Overview

Dataset statistics

Number of variables29
Number of observations10000
Missing cells23239
Missing cells (%)8.0%
Duplicate rows8
Duplicate rows (%)0.1%
Total size in memory2.4 MiB
Average record size in memory251.0 B

Variable types

Unsupported6
Numeric8
Text7
Boolean1
Categorical7

Dataset

Description경상남도 버스업체경영수지분석 시스템 데이터 자료로, 운행시작날짜, 노선등록날짜, 계통거리, 운행횟수, 경유지 등에 대한 정보들을 제공합니다.
Author경상남도
URLhttps://www.data.go.kr/data/15065912/fileData.do

Alerts

Dataset has 8 (0.1%) duplicate rowsDuplicates
Unnamed: 22 is highly imbalanced (98.5%)Imbalance
Unnamed: 23 is highly imbalanced (98.2%)Imbalance
Unnamed: 24 is highly imbalanced (98.0%)Imbalance
Unnamed: 25 is highly imbalanced (97.4%)Imbalance
Unnamed: 26 is highly imbalanced (96.0%)Imbalance
Unnamed: 27 is highly imbalanced (98.0%)Imbalance
Unnamed: 28 is highly imbalanced (99.9%)Imbalance
STR_PUBLIC_ID has 707 (7.1%) missing valuesMissing
END_YMD has 7801 (78.0%) missing valuesMissing
USE_YN has 4317 (43.2%) missing valuesMissing
END_PUBLIC_ID has 739 (7.4%) missing valuesMissing
REMARKS has 9422 (94.2%) missing valuesMissing
VIA_PLACE has 165 (1.7%) missing valuesMissing
No is an unsupported type, check if it needs cleaning or further analysisUnsupported
STR_YMD is an unsupported type, check if it needs cleaning or further analysisUnsupported
H2_KM is an unsupported type, check if it needs cleaning or further analysisUnsupported
REMOTE_KM is an unsupported type, check if it needs cleaning or further analysisUnsupported
N4L_KM is an unsupported type, check if it needs cleaning or further analysisUnsupported
N4H_KM is an unsupported type, check if it needs cleaning or further analysisUnsupported
END_YMD has 1095 (10.9%) zerosZeros

Reproduction

Analysis started2023-12-13 00:03:57.540115
Analysis finished2023-12-13 00:03:58.570332
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

No
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

STR_YMD
Unsupported

REJECTED  UNSUPPORTED 

Missing7
Missing (%)0.1%
Memory size156.2 KiB

STR_PUBLIC_ID
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)0.4%
Missing707
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean13.917142
Minimum0
Maximum67
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T09:03:58.617999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median7
Q320
95-th percentile42
Maximum67
Range67
Interquartile range (IQR)14

Descriptive statistics

Standard deviation13.427049
Coefficient of variation (CV)0.96478494
Kurtosis1.1237089
Mean13.917142
Median Absolute Deviation (MAD)4
Skewness1.3981204
Sum129332
Variance180.28564
MonotonicityNot monotonic
2023-12-13T09:03:58.711836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
7 3410
34.1%
30 1183
 
11.8%
6 615
 
6.2%
2 593
 
5.9%
1 554
 
5.5%
40 382
 
3.8%
3 380
 
3.8%
42 261
 
2.6%
20 251
 
2.5%
12 249
 
2.5%
Other values (24) 1415
14.1%
(Missing) 707
 
7.1%
ValueCountFrequency (%)
0 6
 
0.1%
1 554
 
5.5%
2 593
 
5.9%
3 380
 
3.8%
4 100
 
1.0%
5 150
 
1.5%
6 615
 
6.2%
7 3410
34.1%
8 58
 
0.6%
11 110
 
1.1%
ValueCountFrequency (%)
67 4
 
< 0.1%
61 1
 
< 0.1%
59 151
1.5%
56 1
 
< 0.1%
55 1
 
< 0.1%
54 7
 
0.1%
49 5
 
0.1%
48 4
 
< 0.1%
47 35
 
0.4%
46 8
 
0.1%

END_PLACE
Text

Distinct909
Distinct (%)9.1%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T09:03:58.957190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length2
Mean length2.6530959
Min length1

Characters and Unicode

Total characters26523
Distinct characters317
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique292 ?
Unique (%)2.9%

Sample

1st row울산
2nd row고현
3rd row부춘
4th row대계
5th row울산
ValueCountFrequency (%)
능포 575
 
5.7%
고현 432
 
4.3%
터미널 429
 
4.2%
밀양역 402
 
4.0%
통영 283
 
2.8%
구조라 277
 
2.7%
백병원 255
 
2.5%
진주 201
 
2.0%
울산 196
 
1.9%
시외터미널 174
 
1.7%
Other values (912) 6921
68.2%
2023-12-13T09:03:59.329227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
포 1002
 
3.8%
산 829
 
3.1%
미 759
 
2.9%
동 746
 
2.8%
터 712
 
2.7%
널 708
 
2.7%
양 652
 
2.5%
원 630
 
2.4%
능 621
 
2.3%
현 611
 
2.3%
Other values (307) 19253
72.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25715
97.0%
Open Punctuation 245
 
0.9%
Close Punctuation 245
 
0.9%
Space Separator 152
 
0.6%
Uppercase Letter 100
 
0.4%
Other Punctuation 33
 
0.1%
Decimal Number 18
 
0.1%
Lowercase Letter 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 1002
 
3.9%
산 829
 
3.2%
미 759
 
3.0%
동 746
 
2.9%
터 712
 
2.8%
널 708
 
2.8%
양 652
 
2.5%
원 630
 
2.4%
능 621
 
2.4%
현 611
 
2.4%
Other values (286) 18445
71.7%
Uppercase Letter
ValueCountFrequency (%)
A 75
75.0%
T 8
 
8.0%
R 8
 
8.0%
S 6
 
6.0%
P 1
 
1.0%
X 1
 
1.0%
K 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 12
36.4%
, 8
24.2%
@ 7
21.2%
/ 2
 
6.1%
？ 2
 
6.1%
; 1
 
3.0%
' 1
 
3.0%
Decimal Number
ValueCountFrequency (%)
2 9
50.0%
0 6
33.3%
1 3
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 245
100.0%
Close Punctuation
ValueCountFrequency (%)
) 245
100.0%
Space Separator
ValueCountFrequency (%)
152
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25715
97.0%
Common 693
 
