Overview

Dataset statistics

Number of variables4
Number of observations3558
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory118.3 KiB
Average record size in memory34.0 B

Variable types

Numeric2
Text2

Dataset

Description부산광역시_북구_U옥외광고물통합관리시스템_기관코드_20221021
Author부산광역시 북구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15050092

Alerts

기관코드 is highly overall correlated with 행정동코드High correlation
행정동코드 is highly overall correlated with 기관코드High correlation
기관전체명 has unique valuesUnique
행정동코드 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:25:28.176313
Analysis finished2023-12-10 17:25:31.027860
Duration2.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관코드
Real number (ℝ)

HIGH CORRELATION 

Distinct3203
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4272964.6
Minimum3000042
Maximum6520044
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-11T02:25:31.271528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000042
5-th percentile3100048.9
Q13490114.2
median4200071
Q34970040.2
95-th percentile5650017.2
Maximum6520044
Range3520002
Interquartile range (IQR)1479926

Descriptive statistics

Standard deviation847833.15
Coefficient of variation (CV)0.19841801
Kurtosis-0.9855425
Mean4272964.6
Median Absolute Deviation (MAD)730030.5
Skewness0.25125272
Sum1.5203208 × 1010
Variance7.1882105 × 1011
MonotonicityNot monotonic
2023-12-11T02:25:31.754039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3200153 31
 
0.9%
4180065 13
 
0.4%
4180066 9
 
0.3%
4160029 8
 
0.2%
3030058 7
 
0.2%
4180062 6
 
0.2%
4180071 5
 
0.1%
4400032 5
 
0.1%
3200167 4
 
0.1%
4690074 4
 
0.1%
Other values (3193) 3466
97.4%
ValueCountFrequency (%)
3000042 1
< 0.1%
3000043 1
< 0.1%
3000044 1
< 0.1%
3000045 1
< 0.1%
3000046 1
< 0.1%
3000047 1
< 0.1%
3000049 1
< 0.1%
3000053 1
< 0.1%
3000054 1
< 0.1%
3000056 1
< 0.1%
ValueCountFrequency (%)
6520044 1
< 0.1%
6520043 1
< 0.1%
6520042 1
< 0.1%
6520041 1
< 0.1%
6520040 1
< 0.1%
6520039 1
< 0.1%
6520038 1
< 0.1%
6520037 1
< 0.1%
6520036 1
< 0.1%
6520034 1
< 0.1%

기관명
Text

Distinct3202
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2023-12-11T02:25:32.666715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.4187746
Min length2

Characters and Unicode

Total characters12164
Distinct characters345
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

Unique2962 ?
Unique (%)83.2%

Sample

1st row청운효자동
2nd row사직동
3rd row삼청동
4th row부암동
5th row평창동
ValueCountFrequency (%)
중앙동 31
 
0.9%
남면 13
 
0.4%
서면 9
 
0.3%
북면 8
 
0.2%
송정동 7
 
0.2%
동면 6
 
0.2%
교동 5
 
0.1%
금성면 5
 
0.1%
신흥동 4
 
0.1%
산내면 4
 
0.1%
Other values (3192) 3466
97.4%
2023-12-11T02:25:33.842798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 2232
 
18.3%
면 1225
 
10.1%
1 382
 
3.1%
2 375
 
3.1%
산 301
 
2.5%
읍 254
 
2.1%
3 163
 
1.3%
성 158
 
1.3%
신 157
 
1.3%
천 154
 
1.3%
Other values (335) 6763
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11063
90.9%
Decimal Number 1076
 
8.8%
Other Punctuation 25
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2232
 
20.2%
면 1225
 
11.1%
산 301
 
2.7%
읍 254
 
2.3%
성 158
 
1.4%
신 157
 
1.4%
천 154
 
1.4%
장 149
 
1.3%
남 137
 
1.2%
대 132
 
1.2%
Other values (324) 6164
55.7%
Decimal Number
ValueCountFrequency (%)
1 382
35.5%
2 375
34.9%
3 163
15.1%
4 78
 
7.2%
5 33
 
3.1%
6 21
 
2.0%
7 11
 
1.0%
8 7
 
0.7%
9 4
 
0.4%
0 2
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11063
90.9%
Common 1101
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2232
 
