Overview

Dataset statistics

Number of variables8
Number of observations107
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory67.2 B

Variable types

Numeric2
Text3
Categorical3

Dataset

Description빛가람정보포탈에서 제공중인 버스 노선번호 및 배차간격
Author한전KDN(주)
URLhttps://www.data.go.kr/data/15038335/fileData.do

Alerts

첫차시간 is highly overall correlated with 배차간격High correlation
배차간격 is highly overall correlated with 첫차시간High correlation
리스트번호 has unique valuesUnique
노선번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:38:00.193183
Analysis finished2023-12-12 15:38:01.564098
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

리스트번호
Real number (ℝ)

UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54
Minimum1
Maximum107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T00:38:01.653616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.3
Q127.5
median54
Q380.5
95-th percentile101.7
Maximum107
Range106
Interquartile range (IQR)53

Descriptive statistics

Standard deviation31.032241
Coefficient of variation (CV)0.57467114
Kurtosis-1.2
Mean54
Median Absolute Deviation (MAD)27
Skewness0
Sum5778
Variance963
MonotonicityStrictly increasing
2023-12-13T00:38:01.817696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
69 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
73 1
 
0.9%
Other values (97) 97
90.7%
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 (%)
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%
98 1
0.9%

노선번호
Real number (ℝ)

UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.46729
Minimum1
Maximum224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T00:38:02.373151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.3
Q131.5
median61
Q389.5
95-th percentile170.1
Maximum224
Range223
Interquartile range (IQR)58

Descriptive statistics

Standard deviation46.624011
Coefficient of variation (CV)0.71217262
Kurtosis2.3902238
Mean65.46729
Median Absolute Deviation (MAD)29
Skewness1.3010122
Sum7005
Variance2173.7984
MonotonicityNot monotonic
2023-12-13T00:38:02.606975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
112 1
 
0.9%
58 1
 
0.9%
69 1
 
0.9%
68 1
 
0.9%
93 1
 
0.9%
66 1
 
0.9%
65 1
 
0.9%
64 1
 
0.9%
94 1
 
0.9%
62 1
 
0.9%
Other values (97) 97
90.7%
ValueCountFrequency (%)
1 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%
11 1
0.9%
ValueCountFrequency (%)
224 1
0.9%
206 1
0.9%
203 1
0.9%
202 1
0.9%
201 1
0.9%
195 1
0.9%
112 1
0.9%
111 1
0.9%
109 1
0.9%
108 1
0.9%

노선이름
Text

Distinct105
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-13T00:38:03.038596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.317757
Min length3

Characters and Unicode

Total characters462
Distinct characters58
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)96.3%

Sample

1st row순환01(운천저수지)
2nd row순환01(시청)
3rd row좌석02
4th row풍암06
5th row진월07
ValueCountFrequency (%)
송정19 2
 
1.9%
두암81 2
 
1.9%
송암73 1
 
0.9%
순환01(운천저수지 1
 
0.9%
송정98 1
 
0.9%
송정97 1
 
0.9%
송정96 1
 
0.9%
첨단95 1
 
0.9%
첨단94 1
 
0.9%
송정93 1
 
0.9%
Other values (95) 95
88.8%
2023-12-13T00:38:03.630724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 44
 
9.5%
0 31
 
6.7%
7 31
 
6.7%
9 28
 
6.1%
8 23
 
5.0%
5 21
 
4.5%
2 21
 
4.5%
송 19
 
4.1%
6 18
 
3.9%
3 14
 
3.0%
Other values (48) 212
45.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 244
52.8%
Other Letter 213
46.1%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
송 19
 
8.9%
암 13
 
6.1%
정 13
 
6.1%
곡 9
 
4.2%
단 9
 
4.2%
첨 9
 
4.2%
지 8
 
3.8%
원 7
 
3.3%
월 7
 
3.3%
진 7
 
3.3%
Other values (35) 112
52.6%
Decimal Number
ValueCountFrequency (%)
1 44
18.0%
0 31
12.7%
7 31
12.7%
9 28
11.5%
8 23
9.4%
5 21
8.6%
2 21
8.6%
6 18
7.4%
3 14
 
