Overview

Dataset statistics

Number of variables18
Number of observations100
Missing cells116
Missing cells (%)6.4%
Duplicate rows2
Duplicate rows (%)2.0%
Total size in memory14.4 KiB
Average record size in memory147.3 B

Variable types

Numeric2
Categorical13
Text3

Alerts

cnslt_lclas_nm has constant value ""Constant
cnslt_mlsfc_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 2 (2.0%) duplicate rowsDuplicates
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_nmHigh correlation
cnslt_kwrd_rn1_nm is highly overall correlated with cnslt_sclas_nm and 1 other fieldsHigh correlation
cnslt_kwrd_rn2_nm is highly overall correlated with cnslt_kwrd_rn1_nmHigh correlation
lang_flag_nm is highly imbalanced (91.9%)Imbalance
cnslt_kwrd_rn3_nm has 20 (20.0%) missing valuesMissing
cnslt_kwrd_rn4_nm has 36 (36.0%) missing valuesMissing
cnslt_kwrd_rn5_nm has 60 (60.0%) missing valuesMissing

Reproduction

Analysis started2023-12-10 10:08:02.908902
Analysis finished2023-12-10 10:08:07.153976
Duration4.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

rcept_de
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210199
Minimum20210102
Maximum20210329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:08:07.428018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210102
5-th percentile20210108
Q120210122
median20210207
Q320210220
95-th percentile20210323
Maximum20210329
Range227
Interquartile range (IQR)98.25

Descriptive statistics

Standard deviation73.372972
Coefficient of variation (CV)3.6304924 × 10-6
Kurtosis-1.0396195
Mean20210199
Median Absolute Deviation (MAD)85
Skewness0.36706808
Sum2.0210199 × 109
Variance5383.593
MonotonicityNot monotonic
2023-12-10T19:08:07.853468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
20210209 9
 
9.0%
20210120 7
 
7.0%
20210127 6
 
6.0%
20210217 6
 
6.0%
20210122 5
 
5.0%
20210118 4
 
4.0%
20210206 3
 
3.0%
20210324 3
 
3.0%
20210323 3
 
3.0%
20210121 3
 
3.0%
Other values (32) 51
51.0%
ValueCountFrequency (%)
20210102 2
 
2.0%
20210106 2
 
2.0%
20210108 2
 
2.0%
20210115 3
3.0%
20210118 4
4.0%
20210119 2
 
2.0%
20210120 7
7.0%
20210121 3
3.0%
20210122 5
5.0%
20210123 1
 
1.0%
ValueCountFrequency (%)
20210329 1
 
1.0%
20210324 3
3.0%
20210323 3
3.0%
20210320 1
 
1.0%
20210318 3
3.0%
20210315 1
 
1.0%
20210312 1
 
1.0%
20210309 2
2.0%
20210306 1
 
1.0%
20210305 2
2.0%

lang_flag_nm
Categorical

IMBALANCE 

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

Length

Max length3
Median length3
Mean length2.99
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
한국어 99
99.0%
영어 1
 
1.0%

Length

2023-12-10T19:08:08.162712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:08.456759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국어 99
99.0%
영어 1
 
1.0%

cnslt_lclas_nm
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
쇼핑 100
100.0%

Length

2023-12-10T19:08:08.747264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:08.952208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
쇼핑 100
100.0%

cnslt_mlsfc_nm
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
쇼핑 100
100.0%

Length

2023-12-10T19:08:09.147744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:09.384279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
쇼핑 100
100.0%

cnslt_sclas_nm
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전통시장
62 
특산품
19 
면세점
8 
플리마켓
7 
상점·상가
 
3

Length

Max length5
Median length4
Mean length3.74
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row면세점
2nd row전통시장
3rd row특산품
4th row전통시장
5th row면세점

Common Values

ValueCountFrequency (%)
전통시장 62
62.0%
특산품 19
 
19.0%
면세점 8
 
8.0%
플리마켓 7
 
7.0%
상점·상가 3
 
3.0%
기타 1
 
1.0%

Length

2023-12-10T19:08:09.637581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:09.933620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전통시장 62
62.0%
특산품 19
 
19.0%
면세점 8
 
8.0%
플리마켓 7
 
7.0%
상점·상가 3
 
3.0%
기타 1
 
1.0%

cnslt_kwrd_rn1_nm
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
연락처
13 
오일장
12 
운영시간
9 
개장
6 
정상운영
 
