Overview

Dataset statistics

Number of variables12
Number of observations120
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.4 KiB
Average record size in memory97.1 B

Variable types

Unsupported6
Categorical2
Text4

Alerts

Unnamed: 9 is highly overall correlated with Unnamed: 1High correlation
Unnamed: 1 is highly overall correlated with Unnamed: 9High correlation
전라북도 작은도서관현황(2014) is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:08:31.721259
Analysis finished2024-03-14 02:08:32.331784
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전라북도 작은도서관현황(2014)
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.1 KiB

Unnamed: 1
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
전주시
26 
익산시
17 
정읍시
13 
군산시
12 
남원시
10 
Other values (10)
42 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 26
21.7%
익산시 17
14.2%
정읍시 13
10.8%
군산시 12
10.0%
남원시 10
 
8.3%
김제시 8
 
6.7%
임실군 8
 
6.7%
완주군 6
 
5.0%
고창군 5
 
4.2%
진안군 4
 
3.3%
Other values (5) 11
9.2%

Length

2024-03-14T11:08:32.394967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 26
21.7%
익산시 17
14.2%
정읍시 13
10.8%
군산시 12
10.0%
남원시 10
 
8.3%
김제시 8
 
6.7%
임실군 8
 
6.7%
완주군 6
 
5.0%
고창군 5
 
4.2%
진안군 4
 
3.3%
Other values (5) 11
9.2%

Unnamed: 2
Text

Distinct119
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T11:08:32.631556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length8.5666667
Min length7

Characters and Unicode

Total characters1028
Distinct characters197
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

Unique118 ?
Unique (%)98.3%

Sample

1st row작은도서관 명칭
2nd row간납대작은도서관
3rd row건지산숲속작은도서관
4th row팔복작은도서관
5th row호성작은도서관
ValueCountFrequency (%)
작은도서관 25
 
16.2%
도서관 3
 
1.9%
작은 3
 
1.9%
글마루작은도서관 2
 
1.3%
구이모악작은도서관 1
 
0.6%
청하작은도서관 1
 
0.6%
교동골 1
 
0.6%
검산 1
 
0.6%
황죽작은도서관 1
 
0.6%
이서배꽃뜰작은도서관 1
 
0.6%
Other values (115) 115
74.7%
2024-03-14T11:08:33.038623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 123
 
12.0%
은 122
 
11.9%
서 122
 
11.9%
작 120
 
11.7%
도 120
 
11.7%
34
 
3.3%
산 14
 
1.4%
지 9
 
0.9%
나 9
 
0.9%
동 7
 
0.7%
Other values (187) 348
33.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 991
96.4%
Space Separator 34
 
3.3%
Uppercase Letter 2
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 123
 
12.4%
은 122
 
12.3%
서 122
 
12.3%
작 120
 
12.1%
도 120
 
12.1%
산 14
 
1.4%
지 9
 
0.9%
나 9
 
0.9%
동 7
 
0.7%
마 7
 
0.7%
Other values (183) 338
34.1%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
J 1
50.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 991
96.4%
Common 35
 
3.4%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 123
 
12.4%
은 122
 
12.3%
서 122
 
12.3%
작 120
 
12.1%
도 120
 
12.1%
산 14
 
1.4%
지 9
 
0.9%
나 9
 
0.9%
동 7
 
0.7%
마 7
 
0.7%
Other values (183) 338
34.1%
Common
ValueCountFrequency (%)
34
97.1%
3 1
 
2.9%
Latin
ValueCountFrequency (%)
G 1
50.0%
J 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 991
96.4%
ASCII 37
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 123
 
12.4%
은 122
 
12.3%
서 122
 
12.3%
작 120
 
12.1%
도 120
 
12.1%
산 14
 
1.4%
지 9
 
0.9%
나 9
 
0.9%
동 7
 
0.7%
마 7
 
0.7%
Other values (183) 338
34.1%
ASCII
ValueCountFrequency (%)
34
91.9%
G 1
 
2.7%
J 1
 
2.7%
3 1
 
2.7%

Unnamed: 3
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.1 KiB

Unnamed: 4
Text

Distinct109
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T11:08:33.371161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length8
Mean length7.9
Min length1

