Overview

Dataset statistics

Number of variables8
Number of observations55
Missing cells68
Missing cells (%)15.5%
Duplicate rows1
Duplicate rows (%)1.8%
Total size in memory3.8 KiB
Average record size in memory70.4 B

Variable types

Text3
Numeric4
Categorical1

Dataset

Description전라남도 여수시 공영자전거 운영 대여소정보(스테이션ID, 스테이션 주소, 우편번호, 구, 동의 세부 주소, 대여소 위치_위도좌표,경도좌표)등을 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15049735/fileData.do

Alerts

Dataset has 1 (1.8%) duplicate rowsDuplicates
위도좌표 is highly overall correlated with 경도좌표High correlation
경도좌표 is highly overall correlated with 위도좌표 and 1 other fieldsHigh correlation
대여소 번호 is highly overall correlated with 경도좌표High correlation
비콘 아이디 has 10 (18.2%) missing valuesMissing
대여소 이름 has 10 (18.2%) missing valuesMissing
우편번호 has 10 (18.2%) missing valuesMissing
동 has 10 (18.2%) missing valuesMissing
위도좌표 has 10 (18.2%) missing valuesMissing
경도좌표 has 10 (18.2%) missing valuesMissing
대여소 번호 has 8 (14.5%) missing valuesMissing

Reproduction

Analysis started2023-12-12 14:01:31.122462
Analysis finished2023-12-12 14:01:33.169923
Duration2.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

비콘 아이디
Text

MISSING 

Distinct45
Distinct (%)100.0%
Missing10
Missing (%)18.2%
Memory size572.0 B
2023-12-12T23:01:33.352111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters405
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st rowBC_000001
2nd rowBC_000002
3rd rowBC_000003
4th rowBC_000004
5th rowBC_000005
ValueCountFrequency (%)
bc_000011 1
 
2.2%
bc_000025 1
 
2.2%
bc_000026 1
 
2.2%
bc_000027 1
 
2.2%
bc_000028 1
 
2.2%
bc_000029 1
 
2.2%
bc_000030 1
 
2.2%
bc_000031 1
 
2.2%
bc_000032 1
 
2.2%
bc_000033 1
 
2.2%
Other values (35) 35
77.8%
2023-12-12T23:01:33.752731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 193
47.7%
B 45
 
11.1%
C 45
 
11.1%
_ 45
 
11.1%
1 15
 
3.7%
2 15
 
3.7%
3 15
 
3.7%
4 11
 
2.7%
5 5
 
1.2%
6 4
 
1.0%
Other values (3) 12
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 270
66.7%
Uppercase Letter 90
 
22.2%
Connector Punctuation 45
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 193
71.5%
1 15
 
5.6%
2 15
 
5.6%
3 15
 
5.6%
4 11
 
4.1%
5 5
 
1.9%
6 4
 
1.5%
7 4
 
1.5%
8 4
 
1.5%
9 4
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
B 45
50.0%
C 45
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 315
77.8%
Latin 90
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 193
61.3%
_ 45
 
14.3%
1 15
 
4.8%
2 15
 
4.8%
3 15
 
4.8%
4 11
 
3.5%
5 5
 
1.6%
6 4
 
1.3%
7 4
 
1.3%
8 4
 
1.3%
Latin
ValueCountFrequency (%)
B 45
50.0%
C 45
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 405
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 193
47.7%
B 45
 
11.1%
C 45
 
11.1%
_ 45
 
11.1%
1 15
 
3.7%
2 15
 
3.7%
3 15
 
3.7%
4 11
 
2.7%
5 5
 
1.2%
6 4
 
1.0%
Other values (3) 12
 
3.0%

대여소 이름
Text

MISSING 

Distinct45
Distinct (%)100.0%
Missing10
Missing (%)18.2%
Memory size572.0 B
2023-12-12T23:01:34.026421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.5111111
Min length3

Characters and Unicode

Total characters293
Distinct characters116
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

Unique45 ?
Unique (%)100.0%

Sample

1st row신동아 파밀리에 삼거리
2nd row삼일중학교
3rd row부영1단지 사거리
4th row여수시청
5th row전남대정문
ValueCountFrequency (%)
돌산 2
 
3.3%
주민센터 2
 
3.3%
웅천 2
 
3.3%
소호요트경기장 1
 
1.6%
둔덕삼거리 1
 
1.6%
여수해양경찰서앞 1
 
1.6%
미평공원 1
 
1.6%
내동마을입구 1
 
1.6%
만흥공원 1
 
1.6%
가곡마을입구 1
 
1.6%
Other values (48) 48
78.7%
2023-12-12T23:01:34.462067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
 
