Overview

Dataset statistics

Number of variables18
Number of observations100
Missing cells140
Missing cells (%)7.8%
Duplicate rows4
Duplicate rows (%)4.0%
Total size in memory14.4 KiB
Average record size in memory147.3 B

Variable types

Numeric2
Categorical14
Text2

Alerts

cnslt_lclas_nm has constant value ""Constant
cnslt_ty_nm has constant value ""Constant
tour_purps_nm has constant value ""Constant
cours_nm has constant value ""Constant
cstmr_incln_nm has constant value ""Constant
chnnel_flag_nm has constant value ""Constant
state_nm has constant value ""Constant
Dataset has 4 (4.0%) duplicate rowsDuplicates
cnslt_sclas_nm is highly overall correlated with cnslt_mlsfc_nm and 3 other fieldsHigh correlation
cnslt_mlsfc_nm is highly overall correlated with cnslt_sclas_nm and 3 other fieldsHigh correlation
rcept_de is highly overall correlated with updt_deHigh correlation
updt_de is highly overall correlated with rcept_deHigh correlation
cnslt_kwrd_rn1_nm is highly overall correlated with cnslt_mlsfc_nm and 4 other fieldsHigh correlation
cnslt_kwrd_rn2_nm is highly overall correlated with cnslt_mlsfc_nm and 4 other fieldsHigh correlation
cnslt_kwrd_rn3_nm is highly overall correlated with cnslt_mlsfc_nm and 4 other fieldsHigh correlation
talk_flag_nm is highly overall correlated with cnslt_kwrd_rn1_nm and 2 other fieldsHigh correlation
lang_flag_nm is highly imbalanced (71.4%)Imbalance
cnslt_mlsfc_nm is highly imbalanced (78.9%)Imbalance
cnslt_sclas_nm is highly imbalanced (69.7%)Imbalance
cnslt_kwrd_rn4_nm has 67 (67.0%) missing valuesMissing
cnslt_kwrd_rn5_nm has 73 (73.0%) missing valuesMissing

Reproduction

Analysis started2023-12-10 09:57:53.110297
Analysis finished2023-12-10 09:57:57.750406
Duration4.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

rcept_de
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210713
Minimum20210701
Maximum20210731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:57:57.923841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210701
5-th percentile20210702
Q120210705
median20210709
Q320210720
95-th percentile20210727
Maximum20210731
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.8854438
Coefficient of variation (CV)4.396403 × 10-7
Kurtosis-1.1646378
Mean20210713
Median Absolute Deviation (MAD)6
Skewness0.49120268
Sum2.0210713 × 109
Variance78.951111
MonotonicityNot monotonic
2023-12-10T18:57:58.179747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
20210706 11
 
11.0%
20210704 9
 
9.0%
20210708 8
 
8.0%
20210718 6
 
6.0%
20210702 6
 
6.0%
20210726 5
 
5.0%
20210727 5
 
5.0%
20210703 5
 
5.0%
20210709 4
 
4.0%
20210714 4
 
4.0%
Other values (17) 37
37.0%
ValueCountFrequency (%)
20210701 2
 
2.0%
20210702 6
6.0%
20210703 5
5.0%
20210704 9
9.0%
20210705 4
 
4.0%
20210706 11
11.0%
20210707 2
 
2.0%
20210708 8
8.0%
20210709 4
 
4.0%
20210710 3
 
3.0%
ValueCountFrequency (%)
20210731 1
 
1.0%
20210730 2
 
2.0%
20210728 1
 
1.0%
20210727 5
5.0%
20210726 5
5.0%
20210725 3
3.0%
20210724 3
3.0%
20210722 1
 
1.0%
20210721 3
3.0%
20210720 3
3.0%

lang_flag_nm
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
한국어
95 
영어
 
5

Length

Max length3
Median length3
Mean length2.95
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한국어
2nd row한국어
3rd row영어
4th row한국어
5th row한국어

Common Values

ValueCountFrequency (%)
한국어 95
95.0%
영어 5
 
5.0%

Length

2023-12-10T18:57:58.582251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:58.838933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국어 95
95.0%
영어 5
 
