Overview

Dataset statistics

Number of variables12
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory109.7 B

Variable types

Numeric9
Text2
Categorical1

Dataset

Description파일 다운로드
Author서울교통공사
URLhttps://data.seoul.go.kr/dataList/OA-13213/F/1/datasetView.do

Alerts

연번 is highly overall correlated with 단위High correlation
1호선 is highly overall correlated with 2호선 and 6 other fieldsHigh correlation
2호선 is highly overall correlated with 1호선 and 6 other fieldsHigh correlation
3호선 is highly overall correlated with 1호선 and 6 other fieldsHigh correlation
4호선 is highly overall correlated with 1호선 and 6 other fieldsHigh correlation
5호선 is highly overall correlated with 1호선 and 6 other fieldsHigh correlation
6호선 is highly overall correlated with 1호선 and 6 other fieldsHigh correlation
7호선 is highly overall correlated with 1호선 and 6 other fieldsHigh correlation
8호선 is highly overall correlated with 1호선 and 6 other fieldsHigh correlation
단위 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
장비명 has unique valuesUnique
1호선 has 4 (14.3%) zerosZeros
2호선 has 2 (7.1%) zerosZeros
3호선 has 2 (7.1%) zerosZeros
5호선 has 5 (17.9%) zerosZeros
6호선 has 6 (21.4%) zerosZeros
7호선 has 6 (21.4%) zerosZeros
8호선 has 6 (21.4%) zerosZeros

Reproduction

Analysis started2024-04-29 16:44:12.640666
Analysis finished2024-04-29 16:44:20.312598
Duration7.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:20.364494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.35
Q17.75
median14.5
Q321.25
95-th percentile26.65
Maximum28
Range27
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.2259751
Coefficient of variation (CV)0.56730863
Kurtosis-1.2
Mean14.5
Median Absolute Deviation (MAD)7
Skewness0
Sum406
Variance67.666667
MonotonicityStrictly increasing
2024-04-30T01:44:20.470047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1 1
 
3.6%
16 1
 
3.6%
28 1
 
3.6%
27 1
 
3.6%
26 1
 
3.6%
25 1
 
3.6%
24 1
 
3.6%
23 1
 
3.6%
22 1
 
3.6%
21 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
1 1
3.6%
2 1
3.6%
3 1
3.6%
4 1
3.6%
5 1
3.6%
6 1
3.6%
7 1
3.6%
8 1
3.6%
9 1
3.6%
10 1
3.6%
ValueCountFrequency (%)
28 1
3.6%
27 1
3.6%
26 1
3.6%
25 1
3.6%
24 1
3.6%
23 1
3.6%
22 1
3.6%
21 1
3.6%
20 1
3.6%
19 1
3.6%

시설명
Text

Distinct15
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-30T01:44:20.625670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.75
Min length3

Characters and Unicode

Total characters133
Distinct characters44
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)28.6%

Sample

1st row교환설비
2nd row교환설비
3rd row열차무선
4th row열차무선
5th row열차무선
ValueCountFrequency (%)
정보통신망 5
17.9%
열차무선 3
10.7%
선로설비 3
10.7%
화상모니터링 3
10.7%
교환설비 2
 
7.1%
전화기 2
 
7.1%
비상통화장치 2
 
7.1%
재난방송 1
 
3.6%
광전송설비 1
 
3.6%
무정전전원설비 1
 
3.6%
Other values (5) 5
17.9%
2024-04-30T01:44:20.885705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 10
 
7.5%
설 8
 
6.0%
선 7
 
5.3%
화 7
 
5.3%
정 7
 
5.3%
통 7
 
5.3%
보 6
 
4.5%
전 5
 
3.8%
망 5
 
3.8%
신 5
 
3.8%
Other values (34) 66
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 10
 
7.5%
설 8
 
6.0%
선 7
 
5.3%
화 7
 
5.3%
정 7
 
5.3%
통 7
 
5.3%
보 6
 
4.5%
전 5
 
3.8%
망 5
 
3.8%
신 5
 
3.8%
Other values (34) 66
49.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 10
 
