Overview

Dataset statistics

Number of variables6
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory55.1 B

Variable types

Text5
Numeric1

Dataset

Description수영구 소재 학교 정보 제공(학교명, 소재지, 전화번호 정보 제공)-학교현황 : 21개교(초등학교 10, 중학교 6, 고등학교 4, 특수학교 1)
Author부산광역시 수영구
URLhttps://www.data.go.kr/data/15023404/fileData.do

Alerts

학 교 명 has unique valuesUnique
주 소 has unique valuesUnique
행 정 실 has unique valuesUnique
교 무 실 has unique valuesUnique
팩 스 has unique valuesUnique

Reproduction

Analysis started2024-03-14 19:27:59.547771
Analysis finished2024-03-14 19:28:00.902903
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

학 교 명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-15T04:28:01.412699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2857143
Min length4

Characters and Unicode

Total characters90
Distinct characters33
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row남천초등
2nd row광남초등
3rd row배산초등
4th row수미초등
5th row망미초등
ValueCountFrequency (%)
중 4
 
12.1%
고 2
 
6.1%
동 2
 
6.1%
남천초등 1
 
3.0%
한바다중 1
 
3.0%
부산여상 1
 
3.0%
덕문여고 1
 
3.0%
여 1
 
3.0%
일 1
 
3.0%
남 1
 
3.0%
Other values (18) 18
54.5%
2024-03-15T04:28:02.608104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
13.3%
초 10
 
11.1%
등 10
 
11.1%
중 6
 
6.7%
수 4
 
4.4%
남 3
 
3.3%
영 3
 
3.3%
여 3
 
3.3%
고 3
 
3.3%
안 3
 
3.3%
Other values (23) 33
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78
86.7%
Space Separator 12
 
13.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 10
 
12.8%
등 10
 
12.8%
중 6
 
7.7%
수 4
 
5.1%
남 3
 
3.8%
영 3
 
3.8%
여 3
 
3.8%
고 3
 
3.8%
안 3
 
3.8%
동 3
 
3.8%
Other values (22) 30
38.5%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78
86.7%
Common 12
 
13.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 10
 
12.8%
등 10
 
12.8%
중 6
 
7.7%
수 4
 
5.1%
남 3
 
3.8%
영 3
 
3.8%
여 3
 
3.8%
고 3
 
3.8%
안 3
 
3.8%
동 3
 
3.8%
Other values (22) 30
38.5%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78
86.7%
ASCII 12
 
13.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
100.0%
Hangul
ValueCountFrequency (%)
초 10
 
12.8%
등 10
 
12.8%
중 6
 
7.7%
수 4
 
5.1%
남 3
 
3.8%
영 3
 
3.8%
여 3
 
3.8%
고 3
 
3.8%
안 3
 
3.8%
동 3
 
3.8%
Other values (22) 30
38.5%

주 소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-15T04:28:03.523875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length13.714286
Min length10

Characters and Unicode

Total characters288
Distinct characters39
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

Unique21 ?
Unique (%)100.0%

Sample

1st row남천서로14(남천동)
2nd row광안해변로115(남천동)
3rd row망미배산로48번길85-15(망미동)
4th row연수로310번길91(망미동)
5th row수미로35번길27(망미동)
ValueCountFrequency (%)
남천서로14(남천동 1
 
4.8%
호암로38(광안동 1
 
4.8%
금련로43(망미동 1
 
4.8%
연수로310번길114(광안동 1
 
4.8%
남천서로32번길39(남천동 1
 
4.8%
망미배산로48번길85-23(망미동 1
 
4.8%
광서로74(광안동 1
 
4.8%
연수로310번길127(광안동 1
 
4.8%
망미배산로102(망미동 1
 
4.8%
광안로21번가길57(광안동 1
 
4.8%
Other values (11) 11
52.4%
2024-03-15T04:28:04.466414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 21
 
