Overview

Dataset statistics

Number of variables7
Number of observations91
Missing cells65
Missing cells (%)10.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory59.5 B

Variable types

Text4
Categorical1
Numeric2

Dataset

Description인천광역시 미추홀구의 체력단련장 현황에 대한 데이터로 상호명, 도로명주소, 지번주소, 전화번호 등의 정보를 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15100851/fileData.do

Alerts

구분 has constant value ""Constant
도로명주소 has 1 (1.1%) missing valuesMissing
지번주소 has 5 (5.5%) missing valuesMissing
전화번호 has 59 (64.8%) missing valuesMissing

Reproduction

Analysis started2023-12-12 08:39:36.325055
Analysis finished2023-12-12 08:39:38.231409
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호명
Text

Distinct88
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size860.0 B
2023-12-12T17:39:38.431220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length6.4175824
Min length2

Characters and Unicode

Total characters584
Distinct characters182
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

Unique85 ?
Unique (%)93.4%

Sample

1st row세종헬스
2nd row대왕헬스클럽
3rd rowCBBM휘트니스센타
4th row삼성남녀스포츠센터
5th row머신휘트니스
ValueCountFrequency (%)
휘트니스 7
 
5.2%
피트니스 4
 
3.0%
gym 4
 
3.0%
와이짐 3
 
2.2%
주안점 3
 
2.2%
학익점 2
 
1.5%
주안 2
 
1.5%
더 2
 
1.5%
바디와이짐 2
 
1.5%
인싸짐 2
 
1.5%
Other values (101) 103
76.9%
2023-12-12T17:39:38.914809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43
 
7.4%
스 39
 
6.7%
짐 35
 
6.0%
트 22
 
3.8%
니 21
 
3.6%
이 20
 
3.4%
휘 15
 
2.6%
Y 9
 
1.5%
피 9
 
1.5%
헬 9
 
1.5%
Other values (172) 362
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 427
73.1%
Uppercase Letter 82
 
14.0%
Space Separator 43
 
7.4%
Lowercase Letter 18
 
3.1%
Decimal Number 6
 
1.0%
Close Punctuation 3
 
0.5%
Open Punctuation 3
 
0.5%
Other Punctuation 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 39
 
9.1%
짐 35
 
8.2%
트 22
 
5.2%
니 21
 
4.9%
이 20
 
4.7%
휘 15
 
3.5%
피 9
 
2.1%
헬 9
 
2.1%
점 9
 
2.1%
핏 7
 
1.6%
Other values (130) 241
56.4%
Uppercase Letter
ValueCountFrequency (%)
Y 9
11.0%
G 8
 
9.8%
M 8
 
9.8%
T 8
 
9.8%
P 7
 
8.5%
S 5
 
6.1%
A 5
 
6.1%
E 4
 
4.9%
L 4
 
4.9%
B 4
 
4.9%
Other values (11) 20
24.4%
Lowercase Letter
ValueCountFrequency (%)
o 3
16.7%
s 2
11.1%
i 2
11.1%
n 2
11.1%
r 2
11.1%
h 1
 
5.6%
a 1
 
5.6%
g 1
 
5.6%
p 1
 
5.6%
t 1
 
5.6%
Other values (2) 2
11.1%
Decimal Number
ValueCountFrequency (%)
8 2
33.3%
1 2
33.3%
4 1
16.7%
5 1
16.7%
Space Separator
ValueCountFrequency (%)
43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 427
73.1%
Latin 100
 
