Overview

Dataset statistics

Number of variables9
Number of observations32
Missing cells15
Missing cells (%)5.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory79.1 B

Variable types

Numeric3
Categorical2
Text4

Dataset

Description인천광역시 남동구 종합여행업에 대한 데이터로 연번, 업종, 상호, 소재지(지번), 소재지(도로명), 전화번호, 데이터기준일 항목을 공개합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15103646&srcSe=7661IVAWM27C61E190

Alerts

업종 has constant value ""Constant
데이터기준일 has constant value ""Constant
전화번호 has 15 (46.9%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique
소재지(지번) has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2024-01-28 10:57:42.003193
Analysis finished2024-01-28 10:57:43.336297
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-28T19:57:43.388990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q18.75
median16.5
Q324.25
95-th percentile30.45
Maximum32
Range31
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation9.3808315
Coefficient of variation (CV)0.56853524
Kurtosis-1.2
Mean16.5
Median Absolute Deviation (MAD)8
Skewness0
Sum528
Variance88
MonotonicityStrictly increasing
2024-01-28T19:57:43.482164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 1
 
3.1%
18 1
 
3.1%
32 1
 
3.1%
31 1
 
3.1%
30 1
 
3.1%
29 1
 
3.1%
28 1
 
3.1%
27 1
 
3.1%
26 1
 
3.1%
25 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
1 1
3.1%
2 1
3.1%
3 1
3.1%
4 1
3.1%
5 1
3.1%
6 1
3.1%
7 1
3.1%
8 1
3.1%
9 1
3.1%
10 1
3.1%
ValueCountFrequency (%)
32 1
3.1%
31 1
3.1%
30 1
3.1%
29 1
3.1%
28 1
3.1%
27 1
3.1%
26 1
3.1%
25 1
3.1%
24 1
3.1%
23 1
3.1%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
종합여행업
32 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
종합여행업 32
100.0%

Length

2024-01-28T19:57:43.575665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:57:43.643800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종합여행업 32
100.0%

상호
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-28T19:57:43.781438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length7.84375
Min length3

Characters and Unicode

Total characters251
Distinct characters110
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

Unique32 ?
Unique (%)100.0%

Sample

1st row강서관광(주)
2nd row인천태화관광(주)
3rd row다가보자투어(주)
4th row(주)에코밸리
5th row한국 금해 주식회사
ValueCountFrequency (%)
주식회사 5
 
10.4%
투어 2
 
4.2%
주)갤럭시관광 1
 
2.1%
문화놀이터 1
 
2.1%
뜻 1
 
2.1%
라파클럽 1
 
2.1%
브라보여행(주 1
 
2.1%
뉴스타관광(주 1
 
2.1%
이박통상 1
 
2.1%
주)심지항공여행사 1
 
2.1%
Other values (33) 33
68.8%
2024-01-28T19:57:44.050611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 17
 
6.8%
16
 
6.4%
( 14
 
5.6%
) 14
 
5.6%
어 11
 
4.4%
투 10
 
4.0%
사 7
 
2.8%
이 6
 
2.4%
라 5
 
2.0%
에 5
 
2.0%
Other values (100) 146
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 194
77.3%
Space Separator 16
 
6.4%
Open Punctuation 14
 
5.6%
Close Punctuation 14
 
5.6%
Uppercase Letter 9
 
3.6%
Lowercase Letter 4
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 17
 
8.8%
어 11
 
5.7%
투 10
 
5.2%
사 7
 
3.6%
이 6
 
3.1%
라 5
 
2.6%
에 5
 
2.6%
회 5
 
2.6%
식 5
 
2.6%
여 4
 
2.1%
Other values (84) 119
61.3%
Uppercase Letter
ValueCountFrequency (%)
O 1
11.1%
E 1
11.1%
N 1
11.1%
R 1
11.1%
U 1
11.1%
T 1
11.1%
M 1
11.1%
G 1
11.1%
A 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
r 1
25.0%
w 1
25.0%
e 1
25.0%
a 1
25.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 194
77.3%
Common 44
 
