Overview

Dataset statistics

Number of variables8
Number of observations257
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.7 KiB
Average record size in memory66.5 B

Variable types

Numeric1
Categorical4
Text2
Boolean1

Dataset

Description전북특별자치도내에 있는 관공서 현황(시군명, 건물명칭, 도로면주소 등)우리 기관에서는 더 이상 생성 불가 데이터입니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055813/fileData.do

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기(년) has constant value ""Constant
순번 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 08:56:07.811044
Analysis finished2024-03-14 08:56:09.165619
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct257
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129
Minimum1
Maximum257
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-03-14T17:56:09.380222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.8
Q165
median129
Q3193
95-th percentile244.2
Maximum257
Range256
Interquartile range (IQR)128

Descriptive statistics

Standard deviation74.333707
Coefficient of variation (CV)0.57623029
Kurtosis-1.2
Mean129
Median Absolute Deviation (MAD)64
Skewness0
Sum33153
Variance5525.5
MonotonicityStrictly increasing
2024-03-14T17:56:09.826952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
194 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
Other values (247) 247
96.1%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
257 1
0.4%
256 1
0.4%
255 1
0.4%
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%
249 1
0.4%
248 1
0.4%

시군명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
전주시
36 
익산시
30 
군산시
28 
정읍시
24 
남원시
24 
Other values (9)
115 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 36
14.0%
익산시 30
11.7%
군산시 28
10.9%
정읍시 24
9.3%
남원시 24
9.3%
김제시 20
7.8%
고창군 15
 
5.8%
완주군 14
 
5.4%
부안군 14
 
5.4%
임실군 13
 
5.1%
Other values (4) 39
15.2%

Length

2024-03-14T17:56:10.237991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 36
14.0%
익산시 30
11.7%
군산시 28
10.9%
정읍시 24
9.3%
남원시 24
9.3%
김제시 20
7.8%
고창군 15
 
5.8%
완주군 14
 
5.4%
부안군 14
 
5.4%
임실군 13
 
5.1%
Other values (4) 39
15.2%

건물명칭
Text

Distinct247
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-03-14T17:56:11.207221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.3385214
Min length4

Characters and Unicode

Total characters1629
Distinct characters162
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

Unique238 ?
Unique (%)92.6%

Sample

1st row전주시청
2nd row완산구청
3rd row중앙동주민센터
4th row풍남동주민센터
5th row노송동주민센터
ValueCountFrequency (%)
중앙동주민센터 3
 
1.2%
산내면사무소 2
 
0.8%
동주민센터 2
 
0.8%
성수면사무소 2
 
0.8%
조촌동주민센터 2
 
0.8%
백산면사무소 2
 
0.8%
신풍동주민센터 2
 
0.8%
주천면사무소 2
 
0.8%
동산동주민센터 2
 
0.8%
대산면사무소 2
 
0.8%
Other values (238) 238
91.9%
2024-03-14T17:56:12.603673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 164
 
10.1%
무 164
 
10.1%
사 162
 
9.9%
면 148
 
9.1%
동 95
 
5.8%
주 91
 
5.6%
민 83
 
5.1%
센 83
 
5.1%
터 83
 
5.1%
산 33
 
2.0%
Other values (152) 523
32.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1600
98.2%
Decimal Number 25
 
1.5%
Space Separator 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 164
 
10.2%
무 164
 
10.2%
사 162
 
10.1%
면 148
 
9.2%
동 95
 
5.9%
주 91
 
5.7%
민 83
 
5.2%
센 83
 
5.2%
터 83
 
5.2%
산 33
 
2.1%
Other values (147) 494
30.9%
Decimal Number
ValueCountFrequency (%)
2 10
40.0%
1 10
40.0%
3 4
 
16.0%
4 1
 
4.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1600
98.2%
Common 29
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 164
 
10.2%
무 164
 
10.2%
사 162
 
10.1%
면 148
 
9.2%
동 95
 
5.9%
주 91
 
5.7%
민 83
 
5.2%
센 83
 
5.2%
터 83
 
5.2%
산 33
 
2.1%
Other values (147) 494
30.9%
Common
ValueCountFrequency (%)
2 10
34.5%
1 10
34.5%
4
 
13.8%
3 4
 
13.8%
4 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1600
98.2%
ASCII 29
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 164
 
10.2%
무 164
 
10.2%
사 162
 
10.1%
면 148
 
9.2%
동 95
 
5.9%
주 91
 
5.7%
민 83
 
5.2%
센 83
 
5.2%
터 83
 
5.2%
산 33
 
2.1%
Other values (147) 494
30.9%
ASCII
ValueCountFrequency (%)
2 10
34.5%
1 10
34.5%
4
 
13.8%
3 4
 
13.8%
4 1
 
3.4%

도로명주소
Text

UNIQUE 

Distinct257
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-03-14T17:56:13.899202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length14.595331
Min length10

Characters and Unicode

Total characters3751
Distinct characters218
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

Unique257 ?
Unique (%)100.0%

Sample

1st row전주시 완산구 노송광장로 10
2nd row전주시 완산구 서원로 232
3rd row전주시 완산구 태평3길 43-17
4th row전주시 완산구 어진길 122-12
5th row전주시 완산구 인봉1길 54
ValueCountFrequency (%)
전주시 36
 
3.7%
익산시 30
 
3.1%
군산시 28
 
2.9%
남원시 24
 
2.5%
정읍시 24
 
2.5%
완산구 20
 
2.0%
김제시 20
 
2.0%
덕진구 16
 
1.6%
고창군 14
 
1.4%
완주군 14
 
1.4%
Other values (585) 750
76.8%
2024-03-14T17:56:15.315144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
719
 
