Overview

Dataset statistics

Number of variables22
Number of observations93
Missing cells11
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.7 KiB
Average record size in memory184.4 B

Variable types

Categorical11
Text2
Numeric7
Boolean2

Dataset

Description경기도 수원시에 인가된 시내버스 노선현황 데이터로 노선명, 노선상태, 운행형태, 총인가거리 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15040660/fileData.do

Alerts

업종 has constant value ""Constant
노선상태 has constant value ""Constant
중간배차유무 has constant value ""Constant
벽지노선 has constant value ""Constant
관할관청 has constant value ""Constant
데이터기준일자 has constant value ""Constant
최초인가일자 is highly imbalanced (62.1%)Imbalance
굴곡도 has 11 (11.8%) missing valuesMissing
인가대수 has 1 (1.1%) zerosZeros
등록대수 has 1 (1.1%) zerosZeros

Reproduction

Analysis started2023-12-12 23:44:29.710281
Analysis finished2023-12-12 23:44:29.945964
Duration0.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Categorical

Distinct8
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size876.0 B
수원여객
38 
용남고속
27 
경진여객운수(주)
13 
성우운수(주)
6 
(주)용남고속버스라인
 
3
Other values (3)
6 

Length

Max length11
Median length4
Mean length5.3333333
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row(주)용남고속버스라인
2nd row(주)용남고속버스라인
3rd row(주)용남고속버스라인
4th row경진여객운수(주)
5th row경진여객운수(주)

Common Values

ValueCountFrequency (%)
수원여객 38
40.9%
용남고속 27
29.0%
경진여객운수(주) 13
 
14.0%
성우운수(주) 6
 
6.5%
(주)용남고속버스라인 3
 
3.2%
대원고속 2
 
2.2%
삼경운수(주) 2
 
2.2%
한국스마트버스협동조합 2
 
2.2%

Length

2023-12-13T08:44:30.008225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:44:30.109453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수원여객 38
40.9%
용남고속 27
29.0%
경진여객운수(주 13
 
14.0%
성우운수(주 6
 
6.5%
주)용남고속버스라인 3
 
3.2%
대원고속 2
 
2.2%
삼경운수(주 2
 
2.2%
한국스마트버스협동조합 2
 
2.2%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
시내버스
93 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시내버스
2nd row시내버스
3rd row시내버스
4th row시내버스
5th row시내버스

Common Values

ValueCountFrequency (%)
시내버스 93
100.0%

Length

2023-12-13T08:44:30.258882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:44:30.363224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시내버스 93
100.0%

노선명
Text

Distinct90
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-13T08:44:30.573029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.827957
Min length1

Characters and Unicode

Total characters356
Distinct characters21
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)93.5%

Sample

1st row3003
2nd row3003예약
3rd row7002
4th row3000
5th row3000(예약)
ValueCountFrequency (%)
37 2
 
2.2%
92_1 2
 
2.2%
92 2
 
2.2%
p9110(출근 1
 
1.1%
7_1a 1
 
1.1%
19 1
 
1.1%
13_5 1
 
1.1%
98 1
 
1.1%
83_1 1
 
1.1%
82_1 1
 
1.1%
Other values (80) 80
86.0%
2023-12-13T08:44:30.961977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 74
20.8%
1 49
13.8%
7 31
8.7%
3 30
8.4%
2 30
8.4%
_ 28
 
7.9%
9 20
 
5.6%
8 19
 
5.3%
5 11
 
3.1%
4 10
 
2.8%
Other values (11) 54
15.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 280
78.7%
Connector Punctuation 28
 
7.9%
Other Letter 26
 
7.3%
Close Punctuation 8
 
2.2%
Open Punctuation 8
 
2.2%
Uppercase Letter 6
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 74
26.4%
1 49
17.5%
7 31
11.1%
3 30
10.7%
2 30
10.7%
9 20
 
