Overview

Dataset statistics

Number of variables8
Number of observations380
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.4 KiB
Average record size in memory68.3 B

Variable types

Numeric3
Categorical3
Text1
DateTime1

Dataset

Description광주교통공사의 역간 소요시간 데이터로, 도착역 코드, 출발역, 출발역 코드, 도착역, 통과역수, 역간 소요시간, 기준일자, 호선 정보를 제공합니다.
Author광주교통공사
URLhttps://www.data.go.kr/data/15111482/fileData.do

Alerts

기준일자 has constant value ""Constant
호선 has constant value ""Constant
도착역 코드 is highly overall correlated with 도착역High correlation
출발역 코드 is highly overall correlated with 출발역High correlation
출발역 is highly overall correlated with 출발역 코드High correlation
도착역 is highly overall correlated with 도착역 코드High correlation

Reproduction

Analysis started2023-12-12 21:59:29.363079
Analysis finished2023-12-12 21:59:31.099460
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도착역 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.5
Minimum100
Maximum119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-13T06:59:31.160072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile100.95
Q1104.75
median109.5
Q3114.25
95-th percentile118.05
Maximum119
Range19
Interquartile range (IQR)9.5

Descriptive statistics

Standard deviation5.7738835
Coefficient of variation (CV)0.05272953
Kurtosis-1.2060781
Mean109.5
Median Absolute Deviation (MAD)5
Skewness0
Sum41610
Variance33.337731
MonotonicityNot monotonic
2023-12-13T06:59:31.270310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
110 19
 
5.0%
102 19
 
5.0%
104 19
 
5.0%
112 19
 
5.0%
107 19
 
5.0%
100 19
 
5.0%
109 19
 
5.0%
101 19
 
5.0%
119 19
 
5.0%
106 19
 
5.0%
Other values (10) 190
50.0%
ValueCountFrequency (%)
100 19
5.0%
101 19
5.0%
102 19
5.0%
103 19
5.0%
104 19
5.0%
105 19
5.0%
106 19
5.0%
107 19
5.0%
108 19
5.0%
109 19
5.0%
ValueCountFrequency (%)
119 19
5.0%
118 19
5.0%
117 19
5.0%
116 19
5.0%
115 19
5.0%
114 19
5.0%
113 19
5.0%
112 19
5.0%
111 19
5.0%
110 19
5.0%

출발역
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
송정공원역
 
19
농성역
 
19
녹동역
 
19
소태역
 
19
남광주역
 
19
Other values (15)
285 

Length

Max length14
Median length12.5
Mean length4.9
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row송정공원역
2nd row농성역
3rd row녹동역
4th row소태역
5th row남광주역

Common Values

ValueCountFrequency (%)
송정공원역 19
 
5.0%
농성역 19
 
5.0%
녹동역 19
 
5.0%
소태역 19
 
5.0%
남광주역 19
 
5.0%
쌍촌역 19
 
5.0%
도산역 19
 
5.0%
광주송정역 19
 
5.0%
금남로5가역 19
 
5.0%
양동시장역 19
 
5.0%
Other values (10) 190
50.0%

Length

2023-12-13T06:59:31.378175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송정공원역 19
 
5.0%
농성역 19
 
5.0%
문화전당역(구도청역 19
 
5.0%
운천역 19
 
5.0%
학동중심사입구역 19
 
5.0%
공항역 19
 
5.0%
김대중컨벤션센터역(마륵역 19
 
5.0%
평동역 19
 
5.0%
화정역 19
 
5.0%
돌고개역 19
 
5.0%
Other values (10) 190
50.0%

출발역 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109.5
Minimum100
Maximum119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-13T06:59:31.468183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile100.95
Q1104.75
median109.5
Q3114.25
95-th percentile118.05
Maximum119
Range19
Interquartile range (IQR)9.5

Descriptive statistics

Standard deviation5.7738835
Coefficient of variation (CV)0.05272953
Kurtosis-1.2060781
Mean109.5
Median Absolute Deviation (MAD)5
Skewness0
Sum41610
Variance33.337731
MonotonicityNot monotonic
2023-12-13T06:59:31.568691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
116 19
 