2.6%
Latin 115
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 1002
 
3.9%
산 829
 
3.2%
미 759
 
3.0%
동 746
 
2.9%
터 712
 
2.8%
널 708
 
2.8%
양 652
 
2.5%
원 630
 
2.4%
능 621
 
2.4%
현 611
 
2.4%
Other values (286) 18445
71.7%
Common
ValueCountFrequency (%)
( 245
35.4%
) 245
35.4%
152
21.9%
. 12
 
1.7%
2 9
 
1.3%
, 8
 
1.2%
@ 7
 
1.0%
0 6
 
0.9%
1 3
 
0.4%
/ 2
 
0.3%
Other values (3) 4
 
0.6%
Latin
ValueCountFrequency (%)
A 75
65.2%
s 15
 
13.0%
T 8
 
7.0%
R 8
 
7.0%
S 6
 
5.2%
P 1
 
0.9%
X 1
 
0.9%
K 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25713
96.9%
ASCII 806
 
3.0%
None 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
포 1002
 
3.9%
산 829
 
3.2%
미 759
 
3.0%
동 746
 
2.9%
터 712
 
2.8%
널 708
 
2.8%
양 652
 
2.5%
원 630
 
2.5%
능 621
 
2.4%
현 611
 
2.4%
Other values (285) 18443
71.7%
ASCII
ValueCountFrequency (%)
( 245
30.4%
) 245
30.4%
152
18.9%
A 75
 
9.3%
s 15
 
1.9%
. 12
 
1.5%
2 9
 
1.1%
T 8
 
1.0%
R 8
 
1.0%
, 8
 
1.0%
Other values (10) 29
 
3.6%
None
ValueCountFrequency (%)
？ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅓ 2
100.0%

ENT_DT
Text

Distinct804
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T09:03:59.605938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9946
Min length1

Characters and Unicode

Total characters99946
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

Unique245 ?
Unique (%)2.5%

Sample

1st row20,100,907
2nd row20,181,113
3rd row20,140,406
4th row20,200,325
5th row20,180,411
ValueCountFrequency (%)
20,100,907 206
 
2.1%
20,150,416 201
 
2.0%
20,100,909 169
 
1.7%
20,101,026 162
 
1.6%
20,190,415 150
 
1.5%
20,181,113 149
 
1.5%
20,200,803 148
 
1.5%
20,190,421 148
 
1.5%
20,200,810 147
 
1.5%
20,190,805 146
 
1.5%
Other values (794) 8374
83.7%
2023-12-13T09:03:59.969829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25294
25.3%
, 19988
20.0%
1 18861
18.9%
2 16717
16.7%
9 3691
 
3.7%
8 2949
 
3.0%
4 2775
 
2.8%
5 2558
 
2.6%
3 2558
 
2.6%
6 2279
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79958
80.0%
Other Punctuation 19988
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25294
31.6%
1 18861
23.6%
2 16717
20.9%
9 3691
 
4.6%
8 2949
 
3.7%
4 2775
 
3.5%
5 2558
 
3.2%
3 2558
 
3.2%
6 2279
 
2.9%
7 2276
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 19988
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99946
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25294
25.3%
, 19988
20.0%
1 18861
18.9%
2 16717
16.7%
9 3691
 
3.7%
8 2949
 
3.0%
4 2775
 
2.8%
5 2558
 
2.6%
3 2558
 
2.6%
6 2279
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99946
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25294
25.3%
, 19988
20.0%
1 18861
18.9%
2 16717
16.7%
9 3691
 
3.7%
8 2949
 
3.0%
4 2775
 
2.8%
5 2558
 
2.6%
3 2558
 
2.6%
6 2279
 
2.3%

UPD_DT
Text

Distinct763
Distinct (%)7.6%
Missing6
Missing (%)0.1%
Memory size156.2 KiB
2023-12-13T09:04:00.258136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters99940
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

Unique217 ?
Unique (%)2.2%

Sample

1st row20,101,109
2nd row20,181,113
3rd row20,140,406
4th row20,200,325
5th row20,180,411
ValueCountFrequency (%)
20,101,026 159
 
1.6%
20,190,415 150
 
1.5%
20,200,803 148
 
1.5%
20,190,421 148
 
1.5%
20,181,113 147
 
1.5%
20,200,810 147
 
1.5%
20,150,416 145
 
1.5%
20,190,904 141
 
1.4%
20,190,805 140
 
1.4%
20,150,407 130
 
1.3%
Other values (753) 8539
85.4%
2023-12-13T09:04:00.608417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24776
24.8%
, 19988
20.0%
1 18967
19.0%
2 16793
16.8%
9 3798
 
3.8%
5 2968
 
3.0%
4 2944
 
2.9%
8 2821
 
2.8%
3 2395
 
2.4%
6 2332
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79952
80.0%
Other Punctuation 19988
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24776
31.0%
1 18967
23.7%
2 16793
21.0%
9 3798
 
4.8%
5 2968
 
3.7%
4 2944
 
3.7%
8 2821
 
3.5%
3 2395
 
3.0%
6 2332
 
2.9%
7 2158
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 19988
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99940
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24776
24.8%
, 19988
20.0%
1 18967
19.0%
2 16793
16.8%
9 3798
 
3.8%
5 2968
 
3.0%
4 2944
 
2.9%
8 2821
 
2.8%
3 2395
 
2.4%
6 2332
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99940
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24776
24.8%
, 19988
20.0%
1 18967
19.0%
2 16793
16.8%
9 3798
 
3.8%
5 2968
 
3.0%
4 2944
 
2.9%
8 2821
 
2.8%
3 2395
 
2.4%
6 2332
 
2.3%

LINE_ID
Real number (ℝ)

Distinct1662
Distinct (%)16.6%
Missing9
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean721.7827
Minimum1
Maximum2006
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T09:04:00.733667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18
Q194
median764
Q31185.5
95-th percentile1759
Maximum2006
Range2005
Interquartile range (IQR)1091.5

Descriptive statistics

Standard deviation600.8537
Coefficient of variation (CV)0.83245788
Kurtosis-1.3078964
Mean721.7827
Median Absolute Deviation (MAD)568
Skewness0.25407141
Sum7211331
Variance361025.17
MonotonicityNot monotonic
2023-12-13T09:04:00.849018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63 80
 
