Overview

Dataset statistics

Number of variables5
Number of observations73
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory45.8 B

Variable types

Numeric4
Text1

Dataset

Description역별 요일별 (평일/토요일/일요일) 관할 환승역 환승인원 정보입니다. 해당 데이터는 1년 주기로 업데이트 되는 정보로 연번,역명,평일(일평균),토요일,일요일 환승인원정보로 구성되어 있습니다.
Author서울교통공사
URLhttps://www.data.go.kr/data/15062858/fileData.do

Alerts

평일(일평균) is highly overall correlated with 토요일 and 1 other fieldsHigh correlation
토요일 is highly overall correlated with 평일(일평균) and 1 other fieldsHigh correlation
일요일 is highly overall correlated with 평일(일평균) and 1 other fieldsHigh correlation
연번 has unique valuesUnique
역명 has unique valuesUnique
평일(일평균) has unique valuesUnique
토요일 has unique valuesUnique

Reproduction

Analysis started2024-04-29 22:37:59.578286
Analysis finished2024-04-29 22:38:03.166042
Duration3.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37
Minimum1
Maximum73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-04-30T07:38:03.239218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.6
Q119
median37
Q355
95-th percentile69.4
Maximum73
Range72
Interquartile range (IQR)36

Descriptive statistics

Standard deviation21.217131
Coefficient of variation (CV)0.57343598
Kurtosis-1.2
Mean37
Median Absolute Deviation (MAD)18
Skewness0
Sum2701
Variance450.16667
MonotonicityStrictly increasing
2024-04-30T07:38:03.401422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
56 1
 
1.4%
54 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
Other values (63) 63
86.3%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
73 1
1.4%
72 1
1.4%
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%

역명
Text

UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-04-30T07:38:03.684732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length2
Mean length3.0821918
Min length2

Characters and Unicode

Total characters225
Distinct characters114
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)100.0%

Sample

1st row가락시장
2nd row가산디지털단지
3rd row강남
4th row강남구청
5th row강동
ValueCountFrequency (%)
가락시장 1
 
1.4%
수서 1
 
1.4%
온수 1
 
1.4%
옥수 1
 
1.4%
오금 1
 
1.4%
영등포구청 1
 
1.4%
연신내 1
 
1.4%
여의도 1
 
1.4%
양재 1
 
1.4%
약수 1
 
1.4%
Other values (63) 63
86.3%
2024-04-30T07:38:04.110917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
신 10
 
4.4%
대 8
 
3.6%
구 8
 
3.6%
동 8
 
3.6%
수 6
 
2.7%
지 6
 
2.7%
가 5
 
2.2%
로 5
 
2.2%
공 5
 
2.2%
입 5
 
2.2%
Other values (104) 159
70.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 220
97.8%
Decimal Number 3
 
1.3%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
신 10
 
4.5%
대 8
 
3.6%
구 8
 
3.6%
동 8
 
3.6%
수 6
 
2.7%
지 6
 
2.7%
가 5
 
2.3%
로 5
 
2.3%
공 5
 
2.3%
입 5
 
2.3%
Other values (100) 154
70.0%
Decimal Number
ValueCountFrequency (%)
3 2
66.7%
4 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 220
97.8%
Common 5
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
신 10
 
4.5%
대 8
 
3.6%
구 8
 
3.6%
동 8
 
3.6%
수 6
 
2.7%
지 6
 
2.7%
가 5
 
2.3%
로 5
 
2.3%
공 5
 
2.3%
입 5
 
2.3%
Other values (100) 154
70.0%
Common
ValueCountFrequency (%)
3 2
40.0%
4 1
20.0%
( 1
20.0%
) 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 220
97.8%
ASCII 5
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
신 10
 
4.5%
대 8
 
3.6%
구 8
 
3.6%
동 8
 
3.6%
수 6
 
2.7%
지 6
 
2.7%
가 5
 
2.3%
로 5
 
2.3%
공 5
 
2.3%
입 5
 
2.3%
Other values (100) 154
70.0%
ASCII
ValueCountFrequency (%)
3 2
40.0%
4 1
20.0%
( 1
20.0%
) 1
20.0%

평일(일평균)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64089.438
Minimum5621
Maximum277033
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-04-30T07:38:04.269528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5621
5-th percentile18992.4
Q131294
median49975
Q375537
95-th percentile163466
Maximum277033
Range271412
Interquartile range (IQR)44243

Descriptive statistics

Standard deviation51130.367
Coefficient of variation (CV)0.79779708
Kurtosis4.3344942
Mean64089.438
Median Absolute Deviation (MAD)21280
Skewness1.923337
Sum4678529
Variance2.6143144 × 109
MonotonicityNot monotonic
2024-04-30T07:38:04.404540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36905 1
 