17.1%
Common 57
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 39
 
9.1%
짐 35
 
8.2%
트 22
 
5.2%
니 21
 
4.9%
이 20
 
4.7%
휘 15
 
3.5%
피 9
 
2.1%
헬 9
 
2.1%
점 9
 
2.1%
핏 7
 
1.6%
Other values (130) 241
56.4%
Latin
ValueCountFrequency (%)
Y 9
 
9.0%
G 8
 
8.0%
M 8
 
8.0%
T 8
 
8.0%
P 7
 
7.0%
S 5
 
5.0%
A 5
 
5.0%
E 4
 
4.0%
L 4
 
4.0%
B 4
 
4.0%
Other values (23) 38
38.0%
Common
ValueCountFrequency (%)
43
75.4%
) 3
 
5.3%
( 3
 
5.3%
8 2
 
3.5%
1 2
 
3.5%
' 1
 
1.8%
- 1
 
1.8%
4 1
 
1.8%
5 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 427
73.1%
ASCII 157
 
26.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43
27.4%
Y 9
 
5.7%
G 8
 
5.1%
M 8
 
5.1%
T 8
 
5.1%
P 7
 
4.5%
S 5
 
3.2%
A 5
 
3.2%
E 4
 
2.5%
L 4
 
2.5%
Other values (32) 56
35.7%
Hangul
ValueCountFrequency (%)
스 39
 
9.1%
짐 35
 
8.2%
트 22
 
5.2%
니 21
 
4.9%
이 20
 
4.7%
휘 15
 
3.5%
피 9
 
2.1%
헬 9
 
2.1%
점 9
 
2.1%
핏 7
 
1.6%
Other values (130) 241
56.4%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size860.0 B
체력단련장업
91 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
체력단련장업 91
100.0%

Length

2023-12-12T17:39:39.052965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:39:39.146428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체력단련장업 91
100.0%

도로명주소
Text

MISSING 

Distinct90
Distinct (%)100.0%
Missing1
Missing (%)1.1%
Memory size860.0 B
2023-12-12T17:39:39.419415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length32
Min length23

Characters and Unicode

Total characters2880
Distinct characters144
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 구월로8번길 16 (주안동,1543-11,12)
2nd row인천광역시 미추홀구 석정로 129 (숭의동)
3rd row인천광역시 미추홀구 독정이로 40 (용현동)
4th row인천광역시 미추홀구 인하로 255 (주안동,1436-30,31)
5th row인천광역시 미추홀구 경인남길30번길 65, 4층 401호 (용현동, 대동빌딩)
ValueCountFrequency (%)
인천광역시 90
 
16.1%
미추홀구 90
 
16.1%
주안동 43
 
7.7%
용현동 20
 
3.6%
도화동 12
 
2.1%
2층 11
 
2.0%
3층 10
 
1.8%
인하로 9
 
1.6%
미추홀대로 8
 
1.4%
학익동 8
 
1.4%
Other values (191) 259
46.2%
2023-12-12T17:39:40.020641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
473
 
16.4%
인 117
 
4.1%
홀 106
 
3.7%
미 99
 
3.4%
추 99
 
3.4%
동 96
 
3.3%
구 92
 
3.2%
시 90
 
3.1%
역 90
 
3.1%
광 90
 
3.1%
Other values (134) 1528
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1704
59.2%
Space Separator 473
 
16.4%
Decimal Number 420
 
14.6%
Close Punctuation 90
 
3.1%
Open Punctuation 90
 
3.1%
Other Punctuation 87
 
3.0%
Dash Punctuation 15
 
0.5%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 117
 
6.9%
홀 106
 
6.2%
미 99
 
5.8%
추 99
 
5.8%
동 96
 
5.6%
구 92
 
5.4%
시 90
 
5.3%
역 90
 
5.3%
광 90
 
5.3%
천 90
 
5.3%
Other values (117) 735
43.1%
Decimal Number
ValueCountFrequency (%)
1 78
18.6%
2 59
14.0%
3 58
13.8%
4 42
10.0%
0 39
9.3%
6 33
7.9%
5 30
 
7.1%
8 29
 
6.9%
9 27
 
6.4%
7 25
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 86
98.9%
. 1
 
1.1%
Space Separator
ValueCountFrequency (%)
473
100.0%
Close Punctuation
ValueCountFrequency (%)
) 90
100.0%
Open Punctuation
ValueCountFrequency (%)
( 90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1704
59.2%
Common 1176
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 117
 
