Overview

Dataset statistics

Number of variables9
Number of observations25
Missing cells6
Missing cells (%)2.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory80.3 B

Variable types

Numeric3
Categorical2
Text4

Dataset

Description인천광역시 남동구 국내여행업에 대한 데이터로 연번, 업종, 상호, 소재지(지번), 소재지(도로명), 전화번호, 데이터기준일 항목을 공개합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15103647&srcSe=7661IVAWM27C61E190

Alerts

업종 has constant value ""Constant
데이터기준일 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
전화번호 has 6 (24.0%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique
소재지(지번) has unique valuesUnique
소재지(도로명) has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-01-28 11:05:33.974474
Analysis finished2024-01-28 11:05:35.026042
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-28T20:05:35.072307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median13
Q319
95-th percentile23.8
Maximum25
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.56613852
Kurtosis-1.2
Mean13
Median Absolute Deviation (MAD)6
Skewness0
Sum325
Variance54.166667
MonotonicityStrictly increasing
2024-01-28T20:05:35.163232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 1
 
4.0%
2 1
 
4.0%
25 1
 
4.0%
24 1
 
4.0%
23 1
 
4.0%
22 1
 
4.0%
21 1
 
4.0%
20 1
 
4.0%
19 1
 
4.0%
18 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1 1
4.0%
2 1
4.0%
3 1
4.0%
4 1
4.0%
5 1
4.0%
6 1
4.0%
7 1
4.0%
8 1
4.0%
9 1
4.0%
10 1
4.0%
ValueCountFrequency (%)
25 1
4.0%
24 1
4.0%
23 1
4.0%
22 1
4.0%
21 1
4.0%
20 1
4.0%
19 1
4.0%
18 1
4.0%
17 1
4.0%
16 1
4.0%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
국내여행업
25 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내여행업 25
100.0%

Length

2024-01-28T20:05:35.250524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:05:35.323062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내여행업 25
100.0%

상호
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-01-28T20:05:35.453034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length7.8
Min length3

Characters and Unicode

Total characters195
Distinct characters87
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

Unique25 ?
Unique (%)100.0%

Sample

1st row주식회사 그랜드항공여행사
2nd row(주)준여행사
3rd row주식회사 하늘여행
4th row(주)위드티앤씨
5th row투어맥스
ValueCountFrequency (%)
주식회사 5
 
13.9%
그랜드항공여행사 1
 
2.8%
주)여행마루 1
 
2.8%
주)플러스프레스 1
 
2.8%
아주관광여행사 1
 
2.8%
뉴스타고속관광(주 1
 
2.8%
역사교육 1
 
2.8%
하늘땅 1
 
2.8%
더쎈골프 1
 
2.8%
찐투어 1
 
2.8%
Other values (22) 22
61.1%
2024-01-28T20:05:35.701350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 14
 
7.2%
11
 
5.6%
사 10
 
5.1%
스 8
 
4.1%
어 8
 
4.1%
( 8
 
4.1%
) 8
 
4.1%
회 6
 
3.1%
투 6
 
3.1%
여 6
 
3.1%
Other values (77) 110
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 168
86.2%
Space Separator 11
 
5.6%
Open Punctuation 8
 
4.1%
Close Punctuation 8
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 14
 
8.3%
사 10
 
6.0%
스 8
 
4.8%
어 8
 
4.8%
회 6
 
3.6%
투 6
 
3.6%
여 6
 
3.6%
행 6
 
3.6%
식 5
 
3.0%
이 4
 
2.4%
Other values (74) 95
56.5%
Space Separator
ValueCountFrequency (%)
11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 168
86.2%
Common 27
 
13.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 14
 
8.3%
사 10
 
6.0%
스 8
 
4.8%
어 8
 
4.8%
회 6
 
3.6%
투 6
 
3.6%
여 6
 
3.6%
행 6
 
3.6%
식 5
 
3.0%
이 4
 
2.4%
Other values (74) 95
56.5%
Common
ValueCountFrequency (%)
11
40.7%
( 8
29.6%
) 8
29.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 168
86.2%
ASCII 27
 
13.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 14
 
8.3%
사 10
 
6.0%
스 8
 
4.8%
어 8
 
4.8%
회 6
 
3.6%
투 6
 
3.6%
여 6
 
3.6%
행 6
 
3.6%
식 5
 
3.0%
이 4
 
2.4%
Other values (74) 95
56.5%
ASCII
ValueCountFrequency (%)
11
40.7%
( 8
29.6%
) 8
29.6%

소재지(지번)
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-01-28T20:05:35.907955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length36
Mean length30.4
Min length19

