Overview

Dataset statistics

Number of variables10
Number of observations300
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.2 KiB
Average record size in memory82.4 B

Variable types

Categorical3
Text5
Numeric2

Alerts

시설구분 is highly overall correlated with 종사자정원 and 2 other fieldsHigh correlation
월평균이용인원 is highly overall correlated with 종사자정원 and 2 other fieldsHigh correlation
종사자정원 is highly overall correlated with 종사자현원 and 2 other fieldsHigh correlation
종사자현원 is highly overall correlated with 종사자정원 and 2 other fieldsHigh correlation
시설구분 is highly imbalanced (88.0%)Imbalance
운영주체(법인명) is highly imbalanced (65.5%)Imbalance

Reproduction

Analysis started2024-03-14 00:09:12.826585
Analysis finished2024-03-14 00:09:13.805398
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct16
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
지역아동센터
285 
전라북도
 
1
전주시
 
1
군산시
 
1
익산시
 
1
Other values (11)
 
11

Length

Max length6
Median length6
Mean length5.8533333
Min length3

Unique

Unique15 ?
Unique (%)5.0%

Sample

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

Common Values

ValueCountFrequency (%)
지역아동센터 285
95.0%
전라북도 1
 
0.3%
전주시 1
 
0.3%
군산시 1
 
0.3%
익산시 1
 
0.3%
정읍시 1
 
0.3%
남원시 1
 
0.3%
김제시 1
 
0.3%
완주군 1
 
0.3%
진안군 1
 
0.3%
Other values (6) 6
 
2.0%

Length

2024-03-14T09:09:13.871271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지역아동센터 285
95.0%
전라북도 1
 
0.3%
전주시 1
 
0.3%
군산시 1
 
0.3%
익산시 1
 
0.3%
정읍시 1
 
0.3%
남원시 1
 
0.3%
김제시 1
 
0.3%
완주군 1
 
0.3%
진안군 1
 
0.3%
Other values (6) 6
 
2.0%

시설명
Text

Distinct271
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:09:14.030257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length8
Mean length8.4466667
Min length1

Characters and Unicode

Total characters2534
Distinct characters273
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)82.0%

Sample

1st row285
2nd row65
3rd row반석지역아동센터
4th row흑석나눔지역아동센터
5th row팔복동나눔지역아동센터
ValueCountFrequency (%)
6 4
 
1.3%
희망지역아동센터 3
 
1.0%
솔로몬지역아동센터 3
 
1.0%
한마음지역아동센터 2
 
0.7%
동산지역아동센터 2
 
0.7%
드림지역아동센터 2
 
0.7%
제일지역아동센터 2
 
0.7%
나눔지역아동센터 2
 
0.7%
꿈꾸는지역아동센터 2
 
0.7%
중앙지역아동센터 2
 
0.7%
Other values (261) 276
92.0%
2024-03-14T09:09:14.331190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 296
11.7%
아 294
11.6%
지 287
 
11.3%
터 286
 
11.3%
역 283
 
11.2%
센 281
 
11.1%
23
 
0.9%
나 19
 
0.7%
산 19
 
0.7%
한 16
 
0.6%
Other values (263) 730
28.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2462
97.2%
Decimal Number 33
 
1.3%
Space Separator 23
 
0.9%
Uppercase Letter 8
 
0.3%
Lowercase Letter 7
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 296
12.0%
아 294
11.9%
지 287
11.7%
터 286
11.6%
역 283
11.5%
센 281
11.4%
나 19
 
0.8%
산 19
 
0.8%
한 16
 
0.6%
리 15
 
0.6%
Other values (237) 666
27.1%
Decimal Number
ValueCountFrequency (%)
1 8
24.2%
6 6
18.2%
2 4
12.1%
5 3
 
9.1%
8 3
 
9.1%
4 2
 
6.1%
7 2
 
6.1%
3 2
 
6.1%
0 2
 
6.1%
9 1
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
12.5%
C 1
12.5%
W 1
12.5%
Y 1
12.5%
J 1
12.5%
G 1
12.5%
H 1
12.5%
Z 1
12.5%
Lowercase Letter
ValueCountFrequency (%)
p 2
28.6%
o 1
14.3%
a 1
14.3%
e 1
14.3%
n 1
14.3%
y 1
14.3%
Space Separator
ValueCountFrequency (%)
23
100.0%
Other Punctuation
ValueCountFrequency (%)
! 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2462
97.2%
Common 57
 