7.1%
8 19
 
6.8%
5 11
 
3.9%
4 10
 
3.6%
6 6
 
2.1%
Other Letter
ValueCountFrequency (%)
약 9
34.6%
예 9
34.6%
근 4
15.4%
출 2
 
7.7%
퇴 2
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
P 4
66.7%
A 1
 
16.7%
G 1
 
16.7%
Connector Punctuation
ValueCountFrequency (%)
_ 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 324
91.0%
Hangul 26
 
7.3%
Latin 6
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 74
22.8%
1 49
15.1%
7 31
9.6%
3 30
9.3%
2 30
9.3%
_ 28
 
8.6%
9 20
 
6.2%
8 19
 
5.9%
5 11
 
3.4%
4 10
 
3.1%
Other values (3) 22
 
6.8%
Hangul
ValueCountFrequency (%)
약 9
34.6%
예 9
34.6%
근 4
15.4%
출 2
 
7.7%
퇴 2
 
7.7%
Latin
ValueCountFrequency (%)
P 4
66.7%
A 1
 
16.7%
G 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 330
92.7%
Hangul 26
 
7.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 74
22.4%
1 49
14.8%
7 31
9.4%
3 30
9.1%
2 30
9.1%
_ 28
 
8.5%
9 20
 
6.1%
8 19
 
5.8%
5 11
 
3.3%
4 10
 
3.0%
Other values (6) 28
 
8.5%
Hangul
ValueCountFrequency (%)
약 9
34.6%
예 9
34.6%
근 4
15.4%
출 2
 
7.7%
퇴 2
 
7.7%

노선유형
Categorical

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
일반
68 
경기도 공공버스
21 
한정면허 일반
 
4

Length

Max length8
Median length2
Mean length3.5698925
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 공공버스
2nd row일반
3rd row경기도 공공버스
4th row경기도 공공버스
5th row일반

Common Values

ValueCountFrequency (%)
일반 68
73.1%
경기도 공공버스 21
 
22.6%
한정면허 일반 4
 
4.3%

Length

2023-12-13T08:44:31.100111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:44:31.188568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 72
61.0%
경기도 21
 
17.8%
공공버스 21
 
17.8%
한정면허 4
 
3.4%

노선상태
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
정상
93 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정상
2nd row정상
3rd row정상
4th row정상
5th row정상

Common Values

ValueCountFrequency (%)
정상 93
100.0%

Length

2023-12-13T08:44:31.275030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:44:31.348152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 93
100.0%

운행형태
Categorical

Distinct4
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size876.0 B
일반형시내버스
57 
직행좌석형시내버스
30 
경기순환버스(직행좌석형)
 
4
좌석형시내버스
 
2

Length

Max length13
Median length7
Mean length7.9032258
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row직행좌석형시내버스
2nd row직행좌석형시내버스
3rd row직행좌석형시내버스
4th row직행좌석형시내버스
5th row직행좌석형시내버스

Common Values

ValueCountFrequency (%)
일반형시내버스 57
61.3%
직행좌석형시내버스 30
32.3%
경기순환버스(직행좌석형) 4
 
4.3%
좌석형시내버스 2
 
2.2%

Length

2023-12-13T08:44:31.441746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:44:31.539993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반형시내버스 57
61.3%
직행좌석형시내버스 30
32.3%
경기순환버스(직행좌석형 4
 
4.3%
좌석형시내버스 2
 
2.2%

변경인가일자
Categorical

Distinct34
Distinct (%)36.6%
Missing0
Missing (%)0.0%
Memory size876.0 B
2020-06-01
13 
2020-04-28
11 
<NA>
8 
2020-05-28
6 
2020-06-03
 
5
Other values (29)
50 

Length

Max length10
Median length10
Mean length9.483871
Min length4

Unique

Unique19 ?
Unique (%)20.4%

Sample

1st row2020-04-10
2nd row2020-04-06
3rd row2019-05-13
4th row2020-05-07
5th row<NA>