Characters and Unicode

Total characters760
Distinct characters87
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 간석동 482-3번지
2nd row인천광역시 남동구 만수동 861-8번지
3rd row인천광역시 남동구 간석동 221-2
4th row인천광역시 남동구 논현동 631-8번지 201호
5th row인천광역시 남동구 논현동 650-1번지 지하1층
ValueCountFrequency (%)
인천광역시 25
 
17.2%
남동구 25
 
17.2%
구월동 9
 
6.2%
간석동 6
 
4.1%
논현동 4
 
2.8%
103호 2
 
1.4%
2층 2
 
1.4%
지하1층 2
 
1.4%
만수동 2
 
1.4%
남촌동 2
 
1.4%
Other values (65) 66
45.5%
2024-01-28T20:05:36.233850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
 
15.8%
동 57
 
7.5%
1 48
 
6.3%
구 36
 
4.7%
남 29
 
3.8%
지 28
 
3.7%
인 26
 
3.4%
역 26
 
3.4%
시 26
 
3.4%
천 26
 
3.4%
Other values (77) 338
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 436
57.4%
Decimal Number 176
23.2%
Space Separator 120
 
15.8%
Dash Punctuation 21
 
2.8%
Uppercase Letter 7
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 57
13.1%
구 36
 
8.3%
남 29
 
6.7%
지 28
 
6.4%
인 26
 
6.0%
역 26
 
6.0%
시 26
 
6.0%
천 26
 
6.0%
광 25
 
5.7%
번 24
 
5.5%
Other values (59) 133
30.5%
Decimal Number
ValueCountFrequency (%)
1 48
27.3%
2 23
13.1%
0 22
12.5%
3 20
11.4%
6 16
 
9.1%
5 12
 
6.8%
4 10
 
5.7%
8 9
 
5.1%
9 8
 
4.5%
7 8
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
A 2
28.6%
J 1
14.3%
K 1
14.3%
H 1
14.3%
O 1
14.3%
L 1
14.3%
Space Separator
ValueCountFrequency (%)
120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 436
57.4%
Common 317
41.7%
Latin 7
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 57
13.1%
구 36
 
8.3%
남 29
 
6.7%
지 28
 
6.4%
인 26
 
6.0%
역 26
 
6.0%
시 26
 
6.0%
천 26
 
6.0%
광 25
 
5.7%
번 24
 
5.5%
Other values (59) 133
30.5%
Common
ValueCountFrequency (%)
120
37.9%
1 48
 
15.1%
2 23
 
7.3%
0 22
 
6.9%
- 21
 
6.6%
3 20
 
6.3%
6 16
 
5.0%
5 12
 
3.8%
4 10
 
3.2%
8 9
 
2.8%
Other values (2) 16
 
5.0%
Latin
ValueCountFrequency (%)
A 2
28.6%
J 1
14.3%
K 1
14.3%
H 1
14.3%
O 1
14.3%
L 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 436
57.4%
ASCII 324
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
37.0%
1 48
 
14.8%
2 23
 
7.1%
0 22
 
6.8%
- 21
 
6.5%
3 20
 
6.2%
6 16
 
4.9%
5 12
 
3.7%
4 10
 
3.1%
8 9
 
2.8%
Other values (8) 23
 
7.1%
Hangul
ValueCountFrequency (%)
동 57
13.1%
구 36
 
8.3%
남 29
 
6.7%
지 28
 
6.4%
인 26
 
6.0%
역 26
 
6.0%
시 26
 
6.0%
천 26
 
6.0%
광 25
 
5.7%
번 24
 
5.5%
Other values (59) 133
30.5%

소재지(도로명)
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-01-28T20:05:36.463526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length40
Mean length35.64
Min length23

Characters and Unicode

Total characters891
Distinct characters120
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

Unique25 ?
Unique (%)100.0%

Sample

1st row인천광역시 남동구 구월로 121 (간석동)
2nd row인천광역시 남동구 백범로 210 (만수동)
3rd row인천광역시 남동구 경인로 656 (간석동)
4th row인천광역시 남동구 청능대로 581, 201호 (논현동)
5th row인천광역시 남동구 청능대로 596, 지하1층 (논현동)
ValueCountFrequency (%)
인천광역시 25
 
14.6%
남동구 25
 
14.6%
구월동 9
 
5.3%
간석동 6
 
3.5%
논현동 4
 
2.3%
2층 2
 
1.2%
202호 2
 
1.2%
103호 2
 
1.2%
지하1층 2
 
1.2%
예술로 2
 
1.2%
Other values (88) 92
53.8%
2024-01-28T20:05:36.779880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
146
 
