Overview

Dataset statistics

Number of variables12
Number of observations74
Missing cells3
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory103.8 B

Variable types

Categorical3
Text3
Numeric6

Dataset

Description장성군 버스운행정보 데이터로 노선구분, 노선번호, 기점, 경유지, 종점, 거리, 횟수, 1일(편도)운행거리, 1일(왕복)운행거리,시간 정보를 제공합니다.
URLhttps://www.data.go.kr/data/3033265/fileData.do

Alerts

노선구분 has constant value ""Constant
편도거리(Km) is highly overall correlated with 왕복거리(Km)High correlation
왕복거리(Km) is highly overall correlated with 편도거리(Km)High correlation
편도 운행횟수 is highly overall correlated with 왕복 운행횟수 and 2 other fieldsHigh correlation
왕복 운행횟수 is highly overall correlated with 편도 운행횟수 and 2 other fieldsHigh correlation
1일(편도)운행거리 is highly overall correlated with 편도 운행횟수 and 2 other fieldsHigh correlation
1일(왕복)운행거리 is highly overall correlated with 편도 운행횟수 and 2 other fieldsHigh correlation
기점 is highly imbalanced (65.8%)Imbalance
시 간 has 3 (4.1%) missing valuesMissing
노선번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:12:58.374711
Analysis finished2023-12-12 14:13:02.697997
Duration4.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
관내노선
74 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관내노선 74
100.0%

Length

2023-12-12T23:13:02.777959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:13:02.890481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관내노선 74
100.0%

노선번호
Text

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size724.0 B
2023-12-12T23:13:03.132985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.9864865
Min length1

Characters and Unicode

Total characters221
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)100.0%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5
ValueCountFrequency (%)
1 1
 
1.4%
87 1
 
1.4%
85 1
 
1.4%
84 1
 
1.4%
83 1
 
1.4%
82 1
 
1.4%
81 1
 
1.4%
80 1
 
1.4%
71 1
 
1.4%
70 1
 
1.4%
Other values (64) 64
86.5%
2023-12-12T23:13:03.564613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 47
21.3%
0 35
15.8%
2 24
10.9%
3 18
 
8.1%
- 17
 
7.7%
번 15
 
6.8%
4 11
 
5.0%
9 9
 
4.1%
8 8
 
3.6%
6 8
 
3.6%
Other values (16) 29
13.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 169
76.5%
Other Letter 35
 
15.8%
Dash Punctuation 17
 
7.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 15
42.9%
진 3
 
8.6%
서 2
 
5.7%
월 2
 
5.7%
원 2
 
5.7%
삼 2
 
5.7%
정 1
 
2.9%
아 1
 
2.9%
비 1
 
2.9%
령 1
 
2.9%
Other values (5) 5
 
14.3%
Decimal Number
ValueCountFrequency (%)
1 47
27.8%
0 35
20.7%
2 24
14.2%
3 18
 
10.7%
4 11
 
6.5%
9 9
 
5.3%
8 8
 
4.7%
6 8
 
4.7%
5 5
 
3.0%
7 4
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 186
84.2%
Hangul 35
 
15.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
번 15
42.9%
진 3
 
8.6%
서 2
 
5.7%
월 2
 
5.7%
원 2
 
5.7%
삼 2
 
5.7%
정 1
 
2.9%
아 1
 
2.9%
비 1
 
2.9%
령 1
 
2.9%
Other values (5) 5
 
14.3%
Common
ValueCountFrequency (%)
1 47
25.3%
0 35
18.8%
2 24
12.9%
3 18
 
9.7%
- 17
 
9.1%
4 11
 
5.9%
9 9
 
4.8%
8 8
 
4.3%
6 8
 
4.3%
5 5
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 186
84.2%
Hangul 35
 
15.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 47
25.3%
0 35
18.8%
2 24
12.9%
3 18
 