5
Other values (30)
55 

Length

Max length5
Median length4
Mean length2.88
Min length2

Unique

Unique16 ?
Unique (%)16.0%

Sample

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

Common Values

ValueCountFrequency (%)
연락처 13
 
13.0%
오일장 12
 
12.0%
운영시간 9
 
9.0%
개장 6
 
6.0%
정상운영 5
 
5.0%
문자 5
 
5.0%
야시장 4
 
4.0%
제주 4
 
4.0%
면세점 4
 
4.0%
대정 3
 
3.0%
Other values (25) 35
35.0%

Length

2023-12-10T19:08:10.182338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연락처 13
 
13.0%
오일장 12
 
12.0%
운영시간 9
 
9.0%
개장 6
 
6.0%
정상운영 5
 
5.0%
문자 5
 
5.0%
야시장 4
 
4.0%
제주 4
 
4.0%
면세점 4
 
4.0%
대정 3
 
3.0%
Other values (25) 35
35.0%

cnslt_kwrd_rn2_nm
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
제주
11 
문자
10 
오일장
8 
서귀포
 
6
<NA>
 
5
Other values (38)
60 

Length

Max length4
Median length3
Mean length2.72
Min length2

Unique

Unique24 ?
Unique (%)24.0%

Sample

1st row문자
2nd row물품보관
3rd row제주도청
4th row오일장
5th row문자

Common Values

ValueCountFrequency (%)
제주 11
 
11.0%
문자 10
 
10.0%
오일장 8
 
8.0%
서귀포 6
 
6.0%
<NA> 5
 
5.0%
위판장 4
 
4.0%
야시장 4
 
4.0%
유선 3
 
3.0%
중문 3
 
3.0%
동문시장 3
 
3.0%
Other values (33) 43
43.0%

Length

2023-12-10T19:08:10.597460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제주 11
 
11.0%
문자 10
 
10.0%
오일장 8
 
8.0%
서귀포 6
 
6.0%
na 5
 
5.0%
위판장 4
 
4.0%
야시장 4
 
4.0%
유선 3
 
3.0%
중문 3
 
3.0%
동문시장 3
 
3.0%
Other values (33) 43
43.0%

cnslt_kwrd_rn3_nm
Text

MISSING 

Distinct40
Distinct (%)50.0%
Missing20
Missing (%)20.0%
Memory size932.0 B
2023-12-10T19:08:11.077025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.575
Min length2

Characters and Unicode

Total characters206
Distinct characters78
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

Unique20 ?
Unique (%)25.0%

Sample

1st row숙소
2nd row운영시간
3rd row소비생활
4th row서귀포
5th row숙소
ValueCountFrequency (%)
이용 7
 
8.8%
문자 5
 
6.2%
서귀포 5
 
6.2%
이용시간 4
 
5.0%
제주 3
 
3.8%
플리 3
 
3.8%
대정 3
 
3.8%
판매 3
 
3.8%
중문 3
 
3.8%
동문시장 3
 
3.8%
Other values (30) 41
51.2%
2023-12-10T19:08:11.827099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
문 13
 
6.3%
이 11
 
5.3%
용 11
 
5.3%
포 10
 
4.9%
시 10
 
4.9%
장 8
 
3.9%
서 7
 
3.4%
귀 7
 
3.4%
자 5
 
2.4%
간 5
 
2.4%
Other values (68) 119
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 202
98.1%
Decimal Number 4
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
문 13
 
6.4%
이 11
 
5.4%
용 11
 
5.4%
포 10
 
5.0%
시 10
 
5.0%
장 8
 
4.0%
서 7
 
3.5%
귀 7
 
3.5%
자 5
 
2.5%
간 5
 
2.5%
Other values (66) 115
56.9%
Decimal Number
ValueCountFrequency (%)
0 2
50.0%
1 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 202
98.1%
Common 4
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
문 13
 
6.4%
이 11
 
5.4%
용 11
 
5.4%
포 10
 
5.0%
시 10
 
5.0%
장 8
 
4.0%
서 7
 
3.5%
귀 7
 
3.5%
자 5
 
2.5%
간 5
 
2.5%
Other values (66) 115
56.9%
Common
ValueCountFrequency (%)
0 2
50.0%
1 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 202
98.1%
ASCII 4
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
문 13
 
