Overview

Dataset statistics

Number of variables8
Number of observations60
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory69.2 B

Variable types

Numeric3
Text5

Dataset

Description인천광역시 소재지의 일반(법인)택시 현황(일련번호, 회사명, 대표자, 전화번호, 주소, 우편번호, 면허대수 등) 데이터 입니다.
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15045241

Alerts

대표자 has 1 (1.7%) missing valuesMissing
일련번호 has unique valuesUnique
회사명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-01-28 06:34:44.313494
Analysis finished2024-01-28 06:34:45.746479
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.5
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-01-28T15:34:45.797627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.95
Q115.75
median30.5
Q345.25
95-th percentile57.05
Maximum60
Range59
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation17.464249
Coefficient of variation (CV)0.57259833
Kurtosis-1.2
Mean30.5
Median Absolute Deviation (MAD)15
Skewness0
Sum1830
Variance305
MonotonicityStrictly increasing
2024-01-28T15:34:45.903378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.7%
32 1
 
1.7%
34 1
 
1.7%
35 1
 
1.7%
36 1
 
1.7%
37 1
 
1.7%
38 1
 
1.7%
39 1
 
1.7%
40 1
 
1.7%
41 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
1 1
1.7%
2 1
1.7%
3 1
1.7%
4 1
1.7%
5 1
1.7%
6 1
1.7%
7 1
1.7%
8 1
1.7%
9 1
1.7%
10 1
1.7%
ValueCountFrequency (%)
60 1
1.7%
59 1
1.7%
58 1
1.7%
57 1
1.7%
56 1
1.7%
55 1
1.7%
54 1
1.7%
53 1
1.7%
52 1
1.7%
51 1
1.7%

회사명
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-01-28T15:34:46.114371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.95
Min length5

Characters and Unicode

Total characters417
Distinct characters71
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row검단교통(주)
2nd row경영기업(주)
3rd row경인운수(자)
4th row경진운수(자)
5th row공성교통(주)
ValueCountFrequency (%)
검단교통(주 1
 
1.6%
자)성진기업 1
 
1.6%
송도교통(주 1
 
1.6%
스마트택시㈜ 1
 
1.6%
신광기업(자 1
 
1.6%
신성교통(주 1
 
1.6%
신신운수(자 1
 
1.6%
신원운수(주 1
 
1.6%
신진택시(주 1
 
1.6%
주)알씨운수 1
 
1.6%
Other values (51) 51
83.6%
2024-01-28T15:34:46.425885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 57
 
13.7%
) 57
 
13.7%
주 29
 
7.0%
자 24
 
5.8%
운 24
 
5.8%
수 23
 
5.5%
교 13
 
3.1%
통 13
 
3.1%
업 13
 
3.1%
기 11
 
2.6%
Other values (61) 153
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 300
71.9%
Open Punctuation 57
 
13.7%
Close Punctuation 57
 
13.7%
Other Symbol 2
 
0.5%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 29
 
9.7%
자 24
 
8.0%
운 24
 
8.0%
수 23
 
7.7%
교 13
 
4.3%
통 13
 
4.3%
업 13
 
4.3%
기 11
 
3.7%
신 9
 
3.0%
시 8
 
2.7%
Other values (57) 133
44.3%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 302
72.4%
Common 115
 
27.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 29
 
9.6%
자 24
 
7.9%
운 24
 
7.9%
수 23
 
7.6%
교 13
 
4.3%
통 13
 
4.3%
업 13
 
4.3%
기 11
 
3.6%
신 9
 
3.0%
시 8
 
2.6%
Other values (58) 135
44.7%
Common
ValueCountFrequency (%)
( 57
49.6%
) 57
49.6%
1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 300
71.9%
ASCII 115
 
27.6%
None 2
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 57
49.6%
) 57
49.6%
1
 
