Overview

Dataset statistics

Number of variables7
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory62.7 B

Variable types

Text3
Numeric3
Categorical1

Dataset

Description부산광역시 사상구 관내 공공기관(사상구청, 사상경찰서, 북부소방서, 사상우체국 등)의 명칭, 소재지, 전화번호 등 현황 안내입니다
Author부산광역시 사상구
URLhttps://www.data.go.kr/data/15025564/fileData.do

Alerts

데이터기준일 has constant value ""Constant
위도 is highly overall correlated with 우편번호High correlation
우편번호 is highly overall correlated with 위도High correlation
행정공공기관명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-04-21 01:01:49.225214
Analysis finished2024-04-21 01:01:51.864583
Duration2.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정공공기관명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-04-21T10:01:52.000767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length10.527778
Min length5

Characters and Unicode

Total characters379
Distinct characters90
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row부산광역시 사상구청
2nd row부산광역시 부산도서관
3rd row부산광역시 사상도서관
4th row부산광역시 사상구보건소
5th row부산사상경찰서
ValueCountFrequency (%)
부산광역시 9
 
18.0%
삼락동행정복지센터 1
 
2.0%
모라종합사회복지관 1
 
2.0%
백양종합사회복지관 1
 
2.0%
사상구종합사회복지관 1
 
2.0%
모라3동행정복지센터 1
 
2.0%
학장종합사회복지관 1
 
2.0%
사상구장애인복지관 1
 
2.0%
사상구다누림센터 1
 
2.0%
사상구국제화센터 1
 
2.0%
Other values (32) 32
64.0%
2024-04-21T10:01:52.306029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 23
 
6.1%
산 20
 
5.3%
지 20
 
5.3%
사 18
 
4.7%
복 17
 
4.5%
센 15
 
4.0%
터 15
 
4.0%
동 14
 
3.7%
14
 
3.7%
행 12
 
3.2%
Other values (80) 211
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 358
94.5%
Space Separator 14
 
3.7%
Decimal Number 7
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 23
 
6.4%
산 20
 
5.6%
지 20
 
5.6%
사 18
 
5.0%
복 17
 
4.7%
센 15
 
4.2%
터 15
 
4.2%
동 14
 
3.9%
행 12
 
3.4%
정 12
 
3.4%
Other values (76) 192
53.6%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
3 2
28.6%
2 2
28.6%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 358
94.5%
Common 21
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 23
 
6.4%
산 20
 
5.6%
지 20
 
5.6%
사 18
 
5.0%
복 17
 
4.7%
센 15
 
4.2%
터 15
 
4.2%
동 14
 
3.9%
행 12
 
3.4%
정 12
 
3.4%
Other values (76) 192
53.6%
Common
ValueCountFrequency (%)
14
66.7%
1 3
 
14.3%
3 2
 
9.5%
2 2
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 358
94.5%
ASCII 21
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 23
 
6.4%
산 20
 
5.6%
지 20
 
5.6%
사 18
 
5.0%
복 17
 
4.7%
센 15
 
4.2%
터 15
 
4.2%
동 14
 
3.9%
행 12
 
3.4%
정 12
 
3.4%
Other values (76) 192
53.6%
ASCII
ValueCountFrequency (%)
14
66.7%
1 3
 
14.3%
3 2
 
9.5%
2 2
 
9.5%

도로명주소
Text

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-04-21T10:01:52.511189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27.5
Mean length23.333333
Min length16

Characters and Unicode

Total characters840
Distinct characters57
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

Unique34 ?
Unique (%)94.4%

Sample

1st row부산광역시 사상구 학감대로 242 (감전동)
2nd row부산광역시 사상구 사상로310번길 33 (덕포동)
3rd row부산광역시 사상구 덕상로72번길 9 (덕포동)
4th row부산광역시 사상구 학감대로 242 (감전동)
5th row부산광역시 사상구 학감대로 264 (감전동)
ValueCountFrequency (%)
부산광역시 36
21.4%
사상구 36
21.4%
덕포동 6
 
3.6%
학감대로 5
 
3.0%
감전동 5
 
3.0%
모라동 4
 
2.4%
백양대로 3
 
1.8%
학장동 3
 
1.8%
주례동 3
 
1.8%
17 3
 
1.8%
Other values (56) 64
38.1%
2024-04-21T10:01:52.858835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132
 