17.5%
Latin 13
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 17
 
8.8%
어 11
 
5.7%
투 10
 
5.2%
사 7
 
3.6%
이 6
 
3.1%
라 5
 
2.6%
에 5
 
2.6%
회 5
 
2.6%
식 5
 
2.6%
여 4
 
2.1%
Other values (84) 119
61.3%
Latin
ValueCountFrequency (%)
O 1
 
7.7%
r 1
 
7.7%
E 1
 
7.7%
w 1
 
7.7%
e 1
 
7.7%
N 1
 
7.7%
R 1
 
7.7%
U 1
 
7.7%
T 1
 
7.7%
M 1
 
7.7%
Other values (3) 3
23.1%
Common
ValueCountFrequency (%)
16
36.4%
( 14
31.8%
) 14
31.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 194
77.3%
ASCII 57
 
22.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 17
 
8.8%
어 11
 
5.7%
투 10
 
5.2%
사 7
 
3.6%
이 6
 
3.1%
라 5
 
2.6%
에 5
 
2.6%
회 5
 
2.6%
식 5
 
2.6%
여 4
 
2.1%
Other values (84) 119
61.3%
ASCII
ValueCountFrequency (%)
16
28.1%
( 14
24.6%
) 14
24.6%
O 1
 
1.8%
r 1
 
1.8%
E 1
 
1.8%
w 1
 
1.8%
e 1
 
1.8%
N 1
 
1.8%
R 1
 
1.8%
Other values (6) 6
 
10.5%

소재지(지번)
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-28T19:57:44.261263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length37.5
Mean length34.0625
Min length27

Characters and Unicode

Total characters1090
Distinct characters98
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 간석동 901번지 동우빌딩 301 302호
2nd row인천광역시 남동구 구월동 1235-15번지 선희빌딩 401호
3rd row인천광역시 남동구 구월동 1181-30번지 남일빌딩 라이온스 클럽501호
4th row인천광역시 남동구 만수동 904-21번지 만수동 303호
5th row인천광역시 남동구 만수동 987-12번지 호만수동 나동 3층
ValueCountFrequency (%)
인천광역시 32
 
15.4%
남동구 32
 
15.4%
구월동 16
 
7.7%
만수동 7
 
3.4%
논현동 6
 
2.9%
고잔동 5
 
2.4%
3층 4
 
1.9%
네이쳐프라자 3
 
1.4%
2층 3
 
1.4%
1542-1번지 3
 
1.4%
Other values (87) 97
46.6%
2024-01-28T19:57:44.577925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
182
 
16.7%
동 80
 
7.3%
1 57
 
5.2%
구 50
 
4.6%
2 36
 
3.3%
0 35
 
3.2%
3 35
 
3.2%
인 34
 
3.1%
천 34
 
3.1%
남 34
 
3.1%
Other values (88) 513
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 630
57.8%
Decimal Number 248
 
22.8%
Space Separator 182
 
16.7%
Dash Punctuation 30
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 80
 
12.7%
구 50
 
7.9%
인 34
 
5.4%
천 34
 
5.4%
남 34
 
5.4%
시 33
 
5.2%
역 32
 
5.1%
광 32
 
5.1%
번 32
 
5.1%
지 32
 
5.1%
Other values (76) 237
37.6%
Decimal Number
ValueCountFrequency (%)
1 57
23.0%
2 36
14.5%
0 35
14.1%
3 35
14.1%
4 22
 
8.9%
5 17
 
6.9%
7 17
 
6.9%
6 17
 
6.9%
9 7
 
2.8%
8 5
 
2.0%
Space Separator
ValueCountFrequency (%)
182
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 630
57.8%
Common 460
42.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 80
 
12.7%
구 50
 
7.9%
인 34
 
5.4%
천 34
 
5.4%
남 34
 
5.4%
시 33
 
5.2%
역 32
 
5.1%
광 32
 
5.1%
번 32
 
5.1%
지 32
 
5.1%
Other values (76) 237
37.6%
Common
ValueCountFrequency (%)
182
39.6%
1 57
 
12.4%
2 36
 
7.8%
0 35
 
7.6%
3 35
 
7.6%
- 30
 
6.5%
4 22
 
4.8%
5 17
 
3.7%
7 17
 
3.7%
6 17
 
3.7%
Other values (2) 12
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 630
57.8%
ASCII 460
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
182
39.6%
1 57
 
