Overview

Dataset statistics

Number of variables12
Number of observations119
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.4 KiB
Average record size in memory98.1 B

Variable types

Numeric1
Categorical4
Text7

Alerts

행정구 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
시군구 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 시군구 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
번지 has unique valuesUnique

Reproduction

Analysis started2024-03-14 02:08:23.395054
Analysis finished2024-03-14 02:08:24.936230
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct119
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60
Minimum1
Maximum119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-14T11:08:24.999148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.9
Q130.5
median60
Q389.5
95-th percentile113.1
Maximum119
Range118
Interquartile range (IQR)59

Descriptive statistics

Standard deviation34.496377
Coefficient of variation (CV)0.57493961
Kurtosis-1.2
Mean60
Median Absolute Deviation (MAD)30
Skewness0
Sum7140
Variance1190
MonotonicityStrictly increasing
2024-03-14T11:08:25.129689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
2 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
82 1
 
0.8%
Other values (109) 109
91.6%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%
111 1
0.8%
110 1
0.8%

시군구
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
전주시
26 
익산시
17 
정읍시
13 
군산시
12 
남원시
10 
Other values (9)
41 

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 26
21.8%
익산시 17
14.3%
정읍시 13
10.9%
군산시 12
10.1%
남원시 10
 
8.4%
김제시 8
 
6.7%
임실군 8
 
6.7%
완주군 6
 
5.0%
고창군 5
 
4.2%
진안군 4
 
3.4%
Other values (4) 10
 
8.4%

Length

2024-03-14T11:08:25.350466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 26
21.8%
익산시 17
14.3%
정읍시 13
10.9%
군산시 12
10.1%
남원시 10
 
8.4%
김제시 8
 
6.7%
임실군 8
 
6.7%
완주군 6
 
5.0%
고창군 5
 
4.2%
진안군 4
 
3.4%
Other values (4) 10
 
8.4%

작은도서관 명칭
Text

Distinct118
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T11:08:25.632415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length8.5714286
Min length7

Characters and Unicode

Total characters1020
Distinct characters196
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)98.3%

Sample

1st row간납대작은도서관
2nd row건지산숲속작은도서관
3rd row팔복작은도서관
4th row호성작은도서관
5th row큰나루작은도서관
ValueCountFrequency (%)
작은도서관 24
 
15.8%
작은 3
 
2.0%
도서관 3
 
2.0%
글마루작은도서관 2
 
1.3%
죽산작은도서관 1
 
0.7%
휴먼시아 1
 
0.7%
jg작은도서관 1
 
0.7%
희망남포작은도서관 1
 
0.7%
새마을 1
 
0.7%
길보작은도서관 1
 
0.7%
Other values (114) 114
75.0%
2024-03-14T11:08:25.964825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 122
 
12.0%
은 121
 
11.9%
서 121
 
11.9%
작 119
 
11.7%
도 119
 
11.7%
33
 
3.2%
산 14
 
1.4%
지 9
 
0.9%
나 9
 
0.9%
성 7
 
0.7%
Other values (186) 346
33.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 984
96.5%
Space Separator 33
 
3.2%
Uppercase Letter 2
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 122
 
12.4%
은 121
 
12.3%
서 121
 
12.3%
작 119
 
12.1%
도 119
 
12.1%
산 14
 
1.4%
지 9
 
0.9%
나 9
 
0.9%
성 7
 
0.7%
수 7
 
0.7%
Other values (182) 336
34.1%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
J 1
50.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 984
96.5%
Common 34
 
3.3%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 122
 
12.4%
은 121
 
12.3%
서 121
 
12.3%
작 119
 
12.1%
도 119
 
12.1%
산 14
 
1.4%
지 9
 
0.9%
나 9
 
0.9%
성 7
 
0.7%
수 7
 
0.7%
Other values (182) 336
34.1%
Common
ValueCountFrequency (%)
33
97.1%
3 1
 
2.9%
Latin
ValueCountFrequency (%)
G 1
50.0%
J 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 984
96.5%
ASCII 36
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 122
 
12.4%
은 121
 
12.3%
서 121
 
12.3%
작 119
 
12.1%
도 119
 
12.1%
산 14
 
1.4%
지 9
 
0.9%
나 9
 
0.9%
성 7
 
0.7%
수 7
 
0.7%
Other values (182) 336
34.1%
ASCII
ValueCountFrequency (%)
33
91.7%
G 1
 
2.8%
J 1
 
2.8%
3 1
 
2.8%

개관년도
Categorical

Distinct13
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2008
23 
2013
21 
2009
19 
2011
16 
2012
14 
Other values (8)
26 

