Overview

Dataset statistics

Number of variables9
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory79.2 B

Variable types

Numeric4
Categorical1
Text4

Dataset

Description인천광역시 전세 버스 업체 현황에 대한 데이터로 (업체명, 등록대수, 주소, 전화번호 등)등의 항목 정보에 대해 알 수 있습니다.
Author인천광역시
URLhttps://www.data.go.kr/data/15045235/fileData.do

Alerts

중 is highly overall correlated with 등록High correlation
등록 is highly overall correlated with 중High correlation
연번 has unique valuesUnique
업체명 has unique valuesUnique
중 has 5 (12.2%) zerosZeros

Reproduction

Analysis started2023-12-12 21:24:17.092247
Analysis finished2023-12-12 21:24:19.481248
Duration2.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21
Minimum1
Maximum41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T06:24:19.545994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median21
Q331
95-th percentile39
Maximum41
Range40
Interquartile range (IQR)20

Descriptive statistics

Standard deviation11.979149
Coefficient of variation (CV)0.57043565
Kurtosis-1.2
Mean21
Median Absolute Deviation (MAD)10
Skewness0
Sum861
Variance143.5
MonotonicityStrictly increasing
2023-12-13T06:24:19.694848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1 1
 
2.4%
32 1
 
2.4%
24 1
 
2.4%
25 1
 
2.4%
26 1
 
2.4%
27 1
 
2.4%
28 1
 
2.4%
29 1
 
2.4%
30 1
 
2.4%
31 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
1 1
2.4%
2 1
2.4%
3 1
2.4%
4 1
2.4%
5 1
2.4%
6 1
2.4%
7 1
2.4%
8 1
2.4%
9 1
2.4%
10 1
2.4%
ValueCountFrequency (%)
41 1
2.4%
40 1
2.4%
39 1
2.4%
38 1
2.4%
37 1
2.4%
36 1
2.4%
35 1
2.4%
34 1
2.4%
33 1
2.4%
32 1
2.4%

군구
Categorical

Distinct9
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
서구
9 
남동구
7 
부평구
7 
연수구
5 
중구
4 
Other values (4)
9 

Length

Max length4
Median length3
Mean length2.7317073
Min length2

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row미추홀구
2nd row남동구
3rd row남동구
4th row남동구
5th row연수구

Common Values

ValueCountFrequency (%)
서구 9
22.0%
남동구 7
17.1%
부평구 7
17.1%
연수구 5
12.2%
중구 4
9.8%
미추홀구 3
 
7.3%
계양구 3
 
7.3%
강화군 2
 
4.9%
동구 1
 
2.4%

Length

2023-12-13T06:24:19.845609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:24:19.968927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구 9
22.0%
남동구 7
17.1%
부평구 7
17.1%
연수구 5
12.2%
중구 4
9.8%
미추홀구 3
 
7.3%
계양구 3
 
7.3%
강화군 2
 
4.9%
동구 1
 
2.4%

업체명
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T06:24:20.218477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8.3170732
Min length6

Characters and Unicode

Total characters341
Distinct characters82
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

Unique41 ?
Unique (%)100.0%

Sample

1st row(주)가나다관광
2nd row강서관광(주)
3rd row(주)갤럭시투어
4th row(주)거산관광
5th row㈜골든클래스관광
ValueCountFrequency (%)
주)가나다관광 1
 
2.3%
합)인일관광여행사 1
 
2.3%
승 1
 
2.3%
신백승여행사㈜ 1
 
2.3%
신인천관광(주 1
 
2.3%
주)신정관광 1
 
2.3%
주)아름관광여행사 1
 
2.3%
열린고속관광㈜ 1
 
2.3%
주)우주투어 1
 
2.3%
㈜이삼화관광 1
 
2.3%
Other values (33) 33
76.7%
2023-12-13T06:24:20.613955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 30
 
8.8%
) 30
 
8.8%
주 25
 
7.3%
관 24
 
7.0%
광 24
 
7.0%
㈜ 15
 
4.4%
여 13
 
3.8%
행 13
 
3.8%
사 13
 
3.8%
11
 
3.2%
Other values (72) 143
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 255
74.8%
Open Punctuation 30
 