Characters and Unicode

Total characters948
Distinct characters15
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

Unique105 ?
Unique (%)87.5%

Sample

1st row연락처
2nd row010-7536-7575
3rd row714-2812
4th row212-210
5th row245-9030
ValueCountFrequency (%)
9
 
7.5%
352-3302 2
 
1.7%
533-0522 2
 
1.7%
535-0365 2
 
1.7%
231-3200 1
 
0.8%
625-3312 1
 
0.8%
223-4167 1
 
0.8%
547-0431 1
 
0.8%
543-5007~8 1
 
0.8%
546-2079 1
 
0.8%
Other values (99) 99
82.5%
2024-03-14T11:08:33.755658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 131
13.8%
2 119
12.6%
5 112
11.8%
0 102
10.8%
3 97
10.2%
6 76
8.0%
4 73
7.7%
1 71
7.5%
8 65
6.9%
7 58
6.1%
Other values (5) 44
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 812
85.7%
Dash Punctuation 131
 
13.8%
Other Letter 3
 
0.3%
Math Symbol 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 119
14.7%
5 112
13.8%
0 102
12.6%
3 97
11.9%
6 76
9.4%
4 73
9.0%
1 71
8.7%
8 65
8.0%
7 58
7.1%
9 39
 
4.8%
Other Letter
ValueCountFrequency (%)
연 1
33.3%
락 1
33.3%
처 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 131
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 945
99.7%
Hangul 3
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 131
13.9%
2 119
12.6%
5 112
11.9%
0 102
10.8%
3 97
10.3%
6 76
8.0%
4 73
7.7%
1 71
7.5%
8 65
6.9%
7 58
6.1%
Other values (2) 41
 
4.3%
Hangul
ValueCountFrequency (%)
연 1
33.3%
락 1
33.3%
처 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 945
99.7%
Hangul 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 131
13.9%
2 119
12.6%
5 112
11.9%
0 102
10.8%
3 97
10.3%
6 76
8.0%
4 73
7.7%
1 71
7.5%
8 65
6.9%
7 58
6.1%
Other values (2) 41
 
4.3%
Hangul
ValueCountFrequency (%)
연 1
33.3%
락 1
33.3%
처 1
33.3%

Unnamed: 5
Text

Distinct72
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T11:08:33.930272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length116
Median length18
Mean length8.9
Min length4

Characters and Unicode

Total characters1068
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

Unique67 ?
Unique (%)55.8%

Sample

1st row운영주체
2nd row간납대작은도서관운영위원회
3rd row전주시 직영
4th row팔복동주민자치위원회
5th row호성동주민자치위원회
ValueCountFrequency (%)
직영 36
22.2%
지자체 34
21.0%
주민자치위원회 11
 
6.8%
장수문화원 3
 
1.9%
민간 3
 
1.9%
위탁 3
 
1.9%
전주시 2
 
1.2%
함열초등학교 1
 
0.6%
2(삼성동주민자치위원회 1
 
0.6%
동산여울휴먼시아2차@입주자대표회의 1
 
0.6%
Other values (67) 67
41.4%
2024-03-14T11:08:34.210876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
154
 
14.4%
자 59
 
5.5%
회 55
 
5.1%
지 51
 
4.8%
영 48
 
4.5%
원 39
 
3.7%
체 36
 
3.4%
직 36
 
3.4%
주 33
 
3.1%
위 33
 
3.1%
Other values (141) 524
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 900
84.3%
Space Separator 154
 
14.4%
Decimal Number 12
 
1.1%
Other Punctuation 1
 
0.1%
Open 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 48
 
5.3%
원 39
 
4.3%
체 36
 
4.0%
직 36
 
4.0%
주 33
 
3.7%
위 33
 
3.7%
관 26
 
2.9%
Other values (131) 484
53.8%
Decimal Number
ValueCountFrequency (%)
2 3
25.0%
5 2
16.7%
3 2
16.7%
1 2
16.7%
9 1
 
8.3%
4 1
 
8.3%
6 1
 
8.3%
Space Separator
ValueCountFrequency (%)
154
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 900
84.3%
Common 168
 