12.4%
2 36
 
7.8%
0 35
 
7.6%
3 35
 
7.6%
- 30
 
6.5%
4 22
 
4.8%
5 17
 
3.7%
7 17
 
3.7%
6 17
 
3.7%
Other values (2) 12
 
2.6%
Hangul
ValueCountFrequency (%)
동 80
 
12.7%
구 50
 
7.9%
인 34
 
5.4%
천 34
 
5.4%
남 34
 
5.4%
시 33
 
5.2%
역 32
 
5.1%
광 32
 
5.1%
번 32
 
5.1%
지 32
 
5.1%
Other values (76) 237
37.6%

소재지(도로명)
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-28T19:57:44.802432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length41
Mean length37.6875
Min length26

Characters and Unicode

Total characters1206
Distinct characters124
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 구월로 42, 동우빌딩 301,302호 (간석동)
2nd row인천광역시 남동구 인주대로 723, 선희빌딩 401호 (구월동)
3rd row인천광역시 남동구 남동대로 694, 남일빌딩 라이온스 클럽501호 (구월동)
4th row인천광역시 남동구 백범로247번길 43, 303호 (만수동)
5th row인천광역시 남동구 인주대로 846, 나동 3층호 (만수동)
ValueCountFrequency (%)
인천광역시 32
 
14.0%
남동구 32
 
14.0%
구월동 15
 
6.6%
논현동 5
 
2.2%
만수동 5
 
2.2%
고잔동 4
 
1.7%
인주대로 3
 
1.3%
구월남로 3
 
1.3%
네이쳐프라자 3
 
1.3%
11 3
 
1.3%
Other values (109) 124
54.1%
2024-01-28T19:57:45.188165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
198
 
16.4%
동 71
 
5.9%
구 54
 
4.5%
인 39
 
3.2%
남 39
 
3.2%
천 36
 
3.0%
, 35
 
2.9%
1 34
 
2.8%
3 34
 
2.8%
시 33
 
2.7%
Other values (114) 633
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 692
57.4%
Decimal Number 210
 
17.4%
Space Separator 198
 
16.4%
Other Punctuation 35
 
2.9%
Open Punctuation 32
 
2.7%
Close Punctuation 32
 
2.7%
Dash Punctuation 7
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 71
 
10.3%
구 54
 
7.8%
인 39
 
5.6%
남 39
 
5.6%
천 36
 
5.2%
시 33
 
4.8%
역 33
 
4.8%
호 33
 
4.8%
광 32
 
4.6%
로 32
 
4.6%
Other values (99) 290
41.9%
Decimal Number
ValueCountFrequency (%)
1 34
16.2%
3 34
16.2%
0 31
14.8%
2 30
14.3%
4 24
11.4%
5 14
6.7%
6 14
6.7%
8 13
 
6.2%
7 11
 
5.2%
9 5
 
2.4%
Space Separator
ValueCountFrequency (%)
198
100.0%
Other Punctuation
ValueCountFrequency (%)
, 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 692
57.4%
Common 514
42.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 71
 
10.3%
구 54
 
7.8%
인 39
 
5.6%
남 39
 
5.6%
천 36
 
5.2%
시 33
 
4.8%
역 33
 
4.8%
호 33
 
4.8%
광 32
 
4.6%
로 32
 
4.6%
Other values (99) 290
41.9%
Common
ValueCountFrequency (%)
198
38.5%
, 35
 
6.8%
1 34
 
6.6%
3 34
 
6.6%
( 32
 
6.2%
) 32
 
6.2%
0 31
 
6.0%
2 30
 
5.8%
4 24
 
4.7%
5 14
 
2.7%
Other values (5) 50
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 692
57.4%
ASCII 514
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
198
38.5%
, 35
 
