Overview

Dataset statistics

Number of variables7
Number of observations335
Missing cells111
Missing cells (%)4.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.8 KiB
Average record size in memory57.4 B

Variable types

Categorical1
Text4
Numeric1
DateTime1

Dataset

Description경상북도 영주시 관내 경로당 현황(명칭, 위치, 연락처 등)
Author경상북도 영주시
URLhttps://www.data.go.kr/data/15044594/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연락처 has 111 (33.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:56:44.593757
Analysis finished2023-12-12 18:56:45.552341
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Categorical

Distinct19
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
풍기읍
41 
부석면
30 
안정면
24 
순흥면
22 
단산면
22 
Other values (14)
196 

Length

Max length4
Median length3
Mean length3.2268657
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
풍기읍 41
12.2%
부석면 30
 
9.0%
안정면 24
 
7.2%
순흥면 22
 
6.6%
단산면 22
 
6.6%
문수면 21
 
6.3%
이산면 21
 
6.3%
장수면 20
 
6.0%
봉현면 20
 
6.0%
상망동 16
 
4.8%
Other values (9) 98
29.3%

Length

2023-12-13T03:56:45.650327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
풍기읍 41
12.2%
부석면 30
 
9.0%
안정면 24
 
7.2%
순흥면 22
 
6.6%
단산면 22
 
6.6%
문수면 21
 
6.3%
이산면 21
 
6.3%
장수면 20
 
6.0%
봉현면 20
 
6.0%
상망동 16
 
4.8%
Other values (9) 98
29.3%

경로당명
Text

Distinct333
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T03:56:46.039783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length3.8656716
Min length2

Characters and Unicode

Total characters1295
Distinct characters211
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

Unique331 ?
Unique (%)98.8%

Sample

1st row교촌1리
2nd row교촌2리
3rd row금계1리
4th row금계2리
5th row동부1리
ValueCountFrequency (%)
지동3리 2
 
0.6%
지동2리 2
 
0.6%
세영첼시빌경로당 1
 
0.3%
봉래골 1
 
0.3%
소천4리 1
 
0.3%
용암1리 1
 
0.3%
용바위 1
 
0.3%
송고동 1
 
0.3%
소천6리 1
 
0.3%
소천5리 1
 
0.3%
Other values (324) 324
96.4%
2023-12-13T03:56:46.762660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 180
 
13.9%
1 68
 
5.3%
2 66
 
5.1%
동 43
 
3.3%
회 24
 
1.9%
3 23
 
1.8%
천 22
 
1.7%
산 20
 
1.5%
아 19
 
1.5%
분 19
 
1.5%
Other values (201) 811
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1106
85.4%
Decimal Number 169
 
13.1%
Open Punctuation 9
 
0.7%
Close Punctuation 9
 
0.7%
Other Punctuation 1
 
0.1%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 180
 
16.3%
동 43
 
3.9%
회 24
 
2.2%
천 22
 
2.0%
산 20
 
1.8%
아 19
 
1.7%
분 19
 
1.7%
지 18
 
1.6%
곡 17
 
1.5%
현 17
 
1.5%
Other values (191) 727
65.7%
Decimal Number
ValueCountFrequency (%)
1 68
40.2%
2 66
39.1%
3 23
 
13.6%
4 8
 
4.7%
5 2
 
1.2%
6 2
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1106
85.4%
Common 189
 
14.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 180
 
16.3%
동 43
 
3.9%
회 24
 
2.2%
천 22
 
2.0%
산 20
 
1.8%
아 19
 
1.7%
분 19
 
1.7%
지 18
 
1.6%
곡 17
 
1.5%
현 17
 
1.5%
Other values (191) 727
65.7%
Common
ValueCountFrequency (%)
1 68
36.0%
2 66
34.9%
3 23
 
12.2%
( 9
 
4.8%
) 9
 
4.8%
4 8
 
4.2%
5 2
 
1.1%
6 2
 
1.1%
. 1
 
0.5%
1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1106
85.4%
ASCII 189
 
14.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 180
 
16.3%
동 43
 
3.9%
회 24
 
2.2%
천 22
 
2.0%
산 20
 
1.8%
아 19
 
1.7%
분 19
 
1.7%
지 18
 
1.6%
곡 17
 
1.5%
현 17
 
1.5%
Other values (191) 727
65.7%
ASCII
ValueCountFrequency (%)
1 68
36.0%
2 66
34.9%
3 23
 
