Overview

Dataset statistics

Number of variables12
Number of observations153
Missing cells126
Missing cells (%)6.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.4 KiB
Average record size in memory102.8 B

Variable types

Numeric4
Categorical3
Text4
DateTime1

Dataset

Description전북특별자치도 전주시의 골프연습장업을 제공하며 업종, 사업자명, 인허가일자, 전화번호, 주소 등을 제공합니다.골프연습장업 : 골프를 연습하기 위해 실내 또는 실외에 시설을 갖추어 제공하는 업소항목 : 연번, 업종, 사업자명, 인허가일자, 전화번호, 도로명주소, 지번주소, 위도, 경도, 지도자수, 건축물연면적 등제공부서 : 체육산업과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15112490/fileData.do

Alerts

업종 has constant value ""Constant
위도 is highly overall correlated with 회원모집총인원High correlation
경도 is highly overall correlated with 지도자수High correlation
건축물연면적 is highly overall correlated with 지도자수 and 1 other fieldsHigh correlation
지도자수 is highly overall correlated with 경도 and 2 other fieldsHigh correlation
회원모집총인원 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
회원모집총인원 is highly imbalanced (64.6%)Imbalance
전화번호 has 43 (28.1%) missing valuesMissing
건축물연면적 has 83 (54.2%) missing valuesMissing
연번 has unique valuesUnique
건축물연면적 has 19 (12.4%) zerosZeros

Reproduction

Analysis started2024-03-14 09:56:44.780511
Analysis finished2024-03-14 09:56:49.583677
Duration4.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77
Minimum1
Maximum153
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-14T18:56:49.710120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.6
Q139
median77
Q3115
95-th percentile145.4
Maximum153
Range152
Interquartile range (IQR)76

Descriptive statistics

Standard deviation44.311398
Coefficient of variation (CV)0.5754727
Kurtosis-1.2
Mean77
Median Absolute Deviation (MAD)38
Skewness0
Sum11781
Variance1963.5
MonotonicityStrictly increasing
2024-03-14T18:56:49.993642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
106 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
105 1
 
0.7%
107 1
 
0.7%
Other values (143) 143
93.5%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
153 1
0.7%
152 1
0.7%
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
골프연습장업
153 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
골프연습장업 153
100.0%

Length

2024-03-14T18:56:50.298339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:56:50.466221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
골프연습장업 153
100.0%

사업장명
Text

Distinct152
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T18:56:51.137450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length16
Mean length9.2679739
Min length3

Characters and Unicode

Total characters1418
Distinct characters199
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

Unique151 ?
Unique (%)98.7%

Sample

1st row(주)서일개발 스포디움 지점(스크린골프장)
2nd rowabc골프
3rd rowEG 스크린골프
4th rowGDR 골프존 아카데미 전주점
5th rowGDR아카데미(온스윙)
ValueCountFrequency (%)
골프연습장 19
 
6.9%
스크린골프 18
 
6.5%
스크린 10
 
3.6%
골프 9
 
3.3%
골프존 9
 
3.3%
골프아카데미 6
 
2.2%
스크린골프존 5
 
1.8%
골프클럽 5
 
1.8%
실내골프연습장 5
 
1.8%
아카데미 3
 
1.1%
Other values (175) 187
67.8%
2024-03-14T18:56:52.363890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
프 154
 
10.9%
골 152
 
10.7%
123
 
8.7%
스 84
 
5.9%
크 69
 
4.9%
린 64
 
4.5%
장 44
 
3.1%
습 41
 
2.9%
연 41
 
2.9%
아 26
 
1.8%
Other values (189) 620
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1219
86.0%
Space Separator 123
 
8.7%
Uppercase Letter 51
 
3.6%
Close Punctuation 8
 
0.6%
Open Punctuation 7
 
0.5%
Lowercase Letter 5
 
0.4%
Other Punctuation 3
 
0.2%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
프 154
 
12.6%
골 152
 
12.5%
스 84
 
6.9%
크 69
 
5.7%
린 64
 
5.3%
장 44
 
3.6%
습 41
 
3.4%
연 41
 
3.4%
아 26
 
2.1%
카 26
 
2.1%
Other values (161) 518
42.5%
Uppercase Letter
ValueCountFrequency (%)
G 13
25.5%
R 9
17.6%
D 8
15.7%
S 5
 