2.2%
Latin 15
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 296
12.0%
아 294
11.9%
지 287
11.7%
터 286
11.6%
역 283
11.5%
센 281
11.4%
나 19
 
0.8%
산 19
 
0.8%
한 16
 
0.6%
리 15
 
0.6%
Other values (237) 666
27.1%
Latin
ValueCountFrequency (%)
p 2
13.3%
A 1
 
6.7%
C 1
 
6.7%
W 1
 
6.7%
Y 1
 
6.7%
J 1
 
6.7%
G 1
 
6.7%
o 1
 
6.7%
H 1
 
6.7%
a 1
 
6.7%
Other values (4) 4
26.7%
Common
ValueCountFrequency (%)
23
40.4%
1 8
 
14.0%
6 6
 
10.5%
2 4
 
7.0%
5 3
 
5.3%
8 3
 
5.3%
4 2
 
3.5%
7 2
 
3.5%
3 2
 
3.5%
0 2
 
3.5%
Other values (2) 2
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2462
97.2%
ASCII 72
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 296
12.0%
아 294
11.9%
지 287
11.7%
터 286
11.6%
역 283
11.5%
센 281
11.4%
나 19
 
0.8%
산 19
 
0.8%
한 16
 
0.6%
리 15
 
0.6%
Other values (237) 666
27.1%
ASCII
ValueCountFrequency (%)
23
31.9%
1 8
 
11.1%
6 6
 
8.3%
2 4
 
5.6%
5 3
 
4.2%
8 3
 
4.2%
4 2
 
2.8%
p 2
 
2.8%
7 2
 
2.8%
3 2
 
2.8%
Other values (16) 17
23.6%

설치신고일
Text

Distinct258
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:09:14.571666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length9.83
Min length1

Characters and Unicode

Total characters2949
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique236 ?
Unique (%)78.7%

Sample

1st row-
2nd row-
3rd row2004.10. 8
4th row2004.11. 1
5th row2004.11. 1
ValueCountFrequency (%)
15
 
4.1%
2005 7
 
1.9%
2008 7
 
1.9%
2009 7
 
1.9%
1 6
 
1.7%
2005.12.30 5
 
1.4%
2011 5
 
1.4%
2009.12.31 5
 
1.4%
2006 5
 
1.4%
2012 4
 
1.1%
Other values (250) 297
81.8%
2024-03-14T09:09:14.936765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 775
26.3%
. 572
19.4%
2 508
17.2%
1 342
11.6%
153
 
5.2%
9 96
 
3.3%
7 88
 
3.0%
5 86
 
2.9%
8 84
 
2.8%
3 83
 
2.8%
Other values (3) 162
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2209
74.9%
Other Punctuation 572
 
19.4%
Space Separator 153
 
5.2%
Dash Punctuation 15
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 775
35.1%
2 508
23.0%
1 342
15.5%
9 96
 
4.3%
7 88
 
4.0%
5 86
 
3.9%
8 84
 
3.8%
3 83
 
3.8%
4 76
 
3.4%
6 71
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 572
100.0%
Space Separator
ValueCountFrequency (%)
153
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2949
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 775
26.3%
. 572
19.4%
2 508
17.2%
1 342
11.6%
153
 
5.2%
9 96
 
3.3%
7 88
 
3.0%
5 86
 
2.9%
8 84
 
2.8%
3 83
 
2.8%
Other values (3) 162
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2949
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 775
26.3%
. 572
19.4%
2 508
17.2%
1 342
11.6%
153
 
5.2%
9 96
 
3.3%
7 88
 
3.0%
5 86
 
2.9%
8 84
 
2.8%
3 83
 
2.8%
Other values (3) 162
 
5.5%

시설장
Text

Distinct284
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:09:15.228774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.33
Min length1

Characters and Unicode

Total characters999
Distinct characters144
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique280 ?
Unique (%)93.3%

