Overview

Dataset statistics

Number of variables6
Number of observations26
Missing cells2
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory55.1 B

Variable types

Text3
Categorical1
Numeric2

Dataset

Description김해시 동네책방현황에 대한 데이터로 서점명, 주소, 연락처, 위도, 경도 항목으로 구성되어 있습니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15033331

Alerts

연락처 has 2 (7.7%) missing valuesMissing
서점명 has unique valuesUnique
도로명주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:05:06.177393
Analysis finished2023-12-10 23:05:07.222506
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

서점명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-11T08:05:07.342200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length4
Mean length5.0769231
Min length3

Characters and Unicode

Total characters132
Distinct characters63
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

Unique26 ?
Unique (%)100.0%

Sample

1st row21세기 서점
2nd row가야서점(삼계점)
3rd row가야서점(인제대점)
4th row경운서점
5th row근비도서
ValueCountFrequency (%)
서점 2
 
6.2%
21세기 1
 
3.1%
영운서점 1
 
3.1%
해영서점 1
 
3.1%
학예서림 1
 
3.1%
청운서점 1
 
3.1%
주문도서 1
 
3.1%
제일도서 1
 
3.1%
정문서점 1
 
3.1%
장유서점 1
 
3.1%
Other values (21) 21
65.6%
2023-12-11T08:05:07.697329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 23
 
17.4%
점 19
 
14.4%
6
 
4.5%
도 5
 
3.8%
삼 4
 
3.0%
운 4
 
3.0%
문 3
 
2.3%
가 3
 
2.3%
정 2
 
1.5%
인 2
 
1.5%
Other values (53) 61
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120
90.9%
Space Separator 6
 
4.5%
Close Punctuation 2
 
1.5%
Open Punctuation 2
 
1.5%
Decimal Number 2
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 23
19.2%
점 19
 
15.8%
도 5
 
4.2%
삼 4
 
3.3%
운 4
 
3.3%
문 3
 
2.5%
가 3
 
2.5%
정 2
 
1.7%
인 2
 
1.7%
방 2
 
1.7%
Other values (48) 53
44.2%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120
90.9%
Common 12
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 23
19.2%
점 19
 
15.8%
도 5
 
4.2%
삼 4
 
3.3%
운 4
 
3.3%
문 3
 
2.5%
가 3
 
2.5%
정 2
 
1.7%
인 2
 
1.7%
방 2
 
1.7%
Other values (48) 53
44.2%
Common
ValueCountFrequency (%)
6
50.0%
) 2
 
16.7%
( 2
 
16.7%
2 1
 
8.3%
1 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120
90.9%
ASCII 12
 
9.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 23
19.2%
점 19
 
15.8%
도 5
 
4.2%
삼 4
 
3.3%
운 4
 
3.3%
문 3
 
2.5%
가 3
 
2.5%
정 2
 
1.7%
인 2
 
1.7%
방 2
 
1.7%
Other values (48) 53
44.2%
ASCII
ValueCountFrequency (%)
6
50.0%
) 2
 
16.7%
( 2
 
16.7%
2 1
 
8.3%
1 1
 
8.3%

도로명주소
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-11T08:05:07.932701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27.5
Mean length23.384615
Min length16

Characters and Unicode

Total characters608
Distinct characters75
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

Unique26 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 가락로 301(구산동)
2nd row경상남도 김해시 가야로 157번길 31-19(삼계동)
3rd row경상남도 김해시 인제로 174-1(어방동)
4th row경상남도 김해시 분성로 3번길 96(외동)
5th row경상남도 김해시 한림면 김해대로 1434번길 45
ValueCountFrequency (%)
경상남도 26
22.0%
김해시 26
22.0%
인제로 2
 
1.7%
김해대로 2
 
1.7%
분성로 2
 
1.7%
74(부곡동 1
 
0.8%
율하1로 1
 
0.8%
월산로 1
 
0.8%
8(율하동 1
 
0.8%
진영로 1
 
0.8%
Other values (55) 55
46.6%
2023-12-11T08:05:08.357054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
 
