Overview

Dataset statistics

Number of variables13
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory112.5 B

Variable types

Numeric2
Text6
DateTime1
Categorical4

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 has unique valuesUnique
복지관명 has unique valuesUnique
도로명주소 has unique valuesUnique
면적 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 02:12:17.182171
Analysis finished2024-03-14 02:12:18.112289
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-14T11:12:18.164834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2024-03-14T11:12:18.258039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

시군명
Text

Distinct14
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-14T11:12:18.375516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters72
Distinct characters24
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

Unique9 ?
Unique (%)37.5%

Sample

1st row전주시
2nd row전주시
3rd row전주시
4th row전주시
5th row전주시
ValueCountFrequency (%)
전주시 7
29.2%
군산시 2
 
8.3%
익산시 2
 
8.3%
정읍시 2
 
8.3%
임실군 2
 
8.3%
남원시 1
 
4.2%
김제시 1
 
4.2%
완주군 1
 
4.2%
진안군 1
 
4.2%
무주군 1
 
4.2%
Other values (4) 4
16.7%
2024-03-14T11:12:18.602281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 15
20.8%
군 11
15.3%
주 9
12.5%
전 7
9.7%
산 4
 
5.6%
실 2
 
2.8%
창 2
 
2.8%
임 2
 
2.8%
읍 2
 
2.8%
정 2
 
2.8%
Other values (14) 16
22.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 15
20.8%
군 11
15.3%
주 9
12.5%
전 7
9.7%
산 4
 
5.6%
실 2
 
2.8%
창 2
 
2.8%
임 2
 
2.8%
읍 2
 
2.8%
정 2
 
2.8%
Other values (14) 16
22.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 15
20.8%
군 11
15.3%
주 9
12.5%
전 7
9.7%
산 4
 
5.6%
실 2
 
2.8%
창 2
 
2.8%
임 2
 
2.8%
읍 2
 
2.8%
정 2
 
2.8%
Other values (14) 16
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 15
20.8%
군 11
15.3%
주 9
12.5%
전 7
9.7%
산 4
 
5.6%
실 2
 
2.8%
창 2
 
2.8%
임 2
 
2.8%
읍 2
 
2.8%
정 2
 
2.8%
Other values (14) 16
22.2%

복지관명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-14T11:12:18.767493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length8.75
Min length5

Characters and Unicode

Total characters210
Distinct characters51
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

Unique24 ?
Unique (%)100.0%

Sample

1st row노인복지관
2nd row안골노인복지관
3rd row금암노인복지관
4th row서원노인복지관
5th row덕진노인복지관
ValueCountFrequency (%)
노인복지관 1
 
4.2%
안골노인복지관 1
 
4.2%
고창군노인복지관 1
 
4.2%
순창군장애인노인종합복지관 1
 
4.2%
임실군북부권노인복지관 1
 
4.2%
임실군노인복지관 1
 
4.2%
장수군노인장애인복지관 1
 
4.2%
무주노인종합복지관 1
 
4.2%
진안군복합노인복지타운 1
 
4.2%
완주군근로자종합복지관 1
 
4.2%
Other values (14) 14
58.3%
2024-03-14T11:12:19.055771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 25
11.9%
복 25
11.9%
지 25
11.9%
노 23
 
11.0%
관 23
 
11.0%
군 8
 
3.8%
합 8
 
3.8%
종 7
 
3.3%
시 4
 
1.9%
장 3
 
1.4%
Other values (41) 59
28.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 210
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 25
11.9%
복 25
11.9%
지 25
11.9%
노 23
 
11.0%
관 23
 
11.0%
군 8
 
3.8%
합 8
 
3.8%
종 7
 
3.3%
시 4
 
1.9%
장 3
 
1.4%
Other values (41) 59
28.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 210
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 25
11.9%
복 25
11.9%
지 25
11.9%
노 23
 
11.0%
관 23
 
11.0%
군 8
 
3.8%
합 8
 
3.8%
종 7
 
3.3%
시 4
 
1.9%
장 3
 
1.4%
Other values (41) 59
28.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 210
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 25
11.9%
복 25
11.9%
지 25
11.9%
노 23
 
