Overview

Dataset statistics

Number of variables17
Number of observations91
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.6 KiB
Average record size in memory141.5 B

Variable types

Numeric3
Categorical9
Text5

Alerts

발급종류 has constant value ""Constant
자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 시군명High correlation
위도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 순번 and 4 other fieldsHigh correlation
운영시간 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
관리기관명 is highly overall correlated with 순번 and 3 other fieldsHigh correlation
데이터기준 is highly overall correlated with 운영시간 and 1 other fieldsHigh correlation
데이터기준 is highly imbalanced (91.3%)Imbalance
순번 has unique valuesUnique
설치장소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 03:18:00.512263
Analysis finished2024-03-14 03:18:02.429636
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.604396
Minimum1
Maximum92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-03-14T12:18:02.504159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.5
Q123.5
median47
Q369.5
95-th percentile87.5
Maximum92
Range91
Interquartile range (IQR)46

Descriptive statistics

Standard deviation26.831109
Coefficient of variation (CV)0.57572057
Kurtosis-1.215468
Mean46.604396
Median Absolute Deviation (MAD)23
Skewness-0.01143062
Sum4241
Variance719.90842
MonotonicityStrictly increasing
2024-03-14T12:18:02.625832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
60 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
Other values (81) 81
89.0%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%

시군명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size860.0 B
전주시
29 
군산시
11 
정읍시
8 
완주군
8 
익산시
7 
Other values (9)
28 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 29
31.9%
군산시 11
 
12.1%
정읍시 8
 
8.8%
완주군 8
 
8.8%
익산시 7
 
7.7%
남원시 6
 
6.6%
김제시 6
 
6.6%
무주군 4
 
4.4%
부안군 4
 
4.4%
장수군 2
 
2.2%
Other values (4) 6
 
6.6%

Length

2024-03-14T12:18:02.720765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 29
31.9%
군산시 11
 
12.1%
정읍시 8
 
8.8%
완주군 8
 
8.8%
익산시 7
 
7.7%
남원시 6
 
6.6%
김제시 6
 
6.6%
무주군 4
 
4.4%
부안군 4
 
4.4%
장수군 2
 
2.2%
Other values (4) 6
 
6.6%

설치장소
Text

UNIQUE 

Distinct91
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size860.0 B
2024-03-14T12:18:02.894967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length8.0659341
Min length4

Characters and Unicode

Total characters734
Distinct characters152
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

Unique91 ?
Unique (%)100.0%

Sample

1st row전주시청
2nd row완산구청
3rd row풍남동주민센터
4th row예수병원
5th row평화2동주민센터
ValueCountFrequency (%)
민원실 7
 
5.1%
입구 4
 
2.9%
주민센터 4
 
2.9%
출입구 3
 
2.2%
내 3
 
2.2%
김제시청 2
 
1.4%
수송동 2
 
1.4%
로비 2
 
1.4%
출입 2
 
1.4%
민원실내 2
 
1.4%
Other values (106) 107
77.5%
2024-03-14T12:18:03.214205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47
 
6.4%
민 39
 
5.3%
동 35
 
4.8%
주 31
 
4.2%
터 28
 
3.8%
원 27
 
3.7%
센 27
 
3.7%
청 18
 
2.5%
소 18
 
2.5%
사 16
 
2.2%
Other values (142) 448
61.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 658
89.6%
Space Separator 47
 
6.4%
Decimal Number 17
 
2.3%
Open Punctuation 6
 
0.8%
Close Punctuation 6
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
민 39
 
5.9%
동 35
 
5.3%
주 31
 
4.7%
터 28
 
4.3%
원 27
 
4.1%
센 27
 
4.1%
청 18
 
2.7%
소 18
 
2.7%
사 16
 
2.4%
무 16
 
2.4%
Other values (133) 403
61.2%
Decimal Number
ValueCountFrequency (%)
1 7
41.2%
2 4
23.5%
3 3
17.6%
4 1
 
5.9%
6 1
 
5.9%
5 1
 
5.9%
Space Separator
ValueCountFrequency (%)
47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 658
89.6%
Common 76
 