9.8%
J 2
 
3.9%
A 2
 
3.9%
P 2
 
3.9%
Y 2
 
3.9%
K 1
 
2.0%
O 1
 
2.0%
Other values (6) 6
11.8%
Lowercase Letter
ValueCountFrequency (%)
o 1
20.0%
y 1
20.0%
c 1
20.0%
b 1
20.0%
a 1
20.0%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
. 1
33.3%
Decimal Number
ValueCountFrequency (%)
9 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
123
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1219
86.0%
Common 143
 
10.1%
Latin 56
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
프 154
 
12.6%
골 152
 
12.5%
스 84
 
6.9%
크 69
 
5.7%
린 64
 
5.3%
장 44
 
3.6%
습 41
 
3.4%
연 41
 
3.4%
아 26
 
2.1%
카 26
 
2.1%
Other values (161) 518
42.5%
Latin
ValueCountFrequency (%)
G 13
23.2%
R 9
16.1%
D 8
14.3%
S 5
 
8.9%
J 2
 
3.6%
A 2
 
3.6%
P 2
 
3.6%
Y 2
 
3.6%
K 1
 
1.8%
O 1
 
1.8%
Other values (11) 11
19.6%
Common
ValueCountFrequency (%)
123
86.0%
) 8
 
5.6%
( 7
 
4.9%
& 2
 
1.4%
9 1
 
0.7%
. 1
 
0.7%
2 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1219
86.0%
ASCII 199
 
14.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
프 154
 
12.6%
골 152
 
12.5%
스 84
 
6.9%
크 69
 
5.7%
린 64
 
5.3%
장 44
 
3.6%
습 41
 
3.4%
연 41
 
3.4%
아 26
 
2.1%
카 26
 
2.1%
Other values (161) 518
42.5%
ASCII
ValueCountFrequency (%)
123
61.8%
G 13
 
6.5%
R 9
 
4.5%
) 8
 
4.0%
D 8
 
4.0%
( 7
 
3.5%
S 5
 
2.5%
J 2
 
1.0%
A 2
 
1.0%
P 2
 
1.0%
Other values (18) 20
 
10.1%

인허가일자
Date

Distinct148
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1996-05-23 00:00:00
Maximum2021-09-06 00:00:00
2024-03-14T18:56:52.776139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:53.231216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct109
Distinct (%)99.1%
Missing43
Missing (%)28.1%
Memory size1.3 KiB
2024-03-14T18:56:54.166685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.972727
Min length9

Characters and Unicode

Total characters1317
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

Unique108 ?
Unique (%)98.2%

Sample

1st row063-224-2128
2nd row063-252-4653
3rd row063-271-7577
4th row063-244-2324
5th row063-223-0066
ValueCountFrequency (%)
063-225-2036 2
 
1.8%
063-223-3443 1
 
0.9%
063-224-2128 1
 
0.9%
063-222-0754 1
 
0.9%
063-222-1836 1
 
0.9%
063-221-0315 1
 
0.9%
063-242-0889 1
 
0.9%
063-247-0452 1
 
0.9%
063-276-0808 1
 
0.9%
063-287-0770 1
 
0.9%
Other values (99) 99
90.0%
2024-03-14T18:56:55.500817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 219
16.6%
0 218
16.6%
2 212
16.1%
3 170
12.9%
6 148
11.2%
7 74
 
5.6%
4 71
 
5.4%
8 64
 
4.9%
1 59
 
4.5%
5 48
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1098
83.4%
Dash Punctuation 219
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 218
19.9%
2 212
19.3%
3 170
15.5%
6 148
13.5%
7 74
 
6.7%
4 71
 
6.5%
8 64
 
5.8%
1 59
 
5.4%
5 48
 
4.4%
9 34
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 219
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1317
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 219
16.6%
0 218
16.6%
2 212
16.1%
3 170
12.9%
6 148
11.2%
7 74
 
