Overview

Dataset statistics

Number of variables15
Number of observations146
Missing cells4
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.2 KiB
Average record size in memory127.9 B

Variable types

Categorical1
Text6
Numeric7
DateTime1

Dataset

Description장애인보호작업장 현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=1M4Z2EG8WTUF2JYL79CH25813873&infSeq=1

Alerts

소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
근로장애인정원수(명) is highly overall correlated with 종사자정원수(명) and 1 other fieldsHigh correlation
근로장애인현원수(명) is highly overall correlated with 종사자정원수(명) and 1 other fieldsHigh correlation
종사자정원수(명) is highly overall correlated with 근로장애인정원수(명) and 2 other fieldsHigh correlation
종사자현원수(명) is highly overall correlated with 근로장애인정원수(명) and 2 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
소재지도로명주소 has 4 (2.7%) missing valuesMissing
전화번호 has unique valuesUnique
근로장애인정원수(명) has 35 (24.0%) zerosZeros
근로장애인현원수(명) has 4 (2.7%) zerosZeros

Reproduction

Analysis started2023-12-10 22:38:42.613586
Analysis finished2023-12-10 22:38:47.674058
Duration5.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
수원시
12 
시흥시
11 
고양시
11 
성남시
10 
파주시
 
8
Other values (26)
94 

Length

Max length4
Median length3
Mean length3.0753425
Min length3

Unique

Unique5 ?
Unique (%)3.4%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
수원시 12
 
8.2%
시흥시 11
 
7.5%
고양시 11
 
7.5%
성남시 10
 
6.8%
파주시 8
 
5.5%
김포시 8
 
5.5%
화성시 7
 
4.8%
남양주시 7
 
4.8%
광주시 6
 
4.1%
용인시 6
 
4.1%
Other values (21) 60
41.1%

Length

2023-12-11T07:38:47.755461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 12
 
8.2%
시흥시 11
 
7.5%
고양시 11
 
7.5%
성남시 10
 
6.8%
파주시 8
 
5.5%
김포시 8
 
5.5%
화성시 7
 
4.8%
남양주시 7
 
4.8%
광주시 6
 
4.1%
용인시 6
 
4.1%
Other values (21) 60
41.1%

기관명
Text

Distinct145
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T07:38:47.980323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length8.5205479
Min length2

Characters and Unicode

Total characters1244
Distinct characters225
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)98.6%

Sample

1st row가평나눔일터
2nd row고양보호작업장
3rd row고양시구산동장애인직업재활원
4th row고양시설문동장애인직업재활원
5th row나너우리작업장
ValueCountFrequency (%)
행복한일터 2
 
1.3%
장애인보호작업장 2
 
1.3%
화성시아름장애인보호작업장 2
 
1.3%
사회복지법인 2
 
1.3%
지구촌보호작업장 1
 
0.6%
지심엘앤씨 1
 
0.6%
리드보호작업장 1
 
0.6%
양평꿈그린 1
 
0.6%
창인직업재활시설 1
 
0.6%
대한민국월남전참전자회 1
 
0.6%
Other values (144) 144
91.1%
2023-12-11T07:38:48.392881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 120
 
9.6%
업 94
 
7.6%
작 78
 
6.3%
보 72
 
5.8%
호 71
 
5.7%
인 47
 
3.8%
애 45
 
3.6%
시 28
 
2.3%
터 24
 
1.9%
리 22
 
1.8%
Other values (215) 643
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1208
97.1%
Space Separator 12
 
1.0%
Lowercase Letter 11
 
0.9%
Close Punctuation 3
 
0.2%
Decimal Number 3
 
0.2%
Open Punctuation 2
 
0.2%
Dash Punctuation 2
 
0.2%
Math Symbol 1
 
0.1%
Other Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 120
 
9.9%
업 94
 
7.8%
작 78
 
6.5%
보 72
 
6.0%
호 71
 
5.9%
인 47
 
3.9%
애 45
 
3.7%
시 28
 
2.3%
터 24
 
2.0%
리 22
 
1.8%
Other values (199) 607
50.2%
Lowercase Letter
ValueCountFrequency (%)
p 4
36.4%
a 2
18.2%
y 2
18.2%
h 1
 
9.1%
o 1
 
9.1%
n 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
9 1
33.3%
1 1
33.3%
4 1
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
H 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1207
97.0%
Common 24
 