15.7%
상 42
 
5.0%
사 39
 
4.6%
시 38
 
4.5%
광 37
 
4.4%
산 37
 
4.4%
부 36
 
4.3%
역 36
 
4.3%
구 36
 
4.3%
로 36
 
4.3%
Other values (47) 371
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 524
62.4%
Decimal Number 134
 
16.0%
Space Separator 132
 
15.7%
Close Punctuation 24
 
2.9%
Open Punctuation 24
 
2.9%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 42
 
8.0%
사 39
 
7.4%
시 38
 
7.3%
광 37
 
7.1%
산 37
 
7.1%
부 36
 
6.9%
역 36
 
6.9%
구 36
 
6.9%
로 36
 
6.9%
동 26
 
5.0%
Other values (33) 161
30.7%
Decimal Number
ValueCountFrequency (%)
1 30
22.4%
2 23
17.2%
9 15
11.2%
3 14
10.4%
7 11
 
8.2%
5 11
 
8.2%
0 10
 
7.5%
6 8
 
6.0%
4 7
 
5.2%
8 5
 
3.7%
Space Separator
ValueCountFrequency (%)
132
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 524
62.4%
Common 316
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 42
 
8.0%
사 39
 
7.4%
시 38
 
7.3%
광 37
 
7.1%
산 37
 
7.1%
부 36
 
6.9%
역 36
 
6.9%
구 36
 
6.9%
로 36
 
6.9%
동 26
 
5.0%
Other values (33) 161
30.7%
Common
ValueCountFrequency (%)
132
41.8%
1 30
 
9.5%
) 24
 
7.6%
( 24
 
7.6%
2 23
 
7.3%
9 15
 
4.7%
3 14
 
4.4%
7 11
 
3.5%
5 11
 
3.5%
0 10
 
3.2%
Other values (4) 22
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 524
62.4%
ASCII 316
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
41.8%
1 30
 
9.5%
) 24
 
7.6%
( 24
 
7.6%
2 23
 
7.3%
9 15
 
4.7%
3 14
 
4.4%
7 11
 
3.5%
5 11
 
3.5%
0 10
 
3.2%
Other values (4) 22
 
7.0%
Hangul
ValueCountFrequency (%)
상 42
 
8.0%
사 39
 
7.4%
시 38
 
7.3%
광 37
 
7.1%
산 37
 
7.1%
부 36
 
6.9%
역 36
 
6.9%
구 36
 
6.9%
로 36
 
6.9%
동 26
 
5.0%
Other values (33) 161
30.7%

전화번호
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-04-21T10:01:53.050383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters432
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

Unique36 ?
Unique (%)100.0%

Sample

1st row051-310-4000
2nd row051-310-5400
3rd row051-310-7971
4th row051-310-4791
5th row051-329-0230
ValueCountFrequency (%)
051-310-4000 1
 
2.8%
051-310-5400 1
 
2.8%
051-310-3060 1
 
2.8%
051-311-4017 1
 
2.8%
051-302-5523 1
 
2.8%
051-319-7330 1
 
2.8%
051-366-0505 1
 
2.8%
051-310-3020 1
 
2.8%
051-310-3040 1
 
2.8%
051-310-3080 1
 
2.8%
Other values (26) 26
72.2%
2024-04-21T10:01:53.359505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 101
23.4%
1 79
18.3%
- 72
16.7%
3 57
13.2%
5 47
10.9%
2 20
 
4.6%
4 17
 
3.9%
6 11
 
2.5%
7 10
 
2.3%
9 9
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 360
83.3%
Dash Punctuation 72
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 101
28.1%
1 79
21.9%
3 57
15.8%
5 47
13.1%
2 20
 
5.6%
4 17
 
4.7%
6 11
 
3.1%
7 10
 
2.8%
9 9
 
2.5%
8 9
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 101
23.4%
1 79
18.3%
- 72
16.7%
3 57
13.2%
5 47
10.9%
2 20
 
4.6%
4 17
 
3.9%
6 11
 
2.5%
7 10
 
2.3%
9 9
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 101
23.4%
1 79
18.3%
- 72
16.7%
3 57
13.2%
5 47
10.9%
2 20
 
4.6%
4 17
 
3.9%
6 11
 
2.5%
7 10
 
2.3%
9 9
 
2.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.16184
Minimum35.128681
Maximum35.187073
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-21T10:01:53.477947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.128681
5-th percentile35.134998
Q135.147329
median35.157878
Q335.178338
95-th percentile35.184912
Maximum35.187073
Range0.058392
Interquartile range (IQR)0.0310085

