Overview

Dataset statistics

Number of variables18
Number of observations100
Missing cells122
Missing cells (%)6.8%
Duplicate rows8
Duplicate rows (%)8.0%
Total size in memory14.4 KiB
Average record size in memory147.3 B

Variable types

Numeric2
Categorical14
Text2

Alerts

lang_flag_nm has constant value ""Constant
cnslt_lclas_nm has constant value ""Constant
cnslt_mlsfc_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 8 (8.0%) duplicate rowsDuplicates
cnslt_ty_nm is highly overall correlated with cnslt_kwrd_rn1_nm and 2 other fieldsHigh correlation
cnslt_kwrd_rn2_nm is highly overall correlated with cnslt_ty_nm and 1 other fieldsHigh correlation
cnslt_kwrd_rn1_nm is highly overall correlated with cnslt_sclas_nm and 3 other fieldsHigh correlation
cnslt_kwrd_rn3_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_sclas_nm is highly overall correlated with cnslt_kwrd_rn1_nm and 1 other fieldsHigh correlation
talk_flag_nm is highly overall correlated with cnslt_kwrd_rn1_nm and 2 other fieldsHigh correlation
cnslt_ty_nm is highly imbalanced (91.9%)Imbalance
cnslt_kwrd_rn4_nm has 57 (57.0%) missing valuesMissing
cnslt_kwrd_rn5_nm has 65 (65.0%) missing valuesMissing

Reproduction

Analysis started2023-12-10 09:50:28.595606
Analysis finished2023-12-10 09:50:31.796513
Duration3.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

rcept_de
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210457
Minimum20210201
Maximum20210724
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:50:31.909865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210201
5-th percentile20210202
Q120210406
median20210413
Q320210427
95-th percentile20210708
Maximum20210724
Range523
Interquartile range (IQR)21

Descriptive statistics

Standard deviation146.91415
Coefficient of variation (CV)7.2692147 × 10-6
Kurtosis-0.2001728
Mean20210457
Median Absolute Deviation (MAD)7
Skewness0.61036851
Sum2.0210457 × 109
Variance21583.768
MonotonicityNot monotonic
2023-12-10T18:50:32.129976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20210406 16
16.0%
20210413 12
12.0%
20210702 10
10.0%
20210407 8
 
8.0%
20210405 8
 
8.0%
20210416 5
 
5.0%
20210420 5
 
5.0%
20210202 5
 
5.0%
20210706 4
 
4.0%
20210425 3
 
3.0%
Other values (21) 24
24.0%
ValueCountFrequency (%)
20210201 1
 
1.0%
20210202 5
 
5.0%
20210210 1
 
1.0%
20210221 1
 
1.0%
20210223 1
 
1.0%
20210226 1
 
1.0%
20210405 8
8.0%
20210406 16
16.0%
20210407 8
8.0%
20210408 1
 
1.0%
ValueCountFrequency (%)
20210724 1
 
1.0%
20210722 1
 
1.0%
20210721 1
 
1.0%
20210720 1
 
1.0%
20210714 1
 
1.0%
20210708 1
 
1.0%
20210707 1
 
1.0%
20210706 4
 
4.0%
20210705 1
 
1.0%
20210702 10
10.0%

lang_flag_nm
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한국어 100
100.0%

Length

2023-12-10T18:50:32.340122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:32.486457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국어 100
100.0%

cnslt_lclas_nm
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
음식 100
100.0%

Length

2023-12-10T18:50:32.643618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:32.810178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식 100
100.0%

cnslt_mlsfc_nm
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
음식 100
100.0%

Length

2023-12-10T18:50:32.966068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:33.113822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음식 100
100.0%

cnslt_sclas_nm
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
향토음식
49 
한식
39 
카페
10 
양식
 
1
기타
 
1

Length

Max length4
Median length2
Mean length2.98
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
향토음식 49
49.0%
한식 39
39.0%
카페 10
 
10.0%
양식 1
 
1.0%
기타 1
 
1.0%

Length

2023-12-10T18:50:33.308666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:33.514656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
향토음식 49
49.0%
한식 39
39.0%
카페 10
 
