Overview

Dataset statistics

Number of variables7
Number of observations159
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory60.8 B

Variable types

Numeric4
Categorical2
DateTime1

Dataset

Description충청남도 천안시 시내버스운수업체별 노선 현황에 대한 데이터로 노선번호, 운수업체명, 1회운행거리(km, 편도기준) 등의 항목을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=334&beforeMenuCd=DOM_000000201001001000&publicdatapk=15085744

Alerts

데이터기준일자 has constant value ""Constant
운수업체명 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
비고 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
연번 is highly overall correlated with 노선번호 and 2 other fieldsHigh correlation
노선번호 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
1일운행횟수(회_편도기준) is highly overall correlated with 비고High correlation
연번 has unique valuesUnique
노선번호 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:08:44.346436
Analysis finished2024-01-09 20:08:46.699843
Duration2.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct159
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80
Minimum1
Maximum159
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-10T05:08:46.796217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.9
Q140.5
median80
Q3119.5
95-th percentile151.1
Maximum159
Range158
Interquartile range (IQR)79

Descriptive statistics

Standard deviation46.043458
Coefficient of variation (CV)0.57554322
Kurtosis-1.2
Mean80
Median Absolute Deviation (MAD)40
Skewness0
Sum12720
Variance2120
MonotonicityStrictly increasing
2024-01-10T05:08:46.994351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
2 1
 
0.6%
103 1
 
0.6%
104 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
Other values (149) 149
93.7%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
159 1
0.6%
158 1
0.6%
157 1
0.6%
156 1
0.6%
155 1
0.6%
154 1
0.6%
153 1
0.6%
152 1
0.6%
151 1
0.6%
150 1
0.6%

노선번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct159
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean321.38365
Minimum1
Maximum960
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-10T05:08:47.188555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.9
Q1104.5
median234
Q3505
95-th percentile831
Maximum960
Range959
Interquartile range (IQR)400.5

Descriptive statistics

Standard deviation257.70336
Coefficient of variation (CV)0.80185586
Kurtosis-0.7071926
Mean321.38365
Median Absolute Deviation (MAD)176
Skewness0.63577383
Sum51100
Variance66411.023
MonotonicityNot monotonic
2024-01-10T05:08:47.369982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
2 1
 
0.6%
413 1
 
0.6%
414 1
 
0.6%
420 1
 
0.6%
421 1
 
0.6%
430 1
 
0.6%
431 1
 
0.6%
450 1
 
0.6%
451 1
 
0.6%
Other values (149) 149
93.7%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
5 1
0.6%
7 1
0.6%
9 1
0.6%
10 1
0.6%
11 1
0.6%
12 1
0.6%
13 1
0.6%
ValueCountFrequency (%)
960 1
0.6%
931 1
0.6%
910 1
0.6%
900 1
0.6%
870 1
0.6%
860 1
0.6%
850 1
0.6%
840 1
0.6%
830 1
0.6%
800 1
0.6%

운수업체명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
보성,삼안,새천안
133 
보성,삼안
26 

Length

Max length9
Median length9
Mean length8.3459119
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row보성,삼안,새천안
2nd row보성,삼안,새천안
3rd row보성,삼안,새천안
4th row보성,삼안,새천안
5th row보성,삼안,새천안

Common Values

ValueCountFrequency (%)
보성,삼안,새천안 133
83.6%
보성,삼안 26
 
16.4%

Length

2024-01-10T05:08:47.543011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:08:47.682362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보성,삼안,새천안 133
83.6%
보성,삼안 26
 
16.4%

1회운행거리(km_편도기준)
Real number (ℝ)

Distinct118
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.573333
Minimum3
Maximum43.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-10T05:08:47.831607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4.99
Q110.9
median16.7
Q324.05
95-th percentile32.06
Maximum43.2
Range40.2
Interquartile range (IQR)13.15

Descriptive statistics

Standard deviation8.817467
Coefficient of variation (CV)0.50175268
Kurtosis-0.11801094
Mean17.573333
Median Absolute Deviation (MAD)7
Skewness0.51231149
Sum2794.16
Variance77.747725
MonotonicityNot monotonic
2024-01-10T05:08:47.991997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.8 4
 
2.5%
25.2 3
 
1.9%
20.3 3
 
1.9%
16.5 3
 
1.9%
13.9 3
 
1.9%
15.3 3
 
1.9%
21.3 2
 
1.3%
24.2 2
 
1.3%
14.1 2
 
1.3%
13.1 2
 
1.3%
Other values (108) 132
83.0%
ValueCountFrequency (%)
3.0 1
0.6%
3.8 2
1.3%
4.0 1
0.6%
4.3 1
0.6%
4.5 1
0.6%
4.6 1
0.6%
4.9 1
0.6%
5.0 1
0.6%
5.3 1
0.6%
5.7 1
0.6%
ValueCountFrequency (%)
43.2 1
0.6%
40.5 1
0.6%
40.4 1
0.6%
40.0 1
0.6%
39.6 1
0.6%
35.4 1
0.6%
34.0 1
0.6%
32.6 1
0.6%
32.0 1
0.6%
31.9 1
0.6%

