Overview

Dataset statistics

Number of variables6
Number of observations66
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory52.0 B

Variable types

Numeric2
Text3
Categorical1

Dataset

Description경기도 광주시 행정사사무소 등록현황에 대한 데이터로 상호명, 주소, 우편번호, 행정사, 데이터기준일자 등을 제공합니다.
URLhttps://www.data.go.kr/data/3079677/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
행정사 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:41:59.083021
Analysis finished2023-12-12 00:42:00.221410
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct66
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.5
Minimum1
Maximum66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2023-12-12T09:42:00.323459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.25
Q117.25
median33.5
Q349.75
95-th percentile62.75
Maximum66
Range65
Interquartile range (IQR)32.5

Descriptive statistics

Standard deviation19.196354
Coefficient of variation (CV)0.57302549
Kurtosis-1.2
Mean33.5
Median Absolute Deviation (MAD)16.5
Skewness0
Sum2211
Variance368.5
MonotonicityStrictly increasing
2023-12-12T09:42:00.468190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
51 1
 
1.5%
37 1
 
1.5%
38 1
 
1.5%
39 1
 
1.5%
40 1
 
1.5%
41 1
 
1.5%
42 1
 
1.5%
43 1
 
1.5%
44 1
 
1.5%
Other values (56) 56
84.8%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
66 1
1.5%
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%
58 1
1.5%
57 1
1.5%

상호명
Text

Distinct62
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size660.0 B
2023-12-12T09:42:00.711998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length10.060606
Min length5

Characters and Unicode

Total characters664
Distinct characters122
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

Unique61 ?
Unique (%)92.4%

Sample

1st row알파고 행정사사무소
2nd row효림 행정사 사무소
3rd row초월 큰마음 행정사 사무소
4th row김진광 행정사 사무소
5th rowSK행정사
ValueCountFrequency (%)
행정사 34
22.2%
사무소 33
21.6%
행정사사무소 12
 
7.8%
광주 5
 
3.3%
합동사무소 5
 
3.3%
초월 2
 
1.3%
믿음행정사 1
 
0.7%
민년기 1
 
0.7%
옥토행정사 1
 
0.7%
우성행정사 1
 
0.7%
Other values (58) 58
37.9%
2023-12-12T09:42:01.165007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 126
19.0%
87
13.1%
정 68
10.2%
행 66
 
9.9%
소 61
 
9.2%
무 61
 
9.2%
이 11
 
1.7%
광 7
 
1.1%
동 6
 
0.9%
주 6
 
0.9%
Other values (112) 165
24.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 560
84.3%
Space Separator 87
 
13.1%
Uppercase Letter 12
 
1.8%
Decimal Number 3
 
0.5%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 126
22.5%
정 68
12.1%
행 66
11.8%
소 61
10.9%
무 61
10.9%
이 11
 
2.0%
광 7
 
1.2%
동 6
 
1.1%
주 6
 
1.1%
김 5
 
0.9%
Other values (97) 143
25.5%
Uppercase Letter
ValueCountFrequency (%)
O 2
16.7%
S 2
16.7%
K 2
16.7%
L 1
8.3%
P 1
8.3%
R 1
8.3%
M 1
8.3%
C 1
8.3%
H 1
8.3%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
7 1
33.3%
3 1
33.3%
Space Separator
ValueCountFrequency (%)
87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 560
84.3%
Common 92
 
13.9%
Latin 12
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 126
22.5%
정 68
12.1%
행 66
11.8%
소 61
10.9%
무 61
10.9%
이 11
 
2.0%
광 7
 
1.2%
동 6
 
1.1%
주 6
 
1.1%
김 5
 
0.9%
Other values (97) 143
25.5%
Latin
ValueCountFrequency (%)
O 2
16.7%
S 2
16.7%
K 2
16.7%
L 1
8.3%
P 1
8.3%
R 1
8.3%
M 1
8.3%
C 1
8.3%
H 1
8.3%
Common
ValueCountFrequency (%)
87
94.6%
2 1
 
1.1%
) 1
 
1.1%
( 1
 
1.1%
7 1
 
1.1%
3 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 560
84.3%
ASCII 104
 
15.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 126
22.5%
정 68
12.1%
행 66
11.8%
소 61
10.9%
무 61
10.9%
이 11
 