5.0%

cnslt_lclas_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
교통
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교통 100
100.0%

Length

2023-12-10T18:57:59.066964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:59.401423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교통 100
100.0%

cnslt_mlsfc_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
항공&배편
95 
기타
 
3
위치안내
 
2

Length

Max length5
Median length5
Mean length4.89
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row위치안내
2nd row기타
3rd row항공&배편
4th row항공&배편
5th row항공&배편

Common Values

ValueCountFrequency (%)
항공&배편 95
95.0%
기타 3
 
3.0%
위치안내 2
 
2.0%

Length

2023-12-10T18:57:59.715494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:00.003301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
항공&배편 95
95.0%
기타 3
 
3.0%
위치안내 2
 
2.0%

cnslt_sclas_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
도내배편
88 
입도배편
 
5
위치안내
 
2
자전거대여
 
2
항공
 
2

Length

Max length5
Median length4
Mean length3.96
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row위치안내
2nd row자전거대여
3rd row도내배편
4th row도내배편
5th row도내배편

Common Values

ValueCountFrequency (%)
도내배편 88
88.0%
입도배편 5
 
5.0%
위치안내 2
 
2.0%
자전거대여 2
 
2.0%
항공 2
 
2.0%
기타 1
 
1.0%

Length

2023-12-10T18:58:00.267757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:00.540826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도내배편 88
88.0%
입도배편 5
 
5.0%
위치안내 2
 
2.0%
자전거대여 2
 
2.0%
항공 2
 
2.0%
기타 1
 
1.0%

cnslt_kwrd_rn1_nm
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
우도
35 
성산
26 
종달리항
14 
연락처
7 
안내소
5 
Other values (9)
13 

Length

Max length4
Median length2
Mean length2.51
Min length2

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st row소요시간
2nd row대여
3rd row우도
4th row우도
5th row연락처

Common Values

ValueCountFrequency (%)
우도 35
35.0%
성산 26
26.0%
종달리항 14
 
14.0%
연락처 7
 
7.0%
안내소 5
 
5.0%
소요시간 3
 
3.0%
대여 2
 
2.0%
선사 2
 
2.0%
주차장 1
 
1.0%
사전예약 1
 
1.0%
Other values (4) 4
 
4.0%

Length

2023-12-10T18:58:00.813315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
우도 35
35.0%
성산 26
26.0%
종달리항 14
 
14.0%
연락처 7
 
7.0%
안내소 5
 
5.0%
소요시간 3
 
3.0%
대여 2
 
2.0%
선사 2
 
2.0%
주차장 1
 
1.0%
사전예약 1
 
1.0%
Other values (4) 4
 
4.0%

cnslt_kwrd_rn2_nm
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
운항
31 
성산항
18 
성산
12 
우도
8 
<NA>
4 
Other values (17)
27 

Length

Max length4
Median length2
Mean length2.44
Min length2

Unique

Unique8 ?
Unique (%)8.0%

Sample

1st row성산
2nd row자전거
3rd row운항
4th row운항
5th row성산

Common Values

ValueCountFrequency (%)
운항 31
31.0%
성산항 18
18.0%
성산 12
 
12.0%
우도 8
 
8.0%
<NA> 4
 
4.0%
유선 3
 
3.0%
제주 2
 
2.0%
장애인 2
 
2.0%
렌트 2
 
2.0%
연락처 2
 
2.0%
Other values (12) 16
16.0%

Length

2023-12-10T18:58:01.068138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
운항 31
31.0%
성산항 18
18.0%
성산 12
 
12.0%
우도 8
 
8.0%
na 4
 
4.0%
유선 3
 
3.0%
자전거 2
 
2.0%
이용 2
 
2.0%
문자 2
 
2.0%
정상운영 2
 
2.0%
Other values (12) 16
16.0%

cnslt_kwrd_rn3_nm
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
38 
운항
24 
우도
9 
성산항
5 
이용
4 
Other values (16)
20 

