Overview

Dataset statistics

Number of variables7
Number of observations92
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory62.4 B

Variable types

Text1
Categorical2
Numeric4

Dataset

Description부산광역시 기장군 조명시설(가로등) 설치 현황에 대한 데이터로 도로명, 위치, 종류별 가로등 수의 항목을 제공합니다.
Author부산광역시 기장군
URLhttps://www.data.go.kr/data/15028663/fileData.do

Alerts

가로등_합계 is highly overall correlated with 가로등_고효율_(LED) and 1 other fieldsHigh correlation
가로등_고효율_(LED) is highly overall correlated with 가로등_합계 and 1 other fieldsHigh correlation
총등주(본) is highly overall correlated with 가로등_합계 and 1 other fieldsHigh correlation
가로등_일반 is highly imbalanced (91.3%)Imbalance
가로등_합계 has 3 (3.3%) zerosZeros
가로등_고효율_(LED) has 4 (4.3%) zerosZeros
가로등_고효율_기타 has 68 (73.9%) zerosZeros
총등주(본) has 3 (3.3%) zerosZeros

Reproduction

Analysis started2024-03-14 12:42:17.262413
Analysis finished2024-03-14 12:42:22.249865
Duration4.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도로명
Text

Distinct73
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Memory size864.0 B
2024-03-14T21:42:23.345548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length13.836957
Min length13

Characters and Unicode

Total characters1273
Distinct characters89
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

Unique55 ?
Unique (%)59.8%

Sample

1st row부산광역시 기장군 반송로
2nd row부산광역시 기장군 정관산업로
3rd row부산광역시 기장군 정관중앙로
4th row부산광역시 기장군 모전로
5th row부산광역시 기장군 정관2로
ValueCountFrequency (%)
부산광역시 92
33.1%
기장군 92
33.1%
기장해안로 3
 
1.1%
정관로 2
 
0.7%
방곡로 2
 
0.7%
장안산단로 2
 
0.7%
읍내로 2
 
0.7%
장안로 2
 
0.7%
정관산업로 2
 
0.7%
좌천로 2
 
0.7%
Other values (66) 77
27.7%
2024-03-14T21:42:24.725845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
186
14.6%
산 108
8.5%
장 102
8.0%
기 97
 
7.6%
광 96
 
7.5%
부 94
 
7.4%
시 92
 
7.2%
군 92
 
7.2%
역 92
 
7.2%
로 64
 
5.0%
Other values (79) 250
19.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1067
83.8%
Space Separator 186
 
14.6%
Decimal Number 20
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 108
10.1%
장 102
9.6%
기 97
9.1%
광 96
9.0%
부 94
8.8%
시 92
8.6%
군 92
8.6%
역 92
8.6%
로 64
 
6.0%
길 25
 
2.3%
Other values (71) 205
19.2%
Decimal Number
ValueCountFrequency (%)
1 7
35.0%
2 4
20.0%
6 3
15.0%
4 2
 
10.0%
3 2
 
10.0%
8 1
 
5.0%
5 1
 
5.0%
Space Separator
ValueCountFrequency (%)
186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1067
83.8%
Common 206
 
16.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 108
10.1%
장 102
9.6%
기 97
9.1%
광 96
9.0%
부 94
8.8%
시 92
8.6%
군 92
8.6%
역 92
8.6%
로 64
 
6.0%
길 25
 
2.3%
Other values (71) 205
19.2%
Common
ValueCountFrequency (%)
186
90.3%
1 7
 
3.4%
2 4
 
1.9%
6 3
 
1.5%
4 2
 
1.0%
3 2
 
1.0%
8 1
 
0.5%
5 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1067
83.8%
ASCII 206
 
16.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
186
90.3%
1 7
 
3.4%
2 4
 
1.9%
6 3
 
1.5%
4 2
 
1.0%
3 2
 
1.0%
8 1
 
0.5%
5 1
 
0.5%
Hangul
ValueCountFrequency (%)
산 108
10.1%
장 102
9.6%
기 97
9.1%
광 96
9.0%
부 94
8.8%
시 92
8.6%
군 92
8.6%
역 92
8.6%
로 64
 
6.0%
길 25
 
2.3%
Other values (71) 205
19.2%

위치
Categorical

Distinct29
Distinct (%)31.5%
Missing0
Missing (%)0.0%
Memory size864.0 B
정관신도시내
20 
기장읍내
17 
장안읍내
8 
일광면내
8 
철마면내
5 
Other values (24)
34 