Sample

1st row-
2nd row-
3rd row강명식
4th row류은방울
5th row편윤선
ValueCountFrequency (%)
15
 
5.0%
박희자 2
 
0.7%
최영순 2
 
0.7%
이은영 2
 
0.7%
김경숙 2
 
0.7%
송화순 2
 
0.7%
박순임 1
 
0.3%
이경진 1
 
0.3%
김경원 1
 
0.3%
조남선 1
 
0.3%
Other values (272) 272
90.4%
2024-03-14T09:09:15.603671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
131
 
13.1%
이 48
 
4.8%
김 46
 
4.6%
영 41
 
4.1%
숙 33
 
3.3%
정 30
 
3.0%
순 29
 
2.9%
희 27
 
2.7%
경 25
 
2.5%
박 23
 
2.3%
Other values (134) 566
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 853
85.4%
Space Separator 131
 
13.1%
Dash Punctuation 15
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 48
 
5.6%
김 46
 
5.4%
영 41
 
4.8%
숙 33
 
3.9%
정 30
 
3.5%
순 29
 
3.4%
희 27
 
3.2%
경 25
 
2.9%
박 23
 
2.7%
미 21
 
2.5%
Other values (132) 530
62.1%
Space Separator
ValueCountFrequency (%)
131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 853
85.4%
Common 146
 
14.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 48
 
5.6%
김 46
 
5.4%
영 41
 
4.8%
숙 33
 
3.9%
정 30
 
3.5%
순 29
 
3.4%
희 27
 
3.2%
경 25
 
2.9%
박 23
 
2.7%
미 21
 
2.5%
Other values (132) 530
62.1%
Common
ValueCountFrequency (%)
131
89.7%
- 15
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 853
85.4%
ASCII 146
 
14.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
131
89.7%
- 15
 
10.3%
Hangul
ValueCountFrequency (%)
이 48
 
5.6%
김 46
 
5.4%
영 41
 
4.8%
숙 33
 
3.9%
정 30
 
3.5%
순 29
 
3.4%
희 27
 
3.2%
경 25
 
2.9%
박 23
 
2.7%
미 21
 
2.5%
Other values (132) 530
62.1%

주 소
Text

Distinct286
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:09:15.906707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length15.653333
Min length1

Characters and Unicode

Total characters4696
Distinct characters233
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique285 ?
Unique (%)95.0%

Sample

1st row-
2nd row-
3rd row전주시 덕진구 석소로 5-14
4th row전주시 완산구 흑석로 84-38
5th row전주시 덕진구 기린대로 708
ValueCountFrequency (%)
전주시 65
 
6.2%
군산시 49
 
4.6%
익산시 39
 
3.7%
완산구 38
 
3.6%
정읍시 29
 
2.8%
덕진구 27
 
2.6%
남원시 25
 
2.4%
15
 
1.4%
완주군 11
 
1.0%
김제시 10
 
0.9%
Other values (602) 746
70.8%
2024-03-14T09:09:16.322138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
757
 
16.1%
시 230
 
4.9%
1 228
 
4.9%
산 168
 
3.6%
2 165
 
3.5%
- 141
 
3.0%
동 124
 
2.6%
길 122
 
2.6%
로 119
 
2.5%
3 102
 
2.2%
Other values (223) 2540
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2635
56.1%
Decimal Number 990
 
21.1%
Space Separator 757
 
16.1%
Dash Punctuation 141
 
3.0%
Open Punctuation 73
 
1.6%
Close Punctuation 73
 
1.6%
Other Punctuation 26
 
0.6%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 230
 
8.7%
산 168
 
6.4%
동 124
 
4.7%
길 122
 
4.6%
로 119
 
4.5%
군 100
 
3.8%
주 91
 
3.5%
구 80
 
3.0%
전 71
 
2.7%
면 67
 
2.5%
Other values (204) 1463
55.5%
Decimal Number
ValueCountFrequency (%)
1 228
23.0%
2 165
16.7%
3 102
10.3%
5 87
 
8.8%
4 82
 
8.3%
6 78
 
7.9%
0 69
 
7.0%
7 67
 
6.8%
8 62
 
6.3%
9 50
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 14
53.8%
@ 8
30.8%
/ 3
 