Length

Max length4
Median length4
Mean length3.8991597
Min length1

Unique

Unique3 ?
Unique (%)2.5%

Sample

1st row2013
2nd row2013
3rd row2008
4th row2008
5th row2009

Common Values

ValueCountFrequency (%)
2008 23
19.3%
2013 21
17.6%
2009 19
16.0%
2011 16
13.4%
2012 14
11.8%
2010 7
 
5.9%
2014 7
 
5.9%
- 4
 
3.4%
2007 3
 
2.5%
2004 2
 
1.7%
Other values (3) 3
 
2.5%

Length

2024-03-14T11:08:26.074369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2008 23
19.3%
2013 21
17.6%
2009 19
16.0%
2011 16
13.4%
2012 14
11.8%
2010 7
 
5.9%
2014 7
 
5.9%
4
 
3.4%
2007 3
 
2.5%
2004 2
 
1.7%
Other values (3) 3
 
2.5%

연락처
Text

Distinct105
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T11:08:26.299978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length7.6302521
Min length1

Characters and Unicode

Total characters908
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)84.9%

Sample

1st row-
2nd row714-2812
3rd row212-210
4th row245-9030
5th row271-9337
ValueCountFrequency (%)
12
 
10.1%
352-3302 2
 
1.7%
533-0522 2
 
1.7%
535-0365 2
 
1.7%
635-6634 1
 
0.8%
223-4167 1
 
0.8%
547-0431 1
 
0.8%
543-5007~8 1
 
0.8%
546-2079 1
 
0.8%
545-1923~5 1
 
0.8%
Other values (95) 95
79.8%
2024-03-14T11:08:26.680696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 127
14.0%
2 115
12.7%
5 107
11.8%
3 95
10.5%
0 94
10.4%
6 74
8.1%
4 71
7.8%
1 67
7.4%
8 63
6.9%
7 55
6.1%
Other values (2) 40
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 779
85.8%
Dash Punctuation 127
 
14.0%
Math Symbol 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 115
14.8%
5 107
13.7%
3 95
12.2%
0 94
12.1%
6 74
9.5%
4 71
9.1%
1 67
8.6%
8 63
8.1%
7 55
7.1%
9 38
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 127
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 908
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 127
14.0%
2 115
12.7%
5 107
11.8%
3 95
10.5%
0 94
10.4%
6 74
8.1%
4 71
7.8%
1 67
7.4%
8 63
6.9%
7 55
6.1%
Other values (2) 40
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 908
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 127
14.0%
2 115
12.7%
5 107
11.8%
3 95
10.5%
0 94
10.4%
6 74
8.1%
4 71
7.8%
1 67
7.4%
8 63
6.9%
7 55
6.1%
Other values (2) 40
 
4.4%

운영주체
Text

Distinct71
Distinct (%)59.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T11:08:26.874885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length8
Min length4

Characters and Unicode

Total characters952
Distinct characters151
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

Unique66 ?
Unique (%)55.5%

Sample

1st row간납대작은도서관운영위원회
2nd row전주시 직영
3rd row팔복동주민자치위원회
4th row호성동주민자치위원회
5th row덕진노인복지회관
ValueCountFrequency (%)
직영 36
22.4%
지자체 34
21.1%
주민자치위원회 11
 
6.8%
장수문화원 3
 
1.9%
민간 3
 
1.9%
위탁 3
 
1.9%
전주시 2
 
1.2%
교육문화센터 1
 
0.6%
왕궁면주민자치위원회 1
 
0.6%
2(삼성동주민자치위원회 1
 
0.6%
Other values (66) 66
41.0%
2024-03-14T11:08:27.167196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
자 59
 
6.2%
회 55
 
5.8%
지 51
 
5.4%
영 47
 
4.9%
42
 
4.4%
원 39
 
4.1%
직 36
 
3.8%
체 35
 
3.7%
위 33
 
3.5%
주 32
 
3.4%
Other values (141) 523
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 896
94.1%
Space Separator 42
 
4.4%
Decimal Number 12
 
1.3%
Open Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 59
 
6.6%
회 55
 
6.1%
지 51
 
5.7%
영 47
 
5.2%
원 39
 
4.4%
직 36
 
4.0%
체 35
 
3.9%
위 33
 
3.7%
주 32
 
3.6%
관 26
 
2.9%
Other values (131) 483
53.9%
Decimal Number
ValueCountFrequency (%)
2 3
25.0%
1 2
16.7%
5 2
16.7%
3 2
16.7%
9 1
 