5.6%
4 71
 
5.4%
8 64
 
4.9%
1 59
 
4.5%
5 48
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1317
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 219
16.6%
0 218
16.6%
2 212
16.1%
3 170
12.9%
6 148
11.2%
7 74
 
5.6%
4 71
 
5.4%
8 64
 
4.9%
1 59
 
4.5%
5 48
 
3.6%

도로명주소
Text

Distinct147
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T18:56:57.010780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length41
Mean length23.96732
Min length21

Characters and Unicode

Total characters3667
Distinct characters140
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

Unique141 ?
Unique (%)92.2%

Sample

1st row전북특별자치도 전주시 덕진구 기지로 66
2nd row전북특별자치도 전주시 덕진구 송천중앙로 241
3rd row전북특별자치도 전주시 완산구 백제대로 277
4th row전북특별자치도 전주시 완산구 효자로 266
5th row전북특별자치도 전주시 완산구 바우배기2길 11
ValueCountFrequency (%)
전북특별자치도 153
19.8%
전주시 153
19.8%
완산구 80
 
10.4%
덕진구 73
 
9.5%
효자로 8
 
1.0%
동부대로 7
 
0.9%
백제대로 6
 
0.8%
20 5
 
0.6%
11 5
 
0.6%
쑥고개로 5
 
0.6%
Other values (211) 276
35.8%
2024-03-14T18:56:58.664937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
618
16.9%
전 322
 
8.8%
자 162
 
4.4%
북 156
 
4.3%
주 156
 
4.3%
시 156
 
4.3%
구 154
 
4.2%
도 153
 
4.2%
치 153
 
4.2%
별 153
 
4.2%
Other values (130) 1484
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2566
70.0%
Space Separator 618
 
16.9%
Decimal Number 450
 
12.3%
Dash Punctuation 26
 
0.7%
Other Punctuation 3
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 322
 
12.5%
자 162
 
6.3%
북 156
 
6.1%
주 156
 
6.1%
시 156
 
6.1%
구 154
 
6.0%
도 153
 
6.0%
치 153
 
6.0%
별 153
 
6.0%
특 153
 
6.0%
Other values (115) 848
33.0%
Decimal Number
ValueCountFrequency (%)
1 96
21.3%
2 67
14.9%
6 46
10.2%
4 42
9.3%
3 41
9.1%
7 34
 
7.6%
0 33
 
7.3%
5 32
 
7.1%
9 31
 
6.9%
8 28
 
6.2%
Space Separator
ValueCountFrequency (%)
618
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2566
70.0%
Common 1101
30.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 322
 
12.5%
자 162
 
6.3%
북 156
 
6.1%
주 156
 
6.1%
시 156
 
6.1%
구 154
 
6.0%
도 153
 
6.0%
치 153
 
6.0%
별 153
 
6.0%
특 153
 
6.0%
Other values (115) 848
33.0%
Common
ValueCountFrequency (%)
618
56.1%
1 96
 
8.7%
2 67
 
6.1%
6 46
 
4.2%
4 42
 
3.8%
3 41
 
3.7%
7 34
 
3.1%
0 33
 
3.0%
5 32
 
2.9%
9 31
 
2.8%
Other values (5) 61
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2566
70.0%
ASCII 1101
30.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
618
56.1%
1 96
 
8.7%
2 67
 
6.1%
6 46
 
4.2%
4 42
 
3.8%
3 41
 
3.7%
7 34
 
3.1%
0 33
 
3.0%
5 32
 
2.9%
9 31
 
2.8%
Other values (5) 61
 
5.5%
Hangul
ValueCountFrequency (%)
전 322
 
12.5%
자 162
 
6.3%
북 156
 
6.1%
주 156
 
6.1%
시 156
 
6.1%
구 154
 
6.0%
도 153
 
6.0%
치 153
 
6.0%
별 153
 
6.0%
특 153
 
6.0%
Other values (115) 848
33.0%

지번주소
Text

Distinct147
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-14T18:57:00.071305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length32
Mean length27
Min length23

