Overview

Dataset statistics

Number of variables6
Number of observations538
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.9 KiB
Average record size in memory49.2 B

Variable types

Categorical1
Text3
Numeric1
DateTime1

Dataset

Description경상북도 안동시 읍면동별 경로당 주소, 건축연도, 규모 등의 제공(경상북도 안동시 노인여가 복지시설(경로당)의 명칭 등 현황입니다.)
Author경상북도 안동시
URLhttps://www.data.go.kr/data/15007438/fileData.do

Alerts

데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2023-12-12 14:14:23.909246
Analysis finished2023-12-12 14:14:24.657898
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동명
Categorical

Distinct24
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
풍산읍
43 
와룡면
40 
길안면
 
33
임동면
 
31
용상동
 
31
Other values (19)
360 

Length

Max length3
Median length3
Mean length2.9684015
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
풍산읍 43
 
8.0%
와룡면 40
 
7.4%
길안면 33
 
6.1%
임동면 31
 
5.8%
용상동 31
 
5.8%
일직면 29
 
5.4%
북후면 27
 
5.0%
예안면 26
 
4.8%
풍천면 25
 
4.6%
녹전면 24
 
4.5%
Other values (14) 229
42.6%

Length

2023-12-12T23:14:24.740681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
풍산읍 43
 
8.0%
와룡면 40
 
7.4%
길안면 33
 
6.1%
임동면 31
 
5.8%
용상동 31
 
5.8%
일직면 29
 
5.4%
북후면 27
 
5.0%
예안면 26
 
4.8%
풍천면 25
 
4.6%
녹전면 24
 
4.5%
Other values (14) 229
42.6%

경로당명
Text

Distinct534
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-12T23:14:25.024825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.4386617
Min length2

Characters and Unicode

Total characters2388
Distinct characters262
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

Unique530 ?
Unique (%)98.5%

Sample

1st row풍산읍분회
2nd row안교1리
3rd row안교2리
4th row하리1리
5th row마애리
ValueCountFrequency (%)
용상동 15
 
2.7%
대곡1리 2
 
0.4%
6주공아파트 2
 
0.4%
4주공아파트 2
 
0.4%
3주공아파트 2
 
0.4%
5주공아파트 2
 
0.4%
대곡2리 2
 
0.4%
갈전1리 2
 
0.4%
금계리 2
 
0.4%
보현 1
 
0.2%
Other values (522) 522
94.2%
2023-12-12T23:14:25.493837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 356
 
14.9%
2 109
 
4.6%
1 103
 
4.3%
아 55
 
2.3%
트 49
 
2.1%
파 49
 
2.1%
동 42
 
1.8%
천 41
 
1.7%
곡 37
 
1.5%
상 35
 
1.5%
Other values (252) 1512
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2126
89.0%
Decimal Number 240
 
10.1%
Space Separator 16
 
0.7%
Uppercase Letter 4
 
0.2%
Other Punctuation 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 356
 
16.7%
아 55
 
2.6%
트 49
 
2.3%
파 49
 
2.3%
동 42
 
2.0%
천 41
 
1.9%
곡 37
 
1.7%
상 35
 
1.6%
대 34
 
1.6%
하 29
 
1.4%
Other values (237) 1399
65.8%
Decimal Number
ValueCountFrequency (%)
2 109
45.4%
1 103
42.9%
3 19
 
7.9%
5 3
 
1.2%
6 2
 
0.8%
4 2
 
0.8%
7 1
 
0.4%
8 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
T 1
25.0%
K 1
25.0%
G 1
25.0%
A 1
25.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2126
89.0%
Common 257
 
10.8%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 356
 
16.7%
아 55
 
2.6%
트 49
 
2.3%
파 49
 
2.3%
동 42
 
2.0%
천 41
 
1.9%
곡 37
 
1.7%
상 35
 
1.6%
대 34
 
1.6%
하 29
 
1.4%
Other values (237) 1399
65.8%
Common
ValueCountFrequency (%)
2 109
42.4%
1 103
40.1%
3 19
 
7.4%
16
 
6.2%
5 3
 
1.2%
6 2
 
0.8%
4 2
 
0.8%
& 1
 
0.4%
7 1
 
0.4%
8 1
 
0.4%
Latin
ValueCountFrequency (%)
T 1
20.0%
K 1
20.0%
e 1
20.0%
G 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2126
89.0%
ASCII 262
 
11.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 356
 
16.7%
아 55
 
2.6%
트 49
 
2.3%
파 49
 
2.3%
동 42
 
2.0%
천 41
 
1.9%
곡 37
 
1.7%
상 35
 
1.6%
대 34
 
1.6%
하 29
 
1.4%
Other values (237) 1399
65.8%
ASCII
ValueCountFrequency (%)
2 109
41.6%
1 103
39.3%
3 19
 
