Overview

Dataset statistics

Number of variables13
Number of observations267
Missing cells237
Missing cells (%)6.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.8 KiB
Average record size in memory110.5 B

Variable types

Numeric4
Categorical4
Text4
DateTime1

Dataset

Description전북특별자치도 전주시의 체육도장업을 제공하며, 업종, 구분, 사업장명, 인허가일자, 전화번호, 도로명주소, 지번주소 등을 제공합니다.체육도장업 : 태권도, 검도 등 신체 및 정신을 단련시키는 업소항목 : 업종, 구분, 사업장명, 인허가일자, 전화번호, 도로명주소, 지번주소, 위도, 경도 등제공부서 : 체육산업과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15112498/fileData.do

Alerts

업종 has constant value ""Constant
연번 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번High correlation
회원모집총인원 is highly imbalanced (62.8%)Imbalance
전화번호 has 98 (36.7%) missing valuesMissing
도로명주소 has 3 (1.1%) missing valuesMissing
위도 has 3 (1.1%) missing valuesMissing
경도 has 3 (1.1%) missing valuesMissing
건축물연면적 has 130 (48.7%) missing valuesMissing
연번 has unique valuesUnique
건축물연면적 has 55 (20.6%) zerosZeros

Reproduction

Analysis started2024-03-14 14:40:05.736778
Analysis finished2024-03-14 14:40:12.065599
Duration6.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct267
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134
Minimum1
Maximum267
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-14T23:40:12.293761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.3
Q167.5
median134
Q3200.5
95-th percentile253.7
Maximum267
Range266
Interquartile range (IQR)133

Descriptive statistics

Standard deviation77.220464
Coefficient of variation (CV)0.57627212
Kurtosis-1.2
Mean134
Median Absolute Deviation (MAD)67
Skewness0
Sum35778
Variance5963
MonotonicityStrictly increasing
2024-03-14T23:40:12.747112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
185 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
174 1
 
0.4%
175 1
 
0.4%
176 1
 
0.4%
177 1
 
0.4%
178 1
 
0.4%
Other values (257) 257
96.3%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
267 1
0.4%
266 1
0.4%
265 1
0.4%
264 1
0.4%
263 1
0.4%
262 1
0.4%
261 1
0.4%
260 1
0.4%
259 1
0.4%
258 1
0.4%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
체육도장업
267 

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 267
100.0%

Length

2024-03-14T23:40:13.157223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:40:13.450102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체육도장업 267
100.0%

구분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
태권도
186 
권투
25 
검도
21 
유도
 
15
합기도
 
12
Other values (2)
 
8

Length

Max length4
Median length3
Mean length2.7640449
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
태권도 186
69.7%
권투 25
 
9.4%
검도 21
 
7.9%
유도 15
 
5.6%
합기도 12
 
4.5%
우슈 5
 
1.9%
<NA> 3
 
1.1%

Length

2024-03-14T23:40:13.807270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:40:14.164545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
태권도 186
69.7%
권투 25
 
9.4%
검도 21
 
7.9%
유도 15
 
5.6%
합기도 12
 
4.5%
우슈 5
 
1.9%
na 3
 
1.1%

사업장명
Text

Distinct258
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-03-14T23:40:15.219424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length8.4681648
Min length3

Characters and Unicode

Total characters2261
Distinct characters257
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)93.6%

Sample

1st row관우검도관
2nd row메리트 검도관
3rd row명지 검도관
4th row무궁화검도관
5th row미르검도관
ValueCountFrequency (%)
태권도 50
 
10.4%
태권도장 20
 
4.1%
경희대 18
 
3.7%
용인대 13
 
2.7%
국가대표 11
 
2.3%
체육관 8
 
1.7%
검도관 6
 
1.2%
박사 6
 
1.2%
합기도 6
 
1.2%
복싱 6
 
1.2%
Other values (293) 339
70.2%
2024-03-14T23:40:16.775744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
216
 
9.6%
도 214
 
9.5%
태 173
 
7.7%
권 167
 
7.4%
관 101
 
4.5%
대 77
 
3.4%
육 57
 
2.5%
체 48
 
2.1%
장 38
 
1.7%
경 33
 
1.5%
Other values (247) 1137
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1939
85.8%
Space Separator 216
 