Common Values

ValueCountFrequency (%)
2020-06-01 13
14.0%
2020-04-28 11
 
11.8%
<NA> 8
 
8.6%
2020-05-28 6
 
6.5%
2020-06-03 5
 
5.4%
2020-04-10 4
 
4.3%
2020-05-07 4
 
4.3%
2020-04-21 4
 
4.3%
2020-04-06 4
 
4.3%
2019-03-01 3
 
3.2%
Other values (24) 31
33.3%

Length

2023-12-13T08:44:31.630795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-06-01 13
14.0%
2020-04-28 11
 
11.8%
na 8
 
8.6%
2020-05-28 6
 
6.5%
2020-06-03 5
 
5.4%
2020-04-10 4
 
4.3%
2020-05-07 4
 
4.3%
2020-04-21 4
 
4.3%
2020-04-06 4
 
4.3%
2019-03-01 3
 
3.2%
Other values (24) 31
33.3%

최초인가일자
Categorical

IMBALANCE 

Distinct8
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
76 
2020-03-30
 
6
2020-03-27
 
4
2020-10-12
 
2
2021-04-20
 
2
Other values (3)
 
3

Length

Max length10
Median length4
Mean length5.0967742
Min length4

Unique

Unique3 ?
Unique (%)3.2%

Sample

1st row<NA>
2nd row2020-03-30
3rd row<NA>
4th row<NA>
5th row2020-03-27

Common Values

ValueCountFrequency (%)
<NA> 76
81.7%
2020-03-30 6
 
6.5%
2020-03-27 4
 
4.3%
2020-10-12 2
 
2.2%
2021-04-20 2
 
2.2%
2021-01-08 1
 
1.1%
2020-11-19 1
 
1.1%
2018-12-27 1
 
1.1%

Length

2023-12-13T08:44:31.732135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:44:31.818489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 76
81.7%
2020-03-30 6
 
6.5%
2020-03-27 4
 
4.3%
2020-10-12 2
 
2.2%
2021-04-20 2
 
2.2%
2021-01-08 1
 
1.1%
2020-11-19 1
 
1.1%
2018-12-27 1
 
1.1%

운송개시일
Categorical

Distinct30
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Memory size876.0 B
2021-08-01
32 
2021-07-30
12 
2021-01-01
5 
2021-03-01
4 
2020-04-01
4 
Other values (25)
36 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique16 ?
Unique (%)17.2%

Sample

1st row2021-01-01
2nd row2020-04-02
3rd row2021-04-05
4th row2021-03-01
5th row2020-04-01

Common Values

ValueCountFrequency (%)
2021-08-01 32
34.4%
2021-07-30 12
 
12.9%
2021-01-01 5
 
5.4%
2021-03-01 4
 
4.3%
2020-04-01 4
 
4.3%
2021-02-04 3
 
3.2%
2021-07-01 3
 
3.2%
2020-10-26 2
 
2.2%
2020-02-08 2
 
2.2%
2021-08-03 2
 
2.2%
Other values (20) 24
25.8%

Length

2023-12-13T08:44:31.903962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-08-01 32
34.4%
2021-07-30 12
 
12.9%
2021-01-01 5
 
5.4%
2021-03-01 4
 
4.3%
2020-04-01 4
 
4.3%
2021-02-04 3
 
3.2%
2021-07-01 3
 
3.2%
2021-04-28 2
 
2.2%
2021-06-01 2
 
2.2%
2021-01-09 2
 
2.2%
Other values (20) 24
25.8%

인가대수
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.892473
Minimum0
Maximum38
Zeros1
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-13T08:44:31.988815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median12
Q316
95-th percentile30
Maximum38
Range38
Interquartile range (IQR)11