0.9%
Hangul
ValueCountFrequency (%)
주 29
 
9.7%
자 24
 
8.0%
운 24
 
8.0%
수 23
 
7.7%
교 13
 
4.3%
통 13
 
4.3%
업 13
 
4.3%
기 11
 
3.7%
신 9
 
3.0%
시 8
 
2.7%
Other values (57) 133
44.3%
None
ValueCountFrequency (%)
㈜ 2
100.0%

대표자
Text

MISSING 

Distinct54
Distinct (%)91.5%
Missing1
Missing (%)1.7%
Memory size612.0 B
2024-01-28T15:34:46.615792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length4.8305085
Min length3

Characters and Unicode

Total characters285
Distinct characters91
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

Unique49 ?
Unique (%)83.1%

Sample

1st row김복태+김민정
2nd row차영남+차준환
3rd row유충희
4th row한도섭
5th row진충남+진형민
ValueCountFrequency (%)
유충희 2
 
3.4%
안종태 2
 
3.4%
김영종 2
 
3.4%
유흥주+윤래성 2
 
3.4%
하기철 2
 
3.4%
허주현 1
 
1.7%
김복태+김민정 1
 
1.7%
오성국 1
 
1.7%
김철주+양준모 1
 
1.7%
이해영 1
 
1.7%
Other values (44) 44
74.6%
2024-01-28T15:34:46.892941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 28
 
9.8%
+ 27
 
9.5%
성 10
 
3.5%
주 9
 
3.2%
이 8
 
2.8%
철 8
 
2.8%
종 8
 
2.8%
영 7
 
2.5%
환 6
 
2.1%
준 6
 
2.1%
Other values (81) 168
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 258
90.5%
Math Symbol 27
 
9.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 28
 
10.9%
성 10
 
3.9%
주 9
 
3.5%
이 8
 
3.1%
철 8
 
3.1%
종 8
 
3.1%
영 7
 
2.7%
환 6
 
2.3%
준 6
 
2.3%
수 6
 
2.3%
Other values (80) 162
62.8%
Math Symbol
ValueCountFrequency (%)
+ 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 258
90.5%
Common 27
 
9.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 28
 
10.9%
성 10
 
3.9%
주 9
 
3.5%
이 8
 
3.1%
철 8
 
3.1%
종 8
 
3.1%
영 7
 
2.7%
환 6
 
2.3%
준 6
 
2.3%
수 6
 
2.3%
Other values (80) 162
62.8%
Common
ValueCountFrequency (%)
+ 27
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 258
90.5%
ASCII 27
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 28
 
10.9%
성 10
 
3.9%
주 9
 
3.5%
이 8
 
3.1%
철 8
 
3.1%
종 8
 
3.1%
영 7
 
2.7%
환 6
 
2.3%
준 6
 
2.3%
수 6
 
2.3%
Other values (80) 162
62.8%
ASCII
ValueCountFrequency (%)
+ 27
100.0%

전화번호
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-01-28T15:34:47.099605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters720
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

Unique60 ?
Unique (%)100.0%

Sample

1st row032-563-1977
2nd row032-862-1515
3rd row032-574-2299
4th row032-525-3331
5th row032-578-7900
ValueCountFrequency (%)
032-563-1977 1
 
1.7%
032-862-1515 1
 
1.7%
032-934-1588 1
 
1.7%
032-438-1221 1
 
1.7%
032-572-3133 1
 
1.7%
032-576-2774 1
 
1.7%
032-862-0876 1
 
1.7%
032-862-6001 1
 
1.7%
032-578-1611 1
 
1.7%
032-571-3910 1
 
1.7%
Other values (50) 50
83.3%
2024-01-28T15:34:47.389441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 120
16.7%
2 111
15.4%
3 99
13.8%
0 96
13.3%
5 59
8.2%
1 56
7.8%
7 52
7.2%
8 49
6.8%
6 29
 
4.0%
4 27
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
83.3%
Dash Punctuation 120
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 111
18.5%
3 99
16.5%
0 96
16.0%
5 59
9.8%
1 56
9.3%
7 52
8.7%
8 49
8.2%
6 29
 
4.8%
4 27
 
4.5%
9 22
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 720
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 120
16.7%
2 111
15.4%
3 99
13.8%
0 96
13.3%
5 59
8.2%
1 56
7.8%
7 52
7.2%
8 49
6.8%
6 29
 
