18 2
 
4.3%
25 2
 
4.3%
70 1
 
2.2%
40 1
 
2.2%
7 1
 
2.2%
Other values (5) 5
10.9%
(Missing) 8
17.4%
ValueCountFrequency (%)
3 1
 
2.2%
4 6
13.0%
7 1
 
2.2%
10 5
10.9%
13 1
 
2.2%
14 1
 
2.2%
15 5
10.9%
16 1
 
2.2%
17 1
 
2.2%
18 2
 
4.3%
ValueCountFrequency (%)
70 1
 
2.2%
40 1
 
2.2%
30 5
10.9%
25 2
 
4.3%
20 5
10.9%
18 2
 
4.3%
17 1
 
2.2%
16 1
 
2.2%
15 5
10.9%
14 1
 
2.2%

입소자(근로장애인)현원
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct14
Distinct (%)73.7%
Missing27
Missing (%)58.7%
Infinite0
Infinite (%)0.0%
Mean13.526316
Minimum0
Maximum35
Zeros2
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-14T10:28:24.677940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q324.5
95-th percentile33.2
Maximum35
Range35
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation12.258187
Coefficient of variation (CV)0.90624732
Kurtosis-1.2294756
Mean13.526316
Median Absolute Deviation (MAD)7
Skewness0.59715157
Sum257
Variance150.26316
MonotonicityNot monotonic
2024-03-14T10:28:24.776123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
4 4
 
8.7%
0 2
 
4.3%
29 2
 
4.3%
35 1
 
2.2%
33 1
 
2.2%
20 1
 
2.2%
30 1
 
2.2%
10 1
 
2.2%
3 1
 
2.2%
5 1
 
2.2%
Other values (4) 4
 
8.7%
(Missing) 27
58.7%
ValueCountFrequency (%)
0 2
4.3%
2 1
 
2.2%
3 1
 
2.2%
4 4
8.7%
5 1
 
2.2%
10 1
 
2.2%
13 1
 
2.2%
15 1
 
2.2%
17 1
 
2.2%
20 1
 
2.2%
ValueCountFrequency (%)
35 1
2.2%
33 1
2.2%
30 1
2.2%
29 2
4.3%
20 1
2.2%
17 1
2.2%
15 1
2.2%
13 1
2.2%
10 1
2.2%
5 1
2.2%

종사자 정원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)52.6%
Missing27
Missing (%)58.7%
Infinite0
Infinite (%)0.0%
Mean7.9473684
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-14T10:28:24.879874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median5
Q38.5
95-th percentile30
Maximum30
Range29
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation9.4249886
Coefficient of variation (CV)1.1859257
Kurtosis1.5649822
Mean7.9473684
Median Absolute Deviation (MAD)4
Skewness1.5845359
Sum151
Variance88.830409
MonotonicityNot monotonic
2024-03-14T10:28:24.975798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 7
 
15.2%
30 2
 
4.3%
8 2
 
4.3%
6 2
 
4.3%
21 1
 
2.2%
15 1
 
2.2%
2 1
 
2.2%
5 1
 
2.2%
9 1
 
2.2%
4 1
 
2.2%
(Missing) 27
58.7%
ValueCountFrequency (%)
1 7
15.2%
2 1
 
2.2%
4 1
 
2.2%
5 1
 
2.2%
6 2
 
4.3%
8 2
 
4.3%
9 1
 
2.2%
15 1
 
2.2%
21 1
 
2.2%
30 2
 
4.3%
ValueCountFrequency (%)
30 2
 
4.3%
21 1
 
2.2%
15 1
 
2.2%
9 1
 
2.2%
8 2
 
4.3%
6 2
 
4.3%
5 1
 
2.2%
4 1
 
2.2%
2 1
 
2.2%
1 7
15.2%

종사자 현원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)52.6%
Missing27
Missing (%)58.7%
Infinite0
Infinite (%)0.0%
Mean7.4210526
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-14T10:28:25.081769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median5
Q37
95-th percentile28.2
Maximum30
Range29
Interquartile range (IQR)6

Descriptive statistics

Standard deviation8.9648436
Coefficient of variation (CV)1.2080286
Kurtosis2.0506888
Mean7.4210526
Median Absolute Deviation (MAD)4
Skewness1.7030155
Sum141
Variance80.368421
MonotonicityNot monotonic
2024-03-14T10:28:25.159035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 7
 
15.2%
7 3
 
6.5%
5 2
 
4.3%
18 1
 
2.2%
28 1
 
2.2%
15 1
 
2.2%
30 1
 
2.2%
2 1
 
2.2%
6 1
 
2.2%
4 1
 
2.2%
(Missing) 27
58.7%
ValueCountFrequency (%)
1 7
15.2%
2 1
 
2.2%
4 1
 
2.2%
5 2
 
4.3%
6 1
 
2.2%
7 3
6.5%
15 1
 
2.2%
18 1
 
2.2%
28 1
 
2.2%
30 1
 
2.2%
ValueCountFrequency (%)
30 1
 
2.2%
28 1
 
2.2%
18 1
 
2.2%
15 1
 
2.2%
7 3
6.5%
6 1
 
2.2%
5 2
 
4.3%
4 1
 
2.2%
2 1
 
2.2%
1 7
15.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
2022-07-25
46 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-07-25
2nd row2022-07-25
3rd row2022-07-25
4th row2022-07-25
5th row2022-07-25