8.8%
Close Punctuation 30
 
8.8%
Other Symbol 15
 
4.4%
Space Separator 11
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 25
 
9.8%
관 24
 
9.4%
광 24
 
9.4%
여 13
 
5.1%
행 13
 
5.1%
사 13
 
5.1%
어 8
 
3.1%
투 8
 
3.1%
인 6
 
2.4%
천 5
 
2.0%
Other values (68) 116
45.5%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 15
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 270
79.2%
Common 71
 
20.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 25
 
9.3%
관 24
 
8.9%
광 24
 
8.9%
㈜ 15
 
5.6%
여 13
 
4.8%
행 13
 
4.8%
사 13
 
4.8%
어 8
 
3.0%
투 8
 
3.0%
인 6
 
2.2%
Other values (69) 121
44.8%
Common
ValueCountFrequency (%)
( 30
42.3%
) 30
42.3%
11
 
15.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 255
74.8%
ASCII 71
 
20.8%
None 15
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 30
42.3%
) 30
42.3%
11
 
15.5%
Hangul
ValueCountFrequency (%)
주 25
 
9.8%
관 24
 
9.4%
광 24
 
9.4%
여 13
 
5.1%
행 13
 
5.1%
사 13
 
5.1%
어 8
 
3.1%
투 8
 
3.1%
인 6
 
2.4%
천 5
 
2.0%
Other values (68) 116
45.5%
None
ValueCountFrequency (%)
㈜ 15
100.0%

대표자
Text

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T06:24:20.837289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.097561
Min length3

Characters and Unicode

Total characters127
Distinct characters72
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

Unique39 ?
Unique (%)95.1%

Sample

1st row김정옥
2nd row김 철
3rd row최효순
4th row이경희
5th row오경희
ValueCountFrequency (%)
유경자 2
 
4.8%
한창수 1
 
2.4%
민대원외1 1
 
2.4%
하경용 1
 
2.4%
여주삼 1
 
2.4%
정태화 1
 
2.4%
고재수 1
 
2.4%
박팔용 1
 
2.4%
장병일 1
 
2.4%
윤정호 1
 
2.4%
Other values (31) 31
73.8%
2023-12-13T06:24:21.176085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 7
 
5.5%
정 6
 
4.7%
경 6
 
4.7%
수 5
 
3.9%
용 5
 
3.9%
김 4
 
3.1%
박 4
 
3.1%
유 3
 
2.4%
현 3
 
2.4%
창 3
 
2.4%
Other values (62) 81
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123
96.9%
Space Separator 3
 
2.4%
Decimal Number 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 7
 
5.7%
정 6
 
4.9%
경 6
 
4.9%
수 5
 
4.1%
용 5
 
4.1%
김 4
 
3.3%
박 4
 
3.3%
유 3
 
2.4%
현 3
 
2.4%
창 3
 
2.4%
Other values (60) 77
62.6%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123
96.9%
Common 4
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 7
 
5.7%
정 6
 
4.9%
경 6
 
4.9%
수 5
 
4.1%
용 5
 
4.1%
김 4
 
3.3%
박 4
 
3.3%
유 3
 
2.4%
현 3
 
2.4%
창 3
 
2.4%
Other values (60) 77
62.6%
Common
ValueCountFrequency (%)
3
75.0%
1 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123
96.9%
ASCII 4
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 7
 
5.7%
정 6
 
4.9%
경 6
 
4.9%
수 5
 
4.1%
용 5
 
4.1%
김 4
 
3.3%
박 4
 
3.3%
유 3
 
2.4%
현 3
 
2.4%
창 3
 
2.4%
Other values (60) 77
62.6%
ASCII
ValueCountFrequency (%)
3
75.0%
1 1
 
25.0%

대
Real number (ℝ)

Distinct30
Distinct (%)73.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.853659
Minimum1
Maximum63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T06:24:21.283882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q112
median21
Q332
95-th percentile44
Maximum63
Range62
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.753916
Coefficient of variation (CV)0.64558225
Kurtosis0.22251915
Mean22.853659
Median Absolute Deviation (MAD)10
Skewness0.60144196
Sum937
Variance217.67805
MonotonicityNot monotonic
2023-12-13T06:24:21.386787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
9 3
 