10.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
민 39
 
5.9%
동 35
 
5.3%
주 31
 
4.7%
터 28
 
4.3%
원 27
 
4.1%
센 27
 
4.1%
청 18
 
2.7%
소 18
 
2.7%
사 16
 
2.4%
무 16
 
2.4%
Other values (133) 403
61.2%
Common
ValueCountFrequency (%)
47
61.8%
1 7
 
9.2%
( 6
 
7.9%
) 6
 
7.9%
2 4
 
5.3%
3 3
 
3.9%
4 1
 
1.3%
6 1
 
1.3%
5 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 658
89.6%
ASCII 76
 
10.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47
61.8%
1 7
 
9.2%
( 6
 
7.9%
) 6
 
7.9%
2 4
 
5.3%
3 3
 
3.9%
4 1
 
1.3%
6 1
 
1.3%
5 1
 
1.3%
Hangul
ValueCountFrequency (%)
민 39
 
5.9%
동 35
 
5.3%
주 31
 
4.7%
터 28
 
4.3%
원 27
 
4.1%
센 27
 
4.1%
청 18
 
2.7%
소 18
 
2.7%
사 16
 
2.4%
무 16
 
2.4%
Other values (133) 403
61.2%

설치위치
Text

Distinct68
Distinct (%)74.7%
Missing0
Missing (%)0.0%
Memory size860.0 B
2024-03-14T12:18:03.476452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length7.3406593
Min length2

Characters and Unicode

Total characters668
Distinct characters137
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

Unique57 ?
Unique (%)62.6%

Sample

1st row전주시청 민원실 내
2nd row완산구청 민원실
3rd row주민센터 밖
4th row예수병원 내
5th row주민센터 밖
ValueCountFrequency (%)
주민센터 16
 
8.4%
앞 14
 
7.3%
민원실 12
 
6.3%
내 11
 
5.8%
로비 7
 
3.7%
내부 7
 
3.7%
1층 6
 
3.1%
청사 4
 
2.1%
밖 4
 
2.1%
부안읍 3
 
1.6%
Other values (90) 107
56.0%
2024-03-14T12:18:03.903644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
101
 
15.1%
민 34
 
5.1%
1 30
 
4.5%
로 25
 
3.7%
터 21
 
3.1%
원 21
 
3.1%
센 20
 
3.0%
내 20
 
3.0%
주 19
 
2.8%
앞 16
 
2.4%
Other values (127) 361
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 483
72.3%
Space Separator 101
 
15.1%
Decimal Number 82
 
12.3%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
민 34
 
7.0%
로 25
 
5.2%
터 21
 
4.3%
원 21
 
4.3%
센 20
 
4.1%
내 20
 
4.1%
주 19
 
3.9%
앞 16
 
3.3%
실 16
 
3.3%
청 15
 
3.1%
Other values (115) 276
57.1%
Decimal Number
ValueCountFrequency (%)
1 30
36.6%
7 8
 
9.8%
0 7
 
8.5%
2 7
 
8.5%
8 6
 
7.3%
4 6
 
7.3%
3 6
 
7.3%
6 5
 
6.1%
9 4
 
4.9%
5 3
 
3.7%
Space Separator
ValueCountFrequency (%)
101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 483
72.3%
Common 185
 
27.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
민 34
 
7.0%
로 25
 
5.2%
터 21
 
4.3%
원 21
 
4.3%
센 20
 
4.1%
내 20
 
4.1%
주 19
 
3.9%
앞 16
 
3.3%
실 16
 
3.3%
청 15
 
3.1%
Other values (115) 276
57.1%
Common
ValueCountFrequency (%)
101
54.6%
1 30
 
16.2%
7 8
 
4.3%
0 7
 
3.8%
2 7
 
3.8%
8 6
 
3.2%
4 6
 
3.2%
3 6
 
3.2%
6 5
 
2.7%
9 4
 
2.2%
Other values (2) 5
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 483
72.3%
ASCII 185
 