16.4%
동 56
 
6.3%
구 38
 
4.3%
1 37
 
4.2%
인 32
 
3.6%
남 32
 
3.6%
천 28
 
3.1%
역 27
 
3.0%
시 26
 
2.9%
) 25
 
2.8%
Other values (110) 444
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 507
56.9%
Decimal Number 154
 
17.3%
Space Separator 146
 
16.4%
Close Punctuation 25
 
2.8%
Open Punctuation 25
 
2.8%
Other Punctuation 25
 
2.8%
Uppercase Letter 6
 
0.7%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 56
 
11.0%
구 38
 
7.5%
인 32
 
6.3%
남 32
 
6.3%
천 28
 
5.5%
역 27
 
5.3%
시 26
 
5.1%
로 25
 
4.9%
광 25
 
4.9%
호 17
 
3.4%
Other values (89) 201
39.6%
Decimal Number
ValueCountFrequency (%)
1 37
24.0%
2 23
14.9%
0 22
14.3%
5 14
 
9.1%
3 14
 
9.1%
8 11
 
7.1%
7 10
 
6.5%
6 9
 
5.8%
4 7
 
4.5%
9 7
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
A 2
33.3%
J 1
16.7%
K 1
16.7%
N 1
16.7%
O 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 24
96.0%
. 1
 
4.0%
Space Separator
ValueCountFrequency (%)
146
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 507
56.9%
Common 378
42.4%
Latin 6
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 56
 
11.0%
구 38
 
7.5%
인 32
 
6.3%
남 32
 
6.3%
천 28
 
5.5%
역 27
 
5.3%
시 26
 
5.1%
로 25
 
4.9%
광 25
 
4.9%
호 17
 
3.4%
Other values (89) 201
39.6%
Common
ValueCountFrequency (%)
146
38.6%
1 37
 
9.8%
) 25
 
6.6%
( 25
 
6.6%
, 24
 
6.3%
2 23
 
6.1%
0 22
 
5.8%
5 14
 
3.7%
3 14
 
3.7%
8 11
 
2.9%
Other values (6) 37
 
9.8%
Latin
ValueCountFrequency (%)
A 2
33.3%
J 1
16.7%
K 1
16.7%
N 1
16.7%
O 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 507
56.9%
ASCII 384
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
146
38.0%
1 37
 
9.6%
) 25
 
6.5%
( 25
 
6.5%
, 24
 
6.2%
2 23
 
6.0%
0 22
 
5.7%
5 14
 
3.6%
3 14
 
3.6%
8 11
 
2.9%
Other values (11) 43
 
11.2%
Hangul
ValueCountFrequency (%)
동 56
 
11.0%
구 38
 
7.5%
인 32
 
6.3%
남 32
 
6.3%
천 28
 
5.5%
역 27
 
5.3%
시 26
 
5.1%
로 25
 
4.9%
광 25
 
4.9%
호 17
 
3.4%
Other values (89) 201
39.6%

전화번호
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing6
Missing (%)24.0%
Memory size332.0 B
2024-01-28T20:05:36.952440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.894737
Min length9

Characters and Unicode

Total characters226
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 (%)100.0%

Sample

1st row032-421-2161
2nd row032-464-9950
3rd row032-434-3366
4th row032-426-3100
5th row032-435-0551
ValueCountFrequency (%)
032-421-2161 1
 
5.3%
070-4135-6198 1
 
5.3%
070-7931-3884 1
 
5.3%
032-434-8871 1
 
5.3%
032-442-7777 1
 
5.3%
070-7677-9677 1
 
5.3%
032-422-0268 1
 
5.3%
1588-9163 1
 
5.3%
1833-3278 1
 
5.3%
032-874-9001 1
 
5.3%
Other values (9) 9
47.4%
2024-01-28T20:05:37.219875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 36
15.9%
3 32
14.2%
2 29
12.8%
0 28
12.4%
4 20
8.8%
7 18
8.0%
1 17
7.5%
6 14
 
6.2%
8 12
 
5.3%
5 11
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190
84.1%
Dash Punctuation 36
 
15.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 32
16.8%
2 29
15.3%
0 28
14.7%
4 20
10.5%
7 18
9.5%
1 17
8.9%
6 14
7.4%
8 12
 
6.3%
5 11
 
5.8%
9 9
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 226
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 36
15.9%
3 32
14.2%
2 29
12.8%
0 28
12.4%
4 20
8.8%
7 18
8.0%
1 17
7.5%
6 14
 
