Overview

Dataset statistics

Number of variables7
Number of observations142
Missing cells16
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory60.9 B

Variable types

Text3
Numeric3
Categorical1

Dataset

Description- 제주도 내 위치한 새마을문고의 이름, 주소, 열람석 수, 도서 자료 수 등의 정보를 제공합니다. - 데이터 기준일: 2021.11.23 - 데이터 제공처: 제주특별자치도
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/889

Alerts

데이터 기준일 has constant value ""Constant
열람석(개) has 2 (1.4%) missing valuesMissing
전화 번호 has 14 (9.9%) missing valuesMissing
문고명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-11 19:53:38.162302
Analysis finished2023-12-11 19:53:40.074123
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

문고명
Text

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T04:53:40.257767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.2605634
Min length5

Characters and Unicode

Total characters1173
Distinct characters146
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)100.0%

Sample

1st row119새마을문고
2nd row가파리새마을문고
3rd row감산리새마을문고
4th row강구리새마을문고
5th row광령1리새마을문고
ValueCountFrequency (%)
119새마을문고 1
 
0.7%
일도대림새마을문고 1
 
0.7%
일도성환새마을문고 1
 
0.7%
유수암리새마을문고 1
 
0.7%
으뜸새마을문고 1
 
0.7%
의귀리새마을문고 1
 
0.7%
이도1동새마을문고 1
 
0.7%
일도2동새마을문고 1
 
0.7%
위미2리새마을문고 1
 
0.7%
위미1리새마을문고 1
 
0.7%
Other values (132) 132
93.0%
2023-12-12T04:53:40.697429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
문 141
12.0%
고 140
11.9%
새 136
11.6%
마 136
11.6%
을 136
11.6%
리 73
 
6.2%
1 26
 
2.2%
동 21
 
1.8%
도 15
 
1.3%
하 12
 
1.0%
Other values (136) 337
28.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1124
95.8%
Decimal Number 45
 
3.8%
Uppercase Letter 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
문 141
12.5%
고 140
12.5%
새 136
12.1%
마 136
12.1%
을 136
12.1%
리 73
 
6.5%
동 21
 
1.9%
도 15
 
1.3%
하 12
 
1.1%
서 11
 
1.0%
Other values (130) 303
27.0%
Decimal Number
ValueCountFrequency (%)
1 26
57.8%
2 12
26.7%
3 5
 
11.1%
9 2
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
J 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1124
95.8%
Common 45
 
3.8%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
문 141
12.5%
고 140
12.5%
새 136
12.1%
마 136
12.1%
을 136
12.1%
리 73
 
6.5%
동 21
 
1.9%
도 15
 
1.3%
하 12
 
1.1%
서 11
 
1.0%
Other values (130) 303
27.0%
Common
ValueCountFrequency (%)
1 26
57.8%
2 12
26.7%
3 5
 
11.1%
9 2
 
4.4%
Latin
ValueCountFrequency (%)
C 2
50.0%
J 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1124
95.8%
ASCII 49
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
문 141
12.5%
고 140
12.5%
새 136
12.1%
마 136
12.1%
을 136
12.1%
리 73
 
6.5%
동 21
 
1.9%
도 15
 
1.3%
하 12
 
1.1%
서 11
 
1.0%
Other values (130) 303
27.0%
ASCII
ValueCountFrequency (%)
1 26
53.1%
2 12
24.5%
3 5
 
10.2%
9 2
 
4.1%
C 2
 
4.1%
J 2
 
4.1%

주소
Text

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T04:53:41.073821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length15.140845
Min length9

Characters and Unicode

Total characters2150
Distinct characters159
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)100.0%

Sample

1st row서귀포시 서귀포시 천제연로 164
2nd row서귀포시 대정읍 가파로67번길 12-1
3rd row서귀포시 안덕면 감산중로 32
4th row제주시 한림읍 강구로 92
5th row제주시 애월읍 광성로 298-1
ValueCountFrequency (%)
제주시 80
 
