Overview

Dataset statistics

Number of variables5
Number of observations757
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.4 KiB
Average record size in memory41.2 B

Variable types

Numeric1
Categorical2
Text2

Dataset

Description대구 지역 여행업 업체 현황정보에 관한 공공데이터로 구군, 업종중분류(종합여행업,국내외여행업,국내여행업), 업체명, 소재지 등의 정보를 제공합니다.
Author대구광역시
URLhttps://www.data.go.kr/data/15054193/fileData.do

Alerts

연번 is highly overall correlated with 구군명High correlation
구군명 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-29 22:33:52.186777
Analysis finished2024-04-29 22:33:54.102470
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct757
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean379
Minimum1
Maximum757
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2024-04-30T07:33:54.172356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile38.8
Q1190
median379
Q3568
95-th percentile719.2
Maximum757
Range756
Interquartile range (IQR)378

Descriptive statistics

Standard deviation218.67137
Coefficient of variation (CV)0.57696931
Kurtosis-1.2
Mean379
Median Absolute Deviation (MAD)189
Skewness0
Sum286903
Variance47817.167
MonotonicityStrictly increasing
2024-04-30T07:33:54.313118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
510 1
 
0.1%
501 1
 
0.1%
502 1
 
0.1%
503 1
 
0.1%
504 1
 
0.1%
505 1
 
0.1%
506 1
 
0.1%
507 1
 
0.1%
508 1
 
0.1%
Other values (747) 747
98.7%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
757 1
0.1%
756 1
0.1%
755 1
0.1%
754 1
0.1%
753 1
0.1%
752 1
0.1%
751 1
0.1%
750 1
0.1%
749 1
0.1%
748 1
0.1%

구군명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
중구
281 
달서구
116 
수성구
106 
동구
87 
북구
70 
Other values (4)
97 

Length

Max length3
Median length2
Mean length2.327609
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 281
37.1%
달서구 116
15.3%
수성구 106
 
14.0%
동구 87
 
11.5%
북구 70
 
9.2%
서구 37
 
4.9%
남구 34
 
4.5%
달성군 24
 
3.2%
군위군 2
 
0.3%

Length

2024-04-30T07:33:54.447587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:33:54.561895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 281
37.1%
달서구 116
15.3%
수성구 106
 
14.0%
동구 87
 
11.5%
북구 70
 
9.2%
서구 37
 
4.9%
남구 34
 
4.5%
달성군 24
 
3.2%
군위군 2
 
0.3%

업종중분류
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
국내외여행업
442 
종합여행업
196 
국내여행업
119 

Length

Max length6
Median length6
Mean length5.5838838
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내외여행업 442
58.4%
종합여행업 196
25.9%
국내여행업 119
 
15.7%

Length

2024-04-30T07:33:54.709083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T07:33:54.813066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내외여행업 442
58.4%
종합여행업 196
25.9%
국내여행업 119
 
15.7%

업체명
Text

Distinct684
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-04-30T07:33:55.015504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length20
Mean length7.9498018
Min length2

Characters and Unicode

Total characters6018
Distinct characters423
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique613 ?
Unique (%)81.0%

Sample

1st row경상관광(주)
2nd row(주)신세계항공여행사
3rd row(주)다모아관광여행사
4th row(주)코스모스항공여행사
5th row(주)알파항공여행사
ValueCountFrequency (%)
주식회사 67
 
7.3%
여행사 15
 
1.6%
투어 9
 
1.0%
㈜아름다운 3
 
0.3%
여행 3
 
0.3%
주 3
 
0.3%
tour 3
 
0.3%
트래블 3
 
0.3%
㈜ 3
 
0.3%
사람과 3
 
0.3%
Other values (727) 808
87.8%
2024-04-30T07:33:55.422300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 429
 
7.1%
) 353
 
5.9%
( 353
 
5.9%
사 311
 
5.2%
행 301
 
5.0%
여 292
 
4.9%
어 238
 
4.0%
투 230
 
3.8%
163
 
2.7%
㈜ 130
 
2.2%
Other values (413) 3218
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4877
81.0%
Close Punctuation 353
 
5.9%
Open Punctuation 353
 
5.9%
Space Separator 163
 
2.7%
Other Symbol 130
 
2.2%
Uppercase Letter 94
 
1.6%
Lowercase Letter 32
 
0.5%
Other Punctuation 12
 
0.2%
Decimal Number 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 429
 
8.8%
사 311
 
6.4%
행 301
 
6.2%
여 292
 
6.0%
어 238
 
4.9%
투 230
 
4.7%
이 121
 
2.5%
스 99
 
2.0%
관 92
 
1.9%
광 92
 
1.9%
Other values (364) 2672
54.8%
Uppercase Letter
ValueCountFrequency (%)
T 10
10.6%
O 10
10.6%
R 7
 