9.7%
- 17
 
9.1%
4 11
 
5.9%
9 9
 
4.8%
8 8
 
4.3%
6 8
 
4.3%
5 5
 
2.7%
Hangul
ValueCountFrequency (%)
번 15
42.9%
진 3
 
8.6%
서 2
 
5.7%
월 2
 
5.7%
원 2
 
5.7%
삼 2
 
5.7%
정 1
 
2.9%
아 1
 
2.9%
비 1
 
2.9%
령 1
 
2.9%
Other values (5) 5
 
14.3%

기점
Categorical

IMBALANCE 

Distinct6
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size724.0 B
장성
63 
사거리
 
6
광주
 
2
사창
 
1
초동
 
1

Length

Max length3
Median length2
Mean length2.0945946
Min length2

Unique

Unique3 ?
Unique (%)4.1%

Sample

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

Common Values

ValueCountFrequency (%)
장성 63
85.1%
사거리 6
 
8.1%
광주 2
 
2.7%
사창 1
 
1.4%
초동 1
 
1.4%
상무대 1
 
1.4%

Length

2023-12-12T23:13:03.760062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:13:03.911227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장성 63
85.1%
사거리 6
 
8.1%
광주 2
 
2.7%
사창 1
 
1.4%
초동 1
 
1.4%
상무대 1
 
1.4%

경유지
Text

Distinct70
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size724.0 B
2023-12-12T23:13:04.183446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length20
Mean length11.054054
Min length2

Characters and Unicode

Total characters818
Distinct characters132
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

Unique66 ?
Unique (%)89.2%

Sample

1st row신촌
2nd row신촌,청룡유탕
3rd row성산,신촌(청룡)
4th row군청,문화센터,행복마을,황룡시장
5th row군청,교육청,구산동
ValueCountFrequency (%)
신흥,광암 2
 
2.7%
신흥,율리,궁평,광암 2
 
2.7%
밀등,신흥,광암 2
 
2.7%
대악,약수 2
 
2.7%
주산 1
 
1.3%
동화,통안,동계,매실,구석,황룡중 1
 
1.3%
동화,사창,염치,덕산 1
 
1.3%
주공,동화,사창,삼서,옥동 1
 
1.3%
사창,신기(아계),화산,절암 1
 
1.3%
사창,아계,절암,자초 1
 
1.3%
Other values (61) 61
81.3%
2023-12-12T23:13:04.701963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 211
25.8%
산 36
 
4.4%
신 28
 
3.4%
동 26
 
3.2%
화 20
 
2.4%
암 18
 
2.2%
서 18
 
2.2%
흥 17
 
2.1%
삼 15
 
1.8%
사 15
 
1.8%
Other values (122) 414
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 598
73.1%
Other Punctuation 211
 
25.8%
Open Punctuation 4
 
0.5%
Close Punctuation 4
 
0.5%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 36
 
6.0%
신 28
 
4.7%
동 26
 
4.3%
화 20
 
3.3%
암 18
 
3.0%
서 18
 
3.0%
흥 17
 
2.8%
삼 15
 
2.5%
사 15
 
2.5%
창 14
 
2.3%
Other values (118) 391
65.4%
Other Punctuation
ValueCountFrequency (%)
, 211
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 598
73.1%
Common 220
 
26.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 36
 
6.0%
신 28
 
4.7%
동 26
 
4.3%
화 20
 
3.3%
암 18
 
3.0%
서 18
 
3.0%
흥 17
 
2.8%
삼 15
 
2.5%
사 15
 
2.5%
창 14
 
2.3%
Other values (118) 391
65.4%
Common
ValueCountFrequency (%)
, 211
95.9%
( 4
 
1.8%
) 4
 
1.8%
1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 598
73.1%
ASCII 220
 
26.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 211
95.9%
( 4
 
1.8%
) 4
 
1.8%
1
 
0.5%
Hangul
ValueCountFrequency (%)
산 36
 
6.0%
신 28
 
4.7%
동 26
 
4.3%
화 20
 
3.3%
암 18
 
3.0%
서 18
 
3.0%
흥 17
 
2.8%
삼 15
 
2.5%
사 15
 
2.5%
창 14
 
2.3%
Other values (118) 391
65.4%

종 점
Categorical

Distinct30
Distinct (%)40.5%
Missing0
Missing (%)0.0%
Memory size724.0 B
장성
13 
상무대
6 
사거리
6 
광주
 