Length

Max length4
Median length2
Mean length2.86
Min length2

Unique

Unique13 ?
Unique (%)13.0%

Sample

1st row일출봉
2nd row문자
3rd row<NA>
4th row<NA>
5th row우도

Common Values

ValueCountFrequency (%)
<NA> 38
38.0%
운항 24
24.0%
우도 9
 
9.0%
성산항 5
 
5.0%
이용 4
 
4.0%
문자 3
 
3.0%
선적 2
 
2.0%
유선 2
 
2.0%
드림 1
 
1.0%
오름 1
 
1.0%
Other values (11) 11
 
11.0%

Length

2023-12-10T18:58:01.380996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 38
38.0%
운항 24
24.0%
우도 9
 
9.0%
성산항 5
 
5.0%
이용 4
 
4.0%
문자 3
 
3.0%
선적 2
 
2.0%
유선 2
 
2.0%
제주 1
 
1.0%
일출봉 1
 
1.0%
Other values (11) 11
 
11.0%

cnslt_kwrd_rn4_nm
Text

MISSING 

Distinct18
Distinct (%)54.5%
Missing67
Missing (%)67.0%
Memory size932.0 B
2023-12-10T18:58:01.788865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.6969697
Min length2

Characters and Unicode

Total characters89
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)30.3%

Sample

1st row폭포
2nd row안전
3rd row문자
4th row사려니
5th row면세점
ValueCountFrequency (%)
문자 3
 
9.1%
관광안내소 3
 
9.1%
요금 3
 
9.1%
이용 3
 
9.1%
운항 3
 
9.1%
성산항 3
 
9.1%
제주 3
 
9.1%
종달리항 2
 
6.1%
폭포 1
 
3.0%
관광정보 1
 
3.0%
Other values (8) 8
24.2%
2023-12-10T18:58:02.502593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
항 8
 
9.0%
산 4
 
4.5%
관 4
 
4.5%
광 4
 
4.5%
안 4
 
4.5%
성 4
 
4.5%
운 4
 
4.5%
이 3
 
3.4%
자 3
 
3.4%
용 3
 
3.4%
Other values (30) 48
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
항 8
 
9.0%
산 4
 
4.5%
관 4
 
4.5%
광 4
 
4.5%
안 4
 
4.5%
성 4
 
4.5%
운 4
 
4.5%
이 3
 
3.4%
자 3
 
3.4%
용 3
 
3.4%
Other values (30) 48
53.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
항 8
 
9.0%
산 4
 
4.5%
관 4
 
4.5%
광 4
 
4.5%
안 4
 
4.5%
성 4
 
4.5%
운 4
 
4.5%
이 3
 
3.4%
자 3
 
3.4%
용 3
 
3.4%
Other values (30) 48
53.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
항 8
 
9.0%
산 4
 
4.5%
관 4
 
4.5%
광 4
 
4.5%
안 4
 
4.5%
성 4
 
4.5%
운 4
 
4.5%
이 3
 
3.4%
자 3
 
3.4%
용 3
 
3.4%
Other values (30) 48
53.9%

cnslt_kwrd_rn5_nm
Text

MISSING 

Distinct19
Distinct (%)70.4%
Missing73
Missing (%)73.0%
Memory size932.0 B
2023-12-10T18:58:02.845523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.4814815
Min length2

Characters and Unicode

Total characters67
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)55.6%

Sample

1st row천지연
2nd row관광지
3rd row안전
4th row성산
5th row성산항
ValueCountFrequency (%)
방문 5
18.5%
운항 3
 
11.1%
제주 2
 
7.4%
성산포항 2
 
7.4%
우도 1
 
3.7%
천지연 1
 
3.7%
현장 1
 
3.7%
교통 1
 
3.7%
왕복 1
 
3.7%
서귀포 1
 
3.7%
Other values (9) 9
33.3%
2023-12-10T18:58:03.477653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
항 7
 
10.4%
방 5
 
7.5%
문 5
 
7.5%
성 4
 
6.0%
산 4
 
6.0%
포 3
 
4.5%
주 3
 
4.5%
운 3
 
4.5%
제 2
 
3.0%
안 2
 
3.0%
Other values (26) 29
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
항 7
 