5.7%
4 13
 
5.3%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 249
53.9%
Hangul 213
46.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
송 19
 
8.9%
암 13
 
6.1%
정 13
 
6.1%
곡 9
 
4.2%
단 9
 
4.2%
첨 9
 
4.2%
지 8
 
3.8%
원 7
 
3.3%
월 7
 
3.3%
진 7
 
3.3%
Other values (35) 112
52.6%
Common
ValueCountFrequency (%)
1 44
17.7%
0 31
12.4%
7 31
12.4%
9 28
11.2%
8 23
9.2%
5 21
8.4%
2 21
8.4%
6 18
7.2%
3 14
 
5.6%
4 13
 
5.2%
Other values (3) 5
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 249
53.9%
Hangul 213
46.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 44
17.7%
0 31
12.4%
7 31
12.4%
9 28
11.2%
8 23
9.2%
5 21
8.4%
2 21
8.4%
6 18
7.2%
3 14
 
5.6%
4 13
 
5.2%
Other values (3) 5
 
2.0%
Hangul
ValueCountFrequency (%)
송 19
 
8.9%
암 13
 
6.1%
정 13
 
6.1%
곡 9
 
4.2%
단 9
 
4.2%
첨 9
 
4.2%
지 8
 
3.8%
원 7
 
3.3%
월 7
 
3.3%
진 7
 
3.3%
Other values (35) 112
52.6%

기점(정류소명칭)
Text

Distinct64
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-13T00:38:03.913982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.0747664
Min length2

Characters and Unicode

Total characters436
Distinct characters126
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)42.1%

Sample

1st row세하동
2nd row세하동
3rd row혁신도시
4th row장등동
5th row살레시오고
ValueCountFrequency (%)
장등동 10
 
9.3%
도산동 6
 
5.6%
살레시오고 4
 
3.7%
하남2지구 4
 
3.7%
문화전당역 4
 
3.7%
무등산국립공원 3
 
2.8%
양동시장 3
 
2.8%
매월동 3
 
2.8%
서광주역 3
 
2.8%
상무지구 3
 
2.8%
Other values (54) 64
59.8%
2023-12-13T00:38:04.386658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 33
 
7.6%
산 18
 
4.1%
장 17
 
3.9%
지 17
 
3.9%
등 14
 
3.2%
구 14
 
3.2%
광 11
 
2.5%
시 10
 
2.3%
원 10
 
2.3%
무 9
 
2.1%
Other values (116) 283
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 421
96.6%
Decimal Number 8
 
1.8%
Uppercase Letter 3
 
0.7%
Open Punctuation 2
 
0.5%
Close Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 33
 
7.8%
산 18
 
4.3%
장 17
 
4.0%
지 17
 
4.0%
등 14
 
3.3%
구 14
 
3.3%
광 11
 
2.6%
시 10
 
2.4%
원 10
 
2.4%
무 9
 
2.1%
Other values (109) 268
63.7%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
S 1
33.3%
K 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 6
75.0%
1 2
 
25.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 421
96.6%
Common 12
 
2.8%
Latin 3
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 33
 
7.8%
산 18
 
4.3%
장 17
 
4.0%
지 17
 
4.0%
등 14
 
3.3%
구 14
 
3.3%
광 11
 
2.6%
시 10
 
2.4%
원 10
 
2.4%
무 9
 
2.1%
Other values (109) 268
63.7%
Common
ValueCountFrequency (%)
2 6
50.0%
1 2
 
16.7%
( 2
 
16.7%
) 2
 
16.7%
Latin
ValueCountFrequency (%)
A 1
33.3%
S 1
33.3%
K 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 421
96.6%
ASCII 15
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 33
 
7.8%
산 18
 
4.3%
장 17
 
4.0%
지 17
 
4.0%
등 14
 
3.3%
구 14
 
3.3%
광 11
 
2.6%
시 10
 
2.4%
원 10
 
2.4%
무 9
 
2.1%
Other values (109) 268
63.7%
ASCII
ValueCountFrequency (%)
2 6
40.0%
1 2
 
13.3%
( 2
 
13.3%
) 2
 
13.3%
A 1
 
6.7%
S 1
 
6.7%
K 1
 
6.7%

종점(정류소명칭)
Text

Distinct58
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-13T00:38:04.665331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length3.6542056
Min length2

