Overview

Dataset statistics

Number of variables4
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory825.0 B
Average record size in memory39.3 B

Variable types

Numeric1
Text3

Dataset

Description인천광역시 부평구 국내 여행업 현황 데이터입니다.(상호,소재지(도로명))ex) 거산항공여행사,인천광역시 부평구 부평대로 6 (부평동, 대신스카이프라자 301호)
Author인천광역시 부평구
URLhttps://www.data.go.kr/data/15089234/fileData.do

Alerts

순번 has unique valuesUnique
상호 has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:19:24.317740
Analysis finished2023-12-12 04:19:25.213740
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T13:19:25.274464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2023-12-12T13:19:25.393327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

상호
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T13:19:25.553997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length7.7142857
Min length4

Characters and Unicode

Total characters162
Distinct characters77
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

Unique21 ?
Unique (%)100.0%

Sample

1st row거산항공여행사
2nd row삼희관광
3rd row(주)아름관광여행사
4th row(주)길벗여행사
5th row승희여행사
ValueCountFrequency (%)
주식회사 3
 
12.0%
거산항공여행사 1
 
4.0%
그림피 1
 
4.0%
망고국제무역 1
 
4.0%
이편한여행 1
 
4.0%
한솔네트웍스 1
 
4.0%
주)인천다나관광 1
 
4.0%
인우여행사 1
 
4.0%
라이온투어(주 1
 
4.0%
주)칠성관광 1
 
4.0%
Other values (13) 13
52.0%
2023-12-12T13:19:25.845943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
7.4%
11
 
6.8%
10
 
6.2%
10
 
6.2%
) 9
 
5.6%
( 9
 
5.6%
4
 
2.5%
4
 
2.5%
4
 
2.5%
4
 
2.5%
Other values (67) 85
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 140
86.4%
Close Punctuation 9
 
5.6%
Open Punctuation 9
 
5.6%
Space Separator 4
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12
 
8.6%
11
 
7.9%
10
 
7.1%
10
 
7.1%
4
 
2.9%
4
 
2.9%
4
 
2.9%
4
 
2.9%
4
 
2.9%
3
 
2.1%
Other values (64) 74
52.9%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 140
86.4%
Common 22
 
13.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12
 
8.6%
11
 
7.9%
10
 
7.1%
10
 
7.1%
4
 
2.9%
4
 
2.9%
4
 
2.9%
4
 
2.9%
4
 
2.9%
3
 
2.1%
Other values (64) 74
52.9%
Common
ValueCountFrequency (%)
) 9
40.9%
( 9
40.9%
4
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 140
86.4%
ASCII 22
 
13.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
12
 
8.6%
11
 
7.9%
10
 
7.1%
10
 
7.1%
4
 
2.9%
4
 
2.9%
4
 
2.9%
4
 
2.9%
4
 
2.9%
3
 
2.1%
Other values (64) 74
52.9%
ASCII
ValueCountFrequency (%)
) 9
40.9%
( 9
40.9%
4
18.2%
Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T13:19:26.058090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length31
Mean length25.190476
Min length18

Characters and Unicode

Total characters529
Distinct characters78
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

Unique19 ?
Unique (%)90.5%

Sample

1st row인천광역시 부평구 부평동 194-4
2nd row인천광역시 부평구 갈산동 169-25
3rd row인천광역시 부평구 부평동 373-26 추인타워 402호
4th row인천광역시 부평구 삼산동 426-9 에스엠메디칼프라자 501호
5th row인천광역시 부평구 산곡동 182 한양프라자 206호
ValueCountFrequency (%)
인천광역시 21
20.2%
부평구 21
20.2%
십정동 6
 
5.8%
삼산동 5
 
4.8%
부평동 4
 
3.8%
167-7 2
 
1.9%
산곡동 2
 
1.9%
청천동 2
 
1.9%
206호 2
 
1.9%
부개동 1
 
1.0%
Other values (38) 38
36.5%
2023-12-12T13:19:26.365997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
18.7%
27
 
5.1%
26
 
4.9%
23
 
4.3%
23
 
4.3%
22
 
4.2%
21
 
4.0%
21
 
4.0%
21
 
4.0%
21
 
4.0%
Other values (68) 225
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 309
58.4%
Decimal Number 101
 