4.0%
4 27
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 120
16.7%
2 111
15.4%
3 99
13.8%
0 96
13.3%
5 59
8.2%
1 56
7.8%
7 52
7.2%
8 49
6.8%
6 29
 
4.0%
4 27
 
3.8%

팩스번호
Text

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-01-28T15:34:47.577912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters720
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

Unique58 ?
Unique (%)96.7%

Sample

1st row032-563-1971
2nd row032-863-8819
3rd row032-574-0311
4th row032-525-3339
5th row032-578-7902
ValueCountFrequency (%)
032-577-9114 2
 
3.3%
032-423-3120 1
 
1.7%
032-576-9021 1
 
1.7%
032-439-1221 1
 
1.7%
032-572-6133 1
 
1.7%
032-583-9339 1
 
1.7%
032-862-0875 1
 
1.7%
032-862-6003 1
 
1.7%
032-581-1611 1
 
1.7%
032-572-1116 1
 
1.7%
Other values (49) 49
81.7%
2024-01-28T15:34:47.847400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 120
16.7%
2 110
15.3%
3 108
15.0%
0 89
12.4%
7 53
7.4%
1 53
7.4%
5 50
6.9%
8 46
 
6.4%
6 34
 
4.7%
9 29
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
83.3%
Dash Punctuation 120
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 110
18.3%
3 108
18.0%
0 89
14.8%
7 53
8.8%
1 53
8.8%
5 50
8.3%
8 46
7.7%
6 34
 
5.7%
9 29
 
4.8%
4 28
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 720
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 120
16.7%
2 110
15.3%
3 108
15.0%
0 89
12.4%
7 53
7.4%
1 53
7.4%
5 50
6.9%
8 46
 
6.4%
6 34
 
4.7%
9 29
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 120
16.7%
2 110
15.3%
3 108
15.0%
0 89
12.4%
7 53
7.4%
1 53
7.4%
5 50
6.9%
8 46
 
6.4%
6 34
 
4.7%
9 29
 
4.0%

주 소
Text

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-01-28T15:34:48.089745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length22
Mean length18.8
Min length15

Characters and Unicode

Total characters1128
Distinct characters83
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

Unique58 ?
Unique (%)96.7%

Sample

1st row인천광역시 서구 봉수대로 1493
2nd row인천광역시 미추홀구 염창로 124
3rd row인천광역시 서구 옻우물로 20
4th row인천광역시 부평구 부평북로 367
5th row인천광역시 서구 중봉대로198번길 34
ValueCountFrequency (%)
인천광역시 60
24.8%
서구 23
 
9.5%
미추홀구 15
 
6.2%
남동구 7
 
2.9%
계양구 5
 
2.1%
부평구 5
 
2.1%
22 4
 
1.7%
중봉대로198번길 3
 
1.2%
석정로 3
 
1.2%
염창로 3
 
1.2%
Other values (98) 114
47.1%
2024-01-28T15:34:48.422947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
182
16.1%
인 62
 
5.5%
천 61
 
5.4%
역 60
 
5.3%
시 60
 
5.3%
로 60
 
5.3%
광 60
 
5.3%
구 58
 
5.1%
1 43
 
3.8%
3 28
 
2.5%
Other values (73) 454
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 729
64.6%
Decimal Number 210
 
18.6%
Space Separator 182
 
16.1%
Dash Punctuation 5
 
0.4%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 62
 
8.5%
천 61
 
8.4%
역 60
 
8.2%
시 60
 
8.2%
로 60
 
8.2%
광 60
 
8.2%
구 58
 
8.0%
서 24
 
3.3%
길 24
 
3.3%
번 23
 
3.2%
Other values (60) 237
32.5%
Decimal Number
ValueCountFrequency (%)
1 43
20.5%
3 28
13.3%
2 28
13.3%
4 20
9.5%
9 17
 