8.3%
6 1
 
8.3%
4 1
 
8.3%
Space Separator
ValueCountFrequency (%)
42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 896
94.1%
Common 56
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 59
 
6.6%
회 55
 
6.1%
지 51
 
5.7%
영 47
 
5.2%
원 39
 
4.4%
직 36
 
4.0%
체 35
 
3.9%
위 33
 
3.7%
주 32
 
3.6%
관 26
 
2.9%
Other values (131) 483
53.9%
Common
ValueCountFrequency (%)
42
75.0%
2 3
 
5.4%
1 2
 
3.6%
5 2
 
3.6%
3 2
 
3.6%
( 1
 
1.8%
@ 1
 
1.8%
9 1
 
1.8%
6 1
 
1.8%
4 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 896
94.1%
ASCII 56
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
자 59
 
6.6%
회 55
 
6.1%
지 51
 
5.7%
영 47
 
5.2%
원 39
 
4.4%
직 36
 
4.0%
체 35
 
3.9%
위 33
 
3.7%
주 32
 
3.6%
관 26
 
2.9%
Other values (131) 483
53.9%
ASCII
ValueCountFrequency (%)
42
75.0%
2 3
 
5.4%
1 2
 
3.6%
5 2
 
3.6%
3 2
 
3.6%
( 1
 
1.8%
@ 1
 
1.8%
9 1
 
1.8%
6 1
 
1.8%
4 1
 
1.8%

건물면적(㎡)
Text

Distinct86
Distinct (%)72.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T11:08:27.379595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.8487395
Min length1

Characters and Unicode

Total characters339
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)52.9%

Sample

1st row49
2nd row50
3rd row270
4th row137
5th row179
ValueCountFrequency (%)
100 5
 
4.2%
4
 
3.4%
132 4
 
3.4%
138 3
 
2.5%
135 3
 
2.5%
145 3
 
2.5%
126 3
 
2.5%
173 2
 
1.7%
120 2
 
1.7%
181 2
 
1.7%
Other values (75) 88
73.9%
2024-03-14T11:08:27.859367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 96
28.3%
2 42
12.4%
3 34
 
10.0%
0 33
 
9.7%
6 29
 
8.6%
5 25
 
7.4%
8 22
 
6.5%
7 19
 
5.6%
9 19
 
5.6%
4 14
 
4.1%
Other values (2) 6
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 333
98.2%
Dash Punctuation 4
 
1.2%
Space Separator 2
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 96
28.8%
2 42
12.6%
3 34
 
10.2%
0 33
 
9.9%
6 29
 
8.7%
5 25
 
7.5%
8 22
 
6.6%
7 19
 
5.7%
9 19
 
5.7%
4 14
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 339
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 96
28.3%
2 42
12.4%
3 34
 
10.0%
0 33
 
9.7%
6 29
 
8.6%
5 25
 
7.4%
8 22
 
6.5%
7 19
 
5.6%
9 19
 
5.6%
4 14
 
4.1%
Other values (2) 6
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 339
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 96
28.3%
2 42
12.4%
3 34
 
10.0%
0 33
 
9.7%
6 29
 
8.6%
5 25
 
7.4%
8 22
 
6.5%
7 19
 
5.6%
9 19
 
5.6%
4 14
 
4.1%
Other values (2) 6
 
1.8%

열람석(㎡)
Categorical

Distinct43
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
-
13 
50
12 
20
10 
30
10 
40
9 
Other values (38)
65 

Length

Max length3
Median length2
Mean length2.092437
Min length1

Unique

Unique25 ?
Unique (%)21.0%

Sample

1st row15
2nd row30
3rd row74
4th row20
5th row40

Common Values

ValueCountFrequency (%)
- 13
 
10.9%
50 12
 
10.1%
20 10
 
8.4%
30 10
 
8.4%
40 9
 
7.6%
15 5
 
4.2%
25 5
 
4.2%
- 5
 
4.2%
10 5
 
4.2%
24 4
 
3.4%
Other values (33) 41
34.5%

Length

2024-03-14T11:08:27.975149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
18
15.1%
50 12
 
10.1%
20 10
 
8.4%
30 10
 
8.4%
40 9
 
7.6%
15 5
 
4.2%
25 5
 
4.2%
10 5
 
4.2%
24 4
 
3.4%
100 2
 
1.7%
Other values (32) 39
32.8%

보유장서
Text

Distinct111
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T11:08:28.198282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.1176471
Min length3

