Overview

Dataset statistics

Number of variables14
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory118.9 B

Variable types

Numeric3
Categorical5
Text5
DateTime1

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 시군명High correlation
우편번호 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 has unique valuesUnique
명칭 has unique valuesUnique
도로명주소 has unique valuesUnique
대표자 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 02:32:46.940647
Analysis finished2024-03-14 02:32:48.302146
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.5
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-14T11:32:48.360120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.25
Q112.25
median23.5
Q334.75
95-th percentile43.75
Maximum46
Range45
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation13.422618
Coefficient of variation (CV)0.57117522
Kurtosis-1.2
Mean23.5
Median Absolute Deviation (MAD)11.5
Skewness0
Sum1081
Variance180.16667
MonotonicityStrictly increasing
2024-03-14T11:32:48.479839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 1
 
2.2%
36 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
34 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
46 1
2.2%
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%

시군명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)23.9%
Missing0
Missing (%)0.0%
Memory size500.0 B
전주시
21 
익산시
8 
군산시
5 
정읍시
3 
남원시
 
2
Other values (6)
7 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique5 ?
Unique (%)10.9%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 21
45.7%
익산시 8
 
17.4%
군산시 5
 
10.9%
정읍시 3
 
6.5%
남원시 2
 
4.3%
김제시 2
 
4.3%
완주군 1
 
2.2%
장수군 1
 
2.2%
순창군 1
 
2.2%
고창군 1
 
2.2%

Length

2024-03-14T11:32:48.601237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 21
45.7%
익산시 8
 
17.4%
군산시 5
 
10.9%
정읍시 3
 
6.5%
남원시 2
 
4.3%
김제시 2
 
4.3%
완주군 1
 
2.2%
장수군 1
 
2.2%
순창군 1
 
2.2%
고창군 1
 
2.2%

명칭
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T11:32:48.818081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length13.913043
Min length4

Characters and Unicode

Total characters640
Distinct characters90
Distinct categories3 ?
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 row전주성모간호요양보호사교육원
2nd row목민요양보호사교육원
3rd row탑클래스
4th row전주성신간호학원 부설 요양보호사교육원
5th row온누리요양보호사교육원
ValueCountFrequency (%)
요양보호사교육원 11
 
17.2%
부설 5
 
7.8%
평화요양보호사교육원 2
 
3.1%
전주성모간호요양보호사교육원 1
 
1.6%
제이성모요양보호사교육원 1
 
1.6%
고창요양보호사교육원 1
 
1.6%
군산여성인력개발센터 1
 
1.6%
익산간호요양보호사교육원 1
 
1.6%
이리간호교육원 1
 
1.6%
원광보건대학평생교육원요양보호사교육원 1
 
1.6%
Other values (39) 39
60.9%
2024-03-14T11:32:49.221010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 65
 
10.2%
호 64
 
10.0%
교 49
 
7.7%
육 48
 
7.5%
양 46
 
7.2%
보 46
 
7.2%
요 45
 
7.0%
사 45
 
7.0%
간 18
 
2.8%
18
 
2.8%
Other values (80) 196
30.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 620
96.9%
Space Separator 18
 
2.8%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 65
 
10.5%
호 64
 
10.3%
교 49
 
7.9%
육 48
 
7.7%
양 46
 
7.4%
보 46
 
7.4%
요 45
 
7.3%
사 45
 
7.3%
간 18
 
2.9%
학 16
 
2.6%
Other values (77) 178
28.7%
Uppercase Letter
ValueCountFrequency (%)
J 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 620
96.9%
Common 18
 
2.8%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 65
 
10.5%
호 64
 
10.3%
교 49
 
7.9%
육 48
 
7.7%
양 46
 
7.4%
보 46
 
7.4%
요 45
 
7.3%
사 45
 
7.3%
간 18
 
2.9%
학 16
 
2.6%
Other values (77) 178
28.7%
Latin
ValueCountFrequency (%)
J 1
50.0%
K 1
50.0%
Common
ValueCountFrequency (%)
18
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 620
96.9%
ASCII 20
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 65
 
10.5%
호 64
 
10.3%
교 49
 
7.9%
육 48
 
7.7%
양 46
 
7.4%
보 46
 
7.4%
요 45
 
7.3%
사 45
 
7.3%
간 18
 
2.9%
학 16
 
2.6%
Other values (77) 178
28.7%
ASCII
ValueCountFrequency (%)
18
90.0%
J 1
 
5.0%
K 1
 
5.0%

도로명주소
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T11:32:49.450842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length15.782609
Min length10