6.9%
홀 106
 
6.2%
미 99
 
5.8%
추 99
 
5.8%
동 96
 
5.6%
구 92
 
5.4%
시 90
 
5.3%
역 90
 
5.3%
광 90
 
5.3%
천 90
 
5.3%
Other values (117) 735
43.1%
Common
ValueCountFrequency (%)
473
40.2%
) 90
 
7.7%
( 90
 
7.7%
, 86
 
7.3%
1 78
 
6.6%
2 59
 
5.0%
3 58
 
4.9%
4 42
 
3.6%
0 39
 
3.3%
6 33
 
2.8%
Other values (7) 128
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1704
59.2%
ASCII 1176
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
473
40.2%
) 90
 
7.7%
( 90
 
7.7%
, 86
 
7.3%
1 78
 
6.6%
2 59
 
5.0%
3 58
 
4.9%
4 42
 
3.6%
0 39
 
3.3%
6 33
 
2.8%
Other values (7) 128
 
10.9%
Hangul
ValueCountFrequency (%)
인 117
 
6.9%
홀 106
 
6.2%
미 99
 
5.8%
추 99
 
5.8%
동 96
 
5.6%
구 92
 
5.4%
시 90
 
5.3%
역 90
 
5.3%
광 90
 
5.3%
천 90
 
5.3%
Other values (117) 735
43.1%

지번주소
Text

MISSING 

Distinct84
Distinct (%)97.7%
Missing5
Missing (%)5.5%
Memory size860.0 B
2023-12-12T17:39:40.352070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length32
Mean length24.069767
Min length15

Characters and Unicode

Total characters2070
Distinct characters114
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

Unique82 ?
Unique (%)95.3%

Sample

1st row인천광역시 미추홀구 주안동 1543-11 1543-11,12
2nd row인천광역시 미추홀구 숭의동 105-6
3rd row인천광역시 미추홀구 용현동 492-3
4th row인천광역시 미추홀구 주안동 1436-30 1436-30,31
5th row인천광역시 미추홀구 주안동 1371-1
ValueCountFrequency (%)
인천광역시 86
22.5%
미추홀구 86
22.5%
주안동 41
 
10.7%
용현동 21
 
5.5%
도화동 12
 
3.1%
학익동 8
 
2.1%
0 4
 
1.0%
190-5 2
 
0.5%
숭의동 2
 
0.5%
문학동 2
 
0.5%
Other values (118) 119
31.1%
2023-12-12T17:39:40.846796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
382
18.5%
동 90
 
4.3%
인 88
 
4.3%
홀 88
 
4.3%
미 87
 
4.2%
추 87
 
4.2%
광 86
 
4.2%
역 86
 
4.2%
시 86
 
4.2%
구 86
 
4.2%
Other values (104) 904
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1212
58.6%
Decimal Number 391
 
18.9%
Space Separator 382
 
18.5%
Dash Punctuation 79
 
3.8%
Other Punctuation 4
 
0.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 90
 
7.4%
인 88
 
7.3%
홀 88
 
7.3%
미 87
 
7.2%
추 87
 
7.2%
광 86
 
7.1%
역 86
 
7.1%
시 86
 
7.1%
구 86
 
7.1%
천 86
 
7.1%
Other values (89) 342
28.2%
Decimal Number
ValueCountFrequency (%)
1 83
21.2%
6 49
12.5%
2 48
12.3%
4 41
10.5%
9 40
10.2%
3 33
 
8.4%
5 30
 
7.7%
0 27
 
6.9%
7 23
 
5.9%
8 17
 
4.3%
Space Separator
ValueCountFrequency (%)
382
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1212
58.6%
Common 858
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 90
 