10.0%
양식 1
 
1.0%
기타 1
 
1.0%

cnslt_kwrd_rn1_nm
Categorical

HIGH CORRELATION 

Distinct39
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
외국어
18 
음식점
7 
<NA>
7 
이용
 
5
해녀
 
5
Other values (34)
58 

Length

Max length4
Median length3
Mean length2.84
Min length2

Unique

Unique18 ?
Unique (%)18.0%

Sample

1st row카페
2nd row식당
3rd row사전예약
4th row외국인
5th row<NA>

Common Values

ValueCountFrequency (%)
외국어 18
18.0%
음식점 7
 
7.0%
<NA> 7
 
7.0%
이용 5
 
5.0%
해녀 5
 
5.0%
연락처 4
 
4.0%
이용시간 4
 
4.0%
휴무일 3
 
3.0%
식당 3
 
3.0%
인원 3
 
3.0%
Other values (29) 41
41.0%

Length

2023-12-10T18:50:33.741561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
외국어 18
18.0%
na 7
 
7.0%
음식점 7
 
7.0%
이용 5
 
5.0%
해녀 5
 
5.0%
연락처 4
 
4.0%
이용시간 4
 
4.0%
휴무일 3
 
3.0%
식당 3
 
3.0%
인원 3
 
3.0%
Other values (29) 41
41.0%

cnslt_kwrd_rn2_nm
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
20 
이용
16 
문자
8 
운영시간
7 
이용시간
 
4
Other values (30)
45 

Length

Max length5
Median length4
Mean length2.92
Min length2

Unique

Unique20 ?
Unique (%)20.0%

Sample

1st row이용시간
2nd row맑은
3rd row운영시간
4th row공지
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 20
20.0%
이용 16
16.0%
문자 8
 
8.0%
운영시간 7
 
7.0%
이용시간 4
 
4.0%
유선 3
 
3.0%
중문 3
 
3.0%
비자림 3
 
3.0%
음식점 3
 
3.0%
제주 3
 
3.0%
Other values (25) 30
30.0%

Length

2023-12-10T18:50:34.067794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 20
20.0%
이용 16
16.0%
문자 8
 
8.0%
운영시간 7
 
7.0%
이용시간 4
 
4.0%
유선 3
 
3.0%
중문 3
 
3.0%
비자림 3
 
3.0%
음식점 3
 
3.0%
제주 3
 
3.0%
Other values (25) 30
30.0%

cnslt_kwrd_rn3_nm
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
47 
이용
10 
식당
9 
이용시간
5 
음식점
 
3
Other values (22)
26 

Length

Max length4
Median length4
Mean length3.21
Min length2

Unique

Unique19 ?
Unique (%)19.0%

Sample

1st row이용
2nd row<NA>
3rd row<NA>
4th row이용시간
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 47
47.0%
이용 10
 
10.0%
식당 9
 
9.0%
이용시간 5
 
5.0%
음식점 3
 
3.0%
문자 3
 
3.0%
체험 2
 
2.0%
산방산 2
 
2.0%
유선 1
 
1.0%
만장굴 1
 
1.0%
Other values (17) 17
 
17.0%

Length

2023-12-10T18:50:34.778034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 47
47.0%
이용 10
 
10.0%
식당 9
 
9.0%
이용시간 5
 
5.0%
음식점 3
 
3.0%
문자 3
 
3.0%
체험 2
 
2.0%
산방산 2
 
2.0%
호텔 1
 
1.0%
흑돼지 1
 
1.0%
Other values (17) 17
 
17.0%

cnslt_kwrd_rn4_nm
Text

MISSING 

Distinct25
Distinct (%)58.1%
Missing57
Missing (%)57.0%
Memory size932.0 B
2023-12-10T18:50:35.073982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.4418605
Min length2

Characters and Unicode

Total characters105
Distinct characters51
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

Unique16 ?
Unique (%)37.2%

Sample

1st row이용
2nd row보관함
3rd row맛집
4th row마을
5th row유선
ValueCountFrequency (%)
이용 8
18.6%
음식점 3
 
