Overview

Dataset statistics

Number of variables7
Number of observations282
Missing cells178
Missing cells (%)9.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.1 KiB
Average record size in memory58.5 B

Variable types

Text4
Categorical1
Numeric2

Dataset

Description인천광역시 미추홀구의 당구장 현황에 대한 데이터로 상호명, 도로명주소, 지번주소, 전화번호 등의 정보를 제공하고 있습니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15100728&srcSe=7661IVAWM27C61E190

Alerts

구분 has constant value ""Constant
도로명주소 has 16 (5.7%) missing valuesMissing
지번주소 has 12 (4.3%) missing valuesMissing
전화번호 has 120 (42.6%) missing valuesMissing
위도 has 15 (5.3%) missing valuesMissing
경도 has 15 (5.3%) missing valuesMissing

Reproduction

Analysis started2024-03-18 05:01:53.870279
Analysis finished2024-03-18 05:01:55.853757
Duration1.98 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호명
Text

Distinct249
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-03-18T14:01:56.077926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.9822695
Min length3

Characters and Unicode

Total characters1687
Distinct characters241
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)79.4%

Sample

1st row현대당구장
2nd row호림당구장
3rd row필승당구장
4th row동양당구장
5th row반도당구장
ValueCountFrequency (%)
당구장 24
 
6.8%
당구클럽 23
 
6.5%
sbs당구클럽 7
 
2.0%
sbs당구장 5
 
1.4%
가브리엘 4
 
1.1%
유성당구장 3
 
0.8%
sky당구클럽 3
 
0.8%
클럽 3
 
0.8%
당구 3
 
0.8%
태평양당구장 2
 
0.6%
Other values (254) 276
78.2%
2024-03-18T14:01:56.538198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 271
16.1%
당 267
15.8%
장 186
 
11.0%
클 81
 
4.8%
럽 81
 
4.8%
74
 
4.4%
S 35
 
2.1%
스 30
 
1.8%
대 17
 
1.0%
B 16
 
0.9%
Other values (231) 629
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1462
86.7%
Uppercase Letter 119
 
7.1%
Space Separator 74
 
4.4%
Decimal Number 18
 
1.1%
Other Punctuation 8
 
0.5%
Lowercase Letter 5
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 271
18.5%
당 267
18.3%
장 186
 
12.7%
클 81
 
5.5%
럽 81
 
5.5%
스 30
 
2.1%
대 17
 
1.2%
리 16
 
1.1%
이 14
 
1.0%
아 11
 
0.8%
Other values (200) 488
33.4%
Uppercase Letter
ValueCountFrequency (%)
S 35
29.4%
B 16
13.4%
K 11
 
9.2%
C 11
 
9.2%
J 6
 
5.0%
I 6
 
5.0%
Y 5
 
4.2%
P 5
 
4.2%
V 4
 
3.4%
O 4
 
3.4%
Other values (8) 16
13.4%
Decimal Number
ValueCountFrequency (%)
0 8
44.4%
2 5
27.8%
1 3
 
16.7%
7 1
 
5.6%
5 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 5
62.5%
& 2
 
25.0%
' 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
s 2
40.0%
b 2
40.0%
n 1
20.0%
Space Separator
ValueCountFrequency (%)
74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1462
86.7%
Latin 124
 
7.4%
Common 101
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 271
18.5%
당 267
18.3%
장 186
 
12.7%
클 81
 
5.5%
럽 81
 
5.5%
스 30
 
2.1%
대 17
 
1.2%
리 16
 
1.1%
이 14
 
1.0%
아 11
 
0.8%
Other values (200) 488
33.4%
Latin
ValueCountFrequency (%)
S 35
28.2%
B 16
12.9%
K 11
 
8.9%
C 11
 
8.9%
J 6
 
4.8%
I 6
 
4.8%
Y 5
 
4.0%
P 5
 
4.0%
V 4
 
3.2%
O 4
 
3.2%
Other values (11) 21
16.9%
Common
ValueCountFrequency (%)
74
73.3%
0 8
 
7.9%
2 5
 
5.0%
. 5
 
5.0%
1 3
 
3.0%
& 2
 
2.0%
- 1
 
1.0%
7 1
 
1.0%
' 1
 
1.0%
5 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1462
86.7%
ASCII 225
 
13.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 271
18.5%
당 267
18.3%
장 186
 