7.5%
설 8
 
6.0%
선 7
 
5.3%
화 7
 
5.3%
정 7
 
5.3%
통 7
 
5.3%
보 6
 
4.5%
전 5
 
3.8%
망 5
 
3.8%
신 5
 
3.8%
Other values (34) 66
49.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 10
 
7.5%
설 8
 
6.0%
선 7
 
5.3%
화 7
 
5.3%
정 7
 
5.3%
통 7
 
5.3%
보 6
 
4.5%
전 5
 
3.8%
망 5
 
3.8%
신 5
 
3.8%
Other values (34) 66
49.6%

장비명
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-04-30T01:44:21.070167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.2857143
Min length2

Characters and Unicode

Total characters148
Distinct characters87
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st rowIP교환기
2nd row게이트웨이
3rd row기지국
4th row이동국
5th rowIRCP
ValueCountFrequency (%)
ip교환기 1
 
3.6%
게이트웨이 1
 
3.6%
음성유도기 1
 
3.6%
콜폰 1
 
3.6%
승강장 1
 
3.6%
워크그룹스위치 1
 
3.6%
에지스위치 1
 
3.6%
백본스위치 1
 
3.6%
코어스위치 1
 
3.6%
방화벽 1
 
3.6%
Other values (18) 18
64.3%
2024-04-30T01:44:21.382914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
치 5
 
3.4%
스 5
 
3.4%
( 5
 
3.4%
) 5
 
3.4%
선 4
 
2.7%
위 4
 
2.7%
전 4
 
2.7%
비 4
 
2.7%
설 4
 
2.7%
기 3
 
2.0%
Other values (77) 105
70.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
84.5%
Uppercase Letter 12
 
8.1%
Open Punctuation 5
 
3.4%
Close Punctuation 5
 
3.4%
Other Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
치 5
 
4.0%
스 5
 
4.0%
선 4
 
3.2%
위 4
 
3.2%
전 4
 
3.2%
비 4
 
3.2%
설 4
 
3.2%
기 3
 
2.4%
이 3
 
2.4%
용 3
 
2.4%
Other values (67) 86
68.8%
Uppercase Letter
ValueCountFrequency (%)
R 3
25.0%
V 2
16.7%
P 2
16.7%
I 2
16.7%
D 1
 
8.3%
N 1
 
8.3%
C 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
84.5%
Latin 12
 
8.1%
Common 11
 
7.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
치 5
 
4.0%
스 5
 
4.0%
선 4
 
3.2%
위 4
 
3.2%
전 4
 
3.2%
비 4
 
3.2%
설 4
 
3.2%
기 3
 
2.4%
이 3
 
2.4%
용 3
 
2.4%
Other values (67) 86
68.8%
Latin
ValueCountFrequency (%)
R 3
25.0%
V 2
16.7%
P 2
16.7%
I 2
16.7%
D 1
 
8.3%
N 1
 
8.3%
C 1
 
8.3%
Common
ValueCountFrequency (%)
( 5
45.5%
) 5
45.5%
/ 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
84.5%
ASCII 23
 
15.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
치 5
 
4.0%
스 5
 
4.0%
선 4
 
3.2%
위 4
 
3.2%
전 4
 
3.2%
비 4
 
3.2%
설 4
 
3.2%
기 3
 
2.4%
이 3
 
2.4%
용 3
 
2.4%
Other values (67) 86
68.8%
ASCII
ValueCountFrequency (%)
( 5
21.7%
) 5
21.7%
R 3
13.0%
V 2
 
8.7%
P 2
 
8.7%
I 2
 
8.7%
D 1
 
4.3%
N 1
 
4.3%
/ 1
 
4.3%
C 1
 
4.3%

단위
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
식
15 
대
8 
Km
3 
장치
2 

Length

Max length2
Median length1
Mean length1.1785714
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row식
2nd row식
3rd row장치
4th row장치
5th row대