6.4%
이 11
 
5.4%
용 11
 
5.4%
포 10
 
5.0%
시 10
 
5.0%
장 8
 
4.0%
서 7
 
3.5%
귀 7
 
3.5%
자 5
 
2.5%
간 5
 
2.5%
Other values (66) 115
56.9%
ASCII
ValueCountFrequency (%)
0 2
50.0%
1 2
50.0%

cnslt_kwrd_rn4_nm
Text

MISSING 

Distinct34
Distinct (%)53.1%
Missing36
Missing (%)36.0%
Memory size932.0 B
2023-12-10T19:08:12.191360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.5
Min length2

Characters and Unicode

Total characters160
Distinct characters63
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

Unique23 ?
Unique (%)35.9%

Sample

1st row면세점
2nd row유아
3rd row제주
4th row중문
5th row면세점
ValueCountFrequency (%)
이용 9
 
14.1%
제주 8
 
12.5%
한라 3
 
4.7%
판매 3
 
4.7%
서귀포 3
 
4.7%
마켓 3
 
4.7%
동문시장 3
 
4.7%
오일장 3
 
4.7%
면세점 2
 
3.1%
상인회 2
 
3.1%
Other values (24) 25
39.1%
2023-12-10T19:08:12.754037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 10
 
6.2%
주 10
 
6.2%
장 10
 
6.2%
이 9
 
5.6%
용 9
 
5.6%
문 7
 
4.4%
시 5
 
3.1%
매 5
 
3.1%
판 4
 
2.5%
서 4
 
2.5%
Other values (53) 87
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 158
98.8%
Uppercase Letter 2
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 10
 
6.3%
주 10
 
6.3%
장 10
 
6.3%
이 9
 
5.7%
용 9
 
5.7%
문 7
 
4.4%
시 5
 
3.2%
매 5
 
3.2%
판 4
 
2.5%
서 4
 
2.5%
Other values (51) 85
53.8%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
A 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 158
98.8%
Latin 2
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 10
 
6.3%
주 10
 
6.3%
장 10
 
6.3%
이 9
 
5.7%
용 9
 
5.7%
문 7
 
4.4%
시 5
 
3.2%
매 5
 
3.2%
판 4
 
2.5%
서 4
 
2.5%
Other values (51) 85
53.8%
Latin
ValueCountFrequency (%)
S 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 158
98.8%
ASCII 2
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 10
 
6.3%
주 10
 
6.3%
장 10
 
6.3%
이 9
 
5.7%
용 9
 
5.7%
문 7
 
4.4%
시 5
 
3.2%
매 5
 
3.2%
판 4
 
2.5%
서 4
 
2.5%
Other values (51) 85
53.8%
ASCII
ValueCountFrequency (%)
S 1
50.0%
A 1
50.0%

cnslt_kwrd_rn5_nm
Text

MISSING 

Distinct24
Distinct (%)60.0%
Missing60
Missing (%)60.0%
Memory size932.0 B
2023-12-10T19:08:13.039323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.45
Min length2

Characters and Unicode

Total characters98
Distinct characters48
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

Unique18 ?
Unique (%)45.0%

Sample

1st row중문
2nd row사무실
3rd row상인회
4th row중문
5th row유선
ValueCountFrequency (%)
제주 9
22.5%
이용 3
 
7.5%
문의처 3
 
7.5%
중문 3
 
7.5%
야시장 2
 
5.0%
골목 2
 
5.0%
탐방 1
 
2.5%
서귀포 1
 
2.5%
보관 1
 
2.5%
신라 1
 
2.5%
Other values (14) 14
35.0%
2023-12-10T19:08:13.653428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 10
 
10.2%
제 9
 
9.2%
문 7
 
7.1%
중 4
 
4.1%
처 4
 
4.1%
장 4
 
4.1%
이 3
 
3.1%
용 3
 
3.1%
의 3
 
3.1%
시 3
 
3.1%
Other values (38) 48
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 98
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 10
 
10.2%
제 9
 
9.2%
문 7
 
7.1%
중 4
 
4.1%
처 4
 
4.1%
장 4
 
4.1%
이 3
 
3.1%
용 3
 
3.1%
의 3
 
3.1%
시 3
 
3.1%
Other values (38) 48
49.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 98
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 10
 
10.2%
제 9
 
9.2%
문 7
 
7.1%
중 4
 
4.1%
처 4
 
4.1%
장 4
 
4.1%
이 3
 
3.1%
용 3
 
3.1%
의 3
 
3.1%
시 3
 
3.1%
Other values (38) 48
49.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 98
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 10
 
