Overview

Dataset statistics

Number of variables5
Number of observations276
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.0 KiB
Average record size in memory44.5 B

Variable types

Numeric4
Text1

Dataset

Description서울교통공사 1-8호선 역사면적정보입니다. 해당 데이터는 호선, 역명, 대합실 면적, 승강장 면적으로 구성되어 있습니다. 2023년 5월 기준입니다.
URLhttps://www.data.go.kr/data/15060120/fileData.do

Alerts

연번 is highly overall correlated with 호선High correlation
호선 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:05:20.431969
Analysis finished2023-12-12 21:05:22.646253
Duration2.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct276
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean138.5
Minimum1
Maximum276
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T06:05:22.734695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.75
Q169.75
median138.5
Q3207.25
95-th percentile262.25
Maximum276
Range275
Interquartile range (IQR)137.5

Descriptive statistics

Standard deviation79.818544
Coefficient of variation (CV)0.57630718
Kurtosis-1.2
Mean138.5
Median Absolute Deviation (MAD)69
Skewness0
Sum38226
Variance6371
MonotonicityStrictly increasing
2023-12-13T06:05:22.884173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
184 1
 
0.4%
190 1
 
0.4%
189 1
 
0.4%
188 1
 
0.4%
187 1
 
0.4%
186 1
 
0.4%
185 1
 
0.4%
183 1
 
0.4%
175 1
 
0.4%
Other values (266) 266
96.4%
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 (%)
276 1
0.4%
275 1
0.4%
274 1
0.4%
273 1
0.4%
272 1
0.4%
271 1
0.4%
270 1
0.4%
269 1
0.4%
268 1
0.4%
267 1
0.4%

호선
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6014493
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T06:05:23.016281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q36
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.0055917
Coefficient of variation (CV)0.43586086
Kurtosis-1.1523668
Mean4.6014493
Median Absolute Deviation (MAD)2
Skewness-0.051736261
Sum1270
Variance4.0223979
MonotonicityIncreasing
2023-12-13T06:05:23.125900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
5 56
20.3%
2 51
18.5%
7 42
15.2%
6 39
14.1%
3 34
12.3%
4 26
9.4%
8 18
 
6.5%
1 10
 
3.6%
ValueCountFrequency (%)
1 10
 
3.6%
2 51
18.5%
3 34
12.3%
4 26
9.4%
5 56
20.3%
6 39
14.1%
7 42
15.2%
8 18
 
6.5%
ValueCountFrequency (%)
8 18
 
6.5%
7 42
15.2%
6 39
14.1%
5 56
20.3%
4 26
9.4%
3 34
12.3%
2 51
18.5%
1 10
 
3.6%

역명
Text

Distinct240
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-13T06:05:23.370110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length2
Mean length2.9202899
Min length2

Characters and Unicode

Total characters806
Distinct characters207
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique206 ?
Unique (%)74.6%

Sample

1st row서울역
2nd row시청
3rd row종각
4th row종로3가
5th row종로5가
ValueCountFrequency (%)
종로3가 3
 
1.1%
동대문역사문화공원 3
 
1.1%
사당 2
 
0.7%
서울역 2
 
0.7%
가락시장 2
 
0.7%
까치산 2
 
0.7%
교대 2
 
0.7%
대림 2
 
0.7%
영등포구청 2
 
0.7%
합정 2
 
0.7%
Other values (230) 254
92.0%
2023-12-13T06:05:23.815853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 32
 
4.0%
구 28
 
3.5%
신 24
 
3.0%
동 22
 
2.7%
산 20
 
2.5%
문 15
 
1.9%
로 15
 
1.9%
지 15
 
1.9%
청 14
 
1.7%
입 14
 
1.7%
Other values (197) 607
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 798
99.0%
Decimal Number 8
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 32
 
4.0%
구 28
 
3.5%
신 24
 
3.0%
동 22
 
2.8%
산 20
 
2.5%
문 15
 
1.9%
로 15
 
1.9%
지 15
 
1.9%
청 14
 
1.8%
입 14
 
1.8%
Other values (194) 599
75.1%
Decimal Number
ValueCountFrequency (%)
3 5
62.5%
4 2
 
25.0%
5 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 798
99.0%
Common 8
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 32
 
4.0%
구 28
 
3.5%
신 24
 
3.0%
동 22
 
2.8%
산 20
 
2.5%
문 15
 
1.9%
로 15
 
1.9%
지 15
 
1.9%
청 14
 
1.8%
입 14
 
1.8%
Other values (194) 599
75.1%
Common
ValueCountFrequency (%)
3 5
62.5%
4 2
 
25.0%
5 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 798
99.0%
ASCII 8
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 32
 
4.0%
구 28
 
3.5%
신 24
 
3.0%
동 22
 
2.8%
산 20
 
2.5%
문 15
 
1.9%
로 15
 
1.9%
지 15
 
1.9%
청 14
 
1.8%
입 14
 
1.8%
Other values (194) 599
75.1%
ASCII
ValueCountFrequency (%)
3 5
62.5%
4 2
 
25.0%
5 1
 
12.5%

대합실면적
Real number (ℝ)