Characters and Unicode

Total characters726
Distinct characters104
Distinct categories6 ?
Distinct scripts2 ?
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 row전주시 완산구 어진길 114
2nd row전주시 완산구 용머리로 203
3rd row전주시 완산구 팔달로 212-8 (경원동3가)
4th row전주시 완산구 팔달로 250
5th row전주시 완산구 팔달로 202-16 (3층)
ValueCountFrequency (%)
전주시 21
 
11.6%
완산구 13
 
7.2%
익산시 8
 
4.4%
덕진구 8
 
4.4%
군산시 5
 
2.8%
익산대로 4
 
2.2%
무왕로 4
 
2.2%
팔달로 3
 
1.7%
장승배기로 3
 
1.7%
정읍시 3
 
1.7%
Other values (103) 109
60.2%
2024-03-14T11:32:49.842825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135
18.6%
로 43
 
5.9%
시 41
 
5.6%
1 33
 
4.5%
산 31
 
4.3%
2 25
 
3.4%
전 23
 
3.2%
주 23
 
3.2%
구 21
 
2.9%
동 15
 
2.1%
Other values (94) 336
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 417
57.4%
Decimal Number 139
 
19.1%
Space Separator 135
 
18.6%
Open Punctuation 14
 
1.9%
Close Punctuation 14
 
1.9%
Dash Punctuation 7
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 43
 
10.3%
시 41
 
9.8%
산 31
 
7.4%
전 23
 
5.5%
주 23
 
5.5%
구 21
 
5.0%
동 15
 
3.6%
완 14
 
3.4%
익 12
 
2.9%
덕 10
 
2.4%
Other values (80) 184
44.1%
Decimal Number
ValueCountFrequency (%)
1 33
23.7%
2 25
18.0%
3 15
10.8%
4 13
 
9.4%
0 12
 
8.6%
7 11
 
7.9%
6 9
 
6.5%
5 8
 
5.8%
8 8
 
5.8%
9 5
 
3.6%
Space Separator
ValueCountFrequency (%)
135
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 417
57.4%
Common 309
42.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 43
 
10.3%
시 41
 
9.8%
산 31
 
7.4%
전 23
 
5.5%
주 23
 
5.5%
구 21
 
5.0%
동 15
 
3.6%
완 14
 
3.4%
익 12
 
2.9%
덕 10
 
2.4%
Other values (80) 184
44.1%
Common
ValueCountFrequency (%)
135
43.7%
1 33
 
10.7%
2 25
 
8.1%
3 15
 
4.9%
( 14
 
4.5%
) 14
 
4.5%
4 13
 
4.2%
0 12
 
3.9%
7 11
 
3.6%
6 9
 
2.9%
Other values (4) 28
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 417
57.4%
ASCII 309
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135
43.7%
1 33
 
10.7%
2 25
 
8.1%
3 15
 
4.9%
( 14
 
4.5%
) 14
 
4.5%
4 13
 
4.2%
0 12
 
3.9%
7 11
 
3.6%
6 9
 
2.9%
Other values (4) 28
 
9.1%
Hangul
ValueCountFrequency (%)
로 43
 
10.3%
시 41
 
9.8%
산 31
 
7.4%
전 23
 
5.5%
주 23
 
5.5%
구 21
 
5.0%
동 15
 
3.6%
완 14
 
3.4%
익 12
 
2.9%
덕 10
 
2.4%
Other values (80) 184
44.1%

대표자
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T11:32:50.077223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.3478261
Min length3

Characters and Unicode

Total characters154
Distinct characters69
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

Unique46 ?
Unique (%)100.0%

Sample

1st row윤석길
2nd row김옥숙
3rd row송제기
4th row이연주
5th row박흥순
ValueCountFrequency (%)
윤석길 1
 
2.2%
이태영 1
 
2.2%
김재홍 1
 
2.2%
백지연 1
 
2.2%
기성옥 1
 
2.2%
지정무 1
 
2.2%
김인종 1
 
2.2%
정선희 1
 
2.2%
오순옥 1
 
2.2%
권선숙 1
 
2.2%
Other values (36) 36
78.3%
2024-03-14T11:32:50.534694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 11
 
7.1%
박 9
 
5.8%
성 9
 
5.8%
이 7
 
4.5%
김 7
 
4.5%
기 5
 
3.2%
숙 5
 
3.2%
순 4
 
2.6%
옥 4
 
2.6%
선 4
 
2.6%
Other values (59) 89
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151
98.1%
Other Punctuation 1
 
