Overview

Dataset statistics

Number of variables13
Number of observations26
Missing cells26
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory111.1 B

Variable types

Categorical6
Text5
Numeric2

Alerts

철도운영기관명 has constant value ""Constant
선명 has constant value ""Constant
운영시간_평일 is highly overall correlated with 운영시간_휴일 and 1 other fieldsHigh correlation
운영시간_휴일 is highly overall correlated with 운영시간_평일 and 1 other fieldsHigh correlation
주차면수 is highly overall correlated with 기타요금High correlation
주차요금 is highly overall correlated with 기타요금High correlation
기타요금 is highly overall correlated with 주차면수 and 3 other fieldsHigh correlation
출구번호 has 2 (7.7%) missing valuesMissing
월정기권 has 22 (84.6%) missing valuesMissing
전화번호 has 2 (7.7%) missing valuesMissing
주차면수 has unique valuesUnique

Reproduction

Analysis started2024-04-17 10:33:20.054543
Analysis finished2024-04-17 10:33:21.292979
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

철도운영기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
인천교통공사
26 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천교통공사
2nd row인천교통공사
3rd row인천교통공사
4th row인천교통공사
5th row인천교통공사

Common Values

ValueCountFrequency (%)
인천교통공사 26
100.0%

Length

2024-04-17T19:33:21.345678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:33:21.427821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천교통공사 26
100.0%

선명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
인천1호선
26 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천1호선
2nd row인천1호선
3rd row인천1호선
4th row인천1호선
5th row인천1호선

Common Values

ValueCountFrequency (%)
인천1호선 26
100.0%

Length

2024-04-17T19:33:21.505440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:33:21.582983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천1호선 26
100.0%

역명
Text

Distinct17
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-17T19:33:21.704517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.6538462
Min length2

Characters and Unicode

Total characters95
Distinct characters50
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

Unique10 ?
Unique (%)38.5%

Sample

1st row갈산
2nd row경인교대입구
3rd row경인교대입구
4th row계양
5th row계양
ValueCountFrequency (%)
인천터미널 3
11.5%
예술회관 3
11.5%
부평시장 2
 
7.7%
계양 2
 
7.7%
귤현 2
 
7.7%
작전 2
 
7.7%
경인교대입구 2
 
7.7%
센트럴파크 1
 
3.8%
신연수 1
 
3.8%
원인재 1
 
3.8%
Other values (7) 7
26.9%
2024-04-17T19:33:22.005453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 6
 
6.3%
관 3
 
3.2%
천 3
 
3.2%
양 3
 
3.2%
계 3
 
3.2%
장 3
 
3.2%
크 3
 
3.2%
경 3
 
3.2%
회 3
 
3.2%
술 3
 
3.2%
Other values (40) 62
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 95
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 6
 
6.3%
관 3
 
3.2%
천 3
 
3.2%
양 3
 
3.2%
계 3
 
3.2%
장 3
 
3.2%
크 3
 
3.2%
경 3
 
3.2%
회 3
 
3.2%
술 3
 
3.2%
Other values (40) 62
65.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 95
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 6
 
6.3%
관 3
 
3.2%
천 3
 
3.2%
양 3
 
3.2%
계 3
 
3.2%
장 3
 
3.2%
크 3
 
3.2%
경 3
 
3.2%
회 3
 
3.2%
술 3
 
3.2%
Other values (40) 62
65.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 95
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 6
 
6.3%
관 3
 
3.2%
천 3
 
3.2%
양 3
 
3.2%
계 3
 
3.2%
장 3
 
3.2%
크 3
 
3.2%
경 3
 
3.2%
회 3
 
3.2%
술 3
 
3.2%
Other values (40) 62
65.3%

환승주차장명
Text

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-17T19:33:22.174224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length10.384615
Min length3

Characters and Unicode

Total characters270
Distinct characters85
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)92.3%

Sample

1st row갈산역 공영주차장
2nd row계산복개천상류주차장
3rd row계산복개천하류주차장
4th row계양역 공영주차장
5th row계양역 사설주차장
ValueCountFrequency (%)
주차장 7
 
