Overview

Dataset statistics

Number of variables7
Number of observations184
Missing cells368
Missing cells (%)28.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.6 KiB
Average record size in memory58.7 B

Variable types

Text2
Categorical3
Unsupported2

Dataset

Description경상남도 밀양시 시내버스노선별 배차 현황입니다
Author경상남도 밀양시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15071999

Alerts

기점 is highly overall correlated with 종점High correlation
종점 is highly overall correlated with 기점High correlation
도착시간 has 184 (100.0%) missing valuesMissing
운행시간 has 184 (100.0%) missing valuesMissing
도착시간 is an unsupported type, check if it needs cleaning or further analysisUnsupported
운행시간 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 23:34:01.099450
Analysis finished2023-12-10 23:34:01.506484
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선번호
Text

Distinct178
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-11T08:34:01.764776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.451087
Min length2

Characters and Unicode

Total characters635
Distinct characters83
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)93.5%

Sample

1st row1-2가곡
2nd row1-2금동
3rd row1-2번
4th row1-2부산대
5th row10롯데
ValueCountFrequency (%)
청운 2
 
1.1%
초동공단 2
 
1.1%
1칠성 2
 
1.1%
4-1번 2
 
1.1%
2초동 2
 
1.1%
초동면소 2
 
1.1%
삼랑2 1
 
0.5%
삼랑3-1 1
 
0.5%
1-2가곡 1
 
0.5%
부산대4 1
 
0.5%
Other values (168) 168
91.3%
2023-12-11T08:34:02.225145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 58
 
9.1%
2 42
 
6.6%
4 39
 
6.1%
동 28
 
4.4%
대 28
 
4.4%
- 24
 
3.8%
산 23
 
3.6%
3 19
 
3.0%
성 18
 
2.8%
6 15
 
2.4%
Other values (73) 341
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 408
64.3%
Decimal Number 203
32.0%
Dash Punctuation 24
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 28
 
6.9%
대 28
 
6.9%
산 23
 
5.6%
성 18
 
4.4%
번 15
 
3.7%
곡 15
 
3.7%
부 15
 
3.7%
가 12
 
2.9%
초 10
 
2.5%
금 10
 
2.5%
Other values (62) 234
57.4%
Decimal Number
ValueCountFrequency (%)
1 58
28.6%
2 42
20.7%
4 39
19.2%
3 19
 
9.4%
6 15
 
7.4%
7 14
 
6.9%
5 9
 
4.4%
9 3
 
1.5%
8 2
 
1.0%
0 2
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 408
64.3%
Common 227
35.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 28
 
6.9%
대 28
 
6.9%
산 23
 
5.6%
성 18
 
4.4%
번 15
 
3.7%
곡 15
 
3.7%
부 15
 
3.7%
가 12
 
2.9%
초 10
 
2.5%
금 10
 
2.5%
Other values (62) 234
57.4%
Common
ValueCountFrequency (%)
1 58
25.6%
2 42
18.5%
4 39
17.2%
- 24
10.6%
3 19
 
8.4%
6 15
 
6.6%
7 14
 
6.2%
5 9
 
4.0%
9 3
 
1.3%
8 2
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 408
64.3%
ASCII 227
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 58
25.6%
2 42
18.5%
4 39
17.2%
- 24
10.6%
3 19
 
8.4%
6 15
 
6.6%
7 14
 
6.2%
5 9
 
4.0%
9 3
 
1.3%
8 2
 
0.9%
Hangul
ValueCountFrequency (%)
동 28
 
6.9%
대 28
 
6.9%
산 23
 
5.6%
성 18
 
4.4%
번 15
 
3.7%
곡 15
 
3.7%
부 15
 
3.7%
가 12
 
2.9%
초 10
 
2.5%
금 10
 
2.5%
Other values (62) 234
57.4%

기점
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
밀양역(종점)
73 
시외버스터미널
72 
부산대학교밀양캠퍼스
9 
금동
 