0.6%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 11
 
7.3%
박 9
 
6.0%
성 9
 
6.0%
이 7
 
4.6%
김 7
 
4.6%
기 5
 
3.3%
숙 5
 
3.3%
순 4
 
2.6%
옥 4
 
2.6%
선 4
 
2.6%
Other values (56) 86
57.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151
98.1%
Common 3
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 11
 
7.3%
박 9
 
6.0%
성 9
 
6.0%
이 7
 
4.6%
김 7
 
4.6%
기 5
 
3.3%
숙 5
 
3.3%
순 4
 
2.6%
옥 4
 
2.6%
선 4
 
2.6%
Other values (56) 86
57.0%
Common
ValueCountFrequency (%)
, 1
33.3%
( 1
33.3%
) 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151
98.1%
ASCII 3
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 11
 
7.3%
박 9
 
6.0%
성 9
 
6.0%
이 7
 
4.6%
김 7
 
4.6%
기 5
 
3.3%
숙 5
 
3.3%
순 4
 
2.6%
옥 4
 
2.6%
선 4
 
2.6%
Other values (56) 86
57.0%
ASCII
ValueCountFrequency (%)
, 1
33.3%
( 1
33.3%
) 1
33.3%

지정일
Date

Distinct36
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum2008-02-19 00:00:00
Maximum2015-06-29 00:00:00
2024-03-14T11:32:50.634463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:32:50.725775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)

정원
Real number (ℝ)

Distinct10
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.782609
Minimum15
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-14T11:32:51.089365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile17
Q130
median30
Q340
95-th percentile40
Maximum40
Range25
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.0990235
Coefficient of variation (CV)0.22336189
Kurtosis0.080534986
Mean31.782609
Median Absolute Deviation (MAD)5
Skewness-0.62772079
Sum1462
Variance50.396135
MonotonicityNot monotonic
2024-03-14T11:32:51.171315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
30 20
43.5%
40 14
30.4%
35 2
 
4.3%
20 2
 
4.3%
15 2
 
4.3%
25 2
 
4.3%
26 1
 
2.2%
16 1
 
2.2%
36 1
 
2.2%
34 1
 
2.2%
ValueCountFrequency (%)
15 2
 
4.3%
16 1
 
2.2%
20 2
 
4.3%
25 2
 
4.3%
26 1
 
2.2%
30 20
43.5%
34 1
 
2.2%
35 2
 
4.3%
36 1
 
2.2%
40 14
30.4%
ValueCountFrequency (%)
40 14
30.4%
36 1
 
2.2%
35 2
 
4.3%
34 1
 
2.2%
30 20
43.5%
26 1
 
2.2%
25 2
 
4.3%
20 2
 
4.3%
16 1
 
2.2%
15 2
 
4.3%

전화번호
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T11:32:51.360222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length12
Mean length12.413043
Min length1

Characters and Unicode

Total characters571
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

Unique46 ?
Unique (%)100.0%

Sample

1st row063-283-6662~5
2nd row063-229-3144
3rd row063-282-6500
4th row063-285-1999, 063-285-1990
5th row063-231-4554
ValueCountFrequency (%)
063-283-6662~5 1
 
2.1%
063-272-4747 1
 
2.1%
063-563-0038 1
 
2.1%
063-468-0055 1
 
2.1%
063-858-9840 1
 
2.1%
063-851-2411 1
 
2.1%
063-840-1534 1
 
2.1%
063-853-8331 1
 
2.1%
063-852-0129 1
 
2.1%
063-857-7698 1
 
2.1%
Other values (38) 38
79.2%
2024-03-14T11:32:51.663967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 95
16.6%
3 82
14.4%
0 73
12.8%
6 72
12.6%
2 62
10.9%
8 37
 
6.5%
5 36
 
6.3%
4 30
 
5.3%
1 29
 
5.1%
9 26
 
4.6%
Other values (4) 29
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 471
82.5%
Dash Punctuation 95
 
16.6%
Other Punctuation 2
 
0.4%
Space Separator 2
 
0.4%
Math Symbol 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 82
17.4%
0 73
15.5%
6 72
15.3%
2 62
13.2%
8 37
7.9%
5 36
7.6%
4 30
 
6.4%
1 29
 
6.2%
9 26
 
5.5%
7 24
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 95
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 571
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 95
16.6%
3 82
14.4%
0 73
12.8%
6 72
12.6%
2 62
10.9%
8 37
 
6.5%
5 36
 
6.3%
4 30
 
5.3%
1 29
 
5.1%
9 26
 
4.6%
Other values (4) 29
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 571
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 95
16.6%
3 82
14.4%
0 73
12.8%
6 72
12.6%
2 62
10.9%
8 37
 