5.5%
공 12
 
4.1%
여 12
 
4.1%
원 11
 
3.8%
동 8
 
2.7%
리 8
 
2.7%
수 8
 
2.7%
터 7
 
2.4%
거 7
 
2.4%
구 7
 
2.4%
Other values (106) 197
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 270
92.2%
Space Separator 16
 
5.5%
Decimal Number 3
 
1.0%
Uppercase Letter 2
 
0.7%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 12
 
4.4%
여 12
 
4.4%
원 11
 
4.1%
동 8
 
3.0%
리 8
 
3.0%
수 8
 
3.0%
터 7
 
2.6%
거 7
 
2.6%
구 7
 
2.6%
장 6
 
2.2%
Other values (99) 184
68.1%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 270
92.2%
Common 21
 
7.2%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 12
 
4.4%
여 12
 
4.4%
원 11
 
4.1%
동 8
 
3.0%
리 8
 
3.0%
수 8
 
3.0%
터 7
 
2.6%
거 7
 
2.6%
구 7
 
2.6%
장 6
 
2.2%
Other values (99) 184
68.1%
Common
ValueCountFrequency (%)
16
76.2%
1 2
 
9.5%
2 1
 
4.8%
( 1
 
4.8%
) 1
 
4.8%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 270
92.2%
ASCII 23
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
69.6%
1 2
 
8.7%
2 1
 
4.3%
( 1
 
4.3%
) 1
 
4.3%
K 1
 
4.3%
T 1
 
4.3%
Hangul
ValueCountFrequency (%)
공 12
 
4.4%
여 12
 
4.4%
원 11
 
4.1%
동 8
 
3.0%
리 8
 
3.0%
수 8
 
3.0%
터 7
 
2.6%
거 7
 
2.6%
구 7
 
2.6%
장 6
 
2.2%
Other values (99) 184
68.1%

우편번호
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)75.6%
Missing10
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean431910.04
Minimum59633
Maximum556811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T23:01:34.630507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum59633
5-th percentile59672.8
Q1550010
median550220
Q3555010
95-th percentile555106
Maximum556811
Range497178
Interquartile range (IQR)5000

Descriptive statistics

Standard deviation214113.96
Coefficient of variation (CV)0.49573739
Kurtosis-0.51038943
Mean431910.04
Median Absolute Deviation (MAD)4790
Skewness-1.2303467
Sum19435952
Variance4.5844788 × 1010
MonotonicityNot monotonic
2023-12-12T23:01:34.784246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
555010 6
 
10.9%
550833 3
 
5.5%
555070 2
 
3.6%
555060 2
 
3.6%
550210 2
 
3.6%
550030 2
 
3.6%
59633 1
 
1.8%
59718 1
 
1.8%
59649 1
 
1.8%
59695 1
 
1.8%
Other values (24) 24
43.6%
(Missing) 10
18.2%
ValueCountFrequency (%)
59633 1
1.8%
59649 1
1.8%
59672 1
1.8%
59676 1
1.8%
59695 1
1.8%
59697 1
1.8%
59713 1
1.8%
59718 1
1.8%
59735 1
1.8%
59760 1
1.8%
ValueCountFrequency (%)
556811 1
 
1.8%
555707 1
 
1.8%
555110 1
 
1.8%
555090 1
 
1.8%
555070 2
 
3.6%
555060 2
 
3.6%
555010 6
10.9%
550833 3
5.5%
550818 1
 
1.8%
550800 1
 
1.8%

구
Categorical

Distinct3
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
여수시
44 
<NA>
10 
여수시
 
1

Length

Max length4
Median length3
Mean length3.2
Min length3

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
여수시 44
80.0%
<NA> 10
 
18.2%
여수시 1
 
1.8%

Length

2023-12-12T23:01:34.922484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:01:35.034486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여수시 45
81.8%
na 10
 
18.2%

동
Text

MISSING 

Distinct24
Distinct (%)53.3%
Missing10
Missing (%)18.2%
Memory size572.0 B
2023-12-12T23:01:35.192626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8222222
Min length2

Characters and Unicode

Total characters127
Distinct characters42
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)28.9%

Sample

1st row학동
2nd row소라면
3rd row학동
4th row학동
5th row미평동
ValueCountFrequency (%)
학동 8
17.8%
돌산읍 4
 
8.9%
오림동 3
 
6.7%
웅천동 3
 
6.7%
소호동 2
 
4.4%
소라면 2
 
4.4%
둔덕동 2
 
4.4%
선원동 2
 
4.4%
미평동 2
 
4.4%
수정동 2
 
4.4%
Other values (14) 15
33.3%
2023-12-12T23:01:35.545946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 39
30.7%
학 8
 
