Overview

Dataset statistics

Number of variables5
Number of observations285
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.4 KiB
Average record size in memory44.5 B

Variable types

Numeric4
Text1

Dataset

Description서울교통공사의 일평균 환승유입순위 데이터입니다. 해당 데이터는 순위, 해당호선, 역번호, 역명, 환승유입인원수 데이터를 포함하고 있습니다. 2022년 12월 기준 데이터입니다.
URLhttps://www.data.go.kr/data/15044246/fileData.do

Alerts

순위 is highly overall correlated with 일평균환승유입인원수High correlation
호선 is highly overall correlated with 역번호High correlation
역번호 is highly overall correlated with 호선High correlation
일평균환승유입인원수 is highly overall correlated with 순위High correlation
순위 has unique valuesUnique
역번호 has unique valuesUnique
역명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:08:30.230129
Analysis finished2023-12-12 14:08:32.366388
Duration2.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순위
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct285
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean143
Minimum1
Maximum285
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T23:08:32.440209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.2
Q172
median143
Q3214
95-th percentile270.8
Maximum285
Range284
Interquartile range (IQR)142

Descriptive statistics

Standard deviation82.416625
Coefficient of variation (CV)0.57634003
Kurtosis-1.2
Mean143
Median Absolute Deviation (MAD)71
Skewness0
Sum40755
Variance6792.5
MonotonicityStrictly increasing
2023-12-12T23:08:32.605376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
189 1
 
0.4%
195 1
 
0.4%
194 1
 
0.4%
193 1
 
0.4%
192 1
 
0.4%
191 1
 
0.4%
190 1
 
0.4%
188 1
 
0.4%
197 1
 
0.4%
Other values (275) 275
96.5%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
285 1
0.4%
284 1
0.4%
283 1
0.4%
282 1
0.4%
281 1
0.4%
280 1
0.4%
279 1
0.4%
278 1
0.4%
277 1
0.4%
276 1
0.4%

호선
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8070175
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T23:08:32.728664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q37
95-th percentile8
Maximum9
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.165987
Coefficient of variation (CV)0.45058855
Kurtosis-0.98900904
Mean4.8070175
Median Absolute Deviation (MAD)2
Skewness0.064358114
Sum1370
Variance4.6914999
MonotonicityNot monotonic
2023-12-12T23:08:32.870431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
5 56
19.6%
2 50
17.5%
7 42
14.7%
6 37
13.0%
3 33
11.6%
4 26
9.1%
8 18
 
6.3%
9 13
 
4.6%
1 10
 
3.5%
ValueCountFrequency (%)
1 10
 
3.5%
2 50
17.5%
3 33
11.6%
4 26
9.1%
5 56
19.6%
6 37
13.0%
7 42
14.7%
8 18
 
6.3%
9 13
 
4.6%
ValueCountFrequency (%)
9 13
 
4.6%
8 18
 
6.3%
7 42
14.7%
6 37
13.0%
5 56
19.6%
4 26
9.1%
3 33
11.6%
2 50
17.5%
1 10
 
3.5%

역번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct285
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1730.4456
Minimum150
Maximum4138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T23:08:33.050691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150
5-th percentile205.2
Q1320
median2534
Q32712
95-th percentile2826.8
Maximum4138
Range3988
Interquartile range (IQR)2392

Descriptive statistics

Standard deviation1262.5495
Coefficient of variation (CV)0.72960947
Kurtosis-1.5156214
Mean1730.4456
Median Absolute Deviation (MAD)284
Skewness-0.10121826
Sum493177
Variance1594031.2
MonotonicityNot monotonic
2023-12-12T23:08:33.291938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
239 1
 
0.4%
2727 1
 
0.4%
2551 1
 
0.4%
422 1
 
0.4%
4132 1
 
0.4%
205 1
 
0.4%
2555 1
 
0.4%
2626 1
 
0.4%
337 1
 
0.4%
2752 1
 
0.4%
Other values (275) 275
96.5%
ValueCountFrequency (%)
150 1
0.4%
151 1
0.4%
152 1
0.4%
153 1
0.4%
154 1
0.4%
155 1
0.4%
156 1
0.4%
157 1
0.4%
158 1
0.4%
159 1
0.4%
ValueCountFrequency (%)
4138 1
0.4%
4137 1
0.4%
4136 1
0.4%
4135 1
0.4%
4134 1
0.4%
4133 1
0.4%
4132 1
0.4%
4131 1
0.4%
4130 1
0.4%
4129 1
0.4%

역명
Text

UNIQUE 

Distinct285
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-12T23:08:33.695027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length3.877193
Min length2

Characters and Unicode

Total characters1105
Distinct characters223
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

Unique285 ?
Unique (%)100.0%

Sample

1st row홍대입구
2nd row서울역(1)
3rd row강남
4th row종각
5th row잠실(2)
ValueCountFrequency (%)
홍대입구 1
 
0.4%
경찰병원 1
 
0.4%
굽은다리 1
 
0.4%
동대문역사문화공원(4 1
 
0.4%
석촌고분 1
 
0.4%
동대문역사문화공원(2 1
 
0.4%
둔촌동 1
 
0.4%
대흥 1
 
0.4%
대청 1
 
0.4%
신정 1
 
0.4%
Other values (275) 275
96.5%
2023-12-12T23:08:34.211895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 87
 