Common Values

ValueCountFrequency (%)
식 15
53.6%
대 8
28.6%
Km 3
 
10.7%
장치 2
 
7.1%

Length

2024-04-30T01:44:21.490696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T01:44:21.583112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식 15
53.6%
대 8
28.6%
km 3
 
10.7%
장치 2
 
7.1%

1호선
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.857143
Minimum0
Maximum972
Zeros4
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:21.678105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.75
median10
Q342.5
95-th percentile280.55
Maximum972
Range972
Interquartile range (IQR)37.75

Descriptive statistics

Standard deviation190.22067
Coefficient of variation (CV)2.5411159
Kurtosis19.670748
Mean74.857143
Median Absolute Deviation (MAD)10
Skewness4.2476498
Sum2096
Variance36183.905
MonotonicityNot monotonic
2024-04-30T01:44:21.774981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
10 6
21.4%
0 4
14.3%
5 2
 
7.1%
32 2
 
7.1%
972 1
 
3.6%
224 1
 
3.6%
148 1
 
3.6%
56 1
 
3.6%
74 1
 
3.6%
2 1
 
3.6%
Other values (8) 8
28.6%
ValueCountFrequency (%)
0 4
14.3%
1 1
 
3.6%
2 1
 
3.6%
4 1
 
3.6%
5 2
 
7.1%
10 6
21.4%
11 1
 
3.6%
12 1
 
3.6%
29 1
 
3.6%
32 2
 
7.1%
ValueCountFrequency (%)
972 1
3.6%
311 1
3.6%
224 1
3.6%
148 1
3.6%
80 1
3.6%
74 1
3.6%
56 1
3.6%
38 1
3.6%
32 2
7.1%
29 1
3.6%

2호선
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean343.42857
Minimum0
Maximum3824
Zeros2
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:21.879005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.7
Q111.25
median53.5
Q3231.75
95-th percentile1650.05
Maximum3824
Range3824
Interquartile range (IQR)220.5

Descriptive statistics

Standard deviation799.19156
Coefficient of variation (CV)2.3270969
Kurtosis14.21472
Mean343.42857
Median Absolute Deviation (MAD)52.5
Skewness3.6406488
Sum9616
Variance638707.14
MonotonicityNot monotonic
2024-04-30T01:44:21.994836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 2
 
7.1%
0 2
 
7.1%
50 2
 
7.1%
2020 1
 
3.6%
52 1
 
3.6%
963 1
 
3.6%
683 1
 
3.6%
282 1
 
3.6%
385 1
 
3.6%
163 1
 
3.6%
Other values (15) 15
53.6%
ValueCountFrequency (%)
0 2
7.1%
2 2
7.1%
3 1
3.6%
5 1
3.6%
6 1
3.6%
13 1
3.6%
14 1
3.6%
19 1
3.6%
37 1
3.6%
50 2
7.1%
ValueCountFrequency (%)
3824 1
3.6%
2020 1
3.6%
963 1
3.6%
683 1
3.6%
385 1
3.6%
282 1
3.6%
240 1
3.6%
229 1
3.6%
166 1
3.6%
163 1
3.6%

3호선
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203.92857
Minimum0
Maximum1758
Zeros2
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:22.144545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.7
Q115.25
median42
Q3157
95-th percentile1136.15
Maximum1758
Range1758
Interquartile range (IQR)141.75

Descriptive statistics

Standard deviation418.49589
Coefficient of variation (CV)2.052169
Kurtosis9.5102678
Mean203.92857
Median Absolute Deviation (MAD)38.5
Skewness3.1418083
Sum5710
Variance175138.81
MonotonicityNot monotonic
2024-04-30T01:44:22.308283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 2
 