12.2%
( 9
 
4.8%
) 9
 
4.8%
4 8
 
4.2%
5 2
 
1.1%
6 2
 
1.1%
. 1
 
0.5%
1
 
0.5%

노인회장
Text

Distinct332
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T03:56:47.303419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9940299
Min length2

Characters and Unicode

Total characters1003
Distinct characters161
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

Unique329 ?
Unique (%)98.2%

Sample

1st row안덕기
2nd row이태복
3rd row차동근
4th row황영대
5th row김두홍
ValueCountFrequency (%)
김영자 2
 
0.6%
이정식 2
 
0.6%
김선호 2
 
0.6%
이동탁 1
 
0.3%
최세현 1
 
0.3%
이정군 1
 
0.3%
이천수 1
 
0.3%
정영섭 1
 
0.3%
배선창 1
 
0.3%
서종기 1
 
0.3%
Other values (322) 322
96.1%
2023-12-13T03:56:48.009112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 75
 
7.5%
이 36
 
3.6%
정 29
 
2.9%
영 28
 
2.8%
기 26
 
2.6%
수 24
 
2.4%
박 22
 
2.2%
호 20
 
2.0%
권 18
 
1.8%
원 17
 
1.7%
Other values (151) 708
70.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1003
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 75
 
7.5%
이 36
 
3.6%
정 29
 
2.9%
영 28
 
2.8%
기 26
 
2.6%
수 24
 
2.4%
박 22
 
2.2%
호 20
 
2.0%
권 18
 
1.8%
원 17
 
1.7%
Other values (151) 708
70.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1003
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 75
 
7.5%
이 36
 
3.6%
정 29
 
2.9%
영 28
 
2.8%
기 26
 
2.6%
수 24
 
2.4%
박 22
 
2.2%
호 20
 
2.0%
권 18
 
1.8%
원 17
 
1.7%
Other values (151) 708
70.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1003
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 75
 
7.5%
이 36
 
3.6%
정 29
 
2.9%
영 28
 
2.8%
기 26
 
2.6%
수 24
 
2.4%
박 22
 
2.2%
호 20
 
2.0%
권 18
 
1.8%
원 17
 
1.7%
Other values (151) 708
70.6%

이용인원
Real number (ℝ)

Distinct81
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.053731
Minimum10
Maximum160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T03:56:48.272175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile19
Q129
median40
Q354
95-th percentile82
Maximum160
Range150
Interquartile range (IQR)25

Descriptive statistics

Standard deviation21.799511
Coefficient of variation (CV)0.49483914
Kurtosis4.1869695
Mean44.053731
Median Absolute Deviation (MAD)12
Skewness1.5728563
Sum14758
Variance475.21866
MonotonicityNot monotonic
2023-12-13T03:56:48.539271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 32
 
9.6%
30 17
 
5.1%
25 15
 
4.5%
28 13
 
3.9%
50 12
 
3.6%
60 11
 
3.3%
20 10
 
3.0%
36 9
 
2.7%
41 9
 
2.7%
42 7
 
2.1%
Other values (71) 200
59.7%
ValueCountFrequency (%)
10 1
 
0.3%
11 1
 
0.3%
12 1
 
0.3%
13 1
 
0.3%
14 2
 
0.6%
15 5
1.5%
16 2
 
0.6%
17 1
 
0.3%
18 2
 
0.6%
19 4
1.2%
ValueCountFrequency (%)
160 1
 
0.3%
149 1
 
0.3%
130 1
 
0.3%
121 1
 
0.3%
110 1
 
0.3%
106 1
 
0.3%
102 1
 
0.3%
97 1
 
0.3%
92 1
 
0.3%
90 3
0.9%

소재지주소
Text

Distinct333
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T03:56:49.048716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length24.152239
Min length18

Characters and Unicode

Total characters8091
Distinct characters170
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

Unique331 ?
Unique (%)98.8%

Sample

1st row경상북도 영주시 풍기읍 금계로10번길 24
2nd row경상북도 영주시 풍기읍 동양대로129번길 162
3rd row경상북도 영주시 풍기읍 무릉길42번길 9
4th row경상북도 영주시 풍기읍 금계로 217
5th row경상북도 영주시 풍기읍 기주로65번길 5
ValueCountFrequency (%)
경상북도 335
19.8%
영주시 335
19.8%
풍기읍 41
 