9.6%
Uppercase Letter 59
 
2.6%
Lowercase Letter 21
 
0.9%
Close Punctuation 8
 
0.4%
Dash Punctuation 7
 
0.3%
Open Punctuation 7
 
0.3%
Decimal Number 2
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 214
 
11.0%
태 173
 
8.9%
권 167
 
8.6%
관 101
 
5.2%
대 77
 
4.0%
육 57
 
2.9%
체 48
 
2.5%
장 38
 
2.0%
경 33
 
1.7%
인 30
 
1.5%
Other values (210) 1001
51.6%
Uppercase Letter
ValueCountFrequency (%)
T 9
15.3%
M 6
 
10.2%
J 5
 
8.5%
I 5
 
8.5%
S 4
 
6.8%
K 4
 
6.8%
P 3
 
5.1%
A 3
 
5.1%
B 3
 
5.1%
E 2
 
3.4%
Other values (12) 15
25.4%
Lowercase Letter
ValueCountFrequency (%)
s 5
23.8%
t 4
19.0%
r 3
14.3%
e 3
14.3%
a 2
 
9.5%
i 2
 
9.5%
o 1
 
4.8%
m 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
· 1
50.0%
& 1
50.0%
Space Separator
ValueCountFrequency (%)
216
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1939
85.8%
Common 242
 
10.7%
Latin 80
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 214
 
11.0%
태 173
 
8.9%
권 167
 
8.6%
관 101
 
5.2%
대 77
 
4.0%
육 57
 
2.9%
체 48
 
2.5%
장 38
 
2.0%
경 33
 
1.7%
인 30
 
1.5%
Other values (210) 1001
51.6%
Latin
ValueCountFrequency (%)
T 9
 
11.2%
M 6
 
7.5%
J 5
 
6.2%
I 5
 
6.2%
s 5
 
6.2%
S 4
 
5.0%
t 4
 
5.0%
K 4
 
5.0%
r 3
 
3.8%
e 3
 
3.8%
Other values (20) 32
40.0%
Common
ValueCountFrequency (%)
216
89.3%
) 8
 
3.3%
- 7
 
2.9%
( 7
 
2.9%
1 2
 
0.8%
· 1
 
0.4%
& 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1939
85.8%
ASCII 321
 
14.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
216
67.3%
T 9
 
2.8%
) 8
 
2.5%
- 7
 
2.2%
( 7
 
2.2%
M 6
 
1.9%
J 5
 
1.6%
I 5
 
1.6%
s 5
 
1.6%
S 4
 
1.2%
Other values (26) 49
 
15.3%
Hangul
ValueCountFrequency (%)
도 214
 
11.0%
태 173
 
8.9%
권 167
 
8.6%
관 101
 
5.2%
대 77
 
4.0%
육 57
 
2.9%
체 48
 
2.5%
장 38
 
2.0%
경 33
 
1.7%
인 30
 
1.5%
Other values (210) 1001
51.6%
None
ValueCountFrequency (%)
· 1
100.0%

인허가일자
Date

Distinct261
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum1989-12-19 00:00:00
Maximum2023-01-02 00:00:00
2024-03-14T23:40:17.191804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:17.635005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct166
Distinct (%)98.2%
Missing98
Missing (%)36.7%
Memory size2.2 KiB
2024-03-14T23:40:18.540276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2028
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

Unique164 ?
Unique (%)97.0%

Sample

1st row063-252-3332
2nd row063-274-0090
3rd row063-247-2727
4th row063-212-5690
5th row063-212-4111
ValueCountFrequency (%)
063-245-1795 3
 
1.8%
063-214-7330 2
 
1.2%
063-237-1881 1
 
0.6%
063-285-4636 1
 
0.6%
063-252-3332 1
 
0.6%
063-271-6674 1
 
0.6%
063-236-7714 1
 
0.6%
063-211-6883 1
 
0.6%
063-222-7206 1
 
0.6%
063-275-7755 1
 
0.6%
Other values (156) 156
92.3%
2024-03-14T23:40:19.825960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 338
16.7%
2 303
14.9%
3 258
12.7%
0 254
12.5%
6 251
12.4%
5 145
7.1%
7 118
 
5.8%
4 102
 
5.0%
1 101
 
5.0%
8 97
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1690
83.3%
Dash Punctuation 338
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 303
17.9%
3 258
15.3%
0 254
15.0%
6 251
14.9%
5 145
8.6%
7 118
 