14.9%
서귀포시 63
 
11.8%
한림읍 12
 
2.2%
남원읍 12
 
2.2%
대정읍 11
 
2.1%
애월읍 8
 
1.5%
안덕면 7
 
1.3%
한경면 6
 
1.1%
표선면 6
 
1.1%
2 6
 
1.1%
Other values (253) 325
60.6%
2023-12-12T04:53:41.756743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
394
18.3%
시 144
 
6.7%
로 111
 
5.2%
1 98
 
4.6%
주 87
 
4.0%
제 82
 
3.8%
서 75
 
3.5%
포 64
 
3.0%
귀 64
 
3.0%
읍 59
 
2.7%
Other values (149) 972
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1311
61.0%
Decimal Number 421
 
19.6%
Space Separator 394
 
18.3%
Dash Punctuation 21
 
1.0%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 144
 
11.0%
로 111
 
8.5%
주 87
 
6.6%
제 82
 
6.3%
서 75
 
5.7%
포 64
 
4.9%
귀 64
 
4.9%
읍 59
 
4.5%
길 55
 
4.2%
한 24
 
1.8%
Other values (134) 546
41.6%
Decimal Number
ValueCountFrequency (%)
1 98
23.3%
5 51
12.1%
3 51
12.1%
2 47
11.2%
4 40
9.5%
8 36
 
8.6%
6 29
 
6.9%
7 23
 
5.5%
0 23
 
5.5%
9 23
 
5.5%
Space Separator
ValueCountFrequency (%)
394
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1311
61.0%
Common 839
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 144
 
11.0%
로 111
 
8.5%
주 87
 
6.6%
제 82
 
6.3%
서 75
 
5.7%
포 64
 
4.9%
귀 64
 
4.9%
읍 59
 
4.5%
길 55
 
4.2%
한 24
 
1.8%
Other values (134) 546
41.6%
Common
ValueCountFrequency (%)
394
47.0%
1 98
 
11.7%
5 51
 
6.1%
3 51
 
6.1%
2 47
 
5.6%
4 40
 
4.8%
8 36
 
4.3%
6 29
 
3.5%
7 23
 
2.7%
0 23
 
2.7%
Other values (5) 47
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1311
61.0%
ASCII 839
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
394
47.0%
1 98
 
11.7%
5 51
 
6.1%
3 51
 
6.1%
2 47
 
5.6%
4 40
 
4.8%
8 36
 
4.3%
6 29
 
3.5%
7 23
 
2.7%
0 23
 
2.7%
Other values (5) 47
 
5.6%
Hangul
ValueCountFrequency (%)
시 144
 
11.0%
로 111
 
8.5%
주 87
 
6.6%
제 82
 
6.3%
서 75
 
5.7%
포 64
 
4.9%
귀 64
 
4.9%
읍 59
 
4.5%
길 55
 
4.2%
한 24
 
1.8%
Other values (134) 546
41.6%

건물면적(m²)
Real number (ℝ)

Distinct47
Distinct (%)33.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.32394
Minimum30
Maximum346.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T04:53:41.977989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile49.5
Q166
median83
Q3117.975
95-th percentile197.34
Maximum346.5
Range316.5
Interquartile range (IQR)51.975

Descriptive statistics

Standard deviation54.296917
Coefficient of variation (CV)0.53587449
Kurtosis7.0729879
Mean101.32394
Median Absolute Deviation (MAD)17
Skewness2.3473517
Sum14388
Variance2948.1552
MonotonicityNot monotonic
2023-12-12T04:53:42.206910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
66.0 27
19.0%
99.0 20
14.1%
132.0 16
 
11.3%
82.5 10
 
7.0%
83.0 7
 
4.9%
82.0 7
 
4.9%
115.5 4
 
2.8%
60.0 3
 
2.1%
49.5 3
 
2.1%
198.0 2
 
1.4%
Other values (37) 43
30.3%
ValueCountFrequency (%)
30.0 1
 
0.7%
33.0 2
1.4%
38.0 1
 
0.7%
40.0 1
 
0.7%
42.9 1
 
0.7%
49.0 1
 
0.7%
49.5 3
2.1%
50.0 2
1.4%
56.0 1
 
0.7%
60.0 3
2.1%
ValueCountFrequency (%)
346.5 1
0.7%
330.0 1
0.7%
328.0 1
0.7%
283.8 2
1.4%
204.6 1
0.7%
198.0 2
1.4%
184.8 1
0.7%
178.2 1
0.7%
165.0 2
1.4%
162.0 1
0.7%