10.4%
방 5
 
7.5%
문 5
 
7.5%
성 4
 
6.0%
산 4
 
6.0%
포 3
 
4.5%
주 3
 
4.5%
운 3
 
4.5%
제 2
 
3.0%
안 2
 
3.0%
Other values (26) 29
43.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
항 7
 
10.4%
방 5
 
7.5%
문 5
 
7.5%
성 4
 
6.0%
산 4
 
6.0%
포 3
 
4.5%
주 3
 
4.5%
운 3
 
4.5%
제 2
 
3.0%
안 2
 
3.0%
Other values (26) 29
43.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
항 7
 
10.4%
방 5
 
7.5%
문 5
 
7.5%
성 4
 
6.0%
산 4
 
6.0%
포 3
 
4.5%
주 3
 
4.5%
운 3
 
4.5%
제 2
 
3.0%
안 2
 
3.0%
Other values (26) 29
43.3%

cnslt_ty_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
일반
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 100
100.0%

Length

2023-12-10T18:58:03.759196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:03.991841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 100
100.0%

tour_purps_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
휴양 및 관광
100 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row휴양 및 관광
2nd row휴양 및 관광
3rd row휴양 및 관광
4th row휴양 및 관광
5th row휴양 및 관광

Common Values

ValueCountFrequency (%)
휴양 및 관광 100
100.0%

Length

2023-12-10T18:58:04.200686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:04.386522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴양 100
33.3%
및 100
33.3%
관광 100
33.3%

cours_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
홈페이지
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
홈페이지 100
100.0%

Length

2023-12-10T18:58:04.596741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:04.786792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
홈페이지 100
100.0%

cstmr_incln_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
일반
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 100
100.0%

Length

2023-12-10T18:58:04.987588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:05.173770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 100
100.0%

chnnel_flag_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전화
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전화 100
100.0%

Length

2023-12-10T18:58:05.396811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:05.562030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전화 100
100.0%

talk_flag_nm
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
인바운드
53 
아웃바운드
47 

Length

Max length5
Median length4
Mean length4.47
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인바운드
2nd row인바운드
3rd row인바운드
4th row아웃바운드
5th row인바운드

Common Values

ValueCountFrequency (%)
인바운드 53
53.0%
아웃바운드 47
47.0%

Length

2023-12-10T18:58:05.748051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:05.945436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인바운드 53
53.0%
아웃바운드 47
47.0%

state_nm
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
완료
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
완료 100
100.0%

Length

2023-12-10T18:58:06.144212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:58:06.326049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완료 100
100.0%

updt_de
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210713
Minimum20210701
Maximum20210731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:58:06.897917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210701
5-th percentile20210702
Q120210706
median20210710
Q320210720
95-th percentile20210727
Maximum20210731
Range30
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation9.1248357
Coefficient of variation (CV)4.5148509 × 10-7
Kurtosis-1.2410155
Mean20210713
Median Absolute Deviation (MAD)6
Skewness0.46059174
Sum2.0210713 × 109
Variance83.262626
MonotonicityNot monotonic
2023-12-10T18:58:07.141196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
20210706 11
 
