Overview

Dataset statistics

Number of variables7
Number of observations84
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory57.6 B

Variable types

Categorical5
Text2

Dataset

Description무인민원발급기설치현황20140718
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202079

Alerts

전라북도 무인민원발급기 설치현황 is highly overall correlated with Unnamed: 3 and 3 other fieldsHigh correlation
Unnamed: 3 is highly overall correlated with 전라북도 무인민원발급기 설치현황 and 2 other fieldsHigh correlation
Unnamed: 4 is highly overall correlated with 전라북도 무인민원발급기 설치현황 and 2 other fieldsHigh correlation
Unnamed: 5 is highly overall correlated with 전라북도 무인민원발급기 설치현황 and 1 other fieldsHigh correlation
Unnamed: 6 is highly overall correlated with 전라북도 무인민원발급기 설치현황 and 3 other fieldsHigh correlation
Unnamed: 1 has 1 (1.2%) missing valuesMissing
Unnamed: 2 has 1 (1.2%) missing valuesMissing

Reproduction

Analysis started2024-03-14 03:25:29.123405
Analysis finished2024-03-14 03:25:29.945703
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도 무인민원발급기 설치현황
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
전주시완산구
14 
전주시덕진구
14 
완주
8 
군산
8 
익산
8 
Other values (12)
32 

Length

Max length6
Median length2
Mean length3.3690476
Min length2

Unique

Unique5 ?
Unique (%)6.0%

Sample

1st row<NA>
2nd row시군명
3rd row전주시완산구
4th row전주시완산구
5th row전주시완산구

Common Values

ValueCountFrequency (%)
전주시완산구 14
16.7%
전주시덕진구 14
16.7%
완주 8
9.5%
군산 8
9.5%
익산 8
9.5%
정읍 7
8.3%
김제 5
 
6.0%
남원 5
 
6.0%
부안 3
 
3.6%
무주 3
 
3.6%
Other values (7) 9
10.7%

Length

2024-03-14T12:25:30.010318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시완산구 14
16.7%
전주시덕진구 14
16.7%
완주 8
9.5%
군산 8
9.5%
익산 8
9.5%
정읍 7
8.3%
김제 5
 
6.0%
남원 5
 
6.0%
무주 3
 
3.6%
부안 3
 
3.6%
Other values (7) 9
10.7%

Unnamed: 1
Text

MISSING 

Distinct82
Distinct (%)98.8%
Missing1
Missing (%)1.2%
Memory size804.0 B
2024-03-14T12:25:30.352923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length10.481928
Min length4

Characters and Unicode

Total characters870
Distinct characters149
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

Unique81 ?
Unique (%)97.6%

Sample

1st row설치장소
2nd row전주시청 민원실 내
3rd row완산구청 민원실 입구
4th row전북도청 민원실 앞
5th row서신동 주민센터 내부
ValueCountFrequency (%)
주민센터 20
 
9.3%
내 19
 
8.9%
민원실 17
 
7.9%
입구 16
 
7.5%
출입구 15
 
7.0%
앞 8
 
3.7%
민원실내 5
 
2.3%
옆 2
 
0.9%
김제시청 2
 
0.9%
수송동 2
 
0.9%
Other values (100) 108
50.5%
2024-03-14T12:25:30.717044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
131
 
15.1%
민 47
 
5.4%
원 37
 
4.3%
구 33
 
3.8%
내 31
 
3.6%
동 31
 
3.6%
입 31
 
3.6%
주 27
 
3.1%
실 25
 
2.9%
센 24
 
2.8%
Other values (139) 453
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 712
81.8%
Space Separator 131
 
15.1%
Decimal Number 21
 
2.4%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
민 47
 
6.6%
원 37
 
5.2%
구 33
 
4.6%
내 31
 
4.4%
동 31
 
4.4%
입 31
 
4.4%
주 27
 
3.8%
실 25
 
3.5%
센 24
 
3.4%
터 24
 
3.4%
Other values (128) 402
56.5%
Decimal Number
ValueCountFrequency (%)
1 8
38.1%
3 4
19.0%
2 4
19.0%
6 2
 
9.5%
5 2
 
9.5%
4 1
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 712
81.8%
Common 156
 
