Overview

Dataset statistics

Number of variables7
Number of observations125
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory59.1 B

Variable types

Numeric2
Categorical3
Text1
DateTime1

Dataset

Description대구광역시 북구의 간선도로 적사함(제설함) 현황 데이터로 행정동명, 설치장소, 적사함수, 관리기관(부서), 관리자 연락처 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15114006/fileData.do

Alerts

관리기관(부서) has constant value ""Constant
데이터 기준일자 has constant value ""Constant
연번 is highly overall correlated with 관리자 연락처High correlation
행정동명 is highly overall correlated with 관리자 연락처High correlation
관리자 연락처 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:20:47.854349
Analysis finished2023-12-12 17:20:48.744873
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct125
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63
Minimum1
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T02:20:48.824374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.2
Q132
median63
Q394
95-th percentile118.8
Maximum125
Range124
Interquartile range (IQR)62

Descriptive statistics

Standard deviation36.228442
Coefficient of variation (CV)0.57505463
Kurtosis-1.2
Mean63
Median Absolute Deviation (MAD)31
Skewness0
Sum7875
Variance1312.5
MonotonicityStrictly increasing
2023-12-13T02:20:48.985745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
80 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
Other values (115) 115
92.0%
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 (%)
125 1
0.8%
124 1
0.8%
123 1
0.8%
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%

행정동명
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
산격2동
11 
읍내동
10 
칠성동
9 
태전1동
 
8
복현2동
 
7
Other values (30)
80 

Length

Max length6
Median length5
Mean length3.64
Min length3

Unique

Unique10 ?
Unique (%)8.0%

Sample

1st row침산3동
2nd row관문동
3rd row고성동
4th row노원12동
5th row노원3동

Common Values

ValueCountFrequency (%)
산격2동 11
 
8.8%
읍내동 10
 
8.0%
칠성동 9
 
7.2%
태전1동 8
 
6.4%
복현2동 7
 
5.6%
매천동 7
 
5.6%
관문동 6
 
4.8%
학정동 5
 
4.0%
태전2동 5
 
4.0%
무태조야동 5
 
4.0%
Other values (25) 52
41.6%

Length

2023-12-13T02:20:49.157781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
산격2동 11
 
8.8%
읍내동 10
 
8.0%
칠성동 9
 
7.2%
태전1동 8
 
6.4%
복현2동 7
 
5.6%
매천동 7
 
5.6%
관문동 6
 
4.8%
학정동 5
 
4.0%
태전2동 5
 
4.0%
무태조야동 5
 
4.0%
Other values (24) 52
41.6%

설치장소
Text

Distinct121
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T02:20:49.403947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length8.608
Min length3

Characters and Unicode

Total characters1076
Distinct characters168
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)93.6%

Sample

1st row대구 북구청
2nd row매천대교하단
3rd row고성네거리
4th row원대오거리
5th row만평네거리
ValueCountFrequency (%)
↔ 20
 
7.8%
양안 17
 
6.7%
입구 6
 
2.4%
좌우측 6
 
2.4%
국우터널 5
 
2.0%
산격대교 5
 
2.0%
지하도 5
 
2.0%
삼거리 4
 
1.6%
복현오거리 4
 
1.6%
앞 4
 
1.6%
Other values (147) 179
70.2%
2023-12-13T02:20:49.856062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
130
 
12.1%
교 50
 
4.6%
대 32
 
3.0%
구 30
 
2.8%
리 29
 
2.7%
거 29
 
2.7%
도 29
 
2.7%
지 22
 
2.0%
우 21
 
2.0%
↔ 21
 
2.0%
Other values (158) 683
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 888
82.5%
Space Separator 130
 
12.1%
Math Symbol 27
 
2.5%
Decimal Number 14
 
1.3%
Uppercase Letter 6
 
0.6%
Other Punctuation 4
 
0.4%
Close Punctuation 3
 
0.3%
Open Punctuation 3
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 50
 
5.6%
대 32
 
3.6%
구 30
 
3.4%
리 29
 
3.3%
거 29
 
3.3%
도 29
 
3.3%
지 22
 
2.5%
우 21
 
2.4%
안 20
 
2.3%
원 18
 
2.0%
Other values (141) 608
68.5%
Decimal Number
ValueCountFrequency (%)
1 4
28.6%
7 2
14.3%
4 2
14.3%
0 2
14.3%
3 2
14.3%
2 1
 
7.1%
5 1
 
7.1%
Math Symbol
ValueCountFrequency (%)
↔ 21
77.8%
~ 6
 
22.2%
Uppercase Letter
ValueCountFrequency (%)
C 3
50.0%
I 3
50.0%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
, 1
 
25.0%
Space Separator
ValueCountFrequency (%)
130
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 888
82.5%
Common 182
 
16.9%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 50
 
5.6%
대 32
 
3.6%
구 30
 
3.4%
리 29
 
3.3%
거 29
 
3.3%
도 29
 
3.3%
지 22
 
2.5%
우 21
 
2.4%
안 20
 
2.3%
원 18
 
2.0%
Other values (141) 608
68.5%
Common
ValueCountFrequency (%)
130
71.4%
↔ 21
 
11.5%
~ 6
 
3.3%
1 4
 
2.2%
. 3
 
1.6%
) 3
 
1.6%
( 3
 
1.6%
7 2
 
1.1%
4 2
 
1.1%
0 2
 
1.1%
Other values (5) 6
 
3.3%
Latin
ValueCountFrequency (%)
C 3
50.0%
I 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 888
82.5%
ASCII 167
 
15.5%
Arrows 21
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
130
77.8%
~ 6
 