27.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
101
54.6%
1 30
 
16.2%
7 8
 
4.3%
0 7
 
3.8%
2 7
 
3.8%
8 6
 
3.2%
4 6
 
3.2%
3 6
 
3.2%
6 5
 
2.7%
9 4
 
2.2%
Other values (2) 5
 
2.7%
Hangul
ValueCountFrequency (%)
민 34
 
7.0%
로 25
 
5.2%
터 21
 
4.3%
원 21
 
4.3%
센 20
 
4.1%
내 20
 
4.1%
주 19
 
3.9%
앞 16
 
3.3%
실 16
 
3.3%
청 15
 
3.1%
Other values (115) 276
57.1%

운영시간
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Memory size860.0 B
24시간
37 
09:00~18:00
21 
08:00~18:00
7 
08:00~20:00
4 
08:00~22:00
 
3
Other values (14)
19 

Length

Max length23
Median length11
Mean length8.3516484
Min length1

Unique

Unique10 ?
Unique (%)11.0%

Sample

1st row05:00~24:00
2nd row24시간
3rd row24시간
4th row24시간
5th row24시간

Common Values

ValueCountFrequency (%)
24시간 37
40.7%
09:00~18:00 21
23.1%
08:00~18:00 7
 
7.7%
08:00~20:00 4
 
4.4%
08:00~22:00 3
 
3.3%
09:00~17:00 3
 
3.3%
05:00~24:00 2
 
2.2%
08:00~23:00 2
 
2.2%
08:30~19:00(휴무일 제외) 2
 
2.2%
07:00~17:15 1
 
1.1%
Other values (9) 9
 
9.9%

Length

2024-03-14T12:18:04.030308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
24시간 37
39.4%
09:00~18:00 21
22.3%
08:00~18:00 7
 
7.4%
08:00~20:00 4
 
4.3%
08:00~22:00 3
 
3.2%
09:00~17:00 3
 
3.2%
05:00~24:00 2
 
2.1%
08:00~23:00 2
 
2.1%
08:30~19:00(휴무일 2
 
2.1%
제외 2
 
2.1%
Other values (11) 11
 
11.7%

발급종류
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size860.0 B
-
91 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 91
100.0%

Length

2024-03-14T12:18:04.114976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:18:04.179635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
91
100.0%

도로명주소
Text

Distinct87
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size860.0 B
2024-03-14T12:18:04.431207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length13.571429
Min length9

Characters and Unicode

Total characters1235
Distinct characters131
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

Unique83 ?
Unique (%)91.2%

Sample

1st row전주시 완산구 노송광장로 10
2nd row전주시 완산구 서원로 232
3rd row전주시 완산구 어진길 122-12
4th row전주시 완산구 서원로 365
5th row전주시 완산구 평화18길 14-16
ValueCountFrequency (%)
전주시 29
 
9.0%
완산구 15
 
4.7%
덕진구 14
 
4.3%
군산시 11
 
3.4%
정읍시 8
 
2.5%
완주군 8
 
2.5%
익산시 7
 
2.2%
남원시 6
 
1.9%
김제시 6
 
1.9%
중앙로 5
 
1.6%
Other values (175) 213
66.1%
2024-03-14T12:18:04.811268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
231
 
18.7%
로 72
 
5.8%
시 70
 
5.7%
1 62
 
5.0%
산 47
 
3.8%
주 43
 
3.5%
군 35
 
2.8%
2 35
 
2.8%
구 31
 
2.5%
전 30
 
2.4%
Other values (121) 579
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 744
60.2%
Decimal Number 251
 
20.3%
Space Separator 231
 
18.7%
Dash Punctuation 9
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 72
 
9.7%
시 70
 
9.4%
산 47
 
6.3%
주 43
 
5.8%
군 35
 
4.7%
구 31
 
4.2%
전 30
 
4.0%
완 23
 
3.1%
읍 21
 
2.8%
길 21
 
2.8%
Other values (109) 351
47.2%
Decimal Number
ValueCountFrequency (%)
1 62
24.7%
2 35
13.9%
3 30
12.0%
5 22
 