Length

Max length13
Median length12
Mean length5.2282609
Min length3

Unique

Unique17 ?
Unique (%)18.5%

Sample

1st row기장체육관~반송
2nd row곰내터널~계좌터널
3rd row정관신도시내
4th row정관신도시내
5th row정관신도시내

Common Values

ValueCountFrequency (%)
정관신도시내 20
21.7%
기장읍내 17
18.5%
장안읍내 8
 
8.7%
일광면내 8
 
8.7%
철마면내 5
 
5.4%
기장~울산 3
 
3.3%
정관산단내 3
 
3.3%
곰내터널~계좌터널 3
 
3.3%
반룡산업단지내 2
 
2.2%
기장해안도로 2
 
2.2%
Other values (19) 21
22.8%

Length

2024-03-14T21:42:25.138193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
정관신도시내 20
20.6%
기장읍내 17
17.5%
장안읍내 8
 
8.2%
일광면내 8
 
8.2%
철마면내 5
 
5.2%
해안도로 3
 
3.1%
기장~울산 3
 
3.1%
정관산단내 3
 
3.1%
곰내터널~계좌터널 3
 
3.1%
장안산단내 2
 
2.1%
Other values (23) 25
25.8%

가로등_합계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct75
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123.18478
Minimum0
Maximum660
Zeros3
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-03-14T21:42:25.509351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.1
Q132
median71.5
Q3133.25
95-th percentile399
Maximum660
Range660
Interquartile range (IQR)101.25

Descriptive statistics

Standard deviation141.24361
Coefficient of variation (CV)1.1465995
Kurtosis3.9358533
Mean123.18478
Median Absolute Deviation (MAD)44.5
Skewness2.0018522
Sum11333
Variance19949.757
MonotonicityNot monotonic
2024-03-14T21:42:25.943717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 4
 
4.3%
48 3
 
3.3%
0 3
 
3.3%
21 2
 
2.2%
58 2
 
2.2%
19 2
 
2.2%
32 2
 
2.2%
54 2
 
2.2%
59 2
 
2.2%
127 2
 
2.2%
Other values (65) 68
73.9%
ValueCountFrequency (%)
0 3
3.3%
7 1
 
1.1%
13 1
 
1.1%
15 1
 
1.1%
16 1
 
1.1%
18 1
 
1.1%
19 2
2.2%
20 4
4.3%
21 2
2.2%
25 1
 
1.1%
ValueCountFrequency (%)
660 1
1.1%
657 1
1.1%
519 1
1.1%
489 1
1.1%
410 1
1.1%
390 1
1.1%
365 2
2.2%
338 1
1.1%
334 1
1.1%
315 1
1.1%

가로등_일반
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size864.0 B
0
91 
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 91
98.9%
5 1
 
1.1%

Length

2024-03-14T21:42:26.346019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:42:26.641321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 91
98.9%
5 1
 
1.1%

가로등_고효율_(LED)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct74
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.38043
Minimum0
Maximum660
Zeros4
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-03-14T21:42:26.959960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.3
Q130.5
median65
Q3133.25
95-th percentile390.2
Maximum660
Range660
Interquartile range (IQR)102.75

Descriptive statistics

Standard deviation138.53962
Coefficient of variation (CV)1.1802616
Kurtosis4.3377882
Mean117.38043
Median Absolute Deviation (MAD)40.5
Skewness2.0843926
Sum10799
Variance19193.227
MonotonicityNot monotonic
2024-03-14T21:42:27.396064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4
 
4.3%
20 4
 
4.3%
48 3
 
3.3%
337 2
 
2.2%
32 2
 
2.2%
103 2
 
2.2%
70 2
 
2.2%
21 2
 
2.2%
59 2
 
2.2%
50 2
 
2.2%
Other values (64) 67
72.8%
ValueCountFrequency (%)
0 4
4.3%
7 1
 
1.1%
13 1
 
1.1%
14 1
 
1.1%
15 1
 
1.1%
16 1
 
1.1%
18 1
 
1.1%
19 1
 
1.1%
20 4
4.3%
21 2
2.2%
ValueCountFrequency (%)
660 1
1.1%
638 1
1.1%
519 1
1.1%
487 1
1.1%
410 1
1.1%
374 1
1.1%
338 1
1.1%
337 2
2.2%
334 1
1.1%
314 1
1.1%

가로등_고효율_기타
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.75
Minimum0
Maximum146
Zeros68
Zeros (%)73.9%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-03-14T21:42:27.775555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile22
Maximum146
Range146
Interquartile range (IQR)2

Descriptive statistics

Standard deviation19.083751
Coefficient of variation (CV)3.3189133
Kurtosis37.90586
Mean5.75
Median Absolute Deviation (MAD)0
Skewness5.8153851
Sum529
Variance364.18956
MonotonicityNot monotonic
2024-03-14T21:42:28.150427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 68
73.9%
11 3
 
