Overview

Dataset statistics

Number of variables10
Number of observations300
Missing cells265
Missing cells (%)8.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.7 KiB
Average record size in memory84.4 B

Variable types

Numeric4
Categorical1
Text4
DateTime1

Dataset

Description전북특별자치도 전주시의 당구장업을 제공하며 업종, 사업장명, 인허가일자, 전화번호, 도로명주소, 지번주소 등을 제공합니다.당구장업 : 당구를 하는데 필요한 시설을 갖추어 놓은 업소항목 : 연번, 사업장명, 인허가일자, 전화번호, 도로명주소, 지번주소, 위도, 경도 등제공부서 : 체육산업과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15112491/fileData.do

Alerts

업종 has constant value ""Constant
전화번호 has 131 (43.7%) missing valuesMissing
도로명주소 has 13 (4.3%) missing valuesMissing
위도 has 12 (4.0%) missing valuesMissing
경도 has 12 (4.0%) missing valuesMissing
건축물연면적 has 97 (32.3%) missing valuesMissing
연번 has unique valuesUnique
건축물연면적 has 24 (8.0%) zerosZeros

Reproduction

Analysis started2024-03-14 13:42:28.410400
Analysis finished2024-03-14 13:42:33.922961
Duration5.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct300
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean150.5
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-14T22:42:34.141828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.95
Q175.75
median150.5
Q3225.25
95-th percentile285.05
Maximum300
Range299
Interquartile range (IQR)149.5

Descriptive statistics

Standard deviation86.746758
Coefficient of variation (CV)0.57639042
Kurtosis-1.2
Mean150.5
Median Absolute Deviation (MAD)75
Skewness0
Sum45150
Variance7525
MonotonicityStrictly increasing
2024-03-14T22:42:34.790259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
208 1
 
0.3%
206 1
 
0.3%
205 1
 
0.3%
204 1
 
0.3%
203 1
 
0.3%
202 1
 
0.3%
201 1
 
0.3%
200 1
 
0.3%
199 1
 
0.3%
Other values (290) 290
96.7%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
300 1
0.3%
299 1
0.3%
298 1
0.3%
297 1
0.3%
296 1
0.3%
295 1
0.3%
294 1
0.3%
293 1
0.3%
292 1
0.3%
291 1
0.3%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
당구장업
300 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
당구장업 300
100.0%

Length

2024-03-14T22:42:35.206865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:42:35.512709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당구장업 300
100.0%

사업장명
Text

Distinct284
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T22:42:36.507381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length5.9466667
Min length2

Characters and Unicode

Total characters1784
Distinct characters281
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

Unique269 ?
Unique (%)89.7%

Sample

1st row24시당구장
2nd row777 당구장
3rd rowBALL ROCK
4th rowCC 클럽
5th rowH 당구클럽
ValueCountFrequency (%)
당구장 49
 
12.2%
당구클럽 33
 
8.2%
당구 4
 
1.0%
스타 3
 
0.7%
당구존 3
 
0.7%
구슬 3
 
0.7%
아지트 3
 
0.7%
킹 3
 
0.7%
구슬당구클럽 3
 
0.7%
반월당구장 2
 
0.5%
Other values (279) 296
73.6%
2024-03-14T22:42:37.838726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 292
16.4%
당 284
15.9%
장 188
 
10.5%
102
 
5.7%
럽 87
 
4.9%
클 86
 
4.8%
스 30
 
1.7%
리 18
 
1.0%
아 16
 
0.9%
드 14
 
0.8%
Other values (271) 667
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1609
90.2%
Space Separator 102
 
5.7%
Uppercase Letter 49
 
2.7%
Decimal Number 9
 
0.5%
Lowercase Letter 7
 
0.4%
Other Punctuation 3
 
0.2%
Letter Number 2
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 292
18.1%
당 284
17.7%
장 188
 
11.7%
럽 87
 
5.4%
클 86
 
5.3%
스 30
 
1.9%
리 18
 
1.1%
아 16
 
1.0%
드 14
 
0.9%
대 13
 
0.8%
Other values (238) 581
36.1%
Uppercase Letter
ValueCountFrequency (%)
K 7
14.3%
J 6
12.2%
B 5
10.2%
C 5
10.2%
S 4
8.2%
I 3
 