Descriptive statistics

Standard deviation8.6721222
Coefficient of variation (CV)0.729211
Kurtosis0.55358548
Mean11.892473
Median Absolute Deviation (MAD)6
Skewness0.78550378
Sum1106
Variance75.205704
MonotonicityNot monotonic
2023-12-13T08:44:32.108336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 10
 
10.8%
14 8
 
8.6%
2 8
 
8.6%
12 7
 
7.5%
13 6
 
6.5%
5 5
 
5.4%
16 4
 
4.3%
18 3
 
3.2%
10 3
 
3.2%
11 3
 
3.2%
Other values (20) 36
38.7%
ValueCountFrequency (%)
0 1
 
1.1%
1 10
10.8%
2 8
8.6%
3 1
 
1.1%
4 3
 
3.2%
5 5
5.4%
6 3
 
3.2%
7 2
 
2.2%
8 2
 
2.2%
9 1
 
1.1%
ValueCountFrequency (%)
38 1
1.1%
36 1
1.1%
34 1
1.1%
31 1
1.1%
30 2
2.2%
26 1
1.1%
24 1
1.1%
22 2
2.2%
21 2
2.2%
20 2
2.2%

등록대수
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.870968
Minimum0
Maximum38
Zeros1
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-13T08:44:32.203433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median12
Q316
95-th percentile30
Maximum38
Range38
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.728048
Coefficient of variation (CV)0.73524317
Kurtosis0.57151804
Mean11.870968
Median Absolute Deviation (MAD)6
Skewness0.79534632
Sum1104
Variance76.178822
MonotonicityNot monotonic
2023-12-13T08:44:32.294623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 10
 
10.8%
14 8
 
8.6%
2 8
 
8.6%
12 7
 
7.5%
13 6
 
6.5%
5 5
 
5.4%
16 4
 
4.3%
19 3
 
3.2%
4 3
 
3.2%
15 3
 
3.2%
Other values (20) 36
38.7%
ValueCountFrequency (%)
0 1
 
1.1%
1 10
10.8%
2 8
8.6%
3 2
 
2.2%
4 3
 
3.2%
5 5
5.4%
6 2
 
2.2%
7 2
 
2.2%
8 2
 
2.2%
9 1
 
1.1%
ValueCountFrequency (%)
38 1
1.1%
36 1
1.1%
35 1
1.1%
31 1
1.1%
30 2
2.2%
26 1
1.1%
24 1
1.1%
22 2
2.2%
21 2
2.2%
20 2
2.2%

인가횟수
Real number (ℝ)

Distinct60
Distinct (%)64.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.666667
Minimum2
Maximum191
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-13T08:44:32.399355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q122
median58
Q393
95-th percentile138.8
Maximum191
Range189
Interquartile range (IQR)71

Descriptive statistics

Standard deviation45.516202
Coefficient of variation (CV)0.75026706
Kurtosis-0.52947097
Mean60.666667
Median Absolute Deviation (MAD)36
Skewness0.4233083
Sum5642
Variance2071.7246
MonotonicityNot monotonic
2023-12-13T08:44:32.515052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 13
 
14.0%
80 5
 
5.4%
5 4
 
4.3%
67 3
 
3.2%
45 3
 
3.2%
57 3
 
3.2%
90 2
 
2.2%
84 2
 
2.2%
25 2
 
2.2%
110 2
 
2.2%
Other values (50) 54
58.1%
ValueCountFrequency (%)
2 13
14.0%
3 1
 
1.1%
4 1
 
1.1%
5 4
 
4.3%
12 1
 
1.1%
16 1
 
1.1%
19 1
 
1.1%
20 1
 
1.1%
22 2
 
2.2%
23 1
 
1.1%
ValueCountFrequency (%)
191 1
1.1%
153 1
1.1%
152 1
1.1%
141 1
1.1%
140 1
1.1%
138 1
1.1%
134 1
1.1%
132 1
1.1%
130 2
2.2%
117 1
1.1%