0.8%
65 79
 
0.8%
70 59
 
0.6%
18 53
 
0.5%
1022 53
 
0.5%
69 50
 
0.5%
72 49
 
0.5%
1051 49
 
0.5%
17 48
 
0.5%
1088 47
 
0.5%
Other values (1652) 9424
94.2%
ValueCountFrequency (%)
1 29
0.3%
2 31
0.3%
3 33
0.3%
4 42
0.4%
5 30
0.3%
6 17
0.2%
7 19
0.2%
8 20
0.2%
9 19
0.2%
10 19
0.2%
ValueCountFrequency (%)
2006 2
 
< 0.1%
2004 1
 
< 0.1%
2003 5
0.1%
2002 7
0.1%
2001 5
0.1%
2000 1
 
< 0.1%
1998 1
 
< 0.1%
1997 1
 
< 0.1%
1996 1
 
< 0.1%
1995 2
 
< 0.1%

TOT_KM
Text

Distinct1564
Distinct (%)15.6%
Missing6
Missing (%)0.1%
Memory size156.2 KiB
2023-12-13T09:04:01.199000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length3.8269962
Min length1

Characters and Unicode

Total characters38247
Distinct characters12
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

Unique467 ?
Unique (%)4.7%

Sample

1st row139
2nd row35.8
3rd row39.4
4th row21.1
5th row556
ValueCountFrequency (%)
28.8 91
 
0.9%
26.4 84
 
0.8%
20.5 78
 
0.8%
82 77
 
0.8%
102.5 72
 
0.7%
25.8 68
 
0.7%
61.5 68
 
0.7%
10.9 68
 
0.7%
35.8 64
 
0.6%
47.1 60
 
0.6%
Other values (1554) 9264
92.7%
2023-12-13T09:04:01.663602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 8056
21.1%
1 4868
12.7%
2 4798
12.5%
4 3318
8.7%
3 3277
8.6%
6 3203
 
8.4%
8 2726
 
7.1%
5 2645
 
6.9%
9 1851
 
4.8%
7 1799
 
4.7%
Other values (2) 1706
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30181
78.9%
Other Punctuation 8066
 
21.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4868
16.1%
2 4798
15.9%
4 3318
11.0%
3 3277
10.9%
6 3203
10.6%
8 2726
9.0%
5 2645
8.8%
9 1851
 
6.1%
7 1799
 
6.0%
0 1696
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 8056
99.9%
, 10
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 38247
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 8056
21.1%
1 4868
12.7%
2 4798
12.5%
4 3318
8.7%
3 3277
8.6%
6 3203
 
8.4%
8 2726
 
7.1%
5 2645
 
6.9%
9 1851
 
4.8%
7 1799
 
4.7%
Other values (2) 1706
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38247
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 8056
21.1%
1 4868
12.7%
2 4798
12.5%
4 3318
8.7%
3 3277
8.6%
6 3203
 
8.4%
8 2726
 
7.1%
5 2645
 
6.9%
9 1851
 
4.8%
7 1799
 
4.7%
Other values (2) 1706
 
4.5%

END_YMD
Real number (ℝ)

MISSING  ZEROS 

Distinct243
Distinct (%)11.1%
Missing7801
Missing (%)78.0%
Infinite0
Infinite (%)0.0%
Mean10119284
Minimum0
Maximum20210630
Zeros1095
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T09:04:01.783780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median20100127
Q320160630
95-th percentile20200140
Maximum20210630
Range20210630
Interquartile range (IQR)20160630

Descriptive statistics

Standard deviation10080271
Coefficient of variation (CV)0.99614476
Kurtosis-2.0017332
Mean10119284
Median Absolute Deviation (MAD)110503
Skewness-0.0081751626
Sum2.2252305 × 1010
Variance1.0161187 × 1014
MonotonicityNot monotonic
2023-12-13T09:04:01.899494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1095
 
10.9%
20100127 81
 
0.8%
20180630 55
 
0.5%
20200630 53
 
0.5%
20121231 51
 
0.5%
20190630 29
 
0.3%
20141120 22
 
0.2%
20170531 21
 
0.2%
20160630 20
 
0.2%
20120430 19
 
0.2%
Other values (233) 753
 
7.5%
(Missing) 7801
78.0%
ValueCountFrequency (%)
0 1095
10.9%
20100127 81
 
0.8%
20100430 2
 
< 0.1%
20100510 1
 
< 0.1%
20100630 4
 
< 0.1%
20100930 1
 
< 0.1%
20101031 2
 
< 0.1%
20101101 2
 
< 0.1%
20101213 1
 
< 0.1%
20101231 5
 
0.1%
ValueCountFrequency (%)
20210630 5
 
0.1%
20210624 1
 
< 0.1%
20210531 1
 
< 0.1%
20210516 1
 
< 0.1%
20201231 2
 
< 0.1%
20201130 2
 
< 0.1%
20200920 1
 
< 0.1%
20200731 13
0.1%
20200706 2
 
< 0.1%
20200705 1
 
< 0.1%

USE_YN
Boolean

MISSING 

Distinct2
Distinct (%)< 0.1%
Missing4317
Missing (%)43.2%
Memory size97.7 KiB
True
4722 
False
961 
(Missing)
4317 
ValueCountFrequency (%)
True 4722
47.2%
False 961
 
9.6%
(Missing) 4317
43.2%
2023-12-13T09:04:02.001793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

END_PUBLIC_ID
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)0.4%
Missing739
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean12.472087
Minimum1
Maximum74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T09:04:02.082667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median7
Q317
95-th percentile30
Maximum74
Range73
Interquartile range (IQR)11

Descriptive statistics

Standard deviation11.592412
Coefficient of variation (CV)0.9294685
Kurtosis2.5095119
Mean12.472087
Median Absolute Deviation (MAD)4
Skewness1.6446003
Sum115504
Variance134.38402
MonotonicityNot monotonic
2023-12-13T09:04:02.188060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
7 3417
34.2%
30 1197
 
