Overview

Dataset statistics

Number of variables6
Number of observations254
Missing cells100
Missing cells (%)6.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.0 KiB
Average record size in memory48.5 B

Variable types

Categorical3
Text3

Dataset

Description성남시 내 운영중인 여행업(국내,국외,일반여행업) 현황 데이터로, 업종,상호명,소재지주소,전화번호 등의 항목으로 구성되어 있습니다
URLhttps://www.data.go.kr/data/3073432/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 100 (39.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 09:01:16.951435
Analysis finished2023-12-12 09:01:17.463163
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구별
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
분당구
179 
수정구
40 
중원구
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분당구 179
70.5%
수정구 40
 
15.7%
중원구 35
 
13.8%

Length

2023-12-12T18:01:17.529634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:01:17.618760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분당구 179
70.5%
수정구 40
 
15.7%
중원구 35
 
13.8%

업종
Categorical

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
국내외여행업
142 
종합여행업
78 
국내여행업+국내외여행업
19 
국내여행업
15 

Length

Max length12
Median length6
Mean length6.0826772
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내외여행업 142
55.9%
종합여행업 78
30.7%
국내여행업+국내외여행업 19
 
7.5%
국내여행업 15
 
5.9%

Length

2023-12-12T18:01:17.715871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:01:17.809691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내외여행업 142
55.9%
종합여행업 78
30.7%
국내여행업+국내외여행업 19
 
7.5%
국내여행업 15
 
5.9%

상호명
Text

Distinct253
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-12T18:01:17.996883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length7.4645669
Min length2

Characters and Unicode

Total characters1896
Distinct characters306
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique252 ?
Unique (%)99.2%

Sample

1st row(주)비즈하나
2nd row(주)늘푸른여행사
3rd row이천여행사
4th row(주)선목여행
5th row뉴한솔고속(주)
ValueCountFrequency (%)
주식회사 35
 
11.0%
여행사 4
 
1.3%
호인 2
 
0.6%
로드스타 1
 
0.3%
노랑풍선분당 1
 
0.3%
드림관광(주 1
 
0.3%
엘투어(주 1
 
0.3%
분당롯데관광(주 1
 
0.3%
트래블마일즈 1
 
0.3%
에스케이플래닛(주 1
 
0.3%
Other values (271) 271
85.0%
2023-12-12T18:01:18.407129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 121
 
6.4%
) 85
 
4.5%
( 84
 
4.4%
사 82
 
4.3%
어 80
 
4.2%
투 73
 
3.9%
65
 
3.4%
이 56
 
3.0%
행 55
 
2.9%
여 54
 
2.8%
Other values (296) 1141
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1589
83.8%
Close Punctuation 85
 
4.5%
Open Punctuation 84
 
4.4%
Space Separator 65
 
3.4%
Other Symbol 29
 
1.5%
Uppercase Letter 27
 
1.4%
Lowercase Letter 16
 
0.8%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 121
 
7.6%
사 82
 
5.2%
어 80
 
5.0%
투 73
 
4.6%
이 56
 
3.5%
행 55
 
3.5%
여 54
 
3.4%
스 45
 
2.8%
회 41
 
2.6%
식 39
 
2.5%
Other values (263) 943
59.3%
Uppercase Letter
ValueCountFrequency (%)
O 3
 
11.1%
J 3
 
11.1%
T 2
 
7.4%
S 2
 
7.4%
P 2
 
7.4%
K 2
 
7.4%
C 2
 
7.4%
B 1
 
3.7%
M 1
 
3.7%
A 1
 
3.7%
Other values (8) 8
29.6%
Lowercase Letter
ValueCountFrequency (%)
l 2
12.5%
i 2
12.5%
u 2
12.5%
a 2
12.5%
e 2
12.5%
n 2
12.5%
g 1
6.2%
t 1
6.2%
o 1
6.2%
r 1
6.2%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 84
100.0%
Space Separator
ValueCountFrequency (%)
65
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1618
85.3%
Common 235
 