7.3%
28 3
 
7.3%
1 3
 
7.3%
15 3
 
7.3%
17 2
 
4.9%
4 2
 
4.9%
20 2
 
4.9%
21 1
 
2.4%
24 1
 
2.4%
56 1
 
2.4%
Other values (20) 20
48.8%
ValueCountFrequency (%)
1 3
7.3%
4 2
4.9%
5 1
 
2.4%
9 3
7.3%
11 1
 
2.4%
12 1
 
2.4%
13 1
 
2.4%
15 3
7.3%
17 2
4.9%
18 1
 
2.4%
ValueCountFrequency (%)
63 1
2.4%
56 1
2.4%
44 1
2.4%
43 1
2.4%
40 1
2.4%
39 1
2.4%
37 1
2.4%
36 1
2.4%
35 1
2.4%
33 1
2.4%

중
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.439024
Minimum0
Maximum115
Zeros5
Zeros (%)12.2%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T06:24:21.500996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median10
Q334
95-th percentile84
Maximum115
Range115
Interquartile range (IQR)32

Descriptive statistics

Standard deviation30.738452
Coefficient of variation (CV)1.311422
Kurtosis2.2077391
Mean23.439024
Median Absolute Deviation (MAD)9
Skewness1.6688246
Sum961
Variance944.85244
MonotonicityNot monotonic
2023-12-13T06:24:21.615672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 5
 
12.2%
1 5
 
12.2%
4 2
 
4.9%
3 2
 
4.9%
2 2
 
4.9%
5 2
 
4.9%
50 1
 
2.4%
17 1
 
2.4%
76 1
 
2.4%
54 1
 
2.4%
Other values (19) 19
46.3%
ValueCountFrequency (%)
0 5
12.2%
1 5
12.2%
2 2
 
4.9%
3 2
 
4.9%
4 2
 
4.9%
5 2
 
4.9%
6 1
 
2.4%
9 1
 
2.4%
10 1
 
2.4%
11 1
 
2.4%
ValueCountFrequency (%)
115 1
2.4%
113 1
2.4%
84 1
2.4%
76 1
2.4%
71 1
2.4%
54 1
2.4%
53 1
2.4%
50 1
2.4%
42 1
2.4%
36 1
2.4%

등록
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.292683
Minimum6
Maximum139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-13T06:24:21.745672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile15
Q126
median39
Q365
95-th percentile112
Maximum139
Range133
Interquartile range (IQR)39

Descriptive statistics

Standard deviation28.819476
Coefficient of variation (CV)0.62254927
Kurtosis2.0598962
Mean46.292683
Median Absolute Deviation (MAD)15
Skewness1.3242564
Sum1898
Variance830.5622
MonotonicityNot monotonic
2023-12-13T06:24:21.873414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
27 2
 
4.9%
20 2
 
4.9%
24 2
 
4.9%
68 2
 
4.9%
31 2
 
4.9%
6 2
 
4.9%
26 1
 
2.4%
39 1
 
2.4%
77 1
 
2.4%
65 1
 
2.4%
Other values (25) 25
61.0%
ValueCountFrequency (%)
6 2
4.9%
15 1
2.4%
20 2
4.9%
21 1
2.4%
23 1
2.4%
24 2
4.9%
25 1
2.4%
26 1
2.4%
27 2
4.9%
28 1
2.4%
ValueCountFrequency (%)
139 1
2.4%
114 1
2.4%
112 1
2.4%
77 1
2.4%
75 1
2.4%
72 1
2.4%
68 2
4.9%
67 1
2.4%
66 1
2.4%
65 1
2.4%

주소
Text

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T06:24:22.141222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length23.292683
Min length14

Characters and Unicode

Total characters955
Distinct characters132
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)95.1%

Sample

1st row남구 경원대로 752번길 19 (주안동,112호)
2nd row남동구 구월로 42 (동우빌딩, 3층)
3rd row남동구 방축로 501 (간석동, 우성상가305호)
4th row남동구 백범로 141 (만수동, 보강빌딩 3층)
5th row연수구 청명로 34 (청학동, 205호)
ValueCountFrequency (%)
서구 9
 
4.8%
남동구 7
 
3.7%
부평구 7
 
3.7%
3층 6
 
3.2%
연수구 5
 
2.7%
2층 4
 
2.1%
경명대로 4
 
2.1%
중구 4
 
2.1%
계양구 3
 
1.6%
인주대로 3
 
1.6%
Other values (116) 135
72.2%
2023-12-13T06:24:22.595100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
151
 