1.9%
Latin 12
 
1.0%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 120
 
9.9%
업 94
 
7.8%
작 78
 
6.5%
보 72
 
6.0%
호 71
 
5.9%
인 47
 
3.9%
애 45
 
3.7%
시 28
 
2.3%
터 24
 
2.0%
리 22
 
1.8%
Other values (198) 606
50.2%
Common
ValueCountFrequency (%)
12
50.0%
) 3
 
12.5%
( 2
 
8.3%
- 2
 
8.3%
~ 1
 
4.2%
9 1
 
4.2%
1 1
 
4.2%
. 1
 
4.2%
4 1
 
4.2%
Latin
ValueCountFrequency (%)
p 4
33.3%
a 2
16.7%
y 2
16.7%
h 1
 
8.3%
o 1
 
8.3%
n 1
 
8.3%
H 1
 
8.3%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1207
97.0%
ASCII 36
 
2.9%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 120
 
9.9%
업 94
 
7.8%
작 78
 
6.5%
보 72
 
6.0%
호 71
 
5.9%
인 47
 
3.9%
애 45
 
3.7%
시 28
 
2.3%
터 24
 
2.0%
리 22
 
1.8%
Other values (198) 606
50.2%
ASCII
ValueCountFrequency (%)
12
33.3%
p 4
 
11.1%
) 3
 
8.3%
( 2
 
5.6%
a 2
 
5.6%
y 2
 
5.6%
- 2
 
5.6%
~ 1
 
2.8%
h 1
 
2.8%
9 1
 
2.8%
Other values (6) 6
16.7%
CJK
ValueCountFrequency (%)
愛 1
100.0%

소재지지번주소
Text

Distinct142
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T07:38:48.692842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length36
Mean length22.054795
Min length16

Characters and Unicode

Total characters3220
Distinct characters201
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

Unique139 ?
Unique (%)95.2%

Sample

1st row경기도 가평군 가평읍 대곡리 44-3번지
2nd row경기도 고양시 일산서구 탄현동 1654번지
3rd row경기도 고양시 일산서구 구산동 627-15번지
4th row경기도 고양시 일산동구 설문동 139번지
5th row경기도 고양시 덕양구 주교동 583-3번지 대양빌라, 대양빌딩
ValueCountFrequency (%)
경기도 146
 
20.9%
수원시 12
 
1.7%
고양시 11
 
1.6%
시흥시 11
 
1.6%
성남시 10
 
1.4%
상대원동 8
 
1.1%
파주시 8
 
1.1%
김포시 8
 
1.1%
중원구 8
 
1.1%
남양주시 7
 
1.0%
Other values (355) 469
67.2%
2023-12-11T07:38:49.100451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
552
 
17.1%
지 154
 
4.8%
시 153
 
4.8%
도 151
 
4.7%
기 148
 
4.6%
번 146
 
4.5%
경 146
 
4.5%
동 111
 
3.4%
- 110
 
3.4%
1 101
 
3.1%
Other values (191) 1448
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1967
61.1%
Decimal Number 584
 
18.1%
Space Separator 552
 
17.1%
Dash Punctuation 110
 
3.4%
Other Punctuation 3
 
0.1%
Uppercase Letter 3
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 154
 
7.8%
시 153
 
7.8%
도 151
 
7.7%
기 148
 
7.5%
번 146
 
7.4%
경 146
 
7.4%
동 111
 
5.6%
양 54
 
2.7%
구 53
 
2.7%
리 50
 
2.5%
Other values (174) 801
40.7%
Decimal Number
ValueCountFrequency (%)
1 101
17.3%
2 78
13.4%
3 66
11.3%
5 62
10.6%
4 56
9.6%
6 50
8.6%
9 49
8.4%
7 45
7.7%
8 43
7.4%
0 34
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
S 1
33.3%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
552
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 110
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1967
61.1%
Common 1249
38.8%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 154
 
7.8%
시 153
 
7.8%
도 151
 
7.7%
기 148
 
7.5%
번 146
 
7.4%
경 146
 
7.4%
동 111
 
5.6%
양 54
 
2.7%
구 53
 
2.7%
리 50
 
2.5%
Other values (174) 801
40.7%
Common
ValueCountFrequency (%)
552
44.2%
- 110
 
8.8%
1 101
 
8.1%
2 78
 
6.2%
3 66
 
5.3%
5 62
 
5.0%
4 56
 
4.5%
6 50
 
4.0%
9 49
 
3.9%
7 45
 
3.6%
Other values (3) 80
 
6.4%
Latin
ValueCountFrequency (%)
K 1
25.0%
n 1
25.0%
S 1
25.0%
B 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1967
61.1%
ASCII 1253
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
552
44.1%
- 110
 
8.8%
1 101
 
8.1%
2 78
 
6.2%
3 66
 
5.3%
5 62
 
4.9%
4 56
 
4.5%
6 50
 
4.0%
9 49
 
3.9%
7 45
 
3.6%
Other values (7) 84
 
6.7%
Hangul
ValueCountFrequency (%)
지 154
 
7.8%
시 153
 
7.8%
도 151
 
7.7%
기 148
 
7.5%
번 146
 
7.4%
경 146
 
7.4%
동 111
 
5.6%
양 54
 
2.7%
구 53
 
2.7%
리 50
 
2.5%
Other values (174) 801
40.7%

소재지도로명주소
Text

MISSING 

Distinct137
Distinct (%)96.5%
Missing4
Missing (%)2.7%
Memory size1.3 KiB
2023-12-11T07:38:49.349144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length19.640845
Min length13

Characters and Unicode

Total characters2789
Distinct characters186
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

Unique134 ?
Unique (%)94.4%

Sample

1st row경기도 가평군 가평읍 자라섬로 30
2nd row경기도 고양시 일산서구 탄현로 118-17
3rd row경기도 고양시 일산서구 송산로174번길 13-1
4th row경기도 고양시 일산동구 장진천길46번길 89-12
5th row경기도 고양시 덕양구 마상로114번길 22
ValueCountFrequency (%)
경기도 142
 