Characters and Unicode

Total characters4131
Distinct characters67
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

Unique141 ?
Unique (%)92.2%

Sample

1st row전북특별자치도 전주시 덕진구 중동 774-4
2nd row전북특별자치도 전주시 덕진구 송천동2가 492-51
3rd row전북특별자치도 전주시 완산구 중화산동2가 595-9
4th row전북특별자치도 전주시 완산구 중화산동2가 485-44
5th row전북특별자치도 전주시 완산구 효자동2가 1234-2
ValueCountFrequency (%)
전북특별자치도 153
19.9%
전주시 153
19.9%
완산구 80
 
10.4%
덕진구 73
 
9.5%
효자동2가 16
 
2.1%
효자동3가 13
 
1.7%
인후동1가 12
 
1.6%
중화산동2가 10
 
1.3%
송천동2가 9
 
1.2%
평화동2가 9
 
1.2%
Other values (176) 241
31.3%
2024-03-14T18:57:01.940003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
620
 
15.0%
전 307
 
7.4%
자 188
 
4.6%
1 172
 
4.2%
북 154
 
3.7%
동 153
 
3.7%
특 153
 
3.7%
별 153
 
3.7%
치 153
 
3.7%
도 153
 
3.7%
Other values (57) 1925
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2591
62.7%
Decimal Number 786
 
19.0%
Space Separator 620
 
15.0%
Dash Punctuation 134
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 307
 
11.8%
자 188
 
7.3%
북 154
 
5.9%
동 153
 
5.9%
특 153
 
5.9%
별 153
 
5.9%
치 153
 
5.9%
도 153
 
5.9%
주 153
 
5.9%
시 153
 
5.9%
Other values (45) 871
33.6%
Decimal Number
ValueCountFrequency (%)
1 172
21.9%
2 139
17.7%
3 87
11.1%
4 69
8.8%
5 66
 
8.4%
6 66
 
8.4%
7 60
 
7.6%
8 55
 
7.0%
9 42
 
5.3%
0 30
 
3.8%
Space Separator
ValueCountFrequency (%)
620
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2591
62.7%
Common 1540
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 307
 
11.8%
자 188
 
7.3%
북 154
 
5.9%
동 153
 
5.9%
특 153
 
5.9%
별 153
 
5.9%
치 153
 
5.9%
도 153
 
5.9%
주 153
 
5.9%
시 153
 
5.9%
Other values (45) 871
33.6%
Common
ValueCountFrequency (%)
620
40.3%
1 172
 
11.2%
2 139
 
9.0%
- 134
 
8.7%
3 87
 
5.6%
4 69
 
4.5%
5 66
 
4.3%
6 66
 
4.3%
7 60
 
3.9%
8 55
 
3.6%
Other values (2) 72
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2591
62.7%
ASCII 1540
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
620
40.3%
1 172
 
11.2%
2 139
 
9.0%
- 134
 
8.7%
3 87
 
5.6%
4 69
 
4.5%
5 66
 
4.3%
6 66
 
4.3%
7 60
 
3.9%
8 55
 
3.6%
Other values (2) 72
 
4.7%
Hangul
ValueCountFrequency (%)
전 307
 
11.8%
자 188
 
7.3%
북 154
 
5.9%
동 153
 
5.9%
특 153
 
5.9%
별 153
 
5.9%
치 153
 
5.9%
도 153
 
5.9%
주 153
 
5.9%
시 153
 
5.9%
Other values (45) 871
33.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct147
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.828509
Minimum35.779564
Maximum35.879082
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-14T18:57:02.373157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.779564
5-th percentile35.788268
Q135.814043
median35.826525
Q335.842146
95-th percentile35.868586
Maximum35.879082
Range0.0995179
Interquartile range (IQR)0.02810252

Descriptive statistics

Standard deviation0.024390105
Coefficient of variation (CV)0.00068074575
Kurtosis-0.74752456
Mean35.828509
Median Absolute Deviation (MAD)0.01481366
Skewness0.15239005
Sum5481.7619
Variance0.00059487723
MonotonicityNot monotonic
2024-03-14T18:57:02.833780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.80800187 2
 