17.9%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
민 47
 
6.6%
원 37
 
5.2%
구 33
 
4.6%
내 31
 
4.4%
동 31
 
4.4%
입 31
 
4.4%
주 27
 
3.8%
실 25
 
3.5%
센 24
 
3.4%
터 24
 
3.4%
Other values (128) 402
56.5%
Common
ValueCountFrequency (%)
131
84.0%
1 8
 
5.1%
3 4
 
2.6%
2 4
 
2.6%
) 2
 
1.3%
( 2
 
1.3%
6 2
 
1.3%
5 2
 
1.3%
4 1
 
0.6%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 712
81.8%
ASCII 158
 
18.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
131
82.9%
1 8
 
5.1%
3 4
 
2.5%
2 4
 
2.5%
) 2
 
1.3%
( 2
 
1.3%
6 2
 
1.3%
5 2
 
1.3%
K 1
 
0.6%
4 1
 
0.6%
Hangul
ValueCountFrequency (%)
민 47
 
6.6%
원 37
 
5.2%
구 33
 
4.6%
내 31
 
4.4%
동 31
 
4.4%
입 31
 
4.4%
주 27
 
3.8%
실 25
 
3.5%
센 24
 
3.4%
터 24
 
3.4%
Other values (128) 402
56.5%

Unnamed: 2
Text

MISSING 

Distinct79
Distinct (%)95.2%
Missing1
Missing (%)1.2%
Memory size804.0 B
2024-03-14T12:25:31.004905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.9879518
Min length5

Characters and Unicode

Total characters829
Distinct characters128
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

Unique75 ?
Unique (%)90.4%

Sample

1st row소 재 지
2nd row완산구 노송광장로 10
3rd row완산구 서원로 232
4th row완산구 효자로 225
5th row완산구 서신천변14길 10
ValueCountFrequency (%)
덕진구 14
 
6.4%
완산구 14
 
6.4%
중앙로 6
 
2.7%
시청로 3
 
1.4%
봉동읍 3
 
1.4%
부안읍 3
 
1.4%
25 3
 
1.4%
10 3
 
1.4%
7 3
 
1.4%
조촌로 2
 
0.9%
Other values (154) 165
75.3%
2024-03-14T12:25:31.416236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
136
 
16.4%
로 64
 
7.7%
1 58
 
7.0%
2 34
 
4.1%
구 30
 
3.6%
5 25
 
3.0%
산 25
 
3.0%
3 24
 
2.9%
9 21
 
2.5%
길 19
 
2.3%
Other values (118) 393
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 444
53.6%
Decimal Number 236
28.5%
Space Separator 136
 
16.4%
Dash Punctuation 9
 
1.1%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 64
 
14.4%
구 30
 
6.8%
산 25
 
5.6%
길 19
 
4.3%
진 16
 
3.6%
완 14
 
3.2%
덕 14
 
3.2%
읍 13
 
2.9%
동 10
 
2.3%
성 9
 
2.0%
Other values (104) 230
51.8%
Decimal Number
ValueCountFrequency (%)
1 58
24.6%
2 34
14.4%
5 25
10.6%
3 24
10.2%
9 21
 
8.9%
0 18
 
7.6%
7 17
 
7.2%
6 16
 
6.8%
4 14
 
5.9%
8 9
 
3.8%
Space Separator
ValueCountFrequency (%)
136
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 444
53.6%
Common 385
46.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 64
 
14.4%
구 30
 
6.8%
산 25
 
5.6%
길 19
 
4.3%
진 16
 
3.6%
완 14
 
3.2%
덕 14
 
3.2%
읍 13
 
2.9%
동 10
 
2.3%
성 9
 
2.0%
Other values (104) 230
51.8%
Common
ValueCountFrequency (%)
136
35.3%
1 58
15.1%
2 34
 
8.8%
5 25
 
6.5%
3 24
 
6.2%
9 21
 
5.5%
0 18
 
4.7%
7 17
 
4.4%
6 16
 
4.2%
4 14
 
3.6%
Other values (4) 22
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 444
53.6%
ASCII 385
46.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
136
35.3%
1 58
15.1%
2 34
 
8.8%
5 25
 
6.5%
3 24
 
6.2%
9 21
 
5.5%
0 18
 
4.7%
7 17
 
4.4%
6 16
 
4.2%
4 14
 
3.6%
Other values (4) 22
 
5.7%
Hangul
ValueCountFrequency (%)
로 64
 
14.4%
구 30
 
6.8%
산 25
 
5.6%
길 19
 
4.3%
진 16
 
3.6%
완 14
 
3.2%
덕 14
 
3.2%
읍 13
 
2.9%
동 10
 
2.3%
성 9
 
2.0%
Other values (104) 230
51.8%

Unnamed: 3
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
24시간
36 
09:00~18:00
21 
08:00~18:00
6 
08:00~20:00
5 
08:00~22:00
4 
Other values (12)
12 

