Overview

Dataset statistics

Number of variables5
Number of observations80
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory42.6 B

Variable types

Numeric1
Categorical2
Text2

Dataset

Description대전광역시 중구 체육도장업(연번, 업종, 상호명, 주소(도로명), 우편번호, 데이터기준일자) 등의 정보를 제공합니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15099439/fileData.do

Alerts

업종 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
주소(도로명) has unique valuesUnique

Reproduction

Analysis started2024-04-19 06:25:24.441798
Analysis finished2024-04-19 06:25:24.908365
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.5
Minimum1
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2024-04-19T15:25:25.268624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.95
Q120.75
median40.5
Q360.25
95-th percentile76.05
Maximum80
Range79
Interquartile range (IQR)39.5

Descriptive statistics

Standard deviation23.2379
Coefficient of variation (CV)0.57377531
Kurtosis-1.2
Mean40.5
Median Absolute Deviation (MAD)20
Skewness0
Sum3240
Variance540
MonotonicityStrictly increasing
2024-04-19T15:25:25.407180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
42 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
53 1
 
1.2%
Other values (70) 70
87.5%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%
72 1
1.2%
71 1
1.2%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
체육도장업
80 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체육도장업 80
100.0%

Length

2024-04-19T15:25:25.533255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:25:25.621124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체육도장업 80
100.0%

상호명
Text

Distinct79
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
2024-04-19T15:25:25.834780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length8.175
Min length5

Characters and Unicode

Total characters654
Distinct characters170
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

Unique78 ?
Unique (%)97.5%

Sample

1st row경희대청룡태권도
2nd row여명체육관
3rd row한사랑 태권도장
4th row한밭체육관
5th row경희태권도
ValueCountFrequency (%)
합기도 8
 
6.6%
태권도 4
 
3.3%
태권도장 3
 
2.5%
용인대 3
 
2.5%
검도관 2
 
1.6%
흑추관 2
 
1.6%
judo 2
 
1.6%
양우관 2
 
1.6%
소나무향기태권도 2
 
1.6%
다윗복싱클럽 1
 
0.8%
Other values (93) 93
76.2%
2024-04-19T15:25:26.229532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 64
 
9.8%
태 46
 
7.0%
43
 
6.6%
권 41
 
6.3%
관 35
 
5.4%
대 19
 
2.9%
기 15
 
2.3%
체 14
 
2.1%
장 13
 
2.0%
용 13
 
2.0%
Other values (160) 351
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 567
86.7%
Space Separator 43
 
6.6%
Uppercase Letter 19
 
2.9%
Lowercase Letter 12
 
1.8%
Close Punctuation 4
 
0.6%
Open Punctuation 4
 
0.6%
Decimal Number 3
 
0.5%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 64
 
11.3%
태 46
 
8.1%
권 41
 
7.2%
관 35
 
6.2%
대 19
 
3.4%
기 15
 
2.6%
체 14
 
2.5%
장 13
 
2.3%
용 13
 
2.3%
육 13
 
2.3%
Other values (131) 294
51.9%
Uppercase Letter
ValueCountFrequency (%)
M 3
15.8%
A 2
10.5%
J 2
10.5%
D 2
10.5%
Y 2
10.5%
L 1
 
5.3%
I 1
 
5.3%
F 1
 
5.3%
B 1
 
5.3%
O 1
 
5.3%
Other values (3) 3
15.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
16.7%
o 2
16.7%
f 1
8.3%
d 1
8.3%
u 1
8.3%
m 1
8.3%
s 1
8.3%
t 1
8.3%
r 1
8.3%
a 1
8.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 567
86.7%
Common 56
 