7.4%
A 7
 
7.4%
S 7
 
7.4%
L 7
 
7.4%
N 6
 
6.4%
U 6
 
6.4%
C 5
 
5.3%
K 5
 
5.3%
Other values (13) 24
25.5%
Lowercase Letter
ValueCountFrequency (%)
r 5
15.6%
e 4
12.5%
o 4
12.5%
a 3
9.4%
u 3
9.4%
t 3
9.4%
l 2
 
6.2%
v 2
 
6.2%
d 1
 
3.1%
y 1
 
3.1%
Other values (4) 4
12.5%
Other Punctuation
ValueCountFrequency (%)
. 4
33.3%
& 3
25.0%
, 2
16.7%
" 2
16.7%
/ 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 353
100.0%
Open Punctuation
ValueCountFrequency (%)
( 353
100.0%
Space Separator
ValueCountFrequency (%)
163
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 130
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5007
83.2%
Common 885
 
14.7%
Latin 126
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 429
 
8.6%
사 311
 
6.2%
행 301
 
6.0%
여 292
 
5.8%
어 238
 
4.8%
투 230
 
4.6%
㈜ 130
 
2.6%
이 121
 
2.4%
스 99
 
2.0%
관 92
 
1.8%
Other values (365) 2764
55.2%
Latin
ValueCountFrequency (%)
T 10
 
7.9%
O 10
 
7.9%
R 7
 
5.6%
A 7
 
5.6%
S 7
 
5.6%
L 7
 
5.6%
N 6
 
4.8%
U 6
 
4.8%
C 5
 
4.0%
K 5
 
4.0%
Other values (27) 56
44.4%
Common
ValueCountFrequency (%)
) 353
39.9%
( 353
39.9%
163
18.4%
. 4
 
0.5%
& 3
 
0.3%
, 2
 
0.2%
" 2
 
0.2%
1 2
 
0.2%
/ 1
 
0.1%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4877
81.0%
ASCII 1011
 
16.8%
None 130
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 429
 
8.8%
사 311
 
6.4%
행 301
 
6.2%
여 292
 
6.0%
어 238
 
4.9%
투 230
 
4.7%
이 121
 
2.5%
스 99
 
2.0%
관 92
 
1.9%
광 92
 
1.9%
Other values (364) 2672
54.8%
ASCII
ValueCountFrequency (%)
) 353
34.9%
( 353
34.9%
163
16.1%
T 10
 
1.0%
O 10
 
1.0%
R 7
 
0.7%
A 7
 
0.7%
S 7
 
0.7%
L 7
 
0.7%
N 6
 
0.6%
Other values (38) 88
 
8.7%
None
ValueCountFrequency (%)
㈜ 130
100.0%

소재지
Text

Distinct625
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-04-30T07:33:55.836765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length45
Mean length30.311757
Min length15

Characters and Unicode

Total characters22946
Distinct characters307
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique519 ?
Unique (%)68.6%

Sample

1st row대구광역시 중구 태평로 177 (태평로1가)
2nd row대구광역시 중구 국채보상로 627-1 (공평동)
3rd row대구광역시 중구 중앙대로 432-1 (포정동)
4th row대구광역시 중구 국채보상로131길 55, 18호 (동인동1가)
5th row대구광역시 중구 경상감영길 238, 2층 (동문동)
ValueCountFrequency (%)
대구광역시 754
 
16.7%
중구 281
 
6.2%
달서구 116
 
2.6%
수성구 106
 
2.3%
2층 95
 
2.1%
동구 87
 
1.9%
북구 70
 
1.5%
국채보상로 63
 
1.4%
경상감영길 55
 
1.2%
3층 54
 
1.2%
Other values (1131) 2839
62.8%
2024-04-30T07:33:56.406231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3772
 
16.4%
구 1625
 
7.1%
동 1086
 
4.7%
대 1014
 
4.4%
1 889
 
3.9%
시 789
 
3.4%
광 768
 
3.3%
역 763
 
3.3%
로 713
 
3.1%
) 700
 
3.1%
Other values (297) 10827
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13074
57.0%
Decimal Number 3877
 