7.1%
2 1
 
3.6%
33 1
 
3.6%
35 1
 
3.6%
492 1
 
3.6%
366 1
 
3.6%
172 1
 
3.6%
262 1
 
3.6%
107 1
 
3.6%
8 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
0 2
7.1%
2 1
3.6%
5 1
3.6%
8 1
3.6%
12 1
3.6%
13 1
3.6%
16 1
3.6%
31 1
3.6%
33 1
3.6%
34 1
3.6%
ValueCountFrequency (%)
1758 1
3.6%
1483 1
3.6%
492 1
3.6%
366 1
3.6%
262 1
3.6%
184 1
3.6%
172 1
3.6%
152 1
3.6%
146 1
3.6%
141 1
3.6%

4호선
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean211.75
Minimum1
Maximum2500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:22.451540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q112
median30
Q3140.25
95-th percentile951.1
Maximum2500
Range2499
Interquartile range (IQR)128.25

Descriptive statistics

Standard deviation507.70388
Coefficient of variation (CV)2.3976571
Kurtosis16.287718
Mean211.75
Median Absolute Deviation (MAD)28
Skewness3.8782156
Sum5929
Variance257763.23
MonotonicityNot monotonic
2024-04-30T01:44:22.556487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2 3
 
10.7%
26 3
 
10.7%
104 1
 
3.6%
591 1
 
3.6%
374 1
 
3.6%
140 1
 
3.6%
207 1
 
3.6%
85 1
 
3.6%
8 1
 
3.6%
208 1
 
3.6%
Other values (14) 14
50.0%
ValueCountFrequency (%)
1 1
 
3.6%
2 3
10.7%
3 1
 
3.6%
8 1
 
3.6%
9 1
 
3.6%
13 1
 
3.6%
23 1
 
3.6%
25 1
 
3.6%
26 3
10.7%
28 1
 
3.6%
ValueCountFrequency (%)
2500 1
3.6%
1145 1
3.6%
591 1
3.6%
374 1
3.6%
208 1
3.6%
207 1
3.6%
141 1
3.6%
140 1
3.6%
104 1
3.6%
100 1
3.6%

5호선
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean255.85714
Minimum0
Maximum1910
Zeros5
Zeros (%)17.9%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:22.665724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113.25
median57
Q3195.75
95-th percentile1181.8
Maximum1910
Range1910
Interquartile range (IQR)182.5

Descriptive statistics

Standard deviation460.89243
Coefficient of variation (CV)1.8013663
Kurtosis5.8835021
Mean255.85714
Median Absolute Deviation (MAD)56.5
Skewness2.4432543
Sum7164
Variance212421.83
MonotonicityNot monotonic
2024-04-30T01:44:22.795513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 5
17.9%
56 5
17.9%
58 3
 
10.7%
1 1
 
3.6%
1214 1
 
3.6%
1122 1
 
3.6%
767 1
 
3.6%
338 1
 
3.6%
122 1
 
3.6%
1910 1
 
3.6%
Other values (8) 8
28.6%
ValueCountFrequency (%)
0 5
17.9%
1 1
 
3.6%
2 1
 
3.6%
17 1
 
3.6%
30 1
 
3.6%
56 5
17.9%
58 3
10.7%
59 1
 
3.6%
106 1
 
3.6%
122 1
 
3.6%
ValueCountFrequency (%)
1910 1
3.6%
1214 1
3.6%
1122 1
3.6%
767 1
3.6%
555 1
3.6%
338 1
3.6%
309 1
3.6%
158 1
3.6%
122 1
3.6%
106 1
3.6%

6호선
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157.82143
Minimum0
Maximum1207
Zeros6
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:22.926458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111
median39
Q3109
95-th percentile838.55
Maximum1207
Range1207
Interquartile range (IQR)98

Descriptive statistics

Standard deviation300.16885
Coefficient of variation (CV)1.9019524
Kurtosis5.9649549
Mean157.82143
Median Absolute Deviation (MAD)39
Skewness2.549633
Sum4419
Variance90101.337
MonotonicityNot monotonic
2024-04-30T01:44:23.038306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 6
21.4%
39 5
17.9%
38 3
10.7%
11 2
 