5.0%
108 19
 
5.0%
105 19
 
5.0%
104 19
 
5.0%
112 19
 
5.0%
102 19
 
5.0%
115 19
 
5.0%
114 19
 
5.0%
119 19
 
5.0%
110 19
 
5.0%
Other values (10) 190
50.0%
ValueCountFrequency (%)
100 19
5.0%
101 19
5.0%
102 19
5.0%
103 19
5.0%
104 19
5.0%
105 19
5.0%
106 19
5.0%
107 19
5.0%
108 19
5.0%
109 19
5.0%
ValueCountFrequency (%)
119 19
5.0%
118 19
5.0%
117 19
5.0%
116 19
5.0%
115 19
5.0%
114 19
5.0%
113 19
5.0%
112 19
5.0%
111 19
5.0%
110 19
5.0%

도착역
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
화정역
 
19
김대중컨벤션센터역(마륵역)
 
19
상무역
 
19
광주송정역
 
19
금남로4가역
 
19
Other values (15)
285 

Length

Max length14
Median length12.5
Mean length4.9
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화정역
2nd row김대중컨벤션센터역(마륵역)
3rd row상무역
4th row광주송정역
5th row금남로4가역

Common Values

ValueCountFrequency (%)
화정역 19
 
5.0%
김대중컨벤션센터역(마륵역) 19
 
5.0%
상무역 19
 
5.0%
광주송정역 19
 
5.0%
금남로4가역 19
 
5.0%
도산역 19
 
5.0%
남광주역 19
 
5.0%
송정공원역 19
 
5.0%
쌍촌역 19
 
5.0%
돌고개역 19
 
5.0%
Other values (10) 190
50.0%

Length

2023-12-13T06:59:31.672126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화정역 19
 
5.0%
김대중컨벤션센터역(마륵역 19
 
5.0%
운천역 19
 
5.0%
양동시장역 19
 
5.0%
녹동역 19
 
5.0%
농성역 19
 
5.0%
소태역 19
 
5.0%
평동역 19
 
5.0%
금남로5가역 19
 
5.0%
학동중심사입구역 19
 
5.0%
Other values (10) 190
50.0%

통과역수
Real number (ℝ)

Distinct19
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9868421
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-13T06:59:31.765185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q310
95-th percentile16
Maximum19
Range18
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.5785246
Coefficient of variation (CV)0.65530672
Kurtosis-0.58149157
Mean6.9868421
Median Absolute Deviation (MAD)3
Skewness0.57611811
Sum2655
Variance20.962887
MonotonicityNot monotonic
2023-12-13T06:59:31.860279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 38
10.0%
2 36
9.5%
3 34
 
8.9%
4 32
 
8.4%
5 30
 
7.9%
6 28
 
7.4%
7 26
 
6.8%
8 25
 
6.6%
9 22
 
5.8%
10 20
 
5.3%
Other values (9) 89
23.4%
ValueCountFrequency (%)
1 38
10.0%
2 36
9.5%
3 34
8.9%
4 32
8.4%
5 30
7.9%
6 28
7.4%
7 26
6.8%
8 25
6.6%
9 22
5.8%
10 20
5.3%
ValueCountFrequency (%)
19 2
 
0.5%
18 4
 
1.1%
17 6
 
1.6%
16 8
 
2.1%
15 10
2.6%
14 12
3.2%
13 13
3.4%
12 16
4.2%
11 18
4.7%
10 20
5.3%

역간 소요시간
Text

Distinct303
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-13T06:59:32.160742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1900
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

Unique232 ?
Unique (%)61.1%

Sample

1st row12:10
2nd row07:11
3rd row26:18
4th row28:09
5th row04:18
ValueCountFrequency (%)
10:15 4
 