19.2%
로 175
 
4.7%
1 167
 
4.5%
시 165
 
4.4%
면 146
 
3.9%
군 121
 
3.2%
산 120
 
3.2%
2 106
 
2.8%
3 92
 
2.5%
길 91
 
2.4%
Other values (208) 1849
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2246
59.9%
Decimal Number 750
 
20.0%
Space Separator 719
 
19.2%
Dash Punctuation 36
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 175
 
7.8%
시 165
 
7.3%
면 146
 
6.5%
군 121
 
5.4%
산 120
 
5.3%
길 91
 
4.1%
주 72
 
3.2%
구 50
 
2.2%
읍 49
 
2.2%
진 47
 
2.1%
Other values (196) 1210
53.9%
Decimal Number
ValueCountFrequency (%)
1 167
22.3%
2 106
14.1%
3 92
12.3%
4 67
8.9%
5 65
 
8.7%
8 55
 
7.3%
6 53
 
7.1%
7 52
 
6.9%
0 47
 
6.3%
9 46
 
6.1%
Space Separator
ValueCountFrequency (%)
719
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2246
59.9%
Common 1505
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 175
 
7.8%
시 165
 
7.3%
면 146
 
6.5%
군 121
 
5.4%
산 120
 
5.3%
길 91
 
4.1%
주 72
 
3.2%
구 50
 
2.2%
읍 49
 
2.2%
진 47
 
2.1%
Other values (196) 1210
53.9%
Common
ValueCountFrequency (%)
719
47.8%
1 167
 
11.1%
2 106
 
7.0%
3 92
 
6.1%
4 67
 
4.5%
5 65
 
4.3%
8 55
 
3.7%
6 53
 
3.5%
7 52
 
3.5%
0 47
 
3.1%
Other values (2) 82
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2246
59.9%
ASCII 1505
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
719
47.8%
1 167
 
11.1%
2 106
 
7.0%
3 92
 
6.1%
4 67
 
4.5%
5 65
 
4.3%
8 55
 
3.7%
6 53
 
3.5%
7 52
 
3.5%
0 47
 
3.1%
Other values (2) 82
 
5.4%
Hangul
ValueCountFrequency (%)
로 175
 
7.8%
시 165
 
7.3%
면 146
 
6.5%
군 121
 
5.4%
산 120
 
5.3%
길 91
 
4.1%
주 72
 
3.2%
구 50
 
2.2%
읍 49
 
2.2%
진 47
 
2.1%
Other values (196) 1210
53.9%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
전북특별자치도 자치행정과
257 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전북특별자치도 자치행정과
2nd row전북특별자치도 자치행정과
3rd row전북특별자치도 자치행정과
4th row전북특별자치도 자치행정과
5th row전북특별자치도 자치행정과

Common Values

ValueCountFrequency (%)
전북특별자치도 자치행정과 257
100.0%

Length

2024-03-14T17:56:15.538825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:56:15.695308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북특별자치도 257
50.0%
자치행정과 257
50.0%

공개여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size385.0 B
True
257 
ValueCountFrequency (%)
True 257
100.0%
2024-03-14T17:56:15.825453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2016-12-01
257 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016-12-01
2nd row2016-12-01
3rd row2016-12-01
4th row2016-12-01
5th row2016-12-01

Common Values

ValueCountFrequency (%)
2016-12-01 257
100.0%

Length

2024-03-14T17:56:16.011868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:56:16.308917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016-12-01 257
100.0%

갱신주기(년)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
1
257 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 257
100.0%

Length

2024-03-14T17:56:16.620083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:56:16.911760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 257
100.0%

Interactions

2024-03-14T17:56:08.244430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T17:56:17.080856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명
순번1.0000.942
시군명0.9421.000
2024-03-14T17:56:17.304738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명
순번1.0000.764
시군명0.7641.000

Missing values

2024-03-14T17:56:08.583577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T17:56:09.002083image/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

순번시군명건물명칭도로명주소자료출처공개여부작성일갱신주기(년)
01전주시전주시청전주시 완산구 노송광장로 10전북특별자치도 자치행정과Y2016-12-011
12전주시완산구청전주시 완산구 서원로 232전북특별자치도 자치행정과Y2016-12-011
23전주시중앙동주민센터전주시 완산구 태평3길 43-17전북특별자치도 자치행정과Y2016-12-011
34전주시풍남동주민센터전주시 완산구 어진길 122-12전북특별자치도 자치행정과Y2016-12-011
45전주시노송동주민센터전주시 완산구 인봉1길 54전북특별자치도 자치행정과Y2016-12-011
56전주시완산동주민센터전주시 완산구 강당2길 7전북특별자치도 자치행정과Y2016-12-011
67전주시동서학동주민센터전주시 완산구 서학로 26전북특별자치도 자치행정과Y2016-12-011
78전주시서서학동주민센터전주시 완산구 공수내로 24전북특별자치도 자치행정과Y2016-12-011
89전주시중화산1동주민센터전주시 완산구 한두평 3길 16전북특별자치도 자치행정과Y2016-12-011
910전주시중화산2동주민센터전주시 완산구 화산천변로 30전북특별자치도 자치행정과Y2016-12-011
순번시군명건물명칭도로명주소자료출처공개여부작성일갱신주기(년)
247248부안군행안면사무소부안군 행안면 번영로 33전북특별자치도 자치행정과Y2016-12-011
248249부안군계화면사무소부안군 계화면 간재로 405전북특별자치도 자치행정과Y2016-12-011
249250부안군보안면사무소부안군 보안면 영전길 19-29전북특별자치도 자치행정과Y2016-12-011
250251부안군변산면사무소부안군 변산면 지서로 77-1전북특별자치도 자치행정과Y2016-12-011
251252부안군진서면사무소부안군 진서면 청자로 926전북특별자치도 자치행정과Y2016-12-011
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