12.7%
클 81
 
5.5%
럽 81
 
5.5%
스 30
 
2.1%
대 17
 
1.2%
리 16
 
1.1%
이 14
 
1.0%
아 11
 
0.8%
Other values (200) 488
33.4%
ASCII
ValueCountFrequency (%)
74
32.9%
S 35
15.6%
B 16
 
7.1%
K 11
 
4.9%
C 11
 
4.9%
0 8
 
3.6%
J 6
 
2.7%
I 6
 
2.7%
Y 5
 
2.2%
2 5
 
2.2%
Other values (21) 48
21.3%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
당구장업
282 

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 282
100.0%

Length

2024-03-18T14:01:56.656264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:01:56.747476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당구장업 282
100.0%

도로명주소
Text

MISSING 

Distinct260
Distinct (%)97.7%
Missing16
Missing (%)5.7%
Memory size2.3 KiB
2024-03-18T14:01:56.943028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length28.582707
Min length22

Characters and Unicode

Total characters7603
Distinct characters148
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

Unique255 ?
Unique (%)95.9%

Sample

1st row인천광역시 미추홀구 수봉북로 2 (도화동)
2nd row인천광역시 미추홀구 경인로 392 (주안동)
3rd row인천광역시 미추홀구 석바위로 143 (주안동)
4th row인천광역시 미추홀구 경인로 392 (주안동)
5th row인천광역시 미추홀구 석정로456번길 3 (주안동)
ValueCountFrequency (%)
인천광역시 266
18.1%
미추홀구 266
18.1%
주안동 116
 
7.9%
용현동 61
 
4.2%
3층 41
 
2.8%
도화동 36
 
2.5%
2층 31
 
2.1%
경인로 27
 
1.8%
숭의동 19
 
1.3%
인하로 18
 
1.2%
Other values (342) 588
40.0%
2024-03-18T14:01:57.322742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1340
 
17.6%
인 343
 
4.5%
홀 295
 
3.9%
미 287
 
3.8%
추 285
 
3.7%
동 269
 
3.5%
구 268
 
3.5%
천 268
 
3.5%
광 266
 
3.5%
역 266
 
3.5%
Other values (138) 3716
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4551
59.9%
Space Separator 1340
 
17.6%
Decimal Number 1012
 
13.3%
Close Punctuation 266
 
3.5%
Open Punctuation 266
 
3.5%
Other Punctuation 126
 
1.7%
Dash Punctuation 42
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 343
 
7.5%
홀 295
 
6.5%
미 287
 
6.3%
추 285
 
6.3%
동 269
 
5.9%
구 268
 
5.9%
천 268
 
5.9%
광 266
 
5.8%
역 266
 
5.8%
시 266
 
5.8%
Other values (123) 1738
38.2%
Decimal Number
ValueCountFrequency (%)
1 161
15.9%
2 159
15.7%
3 150
14.8%
4 134
13.2%
5 86
8.5%
7 76
7.5%
0 67
6.6%
6 62
 
6.1%
8 60
 
5.9%
9 57
 
5.6%
Space Separator
ValueCountFrequency (%)
1340
100.0%
Close Punctuation
ValueCountFrequency (%)
) 266
100.0%
Open Punctuation
ValueCountFrequency (%)
( 266
100.0%
Other Punctuation
ValueCountFrequency (%)
, 126
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4551
59.9%
Common 3052
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 343
 
7.5%
홀 295
 
6.5%
미 287
 
6.3%
추 285
 
6.3%
동 269
 
5.9%
구 268
 
5.9%
천 268
 
5.9%
광 266
 
5.8%
역 266
 
5.8%
시 266
 
5.8%
Other values (123) 1738
38.2%
Common
ValueCountFrequency (%)
1340
43.9%
) 266
 
8.7%
( 266
 
8.7%
1 161
 
5.3%
2 159
 
5.2%
3 150
 
4.9%
4 134
 
4.4%
, 126
 
4.1%
5 86
 
2.8%
7 76
 
2.5%
Other values (5) 288
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4551
59.9%
ASCII 3052
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1340
43.9%
) 266
 
8.7%
( 266
 
8.7%
1 161
 
5.3%
2 159
 
5.2%
3 150
 
4.9%
4 134
 
4.4%
, 126
 
4.1%
5 86
 
2.8%
7 76
 
2.5%
Other values (5) 288
 
9.4%
Hangul
ValueCountFrequency (%)
인 343
 
7.5%
홀 295
 
6.5%
미 287
 
6.3%
추 285
 
6.3%
동 269
 
5.9%
구 268
 
5.9%
천 268
 
5.9%
광 266
 
5.8%
역 266
 
5.8%
시 266
 
5.8%
Other values (123) 1738
38.2%

지번주소
Text

MISSING 

Distinct256
Distinct (%)94.8%
Missing12
Missing (%)4.3%
Memory size2.3 KiB
2024-03-18T14:01:57.603508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length32
Mean length22.407407
Min length18