21.5%
수원시 12
 
1.8%
고양시 11
 
1.7%
시흥시 11
 
1.7%
성남시 10
 
1.5%
중원구 8
 
1.2%
김포시 8
 
1.2%
화성시 7
 
1.1%
파주시 7
 
1.1%
남양주시 7
 
1.1%
Other values (322) 439
66.3%
2023-12-11T07:38:49.729854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
520
18.6%
시 150
 
5.4%
기 150
 
5.4%
도 147
 
5.3%
경 146
 
5.2%
로 123
 
4.4%
1 105
 
3.8%
2 86
 
3.1%
길 56
 
2.0%
구 51
 
1.8%
Other values (176) 1255
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1724
61.8%
Space Separator 520
 
18.6%
Decimal Number 509
 
18.3%
Dash Punctuation 36
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 150
 
8.7%
기 150
 
8.7%
도 147
 
8.5%
경 146
 
8.5%
로 123
 
7.1%
길 56
 
3.2%
구 51
 
3.0%
양 50
 
2.9%
원 40
 
2.3%
번 36
 
2.1%
Other values (164) 775
45.0%
Decimal Number
ValueCountFrequency (%)
1 105
20.6%
2 86
16.9%
4 50
9.8%
3 45
8.8%
7 45
8.8%
0 39
 
7.7%
9 37
 
7.3%
5 36
 
7.1%
8 33
 
6.5%
6 33
 
6.5%
Space Separator
ValueCountFrequency (%)
520
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1724
61.8%
Common 1065
38.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 150
 
8.7%
기 150
 
8.7%
도 147
 
8.5%
경 146
 
8.5%
로 123
 
7.1%
길 56
 
3.2%
구 51
 
3.0%
양 50
 
2.9%
원 40
 
2.3%
번 36
 
2.1%
Other values (164) 775
45.0%
Common
ValueCountFrequency (%)
520
48.8%
1 105
 
9.9%
2 86
 
8.1%
4 50
 
4.7%
3 45
 
4.2%
7 45
 
4.2%
0 39
 
3.7%
9 37
 
3.5%
5 36
 
3.4%
- 36
 
3.4%
Other values (2) 66
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1724
61.8%
ASCII 1065
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
520
48.8%
1 105
 
9.9%
2 86
 
8.1%
4 50
 
4.7%
3 45
 
4.2%
7 45
 
4.2%
0 39
 
3.7%
9 37
 
3.5%
5 36
 
3.4%
- 36
 
3.4%
Other values (2) 66
 
6.2%
Hangul
ValueCountFrequency (%)
시 150
 
8.7%
기 150
 
8.7%
도 147
 
8.5%
경 146
 
8.5%
로 123
 
7.1%
길 56
 
3.2%
구 51
 
3.0%
양 50
 
2.9%
원 40
 
2.3%
번 36
 
2.1%
Other values (164) 775
45.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct135
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14056.568
Minimum10001
Maximum18631
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T07:38:49.861183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10001
5-th percentile10126.25
Q111844.75
median13957
Q316522
95-th percentile18117.75
Maximum18631
Range8630
Interquartile range (IQR)4677.25

Descriptive statistics

Standard deviation2662.0185
Coefficient of variation (CV)0.18937898
Kurtosis-1.3077099
Mean14056.568
Median Absolute Deviation (MAD)2452
Skewness0.066859986
Sum2052259
Variance7086342.7
MonotonicityNot monotonic
2023-12-11T07:38:49.972693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15455 3
 
2.1%
13207 3
 
2.1%
16522 3
 
2.1%
12918 2
 
1.4%
10048 2
 
1.4%
13204 2
 
1.4%
16681 2
 
1.4%
14086 2
 
1.4%
17177 1
 
0.7%
16816 1
 
0.7%
Other values (125) 125
85.6%
ValueCountFrequency (%)
10001 1
0.7%
10029 1
0.7%
10048 2
1.4%
10053 1
0.7%
10071 1
0.7%
10072 1
0.7%
10101 1
0.7%
10202 1
0.7%
10247 1
0.7%
10248 1
0.7%
ValueCountFrequency (%)
18631 1
0.7%
18627 1
0.7%
18533 1
0.7%
18489 1
0.7%
18329 1
0.7%
18298 1
0.7%
18279 1
0.7%
18123 1
0.7%
18102 1
0.7%
17996 1
0.7%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct145
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.442601
Minimum36.946386
Maximum38.025894
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T07:38:50.082445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.946386
5-th percentile37.071059
Q137.269239
median37.410047
Q337.64772
95-th percentile37.804683
Maximum38.025894
Range1.0795083
Interquartile range (IQR)0.37848033

Descriptive statistics

Standard deviation0.23491979
Coefficient of variation (CV)0.0062741313
Kurtosis-0.70805169
Mean37.442601
Median Absolute Deviation (MAD)0.16288323
Skewness0.12984633
Sum5466.6197
Variance0.055187309
MonotonicityNot monotonic
2023-12-11T07:38:50.201292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.26546148 2
 