15.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 59
 
6.6%
회 55
 
6.1%
지 51
 
5.7%
영 48
 
5.3%
원 39
 
4.3%
체 36
 
4.0%
직 36
 
4.0%
주 33
 
3.7%
위 33
 
3.7%
관 26
 
2.9%
Other values (131) 484
53.8%
Common
ValueCountFrequency (%)
154
91.7%
2 3
 
1.8%
5 2
 
1.2%
3 2
 
1.2%
1 2
 
1.2%
9 1
 
0.6%
@ 1
 
0.6%
( 1
 
0.6%
4 1
 
0.6%
6 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 900
84.3%
ASCII 168
 
15.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
154
91.7%
2 3
 
1.8%
5 2
 
1.2%
3 2
 
1.2%
1 2
 
1.2%
9 1
 
0.6%
@ 1
 
0.6%
( 1
 
0.6%
4 1
 
0.6%
6 1
 
0.6%
Hangul
ValueCountFrequency (%)
자 59
 
6.6%
회 55
 
6.1%
지 51
 
5.7%
영 48
 
5.3%
원 39
 
4.3%
체 36
 
4.0%
직 36
 
4.0%
주 33
 
3.7%
위 33
 
3.7%
관 26
 
2.9%
Other values (131) 484
53.8%

Unnamed: 6
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.1 KiB

Unnamed: 7
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.1 KiB

Unnamed: 8
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.1 KiB

Unnamed: 9
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
익산시
17 
전주시 완산구
14 
정읍시
13 
전주시 덕진구
12 
군산시
12 
Other values (11)
52 

Length

Max length7
Median length3
Mean length3.8666667
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
익산시 17
14.2%
전주시 완산구 14
11.7%
정읍시 13
10.8%
전주시 덕진구 12
10.0%
군산시 12
10.0%
남원시 10
8.3%
김제시 8
6.7%
임실군 8
6.7%
완주군 6
 
5.0%
고창군 5
 
4.2%
Other values (6) 15
12.5%

Length

2024-03-14T11:08:34.365660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 26
17.8%
익산시 17
11.6%
완산구 14
9.6%
정읍시 13
8.9%
덕진구 12
8.2%
군산시 12
8.2%
남원시 10
 
6.8%
임실군 8
 
5.5%
김제시 8
 
5.5%
완주군 6
 
4.1%
Other values (7) 20
13.7%

Unnamed: 10
Text

Distinct104
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T11:08:34.756101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.625
Min length2

Characters and Unicode

Total characters435
Distinct characters120
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

Unique93 ?
Unique (%)77.5%

Sample

1st row행정동.면
2nd row풍남동3가
3rd row인후동2가
4th row팔복동1가
5th row호성동1가
ValueCountFrequency (%)
상동 4
 
3.3%
임실읍 4
 
3.3%
부송동 3
 
2.5%
금동 2
 
1.6%
중화산동2가 2
 
1.6%
안성면 2
 
1.6%
진안읍 2
 
1.6%
평화동1가 2
 
1.6%
효자1가 2
 
1.6%
검산동 2
 
1.6%
Other values (95) 97
79.5%
2024-03-14T11:08:35.135022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 61
 
14.0%
면 39
 
9.0%
산 18
 
4.1%
가 17
 
3.9%
로 15
 
3.4%
읍 11
 
2.5%
서 10
 
2.3%
2 9
 
2.1%
9
 
2.1%
1 8
 
1.8%
Other values (110) 238
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 395
90.8%
Decimal Number 22
 
5.1%
Space Separator 9
 
2.1%
Open Punctuation 4
 
0.9%
Close Punctuation 4
 
0.9%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 61
 
15.4%
면 39
 
9.9%
산 18
 
4.6%
가 17
 
4.3%
로 15
 
3.8%
읍 11
 
2.8%
서 10
 
2.5%
송 8
 
2.0%
화 8
 
2.0%
성 8
 
2.0%
Other values (101) 200
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%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 395
90.8%
Common 40
 