7.4%
인 88
 
7.3%
홀 88
 
7.3%
미 87
 
7.2%
추 87
 
7.2%
광 86
 
7.1%
역 86
 
7.1%
시 86
 
7.1%
구 86
 
7.1%
천 86
 
7.1%
Other values (89) 342
28.2%
Common
ValueCountFrequency (%)
382
44.5%
1 83
 
9.7%
- 79
 
9.2%
6 49
 
5.7%
2 48
 
5.6%
4 41
 
4.8%
9 40
 
4.7%
3 33
 
3.8%
5 30
 
3.5%
0 27
 
3.1%
Other values (5) 46
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1212
58.6%
ASCII 858
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
382
44.5%
1 83
 
9.7%
- 79
 
9.2%
6 49
 
5.7%
2 48
 
5.6%
4 41
 
4.8%
9 40
 
4.7%
3 33
 
3.8%
5 30
 
3.5%
0 27
 
3.1%
Other values (5) 46
 
5.4%
Hangul
ValueCountFrequency (%)
동 90
 
7.4%
인 88
 
7.3%
홀 88
 
7.3%
미 87
 
7.2%
추 87
 
7.2%
광 86
 
7.1%
역 86
 
7.1%
시 86
 
7.1%
구 86
 
7.1%
천 86
 
7.1%
Other values (89) 342
28.2%

전화번호
Text

MISSING 

Distinct31
Distinct (%)96.9%
Missing59
Missing (%)64.8%
Memory size860.0 B
2023-12-12T17:39:41.151452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.09375
Min length12

Characters and Unicode

Total characters387
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

Unique30 ?
Unique (%)93.8%

Sample

1st row032-432-5500
2nd row032-763-9700
3rd row032-868-3355
4th row032-867-7138
5th row032-866-0266
ValueCountFrequency (%)
032-428-1023 2
 
6.2%
032-881-8254 1
 
3.1%
032-432-5500 1
 
3.1%
032-209-9600 1
 
3.1%
032-873-5789 1
 
3.1%
032-889-2226 1
 
3.1%
032-432-5883 1
 
3.1%
032-424-1383 1
 
3.1%
032-888-2017 1
 
3.1%
032-889-2220 1
 
3.1%
Other values (21) 21
65.6%
2023-12-12T17:39:41.587290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 64
16.5%
2 61
15.8%
0 59
15.2%
3 52
13.4%
8 46
11.9%
7 26
6.7%
1 17
 
4.4%
6 17
 
4.4%
9 17
 
4.4%
5 15
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 323
83.5%
Dash Punctuation 64
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 61
18.9%
0 59
18.3%
3 52
16.1%
8 46
14.2%
7 26
8.0%
1 17
 
5.3%
6 17
 
5.3%
9 17
 
5.3%
5 15
 
4.6%
4 13
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 387
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 64
16.5%
2 61
15.8%
0 59
15.2%
3 52
13.4%
8 46
11.9%
7 26
6.7%
1 17
 
4.4%
6 17
 
4.4%
9 17
 
4.4%
5 15
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 387
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 64
16.5%
2 61
15.8%
0 59
15.2%
3 52
13.4%
8 46
11.9%
7 26
6.7%
1 17
 
4.4%
6 17
 
4.4%
9 17
 
4.4%
5 15
 
3.9%

위도
Real number (ℝ)

Distinct87
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.455802
Minimum37.436545
Maximum37.475531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-12T17:39:41.802632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.436545
5-th percentile37.440032
Q137.448194
median37.457067
Q337.463839
95-th percentile37.470196
Maximum37.475531
Range0.03898555
Interquartile range (IQR)0.015645385

Descriptive statistics

Standard deviation0.0093642027
Coefficient of variation (CV)0.00025000674
Kurtosis-0.74076409
Mean37.455802
Median Absolute Deviation (MAD)0.00791305
Skewness0.040888989
Sum3408.4779
Variance8.7688291 × 10-5
MonotonicityNot monotonic
2023-12-12T17:39:42.050607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.45018566 2
 
