Overview

Dataset statistics

Number of variables16
Number of observations199
Missing cells1194
Missing cells (%)37.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.8 KiB
Average record size in memory137.7 B

Variable types

Categorical8
Unsupported6
Text1
Numeric1

Dataset

DescriptionSample
Author(주)넥스트이지
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=NXEKWRDWEBANL

Alerts

네이버 has constant value ""Constant
관광지 has constant value ""Constant
카페 has constant value ""Constant
20200228 has constant value ""Constant
20200301 has constant value ""Constant
https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337 is highly overall correlated with 산방산High correlation
산방산 is highly overall correlated with https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337High correlation
Unnamed: 2 has 199 (100.0%) missing valuesMissing
Unnamed: 3 has 199 (100.0%) missing valuesMissing
Unnamed: 4 has 199 (100.0%) missing valuesMissing
Unnamed: 5 has 199 (100.0%) missing valuesMissing
Unnamed: 13 has 199 (100.0%) missing valuesMissing
Unnamed: 14 has 199 (100.0%) missing valuesMissing
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 06:14:00.210156
Analysis finished2023-12-10 06:14:01.329395
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

산방산
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
산방산
110 
용머리해안
45 
중문관광단지
44 

Length

Max length6
Median length3
Mean length4.1155779
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
산방산 110
55.3%
용머리해안 45
22.6%
중문관광단지 44
 
22.1%

Length

2023-12-10T15:14:01.465309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:01.640348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
산방산 110
55.3%
용머리해안 45
22.6%
중문관광단지 44
 
22.1%

네이버
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
네이버
199 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
네이버 199
100.0%

Length

2023-12-10T15:14:01.810649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:01.943390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
네이버 199
100.0%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

관광지
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
관광지
199 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광지 199
100.0%

Length

2023-12-10T15:14:02.086255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:02.242525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광지 199
100.0%

관광지.1
Categorical

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
관광지
76 
키워드
68 
주소지
50 
숙박지
 
3
행사
 
2

Length

Max length3
Median length3
Mean length2.9899497
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광지 76
38.2%
키워드 68
34.2%
주소지 50
25.1%
숙박지 3
 
1.5%
행사 2
 
1.0%

Length

2023-12-10T15:14:02.440006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:02.608730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광지 76
38.2%
키워드 68
34.2%
주소지 50
25.1%
숙박지 3
 
1.5%
행사 2
 
1.0%

카페
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
카페
199 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
카페 199
100.0%

Length

2023-12-10T15:14:02.782499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:02.931049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
카페 199
100.0%

20200228
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
20200228
199 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200228
2nd row20200228
3rd row20200228
4th row20200228
5th row20200228

Common Values

ValueCountFrequency (%)
20200228 199
100.0%

Length

2023-12-10T15:14:03.080285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:03.248613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200228 199
100.0%

20200301
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
20200301
199 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200301
2nd row20200301
3rd row20200301
4th row20200301
5th row20200301

Common Values

ValueCountFrequency (%)
20200301 199
100.0%

Length

2023-12-10T15:14:03.413492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:03.563606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200301 199
100.0%

협재해수욕장
Text

Distinct138
Distinct (%)69.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-10T15:14:04.049532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.0753769
Min length2

Characters and Unicode

Total characters612
Distinct characters181
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

Unique90 ?
Unique (%)45.2%

Sample

1st row산방산
2nd row용머리해안
3rd row송악산
4th row서귀포
5th row중문
ValueCountFrequency (%)
제주신화월드 4
 
2.0%
바다 3
 
1.5%
제주도 3
 
1.5%
여행 3
 
1.5%
중문 3
 
1.5%
서귀 3
 
1.5%
서귀포 3
 
1.5%
전기 3
 
1.5%
펜션 3
 
1.5%
숙소 3
 
1.5%
Other values (128) 168
84.4%
2023-12-10T15:14:04.773362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 37
 
6.0%
포 16
 
2.6%
도 16
 
2.6%
산 13
 
2.1%
해 13
 
2.1%
수 12
 
2.0%
월 12
 
2.0%
주 11
 
1.8%
귀 11
 
1.8%
제 11
 
1.8%
Other values (171) 460
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 608
99.3%
Decimal Number 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 37
 