11.5%
. 1
 
3.8%
Space Separator
ValueCountFrequency (%)
757
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 141
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2635
56.1%
Common 2060
43.9%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 230
 
8.7%
산 168
 
6.4%
동 124
 
4.7%
길 122
 
4.6%
로 119
 
4.5%
군 100
 
3.8%
주 91
 
3.5%
구 80
 
3.0%
전 71
 
2.7%
면 67
 
2.5%
Other values (204) 1463
55.5%
Common
ValueCountFrequency (%)
757
36.7%
1 228
 
11.1%
2 165
 
8.0%
- 141
 
6.8%
3 102
 
5.0%
5 87
 
4.2%
4 82
 
4.0%
6 78
 
3.8%
( 73
 
3.5%
) 73
 
3.5%
Other values (8) 274
 
13.3%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2635
56.1%
ASCII 2061
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
757
36.7%
1 228
 
11.1%
2 165
 
8.0%
- 141
 
6.8%
3 102
 
4.9%
5 87
 
4.2%
4 82
 
4.0%
6 78
 
3.8%
( 73
 
3.5%
) 73
 
3.5%
Other values (9) 275
 
13.3%
Hangul
ValueCountFrequency (%)
시 230
 
8.7%
산 168
 
6.4%
동 124
 
4.7%
길 122
 
4.6%
로 119
 
4.5%
군 100
 
3.8%
주 91
 
3.5%
구 80
 
3.0%
전 71
 
2.7%
면 67
 
2.5%
Other values (204) 1463
55.5%

전화번호
Text

Distinct286
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:09:16.524149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length8
Mean length8.61
Min length1

Characters and Unicode

Total characters2583
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique284 ?
Unique (%)94.7%

Sample

1st row-
2nd row-
3rd row242-2291
4th row232-8219
5th row214-9002
ValueCountFrequency (%)
15
 
5.0%
854-8663 2
 
0.7%
652-0333 1
 
0.3%
533-9962 1
 
0.3%
635-7005 1
 
0.3%
633-0070 1
 
0.3%
535-9061 1
 
0.3%
633-8889 1
 
0.3%
538-9979 1
 
0.3%
927-3304 1
 
0.3%
Other values (275) 275
91.7%
2024-03-14T09:09:16.822966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 335
13.0%
3 298
11.5%
2 285
11.0%
0 239
9.3%
5 231
8.9%
4 231
8.9%
6 212
8.2%
8 185
7.2%
1 185
7.2%
7 148
5.7%
Other values (4) 234
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2143
83.0%
Dash Punctuation 335
 
13.0%
Space Separator 96
 
3.7%
Close Punctuation 7
 
0.3%
Other Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 298
13.9%
2 285
13.3%
0 239
11.2%
5 231
10.8%
4 231
10.8%
6 212
9.9%
8 185
8.6%
1 185
8.6%
7 148
6.9%
9 129
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 335
100.0%
Space Separator
ValueCountFrequency (%)
96
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2583
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 335
13.0%
3 298
11.5%
2 285
11.0%
0 239
9.3%
5 231
8.9%
4 231
8.9%
6 212
8.2%
8 185
7.2%
1 185
7.2%
7 148
5.7%
Other values (4) 234
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2583
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 335
13.0%
3 298
11.5%
2 285
11.0%
0 239
9.3%
5 231
8.9%
4 231
8.9%
6 212
8.2%
8 185
7.2%
1 185
7.2%
7 148
5.7%
Other values (4) 234
9.1%

종사자정원
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.05
Minimum1
Maximum605
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-14T09:09:16.925088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median2
Q32
95-th percentile3.2
Maximum605
Range604
Interquartile range (IQR)0

Descriptive statistics

Standard deviation36.959358
Coefficient of variation (CV)6.1089848
Kurtosis233.35081
Mean6.05
Median Absolute Deviation (MAD)0
Skewness14.653649
Sum1815
Variance1365.9941
MonotonicityNot monotonic
2024-03-14T09:09:17.025235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 222
74.0%
3 49
 