4
금곡
 
4
Other values (25)
41 

Length

Max length3
Median length2
Mean length2.3243243
Min length2

Unique

Unique17 ?
Unique (%)23.0%

Sample

1st row부흥리
2nd row서동
3rd row유탕
4th row장성
5th row장성

Common Values

ValueCountFrequency (%)
장성 13
17.6%
상무대 6
 
8.1%
사거리 6
 
8.1%
광주 4
 
5.4%
금곡 4
 
5.4%
백양사 4
 
5.4%
비아 3
 
4.1%
성진원 3
 
4.1%
유태 3
 
4.1%
사창 3
 
4.1%
Other values (20) 25
33.8%

Length

2023-12-12T23:13:04.885443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장성 13
17.6%
사거리 6
 
8.1%
상무대 6
 
8.1%
광주 4
 
5.4%
금곡 4
 
5.4%
백양사 4
 
5.4%
사창 3
 
4.1%
대치 3
 
4.1%
생촌 3
 
4.1%
유태 3
 
4.1%
Other values (20) 25
33.8%

편도거리(Km)
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.447297
Minimum5
Maximum54.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2023-12-12T23:13:05.056758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6.145
Q115.175
median20.95
Q327.825
95-th percentile36.47
Maximum54.2
Range49.2
Interquartile range (IQR)12.65

Descriptive statistics

Standard deviation9.8391617
Coefficient of variation (CV)0.45875998
Kurtosis0.89240274
Mean21.447297
Median Absolute Deviation (MAD)6.8
Skewness0.58549003
Sum1587.1
Variance96.809102
MonotonicityNot monotonic
2023-12-12T23:13:05.228684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.5 3
 
4.1%
5.3 2
 
2.7%
11.5 2
 
2.7%
19.1 2
 
2.7%
36.6 2
 
2.7%
24.4 1
 
1.4%
13.8 1
 
1.4%
21.6 1
 
1.4%
21.1 1
 
1.4%
25.9 1
 
1.4%
Other values (58) 58
78.4%
ValueCountFrequency (%)
5.0 1
1.4%
5.1 1
1.4%
5.3 2
2.7%
6.6 1
1.4%
6.8 1
1.4%
7.5 1
1.4%
8.3 1
1.4%
8.5 1
1.4%
9.1 1
1.4%
10.7 1
1.4%
ValueCountFrequency (%)
54.2 1
1.4%
48.0 1
1.4%
36.6 2
2.7%
36.4 1
1.4%
36.2 1
1.4%
34.8 1
1.4%
33.9 1
1.4%
32.8 1
1.4%
32.5 1
1.4%
30.5 1
1.4%

왕복거리(Km)
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.894595
Minimum10
Maximum108.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2023-12-12T23:13:05.375819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile12.29
Q130.35
median41.9
Q355.65
95-th percentile72.94
Maximum108.4
Range98.4
Interquartile range (IQR)25.3

Descriptive statistics

Standard deviation19.678323
Coefficient of variation (CV)0.45875998
Kurtosis0.89240274
Mean42.894595
Median Absolute Deviation (MAD)13.6
Skewness0.58549003
Sum3174.2
Variance387.23641
MonotonicityNot monotonic
2023-12-12T23:13:05.568446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53.0 3
 