Characters and Unicode

Total characters391
Distinct characters107
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)39.3%

Sample

1st row세하동
2nd row세하동
3rd row무등산국립공원(증심사)
4th row매월동
5th row송암공단
ValueCountFrequency (%)
장등동 10
 
9.3%
도산동 7
 
6.5%
송암공단 6
 
5.6%
첨단 5
 
4.7%
월남동 5
 
4.7%
세하동 4
 
3.7%
상무지구 4
 
3.7%
첨단지구 4
 
3.7%
무등산국립공원 3
 
2.8%
대창운수 3
 
2.8%
Other values (48) 56
52.3%
2023-12-13T00:38:05.126406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 35
 
9.0%
산 19
 
4.9%
공 16
 
4.1%
단 16
 
4.1%
등 16
 
4.1%
장 12
 
3.1%
지 12
 
3.1%
구 11
 
2.8%
남 11
 
2.8%
무 10
 
2.6%
Other values (97) 233
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 385
98.5%
Open Punctuation 2
 
0.5%
Close Punctuation 2
 
0.5%
Decimal Number 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 35
 
9.1%
산 19
 
4.9%
공 16
 
4.2%
단 16
 
4.2%
등 16
 
4.2%
장 12
 
3.1%
지 12
 
3.1%
구 11
 
2.9%
남 11
 
2.9%
무 10
 
2.6%
Other values (93) 227
59.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 385
98.5%
Common 6
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 35
 
9.1%
산 19
 
4.9%
공 16
 
4.2%
단 16
 
4.2%
등 16
 
4.2%
장 12
 
3.1%
지 12
 
3.1%
구 11
 
2.9%
남 11
 
2.9%
무 10
 
2.6%
Other values (93) 227
59.0%
Common
ValueCountFrequency (%)
( 2
33.3%
) 2
33.3%
2 1
16.7%
. 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 385
98.5%
ASCII 6
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 35
 
9.1%
산 19
 
4.9%
공 16
 
4.2%
단 16
 
4.2%
등 16
 
4.2%
장 12
 
3.1%
지 12
 
3.1%
구 11
 
2.9%
남 11
 
2.9%
무 10
 
2.6%
Other values (93) 227
59.0%
ASCII
ValueCountFrequency (%)
( 2
33.3%
) 2
33.3%
2 1
16.7%
. 1
16.7%

첫차시간
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size988.0 B
06:00
47 
05:40
38 
06:20
8 
06:10
7 
06:30
5 
Other values (2)
 
2

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st row05:40
2nd row05:40
3rd row05:40
4th row05:40
5th row05:40

Common Values

ValueCountFrequency (%)
06:00 47
43.9%
05:40 38
35.5%
06:20 8
 
7.5%
06:10 7
 
6.5%
06:30 5
 
4.7%
05:38 1
 
0.9%
06:35 1
 
0.9%

Length

2023-12-13T00:38:05.297385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:38:05.448440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
06:00 47
43.9%
05:40 38
35.5%
06:20 8
 
7.5%
06:10 7
 
6.5%
06:30 5
 
4.7%
05:38 1
 
0.9%
06:35 1
 
0.9%

막차시간
Categorical

Distinct25
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size988.0 B
22:30
21 
22:20
13 
22:40
12 
22:00
8 
22:35
7 
Other values (20)
46 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique9 ?
Unique (%)8.4%

Sample

1st row22:10
2nd row22:10
3rd row23:59
4th row22:55
5th row22:50

Common Values

ValueCountFrequency (%)
22:30 21
19.6%
22:20 13
12.1%
22:40 12
11.2%
22:00 8
 
7.5%
22:35 7
 
6.5%
22:10 6
 
5.6%
22:25 4
 
3.7%
22:50 4
 
3.7%
22:45 4
 
3.7%
23:00 4
 
3.7%
Other values (15) 24
22.4%

Length

2023-12-13T00:38:05.623256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
22:30 21
19.6%
22:20 13
12.1%
22:40 12
11.2%
22:00 8
 