7.3%
동 21
 
7.3%
로 21
 
7.3%
( 21
 
7.3%
3 17
 
5.9%
1 16
 
5.6%
광 15
 
5.2%
번 13
 
4.5%
길 13
 
4.5%
안 12
 
4.2%
Other values (29) 118
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163
56.6%
Decimal Number 81
28.1%
Close Punctuation 21
 
7.3%
Open Punctuation 21
 
7.3%
Dash Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 21
12.9%
로 21
12.9%
광 15
9.2%
번 13
 
8.0%
길 13
 
8.0%
안 12
 
7.4%
미 11
 
6.7%
망 10
 
6.1%
남 6
 
3.7%
수 5
 
3.1%
Other values (16) 36
22.1%
Decimal Number
ValueCountFrequency (%)
3 17
21.0%
1 16
19.8%
5 11
13.6%
2 9
11.1%
4 7
8.6%
7 7
8.6%
8 6
 
7.4%
0 5
 
6.2%
9 2
 
2.5%
6 1
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163
56.6%
Common 125
43.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 21
12.9%
로 21
12.9%
광 15
9.2%
번 13
 
8.0%
길 13
 
8.0%
안 12
 
7.4%
미 11
 
6.7%
망 10
 
6.1%
남 6
 
3.7%
수 5
 
3.1%
Other values (16) 36
22.1%
Common
ValueCountFrequency (%)
) 21
16.8%
( 21
16.8%
3 17
13.6%
1 16
12.8%
5 11
8.8%
2 9
7.2%
4 7
 
5.6%
7 7
 
5.6%
8 6
 
4.8%
0 5
 
4.0%
Other values (3) 5
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163
56.6%
ASCII 125
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 21
16.8%
( 21
16.8%
3 17
13.6%
1 16
12.8%
5 11
8.8%
2 9
7.2%
4 7
 
5.6%
7 7
 
5.6%
8 6
 
4.8%
0 5
 
4.0%
Other values (3) 5
 
4.0%
Hangul
ValueCountFrequency (%)
동 21
12.9%
로 21
12.9%
광 15
9.2%
번 13
 
8.0%
길 13
 
8.0%
안 12
 
7.4%
미 11
 
6.7%
망 10
 
6.1%
남 6
 
3.7%
수 5
 
3.1%
Other values (16) 36
22.1%

우편번호
Real number (ℝ)

Distinct15
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48254.619
Minimum48200
Maximum48316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-03-15T04:28:04.674406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48200
5-th percentile48201
Q148237
median48246
Q348275
95-th percentile48315
Maximum48316
Range116
Interquartile range (IQR)38

Descriptive statistics

Standard deviation36.114369
Coefficient of variation (CV)0.00074841268
Kurtosis-0.79983986
Mean48254.619
Median Absolute Deviation (MAD)28
Skewness0.21218301
Sum1013347
Variance1304.2476
MonotonicityNot monotonic
2024-03-15T04:28:04.892574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
48237 4
19.0%
48201 2
 
9.5%
48296 2
 
9.5%
48259 2
 
9.5%
48316 1
 
4.8%
48305 1
 
4.8%
48216 1
 
4.8%
48246 1
 
4.8%
48275 1
 
4.8%
48274 1
 
4.8%
Other values (5) 5
23.8%
ValueCountFrequency (%)
48200 1
 
4.8%
48201 2
9.5%
48216 1
 
4.8%
48237 4
19.0%
48239 1
 
4.8%
48245 1
 
4.8%
48246 1
 
4.8%
48256 1
 
4.8%
48259 2
9.5%
48274 1
 
4.8%
ValueCountFrequency (%)
48316 1
4.8%
48315 1
4.8%
48305 1
4.8%
48296 2
9.5%
48275 1
4.8%
48274 1
4.8%
48259 2
9.5%
48256 1
4.8%
48246 1
4.8%
48245 1
4.8%

행 정 실
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-15T04:28:05.611825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters252
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