총인가거리(편도)
Real number (ℝ)

Distinct69
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.632258
Minimum10.2
Maximum51.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-13T08:44:32.627938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10.2
5-th percentile16.4
Q121.9
median27.9
Q336
95-th percentile49.8
Maximum51.4
Range41.2
Interquartile range (IQR)14.1

Descriptive statistics

Standard deviation9.9891154
Coefficient of variation (CV)0.33710274
Kurtosis-0.48646285
Mean29.632258
Median Absolute Deviation (MAD)6.5
Skewness0.4746946
Sum2755.8
Variance99.782426
MonotonicityNot monotonic
2023-12-13T08:44:32.728945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49.8 3
 
3.2%
21.0 3
 
3.2%
40.5 3
 
3.2%
32.5 2
 
2.2%
19.5 2
 
2.2%
21.9 2
 
2.2%
17.0 2
 
2.2%
18.9 2
 
2.2%
15.5 2
 
2.2%
21.6 2
 
2.2%
Other values (59) 70
75.3%
ValueCountFrequency (%)
10.2 1
1.1%
11.1 1
1.1%
14.2 1
1.1%
15.5 2
2.2%
17.0 2
2.2%
17.2 1
1.1%
18.0 1
1.1%
18.9 2
2.2%
19.2 2
2.2%
19.5 2
2.2%
ValueCountFrequency (%)
51.4 2
2.2%
50.0 2
2.2%
49.8 3
3.2%
46.3 1
 
1.1%
43.6 1
 
1.1%
43.3 1
 
1.1%
43.0 1
 
1.1%
42.5 1
 
1.1%
40.6 2
2.2%
40.5 3
3.2%

굴곡도
Real number (ℝ)

MISSING 

Distinct56
Distinct (%)68.3%
Missing11
Missing (%)11.8%
Infinite0
Infinite (%)0.0%
Mean1.9240244
Minimum1.1
Maximum7.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-13T08:44:32.832467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1
5-th percentile1.1615
Q11.3525
median1.58
Q32.0725
95-th percentile3.125
Maximum7.89
Range6.79
Interquartile range (IQR)0.72

Descriptive statistics

Standard deviation1.0256041
Coefficient of variation (CV)0.53305153
Kurtosis16.212281
Mean1.9240244
Median Absolute Deviation (MAD)0.33
Skewness3.5365379
Sum157.77
Variance1.0518639
MonotonicityNot monotonic
2023-12-13T08:44:32.946372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.58 5
 
5.4%
1.47 3
 
3.2%
1.49 3
 
3.2%
1.27 3
 
3.2%
1.39 3
 
3.2%
1.75 2
 
2.2%
1.98 2
 
2.2%
2.61 2
 
2.2%
1.29 2
 
2.2%
1.26 2
 
2.2%
Other values (46) 55
59.1%
(Missing) 11
 
11.8%
ValueCountFrequency (%)
1.1 1
 
1.1%
1.15 2
2.2%
1.16 2
2.2%
1.19 2
2.2%
1.23 1
 
1.1%
1.24 1
 
1.1%
1.25 1
 
1.1%
1.26 2
2.2%
1.27 3
3.2%
1.29 2
2.2%
ValueCountFrequency (%)
7.89 1
1.1%
5.94 1
1.1%
4.73 1
1.1%
3.5 1
1.1%
3.13 1
1.1%
3.03 1
1.1%
2.93 1
1.1%
2.92 1
1.1%
2.83 1
1.1%
2.64 1
1.1%

중간배차유무
Boolean

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size225.0 B
False
93 
ValueCountFrequency (%)
False 93
100.0%
2023-12-13T08:44:33.034483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

벽지노선
Boolean

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size225.0 B
False
93 
ValueCountFrequency (%)
False 93
100.0%
2023-12-13T08:44:33.090374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