4.1%
10.6 2
 
2.7%
23.0 2
 
2.7%
38.2 2
 
2.7%
73.2 2
 
2.7%
48.8 1
 
1.4%
27.6 1
 
1.4%
43.2 1
 
1.4%
42.2 1
 
1.4%
51.8 1
 
1.4%
Other values (58) 58
78.4%
ValueCountFrequency (%)
10.0 1
1.4%
10.2 1
1.4%
10.6 2
2.7%
13.2 1
1.4%
13.6 1
1.4%
15.0 1
1.4%
16.6 1
1.4%
17.0 1
1.4%
18.2 1
1.4%
21.4 1
1.4%
ValueCountFrequency (%)
108.4 1
1.4%
96.0 1
1.4%
73.2 2
2.7%
72.8 1
1.4%
72.4 1
1.4%
69.6 1
1.4%
67.8 1
1.4%
65.6 1
1.4%
65.0 1
1.4%
61.0 1
1.4%

편도 운행횟수
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7972973
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2023-12-12T23:13:05.714431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q36
95-th percentile13.4
Maximum84
Range83
Interquartile range (IQR)4

Descriptive statistics

Standard deviation10.025966
Coefficient of variation (CV)1.7294207
Kurtosis52.026517
Mean5.7972973
Median Absolute Deviation (MAD)2
Skewness6.7265175
Sum429
Variance100.51999
MonotonicityNot monotonic
2023-12-12T23:13:05.823142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 23
31.1%
6 10
13.5%
1 9
 
12.2%
3 7
 
9.5%
10 6
 
8.1%
4 6
 
8.1%
12 2
 
2.7%
5 2
 
2.7%
18 2
 
2.7%
8 2
 
2.7%
Other values (4) 5
 
6.8%
ValueCountFrequency (%)
1 9
 
12.2%
2 23
31.1%
3 7
 
9.5%
4 6
 
8.1%
5 2
 
2.7%
6 10
13.5%
7 2
 
2.7%
8 2
 
2.7%
9 1
 
1.4%
10 6
 
8.1%
ValueCountFrequency (%)
84 1
 
1.4%
18 2
 
2.7%
16 1
 
1.4%
12 2
 
2.7%
10 6
8.1%
9 1
 
1.4%
8 2
 
2.7%
7 2
 
2.7%
6 10
13.5%
5 2
 
2.7%

왕복 운행횟수
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8986486
Minimum0.5
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2023-12-12T23:13:05.928062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile0.5
Q11
median1.5
Q33
95-th percentile6.7
Maximum42
Range41.5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.012983
Coefficient of variation (CV)1.7294207
Kurtosis52.026517
Mean2.8986486
Median Absolute Deviation (MAD)1
Skewness6.7265175
Sum214.5
Variance25.129998
MonotonicityNot monotonic
2023-12-12T23:13:06.356956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1.0 23
31.1%
3.0 10
13.5%
0.5 9
 
12.2%
1.5 7
 
9.5%
5.0 6
 
8.1%
2.0 6
 
8.1%
6.0 2
 
2.7%
2.5 2
 
2.7%
9.0 2
 
2.7%
4.0 2
 
2.7%
Other values (4) 5
 
6.8%
ValueCountFrequency (%)
0.5 9
 
12.2%
1.0 23
31.1%
1.5 7
 
9.5%
2.0 6
 
8.1%
2.5 2
 
2.7%
3.0 10
13.5%
3.5 2
 
2.7%
4.0 2
 
2.7%
4.5 1
 
1.4%
5.0 6
 
8.1%
ValueCountFrequency (%)
42.0 1
 
1.4%
9.0 2
 
2.7%
8.0 1
 
1.4%
6.0 2
 
2.7%
5.0 6
8.1%
4.5 1
 
1.4%
4.0 2
 
2.7%
3.5 2
 
2.7%
3.0 10
13.5%
2.5 2
 
2.7%

1일(편도)운행거리
Real number (ℝ)

HIGH CORRELATION 

Distinct72
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.705405
Minimum4.55
Maximum991.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2023-12-12T23:13:06.489794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.55
5-th percentile8.9775
Q118.725
median31.9
Q369.675
95-th percentile143.255
Maximum991.2
Range986.65
Interquartile range (IQR)50.95

Descriptive statistics

Standard deviation117.81064
Coefficient of variation (CV)1.9731989
Kurtosis55.097444
Mean59.705405
Median Absolute Deviation (MAD)17.95
Skewness7.0079171
Sum4418.2
Variance13879.346
MonotonicityNot monotonic
2023-12-12T23:13:06.689619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.5 3
 