Length

Max length11
Median length11
Mean length7.702381
Min length1

Unique

Unique12 ?
Unique (%)14.3%

Sample

1st row<NA>
2nd row운영시간
3rd row05:00~24:00
4th row24시간
5th row24시간

Common Values

ValueCountFrequency (%)
24시간 36
42.9%
09:00~18:00 21
25.0%
08:00~18:00 6
 
7.1%
08:00~20:00 5
 
6.0%
08:00~22:00 4
 
4.8%
08:00~24:00 1
 
1.2%
05:00~24:00 1
 
1.2%
08:00~23:00 1
 
1.2%
09:00~21:00 1
 
1.2%
운영시간 1
 
1.2%
Other values (7) 7
 
8.3%

Length

2024-03-14T12:25:31.530878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
24시간 36
42.9%
09:00~18:00 21
25.0%
08:00~18:00 6
 
7.1%
08:00~20:00 5
 
6.0%
08:00~22:00 4
 
4.8%
na 1
 
1.2%
07:30~22:00 1
 
1.2%
07:00~22:00 1
 
1.2%
1
 
1.2%
09:00~17:00 1
 
1.2%
Other values (7) 7
 
8.3%

Unnamed: 4
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Memory size804.0 B
-
46 
토·일요일,공휴일 이용불가
19 
※ 가족관계등록부:토·일요일,공휴일 이용불가 ※ 등기부 등본 :일요일,공휴일 이용불가
8 
토,일,공휴일제외
 
4
<NA>
 
1
Other values (6)
6 

Length

Max length47
Median length1
Mean length10.154762
Min length1

Unique

Unique7 ?
Unique (%)8.3%

Sample

1st row<NA>
2nd row비고
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 46
54.8%
토·일요일,공휴일 이용불가 19
22.6%
※ 가족관계등록부:토·일요일,공휴일 이용불가 ※ 등기부 등본 :일요일,공휴일 이용불가 8
 
9.5%
토,일,공휴일제외 4
 
4.8%
<NA> 1
 
1.2%
비고 1
 
1.2%
토.일요일 이용가능(09:00~18:00) 1
 
1.2%
등기부등본 전용 토·일요일,공휴일 이용불가 1
 
1.2%
호적(공휴일이용불가) 등기부등본(일.공휴일 이용불가) 1
 
1.2%
window xp 기술지원 중단으로 14.4.30부터 기기운영중단 1
 
1.2%

Length

2024-03-14T12:25:31.623012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
46
27.1%
이용불가 37
21.8%
토·일요일,공휴일 20
11.8%
※ 16
 
9.4%
가족관계등록부:토·일요일,공휴일 8
 
4.7%
등기부 8
 
4.7%
등본 8
 
4.7%
일요일,공휴일 8
 
4.7%
토,일,공휴일제외 4
 
2.4%
등기부등본(일.공휴일 1
 
0.6%
Other values (14) 14
 
8.2%

Unnamed: 5
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size804.0 B
O
37 
-
37 
O(토일은 불가)
6 
<NA>
 
1
등기부등본 발급가능
 
1
Other values (2)
 
2

Length

Max length10
Median length1
Mean length1.7142857
Min length1

Unique

Unique4 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row등기부등본 발급가능
3rd rowO
4th rowO
5th rowO

Common Values

ValueCountFrequency (%)
O 37
44.0%
- 37
44.0%
O(토일은 불가) 6
 
7.1%
<NA> 1
 
1.2%
등기부등본 발급가능 1
 
1.2%
o 1
 
1.2%
x 1
 
1.2%

Length

2024-03-14T12:25:31.710133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:25:31.822238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 38
41.8%
37
40.7%
o(토일은 6
 
6.6%
불가 6
 
6.6%
na 1
 
1.1%
등기부등본 1
 
1.1%
발급가능 1
 
1.1%
x 1
 
1.1%

Unnamed: 6
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size804.0 B
O
51 
-
22 
O(토일은 불가)
 