6.8%
1 34
 
6.6%
3 34
 
6.6%
( 32
 
6.2%
) 32
 
6.2%
0 31
 
6.0%
2 30
 
5.8%
4 24
 
4.7%
5 14
 
2.7%
Other values (5) 50
 
9.7%
Hangul
ValueCountFrequency (%)
동 71
 
10.3%
구 54
 
7.8%
인 39
 
5.6%
남 39
 
5.6%
천 36
 
5.2%
시 33
 
4.8%
역 33
 
4.8%
호 33
 
4.8%
광 32
 
4.6%
로 32
 
4.6%
Other values (99) 290
41.9%

전화번호
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing15
Missing (%)46.9%
Memory size388.0 B
2024-01-28T19:57:45.345751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length9

Characters and Unicode

Total characters204
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

Unique17 ?
Unique (%)100.0%

Sample

1st row032-434-0003
2nd row032-431-9101
3rd row032-516-2234
4th row070-8969-1458
5th row032-471-8697
ValueCountFrequency (%)
032-431-9101 1
 
5.9%
070-5143-5802 1
 
5.9%
032-432-0017 1
 
5.9%
032-463-9561 1
 
5.9%
032-442-7777 1
 
5.9%
070-8876-7479 1
 
5.9%
032-468-5432 1
 
5.9%
032-258-8008 1
 
5.9%
032-434-0003 1
 
5.9%
032-516-2234 1
 
5.9%
Other values (7) 7
41.2%
2024-01-28T19:57:45.607755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 33
16.2%
0 30
14.7%
3 24
11.8%
2 22
10.8%
4 18
8.8%
7 17
8.3%
1 16
7.8%
8 15
7.4%
6 12
 
5.9%
5 10
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 171
83.8%
Dash Punctuation 33
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30
17.5%
3 24
14.0%
2 22
12.9%
4 18
10.5%
7 17
9.9%
1 16
9.4%
8 15
8.8%
6 12
 
7.0%
5 10
 
5.8%
9 7
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 204
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 33
16.2%
0 30
14.7%
3 24
11.8%
2 22
10.8%
4 18
8.8%
7 17
8.3%
1 16
7.8%
8 15
7.4%
6 12
 
5.9%
5 10
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 204
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 33
16.2%
0 30
14.7%
3 24
11.8%
2 22
10.8%
4 18
8.8%
7 17
8.3%
1 16
7.8%
8 15
7.4%
6 12
 
5.9%
5 10
 
4.9%

위도
Real number (ℝ)

Distinct29
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.43576
Minimum37.385629
Maximum37.46687
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-28T19:57:45.709611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.385629
5-th percentile37.399749
Q137.406511
median37.445667
Q337.451292
95-th percentile37.459371
Maximum37.46687
Range0.08124171
Interquartile range (IQR)0.044780848

Descriptive statistics

Standard deviation0.023441139
Coefficient of variation (CV)0.00062616972
Kurtosis-0.82599712
Mean37.43576
Median Absolute Deviation (MAD)0.007261895
Skewness-0.86142143
Sum1197.9443
Variance0.00054948701
MonotonicityNot monotonic
2024-01-28T19:57:45.805219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
37.44087947 3
 
9.4%
37.4530871 2
 
6.2%
37.45722551 1
 
3.1%
37.40224243 1
 
3.1%
37.40151444 1
 
3.1%
37.40090402 1
 
3.1%
37.45277041 1
 
3.1%
37.4499291 1
 
3.1%
37.46687026 1
 
3.1%
37.45079909 1
 
3.1%
Other values (19) 19
59.4%
ValueCountFrequency (%)
37.38562855 1
3.1%
37.39940489 1
3.1%
37.40003012 1
3.1%
37.40090402 1
3.1%
37.40151444 1
3.1%
37.40159095 1
3.1%
37.40224243 1
3.1%
37.40519411 1
3.1%
37.40695006 1
3.1%
37.43918718 1
3.1%
ValueCountFrequency (%)
37.46687026 1
3.1%
37.46041023 1
3.1%
37.458521 1
3.1%
37.45722551 1
3.1%
37.45529798 1
3.1%
37.4530871 2
6.2%
37.45277041 1
3.1%
37.45079909 1
3.1%
37.4499291 1
3.1%
37.44974658 1
3.1%