12.0%
6 627
 
6.3%
2 562
 
5.6%
1 493
 
4.9%
3 461
 
4.6%
12 278
 
2.8%
20 251
 
2.5%
13 249
 
2.5%
19 241
 
2.4%
Other values (31) 1485
14.8%
(Missing) 739
 
7.4%
ValueCountFrequency (%)
1 493
 
4.9%
2 562
 
5.6%
3 461
 
4.6%
4 130
 
1.3%
5 177
 
1.8%
6 627
 
6.3%
7 3417
34.2%
8 50
 
0.5%
11 143
 
1.4%
12 278
 
2.8%
ValueCountFrequency (%)
74 1
 
< 0.1%
71 4
 
< 0.1%
69 1
 
< 0.1%
65 1
 
< 0.1%
64 4
 
< 0.1%
62 1
 
< 0.1%
61 1
 
< 0.1%
60 1
 
< 0.1%
59 33
0.3%
58 1
 
< 0.1%

LINE_KM
Real number (ℝ)

Distinct990
Distinct (%)9.9%
Missing6
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean60.36741
Minimum0
Maximum481.7
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T09:04:02.308875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.5
Q116.5
median25.8
Q349.5
95-th percentile334.8
Maximum481.7
Range481.7
Interquartile range (IQR)33

Descriptive statistics

Standard deviation92.355344
Coefficient of variation (CV)1.5298875
Kurtosis7.1403126
Mean60.36741
Median Absolute Deviation (MAD)12.2
Skewness2.7794782
Sum603311.9
Variance8529.5095
MonotonicityNot monotonic
2023-12-13T09:04:02.419589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.5 469
 
4.7%
28.8 182
 
1.8%
12.9 139
 
1.4%
10.9 121
 
1.2%
14.5 99
 
1.0%
17.9 95
 
0.9%
16.8 94
 
0.9%
13.2 93
 
0.9%
32.1 83
 
0.8%
9.7 81
 
0.8%
Other values (980) 8538
85.4%
ValueCountFrequency (%)
0.0 3
 
< 0.1%
0.5 1
 
< 0.1%
1.0 11
0.1%
1.2 1
 
< 0.1%
1.3 4
 
< 0.1%
1.4 3
 
< 0.1%
1.5 10
0.1%
1.6 3
 
< 0.1%
2.0 7
0.1%
2.1 2
 
< 0.1%
ValueCountFrequency (%)
481.7 2
< 0.1%
476.4 1
< 0.1%
476.3 2
< 0.1%
472.3 2
< 0.1%
470.6 2
< 0.1%
464.0 1
< 0.1%
462.0 2
< 0.1%
461.2 1
< 0.1%
461.1 1
< 0.1%
459.5 2
< 0.1%

ROUTE_ID
Real number (ℝ)

Distinct2542
Distinct (%)25.4%
Missing6
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean1073.9821
Minimum1
Maximum3346
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T09:04:02.520955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50
Q1300
median1087
Q31482
95-th percentile2732.35
Maximum3346
Range3345
Interquartile range (IQR)1182

Descriptive statistics

Standard deviation822.6313
Coefficient of variation (CV)0.7659637
Kurtosis0.025585013
Mean1073.9821
Median Absolute Deviation (MAD)649
Skewness0.71946118
Sum10733377
Variance676722.25
MonotonicityNot monotonic
2023-12-13T09:04:02.632864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1045 25
 
0.2%
1053 21
 
0.2%
1079 21
 
0.2%
64 21
 
0.2%
1048 21
 
0.2%
1052 20
 
0.2%
54 20
 
0.2%
13 19
 
0.2%
50 18
 
0.2%
1050 17
 
0.2%
Other values (2532) 9791
97.9%
ValueCountFrequency (%)
1 15
0.1%
2 8
0.1%
3 8
0.1%
4 12
0.1%
5 12
0.1%
6 6
 
0.1%
7 6
 
0.1%
8 8
0.1%
9 9
0.1%
10 12
0.1%
ValueCountFrequency (%)
3346 1
 
< 0.1%
3345 2
< 0.1%
3342 1
 
< 0.1%
3341 1
 
< 0.1%
3340 2
< 0.1%
3338 1
 
< 0.1%
3336 1
 
< 0.1%
3335 1
 
< 0.1%
3333 1
 
< 0.1%
3332 3
< 0.1%

RUN_TIMES
Real number (ℝ)

Distinct103
Distinct (%)1.0%
Missing6
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2.2158955
Minimum0
Maximum39
Zeros35
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T09:04:02.963044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.75
Q11
median1
Q32
95-th percentile7
Maximum39
Range39
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.4164673
Coefficient of variation (CV)1.090515
Kurtosis22.911758
Mean2.2158955
Median Absolute Deviation (MAD)0.33
Skewness3.7397484
Sum22145.66
Variance5.8393144
MonotonicityNot monotonic
2023-12-13T09:04:03.105175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 4924
49.2%
2.0 2347
23.5%
4.0 597
 
6.0%
3.0 501
 
5.0%
6.0 293
 
2.9%
5.0 249
 
2.5%
8.0 149
 
1.5%
7.0 135
 
1.4%
0.5 88
 
0.9%
10.0 57
 
0.6%
Other values (93) 654
 
6.5%
ValueCountFrequency (%)
0.0 35
0.4%
0.01 2
 
< 0.1%
0.02 5
 
0.1%
0.03 2
 
< 0.1%
0.04 2
 
< 0.1%
0.05 2
 
< 0.1%
0.07 3
 
< 0.1%
0.08 2
 
< 0.1%
0.09 6
 
0.1%
0.1 6
 
0.1%
ValueCountFrequency (%)
39.0 1
 
< 0.1%
34.0 1
 
< 0.1%
27.0 1
 
< 0.1%
26.0 1
 
< 0.1%
24.0 3
 
< 0.1%
22.0 4
 
< 0.1%
20.0 4
 
< 0.1%
18.0 12
0.1%
17.0 2
 
< 0.1%
16.0 21
0.2%

REMARKS
Text

MISSING 

Distinct135
Distinct (%)23.4%
Missing9422
Missing (%)94.2%
Memory size156.2 KiB
2023-12-13T09:04:03.325342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length31
Mean length9.0692042
Min length1

Characters and Unicode

Total characters5242
Distinct characters168
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)11.1%

Sample

1st row2013-03-05
2nd row공영
3rd row비수익노선
4th row2011.09.09 경유지변경
5th row고려여객(8회) 공동운수
ValueCountFrequency (%)
공동운수 123
 
13.6%
공영 67
 
7.4%
비수익 61
 
6.8%
비수익노선 46
 
5.1%
공동운행 44
 
4.9%
벽지노선 36
 
4.0%
공동배차 21
 
2.3%
삼성시민윤번 16
 
1.8%
고려여객(2회 16
 
1.8%
천일여객(6회 14
 
1.6%
Other values (170) 458
50.8%
2023-12-13T09:04:03.642002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
332
 