7.3%
16
 
6.1%
5 3
 
1.1%
6 2
 
0.8%
4 2
 
0.8%
& 1
 
0.4%
T 1
 
0.4%
K 1
 
0.4%
Other values (5) 5
 
1.9%

주소
Text

Distinct534
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-12T23:14:25.941736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length40
Mean length21.834572
Min length14

Characters and Unicode

Total characters11747
Distinct characters300
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique530 ?
Unique (%)98.5%

Sample

1st row경상북도 안동시 풍산읍 장터2길 11
2nd row경상북도 안동시 풍산읍 장터중앙길 59
3rd row경상북도 안동시 풍산읍 홍정길 2
4th row경상북도 안동시 풍산읍 우렁길 119
5th row경상북도 안동시 풍산읍 마애길 25-3
ValueCountFrequency (%)
경상북도 538
 
20.0%
안동시 538
 
20.0%
풍산읍 43
 
1.6%
와룡면 40
 
1.5%
길안면 33
 
1.2%
임동면 31
 
1.2%
일직면 29
 
1.1%
북후면 27
 
1.0%
예안면 26
 
1.0%
용상동 25
 
0.9%
Other values (870) 1361
50.6%
2023-12-12T23:14:26.459431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2154
18.3%
동 738
 
6.3%
안 655
 
5.6%
상 586
 
5.0%
북 584
 
5.0%
도 567
 
4.8%
경 557
 
4.7%
시 545
 
4.6%
길 464
 
3.9%
1 362
 
3.1%
Other values (290) 4535
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7527
64.1%
Space Separator 2154
 
18.3%
Decimal Number 1589
 
13.5%
Dash Punctuation 159
 
1.4%
Close Punctuation 128
 
1.1%
Open Punctuation 128
 
1.1%
Other Punctuation 58
 
0.5%
Uppercase Letter 3
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 738
 
9.8%
안 655
 
8.7%
상 586
 
7.8%
북 584
 
7.8%
도 567
 
7.5%
경 557
 
7.4%
시 545
 
7.2%
길 464
 
6.2%
면 328
 
4.4%
로 110
 
1.5%
Other values (272) 2393
31.8%
Decimal Number
ValueCountFrequency (%)
1 362
22.8%
2 253
15.9%
3 189
11.9%
5 139
 
8.7%
6 131
 
8.2%
7 127
 
8.0%
4 118
 
7.4%
9 98
 
6.2%
0 88
 
5.5%
8 84
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
2154
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 159
100.0%
Close Punctuation
ValueCountFrequency (%)
) 128
100.0%
Open Punctuation
ValueCountFrequency (%)
( 128
100.0%
Other Punctuation
ValueCountFrequency (%)
, 58
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7527
64.1%
Common 4216
35.9%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 738
 
9.8%
안 655
 
8.7%
상 586
 
7.8%
북 584
 
7.8%
도 567
 
7.5%
경 557
 
7.4%
시 545
 
7.2%
길 464
 
6.2%
면 328
 
4.4%
로 110
 
1.5%
Other values (272) 2393
31.8%
Common
ValueCountFrequency (%)
2154
51.1%
1 362
 
8.6%
2 253
 
6.0%
3 189
 
4.5%
- 159
 
3.8%
5 139
 
3.3%
6 131
 
3.1%
) 128
 
3.0%
( 128
 
3.0%
7 127
 
3.0%
Other values (5) 446
 
10.6%
Latin
ValueCountFrequency (%)
A 2
50.0%
B 1
25.0%
e 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7527
64.1%
ASCII 4220
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2154
51.0%
1 362
 
8.6%
2 253
 
6.0%
3 189
 
4.5%
- 159
 
3.8%
5 139
 
3.3%
6 131
 
3.1%
) 128
 
3.0%
( 128
 
3.0%
7 127
 
3.0%
Other values (8) 450
 
10.7%
Hangul
ValueCountFrequency (%)
동 738
 
9.8%
안 655
 
8.7%
상 586
 
7.8%
북 584
 
7.8%
도 567
 
7.5%
경 557
 
7.4%
시 545
 
7.2%
길 464
 
6.2%
면 328
 
4.4%
로 110
 
1.5%
Other values (272) 2393
31.8%

등록연도
Real number (ℝ)

Distinct51
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1999.8271
Minimum1962
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.9 KiB
2023-12-12T23:14:26.627596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1962
5-th percentile1985.7
Q11994
median2000
Q32006
95-th percentile2015.15
Maximum2023
Range61
Interquartile range (IQR)12

Descriptive statistics

Standard deviation9.5845666
Coefficient of variation (CV)0.0047926976
Kurtosis0.79518923
Mean1999.8271
Median Absolute Deviation (MAD)6
Skewness-0.31610518
Sum1075907
Variance91.863918
MonotonicityNot monotonic
2023-12-12T23:14:26.761752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1989 49
 