4.1%
22.5 1
 
1.4%
4.55 1
 
1.4%
43.2 1
 
1.4%
21.1 1
 
1.4%
73.2 1
 
1.4%
77.7 1
 
1.4%
36.6 1
 
1.4%
123.5 1
 
1.4%
84.8 1
 
1.4%
Other values (62) 62
83.8%
ValueCountFrequency (%)
4.55 1
1.4%
5.0 1
1.4%
5.3 1
1.4%
8.75 1
1.4%
9.1 1
1.4%
9.55 1
1.4%
10.7 1
1.4%
10.9 1
1.4%
11.8 1
1.4%
13.2 1
1.4%
ValueCountFrequency (%)
991.2 1
1.4%
218.7 1
1.4%
191.2 1
1.4%
174.0 1
1.4%
126.7 1
1.4%
123.5 1
1.4%
104.4 1
1.4%
103.5 1
1.4%
101.7 1
1.4%
90.3 1
1.4%

1일(왕복)운행거리
Real number (ℝ)

HIGH CORRELATION 

Distinct72
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean119.41081
Minimum9.1
Maximum1982.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2023-12-12T23:13:06.870059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.1
5-th percentile17.955
Q137.45
median63.8
Q3139.35
95-th percentile286.51
Maximum1982.4
Range1973.3
Interquartile range (IQR)101.9

Descriptive statistics

Standard deviation235.62128
Coefficient of variation (CV)1.9731989
Kurtosis55.097444
Mean119.41081
Median Absolute Deviation (MAD)35.9
Skewness7.0079171
Sum8836.4
Variance55517.385
MonotonicityNot monotonic
2023-12-12T23:13:07.060694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53.0 3
 
4.1%
45.0 1
 
1.4%
9.1 1
 
1.4%
86.4 1
 
1.4%
42.2 1
 
1.4%
146.4 1
 
1.4%
155.4 1
 
1.4%
73.2 1
 
1.4%
247.0 1
 
1.4%
169.6 1
 
1.4%
Other values (62) 62
83.8%
ValueCountFrequency (%)
9.1 1
1.4%
10.0 1
1.4%
10.6 1
1.4%
17.5 1
1.4%
18.2 1
1.4%
19.1 1
1.4%
21.4 1
1.4%
21.8 1
1.4%
23.6 1
1.4%
26.4 1
1.4%
ValueCountFrequency (%)
1982.4 1
1.4%
437.4 1
1.4%
382.4 1
1.4%
348.0 1
1.4%
253.4 1
1.4%
247.0 1
1.4%
208.8 1
1.4%
207.0 1
1.4%
203.4 1
1.4%
180.6 1
1.4%

시 간
Text

MISSING 

Distinct68
Distinct (%)95.8%
Missing3
Missing (%)4.1%
Memory size724.0 B
2023-12-12T23:13:07.547124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length47
Mean length16.887324
Min length4

Characters and Unicode

Total characters1199
Distinct characters41
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)91.5%

Sample

1st row07:50 14:00 18:30
2nd row06:30(청룡) 09:00(청룡) 12:00 15:00 18:00
3rd row19:30
4th row07:55 10:55 13:55 16:55
5th row08:25 11:25 14:25 17:25
ValueCountFrequency (%)
06:40 3
 
1.5%
14:10 3
 
1.5%
18:00 3
 
1.5%
16:00 3
 
1.5%
06:45 3
 
1.5%
20:30 3
 
1.5%
17:30 3
 
1.5%
16:10 3
 
1.5%
11:10 3
 
1.5%
10:10 3
 
1.5%
Other values (130) 174
85.3%
2023-12-12T23:13:08.258819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 261
21.8%
: 200
16.7%
1 178
14.8%
133
11.1%
5 89
 