8.8%
9 20
 
8.0%
4 18
 
7.2%
0 18
 
7.2%
6 17
 
6.8%
7 16
 
6.4%
8 13
 
5.2%
Space Separator
ValueCountFrequency (%)
231
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 744
60.2%
Common 491
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 72
 
9.7%
시 70
 
9.4%
산 47
 
6.3%
주 43
 
5.8%
군 35
 
4.7%
구 31
 
4.2%
전 30
 
4.0%
완 23
 
3.1%
읍 21
 
2.8%
길 21
 
2.8%
Other values (109) 351
47.2%
Common
ValueCountFrequency (%)
231
47.0%
1 62
 
12.6%
2 35
 
7.1%
3 30
 
6.1%
5 22
 
4.5%
9 20
 
4.1%
4 18
 
3.7%
0 18
 
3.7%
6 17
 
3.5%
7 16
 
3.3%
Other values (2) 22
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 744
60.2%
ASCII 491
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
231
47.0%
1 62
 
12.6%
2 35
 
7.1%
3 30
 
6.1%
5 22
 
4.5%
9 20
 
4.1%
4 18
 
3.7%
0 18
 
3.7%
6 17
 
3.5%
7 16
 
3.3%
Other values (2) 22
 
4.5%
Hangul
ValueCountFrequency (%)
로 72
 
9.7%
시 70
 
9.4%
산 47
 
6.3%
주 43
 
5.8%
군 35
 
4.7%
구 31
 
4.2%
전 30
 
4.0%
완 23
 
3.1%
읍 21
 
2.8%
길 21
 
2.8%
Other values (109) 351
47.2%

지번주소
Text

Distinct87
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size860.0 B
2024-03-14T12:18:05.104594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length14.934066
Min length10

Characters and Unicode

Total characters1359
Distinct characters105
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

Unique83 ?
Unique (%)91.2%

Sample

1st row전주시 완산구 서노송동 568-
2nd row전주시 완산구 효자동 1가 59
3rd row전주시 완산구 경원동1가 126
4th row전주시 완산구 중화산동1가 3
5th row전주시 완산구 평화동1가 720
ValueCountFrequency (%)
전주시 29
 
8.8%
완산구 15
 
4.6%
덕진구 14
 
4.3%
군산시 11
 
3.3%
정읍시 8
 
2.4%
완주군 8
 
2.4%
익산시 7
 
2.1%
남원시 6
 
1.8%
김제시 6
 
1.8%
무주군 4
 
1.2%
Other values (173) 221
67.2%
2024-03-14T12:18:05.514231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
238
 
17.5%
1 71
 
5.2%
동 71
 
5.2%
시 67
 
4.9%
- 46
 
3.4%
3 43
 
3.2%
산 42
 
3.1%
주 42
 
3.1%
2 39
 
2.9%
군 36
 
2.6%
Other values (95) 664
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 739
54.4%
Decimal Number 336
24.7%
Space Separator 238
 
17.5%
Dash Punctuation 46
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 71
 
9.6%
시 67
 
9.1%
산 42
 
5.7%
주 42
 
5.7%
군 36
 
4.9%
전 29
 
3.9%
구 29
 
3.9%
리 28
 
3.8%
읍 28
 
3.8%
완 23
 
3.1%
Other values (83) 344
46.5%
Decimal Number
ValueCountFrequency (%)
1 71
21.1%
3 43
12.8%
2 39
11.6%
8 35
10.4%
5 31
9.2%
6 29
8.6%
4 28
 
8.3%
7 21
 
6.2%
9 20
 
6.0%
0 19
 
5.7%
Space Separator
ValueCountFrequency (%)
238
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 739
54.4%
Common 620
45.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 71
 