Unique21 ?
Unique (%)100.0%

Sample

1st row051-610-3707
2nd row051-610-6607
3rd row051-754-9106
4th row051-791-4705
5th row051-796-5508
ValueCountFrequency (%)
051-610-3707 1
 
4.8%
051-760-7705 1
 
4.8%
051-797-6707 1
 
4.8%
051-756-1802 1
 
4.8%
051-610-5700 1
 
4.8%
051-750-0150 1
 
4.8%
051-752-3355 1
 
4.8%
051-750-3100 1
 
4.8%
051-750-0770 1
 
4.8%
051-760-0700 1
 
4.8%
Other values (11) 11
52.4%
2024-03-15T04:28:06.797629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 55
21.8%
- 42
16.7%
5 40
15.9%
1 34
13.5%
7 33
13.1%
6 14
 
5.6%
2 12
 
4.8%
9 9
 
3.6%
3 7
 
2.8%
4 3
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210
83.3%
Dash Punctuation 42
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 55
26.2%
5 40
19.0%
1 34
16.2%
7 33
15.7%
6 14
 
6.7%
2 12
 
5.7%
9 9
 
4.3%
3 7
 
3.3%
4 3
 
1.4%
8 3
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 55
21.8%
- 42
16.7%
5 40
15.9%
1 34
13.5%
7 33
13.1%
6 14
 
5.6%
2 12
 
4.8%
9 9
 
3.6%
3 7
 
2.8%
4 3
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 55
21.8%
- 42
16.7%
5 40
15.9%
1 34
13.5%
7 33
13.1%
6 14
 
5.6%
2 12
 
4.8%
9 9
 
3.6%
3 7
 
2.8%
4 3
 
1.2%

교 무 실
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-15T04:28:07.988213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters252
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

Unique21 ?
Unique (%)100.0%

Sample

1st row051-610-3702
2nd row051-610-6600
3rd row051-754-5930
4th row051-791-4700
5th row051-796-5500
ValueCountFrequency (%)
051-610-3702 1
 
4.8%
051-760-7700 1
 
4.8%
051-797-6700 1
 
4.8%
051-756-1801 1
 
4.8%
051-610-5700 1
 
4.8%
051-750-0150 1
 
4.8%
051-752-0046 1
 
4.8%
051-750-3100 1
 
4.8%
051-750-0700 1
 
4.8%
051-760-0700 1
 
4.8%
Other values (11) 11
52.4%
2024-03-15T04:28:09.224204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 69
27.4%
- 42
16.7%
5 36
14.3%
1 33
13.1%
7 27
 
10.7%
6 14
 
5.6%
2 10
 
4.0%
9 9
 
3.6%
3 6
 
2.4%
4 4
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210
83.3%
Dash Punctuation 42
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 69
32.9%
5 36
17.1%
1 33
15.7%
7 27
 
12.9%
6 14
 
6.7%
2 10
 
4.8%
9 9
 
4.3%
3 6
 
2.9%
4 4
 
1.9%
8 2
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 69
27.4%
- 42
16.7%
5 36
14.3%
1 33
13.1%
7 27
 
10.7%
6 14
 
5.6%
2 10
 
4.0%
9 9
 
3.6%
3 6
 
2.4%
4 4
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 69
27.4%
- 42
16.7%
5 36
14.3%
1 33
13.1%
7 27
 
10.7%
6 14
 
5.6%
2 10
 
4.0%
9 9
 
3.6%
3 6
 
2.4%
4 4
 
1.6%

팩 스
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-15T04:28:10.152700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters252
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

Unique21 ?
Unique (%)100.0%

Sample

1st row051-621-0749
2nd row051-628-0767
3rd row051-754-5131
4th row051-791-4725
5th row051-796-5569
ValueCountFrequency (%)
051-621-0749 1
 