Common Values

ValueCountFrequency (%)
2022-07-25 46
100.0%

Length

2024-03-14T10:28:25.246866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:28:25.313198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-07-25 46
100.0%

Interactions

2024-03-14T10:28:19.181318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:16.623467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:17.403468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:17.804670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.262653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.761822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:19.248005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:16.688069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:17.474252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:17.873652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.331376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.826109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:19.348722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:16.767095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:17.540833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:17.944311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.421158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.889154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:19.467765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:16.845171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:17.609310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.025692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.533811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.960459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:19.552756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:17.256737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:17.677110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.110376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.620114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:19.027590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:19.624292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:17.333553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:17.740581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.189052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:18.695050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:19.107556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:28:25.369223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명시설대구분시설소구분도로명주소지번주소위도경도전화번호설치신고일법인명시설장입소자(근로장애인)정원입소자(근로장애인)현원종사자 정원종사자 현원
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시설대구분1.0001.0001.0000.0000.5530.6820.5330.9791.0000.952NaN0.8200.8530.9830.983
시설소구분1.0001.0001.0000.0000.0000.0000.0000.9140.7690.9421.0000.8830.8100.8800.880
도로명주소1.0000.0000.0001.0001.0001.0001.0000.9891.0000.9531.0000.0000.8460.0000.000
지번주소1.0000.5530.0001.0001.0001.0001.0000.9961.0000.9501.0000.5210.8590.7330.733
위도1.0000.6820.0001.0001.0001.0000.7681.0001.0000.8881.0000.6030.4200.3970.333
경도1.0000.5330.0001.0001.0000.7681.0001.0001.0000.8351.0000.4980.6820.3290.449
전화번호1.0000.9790.9140.9890.9961.0001.0001.0001.0000.9811.0001.0000.9661.0001.000
설치신고일1.0001.0000.7691.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
법인명1.0000.9520.9420.9530.9500.8880.8350.9811.0001.0001.0000.8690.9740.8970.953
시설장1.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
입소자(근로장애인)정원1.0000.8200.8830.0000.5210.6030.4981.0001.0000.8691.0001.0000.9230.9570.965
입소자(근로장애인)현원1.0000.8530.8100.8460.8590.4200.6820.9661.0000.9741.0000.9231.0000.8610.838
종사자 정원1.0000.9830.8800.0000.7330.3970.3291.0001.0000.8971.0000.9570.8611.0000.994
종사자 현원1.0000.9830.8800.0000.7330.3330.4491.0001.0000.9531.0000.9650.8380.9941.000
2024-03-14T10:28:25.539035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설대구분시설소구분
시설대구분1.0000.863
시설소구분0.8631.000
2024-03-14T10:28:25.623285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도입소자(근로장애인)정원입소자(근로장애인)현원종사자 정원종사자 현원시설대구분시설소구분
위도1.000-0.002-0.156-0.277-0.322-0.3460.3590.000
경도-0.0021.000-0.555-0.546-0.605-0.4860.2500.000
입소자(근로장애인)정원-0.156-0.5551.0000.9540.8720.8340.7340.677
입소자(근로장애인)현원-0.277-0.5460.9541.0000.8730.8470.5310.564
종사자 정원-0.322-0.6050.8720.8731.0000.9800.7700.722
종사자 현원-0.346-0.4860.8340.8470.9801.0000.7700.722
시설대구분0.3590.2500.7340.5310.7700.7701.0000.863
시설소구분0.0000.0000.6770.5640.7220.7220.8631.000

Missing values

2024-03-14T10:28:19.732949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:28:19.891860image/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.
2024-03-14T10:28:20.003608image/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