7.5%
22:35 7
 
6.5%
22:10 6
 
5.6%
22:25 4
 
3.7%
22:50 4
 
3.7%
22:45 4
 
3.7%
23:00 4
 
3.7%
Other values (15) 24
22.4%

배차간격
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Memory size988.0 B
0:15
9 
0:20
8 
0:25
 
7
0:12
 
6
0:09
 
6
Other values (35)
71 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique19 ?
Unique (%)17.8%

Sample

1st row0:12
2nd row0:12
3rd row0:08
4th row0:08
5th row0:06

Common Values

ValueCountFrequency (%)
0:15 9
 
8.4%
0:20 8
 
7.5%
0:25 7
 
6.5%
0:12 6
 
5.6%
0:09 6
 
5.6%
0:30 6
 
5.6%
0:16 6
 
5.6%
0:13 5
 
4.7%
0:10 5
 
4.7%
0:08 5
 
4.7%
Other values (30) 44
41.1%

Length

2023-12-13T00:38:05.792760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0:15 9
 
8.4%
0:20 8
 
7.5%
0:25 7
 
6.5%
0:12 6
 
5.6%
0:09 6
 
5.6%
0:30 6
 
5.6%
0:16 6
 
5.6%
0:13 5
 
4.7%
0:10 5
 
4.7%
0:08 5
 
4.7%
Other values (30) 44
41.1%

Interactions

2023-12-13T00:38:01.107830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:38:00.894555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:38:01.203730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:38:01.010893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:38:05.911873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
리스트번호노선번호기점(정류소명칭)종점(정류소명칭)첫차시간막차시간배차간격
리스트번호1.0000.8330.6330.5980.5510.5030.727
노선번호0.8331.0000.7980.8890.7780.4630.638
기점(정류소명칭)0.6330.7981.0000.9100.9420.8400.946
종점(정류소명칭)0.5980.8890.9101.0000.9440.8360.936
첫차시간0.5510.7780.9420.9441.0000.8050.914
막차시간0.5030.4630.8400.8360.8051.0000.873
배차간격0.7270.6380.9460.9360.9140.8731.000
2023-12-13T00:38:06.081794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배차간격첫차시간막차시간
배차간격1.0000.5520.342
첫차시간0.5521.0000.457
막차시간0.3420.4571.000
2023-12-13T00:38:06.214828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
리스트번호노선번호첫차시간막차시간배차간격
리스트번호1.0000.4680.3120.1790.262
노선번호0.4681.0000.3730.1910.257
첫차시간0.3120.3731.0000.4570.552
막차시간0.1790.1910.4571.0000.342
배차간격0.2620.2570.5520.3421.000

Missing values

2023-12-13T00:38:01.363342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:38:01.505923image/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

리스트번호노선번호노선이름기점(정류소명칭)종점(정류소명칭)첫차시간막차시간배차간격
01112순환01(운천저수지)세하동세하동05:4022:100:12
121순환01(시청)세하동세하동05:4022:100:12
23109좌석02혁신도시무등산국립공원(증심사)05:4023:590:08
343풍암06장등동매월동05:4022:550:08
454진월07살레시오고송암공단05:4022:500:06
565첨단09무등산국립공첨단05:4022:350:05
6796일곡10하남2지구살레시오고06:0022:350:12
7899수완11진흥고도산동06:0022:300:25
89102수완12하남2지구무등산국립공06:0022:250:15
9106지원15태령월남동05:4022:500:15
리스트번호노선번호노선이름기점(정류소명칭)종점(정류소명칭)첫차시간막차시간배차간격
979885송정296동림마을도산동06:1021:401:05
989931419조선대해오름관살레시오고06:0022:300:25
9910086518효령노인복지상무지구06:0022:150:25
100101871187광천동무등산국립공원06:2022:000:20
1011022241000장원초교공항05:4022:000:15
102103203마을700첨단과학산업단지평동우체국05:3822:150:12
103104202마을701수완중석봉운수차고06:3021:502:00
104105195마을720하남2지구응암공원05:4022:000:10
105106206마을720-1호남대입구봉정06:3517:552:40
106107201마을760풍암SK뷰발산교남06:3022:300:11