Overview

Dataset statistics

Number of variables8
Number of observations334
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.7 KiB
Average record size in memory66.4 B

Variable types

Numeric2
Categorical1
Text3
DateTime2

Dataset

Description진안군에 있는 경로당에 대한 데이터 정보로 소재지 도로명주소, 시설명, 대표자, 회원수, 설치신고일 등을 제공합니다.
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15033493/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 읍면High correlation
읍면 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-15 01:34:59.909788
Analysis finished2024-03-15 01:35:02.077627
Duration2.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct334
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167.5
Minimum1
Maximum334
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-15T10:35:02.289239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.65
Q184.25
median167.5
Q3250.75
95-th percentile317.35
Maximum334
Range333
Interquartile range (IQR)166.5

Descriptive statistics

Standard deviation96.561725
Coefficient of variation (CV)0.57648791
Kurtosis-1.2
Mean167.5
Median Absolute Deviation (MAD)83.5
Skewness0
Sum55945
Variance9324.1667
MonotonicityStrictly increasing
2024-03-15T10:35:02.754886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
231 1
 
0.3%
229 1
 
0.3%
228 1
 
0.3%
227 1
 
0.3%
226 1
 
0.3%
225 1
 
0.3%
224 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
Other values (324) 324
97.0%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
334 1
0.3%
333 1
0.3%
332 1
0.3%
331 1
0.3%
330 1
0.3%
329 1
0.3%
328 1
0.3%
327 1
0.3%
326 1
0.3%
325 1
0.3%

읍면
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
진안읍
78 
부귀면
40 
백운면
32 
성수면
32 
주천면
32 
Other values (6)
120 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진안읍 78
23.4%
부귀면 40
12.0%
백운면 32
9.6%
성수면 32
9.6%
주천면 32
9.6%
동향면 31
 
9.3%
마령면 23
 
6.9%
안천면 18
 
5.4%
상전면 17
 
5.1%
정천면 17
 
5.1%

Length

2024-03-15T10:35:03.132162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진안읍 78
23.4%
부귀면 40
12.0%
백운면 32
9.6%
성수면 32
9.6%
주천면 32
9.6%
동향면 31
 
9.3%
마령면 23
 
6.9%
안천면 18
 
5.4%
상전면 17
 
5.1%
정천면 17
 
5.1%

시설명
Text

Distinct315
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-03-15T10:35:04.212083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.3682635
Min length5

Characters and Unicode

Total characters1793
Distinct characters174
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

Unique300 ?
Unique (%)89.8%

Sample

1st row가막경로당
2nd row검북경로당
3rd row개실경로당
4th row고향마을경로당
5th row관산1동 경로당
ValueCountFrequency (%)
경로당 6
 
1.8%
양지경로당 4
 
1.2%
중리경로당 3
 
0.9%
신기경로당 3
 
0.9%
교동경로당 2
 
0.6%
방화경로당 2
 
0.6%
새마을경로당 2
 
0.6%
문화경로당 2
 
0.6%
괴정경로당 2
 
0.6%
번덕경로당 2
 
0.6%
Other values (306) 312
91.8%
2024-03-15T10:35:05.516968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 335
18.7%
당 306
17.1%
로 305
17.0%
동 45
 
2.5%
정 43
 
2.4%
모 29
 
1.6%
원 28
 
1.6%
신 21
 
1.2%
상 19
 
1.1%
평 18
 
1.0%
Other values (164) 644
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1765
98.4%
Decimal Number 22
 
1.2%
Space Separator 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 335
19.0%
당 306
17.3%
로 305
17.3%
동 45
 
2.5%
정 43
 
2.4%
모 29
 
1.6%
원 28
 
1.6%
신 21
 
1.2%
상 19
 
1.1%
평 18
 
1.0%
Other values (159) 616
34.9%
Decimal Number
ValueCountFrequency (%)
1 10
45.5%
2 9
40.9%
3 2
 
9.1%
4 1
 
4.5%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1765
98.4%
Common 28
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 335
19.0%
당 306
17.3%
로 305
17.3%
동 45
 
2.5%
정 43
 
2.4%
모 29
 
1.6%
원 28
 
1.6%
신 21
 
1.2%
상 19
 
1.1%
평 18
 
1.0%
Other values (159) 616
34.9%
Common
ValueCountFrequency (%)
1 10
35.7%
2 9
32.1%
6
21.4%
3 2
 
7.1%
4 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1765
98.4%
ASCII 28
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 335
19.0%
당 306
17.3%
로 305
17.3%
동 45
 