6
삼랑진
 
6
Other values (9)
18 

Length

Max length10
Median length7
Mean length6.5652174
Min length2

Unique

Unique3 ?
Unique (%)1.6%

Sample

1st row밀양역(종점)
2nd row밀양역(종점)
3rd row밀양역(종점)
4th row밀양역(종점)
5th row롯데아파트

Common Values

ValueCountFrequency (%)
밀양역(종점) 73
39.7%
시외버스터미널 72
39.1%
부산대학교밀양캠퍼스 9
 
4.9%
금동 6
 
3.3%
삼랑진 6
 
3.3%
용성 4
 
2.2%
밀양역 3
 
1.6%
롯데아파트 2
 
1.1%
교동행정복지센터 2
 
1.1%
수산정류소종점 2
 
1.1%
Other values (4) 5
 
2.7%

Length

2023-12-11T08:34:02.378817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
밀양역(종점 73
39.7%
시외버스터미널 72
39.1%
부산대학교밀양캠퍼스 9
 
4.9%
금동 6
 
3.3%
삼랑진 6
 
3.3%
용성 4
 
2.2%
밀양역 3
 
1.6%
롯데아파트 2
 
1.1%
교동행정복지센터 2
 
1.1%
수산정류소종점 2
 
1.1%
Other values (4) 5
 
2.7%

종점
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
시외버스터미널
74 
밀양역(종점)
38 
밀양역
31 
가곡주공아파트
8 
부산대학교밀양캠퍼스
 
7
Other values (9)
26 

Length

Max length10
Median length7
Mean length5.9293478
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row멍에실입구
2nd row금동
3rd row밀양역(종점)
4th row부산대학교밀양캠퍼스
5th row시외버스터미널

Common Values

ValueCountFrequency (%)
시외버스터미널 74
40.2%
밀양역(종점) 38
20.7%
밀양역 31
16.8%
가곡주공아파트 8
 
4.3%
부산대학교밀양캠퍼스 7
 
3.8%
용성 5
 
2.7%
멍에실입구 4
 
2.2%
칠성 4
 
2.2%
금동 3
 
1.6%
롯데아파트 3
 
1.6%
Other values (4) 7
 
3.8%

Length

2023-12-11T08:34:02.562258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
시외버스터미널 74
40.2%
밀양역(종점 38
20.7%
밀양역 31
16.8%
가곡주공아파트 8
 
4.3%
부산대학교밀양캠퍼스 7
 
3.8%
용성 5
 
2.7%
멍에실입구 4
 
2.2%
칠성 4
 
2.2%
금동 3
 
1.6%
롯데아파트 3
 
1.6%
Other values (4) 7
 
3.8%

출발시각
Text

Distinct107
Distinct (%)58.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-11T08:34:02.798769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.25
Min length2

Characters and Unicode

Total characters782
Distinct characters20
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

Unique80 ?
Unique (%)43.5%

Sample

1st row16:48
2nd row""
3rd row7:28
4th row8:24
5th row8:00
ValueCountFrequency (%)
43
 
21.6%
공휴일 12
 
6.0%
6:50 5
 
2.5%
6:40 4
 
2.0%
9:00 3
 
1.5%
14:10 3
 
1.5%
15:00 3
 
1.5%
6:30 3
 
1.5%
7:40 3
 
1.5%
6:45 3
 
1.5%
Other values (92) 117
58.8%
2023-12-11T08:34:03.219190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 141
18.0%
0 128
16.4%
1 89
11.4%
" 86
11.0%
5 60
7.7%
6 48
 
6.1%
2 40
 
5.1%
4 35
 
4.5%
8 31
 
4.0%
3 27
 
3.5%
Other values (10) 97
12.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 494
63.2%
Other Punctuation 227
29.0%
Other Letter 46
 
5.9%
Space Separator 15
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 128
25.9%
1 89
18.0%
5 60
12.1%
6 48
 
9.7%
2 40
 
8.1%
4 35
 
7.1%
8 31
 
6.3%
3 27
 
5.5%
7 20
 
4.0%
9 16
 
3.2%
Other Letter
ValueCountFrequency (%)
일 13
28.3%
공 12
26.1%
휴 12
26.1%
학 4
 
8.7%
대 2
 
4.3%
방 2
 
4.3%
시 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
: 141
62.1%
" 86
37.9%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 736
94.1%
Hangul 46
 
5.9%

Most frequent character per script

Common
ValueCountFrequency (%)
: 141
19.2%
0 128
17.4%
1 89
12.1%
" 86
11.7%
5 60
8.2%
6 48
 