16.9%
Space Separator 3772
 
16.4%
Close Punctuation 700
 
3.1%
Open Punctuation 700
 
3.1%
Other Punctuation 643
 
2.8%
Dash Punctuation 126
 
0.5%
Uppercase Letter 49
 
0.2%
Lowercase Letter 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1625
 
12.4%
동 1086
 
8.3%
대 1014
 
7.8%
시 789
 
6.0%
광 768
 
5.9%
역 763
 
5.8%
로 713
 
5.5%
층 347
 
2.7%
중 322
 
2.5%
호 270
 
2.1%
Other values (266) 5377
41.1%
Uppercase Letter
ValueCountFrequency (%)
C 7
14.3%
T 7
14.3%
Y 6
12.2%
B 6
12.2%
I 6
12.2%
A 5
10.2%
S 5
10.2%
K 4
8.2%
W 1
 
2.0%
H 1
 
2.0%
Decimal Number
ValueCountFrequency (%)
1 889
22.9%
2 698
18.0%
3 407
10.5%
0 388
10.0%
5 360
9.3%
4 292
 
7.5%
6 254
 
6.6%
7 235
 
6.1%
9 178
 
4.6%
8 176
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
c 1
25.0%
t 1
25.0%
d 1
25.0%
e 1
25.0%
Space Separator
ValueCountFrequency (%)
3772
100.0%
Close Punctuation
ValueCountFrequency (%)
) 700
100.0%
Open Punctuation
ValueCountFrequency (%)
( 700
100.0%
Other Punctuation
ValueCountFrequency (%)
, 643
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 126
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13074
57.0%
Common 9819
42.8%
Latin 53
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1625
 
12.4%
동 1086
 
8.3%
대 1014
 
7.8%
시 789
 
6.0%
광 768
 
5.9%
역 763
 
5.8%
로 713
 
5.5%
층 347
 
2.7%
중 322
 
2.5%
호 270
 
2.1%
Other values (266) 5377
41.1%
Common
ValueCountFrequency (%)
3772
38.4%
1 889
 
9.1%
) 700
 
7.1%
( 700
 
7.1%
2 698
 
7.1%
, 643
 
6.5%
3 407
 
4.1%
0 388
 
4.0%
5 360
 
3.7%
4 292
 
3.0%
Other values (6) 970
 
9.9%
Latin
ValueCountFrequency (%)
C 7
13.2%
T 7
13.2%
Y 6
11.3%
B 6
11.3%
I 6
11.3%
A 5
9.4%
S 5
9.4%
K 4
7.5%
W 1
 
1.9%
H 1
 
1.9%
Other values (5) 5
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13074
57.0%
ASCII 9872
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3772
38.2%
1 889
 
9.0%
) 700
 
7.1%
( 700
 
7.1%
2 698
 
7.1%
, 643
 
6.5%
3 407
 
4.1%
0 388
 
3.9%
5 360
 
3.6%
4 292
 
3.0%
Other values (21) 1023
 
10.4%
Hangul
ValueCountFrequency (%)
구 1625
 
12.4%
동 1086
 
8.3%
대 1014
 
7.8%
시 789
 
6.0%
광 768
 
5.9%
역 763
 
5.8%
로 713
 
5.5%
층 347
 
2.7%
중 322
 
2.5%
호 270
 
2.1%
Other values (266) 5377
41.1%

Interactions

2024-04-30T07:33:53.793770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:33:56.505393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구군명업종중분류
연번1.0000.8970.628
구군명0.8971.0000.050
업종중분류0.6280.0501.000
2024-04-30T07:33:56.589929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종중분류구군명
업종중분류1.0000.021
구군명0.0211.000
2024-04-30T07:33:56.703986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구군명업종중분류
연번1.0000.6940.472
구군명0.6941.0000.021
업종중분류0.4720.0211.000

Missing values

2024-04-30T07:33:53.973088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:33:54.062246image/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

연번구군명업종중분류업체명소재지
01중구국내여행업경상관광(주)대구광역시 중구 태평로 177 (태평로1가)
12중구국내여행업(주)신세계항공여행사대구광역시 중구 국채보상로 627-1 (공평동)
23중구국내여행업(주)다모아관광여행사대구광역시 중구 중앙대로 432-1 (포정동)
34중구국내여행업(주)코스모스항공여행사대구광역시 중구 국채보상로131길 55, 18호 (동인동1가)
45중구국내여행업(주)알파항공여행사대구광역시 중구 경상감영길 238, 2층 (동문동)
56중구국내여행업(주)포시즌항공여행사대구광역시 중구 달구벌대로 2034, 806호 (남산동)
67중구국내여행업(주)경일항공여행사대구광역시 중구 명덕로 207, 2층 (남산동)
78중구국내여행업(주)투어일일사대구광역시 중구 동덕로36길 28 (동인동2가)
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