열람석(개)
Real number (ℝ)

MISSING 

Distinct37
Distinct (%)26.4%
Missing2
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean29.514286
Minimum10
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T04:53:42.470313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile12
Q120
median25
Q340
95-th percentile56.1
Maximum88
Range78
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.827296
Coefficient of variation (CV)0.50237693
Kurtosis2.2785587
Mean29.514286
Median Absolute Deviation (MAD)9.5
Skewness1.2792597
Sum4132
Variance219.84872
MonotonicityNot monotonic
2023-12-12T04:53:42.737719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
20 21
14.8%
40 18
 
12.7%
24 9
 
6.3%
16 8
 
5.6%
25 8
 
5.6%
26 6
 
4.2%
12 6
 
4.2%
10 6
 
4.2%
36 6
 
4.2%
42 5
 
3.5%
Other values (27) 47
33.1%
ValueCountFrequency (%)
10 6
 
4.2%
12 6
 
4.2%
13 1
 
0.7%
14 4
 
2.8%
15 3
 
2.1%
16 8
 
5.6%
17 1
 
0.7%
20 21
14.8%
21 1
 
0.7%
22 2
 
1.4%
ValueCountFrequency (%)
88 1
 
0.7%
84 1
 
0.7%
78 1
 
0.7%
60 3
2.1%
58 1
 
0.7%
56 1
 
0.7%
54 3
2.1%
51 1
 
0.7%
50 1
 
0.7%
49 1
 
0.7%

도서자료(개)
Real number (ℝ)

Distinct124
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3157.493
Minimum319
Maximum34500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T04:53:43.027948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum319
5-th percentile1193.35
Q11871.25
median2357
Q33645
95-th percentile6072.5
Maximum34500
Range34181
Interquartile range (IQR)1773.75

Descriptive statistics

Standard deviation3222.9261
Coefficient of variation (CV)1.0207231
Kurtosis64.194297
Mean3157.493
Median Absolute Deviation (MAD)707
Skewness6.9828612
Sum448364
Variance10387253
MonotonicityNot monotonic
2023-12-12T04:53:43.279930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2650 3
 
2.1%
1650 3
 
2.1%
1190 2
 
1.4%
2320 2
 
1.4%
2100 2
 
1.4%
2950 2
 
1.4%
2150 2
 
1.4%
1880 2
 
1.4%
2600 2
 
1.4%
1320 2
 
1.4%
Other values (114) 120
84.5%
ValueCountFrequency (%)
319 1
0.7%
940 1
0.7%
974 1
0.7%
1120 1
0.7%
1155 1
0.7%
1190 2
1.4%
1193 1
0.7%
1200 1
0.7%
1260 2
1.4%
1280 1
0.7%
ValueCountFrequency (%)
34500 1
0.7%
12302 1
0.7%
12110 1
0.7%
8065 1
0.7%
7750 1
0.7%
6320 1
0.7%
6120 1
0.7%
6075 1
0.7%
6025 1
0.7%
5940 1
0.7%

전화 번호
Text

MISSING 

Distinct128
Distinct (%)100.0%
Missing14
Missing (%)9.9%
Memory size1.2 KiB
2023-12-12T04:53:43.847085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters1024
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

Unique128 ?
Unique (%)100.0%

Sample

1st row738-2087
2nd row794-7130
3rd row794-1346
4th row796-2347
5th row748-4485
ValueCountFrequency (%)
743-3701 1
 
0.8%
794-1346 1
 
0.8%
764-2720 1
 
0.8%
762-3838 1
 
0.8%
783-3216 1
 
0.8%
773-1945 1
 
0.8%
750-7572 1
 
0.8%
757-4661 1
 
0.8%
799-5044 1
 
0.8%
759-3115 1
 
0.8%
Other values (118) 118
92.2%
2023-12-12T04:53:44.617489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 189
18.5%
- 128
12.5%
4 98
9.6%
3 92
9.0%
8 81
7.9%
6 79
7.7%
9 78
7.6%
2 76
7.4%
1 69
 