7.0%
4 102
 
6.0%
1 101
 
6.0%
8 97
 
5.7%
9 61
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 338
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2028
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 338
16.7%
2 303
14.9%
3 258
12.7%
0 254
12.5%
6 251
12.4%
5 145
7.1%
7 118
 
5.8%
4 102
 
5.0%
1 101
 
5.0%
8 97
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2028
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 338
16.7%
2 303
14.9%
3 258
12.7%
0 254
12.5%
6 251
12.4%
5 145
7.1%
7 118
 
5.8%
4 102
 
5.0%
1 101
 
5.0%
8 97
 
4.8%

도로명주소
Text

MISSING 

Distinct248
Distinct (%)93.9%
Missing3
Missing (%)1.1%
Memory size2.2 KiB
2024-03-14T23:40:21.409292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length23.458333
Min length21

Characters and Unicode

Total characters6193
Distinct characters151
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

Unique232 ?
Unique (%)87.9%

Sample

1st row전북특별자치도 전주시 덕진구 솔내8길 41
2nd row전북특별자치도 전주시 완산구 효천중앙로 55
3rd row전북특별자치도 전주시 덕진구 송천중앙로 122
4th row전북특별자치도 전주시 덕진구 동부대로 815
5th row전북특별자치도 전주시 덕진구 만성중앙로 53-44
ValueCountFrequency (%)
전북특별자치도 264
20.0%
전주시 264
20.0%
덕진구 147
 
11.1%
완산구 117
 
8.9%
견훤로 12
 
0.9%
세병로 9
 
0.7%
솔내로 8
 
0.6%
쪽구름로 7
 
0.5%
무삼지로 7
 
0.5%
만성중앙로 7
 
0.5%
Other values (288) 478
36.2%
2024-03-14T23:40:23.419956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1056
17.1%
전 534
 
8.6%
구 272
 
4.4%
시 267
 
4.3%
북 266
 
4.3%
자 266
 
4.3%
주 264
 
4.3%
별 264
 
4.3%
특 264
 
4.3%
도 264
 
4.3%
Other values (141) 2476
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4366
70.5%
Space Separator 1056
 
17.1%
Decimal Number 730
 
11.8%
Dash Punctuation 41
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 534
 
12.2%
구 272
 
6.2%
시 267
 
6.1%
북 266
 
6.1%
자 266
 
6.1%
주 264
 
6.0%
별 264
 
6.0%
특 264
 
6.0%
도 264
 
6.0%
치 264
 
6.0%
Other values (129) 1441
33.0%
Decimal Number
ValueCountFrequency (%)
1 146
20.0%
2 102
14.0%
3 83
11.4%
4 81
11.1%
5 64
8.8%
6 57
 
7.8%
7 57
 
7.8%
0 54
 
7.4%
8 48
 
6.6%
9 38
 
5.2%
Space Separator
ValueCountFrequency (%)
1056
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4366
70.5%
Common 1827
29.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 534
 
12.2%
구 272
 
6.2%
시 267
 
6.1%
북 266
 
6.1%
자 266
 
6.1%
주 264
 
6.0%
별 264
 
6.0%
특 264
 
6.0%
도 264
 
6.0%
치 264
 
6.0%
Other values (129) 1441
33.0%
Common
ValueCountFrequency (%)
1056
57.8%
1 146
 
8.0%
2 102
 
5.6%
3 83
 
4.5%
4 81
 
4.4%
5 64
 
3.5%
6 57
 
3.1%
7 57
 
3.1%
0 54
 
3.0%
8 48
 
2.6%
Other values (2) 79
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4366
70.5%
ASCII 1827
29.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1056
57.8%
1 146
 
8.0%
2 102
 
5.6%
3 83
 
4.5%
4 81
 
4.4%
5 64
 
3.5%
6 57
 
3.1%
7 57
 
3.1%
0 54
 
3.0%
8 48
 
2.6%
Other values (2) 79
 
4.3%
Hangul
ValueCountFrequency (%)
전 534
 
12.2%
구 272
 
6.2%
시 267
 
6.1%
북 266
 
6.1%
자 266
 
6.1%
주 264
 
6.0%
별 264
 
6.0%
특 264
 
6.0%
도 264
 
6.0%
치 264
 
6.0%
Other values (129) 1441
33.0%

지번주소
Text

Distinct248
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-03-14T23:40:24.989991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length26.771536
Min length23