시군구시설명시설대구분시설소구분도로명주소지번주소위도경도전화번호설치신고일법인명시설장입소자(근로장애인)정원입소자(근로장애인)현원종사자 정원종사자 현원데이터기준일자
0전라북도 전주시동암재활원장애인거주시설지체장애인시설전라북도 전주시 완산구 천잠로 275전라북도 전주시 완산구 효자동3가 1215-535.810512127.092768063-222-44441990-09-03사회복지법인동암<NA>703521182022-07-25
1전라북도 전주시소화진달네집장애인거주시설지적장애인시설전라북도 전주시 완산구 우림로 595-32전라북도 전주시 완산구 용복동 533-135.761307127.061383063-222-27862006-04-28소화자매원<NA>403330282022-07-25
2전라북도 전주시평안의집장애인거주시설지적장애인시설전라북도 전주시 완산구 선너머2길 29-15전라북도 전주시 완산구 중화산동2가 153-835.81427127.127127063-282-77282019-03-13평안한복지<NA>202015152022-07-25
3전라북도 전주시금선백련마을장애인거주시설중증장애인 거주시설전라북도 전주시 완산구 덕적골1길 18-3(평화동1가)전라북도 전주시 완산구 평화동1가 569-335.795917127.138357063-236-05502016-06-17사회복지법인 송광<NA>303030302022-07-25
4전라북도 전주시한마음단기보호센타장애인거주시설장애인 단기거주시설전라북도 전주시 완산구 계룡산길 44-8전라북도 전주시 완산구 삼천동2가 225-135.790575127.104625063-224-66792002-03-27전라북도 장애인 부모회<NA>1010872022-07-25
5전라북도 전주시손수레공동생활가정장애인거주시설장애인공동생활가정전라북도 전주시 덕진구 가재미2길 5-6전라북도 전주시 덕진구 인후동1가 883-735.829071127.162968063-229-09932008-11-18전라북도장애인손수레자립생활협회<NA>43112022-07-25
6전라북도 전주시작은나눔의집장애인거주시설장애인공동생활가정전라북도 전주시 덕진구 가재미5길 17전라북도 전주시 덕진구 인후동1가 870-1735.829794127.159977063-247-63372008-03-10개인<NA>75112022-07-25
7전라북도 전주시희망해1호장애인거주시설장애인공동생활가정전라북도 전주시 완산구 강당1길 2, 201~202호(서완산동2가, 솔빌리지)전라북도 전주시 완산구 서완산동2가 74-2735.808647127.134391063-901-06252016-01-07(사)바른복지사무소<NA>44112022-07-25
8전라북도 전주시희망해2호장애인거주시설장애인공동생활가정전라북도 전주시 완산구 강당2길 14, 다동 307호(서완산동2가, 대종낙원맨션)전라북도 전주시 완산구 서완산동2가 80-13535.810144127.135105063-901-06252017-09-25(사)바른복지사무소<NA>44112022-07-25
9전라북도 전주시함께하는벗장애인거주시설장애인공동생활가정전라북도 전주시 완산구 간납로 52, 원산아파트 610호전라북도 전주시 완산구 남노송동 6435.816931127.159271063-231-03022019-03-14한국지적발달장애인복지협회<NA>44222022-07-25
시군구시설명시설대구분시설소구분도로명주소지번주소위도경도전화번호설치신고일법인명시설장입소자(근로장애인)정원입소자(근로장애인)현원종사자 정원종사자 현원데이터기준일자
36전라북도 전주시예손운동발달센터장애인 지역사회 재활시설재활치료시설전라북도 전주시 덕진구 백제대로 686, 4층전라북도 전주시 덕진구 인후동2가 1529-2635.843718127.144385063-273-22312015-05-07개인<NA>25<NA><NA><NA>2022-07-25
37전라북도 전주시전라북도특수심리&운동발달센터장애인 지역사회 재활시설재활치료시설전라북도 전주시 덕진구 아중로 143, 4층전라북도 전주시 덕진구 인후동1가 916-335.82607127.165313063-224-32422014-02-26개인<NA>10<NA><NA><NA>2022-07-25
38전라북도 전주시하엘언어청각센터장애인 지역사회 재활시설재활치료시설전라북도 전주시 완산구 호암로 80, 성심빌딩 602전라북도 전주시 완산구 효자동2가 1319-235.808336127.103088063-236-14562013-10-01개인<NA>25<NA><NA><NA>2022-07-25
39전라북도 전주시희망찬발달재활센터장애인 지역사회 재활시설재활치료시설전라북도 전주시 완산구 삼천천변1길 17, B-101호전라북도 전주시 완산구 삼천동1가 288-935.795411127.112653063-226-88282017-12-01개인<NA>20<NA><NA><NA>2022-07-25
40전라북도 전주시더불어삶장애인 직업재활시설 및 장애인생산품 판매시설보호작업장전라북도 전주시 덕진구 서당길 37, 2동 1층(용정동, 공장:전주시 덕진구 서당길 37, 1동)전라북도 전주시 덕진구 용정동 92-835.87647127.058007063-214-07892017-04-10사단법인 참복지김관무3015652022-07-25
41전라북도 전주시동암자활자립장장애인 직업재활시설 및 장애인생산품 판매시설보호작업장전라북도 전주시 완산구 천잠로 275전라북도 전주시 완산구 효자동3가 1215-535.810512127.092768063-226-65892001-04-01사회복지법인 동암정진남3017652022-07-25
42전라북도 전주시위드(WITH)장애인 직업재활시설 및 장애인생산품 판매시설보호작업장전라북도 전주시 덕진구 원화전1길 57-55전라북도 전주시 덕진구 화전동 71-635.890497127.071387063-244-64792006-09-25사단법인 전라북도 장애인재활협회최명호3029862022-07-25
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