7.0%
천제연 3
 
7.0%
말고기 3
 
7.0%
이용시간 2
 
4.7%
한림 2
 
4.7%
마을 2
 
4.7%
식당 2
 
4.7%
문자 2
 
4.7%
유선 1
 
2.3%
Other values (15) 15
34.9%
2023-12-10T18:50:35.670857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 10
 
9.5%
용 10
 
9.5%
식 5
 
4.8%
기 4
 
3.8%
제 4
 
3.8%
점 3
 
2.9%
연 3
 
2.9%
천 3
 
2.9%
음 3
 
2.9%
고 3
 
2.9%
Other values (41) 57
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 10
 
9.5%
용 10
 
9.5%
식 5
 
4.8%
기 4
 
3.8%
제 4
 
3.8%
점 3
 
2.9%
연 3
 
2.9%
천 3
 
2.9%
음 3
 
2.9%
고 3
 
2.9%
Other values (41) 57
54.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 10
 
9.5%
용 10
 
9.5%
식 5
 
4.8%
기 4
 
3.8%
제 4
 
3.8%
점 3
 
2.9%
연 3
 
2.9%
천 3
 
2.9%
음 3
 
2.9%
고 3
 
2.9%
Other values (41) 57
54.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 10
 
9.5%
용 10
 
9.5%
식 5
 
4.8%
기 4
 
3.8%
제 4
 
3.8%
점 3
 
2.9%
연 3
 
2.9%
천 3
 
2.9%
음 3
 
2.9%
고 3
 
2.9%
Other values (41) 57
54.3%

cnslt_kwrd_rn5_nm
Text

MISSING 

Distinct22
Distinct (%)62.9%
Missing65
Missing (%)65.0%
Memory size932.0 B
2023-12-10T18:50:35.980685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.4285714
Min length2

Characters and Unicode

Total characters85
Distinct characters44
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 (%)42.9%

Sample

1st row방문
2nd row커피
3rd row횟집
4th row제주
5th row식당
ValueCountFrequency (%)
제주 5
14.3%
말고기 3
 
8.6%
서귀포 3
 
8.6%
이용 3
 
8.6%
유선 2
 
5.7%
폭포 2
 
5.7%
식당 2
 
5.7%
방문 1
 
2.9%
관광지 1
 
2.9%
관광안내소 1
 
2.9%
Other values (12) 12
34.3%
2023-12-10T18:50:36.546043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 6
 
7.1%
제 5
 
5.9%
포 5
 
5.9%
기 4
 
4.7%
이 3
 
3.5%
용 3
 
3.5%
말 3
 
3.5%
고 3
 
3.5%
서 3
 
3.5%
귀 3
 
3.5%
Other values (34) 47
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 85
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 6
 
7.1%
제 5
 
5.9%
포 5
 
5.9%
기 4
 
4.7%
이 3
 
3.5%
용 3
 
3.5%
말 3
 
3.5%
고 3
 
3.5%
서 3
 
3.5%
귀 3
 
3.5%
Other values (34) 47
55.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 85
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 6
 
7.1%
제 5
 
5.9%
포 5
 
5.9%
기 4
 
4.7%
이 3
 
3.5%
용 3
 
3.5%
말 3
 
3.5%
고 3
 
3.5%
서 3
 
3.5%
귀 3
 
3.5%
Other values (34) 47
55.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 85
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 6
 
7.1%
제 5
 
5.9%
포 5
 
5.9%
기 4
 
4.7%
이 3
 
3.5%
용 3
 
3.5%
말 3
 
3.5%
고 3
 
3.5%
서 3
 
3.5%
귀 3
 
3.5%
Other values (34) 47
55.3%

cnslt_ty_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
일반
99 
자동저장
 
1

Length

Max length4
Median length2
Mean length2.02
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 99
99.0%
자동저장 1
 
1.0%

Length

2023-12-10T18:50:36.825273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:36.997466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 99
99.0%
자동저장 1
 