Characters and Unicode

Total characters6050
Distinct characters98
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

Unique244 ?
Unique (%)90.4%

Sample

1st row인천광역시 미추홀구 도화동 633-9
2nd row인천광역시 미추홀구 주안동 1035-16
3rd row인천광역시 미추홀구 주안동 431-1
4th row인천광역시 미추홀구 주안동 989-4
5th row인천광역시 미추홀구 주안동 431-1
ValueCountFrequency (%)
인천광역시 270
24.1%
미추홀구 270
24.1%
주안동 120
 
10.7%
용현동 67
 
6.0%
도화동 38
 
3.4%
숭의동 19
 
1.7%
학익동 17
 
1.5%
문학동 7
 
0.6%
170-3 3
 
0.3%
140-1 3
 
0.3%
Other values (291) 308
27.5%
2024-03-18T14:01:58.083582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1122
18.5%
- 275
 
4.5%
동 272
 
4.5%
미 271
 
4.5%
인 270
 
4.5%
광 270
 
4.5%
역 270
 
4.5%
시 270
 
4.5%
추 270
 
4.5%
홀 270
 
4.5%
Other values (88) 2490
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3379
55.9%
Decimal Number 1265
 
20.9%
Space Separator 1122
 
18.5%
Dash Punctuation 275
 
4.5%
Other Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 272
8.0%
미 271
8.0%
인 270
 
8.0%
광 270
 
8.0%
역 270
 
8.0%
시 270
 
8.0%
추 270
 
8.0%
홀 270
 
8.0%
구 270
 
8.0%
천 270
 
8.0%
Other values (75) 676
20.0%
Decimal Number
ValueCountFrequency (%)
1 263
20.8%
2 180
14.2%
4 124
9.8%
3 124
9.8%
6 114
9.0%
5 108
8.5%
7 99
 
7.8%
0 95
 
7.5%
9 81
 
6.4%
8 77
 
6.1%
Space Separator
ValueCountFrequency (%)
1122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 275
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3379
55.9%
Common 2671
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 272
8.0%
미 271
8.0%
인 270
 
8.0%
광 270
 
8.0%
역 270
 
8.0%
시 270
 
8.0%
추 270
 
8.0%
홀 270
 
8.0%
구 270
 
8.0%
천 270
 
8.0%
Other values (75) 676
20.0%
Common
ValueCountFrequency (%)
1122
42.0%
- 275
 
10.3%
1 263
 
9.8%
2 180
 
6.7%
4 124
 
4.6%
3 124
 
4.6%
6 114
 
4.3%
5 108
 
4.0%
7 99
 
3.7%
0 95
 
3.6%
Other values (3) 167
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3379
55.9%
ASCII 2671
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1122
42.0%
- 275
 
10.3%
1 263
 
9.8%
2 180
 
6.7%
4 124
 
4.6%
3 124
 
4.6%
6 114
 
4.3%
5 108
 
4.0%
7 99
 
3.7%
0 95
 
3.6%
Other values (3) 167
 
6.3%
Hangul
ValueCountFrequency (%)
동 272
8.0%
미 271
8.0%
인 270
 
8.0%
광 270
 
8.0%
역 270
 
8.0%
시 270
 
8.0%
추 270
 
8.0%
홀 270
 
8.0%
구 270
 
8.0%
천 270
 
8.0%
Other values (75) 676
20.0%

전화번호
Text

MISSING 

Distinct160
Distinct (%)98.8%
Missing120
Missing (%)42.6%
Memory size2.3 KiB
2024-03-18T14:01:58.297515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.030864
Min length12

Characters and Unicode

Total characters1949
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

Unique159 ?
Unique (%)98.1%

Sample

1st row032-863-4412
2nd row032-431-2178
3rd row032-422-5514
4th row032-427-2900
5th row032-435-1633
ValueCountFrequency (%)
032-873-5212 3
 
1.9%
032-872-7639 1
 
0.6%
032-258-1515 1
 
0.6%
032-425-8846 1
 
0.6%
032-881-6775 1
 
0.6%
032-891-1237 1
 
0.6%
032-872-6267 1
 
0.6%
032-873-5266 1
 
0.6%
032-425-5516 1
 
0.6%
032-428-1535 1
 
0.6%
Other values (150) 150
92.6%
2024-03-18T14:01:58.664700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 324
16.6%
3 274
14.1%
2 272
14.0%
0 243
12.5%
8 226
11.6%
7 127
 