2.2%
37.45826008 2
 
2.2%
37.46387114 2
 
2.2%
37.45946558 2
 
2.2%
37.46641324 1
 
1.1%
37.45926385 1
 
1.1%
37.44779291 1
 
1.1%
37.46203655 1
 
1.1%
37.46259013 1
 
1.1%
37.46425733 1
 
1.1%
Other values (77) 77
84.6%
ValueCountFrequency (%)
37.43654516 1
1.1%
37.43826067 1
1.1%
37.43926519 1
1.1%
37.43949224 1
1.1%
37.43978679 1
1.1%
37.44027659 1
1.1%
37.44138991 1
1.1%
37.44167383 1
1.1%
37.44234469 1
1.1%
37.44280537 1
1.1%
ValueCountFrequency (%)
37.47553071 1
1.1%
37.47531187 1
1.1%
37.47524526 1
1.1%
37.47033279 1
1.1%
37.47025895 1
1.1%
37.4701339 1
1.1%
37.46994479 1
1.1%
37.46888386 1
1.1%
37.46779195 1
1.1%
37.46676252 1
1.1%

경도
Real number (ℝ)

Distinct87
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.66996
Minimum126.63277
Maximum126.69626
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size951.0 B
2023-12-12T17:39:42.257216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63277
5-th percentile126.63649
Q1126.65808
median126.67545
Q3126.68321
95-th percentile126.69394
Maximum126.69626
Range0.063491
Interquartile range (IQR)0.02513075

Descriptive statistics

Standard deviation0.017667049
Coefficient of variation (CV)0.00013947308
Kurtosis-0.75330923
Mean126.66996
Median Absolute Deviation (MAD)0.0127339
Skewness-0.54971644
Sum11526.966
Variance0.00031212461
MonotonicityNot monotonic
2023-12-12T17:39:42.453732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6332704 2
 
2.2%
126.6426622 2
 
2.2%
126.6943547 2
 
2.2%
126.6797958 2
 
2.2%
126.6789626 1
 
1.1%
126.6738662 1
 
1.1%
126.6492579 1
 
1.1%
126.6962602 1
 
1.1%
126.6807745 1
 
1.1%
126.6822339 1
 
1.1%
Other values (77) 77
84.6%
ValueCountFrequency (%)
126.6327692 1
1.1%
126.6332704 2
2.2%
126.6336714 1
1.1%
126.6356716 1
1.1%
126.6373038 1
1.1%
126.639018 1
1.1%
126.6392488 1
1.1%
126.6407431 1
1.1%
126.6426622 2
2.2%
126.6468659 1
1.1%
ValueCountFrequency (%)
126.6962602 1
1.1%
126.6947749 1
1.1%
126.6945796 1
1.1%
126.6943547 2
2.2%
126.6935278 1
1.1%
126.6916324 1
1.1%
126.6903431 1
1.1%
126.6899021 1
1.1%
126.6898253 1
1.1%
126.6892979 1
1.1%

Interactions

2023-12-12T17:39:37.706962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:39:37.445062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:39:37.816437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:39:37.617076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:39:42.567026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호명도로명주소지번주소전화번호위도경도
상호명1.0001.0000.9941.0000.9410.763
도로명주소1.0001.0001.0001.0001.0001.000
지번주소0.9941.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
위도0.9411.0001.0001.0001.0000.787
경도0.7631.0001.0001.0000.7871.000
2023-12-12T17:39:42.696858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.095
경도0.0951.000

Missing values

2023-12-12T17:39:37.962638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:39:38.081906image/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.
2023-12-12T17:39:38.177710image/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