1.1%
04:17 3
 
0.8%
08:12 3
 
0.8%
06:20 3
 
0.8%
08:11 3
 
0.8%
05:18 2
 
0.5%
15:16 2
 
0.5%
03:15 2
 
0.5%
10:16 2
 
0.5%
15:18 2
 
0.5%
Other values (293) 354
93.2%
2023-12-13T06:59:32.572531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 439
23.1%
: 380
20.0%
0 286
15.1%
2 257
13.5%
3 110
 
5.8%
5 86
 
4.5%
8 77
 
4.1%
4 68
 
3.6%
7 67
 
3.5%
9 67
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1520
80.0%
Other Punctuation 380
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 439
28.9%
0 286
18.8%
2 257
16.9%
3 110
 
7.2%
5 86
 
5.7%
8 77
 
5.1%
4 68
 
4.5%
7 67
 
4.4%
9 67
 
4.4%
6 63
 
4.1%
Other Punctuation
ValueCountFrequency (%)
: 380
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1900
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 439
23.1%
: 380
20.0%
0 286
15.1%
2 257
13.5%
3 110
 
5.8%
5 86
 
4.5%
8 77
 
4.1%
4 68
 
3.6%
7 67
 
3.5%
9 67
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 439
23.1%
: 380
20.0%
0 286
15.1%
2 257
13.5%
3 110
 
5.8%
5 86
 
4.5%
8 77
 
4.1%
4 68
 
3.6%
7 67
 
3.5%
9 67
 
3.5%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2022-12-30 00:00:00
Maximum2022-12-30 00:00:00
2023-12-13T06:59:32.667040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:32.740532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

호선
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
1
380 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 380
100.0%

Length

2023-12-13T06:59:32.832078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:59:32.914990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 380
100.0%

Interactions

2023-12-13T06:59:30.636100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:29.977384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:30.300166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:30.722106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:30.101902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:30.402501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:30.819274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:30.208151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:30.515135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:59:32.972002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도착역 코드출발역출발역 코드도착역통과역수
도착역 코드1.0000.0000.0001.0000.135
출발역0.0001.0001.0000.0000.000
출발역 코드0.0001.0001.0000.0000.147
도착역1.0000.0000.0001.0000.000
통과역수0.1350.0000.1470.0001.000
2023-12-13T06:59:33.172056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출발역도착역
출발역1.0000.000
도착역0.0001.000
2023-12-13T06:59:33.280584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도착역 코드출발역 코드통과역수출발역도착역
도착역 코드1.000-0.0530.0040.0000.986
출발역 코드-0.0531.000-0.0010.9860.000
통과역수0.004-0.0011.0000.0000.000
출발역0.0000.9860.0001.0000.000
도착역0.9860.0000.0000.0001.000

Missing values

2023-12-13T06:59:30.945053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:59:31.056744image/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

도착역 코드출발역출발역 코드도착역통과역수역간 소요시간기준일자호선
0110송정공원역116화정역612:102022-12-301
1114농성역109김대중컨벤션센터역(마륵역)507:112022-12-301
2113녹동역100상무역1326:182022-12-301
3117소태역101광주송정역1628:092022-12-301
4105남광주역103금남로4가역204:182022-12-301
5118쌍촌역111도산역714:232022-12-301
6103도산역118남광주역1526:142022-12-301
7116남광주역103송정공원역1323:102022-12-301
8111광주송정역117쌍촌역612:052022-12-301
9113금남로5가역106상무역712:132022-12-301
도착역 코드출발역출발역 코드도착역통과역수역간 소요시간기준일자호선
370108농성역109돌고개역102:122022-12-301
371108평동역119돌고개역1121:162022-12-301
372107농성역109양동시장역204:232022-12-301
373115금남로5가역106공항역917:272022-12-301
374116공항역115송정공원역101:162022-12-301
375103금남로5가역106남광주역304:112022-12-301
376112평동역119운천역715:232022-12-301
377100문화전당역(구도청역)104녹동역410:152022-12-301
378108녹동역100돌고개역817:072022-12-301
379101녹동역100소태역106:132022-12-301