8.6%
Latin 31
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 64
 
11.3%
태 46
 
8.1%
권 41
 
7.2%
관 35
 
6.2%
대 19
 
3.4%
기 15
 
2.6%
체 14
 
2.5%
장 13
 
2.3%
용 13
 
2.3%
육 13
 
2.3%
Other values (131) 294
51.9%
Latin
ValueCountFrequency (%)
M 3
 
9.7%
A 2
 
6.5%
J 2
 
6.5%
D 2
 
6.5%
Y 2
 
6.5%
e 2
 
6.5%
o 2
 
6.5%
f 1
 
3.2%
d 1
 
3.2%
u 1
 
3.2%
Other values (13) 13
41.9%
Common
ValueCountFrequency (%)
43
76.8%
) 4
 
7.1%
( 4
 
7.1%
, 2
 
3.6%
1 2
 
3.6%
2 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 567
86.7%
ASCII 87
 
13.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 64
 
11.3%
태 46
 
8.1%
권 41
 
7.2%
관 35
 
6.2%
대 19
 
3.4%
기 15
 
2.6%
체 14
 
2.5%
장 13
 
2.3%
용 13
 
2.3%
육 13
 
2.3%
Other values (131) 294
51.9%
ASCII
ValueCountFrequency (%)
43
49.4%
) 4
 
4.6%
( 4
 
4.6%
M 3
 
3.4%
A 2
 
2.3%
, 2
 
2.3%
J 2
 
2.3%
D 2
 
2.3%
1 2
 
2.3%
Y 2
 
2.3%
Other values (19) 21
24.1%

주소(도로명)
Text

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2024-04-19T15:25:26.591264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length27.25
Min length19

Characters and Unicode

Total characters2180
Distinct characters102
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

Unique80 ?
Unique (%)100.0%

Sample

1st row대전광역시 중구 문화로 110(문화동)
2nd row대전광역시 중구 계백로1615번길 66(유천동)
3rd row대전광역시 중구 동서대로1388, 상가동 202호, 203호(목동)
4th row대전광역시 중구 중앙로156번길 10(은행동)
5th row대전광역시 중구 보문산로 31, 114동 3층(산성동, 한밭가든아파트)
ValueCountFrequency (%)
대전광역시 80
 
19.6%
중구 80
 
19.6%
태평로 6
 
1.5%
상가동 5
 
1.2%
목중로 5
 
1.2%
대종로 5
 
1.2%
2층 4
 
1.0%
목동로 4
 
1.0%
평촌로 4
 
1.0%
대둔산로 3
 
0.7%
Other values (172) 212
52.0%
2024-04-19T15:25:27.003529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
329
 
15.1%
대 98
 
4.5%
동 97
 
4.4%
중 92
 
4.2%
광 80
 
3.7%
역 80
 
3.7%
시 80
 
3.7%
구 80
 
3.7%
전 80
 
3.7%
로 79
 
3.6%
Other values (92) 1085
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1234
56.6%
Decimal Number 376
 
17.2%
Space Separator 329
 
15.1%
Other Punctuation 78
 
3.6%
Close Punctuation 77
 
3.5%
Open Punctuation 76
 
3.5%
Dash Punctuation 10
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 98
 
7.9%
동 97
 
7.9%
중 92
 
7.5%
광 80
 
6.5%
역 80
 
6.5%
시 80
 
6.5%
구 80
 
6.5%
전 80
 
6.5%
로 79
 
6.4%
층 57
 
4.6%
Other values (76) 411
33.3%
Decimal Number
ValueCountFrequency (%)
1 75
19.9%
2 72
19.1%
3 48
12.8%
0 44
11.7%
5 33
8.8%
6 31
8.2%
4 25
 
6.6%
7 23
 
6.1%
8 15
 
4.0%
9 10
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 77
98.7%
@ 1
 
1.3%
Space Separator
ValueCountFrequency (%)
329
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1234
56.6%
Common 946
43.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 98
 
7.9%
동 97
 
7.9%
중 92
 
7.5%
광 80
 
6.5%
역 80
 
6.5%
시 80
 
6.5%
구 80
 
6.5%
전 80
 
6.5%
로 79
 
6.4%
층 57
 
4.6%
Other values (76) 411
33.3%
Common
ValueCountFrequency (%)
329
34.8%
, 77
 
8.1%
) 77
 
8.1%
( 76
 
8.0%
1 75
 
7.9%
2 72
 
7.6%
3 48
 
5.1%
0 44
 
4.7%
5 33
 
3.5%
6 31
 
3.3%
Other values (6) 84
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1234
56.6%
ASCII 946
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
329
34.8%
, 77
 
