Overview

Dataset statistics

Number of variables15
Number of observations32
Missing cells83
Missing cells (%)17.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory125.1 B

Variable types

Text3
Categorical1
Numeric1
Unsupported10

Dataset

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

Alerts

Unnamed: 2 has constant value ""Constant
시 설 명 has 9 (28.1%) missing valuesMissing
Unnamed: 1 has 9 (28.1%) missing valuesMissing
Unnamed: 2 has 31 (96.9%) missing valuesMissing
계 has 4 (12.5%) missing valuesMissing
1~4호선 has 3 (9.4%) missing valuesMissing
Unnamed: 6 has 3 (9.4%) missing valuesMissing
Unnamed: 7 has 3 (9.4%) missing valuesMissing
Unnamed: 8 has 3 (9.4%) missing valuesMissing
Unnamed: 9 has 3 (9.4%) missing valuesMissing
5~8호선 has 3 (9.4%) missing valuesMissing
Unnamed: 11 has 3 (9.4%) missing valuesMissing
Unnamed: 12 has 3 (9.4%) missing valuesMissing
Unnamed: 13 has 3 (9.4%) missing valuesMissing
Unnamed: 14 has 3 (9.4%) missing valuesMissing
1~4호선 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
5~8호선 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-29 16:43:57.224847
Analysis finished2024-04-29 16:43:59.265002
Duration2.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시 설 명
Text

MISSING 

Distinct22
Distinct (%)95.7%
Missing9
Missing (%)28.1%
Memory size388.0 B
2024-04-30T01:43:59.377266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length2
Mean length3.5652174
Min length2

Characters and Unicode

Total characters82
Distinct characters50
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)91.3%

Sample

1st row교환
2nd row설비
3rd row열차
4th row무선
5th row재난
ValueCountFrequency (%)
설비 2
 
8.7%
토크백(주장치 1
 
4.3%
선로 1
 
4.3%
음성유도기 1
 
4.3%
장치 1
 
4.3%
통화 1
 
4.3%
비상 1
 
4.3%
통신망 1
 
4.3%
정보 1
 
4.3%
모니터링 1
 
4.3%
Other values (12) 12
52.2%
2024-04-30T01:43:59.670072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 6
 
7.3%
설 5
 
6.1%
전 4
 
4.9%
화 3
 
3.7%
정 3
 
3.7%
송 3
 
3.7%
선 3
 
3.7%
무 2
 
2.4%
상 2
 
2.4%
기 2
 
2.4%
Other values (40) 49
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78
95.1%
Close Punctuation 2
 
2.4%
Open Punctuation 2
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 6
 
7.7%
설 5
 
6.4%
전 4
 
5.1%
화 3
 
3.8%
정 3
 
3.8%
송 3
 
3.8%
선 3
 
3.8%
무 2
 
2.6%
상 2
 
2.6%
기 2
 
2.6%
Other values (38) 45
57.7%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78
95.1%
Common 4
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 6
 
7.7%
설 5
 
6.4%
전 4
 
5.1%
화 3
 
3.8%
정 3
 
3.8%
송 3
 
3.8%
선 3
 
3.8%
무 2
 
2.6%
상 2
 
2.6%
기 2
 
2.6%
Other values (38) 45
57.7%
Common
ValueCountFrequency (%)
) 2
50.0%
( 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78
95.1%
ASCII 4
 
4.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 6
 
7.7%
설 5
 
6.4%
전 4
 
5.1%
화 3
 
3.8%
정 3
 
3.8%
송 3
 
3.8%
선 3
 
3.8%
무 2
 
2.6%
상 2
 
2.6%
기 2
 
2.6%
Other values (38) 45
57.7%
ASCII
ValueCountFrequency (%)
) 2
50.0%
( 2
50.0%

Unnamed: 1
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing9
Missing (%)28.1%
Memory size388.0 B
2024-04-30T01:43:59.859150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.9565217
Min length2

Characters and Unicode

Total characters114
Distinct characters78
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st rowIP교환기
2nd row역사용
3rd row(gateway)
4th row기지국
5th row이동국
ValueCountFrequency (%)
ip교환기 1
 