11.0%
20210704 9
 
9.0%
20210708 8
 
8.0%
20210727 7
 
7.0%
20210718 6
 
6.0%
20210702 6
 
6.0%
20210726 5
 
5.0%
20210705 4
 
4.0%
20210703 4
 
4.0%
20210714 4
 
4.0%
Other values (18) 36
36.0%
ValueCountFrequency (%)
20210701 2
 
2.0%
20210702 6
6.0%
20210703 4
 
4.0%
20210704 9
9.0%
20210705 4
 
4.0%
20210706 11
11.0%
20210707 2
 
2.0%
20210708 8
8.0%
20210709 4
 
4.0%
20210710 3
 
3.0%
ValueCountFrequency (%)
20210731 1
 
1.0%
20210730 2
 
2.0%
20210729 1
 
1.0%
20210728 1
 
1.0%
20210727 7
7.0%
20210726 5
5.0%
20210725 3
3.0%
20210724 3
3.0%
20210722 1
 
1.0%
20210721 1
 
1.0%

Interactions

2023-12-10T18:57:55.138100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:54.722610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:55.358470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:57:54.941192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:58:07.347988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
rcept_delang_flag_nmcnslt_mlsfc_nmcnslt_sclas_nmcnslt_kwrd_rn1_nmcnslt_kwrd_rn2_nmcnslt_kwrd_rn3_nmcnslt_kwrd_rn4_nmcnslt_kwrd_rn5_nmtalk_flag_nmupdt_de
rcept_de1.0000.4780.2640.2700.2110.0000.0000.6130.4580.2560.999
lang_flag_nm0.4781.0000.0000.0000.4110.0000.6790.0000.0000.2150.473
cnslt_mlsfc_nm0.2640.0001.0001.0000.8860.9520.9640.9641.0000.0170.307
cnslt_sclas_nm0.2700.0001.0001.0000.9110.9220.9540.8370.9480.1730.338
cnslt_kwrd_rn1_nm0.2110.4110.8860.9111.0000.8930.8930.8540.8940.7770.244
cnslt_kwrd_rn2_nm0.0000.0000.9520.9220.8931.0000.9470.8540.9170.8180.000
cnslt_kwrd_rn3_nm0.0000.6790.9640.9540.8930.9471.0000.9320.9730.8330.000
cnslt_kwrd_rn4_nm0.6130.0000.9640.8370.8540.8540.9321.0000.9230.6480.000
cnslt_kwrd_rn5_nm0.4580.0001.0000.9480.8940.9170.9730.9231.0001.0000.743
talk_flag_nm0.2560.2150.0170.1730.7770.8180.8330.6481.0001.0000.000
updt_de0.9990.4730.3070.3380.2440.0000.0000.0000.7430.0001.000
2023-12-10T18:58:07.807616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
lang_flag_nmcnslt_kwrd_rn2_nmtalk_flag_nmcnslt_kwrd_rn1_nmcnslt_kwrd_rn3_nmcnslt_sclas_nmcnslt_mlsfc_nm
lang_flag_nm1.0000.0000.1380.3000.4530.0000.000
cnslt_kwrd_rn2_nm0.0001.0000.6690.5380.6460.6620.692
talk_flag_nm0.1380.6691.0000.5860.5750.1190.024
cnslt_kwrd_rn1_nm0.3000.5380.5861.0000.5400.7180.737
cnslt_kwrd_rn3_nm0.4530.6460.5750.5401.0000.7200.769
cnslt_sclas_nm0.0000.6620.1190.7180.7201.0000.984
cnslt_mlsfc_nm0.0000.6920.0240.7370.7690.9841.000
2023-12-10T18:58:08.088966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
rcept_deupdt_delang_flag_nmcnslt_mlsfc_nmcnslt_sclas_nmcnslt_kwrd_rn1_nmcnslt_kwrd_rn2_nmcnslt_kwrd_rn3_nmtalk_flag_nm
rcept_de1.0000.9570.3550.1610.1410.0790.0000.0000.159
updt_de0.9571.0000.3510.1900.1800.0910.0000.0000.000
lang_flag_nm0.3550.3511.0000.0000.0000.3000.0000.4530.138
cnslt_mlsfc_nm0.1610.1900.0001.0000.9840.7370.6920.7690.024
cnslt_sclas_nm0.1410.1800.0000.9841.0000.7180.6620.7200.119
cnslt_kwrd_rn1_nm0.0790.0910.3000.7370.7181.0000.5380.5400.586
cnslt_kwrd_rn2_nm0.0000.0000.0000.6920.6620.5381.0000.6460.669
cnslt_kwrd_rn3_nm0.0000.0000.4530.7690.7200.5400.6461.0000.575
talk_flag_nm0.1590.0000.1380.0240.1190.5860.6690.5751.000