6.5%
5 36
 
6.3%
4 30
 
5.3%
1 29
 
5.1%
9 26
 
4.6%
Other values (4) 29
 
5.1%

FAX
Text

Distinct44
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-03-14T11:32:51.840896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.282609
Min length1

Characters and Unicode

Total characters519
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

Unique43 ?
Unique (%)93.5%

Sample

1st row063-286-6661
2nd row063-229-3147
3rd row063-282-6501
4th row063-285-6991
5th row063-231-4553
ValueCountFrequency (%)
3
 
6.5%
063-445-5056 1
 
2.2%
063-833-3372 1
 
2.2%
063-468-0058 1
 
2.2%
063-858-9841 1
 
2.2%
063-842-2411 1
 
2.2%
063-840-1530 1
 
2.2%
063-853-8334 1
 
2.2%
063-852-0139 1
 
2.2%
063-837-7698 1
 
2.2%
Other values (34) 34
73.9%
2024-03-14T11:32:52.137652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 89
17.1%
3 78
15.0%
6 68
13.1%
0 65
12.5%
2 53
10.2%
8 33
 
6.4%
1 33
 
6.4%
5 32
 
6.2%
4 26
 
5.0%
7 21
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 430
82.9%
Dash Punctuation 89
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 78
18.1%
6 68
15.8%
0 65
15.1%
2 53
12.3%
8 33
7.7%
1 33
7.7%
5 32
7.4%
4 26
 
6.0%
7 21
 
4.9%
9 21
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 519
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 89
17.1%
3 78
15.0%
6 68
13.1%
0 65
12.5%
2 53
10.2%
8 33
 
6.4%
1 33
 
6.4%
5 32
 
6.2%
4 26
 
5.0%
7 21
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 519
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 89
17.1%
3 78
15.0%
6 68
13.1%
0 65
12.5%
2 53
10.2%
8 33
 
6.4%
1 33
 
6.4%
5 32
 
6.2%
4 26
 
5.0%
7 21
 
4.0%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55017
Minimum54085
Maximum56436
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-03-14T11:32:52.267599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54085
5-th percentile54132.25
Q154649.25
median54992
Q355122
95-th percentile56177
Maximum56436
Range2351
Interquartile range (IQR)472.75

Descriptive statistics

Standard deviation610.14701
Coefficient of variation (CV)0.011090154
Kurtosis0.06484497
Mean55017
Median Absolute Deviation (MAD)330
Skewness0.7189431
Sum2530782
Variance372279.38
MonotonicityNot monotonic
2024-03-14T11:32:52.381672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
55039 2
 
4.3%
55000 2
 
4.3%
54545 2
 
4.3%
55122 2
 
4.3%
56165 2
 
4.3%
54893 2
 
4.3%
54662 2
 
4.3%
55764 1
 
2.2%
54536 1
 
2.2%
54645 1
 
2.2%
Other values (29) 29
63.0%
ValueCountFrequency (%)
54085 1
2.2%
54130 1
2.2%
54131 1
2.2%
54136 1
2.2%
54143 1
2.2%
54321 1
2.2%
54392 1
2.2%
54536 1
2.2%
54545 2
4.3%
54554 1
2.2%
ValueCountFrequency (%)
56436 1
2.2%
56315 1
2.2%
56181 1
2.2%
56165 2
4.3%
56038 1
2.2%
55764 1
2.2%
55763 1
2.2%
55615 1
2.2%
55326 1
2.2%
55123 1
2.2%

자료출처
Categorical

CONSTANT 

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

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노인장애인복지과 46
100.0%

Length

2024-03-14T11:32:52.513025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:32:52.675776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인장애인복지과 46
100.0%

공개여부
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 46
100.0%

Length

2024-03-14T11:32:52.780533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:32:52.846709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 46
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
2015.1
46 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 46
100.0%

Length

2024-03-14T11:32:52.916220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:32:52.982529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 46
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
1년
46 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 46
100.0%

Length

2024-03-14T11:32:53.052201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:32:53.119998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 46
100.0%