2.0%
광 7
 
1.2%
동 6
 
1.1%
주 6
 
1.1%
김 5
 
0.9%
Other values (97) 143
25.5%
ASCII
ValueCountFrequency (%)
87
83.7%
O 2
 
1.9%
S 2
 
1.9%
K 2
 
1.9%
L 1
 
1.0%
P 1
 
1.0%
R 1
 
1.0%
M 1
 
1.0%
C 1
 
1.0%
2 1
 
1.0%
Other values (5) 5
 
4.8%

주소
Text

Distinct58
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size660.0 B
2023-12-12T09:42:01.475435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24.5
Mean length18.19697
Min length13

Characters and Unicode

Total characters1201
Distinct characters83
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

Unique53 ?
Unique (%)80.3%

Sample

1st row경기도 광주시 신현로 75
2nd row경기도 광주시 양촌길 146-34
3rd row경기도 광주시 초월읍 경충대로 1003
4th row경기도 광주시 중앙로 320
5th row경기도 광주시 역동로 80
ValueCountFrequency (%)
경기도 66
23.4%
광주시 66
23.4%
회안대로 9
 
3.2%
중앙로 7
 
2.5%
949 5
 
1.8%
초월읍 5
 
1.8%
경안동 4
 
1.4%
행정타운로 3
 
1.1%
곤지암읍 3
 
1.1%
역동로 3
 
1.1%
Other values (96) 111
39.4%
2023-12-12T09:42:01.966907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
216
18.0%
경 81
 
6.7%
도 69
 
5.7%
광 68
 
5.7%
주 68
 
5.7%
시 67
 
5.6%
기 66
 
5.5%
로 54
 
4.5%
1 43
 
3.6%
4 33
 
2.7%
Other values (73) 436
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 724
60.3%
Decimal Number 225
 
18.7%
Space Separator 216
 
18.0%
Dash Punctuation 18
 
1.5%
Open Punctuation 9
 
0.7%
Close Punctuation 9
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 81
11.2%
도 69
 
9.5%
광 68
 
9.4%
주 68
 
9.4%
시 67
 
9.3%
기 66
 
9.1%
로 54
 
7.5%
길 29
 
4.0%
안 21
 
2.9%
대 17
 
2.3%
Other values (59) 184
25.4%
Decimal Number
ValueCountFrequency (%)
1 43
19.1%
4 33
14.7%
3 26
11.6%
2 25
11.1%
9 21
9.3%
7 18
8.0%
6 17
 
7.6%
5 16
 
7.1%
0 16
 
7.1%
8 10
 
4.4%
Space Separator
ValueCountFrequency (%)
216
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 724
60.3%
Common 477
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 81
11.2%
도 69
 
9.5%
광 68
 
9.4%
주 68
 
9.4%
시 67
 
9.3%
기 66
 
9.1%
로 54
 
7.5%
길 29
 
4.0%
안 21
 
2.9%
대 17
 
2.3%
Other values (59) 184
25.4%
Common
ValueCountFrequency (%)
216
45.3%
1 43
 
9.0%
4 33
 
6.9%
3 26
 
5.5%
2 25
 
5.2%
9 21
 
4.4%
7 18
 
3.8%
- 18
 
3.8%
6 17
 
3.6%
5 16
 
3.4%
Other values (4) 44
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 724
60.3%
ASCII 477
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
216
45.3%
1 43
 
9.0%
4 33
 
6.9%
3 26
 
5.5%
2 25
 
5.2%
9 21
 
4.4%
7 18
 
3.8%
- 18
 
3.8%
6 17
 
3.6%
5 16
 
3.4%
Other values (4) 44
 
9.2%
Hangul
ValueCountFrequency (%)
경 81
11.2%
도 69
 
9.5%
광 68
 
9.4%
주 68
 
9.4%
시 67
 
9.3%
기 66
 
9.1%
로 54
 
7.5%
길 29
 
4.0%
안 21
 
2.9%
대 17
 
2.3%
Other values (59) 184
25.4%

우편번호
Real number (ℝ)

Distinct38
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12764.045
Minimum12716
Maximum12821
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2023-12-12T09:42:02.131062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12716
5-th percentile12736
Q112739
median12760
Q312787
95-th percentile12815
Maximum12821
Range105
Interquartile range (IQR)48

Descriptive statistics

Standard deviation27.444171
Coefficient of variation (CV)0.0021501154
Kurtosis-0.9186339
Mean12764.045
Median Absolute Deviation (MAD)21
Skewness0.54743701
Sum842427
Variance753.18252
MonotonicityNot monotonic
2023-12-12T09:42:02.258958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
12739 10
 