1.3%
35.81868325 2
 
1.3%
35.80401821 2
 
1.3%
35.81791472 2
 
1.3%
35.86656728 2
 
1.3%
35.82532391 2
 
1.3%
35.81488365 1
 
0.7%
35.79031846 1
 
0.7%
35.80704603 1
 
0.7%
35.81941556 1
 
0.7%
Other values (137) 137
89.5%
ValueCountFrequency (%)
35.77956446 1
0.7%
35.78628138 1
0.7%
35.78654087 1
0.7%
35.78686647 1
0.7%
35.78705562 1
0.7%
35.78712968 1
0.7%
35.78715258 1
0.7%
35.78776436 1
0.7%
35.78860452 1
0.7%
35.79031846 1
0.7%
ValueCountFrequency (%)
35.87908236 1
0.7%
35.8755158 1
0.7%
35.8736442 1
0.7%
35.87296464 1
0.7%
35.87236539 1
0.7%
35.87183332 1
0.7%
35.86955396 1
0.7%
35.86878732 1
0.7%
35.86845183 1
0.7%
35.86822439 1
0.7%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct147
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12086
Minimum127.05892
Maximum127.17641
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-14T18:57:03.249642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.05892
5-th percentile127.0771
Q1127.10552
median127.11652
Q3127.13424
95-th percentile127.16943
Maximum127.17641
Range0.1174868
Interquartile range (IQR)0.0287255

Descriptive statistics

Standard deviation0.027238486
Coefficient of variation (CV)0.00021427235
Kurtosis-0.29347014
Mean127.12086
Median Absolute Deviation (MAD)0.0139581
Skewness0.15739753
Sum19449.492
Variance0.00074193511
MonotonicityNot monotonic
2024-03-14T18:57:03.709280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1055167 2
 
1.3%
127.1144876 2
 
1.3%
127.1076448 2
 
1.3%
127.1392797 2
 
1.3%
127.1336268 2
 
1.3%
127.1646999 2
 
1.3%
127.1055003 1
 
0.7%
127.1310636 1
 
0.7%
127.1181631 1
 
0.7%
127.1025662 1
 
0.7%
Other values (137) 137
89.5%
ValueCountFrequency (%)
127.0589215 1
0.7%
127.0590138 1
0.7%
127.0593368 1
0.7%
127.0692526 1
0.7%
127.0715313 1
0.7%
127.0727754 1
0.7%
127.0741728 1
0.7%
127.076001 1
0.7%
127.0778376 1
0.7%
127.0785536 1
0.7%
ValueCountFrequency (%)
127.1764083 1
0.7%
127.1750366 1
0.7%
127.1741959 1
0.7%
127.172888 1
0.7%
127.171822 1
0.7%
127.1716521 1
0.7%
127.1710954 1
0.7%
127.1695816 1
0.7%
127.1693314 1
0.7%
127.169048 1
0.7%

지도자수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
112 
0
25 
1
 
11
2
 
4
3
 
1

Length

Max length4
Median length4
Mean length3.1960784
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 112
73.2%
0 25
 
16.3%
1 11
 
7.2%
2 4
 
2.6%
3 1
 
0.7%

Length

2024-03-14T18:57:04.147984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:57:04.492659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 112
73.2%
0 25
 
16.3%
1 11
 
7.2%
2 4
 
2.6%
3 1
 
0.7%

건축물연면적
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct51
Distinct (%)72.9%
Missing83
Missing (%)54.2%
Infinite0
Infinite (%)0.0%
Mean1679.8673
Minimum0
Maximum8650.48
Zeros19
Zeros (%)12.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-14T18:57:04.868966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median882.54
Q32148.245
95-th percentile5355.253
Maximum8650.48
Range8650.48
Interquartile range (IQR)2148.245

Descriptive statistics

Standard deviation2052.0974
Coefficient of variation (CV)1.2215831
Kurtosis2.4865872
Mean1679.8673
Median Absolute Deviation (MAD)882.54
Skewness1.6403548
Sum117590.71
Variance4211103.9
MonotonicityNot monotonic
2024-03-14T18:57:05.394856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 19
 