6.5%
2 40
 
5.4%
4 35
 
4.8%
8 31
 
4.2%
3 27
 
3.7%
Other values (3) 51
 
6.9%
Hangul
ValueCountFrequency (%)
일 13
28.3%
공 12
26.1%
휴 12
26.1%
학 4
 
8.7%
대 2
 
4.3%
방 2
 
4.3%
시 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 736
94.1%
Hangul 46
 
5.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 141
19.2%
0 128
17.4%
1 89
12.1%
" 86
11.7%
5 60
8.2%
6 48
 
6.5%
2 40
 
5.4%
4 35
 
4.8%
8 31
 
4.2%
3 27
 
3.7%
Other values (3) 51
 
6.9%
Hangul
ValueCountFrequency (%)
일 13
28.3%
공 12
26.1%
휴 12
26.1%
학 4
 
8.7%
대 2
 
4.3%
방 2
 
4.3%
시 1
 
2.2%

도착시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing184
Missing (%)100.0%
Memory size1.7 KiB

운행시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing184
Missing (%)100.0%
Memory size1.7 KiB

운행횟수(1일)
Categorical

Distinct14
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
80 
2
43 
""
25 
3
17 
4
 
7
Other values (9)
12 

Length

Max length2
Median length1
Mean length1.173913
Min length1

Unique

Unique8 ?
Unique (%)4.3%

Sample

1st row1
2nd row""
3rd row13
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 80
43.5%
2 43
23.4%
"" 25
 
13.6%
3 17
 
9.2%
4 7
 
3.8%
6 4
 
2.2%
13 1
 
0.5%
56 1
 
0.5%
16 1
 
0.5%
64 1
 
0.5%
Other values (4) 4
 
2.2%

Length

2023-12-11T08:34:03.364361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 80
43.5%
2 43
23.4%
25
 
13.6%
3 17
 
9.2%
4 7
 
3.8%
6 4
 
2.2%
13 1
 
0.5%
56 1
 
0.5%
16 1
 
0.5%
64 1
 
0.5%
Other values (4) 4
 
2.2%

Correlations

2023-12-11T08:34:03.440858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기점종점운행횟수(1일)
기점1.0000.9270.000
종점0.9271.0000.510
운행횟수(1일)0.0000.5101.000
2023-12-11T08:34:03.525414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운행횟수(1일)종점기점
운행횟수(1일)1.0000.1540.000
종점0.1541.0000.510
기점0.0000.5101.000
2023-12-11T08:34:03.603929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기점종점운행횟수(1일)
기점1.0000.5100.000
종점0.5101.0000.154
운행횟수(1일)0.0000.1541.000

Missing values

2023-12-11T08:34:01.344934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:34:01.458890image/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

노선번호기점종점출발시각도착시간운행시간운행횟수(1일)
01-2가곡밀양역(종점)멍에실입구16:48<NA><NA>1
11-2금동밀양역(종점)금동""<NA><NA>""
21-2번밀양역(종점)밀양역(종점)7:28<NA><NA>13
31-2부산대밀양역(종점)부산대학교밀양캠퍼스8:24<NA><NA>1
410롯데롯데아파트시외버스터미널8:00<NA><NA>1
51가곡밀양역(종점)멍에실입구8:48<NA><NA>2
61금동밀양역(종점)금동""<NA><NA>""
71번밀양역(종점)밀양역(종점)5:45<NA><NA>56
81부산대밀양역(종점)부산대학교밀양캠퍼스8:56<NA><NA>3
91서가정밀양역(종점)밀양역(종점)5:55<NA><NA>2
노선번호기점종점출발시각도착시간운행시간운행횟수(1일)
174초동면소시외버스터미널시외버스터미널8:30<NA><NA>1
175칠성밀양역칠성7:05<NA><NA>1
176칠성1-2칠성밀양역""<NA><NA>1
177칠성2칠성밀양역""<NA><NA>2
178표충사시외버스터미널시외버스터미널공휴일 06:35<NA><NA>1
179표충사1시외버스터미널시외버스터미널6:35<NA><NA>3
180표충사2시외버스터미널시외버스터미널9:10<NA><NA>1
181표충사3시외버스터미널시외버스터미널13:10<NA><NA>2
182해동1밀양역(종점)밀양역(종점)6:50<NA><NA>1
183화봉1밀양역(종점)밀양역(종점)6:21<NA><NA>2