4.8%
051-753-6592 1
 
4.8%
051-797-6801 1
 
4.8%
051-751-0920 1
 
4.8%
051-610-5801 1
 
4.8%
051-751-0113 1
 
4.8%
051-751-9674 1
 
4.8%
051-750-3103 1
 
4.8%
051-750-0799 1
 
4.8%
051-753-8125 1
 
4.8%
Other values (11) 11
52.4%
2024-03-15T04:28:11.024357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 44
17.5%
- 42
16.7%
1 39
15.5%
0 36
14.3%
7 29
11.5%
9 12
 
4.8%
6 11
 
4.4%
4 11
 
4.4%
3 11
 
4.4%
2 10
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210
83.3%
Dash Punctuation 42
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 44
21.0%
1 39
18.6%
0 36
17.1%
7 29
13.8%
9 12
 
5.7%
6 11
 
5.2%
4 11
 
5.2%
3 11
 
5.2%
2 10
 
4.8%
8 7
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 44
17.5%
- 42
16.7%
1 39
15.5%
0 36
14.3%
7 29
11.5%
9 12
 
4.8%
6 11
 
4.4%
4 11
 
4.4%
3 11
 
4.4%
2 10
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 44
17.5%
- 42
16.7%
1 39
15.5%
0 36
14.3%
7 29
11.5%
9 12
 
4.8%
6 11
 
4.4%
4 11
 
4.4%
3 11
 
4.4%
2 10
 
4.0%

Interactions

2024-03-15T04:27:59.877753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T04:28:11.261564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학 교 명주 소우편번호행 정 실교 무 실팩 스
학 교 명1.0001.0001.0001.0001.0001.000
주 소1.0001.0001.0001.0001.0001.000
우편번호1.0001.0001.0001.0001.0001.000
행 정 실1.0001.0001.0001.0001.0001.000
교 무 실1.0001.0001.0001.0001.0001.000
팩 스1.0001.0001.0001.0001.0001.000

Missing values

2024-03-15T04:28:00.350145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:28:00.748852image/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

학 교 명주 소우편번호행 정 실교 무 실팩 스
0남천초등남천서로14(남천동)48316051-610-3707051-610-3702051-621-0749
1광남초등광안해변로115(남천동)48305051-610-6607051-610-6600051-628-0767
2배산초등망미배산로48번길85-15(망미동)48201051-754-9106051-754-5930051-754-5131
3수미초등연수로310번길91(망미동)48237051-791-4705051-791-4700051-791-4725
4망미초등수미로35번길27(망미동)48216051-796-5508051-796-5500051-796-5569
5수영초등광서로16번길33(광안동)48246051-792-2572051-792-2500051-757-6494
6광안초등광안로35번길42(광안동)48296051-790-2207051-790-2200051-753-4421
7호암초등호암로57(광안동)48259051-712-3605051-712-3600051-712-3678
8민락초등광남로257번길12(민락동)48275051-752-8694051-752-8694051-753-5702
9민안초등감포로38번길33(민락동)48274051-751-3931051-751-3931051-753-4031
학 교 명주 소우편번호행 정 실교 무 실팩 스
11수 영 중호암로38(광안동)48256051-760-7705051-760-7700051-753-6592
12한바다중광안로21번가길57(광안동)48296051-760-0700051-760-0700051-753-8125
13망 미 중망미배산로102(망미동)48200051-750-0770051-750-0700051-750-0799
14광 안 중연수로310번길127(광안동)48237051-750-3100051-750-3100051-750-3103
15동수영중광서로74(광안동)48245051-752-3355051-752-0046051-751-9674
16남 일 고망미배산로48번길85-23(망미동)48201051-750-0150051-750-0150051-751-0113
17동 여 고남천서로32번길39(남천동)48315051-610-5700051-610-5700051-610-5801
18덕문여고연수로310번길114(광안동)48237051-756-1802051-756-1801051-751-0920
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20배화학교연수로310번길73(망미동)48237051-760-2521051-760-2500051-757-8548