6.3%
산 5
 
3.9%
소 4
 
3.1%
천 4
 
3.1%
읍 4
 
3.1%
돌 4
 
3.1%
오 3
 
2.4%
림 3
 
2.4%
웅 3
 
2.4%
Other values (32) 50
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126
99.2%
Decimal Number 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 39
31.0%
학 8
 
6.3%
산 5
 
4.0%
소 4
 
3.2%
천 4
 
3.2%
읍 4
 
3.2%
돌 4
 
3.2%
오 3
 
2.4%
림 3
 
2.4%
웅 3
 
2.4%
Other values (31) 49
38.9%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 126
99.2%
Common 1
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 39
31.0%
학 8
 
6.3%
산 5
 
4.0%
소 4
 
3.2%
천 4
 
3.2%
읍 4
 
3.2%
돌 4
 
3.2%
오 3
 
2.4%
림 3
 
2.4%
웅 3
 
2.4%
Other values (31) 49
38.9%
Common
ValueCountFrequency (%)
4 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 126
99.2%
ASCII 1
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 39
31.0%
학 8
 
6.3%
산 5
 
4.0%
소 4
 
3.2%
천 4
 
3.2%
읍 4
 
3.2%
돌 4
 
3.2%
오 3
 
2.4%
림 3
 
2.4%
웅 3
 
2.4%
Other values (31) 49
38.9%
ASCII
ValueCountFrequency (%)
4 1
100.0%

위도좌표
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct45
Distinct (%)100.0%
Missing10
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean92.585562
Minimum34.715063
Maximum127.7661
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T23:01:35.703686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.715063
5-th percentile34.721991
Q134.763452
median127.65748
Q3127.71743
95-th percentile127.7481
Maximum127.7661
Range93.051041
Interquartile range (IQR)92.953975

Descriptive statistics

Standard deviation45.573365
Coefficient of variation (CV)0.49222972
Kurtosis-1.8103507
Mean92.585562
Median Absolute Deviation (MAD)0.086132
Skewness-0.52173803
Sum4166.3503
Variance2076.9316
MonotonicityNot monotonic
2023-12-12T23:01:35.853805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
34.721369 1
 
1.8%
127.707884 1
 
1.8%
127.70358 1
 
1.8%
127.718871 1
 
1.8%
127.743796 1
 
1.8%
127.6613 1
 
1.8%
127.6524 1
 
1.8%
34.746957 1
 
1.8%
34.799744 1
 
1.8%
34.769403 1
 
1.8%
Other values (35) 35
63.6%
(Missing) 10
 
18.2%
ValueCountFrequency (%)
34.715063 1
1.8%
34.717367 1
1.8%
34.721369 1
1.8%
34.724479 1
1.8%
34.739116 1
1.8%
34.740266 1
1.8%
34.745233 1
1.8%
34.746957 1
1.8%
34.747621 1
1.8%
34.749449 1
1.8%
ValueCountFrequency (%)
127.766104 1
1.8%
127.750531 1
1.8%
127.748943 1
1.8%
127.744732 1
1.8%
127.743796 1
1.8%
127.743617 1
1.8%
127.735601 1
1.8%
127.725903 1
1.8%
127.724427 1
1.8%
127.718871 1
1.8%

경도좌표
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct45
Distinct (%)100.0%
Missing10
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean69.866678
Minimum34.728214
Maximum127.75376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T23:01:35.994758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.728214
5-th percentile34.732549
Q134.753196
median34.768252
Q3127.68309
95-th percentile127.74666
Maximum127.75376
Range93.025548
Interquartile range (IQR)92.929896

Descriptive statistics

Standard deviation45.571807
Coefficient of variation (CV)0.65226813
Kurtosis-1.8103497
Mean69.866678
Median Absolute Deviation (MAD)0.028973
Skewness0.52173975
Sum3144.0005
Variance2076.7896
MonotonicityNot monotonic
2023-12-12T23:01:36.146385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
127.751525 1
 
1.8%
34.755577 1
 
1.8%
34.768252 1
 
1.8%
34.760552 1
 
1.8%
34.772974 1
 
1.8%
34.7685 1
 
1.8%
34.777 1
 
1.8%
127.728012 1
 
1.8%
127.631796 1
 
1.8%
127.694703 1
 
1.8%
Other values (35) 35
63.6%
(Missing) 10
 
18.2%
ValueCountFrequency (%)
34.728214 1
1.8%
34.729844 1
1.8%
34.731041 1
1.8%
34.73858 1
1.8%
34.738972 1
1.8%
34.739279 1
1.8%
34.743085 1
1.8%
34.745659 1
1.8%
34.746303 1
1.8%
34.747158 1
1.8%
ValueCountFrequency (%)
127.753762 1
1.8%
127.751525 1
1.8%
127.747113 1
1.8%
127.744873 1
1.8%
127.732377 1
1.8%
127.728012 1
1.8%
127.709385 1
1.8%
127.700318 1
1.8%
127.695261 1
1.8%
127.694703 1
1.8%