6.5%
4 119
 
6.1%
6 107
 
5.5%
5 102
 
5.2%
1 78
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1625
83.4%
Dash Punctuation 324
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 274
16.9%
2 272
16.7%
0 243
15.0%
8 226
13.9%
7 127
7.8%
4 119
7.3%
6 107
 
6.6%
5 102
 
6.3%
1 78
 
4.8%
9 77
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 324
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1949
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 324
16.6%
3 274
14.1%
2 272
14.0%
0 243
12.5%
8 226
11.6%
7 127
 
6.5%
4 119
 
6.1%
6 107
 
5.5%
5 102
 
5.2%
1 78
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1949
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 324
16.6%
3 274
14.1%
2 272
14.0%
0 243
12.5%
8 226
11.6%
7 127
 
6.5%
4 119
 
6.1%
6 107
 
5.5%
5 102
 
5.2%
1 78
 
4.0%

위도
Real number (ℝ)

MISSING 

Distinct251
Distinct (%)94.0%
Missing15
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean37.45689
Minimum37.437375
Maximum37.477988
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-18T14:01:58.791186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.437375
5-th percentile37.440163
Q137.451487
median37.458204
Q337.463474
95-th percentile37.467953
Maximum37.477988
Range0.0406126
Interquartile range (IQR)0.011986625

Descriptive statistics

Standard deviation0.0083895296
Coefficient of variation (CV)0.00022397827
Kurtosis-0.16482115
Mean37.45689
Median Absolute Deviation (MAD)0.00582567
Skewness-0.28478115
Sum10000.99
Variance7.0384207 × 10-5
MonotonicityNot monotonic
2024-03-18T14:01:58.908527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.46379042 3
 
1.1%
37.45318459 3
 
1.1%
37.45761615 2
 
0.7%
37.45830369 2
 
0.7%
37.47798768 2
 
0.7%
37.46355341 2
 
0.7%
37.46338033 2
 
0.7%
37.46610539 2
 
0.7%
37.46754729 2
 
0.7%
37.44763845 2
 
0.7%
Other values (241) 245
86.9%
(Missing) 15
 
5.3%
ValueCountFrequency (%)
37.43737508 1
0.4%
37.43759155 1
0.4%
37.43765114 1
0.4%
37.43778893 1
0.4%
37.43803884 1
0.4%
37.43829143 1
0.4%
37.43839975 1
0.4%
37.43856703 1
0.4%
37.43889382 1
0.4%
37.43913243 1
0.4%
ValueCountFrequency (%)
37.47798768 2
0.7%
37.47706783 1
0.4%
37.4762603 1
0.4%
37.47401304 1
0.4%
37.47130713 1
0.4%
37.47047277 1
0.4%
37.47025853 1
0.4%
37.47014679 1
0.4%
37.46982493 1
0.4%
37.46858406 1
0.4%

경도
Real number (ℝ)

MISSING 

Distinct251
Distinct (%)94.0%
Missing15
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean126.66749
Minimum126.63327
Maximum126.70152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-03-18T14:01:59.019849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63327
5-th percentile126.63515
Q1126.6556
median126.67356
Q3126.68078
95-th percentile126.68911
Maximum126.70152
Range0.0682483
Interquartile range (IQR)0.02517975

Descriptive statistics

Standard deviation0.016999787
Coefficient of variation (CV)0.00013420798
Kurtosis-0.83888529
Mean126.66749
Median Absolute Deviation (MAD)0.0112027
Skewness-0.54574515
Sum33820.219
Variance0.00028899275
MonotonicityNot monotonic
2024-03-18T14:01:59.143328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6810625 3
 
1.1%
126.6581578 3
 
1.1%
126.6889988 2
 
0.7%
126.6865718 2
 
0.7%
126.655269 2
 
0.7%
126.6456252 2
 
0.7%
126.6451459 2
 
0.7%
126.6636173 2
 
0.7%
126.6543518 2
 
0.7%
126.6763775 2
 
0.7%
Other values (241) 245
86.9%
(Missing) 15
 
5.3%
ValueCountFrequency (%)
126.6332704 1
0.4%
126.6335634 1
0.4%
126.6336714 1
0.4%
126.6336775 1
0.4%
126.6338533 1
0.4%
126.6339746 1
0.4%
126.634108 1
0.4%
126.6342117 1
0.4%
126.6344363 1
0.4%
126.6344595 1
0.4%
ValueCountFrequency (%)
126.7015187 1
0.4%
126.6943547 1
0.4%
126.6927579 1
0.4%
126.6925199 1
0.4%
126.6906571 1
0.4%
126.6902053 1
0.4%
126.6902005 1
0.4%
126.6898433 1
0.4%
126.6896591 1
0.4%
126.6896191 1
0.4%