12.7%
공영주차장 4
 
7.3%
계양역 3
 
5.5%
귤현역 2
 
3.6%
굴포천 2
 
3.6%
부설주차장 2
 
3.6%
복개주차장 2
 
3.6%
작전역 2
 
3.6%
부설 1
 
1.8%
신세계백화점 1
 
1.8%
Other values (29) 29
52.7%
2024-04-17T19:33:22.467999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
10.7%
장 27
 
10.0%
차 25
 
9.3%
주 24
 
8.9%
역 9
 
3.3%
공 8
 
3.0%
설 7
 
2.6%
천 7
 
2.6%
계 6
 
2.2%
부 6
 
2.2%
Other values (75) 122
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 236
87.4%
Space Separator 29
 
10.7%
Decimal Number 3
 
1.1%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 27
 
11.4%
차 25
 
10.6%
주 24
 
10.2%
역 9
 
3.8%
공 8
 
3.4%
설 7
 
3.0%
천 7
 
3.0%
계 6
 
2.5%
부 6
 
2.5%
영 5
 
2.1%
Other values (69) 112
47.5%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
1 1
33.3%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 236
87.4%
Common 34
 
12.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 27
 
11.4%
차 25
 
10.6%
주 24
 
10.2%
역 9
 
3.8%
공 8
 
3.4%
설 7
 
3.0%
천 7
 
3.0%
계 6
 
2.5%
부 6
 
2.5%
영 5
 
2.1%
Other values (69) 112
47.5%
Common
ValueCountFrequency (%)
29
85.3%
( 1
 
2.9%
3 1
 
2.9%
) 1
 
2.9%
1 1
 
2.9%
2 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 236
87.4%
ASCII 34
 
12.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
85.3%
( 1
 
2.9%
3 1
 
2.9%
) 1
 
2.9%
1 1
 
2.9%
2 1
 
2.9%
Hangul
ValueCountFrequency (%)
장 27
 
11.4%
차 25
 
10.6%
주 24
 
10.2%
역 9
 
3.8%
공 8
 
3.4%
설 7
 
3.0%
천 7
 
3.0%
계 6
 
2.5%
부 6
 
2.5%
영 5
 
2.1%
Other values (69) 112
47.5%

출구번호
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)29.2%
Missing2
Missing (%)7.7%
Infinite0
Infinite (%)0.0%
Mean3.0833333
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-04-17T19:33:22.567026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.75
median3
Q34
95-th percentile6
Maximum8
Range7
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation1.8862585
Coefficient of variation (CV)0.6117595
Kurtosis0.47560067
Mean3.0833333
Median Absolute Deviation (MAD)1
Skewness0.8871498
Sum74
Variance3.557971
MonotonicityNot monotonic
2024-04-17T19:33:22.661510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 6
23.1%
3 6
23.1%
2 4
15.4%
4 3
11.5%
6 2
 
7.7%
5 2
 
7.7%
8 1
 
3.8%
(Missing) 2
 
7.7%
ValueCountFrequency (%)
1 6
23.1%
2 4
15.4%
3 6
23.1%
4 3
11.5%
5 2
 
7.7%
6 2
 
7.7%
8 1
 
3.8%
ValueCountFrequency (%)
8 1
 
3.8%
6 2
 
7.7%
5 2
 
7.7%
4 3
11.5%
3 6
23.1%
2 4
15.4%
1 6
23.1%

주차면수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean596.07692
Minimum7
Maximum4130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2024-04-17T19:33:22.766933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile25.75
Q1139.5
median233
Q3817
95-th percentile2286.25
Maximum4130
Range4123
Interquartile range (IQR)677.5

Descriptive statistics

Standard deviation912.40079
Coefficient of variation (CV)1.5306762
Kurtosis9.5910346
Mean596.07692
Median Absolute Deviation (MAD)149
Skewness2.9811231
Sum15498
Variance832475.19
MonotonicityNot monotonic
2024-04-17T19:33:22.868763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
167 1
 