15.1%
김 28
 
4.6%
해 28
 
4.6%
경 27
 
4.4%
남 26
 
4.3%
도 26
 
4.3%
시 26
 
4.3%
상 26
 
4.3%
로 26
 
4.3%
동 24
 
3.9%
Other values (65) 279
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 363
59.7%
Decimal Number 102
 
16.8%
Space Separator 92
 
15.1%
Close Punctuation 21
 
3.5%
Open Punctuation 21
 
3.5%
Dash Punctuation 6
 
1.0%
Other Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 28
 
7.7%
해 28
 
7.7%
경 27
 
7.4%
남 26
 
7.2%
도 26
 
7.2%
시 26
 
7.2%
상 26
 
7.2%
로 26
 
7.2%
동 24
 
6.6%
번 12
 
3.3%
Other values (50) 114
31.4%
Decimal Number
ValueCountFrequency (%)
1 23
22.5%
4 16
15.7%
2 14
13.7%
3 11
10.8%
0 8
 
7.8%
5 6
 
5.9%
7 6
 
5.9%
9 6
 
5.9%
6 6
 
5.9%
8 6
 
5.9%
Space Separator
ValueCountFrequency (%)
92
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 363
59.7%
Common 245
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 28
 
7.7%
해 28
 
7.7%
경 27
 
7.4%
남 26
 
7.2%
도 26
 
7.2%
시 26
 
7.2%
상 26
 
7.2%
로 26
 
7.2%
동 24
 
6.6%
번 12
 
3.3%
Other values (50) 114
31.4%
Common
ValueCountFrequency (%)
92
37.6%
1 23
 
9.4%
) 21
 
8.6%
( 21
 
8.6%
4 16
 
6.5%
2 14
 
5.7%
3 11
 
4.5%
0 8
 
3.3%
5 6
 
2.4%
7 6
 
2.4%
Other values (5) 27
 
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 363
59.7%
ASCII 245
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
37.6%
1 23
 
9.4%
) 21
 
8.6%
( 21
 
8.6%
4 16
 
6.5%
2 14
 
5.7%
3 11
 
4.5%
0 8
 
3.3%
5 6
 
2.4%
7 6
 
2.4%
Other values (5) 27
 
11.0%
Hangul
ValueCountFrequency (%)
김 28
 
7.7%
해 28
 
7.7%
경 27
 
7.4%
남 26
 
7.2%
도 26
 
7.2%
시 26
 
7.2%
상 26
 
7.2%
로 26
 
7.2%
동 24
 
6.6%
번 12
 
3.3%
Other values (50) 114
31.4%

연락처
Text

MISSING 

Distinct24
Distinct (%)100.0%
Missing2
Missing (%)7.7%
Memory size340.0 B
2023-12-11T08:05:08.552588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters288
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

Unique24 ?
Unique (%)100.0%

Sample

1st row055-339-8962
2nd row055-331-4777
3rd row055-322-5463
4th row055-326-7479
5th row055-343-7896
ValueCountFrequency (%)
055-331-4777 1
 
4.2%
055-322-5463 1
 
4.2%
055-313-3132 1
 
4.2%
055-322-6710 1
 
4.2%
055-335-0639 1
 
4.2%
055-313-4051 1
 
4.2%
055-326-3731 1
 
4.2%
055-343-2150 1
 
4.2%
055-312-7474 1
 
4.2%
055-321-3296 1
 
4.2%
Other values (14) 14
58.3%
2023-12-11T08:05:08.864276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 57
19.8%
3 49
17.0%
- 48
16.7%
0 34
11.8%
2 22
 
7.6%
4 18
 
6.2%
1 16
 
5.6%
7 14
 
4.9%
6 14
 
4.9%
9 12
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
83.3%
Dash Punctuation 48
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 57
23.8%
3 49
20.4%
0 34
14.2%
2 22
 
9.2%
4 18
 
7.5%
1 16
 
6.7%
7 14
 
5.8%
6 14
 
5.8%
9 12
 
5.0%
8 4
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 57
19.8%
3 49
17.0%
- 48
16.7%
0 34
11.8%
2 22
 