11.0%
관 23
 
11.0%
군 8
 
3.8%
합 8
 
3.8%
종 7
 
3.3%
시 4
 
1.9%
장 3
 
1.4%
Other values (41) 59
28.1%

도로명주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-14T11:12:19.268637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length14.583333
Min length10

Characters and Unicode

Total characters350
Distinct characters83
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

Unique24 ?
Unique (%)100.0%

Sample

1st row전주시 완산구 감나무4길 29
2nd row전주시 덕진구 안골1길 11
3rd row전주시 덕진구 삼송5길 12
4th row전주시 완산구 따박골5길 36
5th row전주시 덕진구 송천중앙로 36
ValueCountFrequency (%)
전주시 7
 
7.9%
완산구 4
 
4.5%
덕진구 3
 
3.4%
익산시 2
 
2.2%
29 2
 
2.2%
임실군 2
 
2.2%
정읍시 2
 
2.2%
군산시 2
 
2.2%
36 2
 
2.2%
장수군 1
 
1.1%
Other values (62) 62
69.7%
2024-03-14T11:12:19.615035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65
 
18.6%
1 16
 
4.6%
시 15
 
4.3%
로 13
 
3.7%
군 11
 
3.1%
산 11
 
3.1%
읍 11
 
3.1%
길 11
 
3.1%
주 10
 
2.9%
5 10
 
2.9%
Other values (73) 177
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 208
59.4%
Decimal Number 73
 
20.9%
Space Separator 65
 
18.6%
Dash Punctuation 4
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 15
 
7.2%
로 13
 
6.2%
군 11
 
5.3%
산 11
 
5.3%
읍 11
 
5.3%
길 11
 
5.3%
주 10
 
4.8%
전 8
 
3.8%
구 7
 
3.4%
창 6
 
2.9%
Other values (61) 105
50.5%
Decimal Number
ValueCountFrequency (%)
1 16
21.9%
5 10
13.7%
2 10
13.7%
3 9
12.3%
4 9
12.3%
6 5
 
6.8%
9 4
 
5.5%
7 4
 
5.5%
8 3
 
4.1%
0 3
 
4.1%
Space Separator
ValueCountFrequency (%)
65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 208
59.4%
Common 142
40.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 15
 
7.2%
로 13
 
6.2%
군 11
 
5.3%
산 11
 
5.3%
읍 11
 
5.3%
길 11
 
5.3%
주 10
 
4.8%
전 8
 
3.8%
구 7
 
3.4%
창 6
 
2.9%
Other values (61) 105
50.5%
Common
ValueCountFrequency (%)
65
45.8%
1 16
 
11.3%
5 10
 
7.0%
2 10
 
7.0%
3 9
 
6.3%
4 9
 
6.3%
6 5
 
3.5%
9 4
 
2.8%
7 4
 
2.8%
- 4
 
2.8%
Other values (2) 6
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 208
59.4%
ASCII 142
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
65
45.8%
1 16
 
11.3%
5 10
 
7.0%
2 10
 
7.0%
3 9
 
6.3%
4 9
 
6.3%
6 5
 
3.5%
9 4
 
2.8%
7 4
 
2.8%
- 4
 
2.8%
Other values (2) 6
 
4.2%
Hangul
ValueCountFrequency (%)
시 15
 
7.2%
로 13
 
6.2%
군 11
 
5.3%
산 11
 
5.3%
읍 11
 
5.3%
길 11
 
5.3%
주 10
 
4.8%
전 8
 
3.8%
구 7
 
3.4%
창 6
 
2.9%
Other values (61) 105
50.5%

운영주체
Text

Distinct19
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-14T11:12:19.816209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length7.9583333
Min length3

Characters and Unicode

Total characters191
Distinct characters61
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

Unique16 ?
Unique (%)66.7%

Sample

1st row대한노인회 전북연합회
2nd row사복)중부복지재단
3rd row사단)나누는사람들
4th row사복)금산사복지원
5th row사복)한기장 복지재단
ValueCountFrequency (%)
사복)삼동회 4
 
13.8%
사복)삼육재단 2
 
6.9%
사복)전주가톨릭사회복지회 2
 
6.9%
의료재단 1
 
3.4%
전북연합회 1
 
3.4%
대한노인회 1
 
3.4%
유지재단 1
 
3.4%
재단)대한성공회 1
 
3.4%
사복)선운사복지재단 1
 
3.4%
순창군 1
 
3.4%
Other values (14) 14
48.3%
2024-03-14T11:12:20.086320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
복 22
 