Descriptive statistics

Standard deviation0.017838735
Coefficient of variation (CV)0.00050733224
Kurtosis-1.2723727
Mean35.16184
Median Absolute Deviation (MAD)0.01661362
Skewness-0.1436756
Sum1265.8263
Variance0.00031822047
MonotonicityNot monotonic
2024-04-21T10:01:53.611861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
35.152547 2
 
5.6%
35.172725 1
 
2.8%
35.184901 1
 
2.8%
35.147255 1
 
2.8%
35.177602 1
 
2.8%
35.177006 1
 
2.8%
35.187073 1
 
2.8%
35.184653 1
 
2.8%
35.169215 1
 
2.8%
35.174457 1
 
2.8%
Other values (25) 25
69.4%
ValueCountFrequency (%)
35.128681 1
2.8%
35.12869 1
2.8%
35.137101 1
2.8%
35.1386522 1
2.8%
35.140076 1
2.8%
35.144099 1
2.8%
35.14567 1
2.8%
35.146038 1
2.8%
35.147255 1
2.8%
35.147354 1
2.8%
ValueCountFrequency (%)
35.187073 1
2.8%
35.184944 1
2.8%
35.184901 1
2.8%
35.184653 1
2.8%
35.183724 1
2.8%
35.183319 1
2.8%
35.181196 1
2.8%
35.180911 1
2.8%
35.179033 1
2.8%
35.178106 1
2.8%

경도
Real number (ℝ)

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.98923
Minimum128.96428
Maximum129.01042
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-21T10:01:53.728539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.96428
5-th percentile128.97131
Q1128.98561
median128.98995
Q3128.9948
95-th percentile129.00118
Maximum129.01042
Range0.046138
Interquartile range (IQR)0.00918575

Descriptive statistics

Standard deviation0.0093375594
Coefficient of variation (CV)7.2390226 × 10-5
Kurtosis1.0954006
Mean128.98923
Median Absolute Deviation (MAD)0.0047315
Skewness-0.58255876
Sum4643.6122
Variance8.7190016 × 10-5
MonotonicityNot monotonic
2024-04-21T10:01:53.834093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
128.991451 2
 
5.6%
128.985296 1
 
2.8%
129.000936 1
 
2.8%
128.994844 1
 
2.8%
128.990845 1
 
2.8%
128.977641 1
 
2.8%
128.990081 1
 
2.8%
128.996058 1
 
2.8%
128.985714 1
 
2.8%
128.982968 1
 
2.8%
Other values (25) 25
69.4%
ValueCountFrequency (%)
128.96428 1
2.8%
128.968648 1
2.8%
128.972202 1
2.8%
128.977641 1
2.8%
128.978753 1
2.8%
128.979409 1
2.8%
128.982968 1
2.8%
128.985241 1
2.8%
128.985296 1
2.8%
128.985714 1
2.8%
ValueCountFrequency (%)
129.010418 1
2.8%
129.001419 1
2.8%
129.001094 1
2.8%
129.000936 1
2.8%
128.999351 1
2.8%
128.997873 1
2.8%
128.996969 1
2.8%
128.996058 1
2.8%
128.994844 1
2.8%
128.994779 1
2.8%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46975.889
Minimum46910
Maximum47053
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-21T10:01:53.947724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46910
5-th percentile46924.5
Q146938
median46979
Q347015.25
95-th percentile47042.5
Maximum47053
Range143
Interquartile range (IQR)77.25

Descriptive statistics

Standard deviation42.192604
Coefficient of variation (CV)0.00089817576
Kurtosis-1.2208952
Mean46975.889
Median Absolute Deviation (MAD)41
Skewness0.2428665
Sum1691132
Variance1780.2159
MonotonicityNot monotonic
2024-04-21T10:01:54.059254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
46938 4
 