6.3%
공 295
 
5.6%
수 287
 
5.5%
) 234
 
4.5%
회 233
 
4.4%
( 231
 
4.4%
동 224
 
4.3%
운 212
 
4.0%
여 204
 
3.9%
객 203
 
3.9%
Other values (158) 2787
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3554
67.8%
Decimal Number 724
 
13.8%
Space Separator 332
 
6.3%
Close Punctuation 234
 
4.5%
Open Punctuation 231
 
4.4%
Other Punctuation 87
 
1.7%
Dash Punctuation 37
 
0.7%
Lowercase Letter 23
 
0.4%
Control 8
 
0.2%
Connector Punctuation 7
 
0.1%
Other values (2) 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 295
 
8.3%
수 287
 
8.1%
회 233
 
6.6%
동 224
 
6.3%
운 212
 
6.0%
여 204
 
5.7%
객 203
 
5.7%
비 110
 
3.1%
익 107
 
3.0%
일 107
 
3.0%
Other values (130) 1572
44.2%
Decimal Number
ValueCountFrequency (%)
1 180
24.9%
2 148
20.4%
0 137
18.9%
4 61
 
8.4%
6 56
 
7.7%
8 42
 
5.8%
3 39
 
5.4%
5 36
 
5.0%
9 19
 
2.6%
7 6
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 72
82.8%
, 10
 
11.5%
* 3
 
3.4%
/ 2
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
m 9
39.1%
k 7
30.4%
p 7
30.4%
Math Symbol
ValueCountFrequency (%)
+ 1
33.3%
> 1
33.3%
= 1
33.3%
Control
ValueCountFrequency (%)
4
50.0%
4
50.0%
Space Separator
ValueCountFrequency (%)
332
100.0%
Close Punctuation
ValueCountFrequency (%)
) 234
100.0%
Open Punctuation
ValueCountFrequency (%)
( 231
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
K 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3554
67.8%
Common 1663
31.7%
Latin 25
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 295
 
8.3%
수 287
 
8.1%
회 233
 
6.6%
동 224
 
6.3%
운 212
 
6.0%
여 204
 
5.7%
객 203
 
5.7%
비 110
 
3.1%
익 107
 
3.0%
일 107
 
3.0%
Other values (130) 1572
44.2%
Common
ValueCountFrequency (%)
332
20.0%
) 234
14.1%
( 231
13.9%
1 180
10.8%
2 148
8.9%
0 137
8.2%
. 72
 
4.3%
4 61
 
3.7%
6 56
 
3.4%
8 42
 
2.5%
Other values (14) 170
10.2%
Latin
ValueCountFrequency (%)
m 9
36.0%
k 7
28.0%
p 7
28.0%
K 2
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3554
67.8%
ASCII 1688
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
332
19.7%
) 234
13.9%
( 231
13.7%
1 180
10.7%
2 148
8.8%
0 137
8.1%
. 72
 
4.3%
4 61
 
3.6%
6 56
 
3.3%
8 42
 
2.5%
Other values (18) 195
11.6%
Hangul
ValueCountFrequency (%)
공 295
 
8.3%
수 287
 
8.1%
회 233
 
6.6%
동 224
 
6.3%
운 212
 
6.0%
여 204
 
5.7%
객 203
 
5.7%
비 110
 
3.1%
익 107
 
3.0%
일 107
 
3.0%
Other values (130) 1572
44.2%

H4_KM
Real number (ℝ)

Distinct967
Distinct (%)9.7%
Missing6
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean58.271003
Minimum0
Maximum481.7
Zeros39
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T09:04:03.756039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.2
Q116.4
median25.8
Q348.775
95-th percentile330.6
Maximum481.7
Range481.7
Interquartile range (IQR)32.375

Descriptive statistics

Standard deviation89.896201
Coefficient of variation (CV)1.5427262
Kurtosis7.6793359
Mean58.271003
Median Absolute Deviation (MAD)12.2
Skewness2.8749503
Sum582360.4
Variance8081.3269
MonotonicityNot monotonic
2023-12-13T09:04:03.866805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.5 453
 
4.5%
28.8 179
 
1.8%
12.9 134
 
1.3%
10.9 119
 
1.2%
14.5 97
 
1.0%
17.9 95
 
0.9%
16.8 95
 
0.9%
13.2 91
 
0.9%
32.1 81
 
0.8%
9.7 80
 
0.8%
Other values (957) 8570
85.7%
ValueCountFrequency (%)
0.0 39
0.4%
0.4 1
 
< 0.1%
0.5 1
 
< 0.1%
0.7 3
 
< 0.1%
0.9 1
 
< 0.1%
1.0 4
 
< 0.1%
1.2 1
 
< 0.1%
1.3 4
 
< 0.1%
1.4 3
 
< 0.1%
1.5 10
 
0.1%
ValueCountFrequency (%)
481.7 2
 
< 0.1%
476.3 2
 
< 0.1%
472.3 2
 
< 0.1%
470.6 2
 
< 0.1%
466.5 1
 
< 0.1%
464.0 1
 
< 0.1%
462.0 2
 
< 0.1%
461.2 1
 
< 0.1%
461.1 1
 
< 0.1%
457.1 5
0.1%

VIA_PLACE
Text

MISSING 

Distinct2639
Distinct (%)26.8%
Missing165
Missing (%)1.7%
Memory size156.2 KiB
2023-12-13T09:04:04.049459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length165
Median length120
Mean length14.414642
Min length1

Characters and Unicode

Total characters141768
Distinct characters478
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1277 ?
Unique (%)13.0%

Sample

1st row신복R,공업탑
2nd row고려,덕산,연초,옥포고
3rd row사곡
4th row연초,국산,옥포,덕포
5th row(고속도)
ValueCountFrequency (%)
고속도 241
 
2.3%
수월 150
 
1.4%
수월,연초,옥포,장승포 139
 
1.3%
국민은행,교동,터미널,내일동사무소 98
 
0.9%
옥림,지세포 85
 
0.8%
사곡 83
 
0.8%
고려,덕산 67
 
0.6%
토성-무전 65
 
0.6%
고려,덕산아파트,임전,연초,옥포,장승포 64
 
0.6%
내일동사무소,터미널,교동,국민은행 63
 
0.6%
Other values (2765) 9584
90.1%
2023-12-13T09:04:04.363460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 25254
 