9.6%
시 67
 
9.1%
산 42
 
5.7%
주 42
 
5.7%
군 36
 
4.9%
전 29
 
3.9%
구 29
 
3.9%
리 28
 
3.8%
읍 28
 
3.8%
완 23
 
3.1%
Other values (83) 344
46.5%
Common
ValueCountFrequency (%)
238
38.4%
1 71
 
11.5%
- 46
 
7.4%
3 43
 
6.9%
2 39
 
6.3%
8 35
 
5.6%
5 31
 
5.0%
6 29
 
4.7%
4 28
 
4.5%
7 21
 
3.4%
Other values (2) 39
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 739
54.4%
ASCII 620
45.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
238
38.4%
1 71
 
11.5%
- 46
 
7.4%
3 43
 
6.9%
2 39
 
6.3%
8 35
 
5.6%
5 31
 
5.0%
6 29
 
4.7%
4 28
 
4.5%
7 21
 
3.4%
Other values (2) 39
 
6.3%
Hangul
ValueCountFrequency (%)
동 71
 
9.6%
시 67
 
9.1%
산 42
 
5.7%
주 42
 
5.7%
군 36
 
4.9%
전 29
 
3.9%
구 29
 
3.9%
리 28
 
3.8%
읍 28
 
3.8%
완 23
 
3.1%
Other values (83) 344
46.5%

관리기관명
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
-
16 
정읍시청
8 
익산시청
7 
효자4동 주민센터
6 
남원시
6 
Other values (37)
48 

Length

Max length10
Median length8
Mean length5.2307692
Min length1

Unique

Unique30 ?
Unique (%)33.0%

Sample

1st row전주시청 자치행정과
2nd row완산구청 민원봉사실
3rd row풍남동 주민센터
4th row중화산1동 주민센터
5th row평화2동 주민센터

Common Values

ValueCountFrequency (%)
- 16
17.6%
정읍시청 8
 
8.8%
익산시청 7
 
7.7%
효자4동 주민센터 6
 
6.6%
남원시 6
 
6.6%
덕진동 주민센터 4
 
4.4%
부안군청 4
 
4.4%
고창군청 2
 
2.2%
봉동읍사무소 2
 
2.2%
순창군 2
 
2.2%
Other values (32) 34
37.4%

Length

2024-03-14T12:18:05.677459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주민센터 26
21.7%
16
13.3%
정읍시청 8
 
6.7%
익산시청 7
 
5.8%
효자4동 6
 
5.0%
남원시 6
 
5.0%
덕진동 4
 
3.3%
부안군청 4
 
3.3%
민원봉사실 2
 
1.7%
서신동 2
 
1.7%
Other values (35) 39
32.5%

전화번호
Text

Distinct54
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Memory size860.0 B
2024-03-14T12:18:05.887078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.065934
Min length1

Characters and Unicode

Total characters916
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)46.2%

Sample

1st row063-281-2263
2nd row063-220-5243
3rd row063-220-1722
4th row063-220-1799
5th row063-220-1851
ValueCountFrequency (%)
16
 
17.6%
063-220-5668 6
 
6.6%
063-539-7704 4
 
4.4%
063-279-7187 4
 
4.4%
063-580-4384 4
 
4.4%
063-620-6103 3
 
3.3%
063-650-1421 2
 
2.2%
063-539-7739 2
 
2.2%
063-320-2863 2
 
2.2%
063-220-1875 2
 
2.2%
Other values (44) 46
50.5%
2024-03-14T12:18:06.216391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 166
18.1%
3 139
15.2%
0 134
14.6%
6 112
12.2%
2 91
9.9%
7 58
 
6.3%
5 55
 
6.0%
9 53
 
5.8%
8 41
 
4.5%
4 36
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 750
81.9%
Dash Punctuation 166
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 139
18.5%
0 134
17.9%
6 112
14.9%
2 91
12.1%
7 58
7.7%
5 55
 
7.3%
9 53
 
7.1%
8 41
 
5.5%
4 36
 
4.8%
1 31
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 916
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 166
18.1%
3 139
15.2%
0 134
14.6%
6 112
12.2%
2 91
9.9%
7 58
 
6.3%
5 55
 
6.0%
9 53
 
5.8%
8 41
 
4.5%
4 36
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 916
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 166
18.1%
3 139
15.2%
0 134
14.6%
6 112
12.2%
2 91
9.9%
7 58
 