상호명구분도로명주소지번주소전화번호위도경도
0세종헬스체력단련장업인천광역시 미추홀구 구월로8번길 16 (주안동,1543-11,12)인천광역시 미추홀구 주안동 1543-11 1543-11,12032-432-550037.457067126.691632
1대왕헬스클럽체력단련장업인천광역시 미추홀구 석정로 129 (숭의동)인천광역시 미추홀구 숭의동 105-6032-763-970037.468884126.649674
2CBBM휘트니스센타체력단련장업인천광역시 미추홀구 독정이로 40 (용현동)인천광역시 미추홀구 용현동 492-3<NA>37.459395126.653557
3삼성남녀스포츠센터체력단련장업인천광역시 미추홀구 인하로 255 (주안동,1436-30,31)인천광역시 미추홀구 주안동 1436-30 1436-30,31032-868-335537.448427126.676602
4머신휘트니스체력단련장업인천광역시 미추홀구 경인남길30번길 65, 4층 401호 (용현동, 대동빌딩)<NA><NA>37.451723126.658128
5511GYM체력단련장업인천광역시 미추홀구 한나루로 468 (주안동)인천광역시 미추홀구 주안동 1371-1032-867-713837.448647126.667897
6토크짐주안체력단련장업인천광역시 미추홀구 미추홀대로 725 (주안동)인천광역시 미추홀구 주안동 225-6032-866-026637.462183126.679954
7올림피아헬스체력단련장업인천광역시 미추홀구 경인로 203-12 (도화동, 동아아파트)인천광역시 미추홀구 도화동 601-1 동아아파트032-873-389737.465998126.666282
8유니크휘트니스체력단련장업인천광역시 미추홀구 낙섬서로 4 (용현동,627-287,288,296)인천광역시 미추홀구 용현동 627-287 627-287,288,296032-891-230037.449993126.633671
9FLEX GYM체력단련장업인천광역시 미추홀구 경인로 392 (주안동)인천광역시 미추홀구 주안동 431-1032-428-228037.458034126.68316
상호명구분도로명주소지번주소전화번호위도경도
81Crossfit P4P체력단련장업인천광역시 미추홀구 인하로47번길 71, 백악관빌딩 지하1층 (용현동)인천광역시 미추홀구 용현동 169-12 백악관빌딩<NA>37.453068126.657565
82바디에이프체력단련장업인천광역시 미추홀구 석정로 430, 3층 (주안동)인천광역시 미추홀구 주안동 23-17<NA>37.466374126.683257
83루아크짐체력단련장업인천광역시 미추홀구 송림로 255, 2층 (도화동)인천광역시 미추홀구 도화동 992-4<NA>37.475312126.661346
84와이키키 트레이닝클럽체력단련장업인천광역시 미추홀구 인하로 87-1, 지하1층 (용현동)인천광역시 미추홀구 용현동 190-11<NA>37.450996126.658028
85쎈PT스튜디오체력단련장업인천광역시 미추홀구 숙골로87번길 2, 센타프라자 203호 (도화동)인천광역시 미추홀구 도화동 998-4 센타프라자<NA>37.470134126.66299
86프레임짐체력단련장업인천광역시 미추홀구 경인로 372, 2105호, 2106호 (주안동, 포레나 미추홀)인천광역시 미추홀구 주안동 0 포레나 미추홀<NA>37.458018126.681163
87웨이빗 피트니스체력단련장업인천광역시 미추홀구 미추홀대로 716, 메인프라자 601호,701호 (주안동)인천광역시 미추홀구 주안동 166-1 메인프라자0507-1328-809837.461291126.680592
88크런치핏체력단련장업인천광역시 미추홀구 경원대로 863, 서해빌딩 5층 (주안동)인천광역시 미추홀구 주안동 989-2 서해빌딩<NA>37.45989126.689242
89팀 크루즈체력단련장업인천광역시 미추홀구 인주대로 438, 삼영빌딩 지하1층 (주안동)인천광역시 미추홀구 주안동 1505-2 삼영빌딩<NA>37.450745126.685384
90웰니스짐체력단련장업인천광역시 미추홀구 미추홀대로 695, 인일파크빌딩 9층, 10층 (주안동)인천광역시 미추홀구 주안동 190-5 인혜빌딩<NA>37.459466126.679796