Missing values

2023-12-10T18:57:55.679223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:57:56.835742image/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.
2023-12-10T18:57:57.485849image/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

rcept_delang_flag_nmcnslt_lclas_nmcnslt_mlsfc_nmcnslt_sclas_nmcnslt_kwrd_rn1_nmcnslt_kwrd_rn2_nmcnslt_kwrd_rn3_nmcnslt_kwrd_rn4_nmcnslt_kwrd_rn5_nmcnslt_ty_nmtour_purps_nmcours_nmcstmr_incln_nmchnnel_flag_nmtalk_flag_nmstate_nmupdt_de
020210708한국어교통위치안내위치안내소요시간성산일출봉폭포천지연일반휴양 및 관광홈페이지일반전화인바운드완료20210708
120210725한국어교통기타자전거대여대여자전거문자안전관광지일반휴양 및 관광홈페이지일반전화인바운드완료20210725
220210728영어교통항공&배편도내배편우도운항<NA><NA><NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210728
320210704한국어교통항공&배편도내배편우도운항<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210704
420210704한국어교통항공&배편도내배편연락처성산우도문자안전일반휴양 및 관광홈페이지일반전화인바운드완료20210704
520210709한국어교통위치안내위치안내소요시간숲길오름사려니성산일반휴양 및 관광홈페이지일반전화인바운드완료20210709
620210720한국어교통항공&배편도내배편우도이용시간이용<NA><NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210720
720210720한국어교통기타기타우도이용버스<NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210720
820210718영어교통항공&배편도내배편우도운항<NA><NA><NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210718
920210708한국어교통항공&배편도내배편성산성산항운항<NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210708
rcept_delang_flag_nmcnslt_lclas_nmcnslt_mlsfc_nmcnslt_sclas_nmcnslt_kwrd_rn1_nmcnslt_kwrd_rn2_nmcnslt_kwrd_rn3_nmcnslt_kwrd_rn4_nmcnslt_kwrd_rn5_nmcnslt_ty_nmtour_purps_nmcours_nmcstmr_incln_nmchnnel_flag_nmtalk_flag_nmstate_nmupdt_de
9020210718영어교통항공&배편도내배편우도유선제주관광정보방문일반휴양 및 관광홈페이지일반전화인바운드완료20210718
9120210716한국어교통항공&배편도내배편성산성산항운항<NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210716
9220210718한국어교통항공&배편도내배편우도유선이용운항<NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210718
9320210720한국어교통항공&배편도내배편안내소성산우도관광안내소성산포항일반휴양 및 관광홈페이지일반전화인바운드완료20210720
9420210710한국어교통항공&배편도내배편종달리항운항<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210710
9520210727한국어교통항공&배편도내배편우도장애인숙박이용교통일반휴양 및 관광홈페이지일반전화인바운드완료20210729
9620210727한국어교통항공&배편도내배편우도<NA><NA><NA><NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210727
9720210714한국어교통항공&배편도내배편성산성산항운항<NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210714
9820210724한국어교통항공&배편도내배편안내소성산우도정상운영관광안내소일반휴양 및 관광홈페이지일반전화인바운드완료20210724
9920210713한국어교통항공&배편도내배편종달리항운항<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210713

Duplicate rows

Most frequently occurring

rcept_delang_flag_nmcnslt_lclas_nmcnslt_mlsfc_nmcnslt_sclas_nmcnslt_kwrd_rn1_nmcnslt_kwrd_rn2_nmcnslt_kwrd_rn3_nmcnslt_kwrd_rn4_nmcnslt_kwrd_rn5_nmcnslt_ty_nmtour_purps_nmcours_nmcstmr_incln_nmchnnel_flag_nmtalk_flag_nmstate_nmupdt_de# duplicates
220210708한국어교통항공&배편도내배편성산성산항운항<NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료202107083
020210704한국어교통항공&배편도내배편연락처성산우도성산항방문일반휴양 및 관광홈페이지일반전화인바운드완료202107042
120210704한국어교통항공&배편도내배편우도운항<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료202107042
320210708한국어교통항공&배편도내배편안내소성산우도관광안내소방문일반휴양 및 관광홈페이지일반전화인바운드완료202107082