12.4%
Latin 43
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 121
 
7.5%
사 82
 
5.1%
어 80
 
4.9%
투 73
 
4.5%
이 56
 
3.5%
행 55
 
3.4%
여 54
 
3.3%
스 45
 
2.8%
회 41
 
2.5%
식 39
 
2.4%
Other values (264) 972
60.1%
Latin
ValueCountFrequency (%)
O 3
 
7.0%
J 3
 
7.0%
l 2
 
4.7%
i 2
 
4.7%
u 2
 
4.7%
T 2
 
4.7%
a 2
 
4.7%
S 2
 
4.7%
P 2
 
4.7%
e 2
 
4.7%
Other values (18) 21
48.8%
Common
ValueCountFrequency (%)
) 85
36.2%
( 84
35.7%
65
27.7%
- 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1589
83.8%
ASCII 278
 
14.7%
None 29
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 121
 
7.6%
사 82
 
5.2%
어 80
 
5.0%
투 73
 
4.6%
이 56
 
3.5%
행 55
 
3.5%
여 54
 
3.4%
스 45
 
2.8%
회 41
 
2.6%
식 39
 
2.5%
Other values (263) 943
59.3%
ASCII
ValueCountFrequency (%)
) 85
30.6%
( 84
30.2%
65
23.4%
O 3
 
1.1%
J 3
 
1.1%
l 2
 
0.7%
i 2
 
0.7%
u 2
 
0.7%
T 2
 
0.7%
a 2
 
0.7%
Other values (22) 28
 
10.1%
None
ValueCountFrequency (%)
㈜ 29
100.0%

소재지주소
Text

Distinct249
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-12T18:01:18.737086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length48
Mean length35.035433
Min length22

Characters and Unicode

Total characters8899
Distinct characters228
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

Unique245 ?
Unique (%)96.5%

Sample

1st row경기도 성남시 수정구 공원로 333, 301호(신흥동)
2nd row경기도 성남시 수정구 남문로 9-1(태평동)
3rd row경기도 성남시 수정구 모란로133번길 2(태평동)
4th row경기도 성남시 수정구 복정로158번길 8-2(복정동)
5th row경기도 성남시 수정구 산성대로 189, 302호(수진동)
ValueCountFrequency (%)
경기도 254
 
14.8%
성남시 254
 
14.8%
분당구 176
 
10.2%
수정구 40
 
2.3%
중원구 35
 
2.0%
정자일로 15
 
0.9%
11 13
 
0.8%
성남대로 13
 
0.8%
1층 12
 
0.7%
서현동 11
 
0.6%
Other values (540) 899
52.2%
2023-12-12T18:01:19.206298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1472
 
16.5%
1 390
 
4.4%
성 327
 
3.7%
남 317
 
3.6%
동 280
 
3.1%
구 273
 
3.1%
시 263
 
3.0%
기 259
 
2.9%
경 258
 
2.9%
도 255
 
2.9%
Other values (218) 4805
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5008
56.3%
Decimal Number 1602
 
18.0%
Space Separator 1472
 
16.5%
Open Punctuation 250
 
2.8%
Close Punctuation 249
 
2.8%
Other Punctuation 219
 
2.5%
Dash Punctuation 48
 
0.5%
Uppercase Letter 40
 
0.4%
Lowercase Letter 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 327
 
6.5%
남 317
 
6.3%
동 280
 
5.6%
구 273
 
5.5%
시 263
 
5.3%
기 259
 
5.2%
경 258
 
5.2%
도 255
 
5.1%
로 255
 
5.1%
당 189
 
3.8%
Other values (182) 2332
46.6%
Uppercase Letter
ValueCountFrequency (%)
A 8
20.0%
B 7
17.5%
C 5
12.5%
R 4
10.0%
S 3
 
7.5%
T 3
 
7.5%
M 2
 
5.0%
V 2
 
5.0%
K 2
 
5.0%
E 1
 
2.5%
Other values (3) 3
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 390
24.3%
2 213
13.3%
0 211
13.2%
3 169
10.5%
6 130
 