7.4%
4 57
 
4.8%
3 49
 
4.1%
2 43
 
3.6%
6 34
 
2.8%
7 32
 
2.7%
Other values (31) 123
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 792
66.1%
Other Punctuation 200
 
16.7%
Space Separator 133
 
11.1%
Other Letter 38
 
3.2%
Close Punctuation 17
 
1.4%
Open Punctuation 17
 
1.4%
Math Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 3
 
7.9%
분 2
 
5.3%
메 2
 
5.3%
물 2
 
5.3%
석 2
 
5.3%
서 2
 
5.3%
구 2
 
5.3%
양 2
 
5.3%
사 2
 
5.3%
창 2
 
5.3%
Other values (16) 17
44.7%
Decimal Number
ValueCountFrequency (%)
0 261
33.0%
1 178
22.5%
5 89
 
11.2%
4 57
 
7.2%
3 49
 
6.2%
2 43
 
5.4%
6 34
 
4.3%
7 32
 
4.0%
8 27
 
3.4%
9 22
 
2.8%
Other Punctuation
ValueCountFrequency (%)
: 200
100.0%
Space Separator
ValueCountFrequency (%)
133
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1161
96.8%
Hangul 38
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 3
 
7.9%
분 2
 
5.3%
메 2
 
5.3%
물 2
 
5.3%
석 2
 
5.3%
서 2
 
5.3%
구 2
 
5.3%
양 2
 
5.3%
사 2
 
5.3%
창 2
 
5.3%
Other values (16) 17
44.7%
Common
ValueCountFrequency (%)
0 261
22.5%
: 200
17.2%
1 178
15.3%
133
11.5%
5 89
 
7.7%
4 57
 
4.9%
3 49
 
4.2%
2 43
 
3.7%
6 34
 
2.9%
7 32
 
2.8%
Other values (5) 85
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1161
96.8%
Hangul 38
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 261
22.5%
: 200
17.2%
1 178
15.3%
133
11.5%
5 89
 
7.7%
4 57
 
4.9%
3 49
 
4.2%
2 43
 
3.7%
6 34
 
2.9%
7 32
 
2.8%
Other values (5) 85
 
7.3%
Hangul
ValueCountFrequency (%)
청 3
 
7.9%
분 2
 
5.3%
메 2
 
5.3%
물 2
 
5.3%
석 2
 
5.3%
서 2
 
5.3%
구 2
 
5.3%
양 2
 
5.3%
사 2
 
5.3%
창 2
 
5.3%
Other values (16) 17
44.7%

Interactions

2023-12-12T23:13:01.803113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:12:59.128390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:12:59.676468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.198106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.726231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:01.262187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:01.914840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:12:59.210425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:12:59.756148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.272114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.815147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:01.343572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:02.022099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:12:59.309132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:12:59.843448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.348634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.914105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:01.423587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:02.135826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:12:59.390159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:12:59.918995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.436964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.995293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:01.497553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:02.244664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:12:59.479887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.011153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.531747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:01.073442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:01.590109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:02.329221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:12:59.571748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.107119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:00.610507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:01.165287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:13:01.683494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:13:08.452348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호기점경유지종 점편도거리(Km)왕복거리(Km)편도 운행횟수왕복 운행횟수1일(편도)운행거리1일(왕복)운행거리시 간
노선번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
기점1.0001.0001.0000.0000.6580.6580.0200.0200.0000.0001.000
경유지1.0001.0001.0000.9470.9930.9930.8570.8570.5760.5760.986
종 점1.0000.0000.9471.0000.0000.0000.0000.0000.0000.0000.963
편도거리(Km)1.0000.6580.9930.0001.0001.0000.0000.0000.0000.0000.965
왕복거리(Km)1.0000.6580.9930.0001.0001.0000.0000.0000.0000.0000.965
편도 운행횟수1.0000.0200.8570.0000.0000.0001.0001.0000.9710.9711.000
왕복 운행횟수1.0000.0200.8570.0000.0000.0001.0001.0000.9710.9711.000
1일(편도)운행거리1.0000.0000.5760.0000.0000.0000.9710.9711.0001.0001.000
1일(왕복)운행거리1.0000.0000.5760.0000.0000.0000.9710.9711.0001.0001.000
시 간1.0001.0000.9860.9630.9650.9651.0001.0001.0001.0001.000
2023-12-12T23:13:08.644608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종 점기점
종 점1.0000.000
기점0.0001.000
2023-12-12T23:13:08.804564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
편도거리(Km)왕복거리(Km)편도 운행횟수왕복 운행횟수1일(편도)운행거리1일(왕복)운행거리기점종 점
편도거리(Km)1.0001.000-0.155-0.1550.4020.4020.3870.000
왕복거리(Km)1.0001.000-0.155-0.1550.4020.4020.3870.000
편도 운행횟수-0.155-0.1551.0001.0000.8120.8120.0000.000
왕복 운행횟수-0.155-0.1551.0001.0000.8120.8120.0000.000
1일(편도)운행거리0.4020.4020.8120.8121.0001.0000.0000.000
1일(왕복)운행거리0.4020.4020.8120.8121.0001.0000.0000.000
기점0.3870.3870.0000.0000.0000.0001.0000.000
종 점0.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T23:13:02.472838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:13:02.632373image/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