11.5%
사 21
 
11.0%
) 18
 
9.4%
단 13
 
6.8%
회 11
 
5.8%
재 11
 
5.8%
지 8
 
4.2%
삼 6
 
3.1%
5
 
2.6%
군 4
 
2.1%
Other values (51) 72
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 168
88.0%
Close Punctuation 18
 
9.4%
Space Separator 5
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
복 22
 
13.1%
사 21
 
12.5%
단 13
 
7.7%
회 11
 
6.5%
재 11
 
6.5%
지 8
 
4.8%
삼 6
 
3.6%
군 4
 
2.4%
동 4
 
2.4%
산 3
 
1.8%
Other values (49) 65
38.7%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 168
88.0%
Common 23
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
복 22
 
13.1%
사 21
 
12.5%
단 13
 
7.7%
회 11
 
6.5%
재 11
 
6.5%
지 8
 
4.8%
삼 6
 
3.6%
군 4
 
2.4%
동 4
 
2.4%
산 3
 
1.8%
Other values (49) 65
38.7%
Common
ValueCountFrequency (%)
) 18
78.3%
5
 
21.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 168
88.0%
ASCII 23
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
복 22
 
13.1%
사 21
 
12.5%
단 13
 
7.7%
회 11
 
6.5%
재 11
 
6.5%
지 8
 
4.8%
삼 6
 
3.6%
군 4
 
2.4%
동 4
 
2.4%
산 3
 
1.8%
Other values (49) 65
38.7%
ASCII
ValueCountFrequency (%)
) 18
78.3%
5
 
21.7%

설립년월
Date

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum1994-12-03 00:00:00
Maximum2014-10-30 00:00:00
2024-03-14T11:12:20.184539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:12:20.273478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

면적
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2161.0417
Minimum564
Maximum4670
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-03-14T11:12:20.404083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum564
5-th percentile845.9
Q11383.5
median1854
Q32862.5
95-th percentile3576.6
Maximum4670
Range4106
Interquartile range (IQR)1479

Descriptive statistics

Standard deviation1023.4798
Coefficient of variation (CV)0.47360483
Kurtosis-0.1229043
Mean2161.0417
Median Absolute Deviation (MAD)716.5
Skewness0.60327759
Sum51865
Variance1047510.8
MonotonicityNot monotonic
2024-03-14T11:12:20.502438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1728 1
 
4.2%
2861 1
 
4.2%
1263 1
 
4.2%
1404 1
 
4.2%
1947 1
 
4.2%
564 1
 
4.2%
1220 1
 
4.2%
1761 1
 
4.2%
1055 1
 
4.2%
3603 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
564 1
4.2%
809 1
4.2%
1055 1
4.2%
1220 1
4.2%
1263 1
4.2%
1322 1
4.2%
1404 1
4.2%
1521 1
4.2%
1650 1
4.2%
1718 1
4.2%
ValueCountFrequency (%)
4670 1
4.2%
3603 1
4.2%
3427 1
4.2%
3291 1
4.2%
3279 1
4.2%
2867 1
4.2%
2861 1
4.2%
2759 1
4.2%
2712 1
4.2%
2443 1
4.2%

관장명
Text

Distinct20
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-14T11:12:20.632183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length2.7916667
Min length1

Characters and Unicode

Total characters67
Distinct characters43
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

Unique19 ?
Unique (%)79.2%

Sample

1st row조성문
2nd row이연숙
3rd row서양열(협회장)
4th row김성식
5th row오정석
ValueCountFrequency (%)
5
20.0%
한재수 1
 
4.0%
한갑수 1
 
4.0%
진 1
 
4.0%
김 1
 
4.0%
이영재 1
 
4.0%
김봉술 1
 
4.0%
노기보 1
 
4.0%
서철승 1
 
4.0%
김복례 1
 
4.0%
Other values (11) 11
44.0%
2024-03-14T11:12:20.860725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 5
 