Distinct274
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5679.8575
Minimum0
Maximum20239.47
Zeros2
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T06:05:23.971669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2390.25
Q13923.23
median5098.52
Q37006.0825
95-th percentile10514.188
Maximum20239.47
Range20239.47
Interquartile range (IQR)3082.8525

Descriptive statistics

Standard deviation2731.2725
Coefficient of variation (CV)0.48086991
Kurtosis3.7494583
Mean5679.8575
Median Absolute Deviation (MAD)1474.335
Skewness1.3568273
Sum1567640.7
Variance7459849.7
MonotonicityNot monotonic
2023-12-13T06:05:24.136748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3631.0 2
 
0.7%
0.0 2
 
0.7%
7001.38 1
 
0.4%
4181.76 1
 
0.4%
6510.83 1
 
0.4%
3618.46 1
 
0.4%
6302.13 1
 
0.4%
7829.85 1
 
0.4%
5694.15 1
 
0.4%
3735.6 1
 
0.4%
Other values (264) 264
95.7%
ValueCountFrequency (%)
0.0 2
0.7%
106.16 1
0.4%
504.0 1
0.4%
625.0 1
0.4%
645.0 1
0.4%
700.0 1
0.4%
1743.35 1
0.4%
1791.0 1
0.4%
2080.7 1
0.4%
2192.25 1
0.4%
ValueCountFrequency (%)
20239.47 1
0.4%
15965.0 1
0.4%
15210.51 1
0.4%
14394.53 1
0.4%
13442.0 1
0.4%
13040.93 1
0.4%
12557.98 1
0.4%
12110.1 1
0.4%
11984.9 1
0.4%
11880.0 1
0.4%

승강장면적
Real number (ℝ)

Distinct272
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2333.9107
Minimum752.28
Maximum7175
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T06:05:24.263604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum752.28
5-th percentile1498
Q11907.74
median2168.535
Q32611.89
95-th percentile3519.25
Maximum7175
Range6422.72
Interquartile range (IQR)704.15

Descriptive statistics

Standard deviation749.59055
Coefficient of variation (CV)0.32117362
Kurtosis8.8185133
Mean2333.9107
Median Absolute Deviation (MAD)316.035
Skewness2.1209518
Sum644159.35
Variance561885.99
MonotonicityNot monotonic
2023-12-13T06:05:24.399162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1920.11 2
 
0.7%
1665.0 2
 
0.7%
1640.0 2
 
0.7%
2362.0 2
 
0.7%
2080.0 1
 
0.4%
2421.49 1
 
0.4%
1902.37 1
 
0.4%
2121.44 1
 
0.4%
3376.03 1
 
0.4%
3295.6 1
 
0.4%
Other values (262) 262
94.9%
ValueCountFrequency (%)
752.28 1
0.4%
791.0 1
0.4%
798.0 1
0.4%
938.0 1
0.4%
999.05 1
0.4%
1208.0 1
0.4%
1306.0 1
0.4%
1363.41 1
0.4%
1373.0 1
0.4%
1397.5 1
0.4%
ValueCountFrequency (%)
7175.0 1
0.4%
5721.0 1
0.4%
5392.0 1
0.4%
5064.0 1
0.4%
4978.0 1
0.4%
4567.09 1
0.4%
4194.19 1
0.4%
4048.0 1
0.4%
4021.0 1
0.4%
3860.0 1
0.4%

Interactions

2023-12-13T06:05:22.107207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:20.656776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:21.014094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:21.369994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:22.190230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:20.737461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:21.091396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:21.745589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:22.276275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:20.828949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:21.173645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:21.869599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:22.380405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:20.929361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:21.267228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:05:22.000225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:05:24.520129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선대합실면적승강장면적
연번1.0000.9170.1380.269
호선0.9171.0000.2130.169
대합실면적0.1380.2131.0000.647
승강장면적0.2690.1690.6471.000
2023-12-13T06:05:24.609286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번호선대합실면적승강장면적
연번1.0000.9880.161-0.190
호선0.9881.0000.163-0.189
대합실면적0.1610.1631.0000.375
승강장면적-0.190-0.1890.3751.000

Missing values

2023-12-13T06:05:22.497008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:05:22.610640image/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

연번호선역명대합실면적승강장면적
011서울역8725.02080.0
121시청6863.03784.0
231종각7737.432672.81
341종로3가5628.03683.0
451종로5가7822.02208.0
561동대문3400.02090.0
671동묘앞5700.564194.19
781신설동4164.03076.0
891제기동5105.02815.0
9101청량리5354.01771.0
연번호선역명대합실면적승강장면적
2662678문정3278.751915.2
2672688장지4099.741628.15
2682698복정4444.32141.55
2692708남위례4177.542168.78
2702718산성2874.592263.2
2712728남한산성입구3932.291480.0
2722738단대오거리6496.421636.8
2732748신흥3196.611665.0
2742758수진3402.311665.0
2752768모란7758.772160.0