2.5%
정 43
 
2.4%
모 29
 
1.6%
원 28
 
1.6%
신 21
 
1.2%
상 19
 
1.1%
평 18
 
1.0%
Other values (159) 616
34.9%
ASCII
ValueCountFrequency (%)
1 10
35.7%
2 9
32.1%
6
21.4%
3 2
 
7.1%
4 1
 
3.6%

대표자
Text

Distinct274
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-03-15T10:35:07.223150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.994012
Min length2

Characters and Unicode

Total characters1000
Distinct characters130
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique233 ?
Unique (%)69.8%

Sample

1st row설*남
2nd row송*철
3rd row최*영
4th row박*매
5th row김*수
ValueCountFrequency (%)
김*수 5
 
1.5%
김*환 5
 
1.5%
김*순 4
 
1.2%
박*순 4
 
1.2%
이*우 3
 
0.9%
김*선 3
 
0.9%
김*자 3
 
0.9%
김*곤 3
 
0.9%
최*수 3
 
0.9%
김*남 3
 
0.9%
Other values (264) 298
89.2%
2024-03-15T10:35:09.708454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 335
33.5%
김 71
 
7.1%
이 45
 
4.5%
박 34
 
3.4%
수 20
 
2.0%
순 18
 
1.8%
정 15
 
1.5%
기 14
 
1.4%
전 13
 
1.3%
자 12
 
1.2%
Other values (120) 423
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 665
66.5%
Other Punctuation 335
33.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 71
 
10.7%
이 45
 
6.8%
박 34
 
5.1%
수 20
 
3.0%
순 18
 
2.7%
정 15
 
2.3%
기 14
 
2.1%
전 13
 
2.0%
자 12
 
1.8%
강 12
 
1.8%
Other values (119) 411
61.8%
Other Punctuation
ValueCountFrequency (%)
* 335
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 665
66.5%
Common 335
33.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 71
 
10.7%
이 45
 
6.8%
박 34
 
5.1%
수 20
 
3.0%
순 18
 
2.7%
정 15
 
2.3%
기 14
 
2.1%
전 13
 
2.0%
자 12
 
1.8%
강 12
 
1.8%
Other values (119) 411
61.8%
Common
ValueCountFrequency (%)
* 335
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 665
66.5%
ASCII 335
33.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 335
100.0%
Hangul
ValueCountFrequency (%)
김 71
 
10.7%
이 45
 
6.8%
박 34
 
5.1%
수 20
 
3.0%
순 18
 
2.7%
정 15
 
2.3%
기 14
 
2.1%
전 13
 
2.0%
자 12
 
1.8%
강 12
 
1.8%
Other values (119) 411
61.8%

소재지 도로명주소
Text

Distinct319
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-03-15T10:35:11.436357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length23.260479
Min length21

Characters and Unicode

Total characters7769
Distinct characters201
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

Unique304 ?
Unique (%)91.0%

Sample

1st row전북특별자치도 진안군 진안읍 상가막길 6
2nd row전북특별자치도 진안군 진안읍 검북로 89
3rd row전북특별자치도 진안군 진안읍 개실길 115
4th row전북특별자치도 진안군 진안읍 진장로 51-16
5th row전북특별자치도 진안군 진안읍 성산2길 21-9
ValueCountFrequency (%)
전북특별자치도 334
19.9%
진안군 334
19.9%
진안읍 78
 
4.6%
부귀면 40
 
2.4%
성수면 32
 
1.9%
주천면 32
 
1.9%
백운면 32
 
1.9%
동향면 31
 
1.8%
마령면 23
 
1.4%
안천면 18
 
1.1%
Other values (473) 724
43.1%
2024-03-15T10:35:13.259516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1346
17.3%
안 441
 
5.7%
진 430
 
5.5%
전 356
 
4.6%
자 343
 
4.4%
도 339
 
4.4%
치 338
 
4.4%
북 336
 
4.3%
군 335
 
4.3%
별 334
 
4.3%
Other values (191) 3171
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5455
70.2%
Space Separator 1346
 
17.3%
Decimal Number 867
 
11.2%
Dash Punctuation 97
 
1.2%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 441
 
8.1%
진 430
 
7.9%
전 356
 
6.5%
자 343
 
6.3%
도 339
 
6.2%
치 338
 
6.2%
북 336
 
6.2%
군 335
 
6.1%
별 334
 
6.1%
특 334
 
6.1%
Other values (177) 1869
34.3%
Decimal Number
ValueCountFrequency (%)
1 203
23.4%
2 165
19.0%
3 79
 