기점정류소
Categorical

Distinct36
Distinct (%)38.7%
Missing0
Missing (%)0.0%
Memory size876.0 B
이목동차고지.이목동입구
10 
수원시동부차고지
9 
곡반정동차고지
7 
동탄차고지
6 
능실마을21단지.수원여대입구
6 
Other values (31)
55 

Length

Max length22
Median length16
Mean length9.2150538
Min length3

Unique

Unique19 ?
Unique (%)20.4%

Sample

1st row능실마을21단지.수원여대입구
2nd row삼환나우빌아파트
3rd row수원남부버스공영차고지
4th row능실마을21단지.수원여대입구
5th row수원종합운동장.수원시체육회관.아너스빌위즈

Common Values

ValueCountFrequency (%)
이목동차고지.이목동입구 10
 
10.8%
수원시동부차고지 9
 
9.7%
곡반정동차고지 7
 
7.5%
동탄차고지 6
 
6.5%
능실마을21단지.수원여대입구 6
 
6.5%
수원남부버스공영차고지 6
 
6.5%
경기대정문 4
 
4.3%
수원버스터미널 4
 
4.3%
수원역.헌혈의집 3
 
3.2%
수원아이파크시티.선일초교 3
 
3.2%
Other values (26) 35
37.6%

Length

2023-12-13T08:44:33.180036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이목동차고지.이목동입구 10
 
10.8%
수원시동부차고지 9
 
9.7%
곡반정동차고지 7
 
7.5%
동탄차고지 6
 
6.5%
능실마을21단지.수원여대입구 6
 
6.5%
수원남부버스공영차고지 6
 
6.5%
경기대정문 4
 
4.3%
수원버스터미널 4
 
4.3%
수원역.헌혈의집 3
 
3.2%
수원아이파크시티.선일초교 3
 
3.2%
Other values (26) 35
37.6%

종점정류소
Text

Distinct68
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-13T08:44:33.349746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length9
Min length3

Characters and Unicode

Total characters837
Distinct characters203
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)54.8%

Sample

1st row강남역나라빌딩앞
2nd row선바위역
3rd row인덕원역4호선
4th row강남역나라빌딩앞
5th row강남역나라빌딩앞
ValueCountFrequency (%)
사당역(중 5
 
5.4%
강남역나라빌딩앞 4
 
4.3%
동원고교.해우재입구 3
 
3.2%
사당역 3
 
3.2%
조원뉴타운 3
 
3.2%
수원여자고교 2
 
2.2%
서울역버스환승센터.6번홈(중 2
 
2.2%
성균관대역.고용노동부경기지청.율전성당 2
 
2.2%
시민의숲.양재꽃시장 2
 
2.2%
강남역.역삼세무서 2
 
2.2%
Other values (58) 65
69.9%
2023-12-13T08:44:33.665477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 40
 
4.8%
역 31
 
3.7%
지 23
 
2.7%
교 23
 
2.7%
원 19
 
2.3%
중 15
 
1.8%
트 14
 
1.7%
아 14
 
1.7%
대 13
 
1.6%
( 13
 
1.6%
Other values (193) 632
75.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 742
88.6%
Other Punctuation 40
 
4.8%
Decimal Number 26
 
3.1%
Open Punctuation 13
 
1.6%
Close Punctuation 13
 
1.6%
Uppercase Letter 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 31
 
4.2%
지 23
 
3.1%
교 23
 
3.1%
원 19
 
2.6%
중 15
 
2.0%
트 14
 
1.9%
아 14
 
1.9%
대 13
 
1.8%
강 13
 
1.8%
파 13
 
1.8%
Other values (180) 564
76.0%
Decimal Number
ValueCountFrequency (%)
2 8
30.8%
1 6
23.1%
6 4
15.4%
3 3
 