1.4%
37.37906596 1
 
0.7%
37.81683537 1
 
0.7%
37.47807464 1
 
0.7%
37.48655759 1
 
0.7%
37.54527495 1
 
0.7%
37.26833163 1
 
0.7%
37.30007652 1
 
0.7%
38.0258942 1
 
0.7%
37.8201525 1
 
0.7%
Other values (135) 135
92.5%
ValueCountFrequency (%)
36.94638587 1
0.7%
36.99374291 1
0.7%
36.99994169 1
0.7%
37.00009108 1
0.7%
37.00276049 1
0.7%
37.00800019 1
0.7%
37.01726278 1
0.7%
37.06629402 1
0.7%
37.08535373 1
0.7%
37.08900774 1
0.7%
ValueCountFrequency (%)
38.0258942 1
0.7%
37.90710161 1
0.7%
37.90463712 1
0.7%
37.88235539 1
0.7%
37.86993975 1
0.7%
37.8201525 1
0.7%
37.81683537 1
0.7%
37.8057359 1
0.7%
37.80152268 1
0.7%
37.79420735 1
0.7%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct145
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.02854
Minimum126.55914
Maximum127.72621
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T07:38:50.321742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55914
5-th percentile126.70028
Q1126.83276
median127.0222
Q3127.18017
95-th percentile127.50917
Maximum127.72621
Range1.167068
Interquartile range (IQR)0.34741065

Descriptive statistics

Standard deviation0.24185755
Coefficient of variation (CV)0.0019039623
Kurtosis0.028395863
Mean127.02854
Median Absolute Deviation (MAD)0.1702987
Skewness0.50329164
Sum18546.167
Variance0.058495075
MonotonicityNot monotonic
2023-12-11T07:38:50.438924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0642782 2
 
1.4%
126.9729748 1
 
0.7%
126.9881292 1
 
0.7%
127.5489844 1
 
0.7%
127.5412519 1
 
0.7%
127.6826533 1
 
0.7%
127.7262095 1
 
0.7%
127.6593269 1
 
0.7%
127.0702459 1
 
0.7%
127.5174978 1
 
0.7%
Other values (135) 135
92.5%
ValueCountFrequency (%)
126.5591415 1
0.7%
126.5821326 1
0.7%
126.6180858 1
0.7%
126.6213035 1
0.7%
126.6226107 1
0.7%
126.659809 1
0.7%
126.6759469 1
0.7%
126.6994944 1
0.7%
126.7026314 1
0.7%
126.708534 1
0.7%
ValueCountFrequency (%)
127.7262095 1
0.7%
127.6826533 1
0.7%
127.6593269 1
0.7%
127.554094 1
0.7%
127.5489844 1
0.7%
127.5412519 1
0.7%
127.5174978 1
0.7%
127.5146475 1
0.7%
127.4927543 1
0.7%
127.3958848 1
0.7%

전화번호
Text

UNIQUE 

Distinct146
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T07:38:50.694053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.041096
Min length11

Characters and Unicode

Total characters1758
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

Unique146 ?
Unique (%)100.0%

Sample

1st row031-581-5052
2nd row031-929-1491
3rd row031-2811-8088
4th row031-977-8730
5th row031-963-4182
ValueCountFrequency (%)
031-581-5052 1
 
0.7%
031-323-3450 1
 
0.7%
031-836-4182 1
 
0.7%
031-881-2067 1
 
0.7%
031-847-4182 1
 
0.7%
031-829-9588 1
 
0.7%
031-773-7790 1
 
0.7%
031-774-3688 1
 
0.7%
031-772-7734 1
 
0.7%
031-886-3380 1
 
0.7%
Other values (136) 136
93.2%
2023-12-11T07:38:51.064721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 292
16.6%
0 255
14.5%
3 251
14.3%
1 240
13.7%
2 112
 
6.4%
6 111
 
6.3%
8 109
 
6.2%
7 100
 
5.7%
4 99
 
5.6%
9 96
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1466
83.4%
Dash Punctuation 292
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 255
17.4%
3 251
17.1%
1 240
16.4%
2 112
7.6%
6 111
7.6%
8 109
7.4%
7 100
 
6.8%
4 99
 
6.8%
9 96
 
6.5%
5 93
 
6.3%
Dash Punctuation
ValueCountFrequency (%)
- 292
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1758
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 292
16.6%
0 255
14.5%
3 251
14.3%
1 240
13.7%
2 112
 
6.4%
6 111
 
6.3%
8 109
 
6.2%
7 100
 
5.7%
4 99
 
5.6%
9 96
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1758
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 292
16.6%
0 255
14.5%
3 251
14.3%
1 240
13.7%
2 112
 
6.4%
6 111
 
6.3%
8 109
 
6.2%
7 100
 
5.7%
4 99
 
5.6%
9 96
 
5.5%

홈페이지URL
Text

Distinct76
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T07:38:51.252469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length14.821918
Min length4

Characters and Unicode

Total characters2164
Distinct characters56
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)50.7%