Characters and Unicode

Total characters7148
Distinct characters62
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique229 ?
Unique (%)85.8%

Sample

1st row전북특별자치도 전주시 덕진구 송천동1가 137-69
2nd row전북특별자치도 전주시 완산구 효자동2가 1377-2
3rd row전북특별자치도 전주시 덕진구 송천동1가 395-23
4th row전북특별자치도 전주시 덕진구 호성동1가 785-4
5th row전북특별자치도 전주시 덕진구 만성동 1372-5
ValueCountFrequency (%)
전북특별자치도 267
20.0%
전주시 267
20.0%
덕진구 149
 
11.1%
완산구 118
 
8.8%
인후동1가 28
 
2.1%
송천동1가 22
 
1.6%
송천동2가 22
 
1.6%
서신동 19
 
1.4%
효자동2가 18
 
1.3%
평화동2가 18
 
1.3%
Other values (274) 409
30.6%
2024-03-14T23:40:26.931748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1074
 
15.0%
전 534
 
7.5%
자 306
 
4.3%
1 296
 
4.1%
동 274
 
3.8%
북 272
 
3.8%
주 267
 
3.7%
시 267
 
3.7%
구 267
 
3.7%
도 267
 
3.7%
Other values (52) 3324
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4481
62.7%
Decimal Number 1350
 
18.9%
Space Separator 1074
 
15.0%
Dash Punctuation 235
 
3.3%
Uppercase Letter 5
 
0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 534
 
11.9%
자 306
 
6.8%
동 274
 
6.1%
북 272
 
6.1%
주 267
 
6.0%
시 267
 
6.0%
구 267
 
6.0%
도 267
 
6.0%
치 267
 
6.0%
별 267
 
6.0%
Other values (34) 1493
33.3%
Decimal Number
ValueCountFrequency (%)
1 296
21.9%
2 198
14.7%
3 166
12.3%
7 124
9.2%
6 106
 
7.9%
4 104
 
7.7%
5 102
 
7.6%
9 97
 
7.2%
8 90
 
6.7%
0 67
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
20.0%
X 1
20.0%
E 1
20.0%
P 1
20.0%
M 1
20.0%
Space Separator
ValueCountFrequency (%)
1074
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 235
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4481
62.7%
Common 2662
37.2%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 534
 
11.9%
자 306
 
6.8%
동 274
 
6.1%
북 272
 
6.1%
주 267
 
6.0%
시 267
 
6.0%
구 267
 
6.0%
도 267
 
6.0%
치 267
 
6.0%
별 267
 
6.0%
Other values (34) 1493
33.3%
Common
ValueCountFrequency (%)
1074
40.3%
1 296
 
11.1%
- 235
 
8.8%
2 198
 
7.4%
3 166
 
6.2%
7 124
 
4.7%
6 106
 
4.0%
4 104
 
3.9%
5 102
 
3.8%
9 97
 
3.6%
Other values (3) 160
 
6.0%
Latin
ValueCountFrequency (%)
L 1
20.0%
X 1
20.0%
E 1
20.0%
P 1
20.0%
M 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4481
62.7%
ASCII 2667
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1074
40.3%
1 296
 
11.1%
- 235
 
8.8%
2 198
 
7.4%
3 166
 
6.2%
7 124
 
4.6%
6 106
 
4.0%
4 104
 
3.9%
5 102
 
3.8%
9 97
 
3.6%
Other values (8) 165
 
6.2%
Hangul
ValueCountFrequency (%)
전 534
 
11.9%
자 306
 
6.8%
동 274
 
6.1%
북 272
 
6.1%
주 267
 
6.0%
시 267
 
6.0%
구 267
 
6.0%
도 267
 
6.0%
치 267
 
6.0%
별 267
 
6.0%
Other values (34) 1493
33.3%

위도
Real number (ℝ)

MISSING 

Distinct248
Distinct (%)93.9%
Missing3
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean35.832488
Minimum35.783338
Maximum35.880262
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-14T23:40:27.359309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.783338
5-th percentile35.787502
Q135.809549
median35.834107
Q335.855249
95-th percentile35.873173
Maximum35.880262
Range0.09692427
Interquartile range (IQR)0.045699872