6.1%
M 3
 
6.1%
N 3
 
6.1%
O 3
 
6.1%
L 2
 
4.1%
Other values (8) 8
16.3%
Decimal Number
ValueCountFrequency (%)
2 3
33.3%
7 3
33.3%
1 2
22.2%
4 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
o 3
42.9%
k 2
28.6%
p 1
 
14.3%
r 1
 
14.3%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%
Space Separator
ValueCountFrequency (%)
102
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1609
90.2%
Common 117
 
6.6%
Latin 58
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 292
18.1%
당 284
17.7%
장 188
 
11.7%
럽 87
 
5.4%
클 86
 
5.3%
스 30
 
1.9%
리 18
 
1.1%
아 16
 
1.0%
드 14
 
0.9%
대 13
 
0.8%
Other values (238) 581
36.1%
Latin
ValueCountFrequency (%)
K 7
12.1%
J 6
 
10.3%
B 5
 
8.6%
C 5
 
8.6%
S 4
 
6.9%
I 3
 
5.2%
M 3
 
5.2%
N 3
 
5.2%
O 3
 
5.2%
o 3
 
5.2%
Other values (14) 16
27.6%
Common
ValueCountFrequency (%)
102
87.2%
. 3
 
2.6%
2 3
 
2.6%
7 3
 
2.6%
1 2
 
1.7%
4 1
 
0.9%
( 1
 
0.9%
) 1
 
0.9%
- 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1609
90.2%
ASCII 173
 
9.7%
Number Forms 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 292
18.1%
당 284
17.7%
장 188
 
11.7%
럽 87
 
5.4%
클 86
 
5.3%
스 30
 
1.9%
리 18
 
1.1%
아 16
 
1.0%
드 14
 
0.9%
대 13
 
0.8%
Other values (238) 581
36.1%
ASCII
ValueCountFrequency (%)
102
59.0%
K 7
 
4.0%
J 6
 
3.5%
B 5
 
2.9%
C 5
 
2.9%
S 4
 
2.3%
I 3
 
1.7%
M 3
 
1.7%
. 3
 
1.7%
2 3
 
1.7%
Other values (21) 32
 
18.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅲ 1
50.0%

인허가일자
Date

Distinct291
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
Minimum1989-09-18 00:00:00
Maximum2022-11-30 00:00:00
2024-03-14T22:42:38.083529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:38.494830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct168
Distinct (%)99.4%
Missing131
Missing (%)43.7%
Memory size2.5 KiB
2024-03-14T22:42:39.397031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.011834
Min length12

Characters and Unicode

Total characters2030
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

Unique167 ?
Unique (%)98.8%

Sample

1st row063-275-2554
2nd row063-222-3972
3rd row063-241-0200
4th row063-272-6767
5th row063-227-4939
ValueCountFrequency (%)
063-222-2720 2
 
1.2%
063-236-7761 1
 
0.6%
063-211-4715 1
 
0.6%
063-284-2171 1
 
0.6%
063-255-5177 1
 
0.6%
063-246-4554 1
 
0.6%
063-227-6999 1
 
0.6%
063-255-0889 1
 
0.6%
063-246-1212 1
 
0.6%
063-288-1692 1
 
0.6%
Other values (158) 158
93.5%
2024-03-14T22:42:40.699887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 338
16.7%
2 299
14.7%
3 261
12.9%
0 244
12.0%
6 236
11.6%
4 132
 
6.5%
7 123
 
6.1%
5 120
 
5.9%
1 114
 
5.6%
9 93
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1692
83.3%
Dash Punctuation 338
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 299
17.7%
3 261
15.4%
0 244
14.4%
6 236
13.9%
4 132
7.8%
7 123
7.3%
5 120
7.1%
1 114
 
6.7%
9 93
 
5.5%
8 70
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 338
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2030
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 338
16.7%
2 299
14.7%
3 261
12.9%
0 244
12.0%
6 236
11.6%
4 132
 
6.5%
7 123
 
6.1%
5 120
 
5.9%
1 114
 
5.6%
9 93
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2030
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 338
16.7%
2 299
14.7%
3 261
12.9%
0 244
12.0%
6 236
11.6%
4 132
 
6.5%
7 123
 
6.1%
5 120
 
5.9%
1 114
 
5.6%
9 93
 
4.6%

도로명주소
Text

MISSING 

Distinct278
Distinct (%)96.9%
Missing13
Missing (%)4.3%
Memory size2.5 KiB
2024-03-14T22:42:42.273591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length23.43554
Min length21