1.0%

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

2023-12-10T18:50:37.173926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:37.367253image/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

2023-12-10T18:50:37.571375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:37.791550image/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

2023-12-10T18:50:38.063650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:38.237099image/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

2023-12-10T18:50:38.449244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:38.635169image/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
아웃바운드
70 
인바운드
30 

Length

Max length5
Median length5
Mean length4.7
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아웃바운드 70
70.0%
인바운드 30
30.0%

Length

2023-12-10T18:50:38.842878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:39.076686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아웃바운드 70
70.0%
인바운드 30
30.0%

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

2023-12-10T18:50:39.299345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:50:39.546224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완료 100
100.0%

updt_de
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210457
Minimum20210201
Maximum20210727
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:50:39.733415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210201
5-th percentile20210202
Q120210406
median20210413
Q320210427
95-th percentile20210714
Maximum20210727
Range526
Interquartile range (IQR)21

Descriptive statistics

Standard deviation147.3486
Coefficient of variation (CV)7.2907109 × 10-6
Kurtosis-0.19903454
Mean20210457
Median Absolute Deviation (MAD)7
Skewness0.61540978
Sum2.0210457 × 109
Variance21711.61
MonotonicityNot monotonic
2023-12-10T18:50:40.008529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20210406 15
15.0%
20210413 12
12.0%
20210702 10
 
10.0%
20210407 9
 
9.0%
20210405 8
 
8.0%
20210420 5
 
5.0%
20210202 5
 
5.0%
20210706 4
 
4.0%
20210416 3
 
3.0%
20210427 3
 
3.0%
Other values (20) 26
26.0%
ValueCountFrequency (%)
20210201 1
 
1.0%
20210202 5
 
5.0%
20210210 1
 
1.0%
20210221 1
 
1.0%
20210223 1
 
1.0%
20210226 1
 
1.0%
20210405 8
8.0%
20210406 15
15.0%
20210407 9
9.0%
20210408 1
 
1.0%
ValueCountFrequency (%)
20210727 2
 
2.0%
20210722 1
 
1.0%
20210721 1
 
1.0%
20210720 1
 
1.0%
20210714 1
 
1.0%
20210708 1
 
1.0%
20210707 1
 
1.0%
20210706 4
 
4.0%
20210702 10
10.0%
20210430 1
 
1.0%

Interactions

2023-12-10T18:50:30.424650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:30.026922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:30.583981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:50:30.260417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:50:40.211565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
rcept_decnslt_sclas_nmcnslt_kwrd_rn1_nmcnslt_kwrd_rn2_nmcnslt_kwrd_rn3_nmcnslt_kwrd_rn4_nmcnslt_kwrd_rn5_nmcnslt_ty_nmtalk_flag_nmupdt_de
rcept_de1.0000.5060.8270.6760.7460.9150.8890.0000.5101.000
cnslt_sclas_nm0.5061.0000.9590.0600.9450.8800.9410.1880.3210.506
cnslt_kwrd_rn1_nm0.8270.9591.0000.9120.9460.9420.943NaN0.9010.827
cnslt_kwrd_rn2_nm0.6760.0600.9121.0000.8880.8620.958NaN0.8750.676
cnslt_kwrd_rn3_nm0.7460.9450.9460.8881.0000.9510.901NaN0.9750.746
cnslt_kwrd_rn4_nm0.9150.8800.9420.8620.9511.0000.972NaN0.9690.915
cnslt_kwrd_rn5_nm0.8890.9410.9430.9580.9010.9721.000NaN0.6420.889
cnslt_ty_nm0.0000.188NaNNaNNaNNaNNaN1.0000.0000.000
talk_flag_nm0.5100.3210.9010.8750.9750.9690.6420.0001.0000.510
updt_de1.0000.5060.8270.6760.7460.9150.8890.0000.5101.000
2023-12-10T18:50:40.496930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
talk_flag_nmcnslt_sclas_nmcnslt_ty_nmcnslt_kwrd_rn2_nmcnslt_kwrd_rn1_nmcnslt_kwrd_rn3_nm
talk_flag_nm1.0000.3850.0000.5670.6000.639
cnslt_sclas_nm0.3851.0000.2260.0000.6530.597
cnslt_ty_nm0.0000.2261.0001.0001.0001.000
cnslt_kwrd_rn2_nm0.5670.0001.0001.0000.4100.322
cnslt_kwrd_rn1_nm0.6000.6531.0000.4101.0000.511
cnslt_kwrd_rn3_nm0.6390.5971.0000.3220.5111.000
2023-12-10T18:50:40.724096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
rcept_deupdt_decnslt_sclas_nmcnslt_kwrd_rn1_nmcnslt_kwrd_rn2_nmcnslt_kwrd_rn3_nmcnslt_ty_nmtalk_flag_nm
rcept_de1.0000.9980.4170.4410.3150.3120.0000.360
updt_de0.9981.0000.4170.4410.3150.3120.0000.360
cnslt_sclas_nm0.4170.4171.0000.6530.0000.5970.2260.385
cnslt_kwrd_rn1_nm0.4410.4410.6531.0000.4100.5111.0000.600
cnslt_kwrd_rn2_nm0.3150.3150.0000.4101.0000.3221.0000.567
cnslt_kwrd_rn3_nm0.3120.3120.5970.5110.3221.0001.0000.639
cnslt_ty_nm0.0000.0000.2261.0001.0001.0001.0000.000
talk_flag_nm0.3600.3600.3850.6000.5670.6390.0001.000