17.8%
고 4088
 
2.9%
포 3298
 
2.3%
동 3213
 
2.3%
장 3030
 
2.1%
산 2890
 
2.0%
도 2756
 
1.9%
( 2371
 
1.7%
) 2273
 
1.6%
속 2112
 
1.5%
Other values (468) 90483
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105405
74.4%
Other Punctuation 26573
 
18.7%
Open Punctuation 2371
 
1.7%
Close Punctuation 2273
 
1.6%
Uppercase Letter 1915
 
1.4%
Dash Punctuation 1417
 
1.0%
Decimal Number 892
 
0.6%
Space Separator 819
 
0.6%
Math Symbol 52
 
< 0.1%
Lowercase Letter 51
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 4088
 
3.9%
포 3298
 
3.1%
동 3213
 
3.0%
장 3030
 
2.9%
산 2890
 
2.7%
도 2756
 
2.6%
속 2112
 
2.0%
대 1980
 
1.9%
교 1668
 
1.6%
사 1609
 
1.5%
Other values (413) 78761
74.7%
Uppercase Letter
ValueCountFrequency (%)
C 480
25.1%
I 419
21.9%
R 281
14.7%
A 215
11.2%
S 155
 
8.1%
G 140
 
7.3%
T 103
 
5.4%
J 58
 
3.0%
K 17
 
0.9%
B 14
 
0.7%
Other values (6) 33
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
c 10
19.6%
i 10
19.6%
e 10
19.6%
s 9
17.6%
a 3
 
5.9%
p 3
 
5.9%
q 1
 
2.0%
u 1
 
2.0%
m 1
 
2.0%
o 1
 
2.0%
Other values (2) 2
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 25254
95.0%
. 870
 
3.3%
@ 332
 
1.2%
\ 48
 
0.2%
: 33
 
0.1%
/ 29
 
0.1%
' 4
 
< 0.1%
; 2
 
< 0.1%
& 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 224
25.1%
2 212
23.8%
5 170
19.1%
3 83
 
9.3%
4 75
 
8.4%
0 58
 
6.5%
8 48
 
5.4%
7 14
 
1.6%
6 8
 
0.9%
Math Symbol
ValueCountFrequency (%)
↔ 30
57.7%
→ 12
 
23.1%
~ 6
 
11.5%
> 2
 
3.8%
< 2
 
3.8%
Open Punctuation
ValueCountFrequency (%)
( 2371
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2273
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1417
100.0%
Space Separator
ValueCountFrequency (%)
819
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105405
74.4%
Common 34397
 
24.3%
Latin 1966
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 4088
 
3.9%
포 3298
 
3.1%
동 3213
 
3.0%
장 3030
 
2.9%
산 2890
 
2.7%
도 2756
 
2.6%
속 2112
 
2.0%
대 1980
 
1.9%
교 1668
 
1.6%
사 1609
 
1.5%
Other values (413) 78761
74.7%
Latin
ValueCountFrequency (%)
C 480
24.4%
I 419
21.3%
R 281
14.3%
A 215
10.9%
S 155
 
7.9%
G 140
 
7.1%
T 103
 
5.2%
J 58
 
3.0%
K 17
 
0.9%
B 14
 
0.7%
Other values (18) 84
 
4.3%
Common
ValueCountFrequency (%)
, 25254
73.4%
( 2371
 
6.9%
) 2273
 
6.6%
- 1417
 
4.1%
. 870
 
2.5%
819
 
2.4%
@ 332
 
1.0%
1 224
 
0.7%
2 212
 
0.6%
5 170
 
0.5%
Other values (17) 455
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105391
74.3%
ASCII 36321
 
25.6%
Arrows 42
 
< 0.1%
Compat Jamo 14
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 25254
69.5%
( 2371
 
6.5%
) 2273
 
6.3%
- 1417
 
3.9%
. 870
 
2.4%
819
 
2.3%
C 480
 
1.3%
I 419
 
1.2%
@ 332
 
0.9%
R 281
 
0.8%
Other values (43) 1805
 
5.0%
Hangul
ValueCountFrequency (%)
고 4088
 
3.9%
포 3298
 
3.1%
동 3213
 
3.0%
장 3030
 
2.9%
산 2890
 
2.7%
도 2756
 
2.6%
속 2112
 
2.0%
대 1980
 
1.9%
교 1668
 
1.6%
사 1609
 
1.5%
Other values (407) 78747
74.7%
Arrows
ValueCountFrequency (%)
↔ 30
71.4%
→ 12
 
28.6%
Compat Jamo
ValueCountFrequency (%)
ㅡ 5
35.7%
ㅣ 3
21.4%
ㅎ 2
 
14.3%
ㅏ 2
 
14.3%
ㅖ 1
 
7.1%
ㆍ 1
 
7.1%

H2_KM
Unsupported

REJECTED  UNSUPPORTED 

Missing6
Missing (%)0.1%
Memory size156.2 KiB

STR_PLACE
Text

Distinct443
Distinct (%)4.4%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2023-12-13T09:04:04.604441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length3.0127114
Min length2

Characters and Unicode

Total characters30100
Distinct characters257
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)1.4%

Sample

1st row서울(구의)
2nd row터미널
3rd row터미널
4th row고현
5th row대구
ValueCountFrequency (%)
터미널 1590
 
15.9%
고현 941
 
9.4%
밀양역 421
 
4.2%
마산 368
 
3.7%
대구 332
 
3.3%
고현터미널 281
 
2.8%
진주 274
 
2.7%
서울(남부 272
 
2.7%
능포 270
 
2.7%
부산(서부 265
 
2.6%
Other values (433) 4995
49.9%
2023-12-13T09:04:04.974792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 2098
 
7.0%
미 2090
 
6.9%
널 2061
 
6.8%
고 1391
 
4.6%
산 1312
 
4.4%
현 1293
 
4.3%
부 1250
 
4.2%
대 909
 
3.0%
양 821
 
2.7%
서 686
 
2.3%
Other values (247) 16189
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28550
94.9%
Open Punctuation 679
 