6.1%
포 16
 
2.6%
도 16
 
2.6%
산 13
 
2.1%
해 13
 
2.1%
수 12
 
2.0%
월 12
 
2.0%
주 11
 
1.8%
귀 11
 
1.8%
제 11
 
1.8%
Other values (169) 456
75.0%
Decimal Number
ValueCountFrequency (%)
3 2
50.0%
4 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 608
99.3%
Common 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 37
 
6.1%
포 16
 
2.6%
도 16
 
2.6%
산 13
 
2.1%
해 13
 
2.1%
수 12
 
2.0%
월 12
 
2.0%
주 11
 
1.8%
귀 11
 
1.8%
제 11
 
1.8%
Other values (169) 456
75.0%
Common
ValueCountFrequency (%)
3 2
50.0%
4 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 608
99.3%
ASCII 4
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 37
 
6.1%
포 16
 
2.6%
도 16
 
2.6%
산 13
 
2.1%
해 13
 
2.1%
수 12
 
2.0%
월 12
 
2.0%
주 11
 
1.8%
귀 11
 
1.8%
제 11
 
1.8%
Other values (169) 456
75.0%
ASCII
ValueCountFrequency (%)
3 2
50.0%
4 2
50.0%

3
Real number (ℝ)

Distinct23
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0301508
Minimum1
Maximum182
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:14:05.016090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q36
95-th percentile21
Maximum182
Range181
Interquartile range (IQR)5

Descriptive statistics

Standard deviation14.204818
Coefficient of variation (CV)2.3556324
Kurtosis120.09409
Mean6.0301508
Median Absolute Deviation (MAD)2
Skewness9.9477273
Sum1200
Variance201.77686
MonotonicityNot monotonic
2023-12-10T15:14:05.210270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 65
32.7%
2 34
17.1%
3 25
 
12.6%
6 14
 
7.0%
4 13
 
6.5%
8 10
 
5.0%
9 7
 
3.5%
21 4
 
2.0%
10 4
 
2.0%
11 3
 
1.5%
Other values (13) 20
 
10.1%
ValueCountFrequency (%)
1 65
32.7%
2 34
17.1%
3 25
 
12.6%
4 13
 
6.5%
6 14
 
7.0%
7 3
 
1.5%
8 10
 
5.0%
9 7
 
3.5%
10 4
 
2.0%
11 3
 
1.5%
ValueCountFrequency (%)
182 1
 
0.5%
42 1
 
0.5%
39 1
 
0.5%
30 1
 
0.5%
28 2
1.0%
25 1
 
0.5%
21 4
2.0%
20 2
1.0%
19 1
 
0.5%
18 1
 
0.5%

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing199
Missing (%)100.0%
Memory size1.9 KiB

https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
https://cafe.naver.com/zootycooncafe/370904
62 
https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551
23 
https://cafe.naver.com/seogwipoguesthouse2/380303
21 
https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337
16 
https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/zootycooncafe/370904
 
7
Other values (27)
70 

Length

Max length462
Median length391
Mean length110.05025
Min length37

Unique

Unique8 ?
Unique (%)4.0%

Sample

1st rowhttps://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/idiolle/1074294^https://cafe.naver.com/cosmania/28492132^https://cafe.naver.com/cafegba/1881698^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/mapomommy/795747^https://cafe.naver.com/zootycooncafe/370904^https://cafe.naver.com/idiolle/1075329
2nd rowhttps://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/idiolle/1075329
3rd rowhttps://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/idiolle/1075329
4th rowhttps://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/idiolle/1074294^https://cafe.naver.com/cosmania/28492132^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/zootycooncafe/370904^https://cafe.naver.com/idiolle/1075329
5th rowhttps://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/zootycooncafe/370904

Common Values

ValueCountFrequency (%)
https://cafe.naver.com/zootycooncafe/370904 62
31.2%
https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551 23
 