8.1%
7 16
 
7.6%
8 15
 
7.1%
5 15
 
7.1%
6 14
 
6.7%
0 14
 
6.7%
Space Separator
ValueCountFrequency (%)
182
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 729
64.6%
Common 399
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 62
 
8.5%
천 61
 
8.4%
역 60
 
8.2%
시 60
 
8.2%
로 60
 
8.2%
광 60
 
8.2%
구 58
 
8.0%
서 24
 
3.3%
길 24
 
3.3%
번 23
 
3.2%
Other values (60) 237
32.5%
Common
ValueCountFrequency (%)
182
45.6%
1 43
 
10.8%
3 28
 
7.0%
2 28
 
7.0%
4 20
 
5.0%
9 17
 
4.3%
7 16
 
4.0%
8 15
 
3.8%
5 15
 
3.8%
6 14
 
3.5%
Other values (3) 21
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 729
64.6%
ASCII 399
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
182
45.6%
1 43
 
10.8%
3 28
 
7.0%
2 28
 
7.0%
4 20
 
5.0%
9 17
 
4.3%
7 16
 
4.0%
8 15
 
3.8%
5 15
 
3.8%
6 14
 
3.5%
Other values (3) 21
 
5.3%
Hangul
ValueCountFrequency (%)
인 62
 
8.5%
천 61
 
8.4%
역 60
 
8.2%
시 60
 
8.2%
로 60
 
8.2%
광 60
 
8.2%
구 58
 
8.0%
서 24
 
3.3%
길 24
 
3.3%
번 23
 
3.2%
Other values (60) 237
32.5%

우편번호
Real number (ℝ)

Distinct45
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22207.967
Minimum21077
Maximum23037
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-01-28T15:34:48.559167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21077
5-th percentile21105.9
Q121504
median22176.5
Q322799.75
95-th percentile22843
Maximum23037
Range1960
Interquartile range (IQR)1295.75

Descriptive statistics

Standard deviation618.23867
Coefficient of variation (CV)0.027838598
Kurtosis-1.1511371
Mean22207.967
Median Absolute Deviation (MAD)641
Skewness-0.4613248
Sum1332478
Variance382219.05
MonotonicityNot monotonic
2024-01-28T15:34:48.676905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
22130 3
 
5.0%
22843 3
 
5.0%
21502 3
 
5.0%
22789 3
 
5.0%
22126 2
 
3.3%
22838 2
 
3.3%
22772 2
 
3.3%
22835 2
 
3.3%
21504 2
 
3.3%
22117 2
 
3.3%
Other values (35) 36
60.0%
ValueCountFrequency (%)
21077 1
1.7%
21087 1
1.7%
21104 1
1.7%
21106 1
1.7%
21108 1
1.7%
21302 1
1.7%
21314 1
1.7%
21318 1
1.7%
21448 1
1.7%
21449 1
1.7%
ValueCountFrequency (%)
23037 1
 
1.7%
23021 1
 
1.7%
22843 3
5.0%
22841 1
 
1.7%
22838 2
3.3%
22835 2
3.3%
22830 1
 
1.7%
22824 1
 
1.7%
22819 1
 
1.7%
22818 1
 
1.7%

면허대수
Real number (ℝ)

Distinct36
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.75
Minimum30
Maximum155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-01-28T15:34:48.786299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile64.65
Q178
median85
Q3100
95-th percentile130.7
Maximum155
Range125
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.130296
Coefficient of variation (CV)0.24657711
Kurtosis1.6532007
Mean89.75
Median Absolute Deviation (MAD)11
Skewness0.68477674
Sum5385
Variance489.75
MonotonicityNot monotonic
2024-01-28T15:34:48.881482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
84 4
 
6.7%
79 4
 
6.7%
82 4
 
6.7%
100 4
 
6.7%
90 3
 
5.0%
70 3
 
5.0%
77 2
 
3.3%
88 2
 
3.3%
65 2
 
3.3%
94 2
 
3.3%
Other values (26) 30
50.0%
ValueCountFrequency (%)
30 1
 
1.7%
50 1
 
1.7%
58 1
 
1.7%
65 2
3.3%
70 3
5.0%
71 2
3.3%
72 1
 
1.7%
74 1
 
1.7%
77 2
3.3%
78 2
3.3%
ValueCountFrequency (%)
155 1
1.7%
145 1
1.7%
144 1
1.7%
130 1
1.7%
128 1
1.7%
125 1
1.7%
116 1
1.7%
111 1
1.7%
108 2
3.3%
105 1
1.7%