경도
Real number (ℝ)

Distinct29
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.71256
Minimum126.6934
Maximum126.73585
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-28T19:57:45.901588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.6934
5-th percentile126.69423
Q1126.70276
median126.70914
Q3126.72155
95-th percentile126.73451
Maximum126.73585
Range0.0424522
Interquartile range (IQR)0.018790525

Descriptive statistics

Standard deviation0.012797647
Coefficient of variation (CV)0.00010099747
Kurtosis-0.80777588
Mean126.71256
Median Absolute Deviation (MAD)0.0094516
Skewness0.34075666
Sum4054.8018
Variance0.00016377978
MonotonicityNot monotonic
2024-01-28T19:57:45.985072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
126.7086535 3
 
9.4%
126.7027589 2
 
6.2%
126.6948094 1
 
3.1%
126.7086159 1
 
3.1%
126.7220688 1
 
3.1%
126.7214467 1
 
3.1%
126.7059289 1
 
3.1%
126.7139116 1
 
3.1%
126.6935115 1
 
3.1%
126.7143714 1
 
3.1%
Other values (19) 19
59.4%
ValueCountFrequency (%)
126.6933996 1
3.1%
126.6935115 1
3.1%
126.6948094 1
3.1%
126.6959488 1
3.1%
126.6973101 1
3.1%
126.698049 1
3.1%
126.7021497 1
3.1%
126.7027589 2
6.2%
126.7059289 1
3.1%
126.7072072 1
3.1%
ValueCountFrequency (%)
126.7358518 1
3.1%
126.7348748 1
3.1%
126.7342203 1
3.1%
126.7336097 1
3.1%
126.7312327 1
3.1%
126.7263225 1
3.1%
126.7220688 1
3.1%
126.7218576 1
3.1%
126.7214467 1
3.1%
126.7196067 1
3.1%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-05-01
32 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-01
2nd row2023-05-01
3rd row2023-05-01
4th row2023-05-01
5th row2023-05-01

Common Values

ValueCountFrequency (%)
2023-05-01 32
100.0%

Length

2024-01-28T19:57:46.082480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:57:46.156812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-01 32
100.0%

Interactions

2024-01-28T19:57:42.987413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:57:42.364732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:57:42.785114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:57:43.046985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:57:42.655229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:57:42.853036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:57:43.113457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:57:42.722711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:57:42.926762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T19:57:46.202369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호소재지(지번)소재지(도로명)전화번호위도경도
연번1.0001.0001.0001.0001.0000.0000.000
상호1.0001.0001.0001.0001.0001.0001.000
소재지(지번)1.0001.0001.0001.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
위도0.0001.0001.0001.0001.0001.0000.728
경도0.0001.0001.0001.0001.0000.7281.000
2024-01-28T19:57:46.283835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.000-0.1870.140
위도-0.1871.000-0.043
경도0.140-0.0431.000

Missing values

2024-01-28T19:57:43.191903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T19:57:43.293309image/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