7.5%
김 4
 
6.0%
성 4
 
6.0%
이 3
 
4.5%
재 3
 
4.5%
석 3
 
4.5%
한 2
 
3.0%
서 2
 
3.0%
수 2
 
3.0%
문 2
 
3.0%
Other values (33) 37
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59
88.1%
Dash Punctuation 5
 
7.5%
Space Separator 1
 
1.5%
Close Punctuation 1
 
1.5%
Open Punctuation 1
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 4
 
6.8%
성 4
 
6.8%
이 3
 
5.1%
재 3
 
5.1%
석 3
 
5.1%
한 2
 
3.4%
서 2
 
3.4%
수 2
 
3.4%
문 2
 
3.4%
영 2
 
3.4%
Other values (29) 32
54.2%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59
88.1%
Common 8
 
11.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 4
 
6.8%
성 4
 
6.8%
이 3
 
5.1%
재 3
 
5.1%
석 3
 
5.1%
한 2
 
3.4%
서 2
 
3.4%
수 2
 
3.4%
문 2
 
3.4%
영 2
 
3.4%
Other values (29) 32
54.2%
Common
ValueCountFrequency (%)
- 5
62.5%
1
 
12.5%
) 1
 
12.5%
( 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59
88.1%
ASCII 8
 
11.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 5
62.5%
1
 
12.5%
) 1
 
12.5%
( 1
 
12.5%
Hangul
ValueCountFrequency (%)
김 4
 
6.8%
성 4
 
6.8%
이 3
 
5.1%
재 3
 
5.1%
석 3
 
5.1%
한 2
 
3.4%
서 2
 
3.4%
수 2
 
3.4%
문 2
 
3.4%
영 2
 
3.4%
Other values (29) 32
54.2%

전화번호
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-14T11:12:21.022842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters288
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

Unique24 ?
Unique (%)100.0%

Sample

1st row063-276-2086
2nd row063-243-4377
3rd row063-253-5728
4th row063-227-7481
5th row063-271-9336
ValueCountFrequency (%)
063-276-2086 1
 
4.2%
063-243-4377 1
 
4.2%
063-563-1111 1
 
4.2%
063-650-1173 1
 
4.2%
063-642-3844 1
 
4.2%
063-644-4438 1
 
4.2%
063-353-8286 1
 
4.2%
063-322-1252 1
 
4.2%
063-430-2747 1
 
4.2%
063-290-2165 1
 
4.2%
Other values (14) 14
58.3%
2024-03-14T11:12:21.287879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 48
16.7%
3 44
15.3%
0 39
13.5%
6 37
12.8%
2 29
10.1%
4 19
 
6.6%
7 18
 
6.2%
5 17
 
5.9%
1 15
 
5.2%
8 13
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
83.3%
Dash Punctuation 48
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 44
18.3%
0 39
16.2%
6 37
15.4%
2 29
12.1%
4 19
7.9%
7 18
7.5%
5 17
 
7.1%
1 15
 
6.2%
8 13
 
5.4%
9 9
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 48
16.7%
3 44
15.3%
0 39
13.5%
6 37
12.8%
2 29
10.1%
4 19
 
6.6%
7 18
 
6.2%
5 17
 
5.9%
1 15
 
5.2%
8 13
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 48
16.7%
3 44
15.3%
0 39
13.5%
6 37
12.8%
2 29
10.1%
4 19
 
6.6%
7 18
 
6.2%
5 17
 
5.9%
1 15
 
5.2%
8 13
 
4.5%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
노인장애인복지과
24 

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 24
100.0%

Length

2024-03-14T11:12:21.403999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:12:21.482135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인장애인복지과 24
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
공개
24 

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 24
100.0%

Length

2024-03-14T11:12:21.583397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:12:21.687932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 24
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2015.1
24 

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 24
100.0%

Length

2024-03-14T11:12:21.770903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:12:21.855132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 24
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
1년
24 

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 24
100.0%

Length

2024-03-14T11:12:21.936703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:12:22.039682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 24
100.0%