2.4%
휴천동 35
 
2.1%
부석면 30
 
1.8%
안정면 24
 
1.4%
단산면 22
 
1.3%
순흥면 22
 
1.3%
문수면 21
 
1.2%
이산면 21
 
1.2%
Other values (534) 809
47.7%
2023-12-13T03:56:49.832545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1370
 
16.9%
영 372
 
4.6%
주 372
 
4.6%
상 362
 
4.5%
북 336
 
4.2%
경 335
 
4.1%
도 335
 
4.1%
시 335
 
4.1%
로 316
 
3.9%
1 299
 
3.7%
Other values (160) 3659
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4883
60.4%
Decimal Number 1499
 
18.5%
Space Separator 1370
 
16.9%
Close Punctuation 105
 
1.3%
Open Punctuation 105
 
1.3%
Dash Punctuation 98
 
1.2%
Other Punctuation 21
 
0.3%
Uppercase Letter 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 372
 
7.6%
주 372
 
7.6%
상 362
 
7.4%
북 336
 
6.9%
경 335
 
6.9%
도 335
 
6.9%
시 335
 
6.9%
로 316
 
6.5%
길 226
 
4.6%
번 210
 
4.3%
Other values (141) 1684
34.5%
Decimal Number
ValueCountFrequency (%)
1 299
19.9%
2 203
13.5%
3 177
11.8%
4 148
9.9%
5 140
9.3%
6 123
8.2%
0 114
 
7.6%
7 105
 
7.0%
9 104
 
6.9%
8 86
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
A 4
40.0%
T 3
30.0%
P 3
30.0%
Other Punctuation
ValueCountFrequency (%)
, 20
95.2%
. 1
 
4.8%
Space Separator
ValueCountFrequency (%)
1370
100.0%
Close Punctuation
ValueCountFrequency (%)
) 105
100.0%
Open Punctuation
ValueCountFrequency (%)
( 105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4883
60.4%
Common 3198
39.5%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 372
 
7.6%
주 372
 
7.6%
상 362
 
7.4%
북 336
 
6.9%
경 335
 
6.9%
도 335
 
6.9%
시 335
 
6.9%
로 316
 
6.5%
길 226
 
4.6%
번 210
 
4.3%
Other values (141) 1684
34.5%
Common
ValueCountFrequency (%)
1370
42.8%
1 299
 
9.3%
2 203
 
6.3%
3 177
 
5.5%
4 148
 
4.6%
5 140
 
4.4%
6 123
 
3.8%
0 114
 
3.6%
7 105
 
3.3%
) 105
 
3.3%
Other values (6) 414
 
12.9%
Latin
ValueCountFrequency (%)
A 4
40.0%
T 3
30.0%
P 3
30.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4883
60.4%
ASCII 3208
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1370
42.7%
1 299
 
9.3%
2 203
 
6.3%
3 177
 
5.5%
4 148
 
4.6%
5 140
 
4.4%
6 123
 
3.8%
0 114
 
3.6%
7 105
 
3.3%
) 105
 
3.3%
Other values (9) 424
 
13.2%
Hangul
ValueCountFrequency (%)
영 372
 
7.6%
주 372
 
7.6%
상 362
 
7.4%
북 336
 
6.9%
경 335
 
6.9%
도 335
 
6.9%
시 335
 
6.9%
로 316
 
6.5%
길 226
 
4.6%
번 210
 
4.3%
Other values (141) 1684
34.5%

연락처
Text

MISSING 

Distinct222
Distinct (%)99.1%
Missing111
Missing (%)33.1%
Memory size2.7 KiB
2023-12-13T03:56:50.194808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.008929
Min length12

Characters and Unicode

Total characters2690
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

Unique220 ?
Unique (%)98.2%

Sample

1st row054-636-5513
2nd row054-636-9121
3rd row054-635-4269
4th row054-638-3332
5th row054-636-8127
ValueCountFrequency (%)
054-636-2368 2
 