16.3%
1 14
 
4.7%
12 3
 
1.0%
605 1
 
0.3%
27 1
 
0.3%
7 1
 
0.3%
8 1
 
0.3%
14 1
 
0.3%
21 1
 
0.3%
Other values (6) 6
 
2.0%
ValueCountFrequency (%)
1 14
 
4.7%
2 222
74.0%
3 49
 
16.3%
7 1
 
0.3%
8 1
 
0.3%
12 3
 
1.0%
14 1
 
0.3%
21 1
 
0.3%
23 1
 
0.3%
27 1
 
0.3%
ValueCountFrequency (%)
605 1
0.3%
136 1
0.3%
126 1
0.3%
94 1
0.3%
59 1
0.3%
54 1
0.3%
27 1
0.3%
23 1
0.3%
21 1
0.3%
14 1
0.3%

종사자현원
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.05
Minimum1
Maximum605
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-14T09:09:17.132645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median2
Q32
95-th percentile3.2
Maximum605
Range604
Interquartile range (IQR)0

Descriptive statistics

Standard deviation36.959358
Coefficient of variation (CV)6.1089848
Kurtosis233.35081
Mean6.05
Median Absolute Deviation (MAD)0
Skewness14.653649
Sum1815
Variance1365.9941
MonotonicityNot monotonic
2024-03-14T09:09:17.237905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 222
74.0%
3 49
 
16.3%
1 14
 
4.7%
12 3
 
1.0%
605 1
 
0.3%
27 1
 
0.3%
7 1
 
0.3%
8 1
 
0.3%
14 1
 
0.3%
21 1
 
0.3%
Other values (6) 6
 
2.0%
ValueCountFrequency (%)
1 14
 
4.7%
2 222
74.0%
3 49
 
16.3%
7 1
 
0.3%
8 1
 
0.3%
12 3
 
1.0%
14 1
 
0.3%
21 1
 
0.3%
23 1
 
0.3%
27 1
 
0.3%
ValueCountFrequency (%)
605 1
0.3%
136 1
0.3%
126 1
0.3%
94 1
0.3%
59 1
0.3%
54 1
0.3%
27 1
0.3%
23 1
0.3%
21 1
0.3%
14 1
0.3%

월평균이용인원
Categorical

HIGH CORRELATION 

Distinct49
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
29
81 
19
38 
26
18 
25
16 
28
14 
Other values (44)
133 

Length

Max length5
Median length2
Mean length2.0333333
Min length1

Unique

Unique23 ?
Unique (%)7.7%

Sample

1st row7,503
2nd row1,759
3rd row40
4th row26
5th row29

Common Values

ValueCountFrequency (%)
29 81
27.0%
19 38
12.7%
26 18
 
6.0%
25 16
 
5.3%
28 14
 
4.7%
24 14
 
4.7%
27 12
 
4.0%
35 12
 
4.0%
9 11
 
3.7%
40 7
 
2.3%
Other values (39) 77
25.7%

Length

2024-03-14T09:09:17.341863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
29 81
27.0%
19 38
12.7%
26 18
 
6.0%
25 16
 
5.3%
28 14
 
4.7%
24 14
 
4.7%
27 12
 
4.0%
35 12
 
4.0%
9 11
 
3.7%
40 7
 
2.3%
Other values (39) 77
25.7%

운영주체(법인명)
Categorical

IMBALANCE 

Distinct47
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
개인
231 
-
 
15
대한성공회유지재단
 
4
한기장복지재단
 
3
삼육재단
 
2
Other values (42)
45 

Length

Max length21
Median length2
Mean length3.3933333
Min length1

Unique

Unique39 ?
Unique (%)13.0%

Sample

1st row-
2nd row-
3rd row개인
4th row대한성공회유지재단
5th row대한성공회유지재단

Common Values

ValueCountFrequency (%)
개인 231
77.0%
- 15
 
5.0%
대한성공회유지재단 4
 
1.3%
한기장복지재단 3
 
1.0%
삼육재단 2
 
0.7%
제칠일안식일교회 2
 
0.7%
사회복지법인 한기장복지재단 2
 
0.7%
사회복지법인 삼동회 2
 
0.7%
구세군유지재단 1
 
0.3%
사회복지법인어린이재단 1
 
0.3%
Other values (37) 37
 
12.3%

Length

2024-03-14T09:09:17.445431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
개인 232
73.9%
15
 