9.1%
1999 37
 
6.9%
1998 29
 
5.4%
2004 28
 
5.2%
2001 25
 
4.6%
1997 24
 
4.5%
2008 24
 
4.5%
2002 21
 
3.9%
1996 21
 
3.9%
2000 20
 
3.7%
Other values (41) 260
48.3%
ValueCountFrequency (%)
1962 1
 
0.2%
1963 1
 
0.2%
1972 2
 
0.4%
1975 6
1.1%
1976 1
 
0.2%
1977 2
 
0.4%
1978 2
 
0.4%
1979 3
0.6%
1980 4
0.7%
1981 2
 
0.4%
ValueCountFrequency (%)
2023 1
 
0.2%
2022 2
 
0.4%
2021 4
 
0.7%
2020 6
1.1%
2019 5
0.9%
2018 5
0.9%
2017 2
 
0.4%
2016 2
 
0.4%
2015 4
 
0.7%
2014 10
1.9%

규모(제곱미터)
Text

Distinct469
Distinct (%)87.3%
Missing1
Missing (%)0.2%
Memory size4.3 KiB
2023-12-12T23:14:27.048824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length4.7579143
Min length2

Characters and Unicode

Total characters2555
Distinct characters14
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

Unique430 ?
Unique (%)80.1%

Sample

1st row285.69
2nd row244.59
3rd row80.51
4th row98.6
5th row84.2
ValueCountFrequency (%)
66 9
 
1.7%
49.5 7
 
1.3%
66.5 6
 
1.1%
82.5 4
 
0.7%
132 4
 
0.7%
33 4
 
0.7%
72 3
 
0.6%
112.2 3
 
0.6%
85.8 3
 
0.6%
72.6 3
 
0.6%
Other values (459) 491
91.4%
2023-12-12T23:14:27.469803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 487
19.1%
1 293
11.5%
6 253
9.9%
8 247
9.7%
9 215
8.4%
7 203
7.9%
2 202
7.9%
5 198
7.7%
4 175
 
6.8%
3 161
 
6.3%
Other values (4) 121
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2065
80.8%
Other Punctuation 487
 
19.1%
Open Punctuation 1
 
< 0.1%
Other Letter 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 293
14.2%
6 253
12.3%
8 247
12.0%
9 215
10.4%
7 203
9.8%
2 202
9.8%
5 198
9.6%
4 175
8.5%
3 161
7.8%
0 118
5.7%
Other Punctuation
ValueCountFrequency (%)
. 487
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Letter
ValueCountFrequency (%)
지 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2554
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 487
19.1%
1 293
11.5%
6 253
9.9%
8 247
9.7%
9 215
8.4%
7 203
7.9%
2 202
7.9%
5 198
7.8%
4 175
 
6.9%
3 161
 
6.3%
Other values (3) 120
 
4.7%
Hangul
ValueCountFrequency (%)
지 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2554
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 487
19.1%
1 293
11.5%
6 253
9.9%
8 247
9.7%
9 215
8.4%
7 203
7.9%
2 202
7.9%
5 198
7.8%
4 175
 
6.9%
3 161
 
6.3%
Other values (3) 120
 
4.7%
Hangul
ValueCountFrequency (%)
지 1
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2023-04-18 00:00:00
Maximum2023-04-18 00:00:00
2023-12-12T23:14:27.610138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:14:27.715225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T23:14:24.349220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:14:27.793332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명등록연도
읍면동명1.0000.460
등록연도0.4601.000
2023-12-12T23:14:27.895026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록연도읍면동명
등록연도1.0000.190
읍면동명0.1901.000

Missing values

2023-12-12T23:14:24.478257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:14:24.606227image/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

읍면동명경로당명주소등록연도규모(제곱미터)데이터기준일자
0풍산읍풍산읍분회경상북도 안동시 풍산읍 장터2길 111981285.692023-04-18
1풍산읍안교1리경상북도 안동시 풍산읍 장터중앙길 591998244.592023-04-18
2풍산읍안교2리경상북도 안동시 풍산읍 홍정길 2197580.512023-04-18
3풍산읍하리1리경상북도 안동시 풍산읍 우렁길 119196298.62023-04-18
4풍산읍마애리경상북도 안동시 풍산읍 마애길 25-3200484.22023-04-18
5풍산읍수1리경상북도 안동시 풍산읍 풍산태사로 14581994119.12023-04-18
6풍산읍수2리경상북도 안동시 풍산읍 수석길 181998120.72023-04-18
7풍산읍계평리경상북도 안동시 풍산읍 음실길 8200381.992023-04-18
8풍산읍현애리경상북도 안동시 풍산읍 감애길 29200381.442023-04-18
9풍산읍오미2리경상북도 안동시 풍산읍 새랄1길 3198066.52023-04-18
읍면동명경로당명주소등록연도규모(제곱미터)데이터기준일자
528강남동수하1경상북도 안동시 무주무3길 28-9 (수하동)19891322023-04-18
529강남동수하2경상북도 안동시 무주무4길 46 (수하동)198975.742023-04-18
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