3.6%
1 4
 
2.4%
C 3
 
1.8%
. 3
 
1.8%
I 3
 
1.8%
) 3
 
1.8%
( 3
 
1.8%
7 2
 
1.2%
4 2
 
1.2%
Other values (6) 8
 
4.8%
Hangul
ValueCountFrequency (%)
교 50
 
5.6%
대 32
 
3.6%
구 30
 
3.4%
리 29
 
3.3%
거 29
 
3.3%
도 29
 
3.3%
지 22
 
2.5%
우 21
 
2.4%
안 20
 
2.3%
원 18
 
2.0%
Other values (141) 608
68.5%
Arrows
ValueCountFrequency (%)
↔ 21
100.0%

적사함수
Real number (ℝ)

Distinct13
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.584
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T02:20:49.979914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile7.8
Maximum15
Range14
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.6946303
Coefficient of variation (CV)1.0428136
Kurtosis6.9524037
Mean2.584
Median Absolute Deviation (MAD)1
Skewness2.5788775
Sum323
Variance7.2610323
MonotonicityNot monotonic
2023-12-13T02:20:50.107686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 57
45.6%
2 39
31.2%
4 10
 
8.0%
6 5
 
4.0%
7 3
 
2.4%
5 2
 
1.6%
3 2
 
1.6%
12 2
 
1.6%
13 1
 
0.8%
10 1
 
0.8%
Other values (3) 3
 
2.4%
ValueCountFrequency (%)
1 57
45.6%
2 39
31.2%
3 2
 
1.6%
4 10
 
8.0%
5 2
 
1.6%
6 5
 
4.0%
7 3
 
2.4%
8 1
 
0.8%
10 1
 
0.8%
11 1
 
0.8%
ValueCountFrequency (%)
15 1
 
0.8%
13 1
 
0.8%
12 2
 
1.6%
11 1
 
0.8%
10 1
 
0.8%
8 1
 
0.8%
7 3
 
2.4%
6 5
4.0%
5 2
 
1.6%
4 10
8.0%

관리기관(부서)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
건설과/안전총괄과
125 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건설과/안전총괄과
2nd row건설과/안전총괄과
3rd row건설과/안전총괄과
4th row건설과/안전총괄과
5th row건설과/안전총괄과

Common Values

ValueCountFrequency (%)
건설과/안전총괄과 125
100.0%

Length

2023-12-13T02:20:50.224641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:20:50.379716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설과/안전총괄과 125
100.0%

관리자 연락처
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
053-665-2918
76 
053-665-4352
49 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row053-665-4352
2nd row053-665-4352
3rd row053-665-4352
4th row053-665-4352
5th row053-665-4352

Common Values

ValueCountFrequency (%)
053-665-2918 76
60.8%
053-665-4352 49
39.2%

Length

2023-12-13T02:20:50.523243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:20:50.641773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
053-665-2918 76
60.8%
053-665-4352 49
39.2%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2023-05-01 00:00:00
Maximum2023-05-01 00:00:00
2023-12-13T02:20:50.764894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:20:50.890104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T02:20:48.339343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:20:48.122003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:20:48.451658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:20:48.235128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:20:50.966302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동명적사함수관리자 연락처
연번1.0000.8630.5581.000
행정동명0.8631.0000.4440.796
적사함수0.5580.4441.0000.000
관리자 연락처1.0000.7960.0001.000
2023-12-13T02:20:51.064985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리자 연락처행정동명
관리자 연락처1.0000.597
행정동명0.5971.000
2023-12-13T02:20:51.158805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번적사함수행정동명관리자 연락처
연번1.0000.0820.4510.951
적사함수0.0821.0000.1990.066
행정동명0.4510.1991.0000.597
관리자 연락처0.9510.0660.5971.000

Missing values

2023-12-13T02:20:48.586625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:20:48.701007image/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

연번행정동명설치장소적사함수관리기관(부서)관리자 연락처데이터 기준일자
01침산3동대구 북구청1건설과/안전총괄과053-665-43522023-05-01
12관문동매천대교하단1건설과/안전총괄과053-665-43522023-05-01
23고성동고성네거리1건설과/안전총괄과053-665-43522023-05-01
34노원12동원대오거리1건설과/안전총괄과053-665-43522023-05-01
45노원3동만평네거리1건설과/안전총괄과053-665-43522023-05-01
56노원3동노원네거리1건설과/안전총괄과053-665-43522023-05-01
67침산1동오봉네거리1건설과/안전총괄과053-665-43522023-05-01
78침산3동침산네거리1건설과/안전총괄과053-665-43522023-05-01
89칠성동남침산네거리1건설과/안전총괄과053-665-43522023-05-01
910침산2동동침산네거리1건설과/안전총괄과053-665-43522023-05-01
연번행정동명설치장소적사함수관리기관(부서)관리자 연락처데이터 기준일자
115116국우동국우터널 입구4건설과/안전총괄과053-665-29182023-05-01
116117서변동국우터널 입구6건설과/안전총괄과053-665-29182023-05-01
117118금호동금호택지12건설과/안전총괄과053-665-29182023-05-01
118119산격4동산격동 1437-1171건설과/안전총괄과053-665-29182023-05-01
119120산격2동청소년회관4건설과/안전총괄과053-665-29182023-05-01
120121침산3동북구청 일원7건설과/안전총괄과053-665-29182023-05-01
121122침산2,3동성북로2건설과/안전총괄과053-665-29182023-05-01
122123노원동노원공영주차장4건설과/안전총괄과053-665-29182023-05-01
123124산격2동대불공원~신기공원11건설과/안전총괄과053-665-29182023-05-01
124125복현2동복현로 140 일원7건설과/안전총괄과053-665-29182023-05-01