0.9%
054-637-4560 2
 
0.9%
054-637-0831 1
 
0.4%
054-635-9901 1
 
0.4%
054-636-5513 1
 
0.4%
054-631-3329 1
 
0.4%
054-635-3869 1
 
0.4%
054-631-2127 1
 
0.4%
054-635-4234 1
 
0.4%
054-634-0010 1
 
0.4%
Other values (212) 212
94.6%
2023-12-13T03:56:50.822078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 448
16.7%
3 361
13.4%
5 348
12.9%
6 338
12.6%
4 324
12.0%
0 322
12.0%
7 144
 
5.4%
2 122
 
4.5%
8 112
 
4.2%
1 102
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2242
83.3%
Dash Punctuation 448
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 361
16.1%
5 348
15.5%
6 338
15.1%
4 324
14.5%
0 322
14.4%
7 144
 
6.4%
2 122
 
5.4%
8 112
 
5.0%
1 102
 
4.5%
9 69
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 448
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2690
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 448
16.7%
3 361
13.4%
5 348
12.9%
6 338
12.6%
4 324
12.0%
0 322
12.0%
7 144
 
5.4%
2 122
 
4.5%
8 112
 
4.2%
1 102
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2690
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 448
16.7%
3 361
13.4%
5 348
12.9%
6 338
12.6%
4 324
12.0%
0 322
12.0%
7 144
 
5.4%
2 122
 
4.5%
8 112
 
4.2%
1 102
 
3.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum2017-05-01 00:00:00
Maximum2017-05-01 00:00:00
2023-12-13T03:56:51.063285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:56:51.248912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T03:56:45.089530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:56:51.383410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동이용인원
읍면동1.0000.435
이용인원0.4351.000
2023-12-13T03:56:51.535664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용인원읍면동
이용인원1.0000.190
읍면동0.1901.000

Missing values

2023-12-13T03:56:45.295319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:56:45.491211image/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

읍면동경로당명노인회장이용인원소재지주소연락처데이터기준일자
0풍기읍교촌1리안덕기39경상북도 영주시 풍기읍 금계로10번길 24054-636-55132017-05-01
1풍기읍교촌2리이태복18경상북도 영주시 풍기읍 동양대로129번길 162054-636-91212017-05-01
2풍기읍금계1리차동근97경상북도 영주시 풍기읍 무릉길42번길 9054-635-42692017-05-01
3풍기읍금계2리황영대30경상북도 영주시 풍기읍 금계로 217054-638-33322017-05-01
4풍기읍동부1리김두홍55경상북도 영주시 풍기읍 기주로65번길 5054-636-81272017-05-01
5풍기읍동부2리배선준77경상북도 영주시 풍기읍 기주로60번길 33054-637-43642017-05-01
6풍기읍동부3리김종달110경상북도 영주시 풍기읍 동성로2번길 132<NA>2017-05-01
7풍기읍동부4리여성용85경상북도 영주시 풍기읍 소백로 1941<NA>2017-05-01
8풍기읍만수윤희형35경상북도 영주시 풍기읍 기주로 120-1<NA>2017-05-01
9풍기읍매화김영애40경상북도 영주시 풍기읍 남원로20번길 29, 2층 (삼일슈퍼)054-637-54432017-05-01
읍면동경로당명노인회장이용인원소재지주소연락처데이터기준일자
325가흥2동도화동안창식50경상북도 영주시 신재로12번길 37 (가흥동)054-635-65252017-05-01
326가흥2동삼진권태종40경상북도 영주시 창진로194번길 74-18 (창진동)<NA>2017-05-01
327가흥2동시영아파트고언년42경상북도 영주시 창진로 59 (가흥동)054-637-70902017-05-01
328가흥2동아지동김윤기15경상북도 영주시 회헌로384번길 11 (아지동)054-638-22302017-05-01
329가흥2동이현김문길50경상북도 영주시 영주로53번길 54 (가흥동)<NA>2017-05-01
330가흥2동줄포석용읍44경상북도 영주시 줄포길 78-4 (상줄동)054-633-73232017-05-01
331가흥2동창진이복호70경상북도 영주시 창진로 195 (창진동)054-632-05652017-05-01
332가흥2동필두왕용섭46경상북도 영주시 필두길74번길 52 (상줄동)054-634-44952017-05-01
333가흥2동현대아파트황동규31경상북도 영주시 신재로12번길 67 (가흥동)054-638-87732017-05-01
334가흥2동화성리버빌전옥숙39경상북도 영주시 신재로12번길 56 (가흥동)054-636-84602017-05-01