대여소 번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct45
Distinct (%)95.7%
Missing8
Missing (%)14.5%
Infinite0
Infinite (%)0.0%
Mean23.361702
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T23:01:36.294698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.3
Q112.5
median24
Q333.5
95-th percentile42.7
Maximum45
Range44
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.962195
Coefficient of variation (CV)0.55484806
Kurtosis-1.1724585
Mean23.361702
Median Absolute Deviation (MAD)11
Skewness-0.074519042
Sum1098
Variance168.0185
MonotonicityNot monotonic
2023-12-12T23:01:36.446206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
31 2
 
3.6%
32 2
 
3.6%
35 1
 
1.8%
26 1
 
1.8%
27 1
 
1.8%
28 1
 
1.8%
29 1
 
1.8%
30 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
Other values (35) 35
63.6%
(Missing) 8
 
14.5%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
45 1
1.8%
44 1
1.8%
43 1
1.8%
42 1
1.8%
41 1
1.8%
40 1
1.8%
39 1
1.8%
38 1
1.8%
37 1
1.8%
36 1
1.8%

Interactions

2023-12-12T23:01:32.256348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:31.455314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:31.747057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:32.007534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:32.318114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:31.522830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:31.813439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:32.069840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:32.379502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:31.601623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:31.882269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:32.130883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:32.446133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:31.675303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:31.946185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:01:32.196701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:01:36.549042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비콘 아이디대여소 이름우편번호구동위도좌표경도좌표대여소 번호
비콘 아이디1.0001.0001.0001.0001.0001.0001.0001.000
대여소 이름1.0001.0001.0001.0001.0001.0001.0001.000
우편번호1.0001.0001.0000.0000.0000.5620.5620.693
구1.0001.0000.0001.0000.0000.0000.0000.000
동1.0001.0000.0000.0001.0000.7180.7180.807
위도좌표1.0001.0000.5620.0000.7181.0000.9970.979
경도좌표1.0001.0000.5620.0000.7180.9971.0000.979
대여소 번호1.0001.0000.6930.0000.8070.9790.9791.000
2023-12-12T23:01:36.661140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호위도좌표경도좌표대여소 번호구
우편번호1.000-0.059-0.170-0.2680.000
위도좌표-0.0591.000-0.845-0.4780.000
경도좌표-0.170-0.8451.0000.5860.000
대여소 번호-0.268-0.4780.5861.0000.000
구0.0000.0000.0000.0001.000

Missing values

2023-12-12T23:01:32.533161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:01:32.636149image/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.
2023-12-12T23:01:33.061423image/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

비콘 아이디대여소 이름우편번호구동위도좌표경도좌표대여소 번호
0BC_000001신동아 파밀리에 삼거리59672여수시학동34.766384127.6565831
1BC_000002삼일중학교556811여수시소라면34.763452127.6399852
2BC_000003부영1단지 사거리555010여수시학동127.65631634.7606453
3BC_000004여수시청555010여수시학동127.6630134.7606274
4BC_000005전남대정문550240여수시미평동127.70123434.7734745
5BC_000006거북선공원(흥국체육관)555010여수시학동127.66744134.759796
6BC_000007망마경기장555010여수시학동127.67882534.7583887
7BC_000008선소입구공원555010여수시학동127.66411534.7563968
8BC_000009장성삼거리입구 공원555010여수시학동127.65748534.7558949
9BC_000010소호회센터555060여수시소호동127.65367134.74565910
비콘 아이디대여소 이름우편번호구동위도좌표경도좌표대여소 번호
45<NA><NA><NA><NA><NA><NA><NA><NA>
46<NA><NA><NA><NA><NA><NA><NA><NA>
47<NA><NA><NA><NA><NA><NA><NA><NA>
48<NA><NA><NA><NA><NA><NA><NA><NA>
49<NA><NA><NA><NA><NA><NA><NA><NA>
50<NA><NA><NA><NA><NA><NA><NA><NA>
51<NA><NA><NA><NA><NA><NA><NA><NA>
52<NA><NA><NA><NA><NA><NA><NA><NA>
53<NA><NA><NA><NA><NA><NA><NA>31
54<NA><NA><NA><NA><NA><NA><NA>32

Duplicate rows

Most frequently occurring

비콘 아이디대여소 이름우편번호구동위도좌표경도좌표대여소 번호# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA>8