20.2%
면 1225
 
11.1%
산 301
 
2.7%
읍 254
 
2.3%
성 158
 
1.4%
신 157
 
1.4%
천 154
 
1.4%
장 149
 
1.3%
남 137
 
1.2%
대 132
 
1.2%
Other values (324) 6164
55.7%
Common
ValueCountFrequency (%)
1 382
34.7%
2 375
34.1%
3 163
14.8%
4 78
 
7.1%
5 33
 
3.0%
. 25
 
2.3%
6 21
 
1.9%
7 11
 
1.0%
8 7
 
0.6%
9 4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11063
90.9%
ASCII 1101
 
9.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 2232
 
20.2%
면 1225
 
11.1%
산 301
 
2.7%
읍 254
 
2.3%
성 158
 
1.4%
신 157
 
1.4%
천 154
 
1.4%
장 149
 
1.3%
남 137
 
1.2%
대 132
 
1.2%
Other values (324) 6164
55.7%
ASCII
ValueCountFrequency (%)
1 382
34.7%
2 375
34.1%
3 163
14.8%
4 78
 
7.1%
5 33
 
3.0%
. 25
 
2.3%
6 21
 
1.9%
7 11
 
1.0%
8 7
 
0.6%
9 4
 
0.4%

기관전체명
Text

UNIQUE 

Distinct3558
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size27.9 KiB
2023-12-11T02:25:34.805045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length13.078415
Min length10

Characters and Unicode

Total characters46533
Distinct characters349
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

Unique3558 ?
Unique (%)100.0%

Sample

1st row서울특별시 종로구 청운효자동
2nd row서울특별시 종로구 사직동
3rd row서울특별시 종로구 삼청동
4th row서울특별시 종로구 부암동
5th row서울특별시 종로구 평창동
ValueCountFrequency (%)
경기도 550
 
5.0%
서울특별시 425
 
3.8%
경상북도 345
 
3.1%
전라남도 323
 
2.9%
경상남도 310
 
2.8%
전라북도 243
 
2.2%
충청남도 209
 
1.9%
부산광역시 205
 
1.9%
강원도 199
 
1.8%
인천광역시 158
 
1.4%
Other values (3460) 8104
73.2%
2023-12-11T02:25:36.059673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7533
 
16.2%
시 2776
 
6.0%
도 2548
 
5.5%
동 2523
 
5.4%
구 1796
 
3.9%
경 1275
 
2.7%
남 1240
 
2.7%
면 1225
 
2.6%
광 967
 
2.1%
북 960
 
2.1%
Other values (339) 23690
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37891
81.4%
Space Separator 7533
 
16.2%
Decimal Number 1076
 
2.3%
Other Punctuation 33
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 2776
 
7.3%
도 2548
 
6.7%
동 2523
 
6.7%
구 1796
 
4.7%
경 1275
 
3.4%
남 1240
 
3.3%
면 1225
 
3.2%
광 967
 
2.6%
북 960
 
2.5%
군 934
 
2.5%
Other values (327) 21647
57.1%
Decimal Number
ValueCountFrequency (%)
1 382
35.5%
2 375
34.9%
3 163
15.1%
4 78
 
7.2%
5 33
 
3.1%
6 21
 
2.0%
7 11
 
1.0%
8 7
 
0.7%
9 4
 
0.4%
0 2
 
0.2%
Space Separator
ValueCountFrequency (%)
7533
100.0%
Other Punctuation
ValueCountFrequency (%)
. 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37891
81.4%
Common 8642
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 2776
 
7.3%
도 2548
 
6.7%
동 2523
 
6.7%
구 1796
 
4.7%
경 1275
 
3.4%
남 1240
 
3.3%
면 1225
 
3.2%
광 967
 
2.6%
북 960
 
2.5%
군 934
 
2.5%
Other values (327) 21647
57.1%
Common
ValueCountFrequency (%)
7533
87.2%
1 382
 
4.4%
2 375
 
4.3%
3 163
 
1.9%
4 78
 
0.9%
. 33
 
0.4%
5 33
 
0.4%
6 21
 
0.2%
7 11
 
0.1%
8 7
 
0.1%
Other values (2) 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37891
81.4%
ASCII 8642
 