Characters and Unicode

Total characters6726
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

Unique269 ?
Unique (%)93.7%

Sample

1st row전북특별자치도 전주시 덕진구 송천중앙로 151
2nd row전북특별자치도 전주시 덕진구 기지로 68
3rd row전북특별자치도 전주시 덕진구 명륜5길 10-2
4th row전북특별자치도 전주시 덕진구 명륜5길 10-2
5th row전북특별자치도 전주시 완산구 홍산남로 50
ValueCountFrequency (%)
전북특별자치도 287
20.0%
전주시 287
20.0%
덕진구 193
 
13.4%
완산구 94
 
6.6%
명륜4길 19
 
1.3%
기린대로 11
 
0.8%
백제대로 10
 
0.7%
건산로 9
 
0.6%
6 7
 
0.5%
용리로 7
 
0.5%
Other values (313) 511
35.6%
2024-03-14T22:42:44.226578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1148
17.1%
전 587
 
8.7%
주 295
 
4.4%
북 291
 
4.3%
시 291
 
4.3%
구 290
 
4.3%
자 290
 
4.3%
도 289
 
4.3%
별 287
 
4.3%
치 287
 
4.3%
Other values (141) 2671
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4748
70.6%
Space Separator 1148
 
17.1%
Decimal Number 789
 
11.7%
Dash Punctuation 41
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 587
 
12.4%
주 295
 
6.2%
북 291
 
6.1%
시 291
 
6.1%
구 290
 
6.1%
자 290
 
6.1%
도 289
 
6.1%
별 287
 
6.0%
치 287
 
6.0%
특 287
 
6.0%
Other values (129) 1554
32.7%
Decimal Number
ValueCountFrequency (%)
1 165
20.9%
2 109
13.8%
4 99
12.5%
3 93
11.8%
5 70
8.9%
0 62
 
7.9%
6 55
 
7.0%
8 53
 
6.7%
7 43
 
5.4%
9 40
 
5.1%
Space Separator
ValueCountFrequency (%)
1148
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4748
70.6%
Common 1978
29.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 587
 
12.4%
주 295
 
6.2%
북 291
 
6.1%
시 291
 
6.1%
구 290
 
6.1%
자 290
 
6.1%
도 289
 
6.1%
별 287
 
6.0%
치 287
 
6.0%
특 287
 
6.0%
Other values (129) 1554
32.7%
Common
ValueCountFrequency (%)
1148
58.0%
1 165
 
8.3%
2 109
 
5.5%
4 99
 
5.0%
3 93
 
4.7%
5 70
 
3.5%
0 62
 
3.1%
6 55
 
2.8%
8 53
 
2.7%
7 43
 
2.2%
Other values (2) 81
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4748
70.6%
ASCII 1978
29.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1148
58.0%
1 165
 
8.3%
2 109
 
5.5%
4 99
 
5.0%
3 93
 
4.7%
5 70
 
3.5%
0 62
 
3.1%
6 55
 
2.8%
8 53
 
2.7%
7 43
 
2.2%
Other values (2) 81
 
4.1%
Hangul
ValueCountFrequency (%)
전 587
 
12.4%
주 295
 
6.2%
북 291
 
6.1%
시 291
 
6.1%
구 290
 
6.1%
자 290
 
6.1%
도 289
 
6.1%
별 287
 
6.0%
치 287
 
6.0%
특 287
 
6.0%
Other values (129) 1554
32.7%

지번주소
Text

Distinct291
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T22:42:45.004241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length30
Mean length27.03
Min length23

Characters and Unicode

Total characters8109
Distinct characters62
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique282 ?
Unique (%)94.0%

Sample

1st row전북특별자치도 전주시 덕진구 송천동1가 482-3
2nd row전북특별자치도 전주시 덕진구 중동 774-3
3rd row전북특별자치도 전주시 덕진구 덕진동1가 1262-4
4th row전북특별자치도 전주시 덕진구 덕진동1가 1262-4
5th row전북특별자치도 전주시 완산구 효자동2가 1155-2
ValueCountFrequency (%)
전북특별자치도 300
20.0%
전주시 300
20.0%
덕진구 206
13.7%
완산구 94
 
6.3%
덕진동1가 37
 
2.5%
금암동 32
 
2.1%
인후동1가 26
 
1.7%
송천동1가 19
 
1.3%
효자동3가 15
 
1.0%
삼천동1가 14
 
0.9%
Other values (322) 458
30.5%
2024-03-14T22:42:46.211059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1203
 