15.2%
12738 7
 
10.6%
12798 4
 
6.1%
12745 3
 
4.5%
12761 3
 
4.5%
12736 2
 
3.0%
12778 2
 
3.0%
12773 2
 
3.0%
12793 2
 
3.0%
12767 2
 
3.0%
Other values (28) 29
43.9%
ValueCountFrequency (%)
12716 1
 
1.5%
12733 1
 
1.5%
12735 1
 
1.5%
12736 2
 
3.0%
12738 7
10.6%
12739 10
15.2%
12741 1
 
1.5%
12744 2
 
3.0%
12745 3
 
4.5%
12750 1
 
1.5%
ValueCountFrequency (%)
12821 1
 
1.5%
12820 1
 
1.5%
12817 1
 
1.5%
12816 1
 
1.5%
12812 1
 
1.5%
12807 1
 
1.5%
12806 1
 
1.5%
12804 1
 
1.5%
12798 4
6.1%
12793 2
3.0%

행정사
Text

UNIQUE 

Distinct66
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
2023-12-12T09:42:02.501677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9848485
Min length2

Characters and Unicode

Total characters197
Distinct characters85
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

Unique66 ?
Unique (%)100.0%

Sample

1st row고광섭
2nd row남상근
3rd row남경민
4th row김진광
5th row장인학
ValueCountFrequency (%)
고광섭 1
 
1.5%
조중현 1
 
1.5%
육동주 1
 
1.5%
이현익 1
 
1.5%
이창일 1
 
1.5%
강근구 1
 
1.5%
신이규 1
 
1.5%
박삼근 1
 
1.5%
김진명 1
 
1.5%
김상곤 1
 
1.5%
Other values (56) 56
84.8%
2023-12-12T09:42:02.958952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 13
 
6.6%
김 13
 
6.6%
성 6
 
3.0%
정 5
 
2.5%
근 5
 
2.5%
영 5
 
2.5%
한 5
 
2.5%
기 4
 
2.0%
수 4
 
2.0%
상 4
 
2.0%
Other values (75) 133
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 197
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 13
 
6.6%
김 13
 
6.6%
성 6
 
3.0%
정 5
 
2.5%
근 5
 
2.5%
영 5
 
2.5%
한 5
 
2.5%
기 4
 
2.0%
수 4
 
2.0%
상 4
 
2.0%
Other values (75) 133
67.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 197
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 13
 
6.6%
김 13
 
6.6%
성 6
 
3.0%
정 5
 
2.5%
근 5
 
2.5%
영 5
 
2.5%
한 5
 
2.5%
기 4
 
2.0%
수 4
 
2.0%
상 4
 
2.0%
Other values (75) 133
67.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 197
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 13
 
6.6%
김 13
 
6.6%
성 6
 
3.0%
정 5
 
2.5%
근 5
 
2.5%
영 5
 
2.5%
한 5
 
2.5%
기 4
 
2.0%
수 4
 
2.0%
상 4
 
2.0%
Other values (75) 133
67.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
2023-08-24
66 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-24
2nd row2023-08-24
3rd row2023-08-24
4th row2023-08-24
5th row2023-08-24

Common Values

ValueCountFrequency (%)
2023-08-24 66
100.0%

Length

2023-12-12T09:42:03.105404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:42:03.232619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-24 66
100.0%

Interactions

2023-12-12T09:41:59.522088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:41:59.346195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:41:59.604225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:41:59.431232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:42:03.307586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명주소우편번호행정사
연번1.0000.9190.8850.1771.000
상호명0.9191.0001.0001.0001.000
주소0.8851.0001.0001.0001.000
우편번호0.1771.0001.0001.0001.000
행정사1.0001.0001.0001.0001.000
2023-12-12T09:42:03.401207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호
연번1.000-0.069
우편번호-0.0691.000

Missing values

2023-12-12T09:41:59.763738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:41:59.898917image/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

연번상호명주소우편번호행정사데이터기준일자
01알파고 행정사사무소경기도 광주시 신현로 7512821고광섭2023-08-24
12효림 행정사 사무소경기도 광주시 양촌길 146-3412798남상근2023-08-24
23초월 큰마음 행정사 사무소경기도 광주시 초월읍 경충대로 100312736남경민2023-08-24
34김진광 행정사 사무소경기도 광주시 중앙로 32012739김진광2023-08-24
45SK행정사경기도 광주시 역동로 8012778장인학2023-08-24
56청담행정사사무소경기도 광주시 역동로 11112778박정규2023-08-24
67이재두 행정사경기도 광주시 태성1로 1612788이재두2023-08-24
78성우행정사 사무소경기도 광주시 중앙로335번길 712739김승태2023-08-24
89금상 행정사 사무소경기도 광주시 초월읍 진새골길75번길 1412735김상섭2023-08-24
910조도한 행정사사무소경기도 광주시 회안대로 1612798조도한2023-08-24
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