6.3%
5 55
 
6.0%
9 53
 
5.8%
8 41
 
4.5%
4 36
 
3.9%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct88
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.01513
Minimum126.47058
Maximum127.47233
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-03-14T12:18:06.368018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.47058
5-th percentile126.69678
Q1126.87089
median127.09878
Q3127.13794
95-th percentile127.35604
Maximum127.47233
Range1.0017453
Interquartile range (IQR)0.2670452

Descriptive statistics

Standard deviation0.21067284
Coefficient of variation (CV)0.0016586436
Kurtosis-0.23626381
Mean127.01513
Median Absolute Deviation (MAD)0.1337782
Skewness-0.34178057
Sum11558.377
Variance0.044383044
MonotonicityNot monotonic
2024-03-14T12:18:06.515035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.2325605 2
 
2.2%
126.8805385 2
 
2.2%
126.7177336 2
 
2.2%
127.1720502 1
 
1.1%
126.7366617 1
 
1.1%
126.4705843 1
 
1.1%
126.7331643 1
 
1.1%
126.7335639 1
 
1.1%
126.6945284 1
 
1.1%
126.701973 1
 
1.1%
Other values (78) 78
85.7%
ValueCountFrequency (%)
126.4705843 1
1.1%
126.550305 1
1.1%
126.5503087 1
1.1%
126.6755219 1
1.1%
126.6945284 1
1.1%
126.6990299 1
1.1%
126.6996426 1
1.1%
126.701973 1
1.1%
126.7123933 1
1.1%
126.7177336 2
2.2%
ValueCountFrequency (%)
127.4723296 1
1.1%
127.464585 1
1.1%
127.3938838 1
1.1%
127.3911278 1
1.1%
127.3600511 1
1.1%
127.3520361 1
1.1%
127.2528784 1
1.1%
127.2400822 1
1.1%
127.2346906 1
1.1%
127.2325605 2
2.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct88
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.745601
Minimum35.212657
Maximum36.078317
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2024-03-14T12:18:06.629885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.212657
5-th percentile35.245981
Q135.582963
median35.820613
Q335.919759
95-th percentile35.97033
Maximum36.078317
Range0.86566033
Interquartile range (IQR)0.33679577

Descriptive statistics

Standard deviation0.22572619
Coefficient of variation (CV)0.0063147963
Kurtosis0.040865077
Mean35.745601
Median Absolute Deviation (MAD)0.1196195
Skewness-1.0425621
Sum3252.8497
Variance0.050952312
MonotonicityNot monotonic
2024-03-14T12:18:06.743439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.2459811 2
 
2.2%
35.80384388 2
 
2.2%
35.9646958 2
 
2.2%
35.37032518 1
 
1.1%
35.7295433 1
 
1.1%
35.6208729 1
 
1.1%
35.7317814 1
 
1.1%
35.7265122 1
 
1.1%
35.4379323 1
 
1.1%
35.435836 1
 
1.1%
Other values (78) 78
85.7%
ValueCountFrequency (%)
35.21265667 1
1.1%
35.22289318 1
1.1%
35.22370714 1
1.1%
35.24355953 1
1.1%
35.2459811 2
2.2%
35.2511147 1
1.1%
35.2751276 1
1.1%
35.35028353 1
1.1%
35.37032518 1
1.1%
35.43552989 1
1.1%
ValueCountFrequency (%)
36.078317 1
1.1%
36.00289815 1
1.1%
36.00261431 1
1.1%
35.97752993 1
1.1%
35.9730866 1
1.1%
35.96757296 1
1.1%
35.96488465 1
1.1%
35.9646958 2
2.2%
35.9622388 1
1.1%
35.96117347 1
1.1%

데이터기준
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size860.0 B
2015-09-30
90 
09/10/15
 
1

Length

Max length10
Median length10
Mean length9.978022
Min length8

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row2015-09-30
2nd row2015-09-30
3rd row2015-09-30
4th row2015-09-30
5th row2015-09-30