19.1%
Space Separator 99
 
18.7%
Dash Punctuation 19
 
3.6%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
27
 
8.7%
26
 
8.4%
23
 
7.4%
23
 
7.4%
22
 
7.1%
21
 
6.8%
21
 
6.8%
21
 
6.8%
21
 
6.8%
9
 
2.9%
Other values (55) 95
30.7%
Decimal Number
ValueCountFrequency (%)
1 20
19.8%
4 14
13.9%
2 12
11.9%
6 11
10.9%
5 11
10.9%
9 9
8.9%
7 7
 
6.9%
0 6
 
5.9%
3 6
 
5.9%
8 5
 
5.0%
Space Separator
ValueCountFrequency (%)
99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 309
58.4%
Common 219
41.4%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
27
 
8.7%
26
 
8.4%
23
 
7.4%
23
 
7.4%
22
 
7.1%
21
 
6.8%
21
 
6.8%
21
 
6.8%
21
 
6.8%
9
 
2.9%
Other values (55) 95
30.7%
Common
ValueCountFrequency (%)
99
45.2%
1 20
 
9.1%
- 19
 
8.7%
4 14
 
6.4%
2 12
 
5.5%
6 11
 
5.0%
5 11
 
5.0%
9 9
 
4.1%
7 7
 
3.2%
0 6
 
2.7%
Other values (2) 11
 
5.0%
Latin
ValueCountFrequency (%)
c 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 309
58.4%
ASCII 220
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
45.0%
1 20
 
9.1%
- 19
 
8.6%
4 14
 
6.4%
2 12
 
5.5%
6 11
 
5.0%
5 11
 
5.0%
9 9
 
4.1%
7 7
 
3.2%
0 6
 
2.7%
Other values (3) 12
 
5.5%
Hangul
ValueCountFrequency (%)
27
 
8.7%
26
 
8.4%
23
 
7.4%
23
 
7.4%
22
 
7.1%
21
 
6.8%
21
 
6.8%
21
 
6.8%
21
 
6.8%
9
 
2.9%
Other values (55) 95
30.7%
Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T13:19:26.579987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38
Mean length34.619048
Min length25

Characters and Unicode

Total characters727
Distinct characters109
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 부평대로 6 (부평동, 대신스카이프라자 301호)
2nd row인천광역시 부평구 평천로 323-1 (갈산동)
3rd row인천광역시 부평구 부흥로294번길 4 (부평동,추인타워 402호)
4th row인천광역시 부평구 평천로 398, 501호 (삼산동,에스엠메디칼프라자)
5th row인천광역시 부평구 마장로 287, 206호 (산곡동,한양프라자)
ValueCountFrequency (%)
인천광역시 21
 
14.9%
부평구 21
 
14.9%
십정동 6
 
4.3%
삼산동 4
 
2.8%
부평동 3
 
2.1%
301호 3
 
2.1%
11 3
 
2.1%
1층 3
 
2.1%
마장로 2
 
1.4%
3층 2
 
1.4%
Other values (66) 73
51.8%
2023-12-12T13:19:26.906147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
16.6%
30
 
4.1%
29
 
4.0%
26
 
3.6%
, 24
 
3.3%
23
 
3.2%
1 23
 
3.2%
22
 
3.0%
21
 
2.9%
21
 
2.9%
Other values (99) 387
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 429
59.0%
Space Separator 121
 
16.6%
Decimal Number 106
 
14.6%
Other Punctuation 24
 
3.3%
Close Punctuation 21
 
2.9%
Open Punctuation 21
 
2.9%
Dash Punctuation 3
 
0.4%
Lowercase Letter 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
30
 
7.0%
29
 
6.8%
26
 
6.1%
23
 
5.4%
22
 
5.1%
21
 
4.9%
21
 
4.9%
21
 
4.9%
21
 
4.9%
21
 
4.9%
Other values (82) 194
45.2%
Decimal Number
ValueCountFrequency (%)
1 23
21.7%
3 16
15.1%
2 15
14.2%
6 13
12.3%
4 12
11.3%
0 12
11.3%
9 6
 
5.7%
7 4
 
3.8%
8 3
 
2.8%
5 2
 
1.9%
Space Separator
ValueCountFrequency (%)
121
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 429
59.0%
Common 296
40.7%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
30
 
7.0%
29
 
6.8%
26
 
6.1%
23
 
5.4%
22
 
5.1%
21
 
4.9%
21
 
4.9%
21
 
4.9%
21
 
4.9%
21
 
4.9%
Other values (82) 194
45.2%
Common
ValueCountFrequency (%)
121
40.9%
, 24
 
8.1%
1 23
 
7.8%
) 21
 
7.1%
( 21
 
7.1%
3 16
 
5.4%
2 15
 
5.1%
6 13
 
4.4%
4 12
 
4.1%
0 12
 
4.1%
Other values (5) 18
 
6.1%
Latin
ValueCountFrequency (%)
c 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 429
59.0%
ASCII 298
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
40.6%
, 24
 