11.1%
46985 3
 
8.3%
47053 2
 
5.6%
47016 2
 
5.6%
46934 2
 
5.6%
46935 2
 
5.6%
46929 1
 
2.8%
47023 1
 
2.8%
47039 1
 
2.8%
47015 1
 
2.8%
Other values (17) 17
47.2%
ValueCountFrequency (%)
46910 1
 
2.8%
46911 1
 
2.8%
46929 1
 
2.8%
46931 1
 
2.8%
46934 2
5.6%
46935 2
5.6%
46938 4
11.1%
46943 1
 
2.8%
46946 1
 
2.8%
46949 1
 
2.8%
ValueCountFrequency (%)
47053 2
5.6%
47039 1
2.8%
47032 1
2.8%
47030 1
2.8%
47023 1
2.8%
47022 1
2.8%
47016 2
5.6%
47015 1
2.8%
47007 1
2.8%
47002 1
2.8%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-04-09
36 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-04-09
2nd row2024-04-09
3rd row2024-04-09
4th row2024-04-09
5th row2024-04-09

Common Values

ValueCountFrequency (%)
2024-04-09 36
100.0%

Length

2024-04-21T10:01:54.164285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:01:54.248814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-04-09 36
100.0%

Interactions

2024-04-21T10:01:51.426408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:01:50.920320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:01:51.214239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:01:51.507687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:01:51.052542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:01:51.283495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:01:51.608904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:01:51.129036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:01:51.351655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:01:54.308470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정공공기관명도로명주소전화번호위도경도우편번호
행정공공기관명1.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
위도1.0001.0001.0001.0000.7990.969
경도1.0001.0001.0000.7991.0000.919
우편번호1.0001.0001.0000.9690.9191.000
2024-04-21T10:01:54.403877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도우편번호
위도1.0000.145-0.947
경도0.1451.000-0.021
우편번호-0.947-0.0211.000

Missing values

2024-04-21T10:01:51.721006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:01:51.816808image/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

행정공공기관명도로명주소전화번호위도경도우편번호데이터기준일
0부산광역시 사상구청부산광역시 사상구 학감대로 242 (감전동)051-310-400035.152547128.991451469852024-04-09
1부산광역시 부산도서관부산광역시 사상구 사상로310번길 33 (덕포동)051-310-540035.172725128.985296469492024-04-09
2부산광역시 사상도서관부산광역시 사상구 덕상로72번길 9 (덕포동)051-310-797135.178106128.989808469382024-04-09
3부산광역시 사상구보건소부산광역시 사상구 학감대로 242 (감전동)051-310-479135.152547128.991451469852024-04-09
4부산사상경찰서부산광역시 사상구 학감대로 264 (감전동)051-329-023035.154368128.991364469852024-04-09
5부산사상소방서부산광역시 사상구 삼덕로 17 (삼락동)051-760-440035.174527128.978753469102024-04-09
6부산사상우체국부산광역시 사상구 사상로 165 (괘법동)051-320-333135.160326128.985871469742024-04-09
7부산 북부산세무서부산광역시 사상구 학감대로 263 (감전동)051-310-620035.154657128.99028469842024-04-09
8부산지방노동청북부지청부산광역시 사상구 백양대로 804 (덕포동)051-309-150035.179033128.988908469382024-04-09
9부산광역시 청소년수련관부산광역시 사상구 덕상로 129 (모라동)051-316-221435.183319128.990563469312024-04-09
행정공공기관명도로명주소전화번호위도경도우편번호데이터기준일
26모라3동행정복지센터부산광역시 사상구 모라로110번길 99051-310-306035.184653128.996058469342024-04-09
27덕포1동행정복지센터부산광역시 사상구 강선로 31051-310-308035.169215128.985714469512024-04-09
28덕포2동행정복지센터부산광역시 사상구 사상로333번길 17051-310-310035.174457128.982968469462024-04-09
29괘법동행정복지센터부산광역시 사상구 광장로97번길 6051-310-312035.163759128.987197469672024-04-09
30감전동행정복지센터부산광역시 사상구 새벽시장로56번길 20051-310-314035.154204128.979409469892024-04-09
31주례1동행정복지센터부산광역시 사상구 가야대로255번길 17051-310-316035.151341129.001094470022024-04-09
32주례2동행정복지센터부산광역시 사상구 주례로10번길 15051-310-318035.150064129.010418470072024-04-09
33주례3동행정복지센터부산광역시 사상구 냉정로 10051-310-320035.147354129.001419470152024-04-09
34엄궁동행정복지센터부산광역시 사상구 엄궁북로 15051-310-324035.12869128.972202470392024-04-09
35학장동행정복지센터부산광역시 사상구 학감대로147번길 11051-310-322035.144099128.98731470232024-04-09