14.8%
전 600
 
7.4%
1 419
 
5.2%
자 330
 
4.1%
북 310
 
3.8%
동 306
 
3.8%
주 300
 
3.7%
시 300
 
3.7%
구 300
 
3.7%
도 300
 
3.7%
Other values (52) 3741
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5035
62.1%
Decimal Number 1586
 
19.6%
Space Separator 1203
 
14.8%
Dash Punctuation 274
 
3.4%
Other Punctuation 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 600
 
11.9%
자 330
 
6.6%
북 310
 
6.2%
동 306
 
6.1%
주 300
 
6.0%
시 300
 
6.0%
구 300
 
6.0%
도 300
 
6.0%
치 300
 
6.0%
별 300
 
6.0%
Other values (39) 1689
33.5%
Decimal Number
ValueCountFrequency (%)
1 419
26.4%
2 241
15.2%
3 155
 
9.8%
6 140
 
8.8%
7 136
 
8.6%
4 132
 
8.3%
5 119
 
7.5%
8 87
 
5.5%
0 82
 
5.2%
9 75
 
4.7%
Space Separator
ValueCountFrequency (%)
1203
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 274
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5035
62.1%
Common 3074
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 600
 
11.9%
자 330
 
6.6%
북 310
 
6.2%
동 306
 
6.1%
주 300
 
6.0%
시 300
 
6.0%
구 300
 
6.0%
도 300
 
6.0%
치 300
 
6.0%
별 300
 
6.0%
Other values (39) 1689
33.5%
Common
ValueCountFrequency (%)
1203
39.1%
1 419
 
13.6%
- 274
 
8.9%
2 241
 
7.8%
3 155
 
5.0%
6 140
 
4.6%
7 136
 
4.4%
4 132
 
4.3%
5 119
 
3.9%
8 87
 
2.8%
Other values (3) 168
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5035
62.1%
ASCII 3074
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1203
39.1%
1 419
 
13.6%
- 274
 
8.9%
2 241
 
7.8%
3 155
 
5.0%
6 140
 
4.6%
7 136
 
4.4%
4 132
 
4.3%
5 119
 
3.9%
8 87
 
2.8%
Other values (3) 168
 
5.5%
Hangul
ValueCountFrequency (%)
전 600
 
11.9%
자 330
 
6.6%
북 310
 
6.2%
동 306
 
6.1%
주 300
 
6.0%
시 300
 
6.0%
구 300
 
6.0%
도 300
 
6.0%
치 300
 
6.0%
별 300
 
6.0%
Other values (39) 1689
33.5%

위도
Real number (ℝ)

MISSING 

Distinct279
Distinct (%)96.9%
Missing12
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean35.833103
Minimum35.785362
Maximum35.874592
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-14T22:42:46.616660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.785362
5-th percentile35.794947
Q135.81986
median35.834874
Q335.843875
95-th percentile35.865935
Maximum35.874592
Range0.08922977
Interquartile range (IQR)0.02401427

Descriptive statistics

Standard deviation0.020487845
Coefficient of variation (CV)0.0005717575
Kurtosis-0.34473419
Mean35.833103
Median Absolute Deviation (MAD)0.010458005
Skewness-0.2760781
Sum10319.934
Variance0.0004197518
MonotonicityNot monotonic
2024-03-14T22:42:47.042404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8438746 2
 
0.7%
35.83361927 2
 
0.7%
35.84344481 2
 
0.7%
35.83487437 2
 
0.7%
35.85672059 2
 
0.7%
35.835925 2
 
0.7%
35.85290765 2
 
0.7%
35.83448062 2
 
0.7%
35.84317386 2
 
0.7%
35.81560458 1
 
0.3%
Other values (269) 269
89.7%
(Missing) 12
 
4.0%
ValueCountFrequency (%)
35.78536249 1
0.3%
35.78722665 1
0.3%
35.78725741 1
0.3%
35.78894326 1
0.3%
35.78916338 1
0.3%
35.79031846 1
0.3%
35.79218586 1
0.3%
35.79220091 1
0.3%
35.79305426 1
0.3%
35.79438422 1
0.3%
ValueCountFrequency (%)
35.87459226 1
0.3%
35.87456445 1
0.3%
35.87416504 1
0.3%
35.87364099 1
0.3%
35.87350255 1
0.3%
35.87282301 1
0.3%
35.87187206 1
0.3%
35.87155092 1
0.3%
35.87082881 1
0.3%
35.86682152 1
0.3%