12.4%
8650.48 2
 
1.3%
1262.64 1
 
0.7%
3016.74 1
 
0.7%
723.5 1
 
0.7%
835.99 1
 
0.7%
661.5 1
 
0.7%
877.44 1
 
0.7%
1638.99 1
 
0.7%
1992.0 1
 
0.7%
Other values (41) 41
26.8%
(Missing) 83
54.2%
ValueCountFrequency (%)
0.0 19
12.4%
167.0 1
 
0.7%
198.2 1
 
0.7%
398.68 1
 
0.7%
444.92 1
 
0.7%
477.4 1
 
0.7%
492.02 1
 
0.7%
493.26 1
 
0.7%
640.08 1
 
0.7%
661.5 1
 
0.7%
ValueCountFrequency (%)
8650.48 2
1.3%
6543.44 1
0.7%
5572.0 1
0.7%
5090.34 1
0.7%
5054.0 1
0.7%
4779.65 1
0.7%
4621.82 1
0.7%
4378.2 1
0.7%
4167.88 1
0.7%
3921.03 1
0.7%

회원모집총인원
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
124 
0
26 
1000
 
1
90
 
1
60
 
1

Length

Max length4
Median length4
Mean length3.4640523
Min length1

Unique

Unique3 ?
Unique (%)2.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 124
81.0%
0 26
 
17.0%
1000 1
 
0.7%
90 1
 
0.7%
60 1
 
0.7%

Length

2024-03-14T18:57:05.626575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:57:05.823468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 124
81.0%
0 26
 
17.0%
1000 1
 
0.7%
90 1
 
0.7%
60 1
 
0.7%

Interactions

2024-03-14T18:56:48.286391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:45.436305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:46.465069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:47.650260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:48.439198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:45.704687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:46.925985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:47.848615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:48.563192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:45.958434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:47.169702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:47.999302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:48.703995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:46.220826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:47.422365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:56:48.151287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:57:05.959234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도지도자수건축물연면적회원모집총인원
연번1.0000.0000.1960.3060.0540.732
위도0.0001.0000.7380.5320.2930.699
경도0.1960.7381.0000.7670.3040.652
지도자수0.3060.5320.7671.0000.6830.784
건축물연면적0.0540.2930.3040.6831.0000.845
회원모집총인원0.7320.6990.6520.7840.8451.000
2024-03-14T18:57:06.215591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회원모집총인원지도자수
회원모집총인원1.0000.824
지도자수0.8241.000
2024-03-14T18:57:06.458378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도건축물연면적지도자수회원모집총인원
연번1.0000.115-0.020-0.0120.1540.459
위도0.1151.0000.1000.4320.3380.526
경도-0.0200.1001.0000.0190.5700.455
건축물연면적-0.0120.4320.0191.0000.5160.748
지도자수0.1540.3380.5700.5161.0000.824
회원모집총인원0.4590.5260.4550.7480.8241.000

Missing values

2024-03-14T18:56:48.978918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:56:49.268738image/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.
2024-03-14T18:56:49.473337image/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