5
o
 
2
2014.7.15
 
1
Other values (3)
 
3

Length

Max length11
Median length1
Mean length1.9047619
Min length1

Unique

Unique4 ?
Unique (%)4.8%

Sample

1st row2014.7.15
2nd row호적등초본 발급가능
3rd rowO
4th rowO
5th rowO

Common Values

ValueCountFrequency (%)
O 51
60.7%
- 22
26.2%
O(토일은 불가) 5
 
6.0%
o 2
 
2.4%
2014.7.15 1
 
1.2%
호적등초본 발급가능 1
 
1.2%
O(토.일은 불가) 1
 
1.2%
O(가족관계증명서등) 1
 
1.2%

Length

2024-03-14T12:25:31.925174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:25:32.026884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 53
58.2%
22
24.2%
불가 6
 
6.6%
o(토일은 5
 
5.5%
2014.7.15 1
 
1.1%
호적등초본 1
 
1.1%
발급가능 1
 
1.1%
o(토.일은 1
 
1.1%
o(가족관계증명서등 1
 
1.1%

Correlations

2024-03-14T12:25:32.108899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전라북도 무인민원발급기 설치현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
전라북도 무인민원발급기 설치현황1.0000.9901.0000.9340.8650.9020.940
Unnamed: 10.9901.0000.9951.0000.9770.9841.000
Unnamed: 21.0000.9951.0000.9380.0000.9790.996
Unnamed: 30.9341.0000.9381.0000.8790.7600.865
Unnamed: 40.8650.9770.0000.8791.0000.7030.807
Unnamed: 50.9020.9840.9790.7600.7031.0000.895
Unnamed: 60.9401.0000.9960.8650.8070.8951.000
2024-03-14T12:25:32.213265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 5전라북도 무인민원발급기 설치현황Unnamed: 3Unnamed: 6
Unnamed: 41.0000.4540.5500.5750.573
Unnamed: 50.4541.0000.6710.4600.781
전라북도 무인민원발급기 설치현황0.5500.6711.0000.5060.756
Unnamed: 30.5750.4600.5061.0000.595
Unnamed: 60.5730.7810.7560.5951.000
2024-03-14T12:25:32.329747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전라북도 무인민원발급기 설치현황Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
전라북도 무인민원발급기 설치현황1.0000.5060.5500.6710.756
Unnamed: 30.5061.0000.5750.4600.595
Unnamed: 40.5500.5751.0000.4540.573
Unnamed: 50.6710.4600.4541.0000.781
Unnamed: 60.7560.5950.5730.7811.000

Missing values

2024-03-14T12:25:29.706637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T12:25:29.795001image/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.
2024-03-14T12:25:29.881652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

전라북도 무인민원발급기 설치현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
0<NA><NA><NA><NA><NA><NA>2014.7.15
1시군명설치장소소 재 지운영시간비고등기부등본 발급가능호적등초본 발급가능
2전주시완산구전주시청 민원실 내완산구 노송광장로 1005:00~24:00-OO
3전주시완산구완산구청 민원실 입구완산구 서원로 23224시간-OO
4전주시완산구전북도청 민원실 앞완산구 효자로 22524시간-OO
5전주시완산구서신동 주민센터 내부완산구 서신천변14길 1009:00~18:00토,일,공휴일제외-O
6전주시완산구서신동 주민센터 외부완산구 서신천변14길 1024시간-OO
7전주시완산구삼천3동 주민센터 입구완산구 삼천천변2길 3724시간-OO
8전주시완산구평화2동 주민센터 앞완산구 평화18길 14-1624시간--O
9전주시완산구풍남동 주민센터 입구완산구 어진길 122-1224시간-OO
전라북도 무인민원발급기 설치현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
74무주안성면사무소 출입구안성면 안성로 246-1709:00~18:00---
75장수산서면사무소 출입구 오른쪽산서면 보산로 185809:00~18:00토·일요일,공휴일 이용불가OO
76장수장계면사무소 출입구 중앙현황 왼쪽장계면 한들로 153-309:00~18:00토·일요일,공휴일 이용불가OO
77임실임실군청 민원실 내임실읍 수정로 3008:30~17:30토·일요일,공휴일 이용불가OO(가족관계증명서등)
78순창순창농협 365코너순창읍 순창2길 2508:00~22:00---
79고창고창군청 민원실 출입구고창읍 중앙로 2508:00~22:00-oo
80고창농협하나로마트 출입구고창읍 성산로 2208:00~22:00-xo
81부안부안군지부 농협 365코너부안읍 번영로 121-window xp 기술지원 중단으로 14.4.30부터 기기운영중단--
82부안부안군청 민원실 로비부안읍 당산로 9107:00~22:00-OO
83부안부안KT 민원실부안읍 석정로 1799:00~18:00공휴일,일요일이용불가--