Sample

1st rowwww.
2nd rowhttp://www.gywork.or.kr/
3rd rowhttp://www.kygusanwork.or.kr/
4th rowwww.
5th rowwww.
ValueCountFrequency (%)
www 70
47.9%
www.masul.or.kr 2
 
1.4%
http://www.asrc.or.kr 1
 
0.7%
http://www.ajbj.co.kr 1
 
0.7%
http://www.seongsim.or.kr/working 1
 
0.7%
http://www.silleukceo.or.kr 1
 
0.7%
http://www.changinwon.or.kr 1
 
0.7%
http://www.순환보호작업장.com 1
 
0.7%
http://www.jisim.or.kr 1
 
0.7%
http://www.nscoop.or.kr 1
 
0.7%
Other values (66) 66
45.2%
2023-12-11T07:38:51.742245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 406
18.8%
. 256
11.8%
/ 210
 
9.7%
t 156
 
7.2%
o 137
 
6.3%
r 110
 
5.1%
h 107
 
4.9%
p 97
 
4.5%
: 71
 
3.3%
a 61
 
2.8%
Other values (46) 553
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1556
71.9%
Other Punctuation 537
 
24.8%
Decimal Number 47
 
2.2%
Other Letter 21
 
1.0%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 406
26.1%
t 156
 
10.0%
o 137
 
8.8%
r 110
 
7.1%
h 107
 
6.9%
p 97
 
6.2%
a 61
 
3.9%
k 57
 
3.7%
s 52
 
3.3%
c 51
 
3.3%
Other values (13) 322
20.7%
Other Letter
ValueCountFrequency (%)
일 2
 
9.5%
이 2
 
9.5%
업 1
 
4.8%
는 1
 
4.8%
터 1
 
4.8%
크 1
 
4.8%
누 1
 
4.8%
꿈 1
 
4.8%
장 1
 
4.8%
환 1
 
4.8%
Other values (9) 9
42.9%
Decimal Number
ValueCountFrequency (%)
3 11
23.4%
0 11
23.4%
1 5
10.6%
4 4
 
8.5%
9 4
 
8.5%
7 3
 
6.4%
6 3
 
6.4%
2 3
 
6.4%
5 2
 
4.3%
8 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 256
47.7%
/ 210
39.1%
: 71
 
13.2%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1556
71.9%
Common 587
 
27.1%
Hangul 21
 
1.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 406
26.1%
t 156
 
10.0%
o 137
 
8.8%
r 110
 
7.1%
h 107
 
6.9%
p 97
 
6.2%
a 61
 
3.9%
k 57
 
3.7%
s 52
 
3.3%
c 51
 
3.3%
Other values (13) 322
20.7%
Hangul
ValueCountFrequency (%)
일 2
 
9.5%
이 2
 
9.5%
업 1
 
4.8%
는 1
 
4.8%
터 1
 
4.8%
크 1
 
4.8%
누 1
 
4.8%
꿈 1
 
4.8%
장 1
 
4.8%
환 1
 
4.8%
Other values (9) 9
42.9%
Common
ValueCountFrequency (%)
. 256
43.6%
/ 210
35.8%
: 71
 
12.1%
3 11
 
1.9%
0 11
 
1.9%
1 5
 
0.9%
4 4
 
0.7%
9 4
 
0.7%
7 3
 
0.5%
6 3
 
0.5%
Other values (4) 9
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2143
99.0%
Hangul 21
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 406
18.9%
. 256
11.9%
/ 210
 
9.8%
t 156
 
7.3%
o 137
 
6.4%
r 110
 
5.1%
h 107
 
5.0%
p 97
 
4.5%
: 71
 
3.3%
a 61
 
2.8%
Other values (27) 532
24.8%
Hangul
ValueCountFrequency (%)
일 2
 
9.5%
이 2
 
9.5%
업 1
 
4.8%
는 1
 
4.8%
터 1
 
4.8%
크 1
 
4.8%
누 1
 
4.8%
꿈 1
 
4.8%
장 1
 
4.8%
환 1
 
4.8%
Other values (9) 9
42.9%

근로장애인정원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.267123
Minimum0
Maximum80
Zeros35
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T07:38:51.854352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110
median20
Q330
95-th percentile50
Maximum80
Range80
Interquartile range (IQR)20

Descriptive statistics

Standard deviation17.305088
Coefficient of variation (CV)0.81370142
Kurtosis0.34394329
Mean21.267123
Median Absolute Deviation (MAD)10
Skewness0.63645994
Sum3105
Variance299.46608
MonotonicityNot monotonic
2023-12-11T07:38:51.956380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 35
24.0%
30 30
20.5%
10 16
11.0%
20 15
10.3%
40 7
 