18.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7533
87.2%
1 382
 
4.4%
2 375
 
4.3%
3 163
 
1.9%
4 78
 
0.9%
. 33
 
0.4%
5 33
 
0.4%
6 21
 
0.2%
7 11
 
0.1%
8 7
 
0.1%
Other values (2) 6
 
0.1%
Hangul
ValueCountFrequency (%)
시 2776
 
7.3%
도 2548
 
6.7%
동 2523
 
6.7%
구 1796
 
4.7%
경 1275
 
3.4%
남 1240
 
3.3%
면 1225
 
3.2%
광 967
 
2.6%
북 960
 
2.5%
군 934
 
2.5%
Other values (327) 21647
57.1%

행정동코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3558
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7394881 × 109
Minimum1.1110515 × 109
Maximum5.013062 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.4 KiB
2023-12-11T02:25:36.456151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110515 × 109
5-th percentile1.1380528 × 109
Q12.826054 × 109
median4.2130642 × 109
Q34.6720378 × 109
95-th percentile4.8330322 × 109
Maximum5.013062 × 109
Range3.9020105 × 109
Interquartile range (IQR)1.8459838 × 109

Descriptive statistics

Standard deviation1.1907496 × 109
Coefficient of variation (CV)0.31842583
Kurtosis-0.016687212
Mean3.7394881 × 109
Median Absolute Deviation (MAD)5.059639 × 108
Skewness-1.1130894
Sum1.3305099 × 1013
Variance1.4178846 × 1018
MonotonicityStrictly increasing
2023-12-11T02:25:36.942267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1111051500 1
 
< 0.1%
4514061000 1
 
< 0.1%
4514040000 1
 
< 0.1%
4514041000 1
 
< 0.1%
4514042000 1
 
< 0.1%
4514043000 1
 
< 0.1%
4514044000 1
 
< 0.1%
4514052000 1
 
< 0.1%
4514053000 1
 
< 0.1%
4514056000 1
 
< 0.1%
Other values (3548) 3548
99.7%
ValueCountFrequency (%)
1111051500 1
< 0.1%
1111053000 1
< 0.1%
1111054000 1
< 0.1%
1111055000 1
< 0.1%
1111056000 1
< 0.1%
1111057000 1
< 0.1%
1111058000 1
< 0.1%
1111060000 1
< 0.1%
1111061500 1
< 0.1%
1111063000 1
< 0.1%
ValueCountFrequency (%)
5013062000 1
< 0.1%
5013061000 1
< 0.1%
5013060000 1
< 0.1%
5013059000 1
< 0.1%
5013058000 1
< 0.1%
5013057000 1
< 0.1%
5013056000 1
< 0.1%
5013055000 1
< 0.1%
5013054000 1
< 0.1%
5013053000 1
< 0.1%

Interactions

2023-12-11T02:25:29.887373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:25:29.276255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:25:30.227128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:25:29.556422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:25:37.233335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관코드행정동코드
기관코드1.0000.839
행정동코드0.8391.000
2023-12-11T02:25:37.433917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관코드행정동코드
기관코드1.0000.837
행정동코드0.8371.000

Missing values

2023-12-11T02:25:30.658182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:25:30.935200image/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

기관코드기관명기관전체명행정동코드
03000136청운효자동서울특별시 종로구 청운효자동1111051500
13000042사직동서울특별시 종로구 사직동1111053000
23000043삼청동서울특별시 종로구 삼청동1111054000
33000044부암동서울특별시 종로구 부암동1111055000
43000045평창동서울특별시 종로구 평창동1111056000
53000046무악동서울특별시 종로구 무악동1111057000
63000047교남동서울특별시 종로구 교남동1111058000
73000049가회동서울특별시 종로구 가회동1111060000
83000090종로1.2.3.4가동서울특별시 종로구 종로1.2.3.4가동1111061500
93000091종로5.6가동서울특별시 종로구 종로5.6가동1111063000
기관코드기관명기관전체명행정동코드
35483200153중앙동제주특별자치도 서귀포시 중앙동5013053000
35496520036천지동제주특별자치도 서귀포시 천지동5013054000
35506520037효돈동제주특별자치도 서귀포시 효돈동5013055000
35516520038영천동제주특별자치도 서귀포시 영천동5013056000
35526520039동홍동제주특별자치도 서귀포시 동홍동5013057000
35536520040서홍동제주특별자치도 서귀포시 서홍동5013058000
35546520041대륜동제주특별자치도 서귀포시 대륜동5013059000
35556520042대천동제주특별자치도 서귀포시 대천동5013060000
35566520043중문동제주특별자치도 서귀포시 중문동5013061000
35576520044예래동제주특별자치도 서귀포시 예래동5013062000