Interactions

2024-01-28T15:34:45.382519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:34:44.972154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:34:45.180307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:34:45.447068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:34:45.037100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:34:45.245686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:34:45.530880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:34:45.116468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:34:45.315464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T15:34:48.965765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호회사명대표자전화번호팩스번호주 소우편번호면허대수
일련번호1.0001.0000.6291.0000.9360.9360.0000.000
회사명1.0001.0001.0001.0001.0001.0001.0001.000
대표자0.6291.0001.0001.0001.0001.0000.9650.302
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
팩스번호0.9361.0001.0001.0001.0000.9971.0001.000
주 소0.9361.0001.0001.0000.9971.0000.9870.000
우편번호0.0001.0000.9651.0001.0000.9871.0000.449
면허대수0.0001.0000.3021.0001.0000.0000.4491.000
2024-01-28T15:34:49.053726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호우편번호면허대수
일련번호1.000-0.0560.098
우편번호-0.0561.000-0.052
면허대수0.098-0.0521.000

Missing values

2024-01-28T15:34:45.624399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T15:34:45.711943image/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

일련번호회사명대표자전화번호팩스번호주 소우편번호면허대수
01검단교통(주)김복태+김민정032-563-1977032-563-1971인천광역시 서구 봉수대로 14932264977
12경영기업(주)차영남+차준환032-862-1515032-863-8819인천광역시 미추홀구 염창로 1242213091
23경인운수(자)유충희032-574-2299032-574-0311인천광역시 서구 옻우물로 2022790125
34경진운수(자)한도섭032-525-3331032-525-3339인천광역시 부평구 부평북로 3672131879
45공성교통(주)진충남+진형민032-578-7900032-578-7902인천광역시 서구 중봉대로198번길 3422843108
56국일운수(자)김종우032-862-0255032-868-1840인천광역시 미추홀구 석정로351번길 92212685
67국제산업(자)황재선+황수원032-435-7887032-433-2727인천광역시 남동구 석정로497번길 832150279
78금산운수(자)김광민032-873-7227032-867-6176인천광역시 미추홀구 염창로 1382213082
89대덕택시(자)장인균032-571-5746032-571-2911인천광역시 서구 중봉대로 2342277282
910(주)대도기업안종태032-571-7339032-571-1251인천광역시 서구 원적로17번길 162281990
일련번호회사명대표자전화번호팩스번호주 소우편번호면허대수
5051재인기업(주)김순옥+최상준032-575-3793032-232-6139인천광역시 서구 가정로 1192283584
5152제원기업(유)김영희032-862-6678032-867-3239인천광역시 미추홀구 석정로301번길 4322117100
5253제이비택시(주)주상이+박의배032-762-9331032-766-9729인천광역시 동구 어촌로 2222507108
5354(주)충 인김민규+김진환032-874-1001032-874-8598인천광역시 미추홀구 석정로 3512212670
5455태양상운수(주)주상준+최월천+주미정032-528-1161032-528-1162인천광역시 부평구 부평북로 1792131486
5556풍진기업(주)김철주+양준모+김성수032-577-4700032-577-4701인천광역시 서구 중봉대로198번길 302284385
5657한미교통(주)박수웅032-571-1032032-584-9007인천광역시 서구 거북로46번길 222279471
5758한성운수(주)유흥주+윤래성032-424-7021032-429-7021인천광역시 미추홀구 주안로 16622134155
5859한일운수(주)한경억+윤세헌032-549-3311032-549-3313인천광역시 계양구 계산로 1342108778
5960화신교통(자)박재철032-581-9100032-581-9102인천광역시 서구 건지로95번길 292277270