3.8%
271 1
 
3.8%
784 1
 
3.8%
278 1
 
3.8%
915 1
 
3.8%
136 1
 
3.8%
150 1
 
3.8%
900 1
 
3.8%
546 1
 
3.8%
46 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
7 1
3.8%
19 1
3.8%
46 1
3.8%
90 1
3.8%
100 1
3.8%
119 1
3.8%
136 1
3.8%
150 1
3.8%
167 1
3.8%
188 1
3.8%
ValueCountFrequency (%)
4130 1
3.8%
2715 1
3.8%
1000 1
3.8%
915 1
3.8%
900 1
3.8%
866 1
3.8%
828 1
3.8%
784 1
3.8%
546 1
3.8%
388 1
3.8%

운영시간_평일
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
00:00~23:59
12 
08:00~21:00
3 
11:00~19:00
2 
09;00~19:00
 
1
08:30~22:30
 
1
Other values (7)
7 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique9 ?
Unique (%)34.6%

Sample

1st row09;00~19:00
2nd row11:00~19:00
3rd row11:00~19:00
4th row08:00~21:00
5th row00:00~23:59

Common Values

ValueCountFrequency (%)
00:00~23:59 12
46.2%
08:00~21:00 3
 
11.5%
11:00~19:00 2
 
7.7%
09;00~19:00 1
 
3.8%
08:30~22:30 1
 
3.8%
10:00~23:00 1
 
3.8%
09:00~19:00 1
 
3.8%
10:00~21:00 1
 
3.8%
08:30-21:00 1
 
3.8%
10:30~20:00 1
 
3.8%
Other values (2) 2
 
7.7%

Length

2024-04-17T19:33:22.965540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00~23:59 12
46.2%
08:00~21:00 3
 
11.5%
11:00~19:00 2
 
7.7%
09;00~19:00 1
 
3.8%
08:30~22:30 1
 
3.8%
10:00~23:00 1
 
3.8%
09:00~19:00 1
 
3.8%
10:00~21:00 1
 
3.8%
08:30-21:00 1
 
3.8%
10:30~20:00 1
 
3.8%
Other values (2) 2
 
7.7%

운영시간_휴일
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Memory size340.0 B
00:00~23:59
12 
08:00~21:00
3 
11:00~19:00
2 
09:00~17:00
2 
09;00~19:00
 
1
Other values (6)
6 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique7 ?
Unique (%)26.9%

Sample

1st row09;00~19:00
2nd row11:00~19:00
3rd row11:00~19:00
4th row08:00~21:00
5th row00:00~23:59

Common Values

ValueCountFrequency (%)
00:00~23:59 12
46.2%
08:00~21:00 3
 
11.5%
11:00~19:00 2
 
7.7%
09:00~17:00 2
 
7.7%
09;00~19:00 1
 
3.8%
08:30~22:30 1
 
3.8%
10:00~23:00 1
 
3.8%
08:30-21:00 1
 
3.8%
10:30~20:00 1
 
3.8%
06:00~23:30 1
 
3.8%

Length

2024-04-17T19:33:23.062159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00~23:59 12
46.2%
08:00~21:00 3
 
11.5%
11:00~19:00 2
 
7.7%
09:00~17:00 2
 
7.7%
09;00~19:00 1
 
3.8%
08:30~22:30 1
 
3.8%
10:00~23:00 1
 
3.8%
08:30-21:00 1
 
3.8%
10:30~20:00 1
 
3.8%
06:00~23:30 1
 
3.8%

주차요금
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
8 
6000원
7 
무료
5 
300원
2 
7000원
1 
Other values (3)
3 

Length

Max length6
Median length5
Mean length4.0769231
Min length2

Unique

Unique4 ?
Unique (%)15.4%

Sample

1st row6000원
2nd row6000원
3rd row6000원
4th row7000원
5th row300원

Common Values

ValueCountFrequency (%)
<NA> 8
30.8%
6000원 7
26.9%
무료 5
19.2%
300원 2
 
7.7%
7000원 1
 
3.8%
5000원 1
 
3.8%
4000원 1
 
3.8%
12000원 1
 
3.8%

Length

2024-04-17T19:33:23.164934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:33:23.280561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8
30.8%
6000원 7
26.9%
무료 5
19.2%
300원 2
 
7.7%
7000원 1
 
3.8%
5000원 1
 
3.8%
4000원 1
 
3.8%
12000원 1
 
3.8%

월정기권
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing22
Missing (%)84.6%
Memory size340.0 B
2024-04-17T19:33:23.391276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters24
Distinct characters4
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