4.3%
각종 1
 
4.3%
승강장 1
 
4.3%
워크그룹스위치 1
 
4.3%
에지스위치 1
 
4.3%
백본스위치 1
 
4.3%
코어스위치 1
 
4.3%
방화벽 1
 
4.3%
dvr(nvr 1
 
4.3%
카메라 1
 
4.3%
Other values (13) 13
56.5%
2024-04-30T01:44:00.180581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
위 4
 
3.5%
) 4
 
3.5%
스 4
 
3.5%
( 4
 
3.5%
치 4
 
3.5%
R 3
 
2.6%
선 3
 
2.6%
용 3
 
2.6%
비 2
 
1.8%
신 2
 
1.8%
Other values (68) 81
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86
75.4%
Uppercase Letter 12
 
10.5%
Lowercase Letter 7
 
6.1%
Close Punctuation 4
 
3.5%
Open Punctuation 4
 
3.5%
Other Punctuation 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
위 4
 
4.7%
스 4
 
4.7%
치 4
 
4.7%
선 3
 
3.5%
용 3
 
3.5%
비 2
 
2.3%
신 2
 
2.3%
설 2
 
2.3%
전 2
 
2.3%
본 2
 
2.3%
Other values (52) 58
67.4%
Uppercase Letter
ValueCountFrequency (%)
R 3
25.0%
I 2
16.7%
V 2
16.7%
P 2
16.7%
D 1
 
8.3%
N 1
 
8.3%
C 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
a 2
28.6%
g 1
14.3%
t 1
14.3%
e 1
14.3%
w 1
14.3%
y 1
14.3%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86
75.4%
Latin 19
 
16.7%
Common 9
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
위 4
 
4.7%
스 4
 
4.7%
치 4
 
4.7%
선 3
 
3.5%
용 3
 
3.5%
비 2
 
2.3%
신 2
 
2.3%
설 2
 
2.3%
전 2
 
2.3%
본 2
 
2.3%
Other values (52) 58
67.4%
Latin
ValueCountFrequency (%)
R 3
15.8%
I 2
10.5%
V 2
10.5%
P 2
10.5%
a 2
10.5%
D 1
 
5.3%
N 1
 
5.3%
g 1
 
5.3%
t 1
 
5.3%
e 1
 
5.3%
Other values (3) 3
15.8%
Common
ValueCountFrequency (%)
) 4
44.4%
( 4
44.4%
/ 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86
75.4%
ASCII 28
 
24.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
위 4
 
4.7%
스 4
 
4.7%
치 4
 
4.7%
선 3
 
3.5%
용 3
 
3.5%
비 2
 
2.3%
신 2
 
2.3%
설 2
 
2.3%
전 2
 
2.3%
본 2
 
2.3%
Other values (52) 58
67.4%
ASCII
ValueCountFrequency (%)
) 4
14.3%
( 4
14.3%
R 3
10.7%
I 2
 
7.1%
V 2
 
7.1%
P 2
 
7.1%
a 2
 
7.1%
D 1
 
3.6%
N 1
 
3.6%
g 1
 
3.6%
Other values (6) 6
21.4%

Unnamed: 2
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing31
Missing (%)96.9%
Memory size388.0 B
2024-04-30T01:44:00.270347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
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

Unique1 ?
Unique (%)100.0%

Sample

1st row역사
ValueCountFrequency (%)
역사 1
100.0%
2024-04-30T01:44:00.446556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
역 1
50.0%
사 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 1
50.0%
사 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 1
50.0%
사 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
역 1
50.0%
사 1
50.0%

단위
Categorical

Distinct5
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size388.0 B
식
10 
<NA>
9 
대
8 
Km
3 
장치
2 

Length

Max length4
Median length1
Mean length2
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row식
3rd row<NA>
4th row<NA>
5th row장치

Common Values

ValueCountFrequency (%)
식 10
31.2%
<NA> 9
28.1%
대 8
25.0%
Km 3
 
9.4%
장치 2
 
6.2%

Length

2024-04-30T01:44:00.572506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T01:44:00.678292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식 10
31.2%
na 9
28.1%
대 8
25.0%
km 3
 