7.9%
) 87
 
7.9%
대 32
 
2.9%
구 28
 
2.5%
동 23
 
2.1%
신 22
 
2.0%
산 19
 
1.7%
5 18
 
1.6%
원 16
 
1.4%
2 16
 
1.4%
Other values (213) 757
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 837
75.7%
Decimal Number 94
 
8.5%
Open Punctuation 87
 
7.9%
Close Punctuation 87
 
7.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 32
 
3.8%
구 28
 
3.3%
동 23
 
2.7%
신 22
 
2.6%
산 19
 
2.3%
원 16
 
1.9%
지 15
 
1.8%
문 15
 
1.8%
청 14
 
1.7%
로 14
 
1.7%
Other values (202) 639
76.3%
Decimal Number
ValueCountFrequency (%)
5 18
19.1%
2 16
17.0%
3 14
14.9%
6 11
11.7%
7 11
11.7%
4 9
9.6%
1 6
 
6.4%
8 6
 
6.4%
9 3
 
3.2%
Open Punctuation
ValueCountFrequency (%)
( 87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 837
75.7%
Common 268
 
24.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 32
 
3.8%
구 28
 
3.3%
동 23
 
2.7%
신 22
 
2.6%
산 19
 
2.3%
원 16
 
1.9%
지 15
 
1.8%
문 15
 
1.8%
청 14
 
1.7%
로 14
 
1.7%
Other values (202) 639
76.3%
Common
ValueCountFrequency (%)
( 87
32.5%
) 87
32.5%
5 18
 
6.7%
2 16
 
6.0%
3 14
 
5.2%
6 11
 
4.1%
7 11
 
4.1%
4 9
 
3.4%
1 6
 
2.2%
8 6
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 837
75.7%
ASCII 268
 
24.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 87
32.5%
) 87
32.5%
5 18
 
6.7%
2 16
 
6.0%
3 14
 
5.2%
6 11
 
4.1%
7 11
 
4.1%
4 9
 
3.4%
1 6
 
2.2%
8 6
 
2.2%
Hangul
ValueCountFrequency (%)
대 32
 
3.8%
구 28
 
3.3%
동 23
 
2.7%
신 22
 
2.6%
산 19
 
2.3%
원 16
 
1.9%
지 15
 
1.8%
문 15
 
1.8%
청 14
 
1.7%
로 14
 
1.7%
Other values (202) 639
76.3%

일평균환승유입인원수
Real number (ℝ)

HIGH CORRELATION 

Distinct283
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7327.8281
Minimum319
Maximum34234
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T23:08:34.347981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum319
5-th percentile1306.2
Q13614
median5953
Q38861
95-th percentile20290.8
Maximum34234
Range33915
Interquartile range (IQR)5247

Descriptive statistics

Standard deviation5689.5122
Coefficient of variation (CV)0.77642545
Kurtosis3.3717608
Mean7327.8281
Median Absolute Deviation (MAD)2414
Skewness1.715994
Sum2088431
Variance32370549
MonotonicityDecreasing
2023-12-12T23:08:34.492601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2876 2
 
0.7%
9993 2
 
0.7%
34234 1
 
0.4%
4273 1
 
0.4%
4088 1
 
0.4%
4102 1
 
0.4%
4213 1
 
0.4%
4216 1
 
0.4%
4260 1
 
0.4%
4291 1
 
0.4%
Other values (273) 273
95.8%
ValueCountFrequency (%)
319 1
0.4%
468 1
0.4%
608 1
0.4%
612 1
0.4%
660 1
0.4%
714 1
0.4%
730 1
0.4%
760 1
0.4%
889 1
0.4%
938 1
0.4%
ValueCountFrequency (%)
34234 1
0.4%
28840 1
0.4%
27345 1
0.4%
25473 1
0.4%
24971 1
0.4%
24041 1
0.4%
23652 1
0.4%
23147 1
0.4%
23119 1
0.4%
22871 1
0.4%

Interactions

2023-12-12T23:08:31.612309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:30.437965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:30.814811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:31.224970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:31.725782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:30.519449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:30.899570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:31.309075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:31.862188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:30.611809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:31.016484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:31.402212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:31.992481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:30.713427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:31.131016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:31.504899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:08:34.599422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순위호선역번호일평균환승유입인원수
순위1.0000.3390.4000.951
호선0.3391.0000.9410.393
역번호0.4000.9411.0000.350
일평균환승유입인원수0.9510.3930.3501.000
2023-12-12T23:08:34.694418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순위호선역번호일평균환승유입인원수
순위1.0000.3120.334-1.000
호선0.3121.0000.989-0.312
역번호0.3340.9891.000-0.333
일평균환승유입인원수-1.000-0.312-0.3331.000

Missing values

2023-12-12T23:08:32.181760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:08:32.325271image/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

순위호선역번호역명일평균환승유입인원수
012239홍대입구34234
121150서울역(1)28840
232222강남27345
341152종각25473
452216잠실(2)24971
562232구로디지털단지24041
6772748가산디지털단지(7)23652
782234신도림23147
892221역삼23119
9103332양재22871
순위호선역번호역명일평균환승유입인원수
27527652541왕십리(5)938
2762772244용답889
27727852524영등포구청(5)760
2782792247도림천730
2792804434남태령714
2802812250용두660
28128282827모란(8)612
28228394137둔촌오륜608
28328472711장암468
2842852245신답319