Unique1 ?
Unique (%)25.0%

Sample

1st row70000원
2nd row70000원
3rd row70000원
4th row60000원
ValueCountFrequency (%)
70000원 3
75.0%
60000원 1
 
25.0%
2024-04-17T19:33:23.619106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
66.7%
원 4
 
16.7%
7 3
 
12.5%
6 1
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20
83.3%
Other Letter 4
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
80.0%
7 3
 
15.0%
6 1
 
5.0%
Other Letter
ValueCountFrequency (%)
원 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
83.3%
Hangul 4
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16
80.0%
7 3
 
15.0%
6 1
 
5.0%
Hangul
ValueCountFrequency (%)
원 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
83.3%
Hangul 4
 
16.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16
80.0%
7 3
 
15.0%
6 1
 
5.0%
Hangul
ValueCountFrequency (%)
원 4
100.0%

기타요금
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
15 
300원(15분)
7 
600원(30분)
 
1
1000원(1시간)
 
1
200원(15분)
 
1

Length

Max length10
Median length4
Mean length6.1538462
Min length4

Unique

Unique4 ?
Unique (%)15.4%

Sample

1st row600원(30분)
2nd row300원(15분)
3rd row300원(15분)
4th row300원(15분)
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 15
57.7%
300원(15분) 7
26.9%
600원(30분) 1
 
3.8%
1000원(1시간) 1
 
3.8%
200원(15분) 1
 
3.8%
600원(15분) 1
 
3.8%

Length

2024-04-17T19:33:23.749484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:33:23.843846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 15
57.7%
300원(15분 7
26.9%
600원(30분 1
 
3.8%
1000원(1시간 1
 
3.8%
200원(15분 1
 
3.8%
600원(15분 1
 
3.8%

환승주차장운영기관
Text

Distinct21
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-17T19:33:24.000508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10.5
Mean length7.7692308
Min length3

Characters and Unicode

Total characters202
Distinct characters89
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)69.2%

Sample

1st row부평구 시설관리공단
2nd row계산1동 주민자치위원회
3rd row계산시장 진흥협동조합
4th row코레일공항철도(위탁-하이파킹)
5th row인천교통공사
ValueCountFrequency (%)
부평구 3
 
9.1%
인천교통공사 3
 
9.1%
시설관리공단 3
 
9.1%
신세계백화점 2
 
6.1%
주민자치위원회 2
 
6.1%
연수구청 1
 
3.0%
동부공원사업소 1
 
3.0%
경제자유구역청 1
 
3.0%
홈플러스 1
 
3.0%
작전1동 1
 
3.0%
Other values (15) 15
45.5%
2024-04-17T19:33:24.287177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 11
 
5.4%
시 9
 
4.5%
구 7
 
3.5%
7
 
3.5%
인 6
 
3.0%
설 6
 
3.0%
관 6
 
3.0%
단 6
 
3.0%
천 6
 
3.0%
리 5
 
2.5%
Other values (79) 133
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 186
92.1%
Space Separator 7
 
3.5%
Close Punctuation 2
 
1.0%
Open Punctuation 2
 
1.0%
Decimal Number 2
 
1.0%
Lowercase Letter 2
 
1.0%
Dash Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 11
 
5.9%
시 9
 
4.8%
구 7
 
3.8%
인 6
 
3.2%
설 6
 
3.2%
관 6
 
3.2%
단 6
 
3.2%
천 6
 
3.2%
리 5
 
2.7%
사 4
 
2.2%
Other values (72) 120
64.5%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 185
91.6%
Common 14
 
6.9%
Latin 2
 
1.0%
Han 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 11
 
5.9%
시 9
 
4.9%
구 7
 
3.8%
인 6
 
3.2%
설 6
 
3.2%
관 6
 
3.2%
단 6
 
3.2%
천 6
 
3.2%
리 5
 
2.7%
사 4
 
2.2%
Other values (71) 119
64.3%
Common
ValueCountFrequency (%)
7
50.0%
) 2
 
14.3%
( 2
 
14.3%
1 2
 
14.3%
- 1
 
7.1%
Latin
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Han
ValueCountFrequency (%)
市 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 185
91.6%
ASCII 16
 