1.4%
176330 1
 
1.4%
60866 1
 
1.4%
31294 1
 
1.4%
30947 1
 
1.4%
82046 1
 
1.4%
34812 1
 
1.4%
59357 1
 
1.4%
22950 1
 
1.4%
57167 1
 
1.4%
Other values (63) 63
86.3%
ValueCountFrequency (%)
5621 1
1.4%
8022 1
1.4%
8637 1
1.4%
18186 1
1.4%
19530 1
1.4%
19750 1
1.4%
20411 1
1.4%
20433 1
1.4%
22002 1
1.4%
22950 1
1.4%
ValueCountFrequency (%)
277033 1
1.4%
222447 1
1.4%
183118 1
1.4%
176330 1
1.4%
154890 1
1.4%
153670 1
1.4%
144533 1
1.4%
142508 1
1.4%
136709 1
1.4%
107829 1
1.4%

토요일
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49226.027
Minimum4057
Maximum225439
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-04-30T07:38:04.536331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4057
5-th percentile10458.4
Q123501
median36073
Q357268
95-th percentile132062
Maximum225439
Range221382
Interquartile range (IQR)33767

Descriptive statistics

Standard deviation41654.939
Coefficient of variation (CV)0.84619745
Kurtosis4.7384604
Mean49226.027
Median Absolute Deviation (MAD)17891
Skewness2.0269608
Sum3593500
Variance1.7351339 × 109
MonotonicityNot monotonic
2024-04-30T07:38:04.705370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24743 1
 
1.4%
133349 1
 
1.4%
44342 1
 
1.4%
24336 1
 
1.4%
19497 1
 
1.4%
57268 1
 
1.4%
26600 1
 
1.4%
40801 1
 
1.4%
15793 1
 
1.4%
46051 1
 
1.4%
Other values (63) 63
86.3%
ValueCountFrequency (%)
4057 1
1.4%
6118 1
1.4%
7297 1
1.4%
10324 1
1.4%
10548 1
1.4%
11573 1
1.4%
13455 1
1.4%
14432 1
1.4%
15217 1
1.4%
15793 1
1.4%
ValueCountFrequency (%)
225439 1
1.4%
176018 1
1.4%
155969 1
1.4%
133349 1
1.4%
131204 1
1.4%
125109 1
1.4%
124673 1
1.4%
109847 1
1.4%
93358 1
1.4%
88139 1
1.4%

일요일
Real number (ℝ)

HIGH CORRELATION 

Distinct72
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35018.644
Minimum3069
Maximum163217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-04-30T07:38:04.881881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3069
5-th percentile7604.4
Q117760
median25576
Q340324
95-th percentile93891.4
Maximum163217
Range160148
Interquartile range (IQR)22564

Descriptive statistics

Standard deviation29658.194
Coefficient of variation (CV)0.84692583
Kurtosis5.2132127
Mean35018.644
Median Absolute Deviation (MAD)11864
Skewness2.1053764
Sum2556361
Variance8.7960847 × 108
MonotonicityNot monotonic
2024-04-30T07:38:05.154405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39631 2
 
2.7%
18296 1
 
1.4%
27821 1
 
1.4%
13523 1
 
1.4%
33420 1
 
1.4%
17912 1
 
1.4%
14505 1
 
1.4%
39690 1
 
1.4%
18835 1
 
1.4%
10494 1
 
1.4%
Other values (62) 62
84.9%
ValueCountFrequency (%)
3069 1
1.4%
4850 1
1.4%
5092 1
1.4%
7179 1
1.4%
7888 1
1.4%
8215 1
1.4%
9858 1
1.4%
10047 1
1.4%
10494 1
1.4%
10740 1
1.4%
ValueCountFrequency (%)
163217 1
1.4%
126322 1
1.4%
111961 1
1.4%
95080 1
1.4%
93099 1
1.4%
88443 1
1.4%
87420 1
1.4%
75861 1
1.4%
64588 1
1.4%
62139 1
1.4%

Interactions

2024-04-30T07:38:02.586191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:01.474815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:01.919301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:02.273077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:02.674203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:01.626962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:02.017939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:02.353420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:02.755006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:01.711537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:02.099082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:02.428556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:02.863861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:01.813870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:02.178528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:38:02.497599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:38:05.356143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번역명평일(일평균)토요일일요일
연번1.0001.0000.2760.0740.000
역명1.0001.0001.0001.0001.000
평일(일평균)0.2761.0001.0000.9850.979
토요일0.0741.0000.9851.0000.998
일요일0.0001.0000.9790.9981.000
2024-04-30T07:38:05.611513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번평일(일평균)토요일일요일
연번1.000-0.081-0.037-0.044
평일(일평균)-0.0811.0000.9810.974
토요일-0.0370.9811.0000.992
일요일-0.0440.9740.9921.000

Missing values

2024-04-30T07:38:03.019734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:38:03.117735image/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

연번역명평일(일평균)토요일일요일
01가락시장369052474318296
12가산디지털단지888015094440324
23강남667434504429378
34강남구청606993672024141
45강동562140573069
56건대입구1058208813964588
67고속터미널183118155969111961
78공덕663126631246378
89교대1367099335862139
910군자1050557424855940
연번역명평일(일평균)토요일일요일
6364천호864845671941157
6465청구375402842219714
6566청량리238542600521256
6667총신대입구(이수)686725746841393
6768충무로14250810984775861
6869충정로19750105487179
6970태릉입구502543475724609
7071합정940708700052556
7172홍대입구824647773758833
7273효창공원앞802272974850