Common Values

ValueCountFrequency (%)
2015-09-30 90
98.9%
09/10/15 1
 
1.1%

Length

2024-03-14T12:18:06.848366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:18:06.925163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015-09-30 90
98.9%
09/10/15 1
 
1.1%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size860.0 B
정보화총괄과
91 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정보화총괄과 91
100.0%

Length

2024-03-14T12:18:07.014117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:18:07.088643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정보화총괄과 91
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size860.0 B
공개
91 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 91
100.0%

Length

2024-03-14T12:18:07.173963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:18:07.245346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 91
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size860.0 B
2015.1
91 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 91
100.0%

Length

2024-03-14T12:18:07.313787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:18:07.394944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 91
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size860.0 B
1년
91 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 91
100.0%

Length

2024-03-14T12:18:07.469038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:18:07.539386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 91
100.0%

Interactions

2024-03-14T12:18:01.991879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:18:01.607551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:18:01.799946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:18:02.055153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:18:01.663446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:18:01.874296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:18:02.117163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:18:01.728961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:18:01.930630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T12:18:07.594563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명설치장소설치위치운영시간도로명주소지번주소관리기관명전화번호경도위도데이터기준
순번1.0000.9301.0000.9470.6430.9890.9890.9730.9610.7730.9000.000
시군명0.9301.0001.0001.0000.9141.0001.0000.9990.9930.9230.9360.000
설치장소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설치위치0.9471.0001.0001.0000.9951.0001.0000.0000.0000.9830.9451.000
운영시간0.6430.9141.0000.9951.0000.9610.9610.7260.0000.6910.7481.000
도로명주소0.9891.0001.0001.0000.9611.0001.0001.0001.0001.0001.0001.000
지번주소0.9891.0001.0001.0000.9611.0001.0001.0001.0001.0001.0001.000
관리기관명0.9730.9991.0000.0000.7261.0001.0001.0001.0000.9170.9581.000
전화번호0.9610.9931.0000.0000.0001.0001.0001.0001.0000.9670.9711.000
경도0.7730.9231.0000.9830.6911.0001.0000.9170.9671.0000.7930.509
위도0.9000.9361.0000.9450.7481.0001.0000.9580.9710.7931.0000.000
데이터기준0.0000.0001.0001.0001.0001.0001.0001.0001.0000.5090.0001.000
2024-03-14T12:18:07.705572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명관리기관명운영시간데이터기준
시군명1.0000.7410.5900.000
관리기관명0.7411.0000.2070.742
운영시간0.5900.2071.0000.899
데이터기준0.0000.7420.8991.000
2024-03-14T12:18:07.818455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번경도위도시군명운영시간관리기관명데이터기준
순번1.000-0.4040.0550.7160.2820.6350.000
경도-0.4041.000-0.2420.7100.3290.4930.490
위도0.055-0.2421.0000.7330.3700.5850.000
시군명0.7160.7100.7331.0000.5900.7410.000
운영시간0.2820.3290.3700.5901.0000.2070.899
관리기관명0.6350.4930.5850.7410.2071.0000.742
데이터기준0.0000.4900.0000.0000.8990.7421.000

Missing values

2024-03-14T12:18:02.213936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T12:18:02.369548image/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