Descriptive statistics

Standard deviation0.026070238
Coefficient of variation (CV)0.00072755869
Kurtosis-1.0029172
Mean35.832488
Median Absolute Deviation (MAD)0.023451075
Skewness-0.11335287
Sum9459.7769
Variance0.00067965731
MonotonicityNot monotonic
2024-03-14T23:40:27.819895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.80810941 2
 
0.7%
35.83650143 2
 
0.7%
35.84133398 2
 
0.7%
35.85524854 2
 
0.7%
35.80943202 2
 
0.7%
35.786848 2
 
0.7%
35.82806715 2
 
0.7%
35.83509832 2
 
0.7%
35.83810492 2
 
0.7%
35.85446747 2
 
0.7%
Other values (238) 244
91.4%
(Missing) 3
 
1.1%
ValueCountFrequency (%)
35.7833377 1
0.4%
35.78505813 1
0.4%
35.78510176 1
0.4%
35.78609668 1
0.4%
35.78647996 1
0.4%
35.78672811 1
0.4%
35.786848 2
0.7%
35.78691455 1
0.4%
35.78710423 2
0.7%
35.78712968 1
0.4%
ValueCountFrequency (%)
35.88026197 1
0.4%
35.87937883 1
0.4%
35.87903812 1
0.4%
35.87579274 1
0.4%
35.87454355 1
0.4%
35.87424642 1
0.4%
35.87420701 1
0.4%
35.87416504 1
0.4%
35.87380458 1
0.4%
35.8735992 1
0.4%

경도
Real number (ℝ)

MISSING 

Distinct248
Distinct (%)93.9%
Missing3
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean127.12274
Minimum127.05776
Maximum127.16843
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-14T23:40:28.242025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.05776
5-th percentile127.07174
Q1127.1098
median127.12466
Q3127.13703
95-th percentile127.16477
Maximum127.16843
Range0.1106624
Interquartile range (IQR)0.027226

Descriptive statistics

Standard deviation0.026679038
Coefficient of variation (CV)0.00020986834
Kurtosis-0.038444443
Mean127.12274
Median Absolute Deviation (MAD)0.0135412
Skewness-0.44599501
Sum33560.403
Variance0.00071177107
MonotonicityNot monotonic
2024-03-14T23:40:28.681399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1036346 2
 
0.7%
127.1119882 2
 
0.7%
127.1408488 2
 
0.7%
127.1556216 2
 
0.7%
127.108927 2
 
0.7%
127.132917 2
 
0.7%
127.1647749 2
 
0.7%
127.1161025 2
 
0.7%
127.0609008 2
 
0.7%
127.155094 2
 
0.7%
Other values (238) 244
91.4%
(Missing) 3
 
1.1%
ValueCountFrequency (%)
127.0577638 1
0.4%
127.0587417 1
0.4%
127.0593368 1
0.4%
127.059978 1
0.4%
127.0605586 1
0.4%
127.0608582 1
0.4%
127.0609008 2
0.7%
127.06129 1
0.4%
127.0612927 1
0.4%
127.0618363 1
0.4%
ValueCountFrequency (%)
127.1684262 1
0.4%
127.1682883 1
0.4%
127.1679703 1
0.4%
127.1679419 1
0.4%
127.1679298 1
0.4%
127.167857 1
0.4%
127.1677904 1
0.4%
127.1675484 1
0.4%
127.1673486 1
0.4%
127.1670986 1
0.4%

지도자수
Categorical

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
1
167 
<NA>
71 
0
26 
2
 
3

Length

Max length4
Median length1
Mean length1.7977528
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 167
62.5%
<NA> 71
26.6%
0 26
 
9.7%
2 3
 
1.1%

Length

2024-03-14T23:40:29.106971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:40:29.447599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 167
62.5%
na 71
26.6%
0 26
 
9.7%
2 3
 
1.1%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct81
Distinct (%)59.1%
Missing130
Missing (%)48.7%
Infinite0
Infinite (%)0.0%
Mean706.63365
Minimum0
Maximum10607.74
Zeros55
Zeros (%)20.6%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-03-14T23:40:29.816392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median148.5
Q3925.86
95-th percentile3241.67
Maximum10607.74
Range10607.74
Interquartile range (IQR)925.86