4.8%
사회복지법인 6
 
1.9%
한기장복지재단 5
 
1.6%
대한성공회유지재단 4
 
1.3%
삼육재단 2
 
0.6%
제칠일안식일교회 2
 
0.6%
삼동회 2
 
0.6%
유지재단 2
 
0.6%
전북장애인부 1
 
0.3%
Other values (43) 43
 
13.7%

Interactions

2024-03-14T09:09:13.407465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:09:13.278980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:09:13.499894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:09:13.343936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:09:17.515028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분종사자정원종사자현원월평균이용인원운영주체(법인명)
시설구분1.0001.0001.0001.0000.000
종사자정원1.0001.0001.0001.0000.000
종사자현원1.0001.0001.0001.0000.000
월평균이용인원1.0001.0001.0001.0000.000
운영주체(법인명)0.0000.0000.0000.0001.000
2024-03-14T09:09:17.597639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분월평균이용인원운영주체(법인명)
시설구분1.0000.9400.000
월평균이용인원0.9401.0000.000
운영주체(법인명)0.0000.0001.000
2024-03-14T09:09:17.685879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종사자정원종사자현원시설구분월평균이용인원운영주체(법인명)
종사자정원1.0001.0000.9800.9210.000
종사자현원1.0001.0000.9800.9210.000
시설구분0.9800.9801.0000.9400.000
월평균이용인원0.9210.9210.9401.0000.000
운영주체(법인명)0.0000.0000.0000.0001.000

Missing values

2024-03-14T09:09:13.612971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:09:13.752430image/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

시설구분시설명설치신고일시설장주 소전화번호종사자정원종사자현원월평균이용인원운영주체(법인명)
0전라북도285----6056057,503-
1전주시65----1361361,759-
2지역아동센터반석지역아동센터2004.10. 8강명식전주시 덕진구 석소로 5-14242-22913340개인
3지역아동센터흑석나눔지역아동센터2004.11. 1류은방울전주시 완산구 흑석로 84-38232-82192226대한성공회유지재단
4지역아동센터팔복동나눔지역아동센터2004.11. 1편윤선전주시 덕진구 기린대로 708214-90022229대한성공회유지재단
5지역아동센터한사랑지역아동센터2004.11.17박영철전주시 완산구 쑥고개로 241-8221-08182226개인
6지역아동센터프란치스코지역아동센터2004.12. 2이순남전주시 덕진구 편운로 26-1214-40422229전주카톨릭사회복지회
7지역아동센터푸른지역아동센터2004.12.14정진순전주시 완산구 거마남로 77228-45452229개인
8지역아동센터전주지역아동센터2004.12.14설민자전주시 덕진구 매봉로 40273-36902229개인
9지역아동센터단비지역아동센터2004.12.29서정혜전주시 완산구 흑석로 70282-72332219사회복지법인어린이재단
시설구분시설명설치신고일시설장주 소전화번호종사자정원종사자현원월평균이용인원운영주체(법인명)
290지역아동센터고창지역아동센터2011.3.29유복례고창읍 성산2길 23번지 2층561-39272229개인
291지역아동센터다아솜지역아동센터2011.11.9김설영부안면 복분자로 916-1070-4153-23602216개인
292지역아동센터써미트지역아동센터2012.3.16최만심고창읍 월곡공원2길 37562-37092221개인
293부안군6----77174-
294지역아동센터운호지역아동센터2005.07.29최은숙부안군 진서면 청자로 429-8063-582-75831129개인
295지역아동센터도청지역아동센터2005.10.17강신옥부안군 변산면 도유로 1063-582-8791119개인
296지역아동센터창북지역아동센터2008.02.01김효정부안군 계화면 창북안길 7-28063-581-10861129개인
297지역아동센터부안지역아동센터2008.11.28박상원부안군 부안읍 석제길 5063-584-20042249개인
298지역아동센터아름드리지역아동센터2008.11.11이해범부안군 백산면 임현로 8063-582-03931129개인
299지역아동센터다니엘지역아동센터2009.09.16김경숙부안군 부안읍 부풍로 38063-581-91521129개인