11.6%
https://cafe.naver.com/seogwipoguesthouse2/380303 21
 
10.6%
https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337 16
 
8.0%
https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/zootycooncafe/370904 7
 
3.5%
https://cafe.naver.com/hyjnavercom/55548^https://cafe.naver.com/hyjnavercom/55558^https://cafe.naver.com/hyjnavercom/55556^https://cafe.naver.com/hyjnavercom/55563^https://cafe.naver.com/hyjnavercom/55561^https://cafe.naver.com/hyjnavercom/55565^https://cafe.naver.com/hyjnavercom/55666^https://cafe.naver.com/hyjnavercom/55672 7
 
3.5%
https://cafe.naver.com/idiolle/1075329 6
 
3.0%
https://cafe.naver.com/cosmania/28492132 5
 
2.5%
https://cafe.naver.com/hyjnavercom/55548^https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551^https://cafe.naver.com/hyjnavercom/55558^https://cafe.naver.com/hyjnavercom/55556^https://cafe.naver.com/hyjnavercom/55563^https://cafe.naver.com/hyjnavercom/55561^https://cafe.naver.com/hyjnavercom/55565^https://cafe.naver.com/zootycooncafe/370904^https://cafe.naver.com/hyjnavercom/55666^https://cafe.naver.com/hyjnavercom/55672 4
 
2.0%
https://cafe.naver.com/hyjnavercom/55548^https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551^https://cafe.naver.com/hyjnavercom/55558^https://cafe.naver.com/hyjnavercom/55556^https://cafe.naver.com/hyjnavercom/55563^https://cafe.naver.com/hyjnavercom/55561^https://cafe.naver.com/hyjnavercom/55565^https://cafe.naver.com/hyjnavercom/55666^https://cafe.naver.com/hyjnavercom/55672 4
 
2.0%
Other values (22) 44
22.1%

Length

2023-12-10T15:14:05.485103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://cafe.naver.com/zootycooncafe/370904 62
31.2%
https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551 23
 
11.6%
https://cafe.naver.com/seogwipoguesthouse2/380303 21
 
10.6%
https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337 16
 
8.0%
https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/zootycooncafe/370904 7
 
3.5%
https://cafe.naver.com/hyjnavercom/55548^https://cafe.naver.com/hyjnavercom/55558^https://cafe.naver.com/hyjnavercom/55556^https://cafe.naver.com/hyjnavercom/55563^https://cafe.naver.com/hyjnavercom/55561^https://cafe.naver.com/hyjnavercom/55565^https://cafe.naver.com/hyjnavercom/55666^https://cafe.naver.com/hyjnavercom/55672 7
 
3.5%
https://cafe.naver.com/idiolle/1075329 6
 
3.0%
https://cafe.naver.com/cosmania/28492132 5
 
2.5%
https://cafe.naver.com/hyjnavercom/55548^https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551^https://cafe.naver.com/hyjnavercom/55558^https://cafe.naver.com/hyjnavercom/55556^https://cafe.naver.com/hyjnavercom/55563^https://cafe.naver.com/hyjnavercom/55561^https://cafe.naver.com/hyjnavercom/55565^https://cafe.naver.com/zootycooncafe/370904^https://cafe.naver.com/hyjnavercom/55666^https://cafe.naver.com/hyjnavercom/55672 4
 
2.0%
https://cafe.naver.com/hyjnavercom/55548^https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551^https://cafe.naver.com/hyjnavercom/55558^https://cafe.naver.com/hyjnavercom/55556^https://cafe.naver.com/hyjnavercom/55563^https://cafe.naver.com/hyjnavercom/55561^https://cafe.naver.com/hyjnavercom/55565^https://cafe.naver.com/hyjnavercom/55666^https://cafe.naver.com/hyjnavercom/55672 4
 
2.0%
Other values (22) 44
22.1%

Interactions

2023-12-10T15:14:00.618721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:14:05.616405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산방산관광지.13https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337
산방산1.0000.4050.1580.995
관광지.10.4051.0000.0000.719
30.1580.0001.0000.771
https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/3803370.9950.7190.7711.000
2023-12-10T15:14:05.787509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337산방산관광지.1
https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/3803371.0000.9120.408
산방산0.9121.0000.333
관광지.10.4080.3331.000
2023-12-10T15:14:05.938376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
3산방산관광지.1https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337
31.0000.1490.0000.442
산방산0.1491.0000.3330.912
관광지.10.0000.3331.0000.408
https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/3803370.4420.9120.4081.000

Missing values

2023-12-10T15:14:00.819277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:14:01.198612image/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.