6.2%
8 12
 
5.3%
5 11
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 226
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 36
15.9%
3 32
14.2%
2 29
12.8%
0 28
12.4%
4 20
8.8%
7 18
8.0%
1 17
7.5%
6 14
 
6.2%
8 12
 
5.3%
5 11
 
4.9%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.438718
Minimum37.395297
Maximum37.467213
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-28T20:05:37.334551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.395297
5-th percentile37.400634
Q137.416693
median37.447706
Q337.455821
95-th percentile37.466825
Maximum37.467213
Range0.07191522
Interquartile range (IQR)0.03912881

Descriptive statistics

Standard deviation0.024013102
Coefficient of variation (CV)0.00064139753
Kurtosis-1.0390864
Mean37.438718
Median Absolute Deviation (MAD)0.01233902
Skewness-0.65256922
Sum935.96796
Variance0.00057662905
MonotonicityNot monotonic
2024-01-28T20:05:37.434798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
37.4568925 1
 
4.0%
37.46004476 1
 
4.0%
37.4530871 1
 
4.0%
37.44306241 1
 
4.0%
37.41525721 1
 
4.0%
37.4166926 1
 
4.0%
37.44770574 1
 
4.0%
37.45582141 1
 
4.0%
37.40151444 1
 
4.0%
37.42233585 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
37.39529728 1
4.0%
37.40047259 1
4.0%
37.40127852 1
4.0%
37.40151444 1
4.0%
37.40269499 1
4.0%
37.41525721 1
4.0%
37.4166926 1
4.0%
37.42233585 1
4.0%
37.44022355 1
4.0%
37.44087947 1
4.0%
ValueCountFrequency (%)
37.4672125 1
4.0%
37.46687026 1
4.0%
37.46664377 1
4.0%
37.46448014 1
4.0%
37.46004476 1
4.0%
37.4568925 1
4.0%
37.45582141 1
4.0%
37.4530871 1
4.0%
37.45265315 1
4.0%
37.45173564 1
4.0%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.71244
Minimum126.69351
Maximum126.73585
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-01-28T20:05:37.531165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.69351
5-th percentile126.69624
Q1126.70386
median126.70888
Q3126.72207
95-th percentile126.73088
Maximum126.73585
Range0.0423403
Interquartile range (IQR)0.0182114

Descriptive statistics

Standard deviation0.011582168
Coefficient of variation (CV)9.1405136 × 10-5
Kurtosis-0.78817249
Mean126.71244
Median Absolute Deviation (MAD)0.0070703
Skewness0.38661625
Sum3167.811
Variance0.00013414661
MonotonicityNot monotonic
2024-01-28T20:05:37.618652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
126.7038574 1
 
4.0%
126.7261269 1
 
4.0%
126.7027589 1
 
4.0%
126.708876 1
 
4.0%
126.7048343 1
 
4.0%
126.729188 1
 
4.0%
126.7358518 1
 
4.0%
126.6949468 1
 
4.0%
126.7220688 1
 
4.0%
126.7194107 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
126.6935115 1
4.0%
126.6949468 1
4.0%
126.7013915 1
4.0%
126.7018057 1
4.0%
126.7019459 1
4.0%
126.7027589 1
4.0%
126.7038574 1
4.0%
126.7048343 1
4.0%
126.7049681 1
4.0%
126.7066895 1
4.0%
ValueCountFrequency (%)
126.7358518 1
4.0%
126.7312991 1
4.0%
126.729188 1
4.0%
126.7261269 1
4.0%
126.7257232 1
4.0%
126.7235862 1
4.0%
126.7220688 1
4.0%
126.7194107 1
4.0%
126.7171669 1
4.0%
126.714585 1
4.0%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-05-01
25 

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 25
100.0%

Length

2024-01-28T20:05:37.707292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:05:37.988090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-01 25
100.0%

Interactions

2024-01-28T20:05:34.691535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:05:34.303687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:05:34.498780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:05:34.749556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:05:34.363769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:05:34.561471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:05:34.812931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:05:34.439327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:05:34.633436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T20:05:38.032693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호소재지(지번)소재지(도로명)전화번호위도경도
연번1.0001.0001.0001.0001.0000.4250.861
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
위도0.4251.0001.0001.0001.0001.0000.608
경도0.8611.0001.0001.0001.0000.6081.000
2024-01-28T20:05:38.112152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.000-0.183-0.002
위도-0.1831.000-0.520
경도-0.002-0.5201.000