1일운행횟수(회_편도기준)
Real number (ℝ)

HIGH CORRELATION 

Distinct49
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.062893
Minimum1
Maximum172
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-10T05:08:48.566577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median10
Q322
95-th percentile102
Maximum172
Range171
Interquartile range (IQR)16

Descriptive statistics

Standard deviation33.546809
Coefficient of variation (CV)1.3941303
Kurtosis4.8655991
Mean24.062893
Median Absolute Deviation (MAD)6
Skewness2.2658704
Sum3826
Variance1125.3884
MonotonicityNot monotonic
2024-01-10T05:08:48.729738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
6 19
 
11.9%
1 15
 
9.4%
10 15
 
9.4%
4 10
 
6.3%
2 9
 
5.7%
14 9
 
5.7%
12 8
 
5.0%
8 7
 
4.4%
18 6
 
3.8%
13 5
 
3.1%
Other values (39) 56
35.2%
ValueCountFrequency (%)
1 15
9.4%
2 9
5.7%
4 10
6.3%
5 2
 
1.3%
6 19
11.9%
7 2
 
1.3%
8 7
 
4.4%
9 1
 
0.6%
10 15
9.4%
11 1
 
0.6%
ValueCountFrequency (%)
172 1
0.6%
155 1
0.6%
143 1
0.6%
125 1
0.6%
118 1
0.6%
113 2
1.3%
111 1
0.6%
101 1
0.6%
100 1
0.6%
91 1
0.6%

비고
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
120 
편도
36 
전체휴지
 
3

Length

Max length4
Median length4
Mean length3.5471698
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row편도
3rd row<NA>
4th row<NA>
5th row편도

Common Values

ValueCountFrequency (%)
<NA> 120
75.5%
편도 36
 
22.6%
전체휴지 3
 
1.9%

Length

2024-01-10T05:08:48.926593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:08:49.078723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 120
75.5%
편도 36
 
22.6%
전체휴지 3
 
1.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2022-09-23 00:00:00
Maximum2022-09-23 00:00:00
2024-01-10T05:08:49.168051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:49.271922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T05:08:45.953640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:44.637393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:45.076693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:45.496543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:46.079996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:44.760384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:45.189671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:45.610077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:46.191741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:44.860991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:45.279436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:45.712289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:46.336392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:44.973868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:45.389806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:08:45.830827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:08:49.367390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번노선번호운수업체명1회운행거리(km_편도기준)1일운행횟수(회_편도기준)비고
연번1.0000.9770.8700.6020.4561.000
노선번호0.9771.0000.9170.6090.3271.000
운수업체명0.8700.9171.0000.3080.193NaN
1회운행거리(km_편도기준)0.6020.6090.3081.0000.0000.379
1일운행횟수(회_편도기준)0.4560.3270.1930.0001.0000.846
비고1.0001.000NaN0.3790.8461.000
2024-01-10T05:08:49.506064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운수업체명비고
운수업체명1.0001.000
비고1.0001.000
2024-01-10T05:08:49.601131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번노선번호1회운행거리(km_편도기준)1일운행횟수(회_편도기준)운수업체명비고
연번1.0001.000-0.014-0.1380.6850.915
노선번호1.0001.000-0.014-0.1380.7400.944
1회운행거리(km_편도기준)-0.014-0.0141.000-0.0280.2300.246
1일운행횟수(회_편도기준)-0.138-0.138-0.0281.0000.1430.624
운수업체명0.6850.7400.2300.1431.0001.000
비고0.9150.9440.2460.6241.0001.000

Missing values

2024-01-10T05:08:46.499923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:08:46.636073image/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

연번노선번호운수업체명1회운행거리(km_편도기준)1일운행횟수(회_편도기준)비고데이터기준일자
011보성,삼안,새천안21.3125<NA>2022-09-23
122보성,삼안,새천안23.367편도2022-09-23
233보성,삼안,새천안21.8111<NA>2022-09-23
345보성,삼안,새천안20.353<NA>2022-09-23
457보성,삼안,새천안23.059편도2022-09-23
569보성,삼안,새천안9.231<NA>2022-09-23
6710보성,삼안,새천안18.822<NA>2022-09-23
7811보성,삼안,새천안17.4118<NA>2022-09-23
8912보성,삼안,새천안14.8172<NA>2022-09-23
91013보성,삼안,새천안12.8143<NA>2022-09-23
연번노선번호운수업체명1회운행거리(km_편도기준)1일운행횟수(회_편도기준)비고데이터기준일자
149150800보성,삼안,새천안15.380<NA>2022-09-23
150151830보성,삼안,새천안7.014<NA>2022-09-23
151152840보성,삼안,새천안4.314<NA>2022-09-23
152153850보성,삼안,새천안3.86<NA>2022-09-23
153154860보성,삼안,새천안6.218<NA>2022-09-23
154155870보성,삼안,새천안5.734전체휴지2022-09-23
155156900보성,삼안,새천안19.975<NA>2022-09-23
156157910보성,삼안,새천안20.038<NA>2022-09-23
157158931보성,삼안,새천안18.820전체휴지2022-09-23
158159960보성,삼안,새천안15.524전체휴지2022-09-23