Sample

산방산네이버Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5관광지관광지.1카페2020022820200301협재해수욕장3Unnamed: 13Unnamed: 14https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337
0산방산네이버<NA><NA><NA><NA>관광지관광지카페2020022820200301산방산15<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/idiolle/1074294^https://cafe.naver.com/cosmania/28492132^https://cafe.naver.com/cafegba/1881698^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/mapomommy/795747^https://cafe.naver.com/zootycooncafe/370904^https://cafe.naver.com/idiolle/1075329
1산방산네이버<NA><NA><NA><NA>관광지관광지카페2020022820200301용머리해안10<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/idiolle/1075329
2산방산네이버<NA><NA><NA><NA>관광지관광지카페2020022820200301송악산11<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/idiolle/1075329
3산방산네이버<NA><NA><NA><NA>관광지관광지카페2020022820200301서귀포20<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/idiolle/1074294^https://cafe.naver.com/cosmania/28492132^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/zootycooncafe/370904^https://cafe.naver.com/idiolle/1075329
4산방산네이버<NA><NA><NA><NA>관광지관광지카페2020022820200301중문7<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/zootycooncafe/370904
5산방산네이버<NA><NA><NA><NA>관광지관광지카페2020022820200301서귀21<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/idiolle/1074294^https://cafe.naver.com/cosmania/28492132^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337^https://cafe.naver.com/zootycooncafe/370904^https://cafe.naver.com/idiolle/1075329
6산방산네이버<NA><NA><NA><NA>관광지관광지카페2020022820200301차귀도3<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337
7산방산네이버<NA><NA><NA><NA>관광지관광지카페2020022820200301차귀3<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337
8산방산네이버<NA><NA><NA><NA>관광지관광지카페2020022820200301수월봉9<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337
9산방산네이버<NA><NA><NA><NA>관광지관광지카페2020022820200301초콜릿박물관3<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337
산방산네이버Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5관광지관광지.1카페2020022820200301협재해수욕장3Unnamed: 13Unnamed: 14https://cafe.naver.com/seogwipoguesthouse2/380303^https://cafe.naver.com/seogwipoguesthouse2/380339^https://cafe.naver.com/seogwipoguesthouse2/380337
189중문관광단지네이버<NA><NA><NA><NA>관광지키워드카페2020022820200301지연4<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551
190중문관광단지네이버<NA><NA><NA><NA>관광지키워드카페2020022820200301레이2<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551
191중문관광단지네이버<NA><NA><NA><NA>관광지키워드카페2020022820200301전기6<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551
192중문관광단지네이버<NA><NA><NA><NA>관광지키워드카페2020022820200301객실2<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551
193중문관광단지네이버<NA><NA><NA><NA>관광지키워드카페2020022820200301호텔6<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551^https://cafe.naver.com/zootycooncafe/370904
194중문관광단지네이버<NA><NA><NA><NA>관광지키워드카페2020022820200301펜션21<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551^https://cafe.naver.com/zootycooncafe/370904
195중문관광단지네이버<NA><NA><NA><NA>관광지키워드카페2020022820200301바다뷰4<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551
196중문관광단지네이버<NA><NA><NA><NA>관광지키워드카페2020022820200301바다28<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551
197중문관광단지네이버<NA><NA><NA><NA>관광지키워드카페2020022820200301스파4<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551
198중문관광단지네이버<NA><NA><NA><NA>관광지키워드카페2020022820200301바베큐2<NA><NA>https://cafe.naver.com/seogwipoguesthouse2/380306^https://cafe.naver.com/hyjnavercom/55551