8.1%
5 123
 
7.7%
4 122
 
7.6%
9 89
 
5.6%
8 84
 
5.2%
7 71
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
18.2%
r 2
18.2%
a 2
18.2%
u 1
9.1%
q 1
9.1%
w 1
9.1%
o 1
9.1%
t 1
9.1%
Space Separator
ValueCountFrequency (%)
1472
100.0%
Open Punctuation
ValueCountFrequency (%)
( 250
100.0%
Close Punctuation
ValueCountFrequency (%)
) 249
100.0%
Other Punctuation
ValueCountFrequency (%)
, 219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5008
56.3%
Common 3840
43.2%
Latin 51
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 327
 
6.5%
남 317
 
6.3%
동 280
 
5.6%
구 273
 
5.5%
시 263
 
5.3%
기 259
 
5.2%
경 258
 
5.2%
도 255
 
5.1%
로 255
 
5.1%
당 189
 
3.8%
Other values (182) 2332
46.6%
Latin
ValueCountFrequency (%)
A 8
15.7%
B 7
13.7%
C 5
 
9.8%
R 4
 
7.8%
S 3
 
5.9%
T 3
 
5.9%
M 2
 
3.9%
V 2
 
3.9%
K 2
 
3.9%
e 2
 
3.9%
Other values (11) 13
25.5%
Common
ValueCountFrequency (%)
1472
38.3%
1 390
 
10.2%
( 250
 
6.5%
) 249
 
6.5%
, 219
 
5.7%
2 213
 
5.5%
0 211
 
5.5%
3 169
 
4.4%
6 130
 
3.4%
5 123
 
3.2%
Other values (5) 414
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5008
56.3%
ASCII 3891
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1472
37.8%
1 390
 
10.0%
( 250
 
6.4%
) 249
 
6.4%
, 219
 
5.6%
2 213
 
5.5%
0 211
 
5.4%
3 169
 
4.3%
6 130
 
3.3%
5 123
 
3.2%
Other values (26) 465
 
12.0%
Hangul
ValueCountFrequency (%)
성 327
 
6.5%
남 317
 
6.3%
동 280
 
5.6%
구 273
 
5.5%
시 263
 
5.3%
기 259
 
5.2%
경 258
 
5.2%
도 255
 
5.1%
로 255
 
5.1%
당 189
 
3.8%
Other values (182) 2332
46.6%

전화번호
Text

MISSING 

Distinct152
Distinct (%)98.7%
Missing100
Missing (%)39.4%
Memory size2.1 KiB
2023-12-12T18:01:19.511853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.097403
Min length9

Characters and Unicode

Total characters1863
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

Unique150 ?
Unique (%)97.4%

Sample

1st row031-733-8300
2nd row031-744-5183
3rd row031-753-1600
4th row031-751-5566
5th row031-722-2992
ValueCountFrequency (%)
031-717-7687 2
 
1.3%
031-781-5270 2
 
1.3%
031-711-5454 1
 
0.6%
031-702-3031 1
 
0.6%
1644-4830 1
 
0.6%
031-602-5979 1
 
0.6%
031-715-7700 1
 
0.6%
031-778-7456 1
 
0.6%
031-782-0516 1
 
0.6%
031-889-3577 1
 
0.6%
Other values (142) 142
92.2%
2023-12-12T18:01:20.040298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 320
17.2%
- 305
16.4%
1 238
12.8%
7 230
12.3%
3 198
10.6%
8 123
 
6.6%
2 100
 
5.4%
5 99
 
5.3%
6 87
 
4.7%
4 86
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1558
83.6%
Dash Punctuation 305
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 320
20.5%
1 238
15.3%
7 230
14.8%
3 198
12.7%
8 123
 
7.9%
2 100
 
6.4%
5 99
 
6.4%
6 87
 
5.6%
4 86
 
5.5%
9 77
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 305
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1863
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 320
17.2%
- 305
16.4%
1 238
12.8%
7 230
12.3%
3 198
10.6%
8 123
 
6.6%
2 100
 
5.4%
5 99
 
5.3%
6 87
 
4.7%
4 86
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1863
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 320
17.2%
- 305
16.4%
1 238
12.8%
7 230
12.3%
3 198
10.6%
8 123
 