Characters and Unicode

Total characters609
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)89.9%

Sample

1st row1,225
2nd row1,285
3rd row10,209
4th row10,495
5th row7,968
ValueCountFrequency (%)
6
 
5.0%
2,000 2
 
1.7%
3,200 2
 
1.7%
3,000 2
 
1.7%
5,589 1
 
0.8%
6,479 1
 
0.8%
10,150 1
 
0.8%
8,554 1
 
0.8%
1,713 1
 
0.8%
7,579 1
 
0.8%
Other values (101) 101
84.9%
2024-03-14T11:08:28.538537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 113
18.6%
0 81
13.3%
1 75
12.3%
6 48
7.9%
8 45
 
7.4%
2 43
 
7.1%
7 43
 
7.1%
5 43
 
7.1%
4 37
 
6.1%
9 34
 
5.6%
Other values (3) 47
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 478
78.5%
Other Punctuation 113
 
18.6%
Space Separator 12
 
2.0%
Dash Punctuation 6
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 81
16.9%
1 75
15.7%
6 48
10.0%
8 45
9.4%
2 43
9.0%
7 43
9.0%
5 43
9.0%
4 37
7.7%
9 34
7.1%
3 29
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 113
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 609
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 113
18.6%
0 81
13.3%
1 75
12.3%
6 48
7.9%
8 45
 
7.4%
2 43
 
7.1%
7 43
 
7.1%
5 43
 
7.1%
4 37
 
6.1%
9 34
 
5.6%
Other values (3) 47
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 609
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 113
18.6%
0 81
13.3%
1 75
12.3%
6 48
7.9%
8 45
 
7.4%
2 43
 
7.1%
7 43
 
7.1%
5 43
 
7.1%
4 37
 
6.1%
9 34
 
5.6%
Other values (3) 47
7.7%

행정구
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
익산시
17 
전주시 완산구
14 
정읍시
13 
전주시 덕진구
12 
군산시
12 
Other values (10)
51 

Length

Max length7
Median length3
Mean length3.8739496
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
익산시 17
14.3%
전주시 완산구 14
11.8%
정읍시 13
10.9%
전주시 덕진구 12
10.1%
군산시 12
10.1%
남원시 10
8.4%
김제시 8
6.7%
임실군 8
6.7%
완주군 6
 
5.0%
고창군 5
 
4.2%
Other values (5) 14
11.8%

Length

2024-03-14T11:08:28.681262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 26
17.9%
익산시 17
11.7%
완산구 14
9.7%
정읍시 13
9.0%
덕진구 12
8.3%
군산시 12
8.3%
남원시 10
 
6.9%
김제시 8
 
5.5%
임실군 8
 
5.5%
완주군 6
 
4.1%
Other values (6) 19
13.1%

행정동.면
Text

Distinct103
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T11:08:28.936617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.6134454
Min length2

Characters and Unicode

Total characters430
Distinct characters117
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

Unique92 ?
Unique (%)77.3%

Sample

1st row풍남동3가
2nd row인후동2가
3rd row팔복동1가
4th row호성동1가
5th row덕진동2가
ValueCountFrequency (%)
상동 4
 
3.3%
임실읍 4
 
3.3%
부송동 3
 
2.5%
순창읍 2
 
1.7%
평화동1가 2
 
1.7%
진안읍 2
 
1.7%
금동 2
 
1.7%
안성면 2
 
1.7%
효자1가 2
 
1.7%
중화산동2가 2
 
1.7%
Other values (94) 96
79.3%
2024-03-14T11:08:29.277132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 60
 
14.0%
면 38
 
8.8%
산 18
 
4.2%
가 17
 
4.0%
로 15
 
3.5%
읍 11
 
2.6%
서 10
 
2.3%
2 9
 
2.1%
9
 
2.1%
1 8
 
1.9%
Other values (107) 235
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 391
90.9%
Decimal Number 22
 
5.1%
Space Separator 9
 
2.1%
Open Punctuation 4
 
0.9%
Close Punctuation 4
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 60
 
15.3%
면 38
 
9.7%
산 18
 
4.6%
가 17
 
4.3%
로 15
 
3.8%
읍 11
 
2.8%
서 10
 
2.6%
송 8
 
2.0%
성 8
 
2.0%
화 8
 
2.0%
Other values (99) 198
50.6%
Decimal Number
ValueCountFrequency (%)
2 9
40.9%
1 8
36.4%
5 2
 