4.8%
15 6
 
4.1%
35 6
 
4.1%
50 4
 
2.7%
23 2
 
1.4%
38 2
 
1.4%
Other values (20) 23
15.8%
ValueCountFrequency (%)
0 35
24.0%
8 1
 
0.7%
10 16
11.0%
11 1
 
0.7%
12 1
 
0.7%
13 1
 
0.7%
15 6
 
4.1%
16 2
 
1.4%
17 1
 
0.7%
20 15
10.3%
ValueCountFrequency (%)
80 1
 
0.7%
70 2
 
1.4%
66 1
 
0.7%
56 1
 
0.7%
54 1
 
0.7%
50 4
2.7%
48 1
 
0.7%
42 1
 
0.7%
41 2
 
1.4%
40 7
4.8%

근로장애인현원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.047945
Minimum0
Maximum46
Zeros4
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T07:38:52.055256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.25
Q110
median14.5
Q320
95-th percentile31
Maximum46
Range46
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.0817651
Coefficient of variation (CV)0.50360124
Kurtosis1.1768803
Mean16.047945
Median Absolute Deviation (MAD)4.5
Skewness0.94374932
Sum2343
Variance65.314927
MonotonicityNot monotonic
2023-12-11T07:38:52.146606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
10 37
25.3%
17 9
 
6.2%
12 9
 
6.2%
16 8
 
5.5%
11 8
 
5.5%
20 7
 
4.8%
24 6
 
4.1%
13 6
 
4.1%
15 6
 
4.1%
19 6
 
4.1%
Other values (24) 44
30.1%
ValueCountFrequency (%)
0 4
 
2.7%
3 1
 
0.7%
4 1
 
0.7%
6 1
 
0.7%
8 1
 
0.7%
9 3
 
2.1%
10 37
25.3%
11 8
 
5.5%
12 9
 
6.2%
13 6
 
4.1%
ValueCountFrequency (%)
46 1
 
0.7%
39 1
 
0.7%
37 1
 
0.7%
36 1
 
0.7%
35 1
 
0.7%
34 1
 
0.7%
33 1
 
0.7%
31 2
1.4%
30 3
2.1%
29 1
 
0.7%

종사자정원수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.130137
Minimum2
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T07:38:52.230028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q14
median6.5
Q39
95-th percentile13.75
Maximum20
Range18
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.5160003
Coefficient of variation (CV)0.49311819
Kurtosis0.74453624
Mean7.130137
Median Absolute Deviation (MAD)2.5
Skewness0.91645447
Sum1041
Variance12.362258
MonotonicityNot monotonic
2023-12-11T07:38:52.315377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3 21
14.4%
8 18
12.3%
5 17
11.6%
4 17
11.6%
6 16
11.0%
9 12
8.2%
7 11
7.5%
12 8
 
5.5%
11 7
 
4.8%
10 7
 
4.8%
Other values (6) 12
8.2%
ValueCountFrequency (%)
2 2
 
1.4%
3 21
14.4%
4 17
11.6%
5 17
11.6%
6 16
11.0%
7 11
7.5%
8 18
12.3%
9 12
8.2%
10 7
 
4.8%
11 7
 
4.8%
ValueCountFrequency (%)
20 1
 
0.7%
17 2
 
1.4%
15 3
 
2.1%
14 2
 
1.4%
13 2
 
1.4%
12 8
5.5%
11 7
 
4.8%
10 7
 
4.8%
9 12
8.2%
8 18
12.3%

종사자현원수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5616438
Minimum0
Maximum19
Zeros1
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-11T07:38:52.401194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.25
Q14
median6
Q39
95-th percentile13
Maximum19
Range19
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.4799378
Coefficient of variation (CV)0.53034542
Kurtosis0.84577197
Mean6.5616438
Median Absolute Deviation (MAD)2
Skewness0.87134502
Sum958
Variance12.109967
MonotonicityNot monotonic
2023-12-11T07:38:52.489603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
3 25
17.1%
5 18
12.3%
7 17
11.6%
4 16
11.0%
8 14
9.6%
9 10
 
6.8%
6 10
 
6.8%
10 9
 
6.2%
11 8
 
5.5%
2 5
 
3.4%
Other values (8) 14
9.6%
ValueCountFrequency (%)
0 1
 
0.7%
1 2
 
1.4%
2 5
 
3.4%
3 25
17.1%
4 16
11.0%
5 18
12.3%
6 10
 
6.8%
7 17
11.6%
8 14
9.6%
9 10
 
6.8%
ValueCountFrequency (%)
19 1
 
0.7%
18 1
 
0.7%
15 2
 
1.4%
14 2
 
1.4%
13 3
 
2.1%
12 2
 
1.4%
11 8
5.5%
10 9
6.2%
9 10
6.8%
8 14
9.6%

설치신고일
Date

Distinct143
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1988-11-08 00:00:00
Maximum2022-11-29 00:00:00
2023-12-11T07:38:52.587634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:52.705907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

법인명
Text

Distinct129
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T07:38:52.889868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length11.054795
Min length2

Characters and Unicode

Total characters1614
Distinct characters220
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

Unique115 ?
Unique (%)78.8%

Sample

1st row서울특별시중증장애인복지진흥회
2nd row홀트아동복지회
3rd row해냄복지회
4th row사단법인 위캔잡
5th row사단법인 한국지적발달장애인복지협회
ValueCountFrequency (%)
사회복지법인 39
 
16.5%
사회적협동조합 24
 
10.1%
사단법인 20
 
8.4%
가온나래 3
 
1.3%
주식회사 3
 
1.3%
내일사회적협동조합 3
 
1.3%
천주교수원교구사회복지회 3
 
1.3%
함께하는세상 2
 
0.8%
휴먼복지회 2
 
0.8%
대한불교조계종사회복지재단 2
 
0.8%
Other values (124) 136
57.4%
2023-12-11T07:38:53.189489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 126
 
