Overview

Dataset statistics

Number of variables6
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory53.4 B

Variable types

Text3
Numeric1
Categorical1
DateTime1

Dataset

Description대구교통공사의 사업소별 무재해 현황에 대한 데이터로 무재해 개시일자 및 달성예정일, 목표일수, 누계일수 현황 정보를 제공합니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15119031/fileData.do

Alerts

배수 is highly overall correlated with 개시일자High correlation
개시일자 is highly overall correlated with 배수High correlation

Reproduction

Analysis started2024-04-20 17:12:11.055787
Analysis finished2024-04-20 17:12:11.902074
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

담당부서
Text

Distinct15
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size360.0 B
2024-04-21T02:12:12.428451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length6.9310345
Min length2

Characters and Unicode

Total characters201
Distinct characters38
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.4%

Sample

1st row전사
2nd row전사
3rd row종합관제센터
4th row종합관제센터
5th row1고객센터
ValueCountFrequency (%)
전사 2
 
6.9%
종합관제센터 2
 
6.9%
1고객센터 2
 
6.9%
2고객센터 2
 
6.9%
3고객센터 2
 
6.9%
1호선승무사업소 2
 
6.9%
2호선승무사업소 2
 
6.9%
월배차량기지사업소 2
 
6.9%
문양차량기지사업소 2
 
6.9%
경전철차량기지사업소 2
 
6.9%
Other values (5) 9
31.0%
2024-04-21T02:12:13.316982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 21
 
10.4%
업 19
 
9.5%
소 19
 
9.5%
기 13
 
6.5%
전 10
 
5.0%
센 8
 
4.0%
터 8
 
4.0%
지 7
 
3.5%
량 7
 
3.5%
차 7
 
3.5%
Other values (28) 82
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191
95.0%
Decimal Number 10
 
5.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 21
 
11.0%
업 19
 
9.9%
소 19
 
9.9%
기 13
 
6.8%
전 10
 
5.2%
센 8
 
4.2%
터 8
 
4.2%
지 7
 
3.7%
량 7
 
3.7%
차 7
 
3.7%
Other values (25) 72
37.7%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
1 4
40.0%
3 2
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 191
95.0%
Common 10
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 21
 
11.0%
업 19
 
9.9%
소 19
 
9.9%
기 13
 
6.8%
전 10
 
5.2%
센 8
 
4.2%
터 8
 
4.2%
지 7
 
3.7%
량 7
 
3.7%
차 7
 
3.7%
Other values (25) 72
37.7%
Common
ValueCountFrequency (%)
2 4
40.0%
1 4
40.0%
3 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191
95.0%
ASCII 10
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 21
 
11.0%
업 19
 
9.9%
소 19
 
9.9%
기 13
 
6.8%
전 10
 
5.2%
센 8
 
4.2%
터 8
 
4.2%
지 7
 
3.7%
량 7
 
3.7%
차 7
 
3.7%
Other values (25) 72
37.7%
ASCII
ValueCountFrequency (%)
2 4
40.0%
1 4
40.0%
3 2
20.0%

배수
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)37.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5172414
Minimum1
Maximum16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size389.0 B
2024-04-21T02:12:13.539395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median6
Q39
95-th percentile16
Maximum16
Range15
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.261862
Coefficient of variation (CV)0.80737566
Kurtosis-0.67884937
Mean6.5172414
Median Absolute Deviation (MAD)4
Skewness0.83310146
Sum189
Variance27.687192
MonotonicityNot monotonic
2024-04-21T02:12:13.721289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2 5
17.2%
6 4
13.8%
1 4
13.8%
3 3
10.3%
7 3
10.3%
15 3
10.3%
16 3
10.3%
9 1
 
3.4%
10 1
 
3.4%
5 1
 
3.4%
ValueCountFrequency (%)
1 4
13.8%
2 5
17.2%
3 3
10.3%
4 1
 
3.4%
5 1
 
3.4%
6 4
13.8%
7 3
10.3%
9 1
 
3.4%
10 1
 
3.4%
15 3
10.3%
ValueCountFrequency (%)
16 3
10.3%
15 3
10.3%
10 1
 
3.4%
9 1
 
3.4%
7 3
10.3%
6 4
13.8%
5 1
 
3.4%
4 1
 
3.4%
3 3
10.3%
2 5
17.2%

개시일자
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)48.3%
Missing0
Missing (%)0.0%
Memory size360.0 B
2023-02-11
3 
2016-01-04
2 
2005-03-14
2 
2011-06-04
2 
2015-04-23
2 
Other values (9)
18 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-02-11
2nd row2023-02-11
3rd row2016-01-04
4th row2016-01-04
5th row2005-03-14

Common Values

ValueCountFrequency (%)
2023-02-11 3
 
10.3%
2016-01-04 2
 
6.9%
2005-03-14 2
 
6.9%
2011-06-04 2
 
6.9%
2015-04-23 2
 
6.9%
2015-08-19 2
 
6.9%
2015-04-29 2
 
6.9%
2021-11-16 2
 
6.9%
2005-10-18 2
 
6.9%
2021-08-26 2
 
6.9%
Other values (4) 8
27.6%

Length

2024-04-21T02:12:13.935083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-02-11 3
 
10.3%
2016-01-04 2
 
6.9%
2005-03-14 2
 
6.9%
2011-06-04 2
 
6.9%
2015-04-23 2
 
6.9%
2015-08-19 2
 
6.9%
2015-04-29 2
 
6.9%
2021-11-16 2
 
6.9%
2005-10-18 2
 
6.9%
2021-08-26 2
 
6.9%
Other values (4) 8
27.6%

달성예정일
Date

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size360.0 B
Minimum2022-06-10 00:00:00
Maximum2024-08-17 00:00:00
2024-04-21T02:12:14.121733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:12:14.535434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