경도
Real number (ℝ)

MISSING 

Distinct279
Distinct (%)96.9%
Missing12
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean127.13005
Minimum127.05934
Maximum127.17769
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-14T22:42:47.442041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.05934
5-th percentile127.08173
Q1127.11715
median127.12752
Q3127.14627
95-th percentile127.16948
Maximum127.17769
Range0.1183524
Interquartile range (IQR)0.02912335

Descriptive statistics

Standard deviation0.024044306
Coefficient of variation (CV)0.00018913157
Kurtosis0.42071174
Mean127.13005
Median Absolute Deviation (MAD)0.0132302
Skewness-0.40013632
Sum36613.455
Variance0.00057812867
MonotonicityNot monotonic
2024-03-14T22:42:47.905793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1269609 2
 
0.7%
127.135157 2
 
0.7%
127.1275392 2
 
0.7%
127.1637759 2
 
0.7%
127.1183652 2
 
0.7%
127.1285427 2
 
0.7%
127.1052877 2
 
0.7%
127.133686 2
 
0.7%
127.1255118 2
 
0.7%
127.1093198 1
 
0.3%
Other values (269) 269
89.7%
(Missing) 12
 
4.0%
ValueCountFrequency (%)
127.0593368 1
0.3%
127.059485 1
0.3%
127.059491 1
0.3%
127.0594965 1
0.3%
127.0710118 1
0.3%
127.0714973 1
0.3%
127.0721458 1
0.3%
127.0721831 1
0.3%
127.0738796 1
0.3%
127.0767123 1
0.3%
ValueCountFrequency (%)
127.1776892 1
0.3%
127.1745349 1
0.3%
127.1743246 1
0.3%
127.1736687 1
0.3%
127.1732257 1
0.3%
127.172888 1
0.3%
127.1724775 1
0.3%
127.1722106 1
0.3%
127.1714843 1
0.3%
127.1714523 1
0.3%

건축물연면적
Real number (ℝ)

MISSING  ZEROS 

Distinct115
Distinct (%)56.7%
Missing97
Missing (%)32.3%
Infinite0
Infinite (%)0.0%
Mean836.18547
Minimum0
Maximum41972.29
Zeros24
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-14T22:42:48.331394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1120
median196.48
Q3755.16
95-th percentile3369.312
Maximum41972.29
Range41972.29
Interquartile range (IQR)635.16

Descriptive statistics

Standard deviation3112.2576
Coefficient of variation (CV)3.7219705
Kurtosis152.83082
Mean836.18547
Median Absolute Deviation (MAD)96.48
Skewness11.676774
Sum169745.65
Variance9686147.7
MonotonicityNot monotonic
2024-03-14T22:42:48.757882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 24
 
8.0%
120.0 15
 
5.0%
140.0 13
 
4.3%
160.0 10
 
3.3%
200.0 9
 
3.0%
100.0 9
 
3.0%
180.0 6
 
2.0%
132.0 3
 
1.0%
198.0 3
 
1.0%
300.0 2
 
0.7%
Other values (105) 109
36.3%
(Missing) 97
32.3%
ValueCountFrequency (%)
0.0 24
8.0%
63.47 1
 
0.3%
80.0 2
 
0.7%
99.0 1
 
0.3%
100.0 9
 
3.0%
120.0 15
5.0%
132.0 3
 
1.0%
134.4 1
 
0.3%
136.2 1
 
0.3%
137.97 1
 
0.3%
ValueCountFrequency (%)
41972.29 1
0.3%
7151.87 1
0.3%
6543.44 1
0.3%
5576.02 1
0.3%
5458.32 1
0.3%
4481.0 1
0.3%
3959.31 1
0.3%
3839.32 1
0.3%
3564.51 1
0.3%
3480.94 1
0.3%

Interactions

2024-03-14T22:42:31.971063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:29.026554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:30.021295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:30.971743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:32.218033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:29.280743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:30.264245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:31.229972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:32.446297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:29.522300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:30.490816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:31.469401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:32.706945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:29.781989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:30.741587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:42:31.728209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:42:49.016366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도건축물연면적
연번1.0000.0000.1900.000
위도0.0001.0000.7990.000
경도0.1900.7991.0000.327
건축물연면적0.0000.0000.3271.000
2024-03-14T22:42:49.272203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도건축물연면적
연번1.0000.001-0.0430.030
위도0.0011.000-0.072-0.058
경도-0.043-0.0721.000-0.047
건축물연면적0.030-0.058-0.0471.000