순번시군명설치장소설치위치운영시간발급종류도로명주소지번주소관리기관명전화번호경도위도데이터기준자료출처공개여부작성일갱신주기
01전주시전주시청전주시청 민원실 내05:00~24:00-전주시 완산구 노송광장로 10전주시 완산구 서노송동 568-전주시청 자치행정과063-281-2263127.14780735.8244362015-09-30정보화총괄과공개2015.11년
12전주시완산구청완산구청 민원실24시간-전주시 완산구 서원로 232전주시 완산구 효자동 1가 59완산구청 민원봉사실063-220-5243127.11980335.8121532015-09-30정보화총괄과공개2015.11년
23전주시풍남동주민센터주민센터 밖24시간-전주시 완산구 어진길 122-12전주시 완산구 경원동1가 126풍남동 주민센터063-220-1722127.14811235.8170372015-09-30정보화총괄과공개2015.11년
34전주시예수병원예수병원 내24시간-전주시 완산구 서원로 365전주시 완산구 중화산동1가 3중화산1동 주민센터063-220-1799127.13289935.8141352015-09-30정보화총괄과공개2015.11년
45전주시평화2동주민센터주민센터 밖24시간-전주시 완산구 평화18길 14-16전주시 완산구 평화동1가 720평화2동 주민센터063-220-1851127.13528535.7955182015-09-30정보화총괄과공개2015.11년
56전주시서신동주민센터(내부)주민센터 내09:00~18:00-전주시 완산구 서신천변14길 1전주시 완산구 서신동 804서신동 주민센터063-220-1875127.11532635.8309872015-09-30정보화총괄과공개2015.11년
67전주시서신동주민센터(외부)주민센터 외부24시간-전주시 완산구 서신천변14길 1전주시 완산구 서신동 804서신동 주민센터063-220-1875127.11533435.8311162015-09-30정보화총괄과공개2015.11년
78전주시삼천1동주민센터주민센터 외부24시간-전주시 완산구 성지산로 33전주시 완산구 삼천동1가 573삼천1동 주민센터063-220-1902127.12161635.8008192015-09-30정보화총괄과공개2015.11년
89전주시삼천3동주민센터주민센터 외부24시간-전주시 완산구 삼천천변2길 37전주시 완산구 삼천동1가 287삼천3동 주민센터063-220-1935127.11430835.7968632015-09-30정보화총괄과공개2015.11년
910전주시서곡치안센터서곡치안센터 옆24시간-전주시 완산구 세내로 552전주시 완산구 효자동3가 145효자4동 주민센터063-220-5668127.09919635.8343322015-09-30정보화총괄과공개2015.11년
순번시군명설치장소설치위치운영시간발급종류도로명주소지번주소관리기관명전화번호경도위도데이터기준자료출처공개여부작성일갱신주기
8183군산시조촌동 주민센터 입구조촌로 10224시간-군산시 조촌로 102군산시 조촌동 739-1--126.73801135.9730872015-09-30정보화총괄과공개2015.11년
8284군산시근로자종합복지관동아로1124시간-군산시 동아로11군산시 산북동 3601-3--126.67552235.9611732015-09-30정보화총괄과공개2015.11년
8385군산시군신시 의료원의료원로 2724시간-군산시 의료원로 27군산시 지곡동 29-1--126.71239335.9545932015-09-30정보화총괄과공개2015.11년
8486김제시김제시청 당직실 앞중앙로 4008:00~24:00-김제시 중앙로 40김제시 서암동 353--126.88053935.8038442015-09-30정보화총괄과공개2015.11년
8587김제시김제시청 민원실중앙로 4009:00~18:00-김제시 중앙로 40김제시 서암동 353--126.88053935.8038442015-09-30정보화총괄과공개2015.11년
8688김제시보건소 출입구성산길 13807:30~22:00-김제시 성산길 138김제시 요촌동 423-2--126.88330635.8007792015-09-30정보화총괄과공개2015.11년
8789김제시신풍동사무소 출입구중앙10길 1108:00~18:00-김제시 중앙10길 11김제시 신풍동 188-62--126.89776535.7960892015-09-30정보화총괄과공개2015.11년
8890김제시검산주공 1차 아파트요촌북로 11008:00~20:00-김제시 요촌북로 110김제시 검산동 1030-1--126.89637735.8073952015-09-30정보화총괄과공개2015.11년
8991김제시검산동사무소검산택지길 3408:00~18:00-김제시 검산택지길 34김제시 검산동 1057-11--126.90369435.8032062015-09-30정보화총괄과공개2015.11년
9092군산시오식도동 자유무역관리원군산산단민원센터09:00~21:00(일,공휴일 이용불가)-군산시 자유로 483군산시 오식도동 514군산시청063-454-7840126.55030535.96045509/10/15정보화총괄과공개2015.11년