Missing values

2024-01-28T20:05:34.888958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T20:05:34.985420image/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
01국내여행업주식회사 그랜드항공여행사인천광역시 남동구 간석동 482-3번지인천광역시 남동구 구월로 121 (간석동)032-421-216137.456893126.7038572023-05-01
12국내여행업(주)준여행사인천광역시 남동구 만수동 861-8번지인천광역시 남동구 백범로 210 (만수동)032-464-995037.460045126.7261272023-05-01
23국내여행업주식회사 하늘여행인천광역시 남동구 간석동 221-2인천광역시 남동구 경인로 656 (간석동)032-434-336637.467213126.7049682023-05-01
34국내여행업(주)위드티앤씨인천광역시 남동구 논현동 631-8번지 201호인천광역시 남동구 청능대로 581, 201호 (논현동)032-426-310037.401279126.7235862023-05-01
45국내여행업투어맥스인천광역시 남동구 논현동 650-1번지 지하1층인천광역시 남동구 청능대로 596, 지하1층 (논현동)032-435-055137.400473126.7257232023-05-01
56국내여행업어게인 콜 커뮤니케이션인천광역시 남동구 구월동 1219-5번지 뉴인천빌딩 202호인천광역시 남동구 용천로 3, 뉴인천빌딩 202호 (구월동)032-249-768237.449929126.7139122023-05-01
67국내여행업(주)도울항공인천광역시 남동구 구월동 1542-1번지 네이쳐프라자 7층 705호인천광역시 남동구 선수촌공원로23번길 11, 네이쳐프라자 7층 705호 (구월동)<NA>37.440879126.7086532023-05-01
78국내여행업울타리여행사인천광역시 남동구 구월동 1131-20번지인천광역시 남동구 예술로 208 (구월동)032-441-236537.452653126.7018062023-05-01
89국내여행업투어스토어인천광역시 남동구 구월동 1130번지 홈플러스구월점 지하3층인천광역시 남동구 예술로 198, 지하3층 (구월동, 홈플러스구월점)032-431-252537.451736126.7019462023-05-01
910국내여행업오션스테이인천광역시 남동구 논현동 652-6번지 102호인천광역시 남동구 소래역서로2번길 23, 102호 (논현동)070-4239-523637.402695126.7312992023-05-01
연번업종상호소재지(지번)소재지(도로명)전화번호위도경도데이터기준일
1516국내여행업에스엘피 코리아인천광역시 남동구 고잔동 163-6번지 2층인천광역시 남동구 논현고잔로 142-1, 2층 (고잔동)<NA>37.395297126.7145852023-05-01
1617국내여행업화인투어인천광역시 남동구 간석동 940번지 간석LH1단지 106동 701호인천광역시 남동구 백범로294번길 15, 106동 701호 (간석동, 인천간석엘에이치1단지)<NA>37.46448126.7171672023-05-01
1718국내여행업찐투어인천광역시 남동구 남촌동 652번지 남촌농산물도매시장 업무동 301A호인천광역시 남동구 비류대로 763, 남촌 농산물 도매시장 업무동 301A호 (남촌동)032-422-026837.422336126.7194112023-05-01
1819국내여행업더쎈골프인천광역시 남동구 논현동 632-1번지 칼리오페 8층 817동 828호인천광역시 남동구 논고개로123번길 35, 칼리오페 8층 817-828호 (논현동)070-7677-967737.401514126.7220692023-05-01
1920국내여행업하늘땅 역사교육인천광역시 남동구 간석동 902-11번지 2층인천광역시 남동구 문화로169번길 100, 2층 (간석동)<NA>37.455821126.6949472023-05-01
2021국내여행업뉴스타고속관광(주)인천광역시 남동구 만수동 1073-7번지 흥농빌딩 202호인천광역시 남동구 인주대로888번길 10, 흥농빌딩 202호 (만수동)032-442-777737.447706126.7358522023-05-01
2122국내여행업주식회사 아주관광여행사인천광역시 남동구 도림동 634-6번지 103호인천광역시 남동구 오봉로 14, 103호 (도림동)032-434-887137.416693126.7291882023-05-01
2223국내여행업(주)플러스프레스인천광역시 남동구 남촌동 624-3번지 JK루체스타 5층 509호인천광역시 남동구 남동대로 353, JK루체스타 5층 509호 (남촌동)<NA>37.415257126.7048342023-05-01
2324국내여행업(주)여행마루인천광역시 남동구 구월동 1499-1번지 센트럴프라자 103호인천광역시 남동구 인하로 559, 센트럴프라자 103호 (구월동)032-521-336137.443062126.7088762023-05-01
2425국내여행업낭만투어인천광역시 남동구 구월동 1131-13번지 백세빌딩 601동 73호인천광역시 남동구 구월남로 120, 백세빌딩 601-73호 (구월동)<NA>37.453087126.7027592023-05-01