Missing values

2023-12-10T18:50:30.849597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:50:31.336708image/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.
2023-12-10T18:50:31.641808image/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
020210702한국어음식음식한식카페이용시간이용<NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210702
120210702한국어음식음식한식식당맑은<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210702
220210702한국어음식음식한식사전예약운영시간<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210702
320210702한국어음식음식한식외국인공지이용시간이용방문일반휴양 및 관광홈페이지일반전화아웃바운드완료20210702
420210722한국어음식음식카페<NA><NA><NA><NA><NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210722
520210706한국어음식음식한식<NA><NA><NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210706
620210702한국어음식음식한식음식점<NA><NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210702
720210724한국어음식음식카페물품보관보관물품보관함커피일반휴양 및 관광홈페이지일반전화아웃바운드완료20210727
820210708한국어음식음식한식정방폭포폭포식당맛집횟집일반휴양 및 관광홈페이지일반전화인바운드완료20210708
920210706한국어음식음식카페카페문의처<NA><NA><NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210706
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
9020210420한국어음식음식카페문자리스트호텔마을서귀포일반휴양 및 관광홈페이지일반전화인바운드완료20210420
9120210420한국어음식음식카페문자리스트안덕커피서귀포일반휴양 및 관광홈페이지일반전화아웃바운드완료20210420
9220210420한국어음식음식카페<NA><NA><NA><NA><NA>자동저장휴양 및 관광홈페이지일반전화인바운드완료20210420
9320210413한국어음식음식한식판매<NA><NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210413
9420210413한국어음식음식향토음식이용시간이용<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210413
9520210413한국어음식음식향토음식이용재료소진<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210413
9620210413한국어음식음식한식외국어이용<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210413
9720210416한국어음식음식한식금호음식점리조트인터넷<NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210416
9820210417한국어음식음식한식비자림문자제주갈치맛집일반휴양 및 관광홈페이지일반전화인바운드완료20210417
9920210414한국어음식음식향토음식오름해녀식당코지오일장일반휴양 및 관광홈페이지일반전화인바운드완료20210414

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
620210413한국어음식음식한식외국어이용<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료202104133
720210702한국어음식음식한식음식점<NA><NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료202107023
020210405한국어음식음식향토음식외국어이용<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료202104052
120210405한국어음식음식향토음식<NA><NA><NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료202104052
220210406한국어음식음식향토음식음식점제주이용말고기<NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료202104062
320210406한국어음식음식향토음식이용<NA><NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료202104062
420210407한국어음식음식향토음식이용<NA><NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료202104072
520210407한국어음식음식향토음식휴무일이용시간이용<NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료202104072