Descriptive statistics

Standard deviation1293.9577
Coefficient of variation (CV)1.8311578
Kurtosis25.133554
Mean706.63365
Median Absolute Deviation (MAD)148.5
Skewness4.0758328
Sum96808.81
Variance1674326.6
MonotonicityNot monotonic
2024-03-14T23:40:30.250247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 55
20.6%
165.6 2
 
0.7%
148.5 2
 
0.7%
1034.34 1
 
0.4%
1525.63 1
 
0.4%
670.35 1
 
0.4%
1026.78 1
 
0.4%
531.86 1
 
0.4%
131.0 1
 
0.4%
930.0 1
 
0.4%
Other values (71) 71
26.6%
(Missing) 130
48.7%
ValueCountFrequency (%)
0.0 55
20.6%
72.6 1
 
0.4%
98.2 1
 
0.4%
109.44 1
 
0.4%
110.7 1
 
0.4%
115.5 1
 
0.4%
118.0 1
 
0.4%
123.0 1
 
0.4%
131.0 1
 
0.4%
140.0 1
 
0.4%
ValueCountFrequency (%)
10607.74 1
0.4%
4196.86 1
0.4%
4051.2 1
0.4%
3829.36 1
0.4%
3529.29 1
0.4%
3429.38 1
0.4%
3366.23 1
0.4%
3210.53 1
0.4%
2932.4 1
0.4%
2747.04 1
0.4%

회원모집총인원
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
200 
0
61 
50
 
3
80
 
1
30
 
1

Length

Max length4
Median length4
Mean length3.2696629
Min length1

Unique

Unique3 ?
Unique (%)1.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 200
74.9%
0 61
 
22.8%
50 3
 
1.1%
80 1
 
0.4%
30 1
 
0.4%
20 1
 
0.4%

Length

2024-03-14T23:40:30.676102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:40:31.013490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 200
74.9%
0 61
 
22.8%
50 3
 
1.1%
80 1
 
0.4%
30 1
 
0.4%
20 1
 
0.4%

Interactions

2024-03-14T23:40:09.562763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:06.600262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:07.576164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:08.571427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:09.804148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:06.840125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:07.829723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:08.821748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:10.047399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:07.087118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:08.080192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:09.072022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:10.297308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:07.333093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:08.329952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:40:09.320963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:40:31.239225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분위도경도지도자수건축물연면적회원모집총인원
연번1.0000.8570.3410.0000.0000.0000.000
구분0.8571.0000.0000.0000.0580.0000.286
위도0.3410.0001.0000.8030.0000.0000.000
경도0.0000.0000.8031.0000.0000.2270.000
지도자수0.0000.0580.0000.0001.0000.2320.044
건축물연면적0.0000.0000.0000.2270.2321.0000.000
회원모집총인원0.0000.2860.0000.0000.0440.0001.000
2024-03-14T23:40:31.516425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분회원모집총인원지도자수
구분1.0000.1050.021
회원모집총인원0.1051.0000.042
지도자수0.0210.0421.000
2024-03-14T23:40:31.778810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도건축물연면적구분지도자수회원모집총인원
연번1.0000.0100.104-0.0400.6700.0000.000
위도0.0101.000-0.0110.1200.0000.0000.000
경도0.104-0.0111.0000.0200.0000.0000.000
건축물연면적-0.0400.1200.0201.0000.0000.1760.000
구분0.6700.0000.0000.0001.0000.0210.105
지도자수0.0000.0000.0000.1760.0211.0000.042
회원모집총인원0.0000.0000.0000.0000.1050.0421.000