6.6%
2 100
 
5.4%
5 99
 
5.3%
6 87
 
4.7%
4 86
 
4.6%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-05-31
254 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-31
2nd row2023-05-31
3rd row2023-05-31
4th row2023-05-31
5th row2023-05-31

Common Values

ValueCountFrequency (%)
2023-05-31 254
100.0%

Length

2023-12-12T18:01:20.231035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:01:20.365554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-31 254
100.0%

Correlations

2023-12-12T18:01:20.474685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구별업종
구별1.0000.123
업종0.1231.000
2023-12-12T18:01:20.599318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구별업종
구별1.0000.116
업종0.1161.000
2023-12-12T18:01:20.709076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구별업종
구별1.0000.116
업종0.1161.000

Missing values

2023-12-12T18:01:17.288130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:01:17.395119image/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

구별업종상호명소재지주소전화번호데이터기준일자
0수정구국내외여행업(주)비즈하나경기도 성남시 수정구 공원로 333, 301호(신흥동)031-733-83002023-05-31
1수정구국내외여행업(주)늘푸른여행사경기도 성남시 수정구 남문로 9-1(태평동)031-744-51832023-05-31
2수정구국내외여행업이천여행사경기도 성남시 수정구 모란로133번길 2(태평동)031-753-16002023-05-31
3수정구국내외여행업(주)선목여행경기도 성남시 수정구 복정로158번길 8-2(복정동)031-751-55662023-05-31
4수정구국내외여행업뉴한솔고속(주)경기도 성남시 수정구 산성대로 189, 302호(수진동)031-722-29922023-05-31
5수정구국내여행업주식회사길벗플러스여행사경기도 성남시 수정구 산성대로 331, 429호(신흥동)<NA>2023-05-31
6수정구국내여행업놀짱경기도 성남시 수정구 산성대로 331, 612호(신흥동)<NA>2023-05-31
7수정구국내여행업+국내외여행업(주)착한여행사경기도 성남시 수정구 산성대로 337(신흥동), 6층031-735-88002023-05-31
8수정구종합여행업(주)릴리투어경기도 성남시 수정구 성남대로 1170(수진동) 1층031-741-00062023-05-31
9수정구국내외여행업베트남자유투어경기도 성남시 수정구 성남대로 1244, 인티움 1404호(태평동)<NA>2023-05-31
구별업종상호명소재지주소전화번호데이터기준일자
244분당구종합여행업(주)더블화이트경기도 성남시 분당구 판교로572번길 11, 1층 (야탑동)031-704-33772023-05-31
245분당구종합여행업세아경기도 성남시 분당구 서현로 170, 풍림아이원플러스 T동 2302호 (서현동)<NA>2023-05-31
246분당구종합여행업Blue Signal (블루 시그널)경기도 성남시 분당구 판교역로192번길 14, 리치투게더센터 4층 412호 (삼평동)070-5180-63992023-05-31
247분당구종합여행업주식회사 메타에스아이경기도 성남시 분당구 판교로228번길 15, 판교세븐벤처밸리1 2동 8층 (삼평동)<NA>2023-05-31
248분당구종합여행업소프트랜더스 주식회사경기도 성남시 분당구 판교로289번길 20, 판교테크노밸리 스타트업 캠퍼스 3동 3층 (삼평동)<NA>2023-05-31
249분당구종합여행업트립코스터경기도 성남시 분당구 정자일로 132, 정자역 엠코헤리츠 4단지 401동 208호 (정자동)070-4544-69452023-05-31
250분당구종합여행업다원여행사경기도 성남시 분당구 느티로77번길 23, 지하1층 (정자동)<NA>2023-05-31
251분당구종합여행업로드스타경기도 성남시 분당구 판교역로192번길 16, 판교타워 806호 (삼평동)<NA>2023-05-31
252분당구종합여행업드라이버 가이드 투어즈코리아경기도 성남시 분당구 불정로386번길 10, 601동 2012, 2013호 (서현동, 효자촌미래타운아파트)<NA>2023-05-31
253분당구종합여행업(주)알람투어경기도 성남시 분당구 서현로180번길 13, 서현프라자 7층 703호 (서현동)<NA>2023-05-31