9.1%
5 79
 
9.1%
4 76
 
8.8%
6 74
 
8.5%
8 63
 
7.3%
7 50
 
5.8%
0 40
 
4.6%
9 38
 
4.4%
Space Separator
ValueCountFrequency (%)
1346
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5455
70.2%
Common 2314
29.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 441
 
8.1%
진 430
 
7.9%
전 356
 
6.5%
자 343
 
6.3%
도 339
 
6.2%
치 338
 
6.2%
북 336
 
6.2%
군 335
 
6.1%
별 334
 
6.1%
특 334
 
6.1%
Other values (177) 1869
34.3%
Common
ValueCountFrequency (%)
1346
58.2%
1 203
 
8.8%
2 165
 
7.1%
- 97
 
4.2%
3 79
 
3.4%
5 79
 
3.4%
4 76
 
3.3%
6 74
 
3.2%
8 63
 
2.7%
7 50
 
2.2%
Other values (4) 82
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5455
70.2%
ASCII 2314
29.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1346
58.2%
1 203
 
8.8%
2 165
 
7.1%
- 97
 
4.2%
3 79
 
3.4%
5 79
 
3.4%
4 76
 
3.3%
6 74
 
3.2%
8 63
 
2.7%
7 50
 
2.2%
Other values (4) 82
 
3.5%
Hangul
ValueCountFrequency (%)
안 441
 
8.1%
진 430
 
7.9%
전 356
 
6.5%
자 343
 
6.3%
도 339
 
6.2%
치 338
 
6.2%
북 336
 
6.2%
군 335
 
6.1%
별 334
 
6.1%
특 334
 
6.1%
Other values (177) 1869
34.3%

회원수
Real number (ℝ)

Distinct45
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.520958
Minimum10
Maximum63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-15T10:35:13.518418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile11
Q115
median21
Q330
95-th percentile43
Maximum63
Range53
Interquartile range (IQR)15

Descriptive statistics

Standard deviation10.888922
Coefficient of variation (CV)0.46294552
Kurtosis1.001583
Mean23.520958
Median Absolute Deviation (MAD)7
Skewness1.095294
Sum7856
Variance118.56863
MonotonicityNot monotonic
2024-03-15T10:35:13.786066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
21 18
 
5.4%
15 18
 
5.4%
11 17
 
5.1%
24 17
 
5.1%
13 16
 
4.8%
12 16
 
4.8%
17 16
 
4.8%
20 15
 
4.5%
18 15
 
4.5%
31 14
 
4.2%
Other values (35) 172
51.5%
ValueCountFrequency (%)
10 12
3.6%
11 17
5.1%
12 16
4.8%
13 16
4.8%
14 14
4.2%
15 18
5.4%
16 10
3.0%
17 16
4.8%
18 15
4.5%
19 8
2.4%
ValueCountFrequency (%)
63 1
 
0.3%
61 2
0.6%
60 1
 
0.3%
57 1
 
0.3%
55 1
 
0.3%
51 2
0.6%
50 1
 
0.3%
49 1
 
0.3%
48 3
0.9%
47 1
 
0.3%

설치신고일
Date

Distinct132
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum1991-04-01 00:00:00
Maximum2023-09-14 00:00:00
2024-03-15T10:35:14.081318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:35:14.636976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum2023-11-30 00:00:00
Maximum2023-11-30 00:00:00
2024-03-15T10:35:14.825573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:35:15.131495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T10:35:01.089890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:35:00.564653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:35:01.363480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:35:00.831913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:35:15.308223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면회원수
연번1.0000.9290.381
읍면0.9291.0000.234
회원수0.3810.2341.000
2024-03-15T10:35:15.559923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번회원수읍면
연번1.000-0.1210.745
회원수-0.1211.0000.101
읍면0.7450.1011.000

Missing values

2024-03-15T10:35:01.633657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:35:01.921472image/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

연번읍면시설명대표자소재지 도로명주소회원수설치신고일데이터기준일자
01진안읍가막경로당설*남전북특별자치도 진안군 진안읍 상가막길 6231996-05-132023-11-30
12진안읍검북경로당송*철전북특별자치도 진안군 진안읍 검북로 89132005-01-242023-11-30
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325326주천면양지경모정박*숙전북특별자치도 진안군 주천면 양지1길 23-12411991-04-012023-11-30
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