목표일수
Text

Distinct24
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Memory size360.0 B
2024-04-21T02:12:15.127365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.2758621
Min length3

Characters and Unicode

Total characters124
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)65.5%

Sample

1st row137
2nd row204
3rd row2,700
4th row3,150
5th row6,650
ValueCountFrequency (%)
2,750 2
 
6.9%
3,030 2
 
6.9%
400 2
 
6.9%
800 2
 
6.9%
2,600 2
 
6.9%
6,630 1
 
3.4%
137 1
 
3.4%
6,180 1
 
3.4%
1,290 1
 
3.4%
6,460 1
 
3.4%
Other values (14) 14
48.3%
2024-04-21T02:12:15.971356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40
32.3%
, 18
14.5%
6 12
 
9.7%
3 10
 
8.1%
2 8
 
6.5%
5 8
 
6.5%
4 8
 
6.5%
1 8
 
6.5%
7 7
 
5.6%
8 4
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 106
85.5%
Other Punctuation 18
 
14.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40
37.7%
6 12
 
11.3%
3 10
 
9.4%
2 8
 
7.5%
5 8
 
7.5%
4 8
 
7.5%
1 8
 
7.5%
7 7
 
6.6%
8 4
 
3.8%
9 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 124
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40
32.3%
, 18
14.5%
6 12
 
9.7%
3 10
 
8.1%
2 8
 
6.5%
5 8
 
6.5%
4 8
 
6.5%
1 8
 
6.5%
7 7
 
5.6%
8 4
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 124
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40
32.3%
, 18
14.5%
6 12
 
9.7%
3 10
 
8.1%
2 8
 
6.5%
5 8
 
6.5%
4 8
 
6.5%
1 8
 
6.5%
7 7
 
5.6%
8 4
 
3.2%

누계일수
Text

Distinct26
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size360.0 B
2024-04-21T02:12:16.559963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.2413793
Min length3

Characters and Unicode

Total characters123
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)79.3%

Sample

1st row137
2nd row187
3rd row2,700
4th row2,782
5th row6,650
ValueCountFrequency (%)
2,750 2
 
6.9%
2,600 2
 
6.9%
400 2
 
6.9%
6,180 1
 
3.4%
137 1
 
3.4%
171 1
 
3.4%
1,290 1
 
3.4%
6,336 1
 
3.4%
6,060 1
 
3.4%
464 1
 
3.4%
Other values (16) 16
55.2%
2024-04-21T02:12:17.459311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23
18.7%
, 18
14.6%
6 16
13.0%
2 13
10.6%
4 12
9.8%
1 11
8.9%
7 10
8.1%
3 7
 
5.7%
8 5
 
4.1%
5 4
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 105
85.4%
Other Punctuation 18
 
14.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23
21.9%
6 16
15.2%
2 13
12.4%
4 12
11.4%
1 11
10.5%
7 10
9.5%
3 7
 
6.7%
8 5
 
4.8%
5 4
 
3.8%
9 4
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 123
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23
18.7%
, 18
14.6%
6 16
13.0%
2 13
10.6%
4 12
9.8%
1 11
8.9%
7 10
8.1%
3 7
 
5.7%
8 5
 
4.1%
5 4
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23
18.7%
, 18
14.6%
6 16
13.0%
2 13
10.6%
4 12
9.8%
1 11
8.9%
7 10
8.1%
3 7
 
5.7%
8 5
 
4.1%
5 4
 
3.3%

Interactions

2024-04-21T02:12:11.447037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T02:12:17.668372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
담당부서배수개시일자달성예정일목표일수누계일수
담당부서1.0000.6821.0000.9080.7850.864
배수0.6821.0000.7170.9520.9520.796
개시일자1.0000.7171.0000.8800.6510.810
달성예정일0.9080.9520.8801.0000.9510.944
목표일수0.7850.9520.6510.9511.0001.000
누계일수0.8640.7960.8100.9441.0001.000
2024-04-21T02:12:17.937236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배수개시일자
배수1.0000.641
개시일자0.6411.000

Missing values

2024-04-21T02:12:11.647457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T02:12:11.831674image/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

담당부서배수개시일자달성예정일목표일수누계일수
0전사22023-02-112023-06-27137137
1전사32023-02-112023-09-02204187
2종합관제센터62016-01-042023-05-262,7002,700
3종합관제센터72016-01-042024-08-173,1502,782
41고객센터152005-03-142023-05-286,6506,650
51고객센터162005-03-142024-06-307,0506,714
62고객센터92011-06-042022-08-242,7502,750
72고객센터102011-06-042023-11-184,5504,441
83고객센터52015-04-232022-11-012,7502,750
93고객센터62015-04-232024-05-043,3003,022
담당부서배수개시일자달성예정일목표일수누계일수
19경전철차량기지사업소12021-08-262022-09-29400400
20경전철차량기지사업소22021-08-262023-11-03800705
21시설기계사업소22021-02-202023-03-01740740
22시설기계사업소32021-02-202024-03-051110892
23전기통신사업소12022-04-242023-05-28400400
24전기통신사업소22022-04-242024-06-30800464
25신호전자사업소152006-03-272022-10-286,0606,060
26신호전자사업소162006-03-272023-12-026,4606,336
27경전철기술사업소32018-12-242022-07-051,2901,290
28경전철기술사업소42018-12-242023-09-081,7201,681