9.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 61
 
15.4%
면 39
 
9.9%
산 18
 
4.6%
가 17
 
4.3%
로 15
 
3.8%
읍 11
 
2.8%
서 10
 
2.5%
송 8
 
2.0%
화 8
 
2.0%
성 8
 
2.0%
Other values (101) 200
50.6%
Common
ValueCountFrequency (%)
2 9
22.5%
9
22.5%
1 8
20.0%
( 4
10.0%
) 4
10.0%
5 2
 
5.0%
3 2
 
5.0%
. 1
 
2.5%
9 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 395
90.8%
ASCII 40
 
9.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 61
 
15.4%
면 39
 
9.9%
산 18
 
4.6%
가 17
 
4.3%
로 15
 
3.8%
읍 11
 
2.8%
서 10
 
2.5%
송 8
 
2.0%
화 8
 
2.0%
성 8
 
2.0%
Other values (101) 200
50.6%
ASCII
ValueCountFrequency (%)
2 9
22.5%
9
22.5%
1 8
20.0%
( 4
10.0%
) 4
10.0%
5 2
 
5.0%
3 2
 
5.0%
. 1
 
2.5%
9 1
 
2.5%

Unnamed: 11
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.1 KiB

Correlations

2024-03-14T11:08:35.215503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 5Unnamed: 9
Unnamed: 11.0000.4511.000
Unnamed: 50.4511.0000.720
Unnamed: 91.0000.7201.000
2024-03-14T11:08:35.296604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 9Unnamed: 1
Unnamed: 91.0000.995
Unnamed: 10.9951.000
2024-03-14T11:08:35.377337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 9
Unnamed: 11.0000.995
Unnamed: 90.9951.000

Missing values

2024-03-14T11:08:32.024720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:08:32.241424image/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

전라북도 작은도서관현황(2014)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
0연번시군구작은도서관 명칭개관년도연락처운영주체건물면적(㎡)열람석(㎡)보유장서행정구행정동.면번지
11전주시간납대작은도서관2013010-7536-7575간납대작은도서관운영위원회49.21151225전주시 완산구풍남동3가7-33번지
22전주시건지산숲속작은도서관2013714-2812전주시 직영50301285전주시 덕진구인후동2가산2-91
33전주시팔복작은도서관2008212-210팔복동주민자치위원회2707410209전주시 덕진구팔복동1가1가 138-6 팔복주민센터 2층
44전주시호성작은도서관2008245-9030호성동주민자치위원회1372010495전주시 덕진구호성동1가863-44
55전주시큰나루작은도서관2009271-9337덕진노인복지회관179407968전주시 덕진구덕진동2가2가172
66전주시무지개작은도서관2007212-3696전북인권교육센터1355010117전주시 덕진구팔복동2가703-14
77전주시맑은누리작은도서관2009273-5501전주청소년문화의집117705022전주시 덕진구태진로15-14번지
88전주시청아나루 작은 도서관2010905-7720완산청소년문화의집106257016전주시 완산구중화산동2가161-7
99전주시노송작은도서관2008231-6070재단법인 천주교전주교구 유지재단9195011365전주시 완산구남노송동남노송동 156-13
전라북도 작은도서관현황(2014)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
110110임실군성수골작은도서관2013-성수초등학교403-2411임실군성수면임진로 189
111111순창군청소년센터 작은도서관2008653-1293지자체 직영132307256순창군순창읍장류로 192
112112순창군순창군 문화의집 작은도서관2011650-1665지자체 직영167205721순창군순창읍장류로 407-11
113113고창군고수해마루작은도서관2009561-2726지자체 직영2712717594고창군고수면황산리 308-13(주민자치센터 1층)
114114고창군아산선운산작은도서관2009561-1521지자체 직영2132136567고창군아산면하갑리 190-2
115115고창군대산큰별작은도서관2012564-1521지자체 직영79.379.32501고창군대산면시장길19-2(대산면주민자체센터)
116116고창군무장글샘작은도서관2013561-2780지자체 직영1991991998고창군무장면성내리 75
117117고창군글마루작은도서관2009564-2655고창행복원181.6369668고창군고창읍모양성로 116-13
118118부안군개암작은도서관2013581-3957지자체 직영133392881부안군상서면상서길 8
119119부안군고인돌작은도서관2009582-0608지자체 직영124276701부안군하서면변산로 663-7