Overview

Dataset statistics

Number of variables4
Number of observations189
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory33.7 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description서울특별시 강북구 가로등의 분전함 정보
Author서울특별시 강북구
URLhttps://www.data.go.kr/data/15068535/fileData.do

Alerts

도로명 is highly imbalanced (62.0%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:24:16.048284
Analysis finished2023-12-12 23:24:16.444972
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct189
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95
Minimum1
Maximum189
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T08:24:16.502236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.4
Q148
median95
Q3142
95-th percentile179.6
Maximum189
Range188
Interquartile range (IQR)94

Descriptive statistics

Standard deviation54.703748
Coefficient of variation (CV)0.57582892
Kurtosis-1.2
Mean95
Median Absolute Deviation (MAD)47
Skewness0
Sum17955
Variance2992.5
MonotonicityStrictly increasing
2023-12-13T08:24:16.605708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
131 1
 
0.5%
122 1
 
0.5%
123 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
Other values (179) 179
94.7%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%
183 1
0.5%
182 1
0.5%
181 1
0.5%
180 1
0.5%

도로명
Categorical

IMBALANCE 

Distinct46
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
"
144 
버스6
 
1
벚꽃길
 
1
삼양로
 
1
도봉로
 
1
Other values (41)
41 

Length

Max length9
Median length1
Mean length1.6719577
Min length1

Unique

Unique45 ?
Unique (%)23.8%

Sample

1st row한천로
2nd row"
3rd row"
4th row"
5th row"

Common Values

ValueCountFrequency (%)
" 144
76.2%
버스6 1
 
0.5%
벚꽃길 1
 
0.5%
삼양로 1
 
0.5%
도봉로 1
 
0.5%
구청앞경관 1
 
0.5%
버스1 1
 
0.5%
버스2 1
 
0.5%
버스3 1
 
0.5%
버스4 1
 
0.5%
Other values (36) 36
 
19.0%

Length

2023-12-13T08:24:16.714690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
144
76.2%
방학로 1
 
0.5%
미양마을 1
 
0.5%
자전거도로 1
 
0.5%
벌리길 1
 
0.5%
가오리길 1
 
0.5%
큰마을길 1
 
0.5%
궁안길 1
 
0.5%
무너미길 1
 
0.5%
무너미샛길 1
 
0.5%
Other values (36) 36
 
19.0%

분 전 함관리번호
Text

Distinct188
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T08:24:16.939456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length5.9206349
Min length4

Characters and Unicode

Total characters1119
Distinct characters90
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)98.9%

Sample

1st row한천로-1
2nd row한천로-2
3rd row한천로-3
4th row한천로-4
5th row한천로-5
ValueCountFrequency (%)
삼성a길-1 2
 
1.1%
오패산길-7 1
 
0.5%
가오리길-3 1
 
0.5%
오패산길-8 1
 
0.5%
경찰서길-1 1
 
0.5%
오패산길-1 1
 
0.5%
오패산길-2 1
 
0.5%
오패산길-3 1
 
0.5%
오패산길-4 1
 
0.5%
오패산길-5 1
 
0.5%
Other values (178) 178
94.2%
2023-12-13T08:24:17.256486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 188
 
16.8%
길 96
 
8.6%
로 88
 
7.9%
1 67
 
6.0%
도 39
 
3.5%
봉 37
 
3.3%
오 28
 
2.5%
2 26
 
2.3%
3 23
 
2.1%
천 21
 
1.9%
Other values (80) 506
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 702
62.7%
Decimal Number 215
 
19.2%
Dash Punctuation 188
 
16.8%
Connector Punctuation 8
 
0.7%
Uppercase Letter 4
 
0.4%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 96
 
13.7%
로 88
 
12.5%
도 39
 
5.6%
봉 37
 
5.3%
오 28
 
4.0%
천 21
 
3.0%
한 20
 
2.8%
동 16
 
2.3%
리 16
 
2.3%
계 15
 
2.1%
Other values (65) 326
46.4%
Decimal Number
ValueCountFrequency (%)
1 67
31.2%
2 26
 
12.1%
3 23
 
10.7%
4 20
 
9.3%
5 19
 
8.8%
6 16
 
7.4%
7 14
 
6.5%
8 13
 
6.0%
9 10
 
4.7%
0 7
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 188
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 702
62.7%
Common 413
36.9%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 96
 
13.7%
로 88
 
12.5%
도 39
 
5.6%
봉 37
 
5.3%
오 28
 
4.0%
천 21
 
3.0%
한 20
 
2.8%
동 16
 
2.3%
리 16
 
2.3%
계 15
 
2.1%
Other values (65) 326
46.4%
Common
ValueCountFrequency (%)
- 188
45.5%
1 67
 
16.2%
2 26
 
6.3%
3 23
 
5.6%
4 20
 
4.8%
5 19
 
4.6%
6 16
 
3.9%
7 14
 
3.4%
8 13
 
3.1%
9 10
 
2.4%
Other values (4) 17
 
4.1%
Latin
ValueCountFrequency (%)
A 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 702
62.7%
ASCII 417
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 188
45.1%
1 67
 
16.1%
2 26
 
6.2%
3 23
 
5.5%
4 20
 
4.8%
5 19
 
4.6%
6 16
 
3.8%
7 14
 
3.4%
8 13
 
3.1%
9 10
 
2.4%
Other values (5) 21
 
5.0%
Hangul
ValueCountFrequency (%)
길 96
 
13.7%
로 88
 
12.5%
도 39
 
5.6%
봉 37
 
5.3%
오 28
 
4.0%
천 21
 
3.0%
한 20
 
2.8%
동 16
 
2.3%
리 16
 
2.3%
계 15
 
2.1%
Other values (65) 326
46.4%

주소
Text

Distinct188
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T08:24:17.481751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length12.174603
Min length5