7.6%
4 18
 
6.2%
1 16
 
5.6%
7 14
 
4.9%
6 14
 
4.9%
9 12
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 57
19.8%
3 49
17.0%
- 48
16.7%
0 34
11.8%
2 22
 
7.6%
4 18
 
6.2%
1 16
 
5.6%
7 14
 
4.9%
6 14
 
4.9%
9 12
 
4.2%

선정연월
Categorical

Distinct8
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
2017년 9월
16 
2018년 12월
2 
2019년 4월
2 
2017년 9월
2 
2019년 3월
 
1
Other values (3)
3 

Length

Max length9
Median length8
Mean length8.1538462
Min length8

Unique

Unique4 ?
Unique (%)15.4%

Sample

1st row2017년 9월
2nd row2017년 9월
3rd row2017년 9월
4th row2017년 9월
5th row2018년 12월

Common Values

ValueCountFrequency (%)
2017년 9월 16
61.5%
2018년 12월 2
 
7.7%
2019년 4월 2
 
7.7%
2017년 9월 2
 
7.7%
2019년 3월 1
 
3.8%
2019년 5월 1
 
3.8%
2018년 3월 1
 
3.8%
2021년 3월 1
 
3.8%

Length

2023-12-11T08:05:09.005985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:05:09.136652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017년 18
34.6%
9월 18
34.6%
2019년 4
 
7.7%
2018년 3
 
5.8%
3월 3
 
5.8%
12월 2
 
3.8%
4월 2
 
3.8%
5월 1
 
1.9%
2021년 1
 
1.9%

위도
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.233862
Minimum35.171679
Maximum35.303339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T08:05:09.253128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.171679
5-th percentile35.172929
Q135.20948
median35.238896
Q335.253155
95-th percentile35.281111
Maximum35.303339
Range0.13165964
Interquartile range (IQR)0.043675366

Descriptive statistics

Standard deviation0.033871736
Coefficient of variation (CV)0.00096134043
Kurtosis-0.19968117
Mean35.233862
Median Absolute Deviation (MAD)0.014638837
Skewness-0.30724969
Sum916.08042
Variance0.0011472945
MonotonicityNot monotonic
2023-12-11T08:05:09.393060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
35.2522359276 1
 
3.8%
35.2326716911 1
 
3.8%
35.2388178494 1
 
3.8%
35.1912504479 1
 
3.8%
35.2297273292 1
 
3.8%
35.2534612706 1
 
3.8%
35.2027303152 1
 
3.8%
35.1716794323 1
 
3.8%
35.3033390763 1
 
3.8%
35.195053029 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
35.1716794323 1
3.8%
35.1722439138 1
3.8%
35.1749852659 1
3.8%
35.1912504479 1
3.8%
35.195053029 1
3.8%
35.2026842185 1
3.8%
35.2027303152 1
3.8%
35.2297273292 1
3.8%
35.2326716911 1
3.8%
35.2332685942 1
3.8%
ValueCountFrequency (%)
35.3033390763 1
3.8%
35.2834270808 1
3.8%
35.2741630285 1
3.8%
35.2646153603 1
3.8%
35.2608495443 1
3.8%
35.2536077117 1
3.8%
35.2534612706 1
3.8%
35.2522359276 1
3.8%
35.2485230398 1
3.8%
35.2453383643 1
3.8%

경도
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.8534
Minimum128.72837
Maximum128.91067
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-11T08:05:09.524763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.72837
5-th percentile128.80147
Q1128.80887
median128.86737
Q3128.88364
95-th percentile128.90839
Maximum128.91067
Range0.18229893
Interquartile range (IQR)0.074777774

Descriptive statistics

Standard deviation0.045338811
Coefficient of variation (CV)0.00035186352
Kurtosis0.53651763
Mean128.8534
Median Absolute Deviation (MAD)0.033619839
Skewness-0.85456929
Sum3350.1884
Variance0.0020556078
MonotonicityNot monotonic
2023-12-11T08:05:09.650653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
128.8716796699 1
 