7.1%
904 1
 
3.6%
717 1
 
3.6%
478 1
 
3.6%
205 1
 
3.6%
80 1
 
3.6%
1207 1
 
3.6%
Other values (6) 6
21.4%
ValueCountFrequency (%)
0 6
21.4%
11 2
 
7.1%
12 1
 
3.6%
38 3
10.7%
39 5
17.9%
40 1
 
3.6%
80 1
 
3.6%
83 1
 
3.6%
107 1
 
3.6%
115 1
 
3.6%
ValueCountFrequency (%)
1207 1
3.6%
904 1
3.6%
717 1
3.6%
478 1
3.6%
205 1
3.6%
140 1
3.6%
115 1
3.6%
107 1
3.6%
83 1
3.6%
80 1
3.6%

7호선
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean209.21429
Minimum0
Maximum1851
Zeros6
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:23.160638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median43
Q3159
95-th percentile1018.5
Maximum1851
Range1851
Interquartile range (IQR)152

Descriptive statistics

Standard deviation416.9347
Coefficient of variation (CV)1.9928596
Kurtosis9.0647517
Mean209.21429
Median Absolute Deviation (MAD)43
Skewness2.934239
Sum5858
Variance173834.54
MonotonicityNot monotonic
2024-04-30T01:44:23.294080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 6
21.4%
42 4
14.3%
44 3
 
10.7%
1 1
 
3.6%
213 1
 
3.6%
869 1
 
3.6%
544 1
 
3.6%
251 1
 
3.6%
83 1
 
3.6%
1851 1
 
3.6%
Other values (8) 8
28.6%
ValueCountFrequency (%)
0 6
21.4%
1 1
 
3.6%
9 1
 
3.6%
14 1
 
3.6%
40 1
 
3.6%
42 4
14.3%
44 3
10.7%
55 1
 
3.6%
83 1
 
3.6%
140 1
 
3.6%
ValueCountFrequency (%)
1851 1
3.6%
1099 1
3.6%
869 1
3.6%
544 1
3.6%
251 1
3.6%
248 1
3.6%
213 1
3.6%
141 1
3.6%
140 1
3.6%
83 1
3.6%

8호선
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.392857
Minimum0
Maximum470
Zeros6
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-04-30T01:44:23.418307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median18.5
Q366.5
95-th percentile396.15
Maximum470
Range470
Interquartile range (IQR)61.5

Descriptive statistics

Standard deviation129.43648
Coefficient of variation (CV)1.7168269
Kurtosis4.083802
Mean75.392857
Median Absolute Deviation (MAD)18.5
Skewness2.2272528
Sum2111
Variance16753.803
MonotonicityNot monotonic
2024-04-30T01:44:23.557368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 6
21.4%
18 4
14.3%
19 3
10.7%
104 2
 
7.1%
5 2
 
7.1%
337 1
 
3.6%
220 1
 
3.6%
38 1
 
3.6%
470 1
 
3.6%
428 1
 
3.6%
Other values (6) 6
21.4%
ValueCountFrequency (%)
0 6
21.4%
5 2
 
7.1%
8 1
 
3.6%
17 1
 
3.6%
18 4
14.3%
19 3
10.7%
34 1
 
3.6%
38 1
 
3.6%
40 1
 
3.6%
54 1
 
3.6%
ValueCountFrequency (%)
470 1
3.6%
428 1
3.6%
337 1
3.6%
220 1
3.6%
118 1
3.6%
104 2
7.1%
54 1
3.6%
40 1
3.6%
38 1
3.6%
34 1
3.6%