Missing values

2024-03-14T22:42:32.948711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:42:33.388964image/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.
2024-03-14T22:42:33.739323image/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

연번업종사업장명인허가일자전화번호도로명주소지번주소위도경도건축물연면적
01당구장업24시당구장2000-06-14063-275-2554전북특별자치도 전주시 덕진구 송천중앙로 151전북특별자치도 전주시 덕진구 송천동1가 482-335.860319127.121043210.68
12당구장업777 당구장2019-07-22<NA>전북특별자치도 전주시 덕진구 기지로 68전북특별자치도 전주시 덕진구 중동 774-335.838105127.0593375576.02
23당구장업BALL ROCK2016-09-09<NA>전북특별자치도 전주시 덕진구 명륜5길 10-2전북특별자치도 전주시 덕진구 덕진동1가 1262-435.843174127.125512<NA>
34당구장업CC 클럽2007-08-23<NA>전북특별자치도 전주시 덕진구 명륜5길 10-2전북특별자치도 전주시 덕진구 덕진동1가 1262-435.843174127.125512478.0
45당구장업H 당구클럽2022-04-20063-222-3972전북특별자치도 전주시 완산구 홍산남로 50전북특별자치도 전주시 완산구 효자동2가 1155-235.815574127.1072590.0
56당구장업ING당구장2018-04-17063-241-0200전북특별자치도 전주시 덕진구 동가재미2길 63전북특별자치도 전주시 덕진구 인후동1가 850-1035.834989127.1670991285.83
67당구장업J.B.C당구클럽2008-07-30<NA>전북특별자치도 전주시 완산구 효자천변2길 17전북특별자치도 전주시 완산구 효자동1가 651-235.804478127.114337<NA>
78당구장업JB당구장2016-06-20<NA>전북특별자치도 전주시 덕진구 두간1길 5전북특별자치도 전주시 덕진구 송천동1가 812-335.864825127.121283<NA>
89당구장업JJ포켓클럽2002-06-17<NA><NA>전북특별자치도 전주시 덕진구 덕진동1가 644-16,<NA><NA>160.0
910당구장업JS당구클럽2019-11-18<NA>전북특별자치도 전주시 덕진구 호성3길 6전북특별자치도 전주시 덕진구 호성동1가 587-6735.8614127.151313557.24
연번업종사업장명인허가일자전화번호도로명주소지번주소위도경도건축물연면적
290291당구장업현대당구장2001-10-08063-252-2908<NA>전북특별자치도 전주시 덕진구 금상동 664-77,<NA><NA>160.0
291292당구장업형제당구장1991-01-16063-277-7545<NA>전북특별자치도 전주시 덕진구 덕진동1가 220,<NA><NA>80.0
292293당구장업호남당구장2017-06-30<NA>전북특별자치도 전주시 덕진구 두간로 23전북특별자치도 전주시 덕진구 송천동1가 804-135.86548127.117087<NA>
293294당구장업호성당구장2007-06-25<NA>전북특별자치도 전주시 덕진구 소리로 192전북특별자치도 전주시 덕진구 호성동1가 794-835.857889127.153025254.72
294295당구장업홍백당구장1994-05-07063-241-6790전북특별자치도 전주시 덕진구 동부대로 675전북특별자치도 전주시 덕진구 우아동3가 752-5735.848792127.160432200.0
295296당구장업화성당구장1997-05-09063-251-7944전북특별자치도 전주시 덕진구 전주천동로 412전북특별자치도 전주시 덕진구 진북동 1154-1735.830638127.129092120.0
296297당구장업황궁당구장2016-06-20<NA>전북특별자치도 전주시 완산구 장승배기로 399전북특별자치도 전주시 완산구 동서학동 256-1035.806187127.152371<NA>
297298당구장업황실당구장1999-03-11063-243-3949<NA>전북특별자치도 전주시 덕진구 인후동2가 성학2층2호<NA><NA>176.0
298299당구장업황제당구장2010-01-28063-252-6513전북특별자치도 전주시 덕진구 명륜4길 11-10전북특별자치도 전주시 덕진구 덕진동1가 1261-2835.843333127.126079814.38
299300당구장업힐링탑 당구존2018-11-12063-222-6311전북특별자치도 전주시 완산구 백제대로 264전북특별자치도 전주시 완산구 중화산동2가 651-335.816765127.1233551839.11