7.8%
사 123
 
7.6%
지 99
 
6.1%
복 92
 
5.7%
91
 
5.6%
인 83
 
5.1%
법 65
 
4.0%
단 50
 
3.1%
동 49
 
3.0%
협 45
 
2.8%
Other values (210) 791
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1513
93.7%
Space Separator 91
 
5.6%
Decimal Number 7
 
0.4%
Close Punctuation 2
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 126
 
8.3%
사 123
 
8.1%
지 99
 
6.5%
복 92
 
6.1%
인 83
 
5.5%
법 65
 
4.3%
단 50
 
3.3%
동 49
 
3.2%
협 45
 
3.0%
조 42
 
2.8%
Other values (202) 739
48.8%
Decimal Number
ValueCountFrequency (%)
2 2
28.6%
0 2
28.6%
4 1
14.3%
9 1
14.3%
1 1
14.3%
Space Separator
ValueCountFrequency (%)
91
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1513
93.7%
Common 101
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 126
 
8.3%
사 123
 
8.1%
지 99
 
6.5%
복 92
 
6.1%
인 83
 
5.5%
법 65
 
4.3%
단 50
 
3.3%
동 49
 
3.2%
협 45
 
3.0%
조 42
 
2.8%
Other values (202) 739
48.8%
Common
ValueCountFrequency (%)
91
90.1%
) 2
 
2.0%
2 2
 
2.0%
0 2
 
2.0%
4 1
 
1.0%
9 1
 
1.0%
1 1
 
1.0%
. 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1513
93.7%
ASCII 101
 
6.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 126
 
8.3%
사 123
 
8.1%
지 99
 
6.5%
복 92
 
6.1%
인 83
 
5.5%
법 65
 
4.3%
단 50
 
3.3%
동 49
 
3.2%
협 45
 
3.0%
조 42
 
2.8%
Other values (202) 739
48.8%
ASCII
ValueCountFrequency (%)
91
90.1%
) 2
 
2.0%
2 2
 
2.0%
0 2
 
2.0%
4 1
 
1.0%
9 1
 
1.0%
1 1
 
1.0%
. 1
 
1.0%

Interactions

2023-12-11T07:38:46.853059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:43.343051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:43.869811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.392839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.929313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:45.701024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:46.238553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:46.918769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:43.405000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:43.943301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.457872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.998944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:45.776454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:46.313918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:47.000337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:43.474966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.008681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.528985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:45.073511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:45.849081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:46.399511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:47.085399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:43.541845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.076238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.607723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:45.148760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:45.920316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:46.503405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:47.183629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:43.617567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.167338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.685389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:45.457677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:45.989956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:46.605165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:47.264667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:43.687082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.238269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.752030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:45.525903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:46.073768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:46.693574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:47.339217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:43.775303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.312051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:44.834864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:45.609184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:46.159697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:38:46.774347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:38:53.271217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명소재지우편번호WGS84위도WGS84경도홈페이지URL근로장애인정원수(명)근로장애인현원수(명)종사자정원수(명)종사자현원수(명)
시군명1.0000.9910.9600.9340.0000.4110.0000.2240.416
소재지우편번호0.9911.0000.9020.8490.0000.2990.0000.2090.236
WGS84위도0.9600.9021.0000.6000.0000.0000.4510.0000.042
WGS84경도0.9340.8490.6001.0000.7090.3040.2730.2300.115
홈페이지URL0.0000.0000.0000.7091.0000.9310.7970.9430.870
근로장애인정원수(명)0.4110.2990.0000.3040.9311.0000.5470.7720.828
근로장애인현원수(명)0.0000.0000.4510.2730.7970.5471.0000.8620.657
종사자정원수(명)0.2240.2090.0000.2300.9430.7720.8621.0000.841
종사자현원수(명)0.4160.2360.0420.1150.8700.8280.6570.8411.000
2023-12-11T07:38:53.374419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도근로장애인정원수(명)근로장애인현원수(명)종사자정원수(명)종사자현원수(명)시군명
소재지우편번호1.000-0.9130.2680.0720.1270.1160.1180.855
WGS84위도-0.9131.000-0.252-0.078-0.155-0.139-0.1280.709
WGS84경도0.268-0.2521.0000.0540.0330.0010.0260.629
근로장애인정원수(명)0.072-0.0780.0541.0000.4300.6650.6350.157
근로장애인현원수(명)0.127-0.1550.0330.4301.0000.7020.7030.000
종사자정원수(명)0.116-0.1390.0010.6650.7021.0000.8910.090
종사자현원수(명)0.118-0.1280.0260.6350.7030.8911.0000.149
시군명0.8550.7090.6290.1570.0000.0900.1491.000

Missing values

2023-12-11T07:38:47.448635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:38:47.605766image/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