노선구분노선번호기점경유지종 점편도거리(Km)왕복거리(Km)편도 운행횟수왕복 운행횟수1일(편도)운행거리1일(왕복)운행거리시 간
0관내노선1장성신촌부흥리7.515.063.022.545.007:50 14:00 18:30
1관내노선2장성신촌,청룡유탕서동11.523.0105.057.5115.006:30(청룡) 09:00(청룡) 12:00 15:00 18:00
2관내노선3장성성산,신촌(청룡)유탕5.310.621.05.310.619:30
3관내노선4장성군청,문화센터,행복마을,황룡시장장성8.517.042.017.034.007:55 10:55 13:55 16:55
4관내노선5장성군청,교육청,구산동장성6.813.642.013.627.208:25 11:25 14:25 17:25
5관내노선6장성군청, 문화센터장성5.010.021.05.010.016:00 20:00
6관내노선10장성신흥,광암금곡17.434.8126.0104.4208.806:30 08:20 09:20 10:20 12:20 17:20
7관내노선10-1번장성신흥,율리,궁평,광암금곡19.539.021.019.539.015:20
8관내노선10-2번장성신흥,평암,광암금곡18.937.831.528.3556.714:20
9관내노선10-3번장성밀등,신흥,광암금곡18.236.410.59.118.218:20
노선구분노선번호기점경유지종 점편도거리(Km)왕복거리(Km)편도 운행횟수왕복 운행횟수1일(편도)운행거리1일(왕복)운행거리시 간
64관내노선장성100장성영신,비아광주23.647.28442.0991.21982.405:30 ~ 20:00 (20분~25분 간격 운행)
65관내노선마령100장성마산,덕성,자풍,마령,분향,비아광주34.869.6105.0174.0348.006:55 08:50(회신) 11:55 13:55 16:30
66관내노선녹진100장성녹진,회신,승가,검정,불정,비아광주32.565.031.548.7597.56:25(안청) 12:50
67관내노선진원100초동고산,작동,진원,수촌,신촌,월곡,삼태,비아광주33.967.863.0101.7203.408:30 14:30 17:30
68관내노선진원100-1광주비아,월곡,신촌,수촌,진원,고산,진원,밤실장성32.865.610.516.432.810:10
69관내노선삼서100광주비아,임곡,홍정,보생,삼서상무대48.096.021.048.096.006:45 15:30(사창)
70관내노선삼서100-1상무대삼서,보생,홍정,임곡,비아장성36.472.821.036.472.808:15(사창) 17:05
71관내노선비아100장성남면비아10.721.421.010.721.420:30
72관내노선월정100장성군청,남면,월정,새터비아19.038.021.019.038.07:15
73관내노선월곡100장성군청,주공,단광,수촌,신촌,월곡비아20.140.221.020.140.29:50