Interactions

2024-03-14T11:12:17.721514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:12:17.589967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:12:17.789141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:12:17.659156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:12:22.100742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명복지관명도로명주소운영주체설립년월면적관장명전화번호
순번1.0000.8391.0001.0000.6451.0000.0000.8621.000
시군명0.8391.0001.0001.0000.6891.0000.0000.0001.000
복지관명1.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
운영주체0.6450.6891.0001.0001.0001.0000.8200.7331.000
설립년월1.0001.0001.0001.0001.0001.0001.0000.9781.000
면적0.0000.0001.0001.0000.8201.0001.0000.2661.000
관장명0.8620.0001.0001.0000.7330.9780.2661.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-03-14T11:12:22.193389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번면적
순번1.000-0.355
면적-0.3551.000

Missing values

2024-03-14T11:12:17.907091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:12:18.048044image/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

순번시군명복지관명도로명주소운영주체설립년월면적관장명전화번호자료출처공개여부작성일갱신주기
01전주시노인복지관전주시 완산구 감나무4길 29대한노인회 전북연합회1997-04-131728조성문063-276-2086노인장애인복지과공개2015.11년
12전주시안골노인복지관전주시 덕진구 안골1길 11사복)중부복지재단1994-12-031650이연숙063-243-4377노인장애인복지과공개2015.11년
23전주시금암노인복지관전주시 덕진구 삼송5길 12사단)나누는사람들2001-06-21809서양열(협회장)063-253-5728노인장애인복지과공개2015.11년
34전주시서원노인복지관전주시 완산구 따박골5길 36사복)금산사복지원2002-01-013279김성식063-227-7481노인장애인복지과공개2015.11년
45전주시덕진노인복지관전주시 덕진구 송천중앙로 36사복)한기장 복지재단2007-03-252712오정석063-271-9336노인장애인복지과공개2015.11년
56전주시양지노인복지관전주시 완산구 성지산로 55사복)삼육재단2008-05-133291이재성063-232-1000노인장애인복지과공개2015.11년
67전주시꽃밭정이노인복지관전주시 완산구 평화14길 27-53사복)이랜드2010-02-024670전석복063-237-0770노인장애인복지과공개2015.11년
78군산시군산노인종합복지관군산시 둔배미길 29사복)삼동회2000-10-093427신성호063-442-4227노인장애인복지과공개2015.11년
89군산시금강노인복지관군산시 백릉로 245군장대학교 산학협력단2014-01-091991정호영063-442-0012노인장애인복지과공개2015.11년
910익산시익산시노인종합복지관익산시 동서로 103사복)신광복지재단2005-06-082759문준태063-837-7722노인장애인복지과공개2015.11년
순번시군명복지관명도로명주소운영주체설립년월면적관장명전화번호자료출처공개여부작성일갱신주기
1415김제시김제노인종합복지관김제시 하동1길 79재단)예린 의료재단2008-07-171718노기보063-542-5550노인장애인복지과공개2015.11년
1516완주군완주군근로자종합복지관완주군 봉동읍 둔산3로 94완주군2001-05-102443-063-290-2165노인장애인복지과공개2015.11년
1617진안군진안군복합노인복지타운진안군 진안읍 마이산로 76사복)전주가톨릭사회복지회2008-12-043603김봉술063-430-2747노인장애인복지과공개2015.11년
1718무주군무주노인종합복지관무주군 무주읍 한풍루로 425사복)삼동회2005-12-091055이영재063-322-1252노인장애인복지과공개2015.11년
1819장수군장수군노인장애인복지관장수군 장수읍 노하3길 16사복)자광재단2010-11-151761김 진063-353-8286노인장애인복지과공개2015.11년
1920임실군임실군노인복지관임실군 임실읍 운수로 33-46사복)삼동회2011-11-011220한갑수063-644-4438노인장애인복지과공개2015.11년
2021임실군임실군북부권노인복지관임실군 관촌면 사선1길 24사복)삼동회2011-11-01564-063-642-3844노인장애인복지과공개2015.11년
2122순창군순창군장애인노인종합복지관순창군 순창읍 순창5길 11-4순창군2006-11-151947-063-650-1173노인장애인복지과공개2015.11년
2223고창군고창군노인복지관고창군 고창읍 전봉준로 88-15사복)선운사복지재단2008-01-011404손형석063-563-1111노인장애인복지과공개2015.11년
2324부안군노인여성복지회관부안군 부안읍 매창로 127부안군1998-04-281263-063-580-3936노인장애인복지과공개2015.11년