3.8%
128.8659549595 1
 
3.8%
128.8761503594 1
 
3.8%
128.8035511145 1
 
3.8%
128.8964199609 1
 
3.8%
128.90846169 1
 
3.8%
128.8068711644 1
 
3.8%
128.8145337415 1
 
3.8%
128.7283711573 1
 
3.8%
128.8010410052 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
128.7283711573 1
3.8%
128.8010410052 1
3.8%
128.8027540007 1
3.8%
128.8035511145 1
3.8%
128.8056736543 1
3.8%
128.8068711644 1
3.8%
128.8069755106 1
3.8%
128.8145337415 1
3.8%
128.8286843929 1
3.8%
128.8544197972 1
3.8%
ValueCountFrequency (%)
128.9106700862 1
3.8%
128.90846169 1
3.8%
128.9081666259 1
3.8%
128.9041830175 1
3.8%
128.8977992925 1
3.8%
128.8964199609 1
3.8%
128.8861403362 1
3.8%
128.8761503594 1
3.8%
128.8749667024 1
3.8%
128.8716796699 1
3.8%

Interactions

2023-12-11T08:05:06.585782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:05:06.419159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:05:06.677167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:05:06.497722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:05:09.754990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
서점명도로명주소연락처선정연월위도경도
서점명1.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.000
선정연월1.0001.0001.0001.0000.6540.000
위도1.0001.0001.0000.6541.0000.677
경도1.0001.0001.0000.0000.6771.000
2023-12-11T08:05:09.860620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도선정연월
위도1.0000.4540.364
경도0.4541.0000.000
선정연월0.3640.0001.000

Missing values

2023-12-11T08:05:07.060883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:05:07.188586image/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

서점명도로명주소연락처선정연월위도경도
021세기 서점경상남도 김해시 가락로 301(구산동)055-339-89622017년 9월35.252236128.87168
1가야서점(삼계점)경상남도 김해시 가야로 157번길 31-19(삼계동)055-331-47772017년 9월35.264615128.874967
2가야서점(인제대점)경상남도 김해시 인제로 174-1(어방동)055-322-54632017년 9월35.244209128.904183
3경운서점경상남도 김해시 분성로 3번길 96(외동)055-326-74792017년 9월35.238973128.85442
4근비도서경상남도 김해시 한림면 김해대로 1434번길 45055-343-78962018년 12월35.274163128.828684
5내외서점경상남도 김해시 경원로 80(내동)055-324-70472017년 9월35.236627128.868788
6능력서점경상남도 김해시 생림면 인제로 657055-322-74012019년 3월35.283427128.88614
7북앤북스 서점경상남도 김해시 김해대로 2078, 2층(내동, 삼성홈플러스)055-329-49002019년 5월35.241907128.870261
8뿌리서점경상남도 김해시 우암로 37(외동)055-324-49082017년 9월35.234027128.860509
9삼계서점경상남도 김해시 삼계중앙로 41(삼계동)055-334-91142017년 9월35.26085128.869695
서점명도로명주소연락처선정연월위도경도
16율하서점경상남도 김해시 율하1로 8(율하동)055-321-32962017년 9월35.172244128.806976
17인문책방 생의 한가운데경상남도 김해시 금관대로 1365번길 10-11(내동)<NA>2019년 4월35.245338128.865672
18장유서점경상남도 김해시 번화1로 80번길 15(대청동)055-312-74742017년 9월35.195053128.801041
19정문서점경상남도 김해시 진영읍 진영로 140-1055-343-21502017년 9월35.303339128.728371
20제일도서경상남도 김해시 율하3로 42(율하동)055-326-37312017년 9월35.171679128.814534
21주문도서경상남도 김해시 능동로 149번길 9(부곡동)055-313-40512017년 9월35.20273128.806871
22청운서점경상남도 김해시 삼안로280번길 14-3055-335-06392021년 3월35.253461128.908462
23학예서림경상남도 김해시 활천로 24번길 24(삼정동)055-322-67102017년 9월35.229727128.89642
24해영서점경상남도 김해시 계동로 233(대청동)055-313-31322017년 9월35.19125128.803551
25향교도서경상남도 김해시 구지로 116-3(대성동)055-335-39872019년 4월35.238818128.87615