연번업종상호소재지(지번)소재지(도로명)전화번호위도경도데이터기준일
01종합여행업강서관광(주)인천광역시 남동구 간석동 901번지 동우빌딩 301 302호인천광역시 남동구 구월로 42, 동우빌딩 301,302호 (간석동)032-434-000337.457226126.6948092023-05-01
12종합여행업인천태화관광(주)인천광역시 남동구 구월동 1235-15번지 선희빌딩 401호인천광역시 남동구 인주대로 723, 선희빌딩 401호 (구월동)032-431-910137.449437126.7175822023-05-01
23종합여행업다가보자투어(주)인천광역시 남동구 구월동 1181-30번지 남일빌딩 라이온스 클럽501호인천광역시 남동구 남동대로 694, 남일빌딩 라이온스 클럽501호 (구월동)032-516-223437.444161126.7072072023-05-01
34종합여행업(주)에코밸리인천광역시 남동구 만수동 904-21번지 만수동 303호인천광역시 남동구 백범로247번길 43, 303호 (만수동)070-8969-145837.458521126.7218582023-05-01
45종합여행업한국 금해 주식회사인천광역시 남동구 만수동 987-12번지 호만수동 나동 3층인천광역시 남동구 인주대로 846, 나동 3층호 (만수동)032-471-869737.448188126.7312332023-05-01
56종합여행업주식회사 미래교육여행투어인천광역시 남동구 구월동 1131-13번지 백세빌딩 6층인천광역시 남동구 구월남로 120, 백세빌딩 6층 126호 (구월동)1566-345537.453087126.7027592023-05-01
67종합여행업그라고 에어 앤 투어인천광역시 남동구 고잔동 732-10번지 고잔동 3층 303호인천광역시 남동구 아암대로 1171, 3층 303호 (고잔동)032-818-264637.385629126.6980492023-05-01
78종합여행업지앤엠투어인천광역시 남동구 구월동 1550-4번지 구월테크노밸리디동 307호인천광역시 남동구 선수촌공원로 1, 구월테크노밸리 디동 307호 (구월동)032-863-111737.439187126.7096322023-05-01
89종합여행업(주)지트립인천광역시 남동구 구월동 1407-10번지 호구월동 2층인천광역시 남동구 문화서로4번길 44, 2층호 (구월동)032-432-787137.444675126.697312023-05-01
910종합여행업(주)현대에이엠씨인천광역시 남동구 만수동 1075-1번지 호만수동 3층인천광역시 남동구 소래로 646, 3층호 (만수동)<NA>37.447294126.733612023-05-01
연번업종상호소재지(지번)소재지(도로명)전화번호위도경도데이터기준일
2223종합여행업이박통상 주식회사인천광역시 남동구 수산동 45-9번지 수산동 2층인천광역시 남동구 경신로60번길 9, 2층 (수산동)032-463-956137.443161126.7263222023-05-01
2324종합여행업(주)심지항공여행사인천광역시 남동구 구월동 1264번지 퍼스트하임프라자 315호인천광역시 남동구 호구포로 818, 퍼스트하임프라자 315호 (구월동)032-432-001737.455298126.7196072023-05-01
2425종합여행업주식회사 노닐다인천광역시 남동구 구월동 1222번지 구월동 6호인천광역시 남동구 용천로 14, 6호 (구월동)<NA>37.450799126.7143712023-05-01
2526종합여행업(주)갤럭시관광인천광역시 남동구 간석동 893-1번지 우성 305호인천광역시 남동구 방축로 501, 305호 (간석동, 우성아파트)032-874-900137.46687126.6935112023-05-01
2627종합여행업웨이브투어(주)인천광역시 남동구 구월동 1542-1번지 네이쳐프라자 701동 19호인천광역시 남동구 선수촌공원로23번길 11, 네이쳐프라자 701-19호 (구월동)<NA>37.440879126.7086532023-05-01
2728종합여행업디엠씨트립스인천광역시 남동구 구월동 1219-5번지 뉴인천빌딩 304호인천광역시 남동구 용천로 3, 뉴인천빌딩 304호 (구월동)<NA>37.449929126.7139122023-05-01
2829종합여행업황오빠인천광역시 남동구 구월동 1142-20번지 타워플러스 1301-1호인천광역시 남동구 구월남로 148, 타워플러스 1301-1호 (구월동)<NA>37.45277126.7059292023-05-01
2930종합여행업에이지엠투어(AGM TOUR)인천광역시 남동구 구월동 1542-1번지 네이쳐프라자 505호 내부 제4호인천광역시 남동구 선수촌공원로23번길 11, 네이쳐프라자 505호 내부 제4호 (구월동)<NA>37.440879126.7086532023-05-01
3031종합여행업뉴 에라(New Era)인천광역시 남동구 논현동 631-6번지 논현메디컬센터 4층 420호인천광역시 남동구 청능대로 559, 논현메디컬센터 4층 420호 (논현동)<NA>37.400904126.7214472023-05-01
3132종합여행업인천여행사인천광역시 남동구 논현동 632-1번지 칼리오페 7층 704-1호인천광역시 남동구 논고개로123번길 35, 칼리오페 7층 704-1호 (논현동)<NA>37.401514126.7220692023-05-01