7.9%
CJK 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 11
 
5.9%
시 9
 
4.9%
구 7
 
3.8%
인 6
 
3.2%
설 6
 
3.2%
관 6
 
3.2%
단 6
 
3.2%
천 6
 
3.2%
리 5
 
2.7%
사 4
 
2.2%
Other values (71) 119
64.3%
ASCII
ValueCountFrequency (%)
7
43.8%
) 2
 
12.5%
( 2
 
12.5%
1 2
 
12.5%
- 1
 
6.2%
s 1
 
6.2%
k 1
 
6.2%
CJK
ValueCountFrequency (%)
市 1
100.0%

전화번호
Text

MISSING 

Distinct21
Distinct (%)87.5%
Missing2
Missing (%)7.7%
Memory size340.0 B
2024-04-17T19:33:24.445234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.875
Min length8

Characters and Unicode

Total characters261
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)79.2%

Sample

1st row1566-8578
2nd row032-450-4740
3rd row032-545-4470
4th row1688-1054
5th row02-2268-8360
ValueCountFrequency (%)
1566-8578 3
 
12.5%
02-2268-8360 2
 
8.3%
450-3950 1
 
4.2%
570-7153 1
 
4.2%
032-260-0750 1
 
4.2%
032-540-8025 1
 
4.2%
032-450-4803 1
 
4.2%
032-430-1046 1
 
4.2%
032-430-7317 1
 
4.2%
032-450-3950 1
 
4.2%
Other values (11) 11
45.8%
2024-04-17T19:33:24.730426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 47
18.0%
- 40
15.3%
5 28
10.7%
2 28
10.7%
3 24
9.2%
8 21
8.0%
4 19
7.3%
7 18
 
6.9%
6 15
 
5.7%
1 14
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 221
84.7%
Dash Punctuation 40
 
15.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 47
21.3%
5 28
12.7%
2 28
12.7%
3 24
10.9%
8 21
9.5%
4 19
8.6%
7 18
 
8.1%
6 15
 
6.8%
1 14
 
6.3%
9 7
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 261
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 47
18.0%
- 40
15.3%
5 28
10.7%
2 28
10.7%
3 24
9.2%
8 21
8.0%
4 19
7.3%
7 18
 
6.9%
6 15
 
5.7%
1 14
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 261
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 47
18.0%
- 40
15.3%
5 28
10.7%
2 28
10.7%
3 24
9.2%
8 21
8.0%
4 19
7.3%
7 18
 
6.9%
6 15
 
5.7%
1 14
 
5.4%

Interactions

2024-04-17T19:33:20.835166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:33:20.705022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:33:20.901026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:33:20.773390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T19:33:24.832402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
역명환승주차장명출구번호주차면수운영시간_평일운영시간_휴일주차요금월정기권기타요금환승주차장운영기관전화번호
역명1.0001.0000.8850.8090.8150.9010.9701.0001.0000.9270.900
환승주차장명1.0001.0001.0001.0001.0001.0001.0001.0001.0000.9741.000
출구번호0.8851.0001.0000.0000.6210.6000.0000.0000.0000.9160.914
주차면수0.8091.0000.0001.0000.6820.7300.688NaN0.7560.9701.000
운영시간_평일0.8151.0000.6210.6821.0001.0000.6280.0001.0000.0000.000
운영시간_휴일0.9011.0000.6000.7301.0001.0000.7120.0001.0000.8880.881
주차요금0.9701.0000.0000.6880.6280.7121.0001.0000.9771.0001.000
월정기권1.0001.0000.000NaN0.0000.0001.0001.000NaN1.0001.000
기타요금1.0001.0000.0000.7561.0001.0000.977NaN1.0000.7420.720
환승주차장운영기관0.9270.9740.9160.9700.0000.8881.0001.0000.7421.0001.000
전화번호0.9001.0000.9141.0000.0000.8811.0001.0000.7201.0001.000
2024-04-17T19:33:24.945033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차요금운영시간_평일운영시간_휴일기타요금
주차요금1.0000.2600.3980.769
운영시간_평일0.2601.0000.9660.756
운영시간_휴일0.3980.9661.0000.816
기타요금0.7690.7560.8161.000
2024-04-17T19:33:25.026197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출구번호주차면수운영시간_평일운영시간_휴일주차요금기타요금
출구번호1.0000.1680.2640.2680.0000.000
주차면수0.1681.0000.3580.4190.4740.631
운영시간_평일0.2640.3581.0000.9660.2600.756
운영시간_휴일0.2680.4190.9661.0000.3980.816
주차요금0.0000.4740.2600.3981.0000.769
기타요금0.0000.6310.7560.8160.7691.000