2.3%
Close Punctuation 679
 
2.3%
Uppercase Letter 119
 
0.4%
Decimal Number 29
 
0.1%
Space Separator 18
 
0.1%
Other Punctuation 18
 
0.1%
Lowercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 2098
 
7.3%
미 2090
 
7.3%
널 2061
 
7.2%
고 1391
 
4.9%
산 1312
 
4.6%
현 1293
 
4.5%
부 1250
 
4.4%
대 909
 
3.2%
양 821
 
2.9%
서 686
 
2.4%
Other values (231) 14639
51.3%
Uppercase Letter
ValueCountFrequency (%)
T 50
42.0%
R 36
30.3%
A 32
26.9%
P 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
@ 10
55.6%
, 6
33.3%
; 1
 
5.6%
. 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
s 6
75.0%
i 1
 
12.5%
c 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
2 20
69.0%
1 9
31.0%
Open Punctuation
ValueCountFrequency (%)
( 679
100.0%
Close Punctuation
ValueCountFrequency (%)
) 679
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28550
94.9%
Common 1423
 
4.7%
Latin 127
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 2098
 
7.3%
미 2090
 
7.3%
널 2061
 
7.2%
고 1391
 
4.9%
산 1312
 
4.6%
현 1293
 
4.5%
부 1250
 
4.4%
대 909
 
3.2%
양 821
 
2.9%
서 686
 
2.4%
Other values (231) 14639
51.3%
Common
ValueCountFrequency (%)
( 679
47.7%
) 679
47.7%
2 20
 
1.4%
18
 
1.3%
@ 10
 
0.7%
1 9
 
0.6%
, 6
 
0.4%
; 1
 
0.1%
. 1
 
0.1%
Latin
ValueCountFrequency (%)
T 50
39.4%
R 36
28.3%
A 32
25.2%
s 6
 
4.7%
i 1
 
0.8%
c 1
 
0.8%
P 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28549
94.8%
ASCII 1550
 
5.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 2098
 
7.3%
미 2090
 
7.3%
널 2061
 
7.2%
고 1391
 
4.9%
산 1312
 
4.6%
현 1293
 
4.5%
부 1250
 
4.4%
대 909
 
3.2%
양 821
 
2.9%
서 686
 
2.4%
Other values (230) 14638
51.3%
ASCII
ValueCountFrequency (%)
( 679
43.8%
) 679
43.8%
T 50
 
3.2%
R 36
 
2.3%
A 32
 
2.1%
2 20
 
1.3%
18
 
1.2%
@ 10
 
0.6%
1 9
 
0.6%
, 6
 
0.4%
Other values (6) 11
 
0.7%
Compat Jamo
ValueCountFrequency (%)
ㅅ 1
100.0%

REMOTE_KM
Unsupported

REJECTED  UNSUPPORTED 

Missing6
Missing (%)0.1%
Memory size156.2 KiB

N4L_KM
Unsupported

REJECTED  UNSUPPORTED 

Missing6
Missing (%)0.1%
Memory size156.2 KiB

N4H_KM
Unsupported

REJECTED  UNSUPPORTED 

Missing6
Missing (%)0.1%
Memory size156.2 KiB

Unnamed: 22
Categorical

IMBALANCE 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9956 
,0"
 
16
0
 
8
문"
 
4
진주역"
 
4
Other values (7)
 
12

Length

Max length4
Median length4
Mean length3.9939
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9956
99.6%
,0" 16
 
0.2%
0 8
 
0.1%
문" 4
 
< 0.1%
진주역" 4
 
< 0.1%
오" 3
 
< 0.1%
오죽광" 2
 
< 0.1%
중앙광" 2
 
< 0.1%
장" 2
 
< 0.1%
대림A 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Length

2023-12-13T09:04:05.088068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9956
99.6%
0 24
 
0.2%
문 4
 
< 0.1%
진주역 4
 
< 0.1%
오 3
 
< 0.1%
오죽광 2
 
< 0.1%
중앙광 2
 
< 0.1%
장 2
 
< 0.1%
대림a 1
 
< 0.1%
반성 1
 
< 0.1%

Unnamed: 23
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9957 
0
 
18
진양호
 
18
이현동
 
5
경상대
 
1

Length

Max length4
Median length4
Mean length3.992
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9957
99.6%
0 18
 
0.2%
진양호 18
 
0.2%
이현동 5
 
0.1%
경상대 1
 
< 0.1%
신당 1
 
< 0.1%

Length

2023-12-13T09:04:05.187398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:04:05.297633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9957
99.6%
0 18
 
0.2%
진양호 18
 
0.2%
이현동 5
 
< 0.1%
경상대 1
 
< 0.1%
신당 1
 
< 0.1%

Unnamed: 24
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9957 
0
 
24
진양호
 
10
경상대
 
8
,0"
 
1

Length

Max length4
Median length4
Mean length3.9909
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9957
99.6%
0 24
 
0.2%
진양호 10
 
0.1%
경상대 8
 
0.1%
,0" 1
 
< 0.1%

Length

2023-12-13T09:04:05.391891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:04:05.473894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9957
99.6%
0 25
 
0.2%
진양호 10
 
0.1%
경상대 8
 
0.1%

Unnamed: 25
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9957 
0
 
42
경상대
 
1

Length

Max length4
Median length4
Mean length3.9873
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9957
99.6%
0 42
 
0.4%
경상대 1
 
< 0.1%

Length

2023-12-13T09:04:05.567396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:04:05.664506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9957
99.6%
0 42
 
0.4%
경상대 1
 
< 0.1%

Unnamed: 26
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9957 
0
 
43

Length

Max length4
Median length4
Mean length3.9871
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9957
99.6%
0 43
 
0.4%

Length

2023-12-13T09:04:05.752160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:04:05.844035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9957
99.6%
0 43
 
0.4%

Unnamed: 27
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9981 
0
 
19

Length

Max length4
Median length4
Mean length3.9943
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9981
99.8%
0 19
 
0.2%

Length

2023-12-13T09:04:05.934235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:04:06.013514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9981
99.8%
0 19
 
0.2%

Unnamed: 28
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
0
 
1

Length

Max length4
Median length4
Mean length3.9997
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9999
> 99.9%
0 1
 
< 0.1%

Length

2023-12-13T09:04:06.093020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:04:06.167837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
0 1
 