Missing values

2024-03-14T23:40:10.660540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:40:11.221810image/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.
2024-03-14T23:40:11.827887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번업종구분사업장명인허가일자전화번호도로명주소지번주소위도경도지도자수건축물연면적회원모집총인원
01체육도장업검도관우검도관2005-01-07063-252-3332전북특별자치도 전주시 덕진구 솔내8길 41전북특별자치도 전주시 덕진구 송천동1가 137-6935.861017127.1259452368.88<NA>
12체육도장업검도메리트 검도관2021-04-05<NA>전북특별자치도 전주시 완산구 효천중앙로 55전북특별자치도 전주시 완산구 효자동2가 1377-235.798957127.10787613829.36<NA>
23체육도장업검도명지 검도관2007-08-17063-274-0090전북특별자치도 전주시 덕진구 송천중앙로 122전북특별자치도 전주시 덕진구 송천동1가 395-2335.857722127.1210551<NA><NA>
34체육도장업검도무궁화검도관2004-09-24063-247-2727전북특별자치도 전주시 덕진구 동부대로 815전북특별자치도 전주시 덕진구 호성동1가 785-435.859905127.1534141804.46<NA>
45체육도장업검도미르검도관2020-09-17063-212-5690전북특별자치도 전주시 덕진구 만성중앙로 53-44전북특별자치도 전주시 덕진구 만성동 1372-535.843073127.078041<NA><NA>
56체육도장업검도봉영검도관2004-07-20063-212-4111전북특별자치도 전주시 덕진구 반월5길 4전북특별자치도 전주시 덕진구 반월동 388-535.873805127.0702441<NA><NA>
67체육도장업검도삼정검도관2003-09-17063-247-1199전북특별자치도 전주시 덕진구 아중로 173전북특별자치도 전주시 덕진구 인후동1가 920-535.827101127.1682881<NA><NA>
78체육도장업검도세심검도관2007-04-19<NA>전북특별자치도 전주시 완산구 유연로 284전북특별자치도 전주시 완산구 중화산동2가 744-335.825151127.11648510.00
89체육도장업검도숭의검도관1995-12-18063-224-8111전북특별자치도 전주시 덕진구 소리로 203전북특별자치도 전주시 덕진구 호성동1가 792-235.859111127.153732<NA>143.6<NA>
910체육도장업검도에이스검도관2016-02-26063-277-5080전북특별자치도 전주시 완산구 평화로 115전북특별자치도 전주시 완산구 평화동2가 184-3135.787104127.134378<NA><NA><NA>
연번업종구분사업장명인허가일자전화번호도로명주소지번주소위도경도지도자수건축물연면적회원모집총인원
257258체육도장업합기도용인대백제합기도무술관2021-05-21063-273-0860전북특별자치도 전주시 덕진구 시천로 42전북특별자치도 전주시 덕진구 송천동1가 834-335.863102127.114787<NA><NA><NA>
258259체육도장업합기도청룡 합기도 총본관2021-02-01063-278-5343전북특별자치도 전주시 덕진구 세병로 30전북특별자치도 전주시 덕진구 송천동2가 1326-935.873599127.12800300.00
259260체육도장업합기도청룡아중합기도체육관2020-11-19063-241-5446전북특별자치도 전주시 덕진구 무삼지로 27전북특별자치도 전주시 덕진구 인후동1가 904-235.828067127.1647751<NA><NA>
260261체육도장업합기도투혼 정심관2020-01-07<NA>전북특별자치도 전주시 완산구 모악로 4692전북특별자치도 전주시 완산구 평화동2가 302-335.788308127.13093100.00
261262체육도장업합기도팀 자이언트 효자삼천점2020-09-29063-223-9777전북특별자치도 전주시 완산구 성지산로 60전북특별자치도 전주시 완산구 삼천동1가 58535.801907127.12396311550.0<NA>
262263체육도장업합기도혁신도장2020-03-18<NA>전북특별자치도 전주시 덕진구 기지로 82전북특별자치도 전주시 덕진구 중동 775-235.838105127.060901<NA><NA><NA>
263264체육도장업합기도호성청룡합기도2021-04-20063-245-5343전북특별자치도 전주시 덕진구 견훤로 489전북특별자치도 전주시 덕진구 우아동3가 602-4335.854286127.15498<NA><NA><NA>
264265체육도장업<NA>신양테마파크2004-05-12063-222-0029전북특별자치도 전주시 완산구 용리로 20전북특별자치도 전주시 완산구 삼천동1가 284-835.798355127.112013<NA><NA><NA>
265266체육도장업<NA>언약체육관2001-09-18063-246-1118<NA>전북특별자치도 전주시 덕진구 우아동3가 1102-6,<NA><NA><NA>178.5<NA>
266267체육도장업<NA>영웅체육관2002-09-27063-253-3607<NA>전북특별자치도 전주시 덕진구 송천동1가 472-4,<NA><NA><NA>115.5<NA>