9.1%
3 2
 
9.1%
9 1
 
4.5%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 391
90.9%
Common 39
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 60
 
15.3%
면 38
 
9.7%
산 18
 
4.6%
가 17
 
4.3%
로 15
 
3.8%
읍 11
 
2.8%
서 10
 
2.6%
송 8
 
2.0%
성 8
 
2.0%
화 8
 
2.0%
Other values (99) 198
50.6%
Common
ValueCountFrequency (%)
2 9
23.1%
9
23.1%
1 8
20.5%
( 4
10.3%
) 4
10.3%
5 2
 
5.1%
3 2
 
5.1%
9 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 391
90.9%
ASCII 39
 
9.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 60
 
15.3%
면 38
 
9.7%
산 18
 
4.6%
가 17
 
4.3%
로 15
 
3.8%
읍 11
 
2.8%
서 10
 
2.6%
송 8
 
2.0%
성 8
 
2.0%
화 8
 
2.0%
Other values (99) 198
50.6%
ASCII
ValueCountFrequency (%)
2 9
23.1%
9
23.1%
1 8
20.5%
( 4
10.3%
) 4
10.3%
5 2
 
5.1%
3 2
 
5.1%
9 1
 
2.6%

번지
Text

UNIQUE 

Distinct119
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T11:08:29.486654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length10.403361
Min length2

Characters and Unicode

Total characters1238
Distinct characters179
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)100.0%

Sample

1st row7-33번지
2nd row산2-91
3rd row1가 138-6 팔복주민센터 2층
4th row863-44
5th row2가172
ValueCountFrequency (%)
2층 8
 
3.2%
1층 5
 
2.0%
완주군 5
 
2.0%
3층 4
 
1.6%
내 3
 
1.2%
익산시 2
 
0.8%
장류로 2
 
0.8%
2길 2
 
0.8%
중앙로 2
 
0.8%
795-1 1
 
0.4%
Other values (216) 216
86.4%
2024-03-14T11:08:29.796331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
133
 
10.7%
1 100
 
8.1%
- 62
 
5.0%
2 59
 
4.8%
3 56
 
4.5%
지 41
 
3.3%
0 38
 
3.1%
9 35
 
2.8%
8 33
 
2.7%
4 33
 
2.7%
Other values (169) 648
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 581
46.9%
Decimal Number 438
35.4%
Space Separator 133
 
10.7%
Dash Punctuation 62
 
5.0%
Close Punctuation 8
 
0.6%
Open Punctuation 8
 
0.6%
Lowercase Letter 3
 
0.2%
Uppercase Letter 3
 
0.2%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 41
 
7.1%
로 30
 
5.2%
번 28
 
4.8%
층 21
 
3.6%
길 20
 
3.4%
리 20
 
3.4%
주 17
 
2.9%
동 13
 
2.2%
산 12
 
2.1%
관 11
 
1.9%
Other values (147) 368
63.3%
Decimal Number
ValueCountFrequency (%)
1 100
22.8%
2 59
13.5%
3 56
12.8%
0 38
 
8.7%
9 35
 
8.0%
8 33
 
7.5%
4 33
 
7.5%
5 33
 
7.5%
6 29
 
6.6%
7 22
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
p 1
33.3%
a 1
33.3%
t 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
A 1
33.3%
P 1
33.3%
Other Punctuation
ValueCountFrequency (%)
@ 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
133
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 651
52.6%
Hangul 581
46.9%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 41
 
7.1%
로 30
 
5.2%
번 28
 
4.8%
층 21
 
3.6%
길 20
 
3.4%
리 20
 
3.4%
주 17
 
2.9%
동 13
 
2.2%
산 12
 
2.1%
관 11
 
1.9%
Other values (147) 368
63.3%
Common
ValueCountFrequency (%)
133
20.4%
1 100
15.4%
- 62
9.5%
2 59
9.1%
3 56
8.6%
0 38
 
5.8%
9 35
 
5.4%
8 33
 
5.1%
4 33
 
5.1%
5 33
 
5.1%
Other values (6) 69
10.6%
Latin
ValueCountFrequency (%)
p 1
16.7%
T 1
16.7%
A 1
16.7%
a 1
16.7%
P 1
16.7%
t 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 657
53.1%
Hangul 581
46.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
133
20.2%
1 100
15.2%
- 62
9.4%
2 59
9.0%
3 56
8.5%
0 38
 