11.5%
4 2
 
7.7%
0 2
 
7.7%
5 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 742
88.6%
Common 93
 
11.1%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 31
 
4.2%
지 23
 
3.1%
교 23
 
3.1%
원 19
 
2.6%
중 15
 
2.0%
트 14
 
1.9%
아 14
 
1.9%
대 13
 
1.8%
강 13
 
1.8%
파 13
 
1.8%
Other values (180) 564
76.0%
Common
ValueCountFrequency (%)
. 40
43.0%
( 13
 
14.0%
) 13
 
14.0%
2 8
 
8.6%
1 6
 
6.5%
6 4
 
4.3%
3 3
 
3.2%
4 2
 
2.2%
0 2
 
2.2%
- 1
 
1.1%
Latin
ValueCountFrequency (%)
L 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 742
88.6%
ASCII 95
 
11.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 40
42.1%
( 13
 
13.7%
) 13
 
13.7%
2 8
 
8.4%
1 6
 
6.3%
6 4
 
4.2%
3 3
 
3.2%
4 2
 
2.1%
0 2
 
2.1%
- 1
 
1.1%
Other values (3) 3
 
3.2%
Hangul
ValueCountFrequency (%)
역 31
 
4.2%
지 23
 
3.1%
교 23
 
3.1%
원 19
 
2.6%
중 15
 
2.0%
트 14
 
1.9%
아 14
 
1.9%
대 13
 
1.8%
강 13
 
1.8%
파 13
 
1.8%
Other values (180) 564
76.0%

관할관청
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
경기도 수원시
93 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 수원시
2nd row경기도 수원시
3rd row경기도 수원시
4th row경기도 수원시
5th row경기도 수원시

Common Values

ValueCountFrequency (%)
경기도 수원시 93
100.0%

Length

2023-12-13T08:44:33.791759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:44:33.878818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 93
50.0%
수원시 93
50.0%

업체아이디
Real number (ℝ)

Distinct8
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4104447.3
Minimum4100300
Maximum4111200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-13T08:44:33.953403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4100300
5-th percentile4102700
Q14103100
median4103100
Q34103600
95-th percentile4110800
Maximum4111200
Range10900
Interquartile range (IQR)500

Descriptive statistics

Standard deviation2892.6666
Coefficient of variation (CV)0.00070476397
Kurtosis1.2395214
Mean4104447.3
Median Absolute Deviation (MAD)500
Skewness1.6686393
Sum3.817136 × 108
Variance8367519.9
MonotonicityNot monotonic
2023-12-13T08:44:34.052778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
4103100 38
40.9%
4103600 27
29.0%
4110800 13
 
14.0%
4102700 6
 
6.5%
4105000 3
 
3.2%
4100300 2
 
2.2%
4102000 2
 
2.2%
4111200 2
 
2.2%
ValueCountFrequency (%)
4100300 2
 
2.2%
4102000 2
 
2.2%
4102700 6
 
6.5%
4103100 38
40.9%
4103600 27
29.0%
4105000 3
 
3.2%
4110800 13
 
14.0%
4111200 2
 
2.2%
ValueCountFrequency (%)
4111200 2
 
2.2%
4110800 13
 
14.0%
4105000 3
 
3.2%
4103600 27
29.0%
4103100 38
40.9%
4102700 6
 
6.5%
4102000 2
 
2.2%
4100300 2
 
2.2%

노선아이디
Real number (ℝ)

Distinct90
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0498939 × 108
Minimum2.0000001 × 108
Maximum2.3400002 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-13T08:44:34.166649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0000001 × 108
5-th percentile2.0000002 × 108
Q12.0000007 × 108
median2.0000014 × 108
Q32.0000029 × 108
95-th percentile2.3300027 × 108
Maximum2.3400002 × 108
Range34000010
Interquartile range (IQR)219

Descriptive statistics

Standard deviation11916822
Coefficient of variation (CV)0.058133851
Kurtosis1.9926872
Mean2.0498939 × 108
Median Absolute Deviation (MAD)105
Skewness1.9872558
Sum1.9064013 × 1010
Variance1.4201066 × 1014
MonotonicityNot monotonic
2023-12-13T08:44:34.289065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200000099 2
 