8.1%
) 77
 
8.1%
( 76
 
8.0%
1 75
 
7.9%
2 72
 
7.6%
3 48
 
5.1%
0 44
 
4.7%
5 33
 
3.5%
6 31
 
3.3%
Other values (6) 84
 
8.9%
Hangul
ValueCountFrequency (%)
대 98
 
7.9%
동 97
 
7.9%
중 92
 
7.5%
광 80
 
6.5%
역 80
 
6.5%
시 80
 
6.5%
구 80
 
6.5%
전 80
 
6.5%
로 79
 
6.4%
층 57
 
4.6%
Other values (76) 411
33.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-03-18
80 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-18
2nd row2023-03-18
3rd row2023-03-18
4th row2023-03-18
5th row2023-03-18

Common Values

ValueCountFrequency (%)
2023-03-18 80
100.0%

Length

2024-04-19T15:25:27.132912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:25:27.221902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-18 80
100.0%

Interactions

2024-04-19T15:25:24.654758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T15:25:27.285025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명주소(도로명)
연번1.0001.0001.000
상호명1.0001.0001.000
주소(도로명)1.0001.0001.000

Missing values

2024-04-19T15:25:24.778327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T15:25:24.868245image/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

연번업종상호명주소(도로명)데이터기준일자
01체육도장업경희대청룡태권도대전광역시 중구 문화로 110(문화동)2023-03-18
12체육도장업여명체육관대전광역시 중구 계백로1615번길 66(유천동)2023-03-18
23체육도장업한사랑 태권도장대전광역시 중구 동서대로1388, 상가동 202호, 203호(목동)2023-03-18
34체육도장업한밭체육관대전광역시 중구 중앙로156번길 10(은행동)2023-03-18
45체육도장업경희태권도대전광역시 중구 보문산로 31, 114동 3층(산성동, 한밭가든아파트)2023-03-18
56체육도장업해오름 태권도대전광역시 중구 과례로 25, 4층(문화동)2023-03-18
67체육도장업꾸러기태권도대전광역시 중구 수도산로13, 2층(대흥동)2023-03-18
78체육도장업연세이글태권도대전광역시 중구 목중로 55-7, 1층(목동)2023-03-18
89체육도장업스포렉스태권도대전광역시 중구 유등천동로 468-2(태평동)2023-03-18
910체육도장업용인대온누리태권도장대전광역시 중구 태평로 15(태평동)2023-03-18
연번업종상호명주소(도로명)데이터기준일자
7071체육도장업흑추관 투혼 합기도대전광역시 중구 대둔산로 266, 2층(사정동)2023-03-18
7172체육도장업Dream of Judo 태평유도관대전광역시 중구 평촌로 108, 5층(유천동)2023-03-18
7273체육도장업JUDO FAMILY대전광역시 중구 계룡로874번길 59, 3층, 4층(오류동)2023-03-18
7374체육도장업경희퍼펙트 유도관대전광역시 중구 테미로 21-1, 2층(대흥동)2023-03-18
7475체육도장업흑추관 하랑도장대전광역시 중구 계백로1716번길 24, 3층(문화동)2023-03-18
7576체육도장업경희대멘토태권도대전광역시 중구 문창로 109, 1층 (문창동)2023-03-18
7677체육도장업가호유도관대전광역시 중구 과례로 26, 3층 (문화동)2023-03-18
7778체육도장업태평 검도관대전광역시 중구 태평로 20-1 5층2023-03-18
7879체육도장업Best 검도관대전광역시 중구 목동로42 목동복합빌딩 2층 201, 202호2023-03-18
7980체육도장업용인대 엘리트복싱 체육관대전광역시 중구 계백로 1715, 2층 204호2023-03-18