Interactions

2024-03-14T11:32:47.732379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:32:47.324476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:32:47.527053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:32:47.804457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:32:47.388169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:32:47.591720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:32:47.873540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:32:47.465778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:32:47.665970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:32:53.169457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명명칭도로명주소대표자지정일정원전화번호FAX우편번호
순번1.0000.8161.0001.0001.0000.7510.1321.0000.8890.886
시군명0.8161.0001.0001.0001.0000.8610.3861.0000.0000.966
명칭1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대표자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지정일0.7510.8611.0001.0001.0001.0000.9091.0000.8850.923
정원0.1320.3861.0001.0001.0000.9091.0001.0000.8730.545
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
FAX0.8890.0001.0001.0001.0000.8850.8731.0001.0000.630
우편번호0.8860.9661.0001.0001.0000.9230.5451.0000.6301.000
2024-03-14T11:32:53.278543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번정원우편번호시군명
순번1.0000.1370.1310.502
정원0.1371.000-0.1870.181
우편번호0.131-0.1871.0000.847
시군명0.5020.1810.8471.000

Missing values

2024-03-14T11:32:48.007278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:32:48.219260image/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

순번시군명명칭도로명주소대표자지정일정원전화번호FAX우편번호자료출처공개여부작성일갱신주기
01전주시전주성모간호요양보호사교육원전주시 완산구 어진길 114윤석길2008-02-2835063-283-6662~5063-286-666155039노인장애인복지과공개2015.11년
12전주시목민요양보호사교육원전주시 완산구 용머리로 203김옥숙2009-09-0630063-229-3144063-229-314755048노인장애인복지과공개2015.11년
23전주시탑클래스전주시 완산구 팔달로 212-8 (경원동3가)송제기2010-09-0940063-282-6500063-282-650155000노인장애인복지과공개2015.11년
34전주시전주성신간호학원 부설 요양보호사교육원전주시 완산구 팔달로 250이연주2010-10-2040063-285-1999, 063-285-1990063-285-699154995노인장애인복지과공개2015.11년
45전주시온누리요양보호사교육원전주시 완산구 팔달로 202-16 (3층)박흥순2010-10-2030063-231-4554063-231-455355000노인장애인복지과공개2015.11년
56전주시전주요양보호사교육원전주시 덕진구 떡전 4길 8 (금암동)신성호2010-10-2030063-284-1199063-232-800154932노인장애인복지과공개2015.11년
67전주시전주여성인력개발센터 요양보호사교육원전주시 완산구 장승배기로 213임경진2010-10-2826063-232-2346063-232-234455106노인장애인복지과공개2015.11년
78전주시전주메디칼요양보호사교육원전주시 완산구 용머리로 57정미경2010-10-2840063-225-3910063-225-391155056노인장애인복지과공개2015.11년
89전주시평화요양보호사교육원전주시 완산구 장승배기로 210박선애2011-03-0516063-225-1441063-227-101055122노인장애인복지과공개2015.11년
910전주시송천 탑클래스간호학원 요양보호사교육원전주시 덕진구 천마산로 19이서현2012-08-0130063-277-7701063-277-770254829노인장애인복지과공개2015.11년
순번시군명명칭도로명주소대표자지정일정원전화번호FAX우편번호자료출처공개여부작성일갱신주기
3637정읍시성모간호학원부설요양보호사교육원정읍시 충정로 175-1 (연지동)박미숙2015-06-2925063-534-1119-56165노인장애인복지과공개2015.11년
3738남원시남원간호요양보호사교육원남원시 의총로 77박성희2008-10-0136063-632-2993063-631-299355764노인장애인복지과공개2015.11년
3839남원시남원한국요양보호사교육원남원시 광한북로 43-2 (하정동)최문성2011-08-2440063-626-2233063-626-228355763노인장애인복지과공개2015.11년
3940김제시김제성모 요양보호사교육원김제시 동서로 222 (요촌동)박수임2010-0134063-545-9888063-545-988754392노인장애인복지과공개2015.11년
4041김제시벽성대학평생교육원 요양보호사교육원김제시 공덕면 유강 3길 133김상진,성정숙2010-10-2840063-540-2345063-540-234754321노인장애인복지과공개2015.11년
4142완주군봉동간호학원 부설 요양보호사교육원완주군 봉동읍 봉동로 140배순주2013-06-1930063-261-1125063-261-116555326노인장애인복지과공개2015.11년
4243장수군늘푸른요양보호사교육원장수군 장계면 한들로 107신유림2014-01-1525-063-353-669955615노인장애인복지과공개2015.11년
4344순창군순창요양보호사교육원순창군 순창읍 순화로 25백기성2010-10-2830063-652-8001063-652-801356038노인장애인복지과공개2015.11년
4445고창군고창요양보호사교육원고창군 고창읍 중앙로 180김재홍2014-11-0730063-563-0038063-563-001856436노인장애인복지과공개2015.11년
4546부안군부안요양보호사교육원부안군 부안읍 석정로 241 (2층)김인수2015-05-1230063-582-6222-56315노인장애인복지과공개2015.11년