Interactions

2024-03-18T14:01:55.354952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:01:55.113387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:01:55.439194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:01:55.273102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:01:59.240897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.771
경도0.7711.000
2024-03-18T14:01:59.314910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.064
경도0.0641.000

Missing values

2024-03-18T14:01:55.538410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:01:55.631312image/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.
2024-03-18T14:01:55.762126image/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
0현대당구장당구장업인천광역시 미추홀구 수봉북로 2 (도화동)인천광역시 미추홀구 도화동 633-9032-863-441237.465395126.663284
1호림당구장당구장업<NA>인천광역시 미추홀구 주안동 1035-16032-431-2178<NA><NA>
2필승당구장당구장업인천광역시 미추홀구 경인로 392 (주안동)인천광역시 미추홀구 주안동 431-1032-422-551437.458034126.68316
3동양당구장당구장업인천광역시 미추홀구 석바위로 143 (주안동)인천광역시 미추홀구 주안동 989-4032-427-290037.459939126.688863
4반도당구장당구장업인천광역시 미추홀구 경인로 392 (주안동)인천광역시 미추홀구 주안동 431-1032-435-163337.458034126.68316
5서흥당구장당구장업인천광역시 미추홀구 석정로456번길 3 (주안동)인천광역시 미추홀구 주안동 22-49032-883-500537.466057126.686341
6은하당구장당구장업인천광역시 미추홀구 염전로 241 (도화동)인천광역시 미추홀구 도화동 53-77032-763-185037.474013126.667938
7제일당구장당구장업인천광역시 미추홀구 제일로 39 (도화동)인천광역시 미추홀구 도화동 442-6032-866-186337.459078126.674615
8럭키당구장당구장업<NA>인천광역시 미추홀구 용현동 492-248032-883-777337.458776126.653891
9동아당구장당구장업인천광역시 미추홀구 토금중로 42 (용현동)인천광역시 미추홀구 용현동 621-150032-884-796737.452475126.63776
상호명구분도로명주소지번주소전화번호위도경도
272메가 빌리어드당구장업인천광역시 미추홀구 낙섬서로 36, 2층 (용현동)인천광역시 미추홀구 용현동 621-22032-225-552537.452583126.635584
273엘큐 당구클럽당구장업인천광역시 미추홀구 숙골로 90, 도화프라자 3층 (도화동)인천광역시 미추홀구 도화동 1006-8 도화프라자070-7443-100937.470473126.663498
274가브리엘 당구클럽당구장업인천광역시 미추홀구 경인로 25, 숭의빌딩 2층 (숭의동)인천광역시 미추홀구 숭의동 160-21 숭의빌딩032-888-394937.463648126.645832
275당구홀릭당구장업인천광역시 미추홀구 석정로 433, 영일빌딩 3층 (주안동)인천광역시 미추홀구 주안동 18-28 영일빌딩<NA>37.466763126.683723
276캐슬당구장당구장업인천광역시 미추홀구 토금남로 12, 3층 (용현동)인천광역시 미추홀구 용현동 630-45<NA>37.45245126.633975
277나이스 당구장당구장업인천광역시 미추홀구 미추홀대로734번길 36, 미진상가 2층 (주안동)인천광역시 미추홀구 주안동 147-1 미진상가<NA>37.462802126.682345
278가브리엘 대대클럽당구장업인천광역시 미추홀구 숙골로95번길 21, 2층 201, 202호 (도화동)인천광역시 미추홀구 도화동 997-3<NA>37.470259126.660479
279수정 당구장당구장업인천광역시 미추홀구 인주대로174번길 12, 2층 (용현동)인천광역시 미추홀구 용현동 141-20<NA>37.455178126.656704
280레포츠당구장당구장업인천광역시 미추홀구 주안로 102-1, 3층 (주안동)인천광역시 미추홀구 주안동 140-1<NA>37.46379126.681062
281캐슬당구장당구장업인천광역시 미추홀구 토금남로 12, 3층 (용현동)인천광역시 미추홀구 용현동 630-45<NA><NA><NA>