Missing values

2024-04-17T19:33:20.989773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T19:33:21.123960image/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.
2024-04-17T19:33:21.231738image/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

철도운영기관명선명역명환승주차장명출구번호주차면수운영시간_평일운영시간_휴일주차요금월정기권기타요금환승주차장운영기관전화번호
0인천교통공사인천1호선갈산갈산역 공영주차장216709;00~19:0009;00~19:006000원<NA>600원(30분)부평구 시설관리공단1566-8578
1인천교통공사인천1호선경인교대입구계산복개천상류주차장611911:00~19:0011:00~19:006000원<NA>300원(15분)계산1동 주민자치위원회032-450-4740
2인천교통공사인천1호선경인교대입구계산복개천하류주차장620411:00~19:0011:00~19:006000원<NA>300원(15분)계산시장 진흥협동조합032-545-4470
3인천교통공사인천1호선계양계양역 공영주차장126208:00~21:0008:00~21:007000원70000원300원(15분)코레일공항철도(위탁-하이파킹)1688-1054
4인천교통공사인천1호선계양계양역 사설주차장118800:00~23:5900:00~23:59300원70000원<NA>인천교통공사02-2268-8360
5인천교통공사인천1호선계양역계양역119200:00~23:5900:00~23:59300원70000원<NA>인천교통공사02-2268-8360
6인천교통공사인천1호선귤현귤현역 부설주차장1700:00~23:5900:00~23:59<NA><NA><NA>인천교통공사032-515-9104
7인천교통공사인천1호선귤현귤현역 부설주차장19000:00~23:5900:00~23:59<NA><NA><NA>인천시<NA>
8인천교통공사인천1호선동막평생학습관 및 공영주차장310008:30~22:3008:30~22:30무료<NA><NA>연수구평생학습관032-820-1190
9인천교통공사인천1호선동춘이마트 주차장186610:00~23:0010:00~23:00무료<NA><NA>이마트1588-7270
철도운영기관명선명역명환승주차장명출구번호주차면수운영시간_평일운영시간_휴일주차요금월정기권기타요금환승주차장운영기관전화번호
16인천교통공사인천1호선예술회관문예회관부설주차장<NA>82800:00~23:5900:00~23:59<NA><NA><NA>市시설관리공단570-7153
17인천교통공사인천1호선예술회관롯데백화점 인천점 주차장5100010:30~20:0010:30~20:00<NA><NA><NA>롯데백화점450-3950
18인천교통공사인천1호선원인재원인재역 주차장54600:00~23:5900:00~23:59무료60000원<NA>한국철도시설공단032-749-8752
19인천교통공사인천1호선인천터미널인천터미널 부설 주차장354606:00~23:3006:00~23:3012000원<NA>600원(15분)신세계백화점032-450-3950
20인천교통공사인천1호선인천터미널신세계백화점 인천터미널점 주차장290010:30~23:0010:30~23:00<NA><NA><NA>구월농축산물 도매시장032-430-7317
21인천교통공사인천1호선인천터미널구월농축산물도매시장215000:00~23:5900:00~23:59<NA><NA><NA>신세계백화점032-430-1046
22인천교통공사인천1호선작전작전역 환승 동측 주차장313608:00~21:0008:00~21:006000원<NA>300원(15분)작전1동 주민자치위원회032-450-4803
23인천교통공사인천1호선작전작전역 서측 노상 공영 주차장891508:00~21:0008:00~21:006000원<NA>300원(15분)홈플러스032-540-8025
24인천교통공사인천1호선지식정보단지공영주차장327800:00~23:5900:00~23:59무료<NA><NA>경제자유구역청032-260-0750
25인천교통공사인천1호선테크노파크미추홀타워 주자장478400:00~23:5900:00~23:59무료<NA><NA>(재)인천테크노파크032-899-1588