15.8%
동 43
 
4.5%
구 40
 
4.2%
로 40
 
4.2%
1 35
 
3.7%
2 35
 
3.7%
3 32
 
3.4%
) 32
 
3.4%
( 32
 
3.4%
, 28
 
2.9%
Other values (122) 487
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 501
52.5%
Decimal Number 207
21.7%
Space Separator 151
 
15.8%
Close Punctuation 32
 
3.4%
Open Punctuation 32
 
3.4%
Other Punctuation 28
 
2.9%
Uppercase Letter 3
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 43
 
8.6%
구 40
 
8.0%
로 40
 
8.0%
호 18
 
3.6%
층 17
 
3.4%
길 16
 
3.2%
번 15
 
3.0%
남 14
 
2.8%
대 13
 
2.6%
서 11
 
2.2%
Other values (104) 274
54.7%
Decimal Number
ValueCountFrequency (%)
1 35
16.9%
2 35
16.9%
3 32
15.5%
0 25
12.1%
4 23
11.1%
8 18
8.7%
7 12
 
5.8%
5 10
 
4.8%
9 9
 
4.3%
6 8
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
D 1
33.3%
M 1
33.3%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
151
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 501
52.5%
Common 451
47.2%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 43
 
8.6%
구 40
 
8.0%
로 40
 
8.0%
호 18
 
3.6%
층 17
 
3.4%
길 16
 
3.2%
번 15
 
3.0%
남 14
 
2.8%
대 13
 
2.6%
서 11
 
2.2%
Other values (104) 274
54.7%
Common
ValueCountFrequency (%)
151
33.5%
1 35
 
7.8%
2 35
 
7.8%
3 32
 
7.1%
) 32
 
7.1%
( 32
 
7.1%
, 28
 
6.2%
0 25
 
5.5%
4 23
 
5.1%
8 18
 
4.0%
Other values (5) 40
 
8.9%
Latin
ValueCountFrequency (%)
D 1
33.3%
M 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 501
52.5%
ASCII 454
47.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
151
33.3%
1 35
 
7.7%
2 35
 
7.7%
3 32
 
7.0%
) 32
 
7.0%
( 32
 
7.0%
, 28
 
6.2%
0 25
 
5.5%
4 23
 
5.1%
8 18
 
4.0%
Other values (8) 43
 
9.5%
Hangul
ValueCountFrequency (%)
동 43
 
8.6%
구 40
 
8.0%
로 40
 
8.0%
호 18
 
3.6%
층 17
 
3.4%
길 16
 
3.2%
번 15
 
3.0%
남 14
 
2.8%
대 13
 
2.6%
서 11
 
2.2%
Other values (104) 274
54.7%

전화번호
Text

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-13T06:24:22.826845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.97561
Min length11

Characters and Unicode

Total characters491
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

Unique39 ?
Unique (%)95.1%

Sample

1st row032-433-2526
2nd row032-434-0003
3rd row032-874-9001
4th row032-435-1188
5th row032-812-8855
ValueCountFrequency (%)
032-442-7777 2
 
4.9%
032-433-2526 1
 
2.4%
032-816-2001 1
 
2.4%
032-934-8884 1
 
2.4%
032-874-7000 1
 
2.4%
032-862-7575 1
 
2.4%
032-528-7800 1
 
2.4%
032-584-8855 1
 
2.4%
032-821-1802 1
 
2.4%
032-881-9200 1
 
2.4%
Other values (30) 30
73.2%
2023-12-13T06:24:23.446398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 83
16.9%
- 82
16.7%
2 66
13.4%
3 56
11.4%
8 43
8.8%
7 36
7.3%
5 32
 
6.5%
6 29
 
5.9%
1 28
 
5.7%
4 24
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 409
83.3%
Dash Punctuation 82
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 83
20.3%
2 66
16.1%
3 56
13.7%
8 43
10.5%
7 36
8.8%
5 32
 
7.8%
6 29
 
7.1%
1 28
 
6.8%
4 24
 
5.9%
9 12
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 491
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 83
16.9%
- 82
16.7%
2 66
13.4%
3 56
11.4%
8 43
8.8%
7 36
7.3%
5 32
 
