Overview

Dataset statistics

Number of variables4
Number of observations116
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory34.1 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description폐건전지 폐형광등 분리수거함은 관내 행정복지센터나 공동주택내 재활용품 분리배출장소, 학교등에 설치되어 있습니다.폐건전지와 폐형광등은 재활용은 불가하나 환경훼손의 염려가 있는 폐기물이므로 분리배출 및 수거에 적극 협조하여 주시기 바랍니다.
Author대구광역시 서구
URLhttps://www.data.go.kr/data/15041565/fileData.do

Alerts

연번 is highly overall correlated with 동 별 High correlation
동 별 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-29 22:29:20.674391
Analysis finished2024-04-29 22:29:22.101910
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct116
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.5
Minimum1
Maximum116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-30T07:29:22.185562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.75
Q129.75
median58.5
Q387.25
95-th percentile110.25
Maximum116
Range115
Interquartile range (IQR)57.5

Descriptive statistics

Standard deviation33.630343
Coefficient of variation (CV)0.57487767
Kurtosis-1.2
Mean58.5
Median Absolute Deviation (MAD)29
Skewness0
Sum6786
Variance1131
MonotonicityStrictly increasing
2024-04-30T07:29:22.308434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
75 1
 
0.9%
87 1
 
0.9%
86 1
 
0.9%
85 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
Other values (106) 106
91.4%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
116 1
0.9%
115 1
0.9%
114 1
0.9%
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%

동 별
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
상중이동
23 
내당4동
18 
평리4동
12 
내당1동
7 
평리3동
7 
Other values (12)
49 

Length

Max length6
Median length4
Mean length4.0258621
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row내당1동
2nd row내당1동
3rd row내당1동
4th row내당1동
5th row내당1동

Common Values

ValueCountFrequency (%)
상중이동 23
19.8%
내당4동 18
15.5%
평리4동 12
10.3%
내당1동 7
 
6.0%
평리3동 7
 
6.0%
비산4동 7
 
6.0%
원대동 7
 
6.0%
비산5동 5
 
4.3%
평리6동 5
 
4.3%
비산6동 4
 
3.4%
Other values (7) 21
18.1%

Length

2024-04-30T07:29:22.447933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
상중이동 23
19.8%
내당4동 18
15.5%
평리4동 12
10.3%
내당1동 7
 
6.0%
평리3동 7
 
6.0%
비산4동 7
 
6.0%
원대동 7
 
6.0%
평리6동 5
 
4.3%
비산5동 5
 
4.3%
비산6동 4
 
3.4%
Other values (7) 21
18.1%

도로명주소
Text

Distinct112
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-04-30T07:29:22.698910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length18.25
Min length15

Characters and Unicode

Total characters2117
Distinct characters48
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

Unique108 ?
Unique (%)93.1%

Sample

1st row대구광역시 서구 통학로 35
2nd row대구광역시 서구 달구벌대로357길 22
3rd row대구광역시 서구 통학로 46
4th row대구광역시 서구 서대구로8길 49
5th row대구광역시 서구 통학로 39
ValueCountFrequency (%)
대구광역시 116
25.0%
서구 116
25.0%
평리로 9
 
1.9%
국채보상로 8
 
1.7%
국채보상로46길 5
 
1.1%
당산로 5
 
1.1%
국채보상로34길 5
 
1.1%
통학로 5
 
1.1%
35 4
 
0.9%
서대구로3길 4
 
0.9%
Other values (138) 187
40.3%
2024-04-30T07:29:23.128181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
349
16.5%
구 254
12.0%
서 146
 
6.9%
대 139
 
6.6%
광 116
 
5.5%
역 116
 
5.5%
시 116
 
5.5%
로 116
 
5.5%
길 77
 
3.6%
3 64
 
3.0%
Other values (38) 624
29.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1348
63.7%
Decimal Number 411
 
19.4%
Space Separator 349
 
16.5%
Dash Punctuation 9
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 254
18.8%
서 146
10.8%
대 139
10.3%
광 116
8.6%
역 116
8.6%
시 116
8.6%
로 116
8.6%
길 77
 
5.7%
채 33
 
2.4%
보 33
 
2.4%
Other values (26) 202
15.0%
Decimal Number
ValueCountFrequency (%)
3 64
15.6%
1 57
13.9%
6 52
12.7%
2 49
11.9%
5 47
11.4%
7 44
10.7%
4 41
10.0%
0 23
 
5.6%
8 20
 
4.9%
9 14
 
3.4%
Space Separator
ValueCountFrequency (%)
349
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1348
63.7%
Common 769
36.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 254
18.8%
서 146
10.8%
대 139
10.3%
광 116
8.6%
역 116
8.6%
시 116
8.6%
로 116
8.6%
길 77
 
5.7%
채 33
 
2.4%
보 33
 
2.4%
Other values (26) 202
15.0%
Common
ValueCountFrequency (%)
349
45.4%
3 64
 
8.3%
1 57
 
7.4%
6 52
 
6.8%
2 49
 
6.4%
5 47
 
6.1%
7 44
 
5.7%
4 41
 
5.3%
0 23
 
3.0%
8 20
 
2.6%
Other values (2) 23
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1348
63.7%
ASCII 769
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
349
45.4%
3 64
 
8.3%
1 57
 
7.4%
6 52
 
6.8%
2 49
 
6.4%
5 47
 
6.1%
7 44
 
5.7%
4 41
 
5.3%
0 23
 
3.0%
8 20
 
2.6%
Other values (2) 23
 
3.0%
Hangul
ValueCountFrequency (%)
구 254
18.8%
서 146
10.8%
대 139
10.3%
광 116
8.6%
역 116
8.6%
시 116
8.6%
로 116
8.6%
길 77
 