시군명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도전화번호홈페이지URL근로장애인정원수(명)근로장애인현원수(명)종사자정원수(명)종사자현원수(명)설치신고일법인명
0가평군가평나눔일터경기도 가평군 가평읍 대곡리 44-3번지경기도 가평군 가평읍 자라섬로 301242137.820152127.517498031-581-5052www.010332020-12-04서울특별시중증장애인복지진흥회
1고양시고양보호작업장경기도 고양시 일산서구 탄현동 1654번지경기도 고양시 일산서구 탄현로 118-171024837.702231126.768413031-929-1491http://www.gywork.or.kr/401912112006-01-09홀트아동복지회
2고양시고양시구산동장애인직업재활원경기도 고양시 일산서구 구산동 627-15번지경기도 고양시 일산서구 송산로174번길 13-11020237.682961126.699494031-2811-8088http://www.kygusanwork.or.kr/2011552014-05-01해냄복지회
3고양시고양시설문동장애인직업재활원경기도 고양시 일산동구 설문동 139번지경기도 고양시 일산동구 장진천길46번길 89-121025337.714179126.813892031-977-8730www.024772019-02-01사단법인 위캔잡
4고양시나너우리작업장경기도 고양시 덕양구 주교동 583-3번지 대양빌라, 대양빌딩경기도 고양시 덕양구 마상로114번길 221045937.659743126.834904031-963-4182www.1515332007-04-09사단법인 한국지적발달장애인복지협회
5고양시늘푸른직업재활원경기도 고양시 덕양구 관산동 591번지경기도 고양시 덕양구 고골길 100-151026537.712514126.863807031-963-7489http://eg-jhw.com/3029882006-01-21사단법인 늘푸름
6고양시사무엘장애인보호작업장경기도 고양시 덕양구 성사동 704-4번지경기도 고양시 덕양구 고양대로 13871046437.654517126.838315031-978-1571www.06232018-09-18한국장애인정보화협회
7고양시오렌지보호작업장경기도 고양시 덕양구 동산동 376번지 삼송테크노밸리 330,346호경기도 고양시 덕양구 통일로 1401059437.648933126.90243602-6951-3140www.1010332022-01-27오렌지보호작업장
8고양시위메이드보호작업장경기도 고양시 덕양구 원흥동 702번지경기도 고양시 덕양구 삼원로 511055037.641138126.875725070-8150-0434www.1011432021-03-31사회적협동조합 위메이드
9고양시유앤미직업재활원경기도 고양시 일산동구 장항동 580-7번지경기도 고양시 일산동구 장대길 841043137.638131126.76744031-965-1104www.kawd.org3015862012-02-22사단법인 한국근로장애인진흥회
시군명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도전화번호홈페이지URL근로장애인정원수(명)근로장애인현원수(명)종사자정원수(명)종사자현원수(명)설치신고일법인명
136하남시반올림보호작업장경기도 하남시 풍산동 492번지경기도 하남시 조정대로 351291837.550356127.183387031-5175-4430https://dreamgoods.modoo.at/2017552019-01-02사회적협동조합나눔공동체
137하남시우리누리보호작업장경기도 하남시 덕풍동 762번지경기도 하남시 조정대로 1501293037.553167127.19458031-790-1681https://www.hknuri.co.kr2010342019-10-02사회적협동조합우리누리
138하남시하남장애인직업재활센터경기도 하남시 상산곡동 144-2번지경기도 하남시 하남대로232번길 321302637.495631127.233975031-794-2340http://www.sheltered.co.kr/382012122001-05-15사회복지법인 무형복지재단
139화성시(사)한국장애인협회생산시설경기도 화성시 양감면 사창리 195-8번지경기도 화성시 양감면 정문송산로93번길 10-11862737.101028126.98274031-351-1581www.017442013-12-30사단법인 근로복지회
140화성시더아름다운세상경기도 화성시 봉담읍 분천리 51-1번지경기도 화성시 봉담읍 최루백로 1651832937.20921126.959249031-548-4114www.013552020-12-15꿈에동산 사회적협동조합
141화성시와~우리장애인보호작업장경기도 화성시 봉담읍 동화리 197-7번지경기도 화성시 봉담읍 식골길 81829837.219908126.973261031-223-3065http://www.wauriwork.or.kr/401712102013-12-19대한예수교장로회총회복지재단
142화성시행복플러스보호작업장경기도 화성시 팔탄면 가재리 679번지경기도 화성시 팔탄면 삼천병마로 579-181853337.160876126.928393031-8059-3491http://www.2397369.com/5011882013-12-12사단법인 행복더하기
143화성시행복한일터경기도 화성시 남양읍 무송리 328번지경기도 화성시 남양읍 무하로51번길 341827937.183414126.851968031-366-9512www.masul.or.kr562112122007-03-21천주교수원교구사회복지회
144화성시화성시아름장애인보호작업장경기도 화성시 양감면 대양리 778-2번지경기도 화성시 양감면 제약단지로 2391863137.089008126.936267031-366-1770https://cafe.naver.com/hwanam9013012572016-09-22사단법인 가온나래
145화성시화성시아름장애인보호작업장 동탄점경기도 화성시 산척동 676번지경기도 화성시 동탄대로10길 17-121848937.176721127.107804031-373-3073www.3024672019-08-30사단법인 가온나래