Characters and Unicode

Total characters2301
Distinct characters189
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)98.9%

Sample

1st row한천로105길24(주공204동 건너편)
2nd row한천로897(강북보건소건너편)
3rd row한천로918옆(SK주유소)
4th row한천로940앞(한성운수건너편)
5th row한천로982앞(충북사진관)
ValueCountFrequency (%)
솔샘로177앞(솔샘문화정보센타 2
 
1.0%
월편 2
 
1.0%
도봉로15길17앞 2
 
1.0%
맞은편 2
 
1.0%
한천로105길24(주공204동 2
 
1.0%
삼양로19길25(레미안121동 2
 
1.0%
인수봉로23가길 2
 
1.0%
도봉로78길81앞(터널전기실입구 1
 
0.5%
오패산로176앞(잼스톤타운 1
 
0.5%
오패산로203앞 1
 
0.5%
Other values (186) 186
91.6%
2023-12-13T08:24:17.816166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 175
 
7.6%
1 154
 
6.7%
앞 139
 
6.0%
2 109
 
4.7%
( 101
 
4.4%
) 101
 
4.4%
0 65
 
2.8%
길 62
 
2.7%
3 62
 
2.7%
5 59
 
2.6%
Other values (179) 1274
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1352
58.8%
Decimal Number 687
29.9%
Open Punctuation 101
 
4.4%
Close Punctuation 101
 
4.4%
Uppercase Letter 26
 
1.1%
Dash Punctuation 14
 
0.6%
Space Separator 14
 
0.6%
Other Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 175
 
12.9%
앞 139
 
10.3%
길 62
 
4.6%
봉 45
 
3.3%
삼 37
 
2.7%
도 36
 
2.7%
동 35
 
2.6%
양 30
 
2.2%
한 30
 
2.2%
천 29
 
2.1%
Other values (155) 734
54.3%
Decimal Number
ValueCountFrequency (%)
1 154
22.4%
2 109
15.9%
0 65
9.5%
3 62
9.0%
5 59
 
8.6%
6 53
 
7.7%
9 50
 
7.3%
7 50
 
7.3%
4 48
 
7.0%
8 37
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
A 14
53.8%
S 4
 
15.4%
K 2
 
7.7%
H 2
 
7.7%
N 1
 
3.8%
O 1
 
3.8%
L 1
 
3.8%
G 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 5
83.3%
, 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1352
58.8%
Common 923
40.1%
Latin 26
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 175
 
12.9%
앞 139
 
10.3%
길 62
 
4.6%
봉 45
 
3.3%
삼 37
 
2.7%
도 36
 
2.7%
동 35
 
2.6%
양 30
 
2.2%
한 30
 
2.2%
천 29
 
2.1%
Other values (155) 734
54.3%
Common
ValueCountFrequency (%)
1 154
16.7%
2 109
11.8%
( 101
10.9%
) 101
10.9%
0 65
7.0%
3 62
6.7%
5 59
 
6.4%
6 53
 
5.7%
9 50
 
5.4%
7 50
 
5.4%
Other values (6) 119
12.9%
Latin
ValueCountFrequency (%)
A 14
53.8%
S 4
 
15.4%
K 2
 
7.7%
H 2
 
7.7%
N 1
 
3.8%
O 1
 
3.8%
L 1
 
3.8%
G 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1352
58.8%
ASCII 949
41.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 175
 
12.9%
앞 139
 
10.3%
길 62
 
4.6%
봉 45
 
3.3%
삼 37
 
2.7%
도 36
 
2.7%
동 35
 
2.6%
양 30
 
2.2%
한 30
 
2.2%
천 29
 
2.1%
Other values (155) 734
54.3%
ASCII
ValueCountFrequency (%)
1 154
16.2%
2 109
11.5%
( 101
10.6%
) 101
10.6%
0 65
6.8%
3 62
6.5%
5 59
 
6.2%
6 53
 
5.6%
9 50
 
5.3%
7 50
 
5.3%
Other values (14) 145
15.3%

Interactions

2023-12-13T08:24:16.250914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:24:17.901326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번도로명
순번1.0000.182
도로명0.1821.000
2023-12-13T08:24:17.978724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번도로명
순번1.0000.043
도로명0.0431.000

Missing values

2023-12-13T08:24:16.355710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:24:16.418191image/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

순번도로명분 전 함관리번호주소
01한천로한천로-1한천로105길24(주공204동 건너편)
12"한천로-2한천로897(강북보건소건너편)
23"한천로-3한천로918옆(SK주유소)
34"한천로-4한천로940앞(한성운수건너편)
45"한천로-5한천로982앞(충북사진관)
56"한천로-16한천로991앞(불교만물)
67"한천로-17한천로935앞(북부수도사업소)
78"한천로-18한천로897옆(강북보건소)
89"한천로-19한천로105길24(주공204동)
910삼양로삼양로-1삼양로323앞(부여카센타)
순번도로명분 전 함관리번호주소
179180"불당골길-5레미안201동앞
180181한솔A길한솔A길-1오현로180(한솔A101동 담장옆)
181182보승사길솔매로-1솔매로131앞
182183손병희길손병희길-1삼양로169길78
183184하천길하천길-1도봉로8길62앞
184185대동천길대동천길-1삼양로139길86
185186미양마을미양마을-1솔샘로159(벽산A201동)
186187빨래골길빨래골-1인수봉로23가길 3(SH스카이A)
187188"빨래골-2인수봉로23가길 4(SH스카이A)
188189"빨래골-3인수봉로28가길 27