Interactions

2024-04-30T01:44:19.404053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:12.964899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:13.640012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:14.676248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.447912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.244673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.921098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:17.678040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:18.526689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.470133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:13.026426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:13.716317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:14.760549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.516304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.312386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.993725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:17.785377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:18.596060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.533501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:13.095618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:13.785988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:14.847991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.582623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.374630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:17.068395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:17.896084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:18.666144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.609485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:13.171541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:14.175578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:14.963870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.662005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.484122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:17.152297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:18.038009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:18.959449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.698974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:13.244348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:14.262188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.044145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.774852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.570145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:17.234341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:18.125747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.039195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.771397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:13.308727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:14.344711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.117308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.876879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.639050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:17.302446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:18.210454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.106275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.842945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:13.398738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:14.439877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.202689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.978941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.719490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:17.388253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:18.302426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.185521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.919400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:13.475106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:14.518810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.282013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.076596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.787262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:17.500020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:18.374410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.255074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.995656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:13.561751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:14.597577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:15.368969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.167233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:16.859694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:17.584876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:18.453250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T01:44:19.329693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T01:44:23.671105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설명장비명단위1호선2호선3호선4호선5호선6호선7호선8호선
연번1.0000.9441.0000.8150.4910.4390.7900.4910.2820.3330.2760.000
시설명0.9441.0001.0000.8970.6850.4260.0000.6850.3850.6220.5490.446
장비명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
단위0.8150.8971.0001.0000.0000.0000.1520.0000.3220.0000.0000.504
1호선0.4910.6851.0000.0001.0000.9970.9881.0001.0001.0001.0000.895
2호선0.4390.4261.0000.0000.9971.0000.9870.9970.9370.9410.9410.832
3호선0.7900.0001.0000.1520.9880.9871.0000.9880.8900.8960.8970.755
4호선0.4910.6851.0000.0001.0000.9970.9881.0001.0001.0001.0000.895
5호선0.2820.3851.0000.3221.0000.9370.8901.0001.0001.0001.0000.933
6호선0.3330.6221.0000.0001.0000.9410.8961.0001.0001.0000.9990.985
7호선0.2760.5491.0000.0001.0000.9410.8971.0001.0000.9991.0000.993
8호선0.0000.4461.0000.5040.8950.8320.7550.8950.9330.9850.9931.000
2024-04-30T01:44:23.814259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번1호선2호선3호선4호선5호선6호선7호선8호선단위
연번1.0000.3800.3960.4140.3730.0990.1750.1430.1400.551
1호선0.3801.0000.9600.9580.9830.7060.7230.7050.7110.000
2호선0.3960.9601.0000.9300.9530.6790.6810.6840.6790.000
3호선0.4140.9580.9301.0000.9680.7500.7580.7510.7600.094
4호선0.3730.9830.9530.9681.0000.7290.7410.7270.7370.000
5호선0.0990.7060.6790.7500.7291.0000.9820.9910.9920.191
6호선0.1750.7230.6810.7580.7410.9821.0000.9830.9910.000
7호선0.1430.7050.6840.7510.7270.9910.9831.0000.9900.000
8호선0.1400.7110.6790.7600.7370.9920.9910.9901.0000.323
단위0.5510.0000.0000.0940.0000.1910.0000.0000.3231.000

Missing values

2024-04-30T01:44:20.128058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T01:44:20.264689image/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

연번시설명장비명단위1호선2호선3호선4호선5호선6호선7호선8호선
01교환설비IP교환기식02221010
12교환설비게이트웨이식1050332656384218
23열차무선기지국장치5191325301298
34열차무선이동국장치321661411001588314140
45열차무선IRCP대53161321105
56재난방송복합통신설비식1037312356384017
67광전송설비전송설비(주/부)식1155362858394419
78무정전전원설비무정전전원설비식1071433259394419
89방송설비방송설비(역사용)식1050342656394218
910배선반배선반식005158394419
연번시설명장비명단위1호선2호선3호선4호선5호선6호선7호선8호선
1819화상모니터링DVR(NVR)대80123184208122808338
1920정보통신망방화벽식00020000
2021정보통신망코어스위치식02020000
2122정보통신망백본스위치식214880000
2223정보통신망에지스위치식32163107850000
2324정보통신망워크그룹스위치식743852622070000
2425비상통화장치승강장식56282172140338205251104
2526비상통화장치콜폰대148683366374767478544220
2627음성유도기음성유도기대2249634925911122717869337
2728열차정보안내시스템열차정보안내시스템식1052352656394218