5.8%
9 35
 
5.3%
8 33
 
5.0%
4 33
 
5.0%
5 33
 
5.0%
Other values (12) 75
11.4%
Hangul
ValueCountFrequency (%)
지 41
 
7.1%
로 30
 
5.2%
번 28
 
4.8%
층 21
 
3.6%
길 20
 
3.4%
리 20
 
3.4%
주 17
 
2.9%
동 13
 
2.2%
산 12
 
2.1%
관 11
 
1.9%
Other values (147) 368
63.3%

Interactions

2024-03-14T11:08:24.283010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:08:29.935751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구개관년도운영주체건물면적(㎡)열람석(㎡)행정구
연번1.0000.9260.2780.8250.7730.6730.950
시군구0.9261.0000.0000.0000.8130.7581.000
개관년도0.2780.0001.0000.0000.3530.0000.000
운영주체0.8250.0000.0001.0000.6470.8780.395
건물면적(㎡)0.7730.8130.3530.6471.0000.0000.825
열람석(㎡)0.6730.7580.0000.8780.0001.0000.753
행정구0.9501.0000.0000.3950.8250.7531.000
2024-03-14T11:08:30.122247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구열람석(㎡)시군구개관년도
행정구1.0000.2650.9950.000
열람석(㎡)0.2651.0000.2740.000
시군구0.9950.2741.0000.000
개관년도0.0000.0000.0001.000
2024-03-14T11:08:30.205002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구개관년도열람석(㎡)행정구
연번1.0000.7080.1150.2540.723
시군구0.7081.0000.0000.2740.995
개관년도0.1150.0001.0000.0000.000
열람석(㎡)0.2540.2740.0001.0000.265
행정구0.7230.9950.0000.2651.000

Missing values

2024-03-14T11:08:24.741712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:08:24.873360image/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

연번시군구작은도서관 명칭개관년도연락처운영주체건물면적(㎡)열람석(㎡)보유장서행정구행정동.면번지
01전주시간납대작은도서관2013-간납대작은도서관운영위원회49151,225전주시 완산구풍남동3가7-33번지
12전주시건지산숲속작은도서관2013714-2812전주시 직영50301,285전주시 덕진구인후동2가산2-91
23전주시팔복작은도서관2008212-210팔복동주민자치위원회2707410,209전주시 덕진구팔복동1가1가 138-6 팔복주민센터 2층
34전주시호성작은도서관2008245-9030호성동주민자치위원회1372010,495전주시 덕진구호성동1가863-44
45전주시큰나루작은도서관2009271-9337덕진노인복지회관179407,968전주시 덕진구덕진동2가2가172
56전주시무지개작은도서관2007212-3696전북인권교육센터1355010,117전주시 덕진구팔복동2가703-14
67전주시맑은누리작은도서관2009273-5501전주청소년문화의집117705,022전주시 덕진구태진로15-14번지
78전주시청아나루 작은 도서관2010905-7720완산청소년문화의집106257,016전주시 완산구중화산동2가161-7
89전주시노송작은도서관2008231-6070재단법인 천주교전주교구 유지재단9195011,365전주시 완산구남노송동남노송동 156-13
910전주시모롱지 작은도서관2010275-0061전주시 직영6825012,005전주시 완산구효자동3가1485
연번시군구작은도서관 명칭개관년도연락처운영주체건물면적(㎡)열람석(㎡)보유장서행정구행정동.면번지
109110임실군성수골작은도서관2013-성수초등학교403-2,411임실군성수면임진로 189
110111순창군청소년센터 작은도서관2008653-1293지자체 직영132307,256순창군순창읍장류로 192
111112순창군순창군 문화의집 작은도서관2011650-1665지자체 직영167205,721순창군순창읍장류로 407-11
112113고창군고수해마루작은도서관2009561-2726지자체 직영2712717,594고창군고수면황산리 308-13(주민자치센터 1층)
113114고창군아산선운산작은도서관2009561-1521지자체 직영2132136,567고창군아산면하갑리 190-2
114115고창군대산큰별작은도서관2012564-1521지자체 직영79792,501고창군대산면시장길19-2(대산면주민자체센터)
115116고창군무장글샘작은도서관2013561-2780지자체 직영1991991,998고창군무장면성내리 75
116117고창군글마루작은도서관2009564-2655고창행복원182369,668고창군고창읍모양성로 116-13
117118부안군개암작은도서관2013581-3957지자체 직영133392,881부안군상서면상서길 8
118119부안군고인돌작은도서관2009582-0608지자체 직영124276,701부안군하서면변산로 663-7