8.1%
1 23
 
7.7%
) 21
 
7.0%
( 21
 
7.0%
3 16
 
5.4%
2 15
 
5.0%
6 13
 
4.4%
4 12
 
4.0%
0 12
 
4.0%
Other values (7) 20
 
6.7%
Hangul
ValueCountFrequency (%)
30
 
7.0%
29
 
6.8%
26
 
6.1%
23
 
5.4%
22
 
5.1%
21
 
4.9%
21
 
4.9%
21
 
4.9%
21
 
4.9%
21
 
4.9%
Other values (82) 194
45.2%

Interactions

2023-12-12T13:19:24.604256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:19:27.010147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번상호소재지(지번)소재지(도로명)
순번1.0001.0001.0001.000
상호1.0001.0001.0001.000
소재지(지번)1.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.000

Missing values

2023-12-12T13:19:25.097737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:19:25.181744image/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

순번상호소재지(지번)소재지(도로명)
01거산항공여행사인천광역시 부평구 부평동 194-4인천광역시 부평구 부평대로 6 (부평동, 대신스카이프라자 301호)
12삼희관광인천광역시 부평구 갈산동 169-25인천광역시 부평구 평천로 323-1 (갈산동)
23(주)아름관광여행사인천광역시 부평구 부평동 373-26 추인타워 402호인천광역시 부평구 부흥로294번길 4 (부평동,추인타워 402호)
34(주)길벗여행사인천광역시 부평구 삼산동 426-9 에스엠메디칼프라자 501호인천광역시 부평구 평천로 398, 501호 (삼산동,에스엠메디칼프라자)
45승희여행사인천광역시 부평구 산곡동 182 한양프라자 206호인천광역시 부평구 마장로 287, 206호 (산곡동,한양프라자)
56동포여행사인천광역시 부평구 십정동 403-9인천광역시 부평구 열우물로49번길 6, 4층 (십정동)
67(주)해승여행사인천광역시 부평구 십정동 195-2 1층호인천광역시 부평구 상정로 34, 1층 (십정동)
78주식회사 호은투어인천광역시 부평구 산곡동 159-52 롯데마트 부평점인천광역시 부평구 마장로 296, 롯데마트 부평점 1층 (산곡동)
89울릉스타투어인천광역시 부평구 십정동 352인천광역시 부평구 백범로540번길 32, 1층 (십정동, 그린캐슬)
910(주)모닝투어인천광역시 부평구 부평동 561-4인천광역시 부평구 장제로 71, 301호 (부평동)
순번상호소재지(지번)소재지(도로명)
1112주식회사 그림피인천광역시 부평구 부평동 152-1 다운타운일레븐인천광역시 부평구 대정로 66, 다운타운일레븐 빌딩 309호 (부평동)
1213손오공여행사(불교전문여행)인천광역시 부평구 부개동 498-9 대현프라자인천광역시 부평구 부개로 61-14, 대현프라자 301호 (부개동)
1314체험견학연구소인천광역시 부평구 십정동 441 종근당빌딩 3동 c-4호인천광역시 부평구 백범로 478, 종근당빌딩 3층 c-4호 (십정동)
1415(주)칠성관광인천광역시 부평구 삼산동 167-7인천광역시 부평구 대보로12번길 11, 3층 (삼산동)
1516라이온투어(주)인천광역시 부평구 삼산동 167-7인천광역시 부평구 대보로12번길 11, 3층호 (삼산동)
1617인우여행사인천광역시 부평구 청천동 13-47인천광역시 부평구 마장로473번길 10, 칠복빌딩 4층 (청천동)
1718(주)인천다나관광인천광역시 부평구 십정동 181-267 더카운티인천광역시 부평구 마장로36번길 26, 더카운티 B03호 (십정동)
1819한솔네트웍스 주식회사인천광역시 부평구 청천동 191-8인천광역시 부평구 세월천로 11, 2층 (청천동)
1920이편한여행인천광역시 부평구 삼산동 465-1 대덕리치아노인천광역시 부평구 길주로 623, 대덕리치아노 롯데마트 지하2층 (삼산동)
2021망고국제무역 유한회사인천광역시 부평구 십정동 510-4 세종빌딩인천광역시 부평구 동암남로 29, 세종빌딩 606호 (십정동)