6.7%
5 68
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 896
87.5%
Dash Punctuation 128
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 189
21.1%
4 98
10.9%
3 92
10.3%
8 81
9.0%
6 79
8.8%
9 78
8.7%
2 76
8.5%
1 69
 
7.7%
5 68
 
7.6%
0 66
 
7.4%
Dash Punctuation
ValueCountFrequency (%)
- 128
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1024
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 189
18.5%
- 128
12.5%
4 98
9.6%
3 92
9.0%
8 81
7.9%
6 79
7.7%
9 78
7.6%
2 76
7.4%
1 69
 
6.7%
5 68
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1024
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 189
18.5%
- 128
12.5%
4 98
9.6%
3 92
9.0%
8 81
7.9%
6 79
7.7%
9 78
7.6%
2 76
7.4%
1 69
 
6.7%
5 68
 
6.6%

데이터 기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
20211123
142 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20211123
2nd row20211123
3rd row20211123
4th row20211123
5th row20211123

Common Values

ValueCountFrequency (%)
20211123 142
100.0%

Length

2023-12-12T04:53:44.847123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:53:45.035544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20211123 142
100.0%

Interactions

2023-12-12T04:53:39.303187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:38.459844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:38.837262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:39.429826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:38.576812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:38.945187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:39.577173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:38.702922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:53:39.190223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:53:45.562846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물면적(m²)열람석(개)도서자료(개)
건물면적(m²)1.0000.6910.282
열람석(개)0.6911.0000.373
도서자료(개)0.2820.3731.000
2023-12-12T04:53:45.714534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물면적(m²)열람석(개)도서자료(개)
건물면적(m²)1.0000.4770.425
열람석(개)0.4771.0000.309
도서자료(개)0.4250.3091.000

Missing values

2023-12-12T04:53:39.757380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:53:39.899763image/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.
2023-12-12T04:53:40.013559image/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

문고명주소건물면적(m²)열람석(개)도서자료(개)전화 번호데이터 기준일
0119새마을문고서귀포시 서귀포시 천제연로 164132.0503400738-208720211123
1가파리새마을문고서귀포시 대정읍 가파로67번길 12-182.5101260794-713020211123
2감산리새마을문고서귀포시 안덕면 감산중로 32165.06012110794-134620211123
3강구리새마을문고제주시 한림읍 강구로 9266.0232331796-234720211123
4광령1리새마을문고제주시 애월읍 광성로 298-166.0201560748-448520211123
5귀덕1리새마을문고제주시 한림읍 일주서로 5882-483.0231875796-416620211123
6귀덕3리새마을문고제주시 한림읍 한수풀로 337 2층83.0161280796-360620211123
7금능리새마을문고제주시 한림읍 금능길 39132.0261800796-201120211123
8금악리새마을문고제주시 한림읍 금악로 266.0161942796-636820211123
9꽃동산문고서귀포시 표선면 중산간동로 5236-7165.0252000787-132720211123
문고명주소건물면적(m²)열람석(개)도서자료(개)전화 번호데이터 기준일
132한수리새마을문고제주시 한림읍 한림로 73966.0161466796-258420211123
133한우리서귀포독서문화원서귀포시 중정로 91번길 5666.0104000762-501920211123
134한원리새마을문고제주시 한경면 용금로 14773.0241320773-194020211123
135항운노조새마을문고제주시 임항로 19176.017319<NA>20211123
136해안새마을문고제주시 해안마을7길 1-589.0252149<NA>20211123
137해오름새마을문고제주시 연화로 16 해오름아파트 104동118.8202090744-867420211123
138혜성무지개새마을문고제주시 남광로 65132.0202510755-960520211123
139호근새마을문고서귀포시 호근남로 680.0302100739-594620211123
140화북주공열린새마을문고제주시 동화로1길 10346.5785699702-125420211123
141회수새마을문고서귀포시 중산간서로 65482.5422587738-422020211123