Overview

Dataset statistics

Number of variables4
Number of observations121
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory34.1 B

Variable types

Numeric1
Categorical2
Text1

Dataset

Description대전광역시 서구 관내 인도 및 도로변 등에 설치된 공공쓰레기통 현황(시군구명, 구분명, 소재지주소)에 대한 데이터입니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15087542/fileData.do

Alerts

시군구명 has constant value ""Constant
구분명 has constant value ""Constant
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:05:19.980054
Analysis finished2023-12-12 18:05:20.376133
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61
Minimum1
Maximum121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T03:05:20.448347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q131
median61
Q391
95-th percentile115
Maximum121
Range120
Interquartile range (IQR)60

Descriptive statistics

Standard deviation35.073732
Coefficient of variation (CV)0.57497921
Kurtosis-1.2
Mean61
Median Absolute Deviation (MAD)30
Skewness0
Sum7381
Variance1230.1667
MonotonicityStrictly increasing
2023-12-13T03:05:20.602662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
92 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
Other values (111) 111
91.7%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
대전광역시 서구
121 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대전광역시 서구
2nd row대전광역시 서구
3rd row대전광역시 서구
4th row대전광역시 서구
5th row대전광역시 서구

Common Values

ValueCountFrequency (%)
대전광역시 서구 121
100.0%

Length

2023-12-13T03:05:20.743094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:20.830842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 121
50.0%
서구 121
50.0%

구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
서구청 쓰레기통
121 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서구청 쓰레기통
2nd row서구청 쓰레기통
3rd row서구청 쓰레기통
4th row서구청 쓰레기통
5th row서구청 쓰레기통

Common Values

ValueCountFrequency (%)
서구청 쓰레기통 121
100.0%

Length

2023-12-13T03:05:20.917224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:05:21.010441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구청 121
50.0%
쓰레기통 121
50.0%
Distinct120
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T03:05:21.266180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length25
Mean length20.694215
Min length15

Characters and Unicode

Total characters2504
Distinct characters156
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)98.3%

Sample

1st row대전광역시 서구 둔산서로105
2nd row대전광역시 서구 괴정동135-2
3rd row대전광역시 서구 용문동256-31
4th row대전광역시 서구 용문동259-1
5th row대전광역시 서구 내동167(서우@201동 앞)
ValueCountFrequency (%)
대전광역시 121
24.1%
서구 121
24.1%
둔산동 27
 
5.4%
승강장 19
 
3.8%
19
 
3.8%
10
 
2.0%
탄방동 7
 
1.4%
관저2동 7
 
1.4%
만년동 5
 
1.0%
가장동 5
 
1.0%
Other values (141) 162
32.2%
2023-12-13T03:05:21.792192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
382
 
15.3%
135
 
5.4%
130
 
5.2%
130
 
5.2%
128
 
5.1%
125
 
5.0%
122
 
4.9%
122
 
4.9%
121
 
4.8%
1 81
 
3.2%
Other values (146) 1028
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1684
67.3%
Space Separator 382
 
15.3%
Decimal Number 326
 
13.0%
Dash Punctuation 32
 
1.3%
Close Punctuation 29
 
1.2%
Open Punctuation 29
 
1.2%
Other Punctuation 22
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
135
 
8.0%
130
 
7.7%
130
 
7.7%
128
 
7.6%
125
 
7.4%
122
 
7.2%
122
 
7.2%
121
 
7.2%
44
 
2.6%
42
 
2.5%
Other values (131) 585
34.7%
Decimal Number
ValueCountFrequency (%)
1 81
24.8%
2 51
15.6%
4 33
10.1%
3 33
10.1%
5 30
 
9.2%
0 28
 
8.6%
6 26
 
8.0%
9 20
 
6.1%
8 14
 
4.3%
7 10
 
3.1%
Space Separator
ValueCountFrequency (%)
382
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1684
67.3%
Common 820
32.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
135
 
8.0%
130
 
7.7%
130
 
7.7%
128
 
7.6%
125
 
7.4%
122
 
7.2%
122
 
7.2%
121
 
7.2%
44
 
2.6%
42
 
2.5%
Other values (131) 585
34.7%
Common
ValueCountFrequency (%)
382
46.6%
1 81
 
9.9%
2 51
 
6.2%
4 33
 
4.0%
3 33
 
4.0%
- 32
 
3.9%
5 30
 
3.7%
) 29
 
3.5%
( 29
 
3.5%
0 28
 
3.4%
Other values (5) 92
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1684
67.3%
ASCII 820
32.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
382
46.6%
1 81
 
9.9%
2 51
 
6.2%
4 33
 
4.0%
3 33
 
4.0%
- 32
 
3.9%
5 30
 
3.7%
) 29
 
3.5%
( 29
 
3.5%
0 28
 
3.4%
Other values (5) 92
 
11.2%
Hangul
ValueCountFrequency (%)
135
 
8.0%
130
 
7.7%
130
 
7.7%
128
 
7.6%
125
 
7.4%
122
 
7.2%
122
 
7.2%
121
 
7.2%
44
 
2.6%
42
 
2.5%
Other values (131) 585
34.7%

Interactions

2023-12-13T03:05:20.164864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T03:05:20.264009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:05:20.342744image/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

순번시군구명구분명소재지주소
01대전광역시 서구서구청 쓰레기통대전광역시 서구 둔산서로105
12대전광역시 서구서구청 쓰레기통대전광역시 서구 괴정동135-2
23대전광역시 서구서구청 쓰레기통대전광역시 서구 용문동256-31
34대전광역시 서구서구청 쓰레기통대전광역시 서구 용문동259-1
45대전광역시 서구서구청 쓰레기통대전광역시 서구 내동167(서우@201동 앞)
56대전광역시 서구서구청 쓰레기통대전광역시 서구 괴정동3-3
67대전광역시 서구서구청 쓰레기통대전광역시 서구 탄방동514-387
78대전광역시 서구서구청 쓰레기통대전광역시 서구 용문동 276-6(농협앞)
89대전광역시 서구서구청 쓰레기통대전광역시 서구 용문동594-6(승강장)
910대전광역시 서구서구청 쓰레기통대전광역시 서구 변동오거리(승강장)
순번시군구명구분명소재지주소
111112대전광역시 서구서구청 쓰레기통대전광역시 서구 둔산동1171
112113대전광역시 서구서구청 쓰레기통대전광역시 서구 둔산동 보라@삼거리승강장
113114대전광역시 서구서구청 쓰레기통대전광역시 서구 둔산동 1820
114115대전광역시 서구서구청 쓰레기통대전광역시 서구 둔산동 청솔상가 앞
115116대전광역시 서구서구청 쓰레기통대전광역시 서구 둔산동 문정초교 정문
116117대전광역시 서구서구청 쓰레기통대전광역시 서구 만년동 테크노월드 승강장
117118대전광역시 서구서구청 쓰레기통대전광역시 서구 만년동 청소터미널 승강장
118119대전광역시 서구서구청 쓰레기통대전광역시 서구 만년동 평송수련원 앞 승강장
119120대전광역시 서구서구청 쓰레기통대전광역시 서구 만년동 예술의전당 앞 승강장
120121대전광역시 서구서구청 쓰레기통대전광역시 서구 만년동 시립미술관 앞 승강장