3.3%
16 2
 
2.2%
8 2
 
2.2%
2 2
 
2.2%
3 2
 
2.2%
22 2
 
2.2%
19 2
 
2.2%
13 2
 
2.2%
28 2
 
2.2%
Other values (5) 5
 
5.4%
ValueCountFrequency (%)
0 68
73.9%
2 2
 
2.2%
3 2
 
2.2%
4 1
 
1.1%
5 1
 
1.1%
8 2
 
2.2%
11 3
 
3.3%
13 2
 
2.2%
16 2
 
2.2%
19 2
 
2.2%
ValueCountFrequency (%)
146 1
 
1.1%
99 1
 
1.1%
28 2
2.2%
22 2
2.2%
20 1
 
1.1%
19 2
2.2%
16 2
2.2%
13 2
2.2%
11 3
3.3%
8 2
2.2%

총등주(본)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct71
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.11957
Minimum0
Maximum688
Zeros3
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-03-14T21:42:28.546665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.1
Q132
median72
Q3127
95-th percentile382.3
Maximum688
Range688
Interquartile range (IQR)95

Descriptive statistics

Standard deviation137.43209
Coefficient of variation (CV)1.1634998
Kurtosis4.9110374
Mean118.11957
Median Absolute Deviation (MAD)42
Skewness2.1607741
Sum10867
Variance18887.579
MonotonicityNot monotonic
2024-03-14T21:42:29.002044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 3
 
3.3%
108 3
 
3.3%
0 3
 
3.3%
36 3
 
3.3%
48 3
 
3.3%
13 2
 
2.2%
29 2
 
2.2%
19 2
 
2.2%
50 2
 
2.2%
32 2
 
2.2%
Other values (61) 67
72.8%
ValueCountFrequency (%)
0 3
3.3%
7 1
 
1.1%
11 1
 
1.1%
13 2
2.2%
16 1
 
1.1%
17 1
 
1.1%
19 2
2.2%
20 3
3.3%
21 1
 
1.1%
22 1
 
1.1%
ValueCountFrequency (%)
688 1
1.1%
631 1
1.1%
519 1
1.1%
489 1
1.1%
390 1
1.1%
376 1
1.1%
338 1
1.1%
334 1
1.1%
315 1
1.1%
312 1
1.1%

Interactions

2024-03-14T21:42:20.751025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:17.693825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:18.707713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:19.735592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:20.902020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:17.942446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:18.961229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:19.989358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:21.095524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:18.192928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:19.213521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:20.246881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:21.354925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:18.451400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:19.473898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:42:20.503845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:42:29.281971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로명위치가로등_합계가로등_일반가로등_고효율_(LED)가로등_고효율_기타총등주(본)
도로명1.0000.9900.0001.0000.0000.0000.000
위치0.9901.0000.7570.0000.7490.3780.764
가로등_합계0.0000.7571.0000.0001.0000.4060.954
가로등_일반1.0000.0000.0001.0000.0000.0000.000
가로등_고효율_(LED)0.0000.7491.0000.0001.0000.3040.942
가로등_고효율_기타0.0000.3780.4060.0000.3041.0000.501
총등주(본)0.0000.7640.9540.0000.9420.5011.000
2024-03-14T21:42:29.560007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가로등_일반위치
가로등_일반1.0000.000
위치0.0001.000
2024-03-14T21:42:29.802774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가로등_합계가로등_고효율_(LED)가로등_고효율_기타총등주(본)위치가로등_일반
가로등_합계1.0000.9710.3150.9920.3490.000
가로등_고효율_(LED)0.9711.0000.2000.9650.3410.000
가로등_고효율_기타0.3150.2001.0000.3030.1640.000
총등주(본)0.9920.9650.3031.0000.3690.000
위치0.3490.3410.1640.3691.0000.000
가로등_일반0.0000.0000.0000.0000.0001.000

Missing values

2024-03-14T21:42:21.708964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:42:22.099280image/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

도로명위치가로등_합계가로등_일반가로등_고효율_(LED)가로등_고효율_기타총등주(본)
0부산광역시 기장군 반송로기장체육관~반송910712071
1부산광역시 기장군 정관산업로곰내터널~계좌터널3150169146315
2부산광역시 기장군 정관중앙로정관신도시내78074478
3부산광역시 기장군 모전로정관신도시내20020020
4부산광역시 기장군 정관2로정관신도시내760601676
5부산광역시 기장군 정관로정관신도시내1010938101
6부산광역시 기장군 산단로곰내터널~계좌터널390037416390
7부산광역시 기장군 동부산관광로동부산관광 단지내12701270127
8부산광역시 기장군 기장대로기장~울산48904872489
9부산광역시 기장군 정관산업로곰내터널~계좌터널11301499106
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