5.7%
채 33
 
2.4%
보 33
 
2.4%
Other values (26) 202
15.0%

건물명
Text

Distinct115
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-04-30T07:29:23.371016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length6.6551724
Min length3

Characters and Unicode

Total characters772
Distinct characters150
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

Unique114 ?
Unique (%)98.3%

Sample

1st row내당1동주민센터
2nd row두류초등학교
3rd row황제맨션
4th row보성홍실(1차)
5th row보성홍실(2차)
ValueCountFrequency (%)
삼익뉴타운 2
 
1.6%
양지아파트 1
 
0.8%
노인복지관 1
 
0.8%
평리1동주민센터 1
 
0.8%
달성초등학교 1
 
0.8%
경일중학교 1
 
0.8%
제일종합사회복지관 1
 
0.8%
삼신아파트 1
 
0.8%
신흥아파트 1
 
0.8%
금류타운 1
 
0.8%
Other values (111) 111
91.0%
2024-04-30T07:29:23.718814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
파 37
 
4.8%
트 36
 
4.7%
아 35
 
4.5%
동 27
 
3.5%
교 27
 
3.5%
학 25
 
3.2%
서 21
 
2.7%
리 20
 
2.6%
등 18
 
2.3%
주 17
 
2.2%
Other values (140) 509
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 695
90.0%
Decimal Number 49
 
6.3%
Other Punctuation 8
 
1.0%
Close Punctuation 6
 
0.8%
Open Punctuation 6
 
0.8%
Space Separator 6
 
0.8%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 37
 
5.3%
트 36
 
5.2%
아 35
 
5.0%
동 27
 
3.9%
교 27
 
3.9%
학 25
 
3.6%
서 21
 
3.0%
리 20
 
2.9%
등 18
 
2.6%
주 17
 
2.4%
Other values (123) 432
62.2%
Decimal Number
ValueCountFrequency (%)
1 15
30.6%
2 12
24.5%
3 6
 
12.2%
6 4
 
8.2%
4 4
 
8.2%
0 3
 
6.1%
7 2
 
4.1%
9 1
 
2.0%
8 1
 
2.0%
5 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 6
75.0%
. 2
 
25.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 695
90.0%
Common 75
 
9.7%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 37
 
5.3%
트 36
 
5.2%
아 35
 
5.0%
동 27
 
3.9%
교 27
 
3.9%
학 25
 
3.6%
서 21
 
3.0%
리 20
 
2.9%
등 18
 
2.6%
주 17
 
2.4%
Other values (123) 432
62.2%
Common
ValueCountFrequency (%)
1 15
20.0%
2 12
16.0%
) 6
 
8.0%
, 6
 
8.0%
( 6
 
8.0%
3 6
 
8.0%
6
 
8.0%
6 4
 
5.3%
4 4
 
5.3%
0 3
 
4.0%
Other values (5) 7
9.3%
Latin
ValueCountFrequency (%)
T 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 695
90.0%
ASCII 77
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
파 37
 
5.3%
트 36
 
5.2%
아 35
 
5.0%
동 27
 
3.9%
교 27
 
3.9%
학 25
 
3.6%
서 21
 
3.0%
리 20
 
2.9%
등 18
 
2.6%
주 17
 
2.4%
Other values (123) 432
62.2%
ASCII
ValueCountFrequency (%)
1 15
19.5%
2 12
15.6%
) 6
 
7.8%
, 6
 
7.8%
( 6
 
7.8%
3 6
 
7.8%
6
 
7.8%
6 4
 
5.2%
4 4
 
5.2%
0 3
 
3.9%
Other values (7) 9
11.7%

Interactions

2024-04-30T07:29:21.776231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:29:23.820223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동 별
연번1.0000.938
동 별0.9381.000
2024-04-30T07:29:23.894329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번동 별
연번1.0000.726
동 별0.7261.000

Missing values

2024-04-30T07:29:21.966257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:29:22.063127image/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

연번동 별도로명주소건물명
01내당1동대구광역시 서구 통학로 35내당1동주민센터
12내당1동대구광역시 서구 달구벌대로357길 22두류초등학교
23내당1동대구광역시 서구 통학로 46황제맨션
34내당1동대구광역시 서구 서대구로8길 49보성홍실(1차)
45내당1동대구광역시 서구 통학로 39보성홍실(2차)
56내당1동대구광역시 서구 서대구로8길 15내당시영아파트
67내당1동대구광역시 서구 달구벌대로365길 3서구종합사회복지관
78내당2.3동대구광역시 서구 큰장로15길 11-1내당2.3동주민센터
89내당2.3동대구광역시 서구 달구벌대로377안길 10보라(제림)아파트
910내당2.3동대구광역시 서구 달서로 33내당천주교회
연번동 별도로명주소건물명
106107평리4동대구광역시 서구 국채보상로46길 63평리반도아파트
107108평리4동대구광역시 서구 국채보상로 200서대구병원
108109평리4동대구광역시 서구 국채보상로50길 20평리푸르지오
109110평리5동대구광역시 서구 국채보상로43길 15폴리텍6대학
110111평리5동대구광역시 서구 국채보상로37길 35이현초등학교
111112평리6동대구광역시 서구 당산로86길 13평리6동주민센터
112113평리6동대구광역시 서구 달서천로 186대구서부소방서
113114평리6동대구광역시 서구 서대구로45길 60서평초등학교
114115평리6동대구광역시 서구 문화로37길 6광명아파트
115116평리6동대구광역시 서구 북비산로 156대구연세요양병원