2.2%
200000029 2
 
2.2%
200000025 2
 
2.2%
200000289 1
 
1.1%
200000097 1
 
1.1%
200000266 1
 
1.1%
200000090 1
 
1.1%
200000085 1
 
1.1%
200000023 1
 
1.1%
200000054 1
 
1.1%
Other values (80) 80
86.0%
ValueCountFrequency (%)
200000006 1
1.1%
200000010 1
1.1%
200000015 1
1.1%
200000023 1
1.1%
200000024 1
1.1%
200000025 2
2.2%
200000028 1
1.1%
200000029 2
2.2%
200000031 1
1.1%
200000032 1
1.1%
ValueCountFrequency (%)
234000016 1
1.1%
234000013 1
1.1%
233000356 1
1.1%
233000355 1
1.1%
233000273 1
1.1%
233000272 1
1.1%
233000271 1
1.1%
233000087 1
1.1%
233000083 1
1.1%
233000032 1
1.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-08-02
93 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-02
2nd row2023-08-02
3rd row2023-08-02
4th row2023-08-02
5th row2023-08-02

Common Values

ValueCountFrequency (%)
2023-08-02 93
100.0%

Length

2023-12-13T08:44:34.404632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:44:34.475860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-02 93
100.0%

Sample

업체명업종노선명노선유형노선상태운행형태변경인가일자최초인가일자운송개시일인가대수등록대수인가횟수총인가거리(편도)굴곡도중간배차유무벽지노선기점정류소종점정류소관할관청업체아이디노선아이디데이터기준일자
0(주)용남고속버스라인시내버스3003경기도 공공버스정상직행좌석형시내버스2020-04-10<NA>2021-01-0114146732.51.39NN능실마을21단지.수원여대입구강남역나라빌딩앞경기도 수원시41050002000001082023-08-02
1(주)용남고속버스라인시내버스3003예약일반정상직행좌석형시내버스2020-04-062020-03-302020-04-0222232.5<NA>NN삼환나우빌아파트선바위역경기도 수원시41050002000002932023-08-02
2(주)용남고속버스라인시내버스7002경기도 공공버스정상직행좌석형시내버스2019-05-13<NA>2021-04-05633543.31.49NN수원남부버스공영차고지인덕원역4호선경기도 수원시41050002000001092023-08-02
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업체명업종노선명노선유형노선상태운행형태변경인가일자최초인가일자운송개시일인가대수등록대수인가횟수총인가거리(편도)굴곡도중간배차유무벽지노선기점정류소종점정류소관할관청업체아이디노선아이디데이터기준일자
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84용남고속시내버스9일반정상일반형시내버스2020-09-17<NA>2021-07-3011116727.31.49NN사색의광장금곡동강남아파트경기도 수원시41036002000001032023-08-02
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86용남고속시내버스92일반정상일반형시내버스2020-06-01<NA>2021-07-3011116715.51.93NN곡반정동차고지동원고교.해우재입구경기도 수원시41036002000000252023-08-02
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89용남고속시내버스99_2일반정상일반형시내버스2020-06-01<NA>2021-07-3011114728.04.73NN오목초등학교곡반정동차고지경기도 수원시41036002000001962023-08-02
90용남고속시내버스G5100경기도 공공버스정상직행좌석형시내버스2020-06-052018-12-272021-06-10552549.81.44NN경희대학교시민의숲.양재꽃시장경기도 수원시41036002000002622023-08-02
91한국스마트버스협동조합시내버스P9110(출근)한정면허 일반정상경기순환버스(직행좌석형)2021-04-282021-04-202021-06-0111250.01.39NN수원아이파크시티.선일초교서울역버스환승센터.6번홈(중)경기도 수원시41112002330003552023-08-02
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