연번업종사업장명인허가일자전화번호도로명주소지번주소위도경도지도자수건축물연면적회원모집총인원
01골프연습장업(주)서일개발 스포디움 지점(스크린골프장)2016-12-15063-224-2128전북특별자치도 전주시 덕진구 기지로 66전북특별자치도 전주시 덕진구 중동 774-435.838049127.059014<NA><NA><NA>
12골프연습장업abc골프2007-10-30063-252-4653전북특별자치도 전주시 덕진구 송천중앙로 241전북특별자치도 전주시 덕진구 송천동2가 492-5135.868452127.121095<NA><NA><NA>
23골프연습장업EG 스크린골프2013-10-30<NA>전북특별자치도 전주시 완산구 백제대로 277전북특별자치도 전주시 완산구 중화산동2가 595-935.818073127.12250103737.320
34골프연습장업GDR 골프존 아카데미 전주점2017-11-28<NA>전북특별자치도 전주시 완산구 효자로 266전북특별자치도 전주시 완산구 중화산동2가 485-4435.818683127.11448800.00
45골프연습장업GDR아카데미(온스윙)2011-03-29<NA>전북특별자치도 전주시 완산구 바우배기2길 11전북특별자치도 전주시 완산구 효자동2가 1234-235.817175127.102756<NA><NA><NA>
56골프연습장업Joy 실내골프연습장2010-12-17063-271-7577전북특별자치도 전주시 덕진구 가리내10길 8-1전북특별자치도 전주시 덕진구 덕진동2가 678-435.842549127.110906<NA><NA><NA>
67골프연습장업JS 실내 골프연습장2017-07-31<NA>전북특별자치도 전주시 덕진구 건산로 297전북특별자치도 전주시 덕진구 산정동 873-635.836621127.169331<NA><NA><NA>
78골프연습장업MY GDR골프아카데미2018-06-07<NA>전북특별자치도 전주시 완산구 유연로 154전북특별자치도 전주시 완산구 효자동3가 1627-635.824885127.10223305572.00
89골프연습장업OK스크린골프2016-12-27063-244-2324전북특별자치도 전주시 덕진구 동부대로 445전북특별자치도 전주시 덕진구 우아동2가 926-335.831688127.174196<NA><NA><NA>
910골프연습장업SG스크린골프도청점2016-06-03063-223-0066전북특별자치도 전주시 완산구 홍산중앙로 17전북특별자치도 전주시 완산구 효자동2가 1155-935.815151127.10873400.00
연번업종사업장명인허가일자전화번호도로명주소지번주소위도경도지도자수건축물연면적회원모집총인원
143144골프연습장업행복한 골프클리닉2007-07-09<NA>전북특별자치도 전주시 완산구 메너머1길 14전북특별자치도 전주시 완산구 중화산동2가 573-635.821133127.121417<NA><NA><NA>
144145골프연습장업혁신 스크린골프2014-11-07<NA>전북특별자치도 전주시 덕진구 오공로 126전북특별자치도 전주시 덕진구 만성동 1166-335.835283127.069253<NA><NA><NA>
145146골프연습장업현대골프연습장1996-05-23063-274-6220전북특별자치도 전주시 덕진구 와룡로 97-10전북특별자치도 전주시 덕진구 송천동2가 60435.868138127.1136011887.64<NA>
146147골프연습장업현대비전 스크린2014-01-08063-252-0084전북특별자치도 전주시 덕진구 시천로 99전북특별자치도 전주시 덕진구 송천동2가 606-835.868224127.114344<NA><NA><NA>
147148골프연습장업호남제일 스크린골프2019-01-07063-214-3900전북특별자치도 전주시 덕진구 기린대로 1056전북특별자치도 전주시 덕진구 여의동 1231-1035.869554127.071531<NA>2971.84<NA>
148149골프연습장업홀인원 골프클럽2007-03-20063-228-3500전북특별자치도 전주시 완산구 콩쥐팥쥐로 1700-10전북특별자치도 전주시 완산구 효자동3가 105235.821056127.0834130.00
149150골프연습장업화산골프스쿨2011-07-26063-229-0044전북특별자치도 전주시 완산구 효자로 280전북특별자치도 전주시 완산구 중화산동2가 77235.818841127.115952<NA><NA>60
150151골프연습장업화산체육관 실내골프연습장2008-12-30063-281-2384전북특별자치도 전주시 완산구 백제대로 310전북특별자치도 전주시 완산구 중화산동2가 산 4535.820941127.124575<NA><NA><NA>
151152골프연습장업효천지디알아카데미2021-09-06<NA>전북특별자치도 전주시 완산구 천잠로 58, 이든빌딩 601,701호 (삼천동2가)전북특별자치도 전주시 완산구 삼천동2가 763-3 이든빌딩35.794595127.10595900.00
152153골프연습장업휴먼 스크린골프2011-04-06063-228-7199전북특별자치도 전주시 완산구 우전1길 49-3전북특별자치도 전주시 완산구 효자동2가 1332-235.808002127.10551700.00