6.5%
6 29
 
5.9%
1 28
 
5.7%
4 24
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 491
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 83
16.9%
- 82
16.7%
2 66
13.4%
3 56
11.4%
8 43
8.8%
7 36
7.3%
5 32
 
6.5%
6 29
 
5.9%
1 28
 
5.7%
4 24
 
4.9%

Interactions

2023-12-13T06:24:18.867586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:17.612704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:18.029235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:18.457047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:18.957285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:17.716841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:18.127985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:18.572218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:19.042942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:17.829472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:18.235063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:18.662811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:19.158123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:17.934692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:18.345146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:24:18.765144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:24:23.570185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번군구업체명대표자대중등록주소전화번호
연번1.0000.2001.0000.9450.3810.0000.5840.9450.945
군구0.2001.0001.0001.0000.2790.0000.2121.0001.000
업체명1.0001.0001.0001.0001.0001.0001.0001.0001.000
대표자0.9451.0001.0001.0000.9460.9850.9770.9950.995
대0.3810.2791.0000.9461.0000.0000.5220.9540.954
중0.0000.0001.0000.9850.0001.0000.8200.0000.000
등록0.5840.2121.0000.9770.5220.8201.0001.0001.000
주소0.9451.0001.0000.9950.9540.0001.0001.0001.000
전화번호0.9451.0001.0000.9950.9540.0001.0001.0001.000
2023-12-13T06:24:23.700652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번대중등록군구
연번1.000-0.3100.131-0.0460.077
대-0.3101.000-0.4230.2300.119
중0.131-0.4231.0000.6680.000
등록-0.0460.2300.6681.0000.000
군구0.0770.1190.0000.0001.000

Missing values

2023-12-13T06:24:19.292912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:24:19.436171image/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

연번군구업체명대표자대중등록주소전화번호
01미추홀구(주)가나다관광김정옥23427남구 경원대로 752번길 19 (주안동,112호)032-433-2526
12남동구강서관광(주)김 철282149남동구 구월로 42 (동우빌딩, 3층)032-434-0003
23남동구(주)갤럭시투어최효순28028남동구 방축로 501 (간석동, 우성상가305호)032-874-9001
34남동구(주)거산관광이경희25025남동구 백범로 141 (만수동, 보강빌딩 3층)032-435-1188
45연수구㈜골든클래스관광오경희334275연수구 청명로 34 (청학동, 205호)032-812-8855
56중구(합)국제관광이찬섭37441중구 제물량로257(항동1가)032-887-8861
67동구(주)그랜드관광백창현43043동구 화수로 18 (송현동, 동부상가 304호)032-761-7100
78서구(주)금강고속관광유경자36036서구 경명대로 463 2층032-761-3000
89서구㈜금강고속여행사유경자41923서구 경명대로 463 4층032-761-3003
910부평구㈜길벗여행사김용기30131부평구 평천로 398 (삼산동,SM메디칼프라자501호)032-661-1144
연번군구업체명대표자대중등록주소전화번호
3132부평구(주)인천다나관광하경용17172부평구 마장로38번길 14 (십정동, 3층)032-502-1581
3233서구㈜인천두레관광서준상18220서구 가좌로 83번길 22032-554-0392
3334계양구(주)청우관광여행사이용현115465계양구 경명대로 1016 (계산동,형제빌딩302호)032-777-6666
3435미추홀구㈜칠성관광여행사이창훈17677남구 인주대로 71 (숭의동, 2층)032-461-4800
3536계양구(주)화이트투어민경철39039계양구 계양새로 85 302호(용종동, 보람프라자)032-555-2229
3637서구양지고속관광(주)(영)허성탁91726서구 서곶로 336 (연희동, 3층)032-566-6833
3738부평구㈜월드여행사(영)최정화175067부평구 장제로 170 (부평동)032-668-1400
3839중구(주)제로쿨투어(영)정근옥516중구 운중로 14번길 13 (운남동, 202호)031-388-2626
3940강화군(주)하나강산여행사(영)박춘배12315강화군 강화읍 대산길51번길 1702-732-8500
4041서구(주)글로벌하나여행사강영서426서구 북항로 32번길28 대건프라자402호032-677-8788