< 0.1%

Sample

NoSTR_YMDSTR_PUBLIC_IDEND_PLACEENT_DTUPD_DTLINE_IDTOT_KMEND_YMDUSE_YNEND_PUBLIC_IDLINE_KMROUTE_IDRUN_TIMESREMARKSH4_KMVIA_PLACEH2_KMSTR_PLACEREMOTE_KMN4L_KMN4H_KMUnnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28
279627922010010142울산20,100,90720,101,10910391390Y41389.210260.37<NA>375.8신복R,공업탑0서울(구의)022.70<NA><NA><NA><NA><NA><NA><NA>
3368333663201811017고현20,181,11320,181,113173335.8<NA>Y735.816111.0<NA>35.8고려,덕산,연초,옥포고0터미널0.00.00<NA><NA><NA><NA><NA><NA><NA>
2012820108201403037부춘20,140,40620,140,406143739.4<NA><NA>719.77892.0<NA>19.7사곡0터미널34.800<NA><NA><NA><NA><NA><NA><NA>
1313613118201904117대계20,200,32520,200,325107521.1<NA>Y721.128671.0<NA>21.1연초,국산,옥포,덕포0고현000<NA><NA><NA><NA><NA><NA><NA>
24411243912015031930울산20,180,41120,180,4111093556<NA>Y30111.215175.0<NA>111.2(고속도)0대구000<NA><NA><NA><NA><NA><NA><NA>
1366513647199505016밀양역20,120,11820,120,1186325.8<NA><NA>612.91302.0<NA>12.9국민은행,교동,터미널,내일동사무소0밀양역000<NA><NA><NA><NA><NA><NA><NA>
9310929220100601<NA>거제대교20,101,02620,101,02645320<NA><NA>16.01722.0<NA>16.0토성-무전0미수08.57.5<NA><NA><NA><NA><NA><NA><NA>
5237522819960730<NA>고성20,150,50820,150,508613.4<NA><NA><NA>13.410081.0<NA>13.4교동-무량-양화-덕선0고성013.40<NA><NA><NA><NA><NA><NA><NA>
1891918899201108237망 치20,120,61120,120,61140116.7<NA><NA>716.715391.0<NA>16.7옥림,지세포,구조라0능포000<NA><NA><NA><NA><NA><NA><NA>
1637616356201303047능포20,130,41120,130,411133644.6<NA><NA>722.35972.0<NA>22.3고려,수월,연초,옥포시내,장승포0터미널000<NA><NA><NA><NA><NA><NA><NA>
NoSTR_YMDSTR_PUBLIC_IDEND_PLACEENT_DTUPD_DTLINE_IDTOT_KMEND_YMDUSE_YNEND_PUBLIC_IDLINE_KMROUTE_IDRUN_TIMESREMARKSH4_KMVIA_PLACEH2_KMSTR_PLACEREMOTE_KMN4L_KMN4H_KMUnnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28
2791427894202007227고현20,201,12620,201,126119510.9<NA>Y710.932201.0<NA>10.9수월,아이파크2차,양정,대우푸르지오,문동,상동0고현000<NA><NA><NA><NA><NA><NA><NA>
29142291222018092142부산(서부)20,181,02920,181,0291317406.520180926N40406.516481.0<NA>406.5(경부중부내륙)고속도장유(고속도)(경부중부내륙)고속도장유(고속도)0서울(남부)000<NA><NA><NA><NA><NA><NA><NA>
42884281200808268구포20,101,20820,101,2088160.80<NA>4020.1408.0<NA>20.1남부시장,양산시청0북정020.10<NA><NA><NA><NA><NA><NA><NA>
21134211142018010130부산(동부)20,180,22020,180,2201075380.4<NA>Y3063.414886.0<NA>63.4(고속도,만덕터널)동래전철역앞0마산000<NA><NA><NA><NA><NA><NA><NA>
2691426894199607116칠성20,150,50220,150,5021721<NA><NA>621.01771.0<NA>21.0밀양역,임천,용성0터미널0210<NA><NA><NA><NA><NA><NA><NA>
2001119991201303047학동20,130,42020,130,420526109.2<NA><NA>727.316174.0비수익27.3사곡,거제,동부,연담,평지0고현000<NA><NA><NA><NA><NA><NA><NA>
3726037240202007227신현교20,210,32420,210,324124910<NA>Y710.033241.0<NA>10.0경남은행,고현시장,시청,포로수용소,용산,벽산,덕산베스트3차,벽산,용산,포로수용소,시청,고현시장,수협0고현0.00.00<NA><NA><NA><NA><NA><NA><NA>
37552375322010010120박곡20,210,81220,210,8162910<NA>N2018.812270.000.0내천0합천0.00.00<NA><NA><NA><NA><NA><NA><NA>
2266722647201503187옥동20,150,41620,150,52669537.1<NA>Y737.119591.0<NA>37.1사고,성포,대교,하둔,죽전경유0고현000<NA><NA><NA><NA><NA><NA><NA>
45574550202007227터미널20,200,80320,200,803192832.7<NA>Y710.921073.0<NA>10.9상동,대우푸리지오0터미널000<NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

STR_PUBLIC_IDEND_PLACEENT_DTUPD_DTLINE_IDTOT_KMEND_YMDUSE_YNEND_PUBLIC_IDLINE_KMROUTE_IDRUN_TIMESREMARKSH4_KMVIA_PLACESTR_PLACEUnnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28# duplicates
0000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6
11인천20,170,62320,170,6231201400.8<NA>Y47400.811691.0<NA>400.8마산창원<NA><NA><NA><NA><NA><NA><NA>2
241진주20,200,82020,200,8201341160.2<NA>Y2160.212881.0<NA>160.2공업탑,무거동(신복R),양산울산<NA><NA><NA><NA><NA><NA><NA>2
342양산20,171,20620,171,2061107371.4<NA>Y8371.411771.0<NA>371.4<NA>서울(구의)<NA><NA><NA><NA><NA><NA><NA>2
442울산20,190,42120,190,4211282143.5<NA>Y41350.112310.41<NA>350.1(구)언양JC정류소,신복R,공업탑동서울<NA><NA><NA><NA><NA><NA><NA>2
542해운대20,170,82120,170,821121071.4<NA>Y40396.511740.18<NA>396.5<NA>서울(구의)<NA><NA><NA><NA><NA><NA><NA>2
647부산(동부)20,171,02320,171,0231215457.1<NA>Y40457.111761.0<NA>457.1송도국제도시인천국제공항<NA><NA><NA><NA><NA><NA><NA>2
749창원20,200,32520,200,3251310424.6<NA>Y1424.612531.0<NA>424.6부천,마산고양(백석)<NA><NA><NA><NA><NA><NA><NA>2