9.4%
장치 2
 
6.2%

계
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)100.0%
Missing4
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean1421.0357
Minimum2
Maximum10926
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-04-30T01:44:00.783652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.05
Q1154.25
median301
Q31034.25
95-th percentile7450.3
Maximum10926
Range10924
Interquartile range (IQR)880

Descriptive statistics

Standard deviation2647.0474
Coefficient of variation (CV)1.8627593
Kurtosis7.1234419
Mean1421.0357
Median Absolute Deviation (MAD)274.5
Skewness2.7251407
Sum39789
Variance7006860.1
MonotonicityNot monotonic
2024-04-30T01:44:00.909172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
8613 1
 
3.1%
281 1
 
3.1%
5291 1
 
3.1%
3679 1
 
3.1%
1561 1
 
3.1%
933 1
 
3.1%
524 1
 
3.1%
46 1
 
3.1%
4 1
 
3.1%
2 1
 
3.1%
Other values (18) 18
56.2%
(Missing) 4
 
12.5%
ValueCountFrequency (%)
2 1
3.1%
4 1
3.1%
7 1
3.1%
46 1
3.1%
71 1
3.1%
87 1
3.1%
104 1
3.1%
171 1
3.1%
257 1
3.1%
276 1
3.1%
ValueCountFrequency (%)
10926 1
3.1%
8613 1
3.1%
5291 1
3.1%
3679 1
3.1%
1584 1
3.1%
1561 1
3.1%
1305 1
3.1%
944 1
3.1%
933 1
3.1%
826 1
3.1%

1~4호선
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)9.4%
Memory size388.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)9.4%
Memory size388.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)9.4%
Memory size388.0 B

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)9.4%
Memory size388.0 B

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)9.4%
Memory size388.0 B

5~8호선
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)9.4%
Memory size388.0 B

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)9.4%
Memory size388.0 B

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)9.4%
Memory size388.0 B

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)9.4%
Memory size388.0 B

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)9.4%
Memory size388.0 B

Interactions

2024-04-30T01:43:58.502152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T01:44:01.002573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시 설 명Unnamed: 1단위계
시 설 명1.0001.0001.0000.935
Unnamed: 11.0001.0001.0001.000
단위1.0001.0001.0000.000
계0.9351.0000.0001.000
2024-04-30T01:44:01.098991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계단위
계1.0000.000
단위0.0001.000

Missing values

2024-04-30T01:43:58.699632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T01:43:58.896487image/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.
2024-04-30T01:43:59.095222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시 설 명Unnamed: 1Unnamed: 2단위계1~4호선Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 95~8호선Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14
0<NA><NA><NA><NA><NA>소계1호선2호선3호선4호선소계5호선6호선7호선8호선
1교환IP교환기<NA>식76-22211
2설비역사용<NA><NA>2761191050332615751385117
3<NA>(gateway)<NA><NA><NA>NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
4열차기지국<NA>장치104515231310532212118
5무선이동국<NA>장치826410321281461044161528314140
6<NA>IRCP<NA>대71535181713182115
7재난복합통신설비<NA>식2571021037312415551384917
8방송<NA><NA><NA><NA>NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
9광전송설비전송설비(주/부)<NA>식3051301155362817557425620
시 설 명Unnamed: 1Unnamed: 2단위계1~4호선Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 95~8호선Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14
22정보방화벽<NA>식2220
23통신망코어스위치<NA><NA>4440
24<NA>백본스위치<NA><NA>464622012120
25<NA>에지스위치<NA><NA>524524442171451180
26<NA>워크그룹스위치<NA><NA>9339337439026120800000
27비상승강장<NA>식156165056282172140911304205302100
28통화<NA><NA><NA><NA>NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
29장치콜폰<NA>대367916311507253803762048643482698225
30음성유도기<NA><NA>대5291227122496549858430209127101094304
31열차정보안내시스템<NA><NA>식2811231052352615851395117