10.2%
제 9
 
9.2%
문 7
 
7.1%
중 4
 
4.1%
처 4
 
4.1%
장 4
 
4.1%
이 3
 
3.1%
용 3
 
3.1%
의 3
 
3.1%
시 3
 
3.1%
Other values (38) 48
49.0%

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

2023-12-10T19:08:13.913002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:14.089958image/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

2023-12-10T19:08:14.268492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:14.439949image/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

2023-12-10T19:08:14.610104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:14.786336image/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

2023-12-10T19:08:14.953480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:15.107190image/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

2023-12-10T19:08:15.325390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:15.485644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전화 100
100.0%

talk_flag_nm
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
인바운드
51 
아웃바운드
49 

Length

Max length5
Median length4
Mean length4.49
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인바운드 51
51.0%
아웃바운드 49
49.0%

Length

2023-12-10T19:08:15.732044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:15.937331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인바운드 51
51.0%
아웃바운드 49
49.0%

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

2023-12-10T19:08:16.240908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:08:16.440896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완료 100
100.0%

updt_de
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210199
Minimum20210102
Maximum20210329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:08:16.732365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210102
5-th percentile20210108
Q120210122
median20210207
Q320210220
95-th percentile20210323
Maximum20210329
Range227
Interquartile range (IQR)98.25

Descriptive statistics

Standard deviation73.389458
Coefficient of variation (CV)3.6313081 × 10-6
Kurtosis-1.0391301
Mean20210199
Median Absolute Deviation (MAD)85
Skewness0.36752581
Sum2.0210199 × 109
Variance5386.0125
MonotonicityNot monotonic
2023-12-10T19:08:17.076743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
20210209 9
 
9.0%
20210120 7
 
7.0%
20210127 6
 
6.0%
20210217 6
 
6.0%
20210122 5
 
5.0%
20210118 4
 
4.0%
20210206 3
 
3.0%
20210324 3
 
3.0%
20210121 3
 
3.0%
20210323 3
 
3.0%
Other values (33) 51
51.0%
ValueCountFrequency (%)
20210102 2
 
2.0%
20210106 2
 
2.0%
20210108 2
 
2.0%
20210115 3
3.0%
20210118 4
4.0%
20210119 2
 
2.0%
20210120 7
7.0%
20210121 3
3.0%
20210122 5
5.0%
20210123 1
 
1.0%
ValueCountFrequency (%)
20210329 1
 
1.0%
20210324 3
3.0%
20210323 3
3.0%
20210320 1
 
1.0%
20210319 1
 
1.0%
20210318 2
2.0%
20210315 1
 
1.0%
20210312 1
 
1.0%
20210309 2
2.0%
20210306 1
 
1.0%

Interactions

2023-12-10T19:08:04.500322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:08:04.111707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:08:04.863095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:08:04.294843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:08:17.416968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
rcept_delang_flag_nmcnslt_sclas_nmcnslt_kwrd_rn1_nmcnslt_kwrd_rn2_nmcnslt_kwrd_rn3_nmcnslt_kwrd_rn4_nmcnslt_kwrd_rn5_nmtalk_flag_nmupdt_de
rcept_de1.0000.0000.5410.6460.5990.6240.7740.0000.2521.000
lang_flag_nm0.0001.0000.0000.0000.0000.0001.0000.0000.0000.000
cnslt_sclas_nm0.5410.0001.0000.9140.8540.9900.9540.8800.0000.541
cnslt_kwrd_rn1_nm0.6460.0000.9141.0000.9620.9620.8590.9570.5130.646
cnslt_kwrd_rn2_nm0.5990.0000.8540.9621.0000.9870.8960.9470.4010.599
cnslt_kwrd_rn3_nm0.6240.0000.9900.9620.9871.0000.9670.9450.6310.624
cnslt_kwrd_rn4_nm0.7741.0000.9540.8590.8960.9671.0000.9480.5260.774
cnslt_kwrd_rn5_nm0.0000.0000.8800.9570.9470.9450.9481.0000.0000.000
talk_flag_nm0.2520.0000.0000.5130.4010.6310.5260.0001.0000.252
updt_de1.0000.0000.5410.6460.5990.6240.7740.0000.2521.000
2023-12-10T19:08:17.686142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
lang_flag_nmcnslt_kwrd_rn2_nmcnslt_sclas_nmcnslt_kwrd_rn1_nmtalk_flag_nm
lang_flag_nm1.0000.0000.0000.0000.000
cnslt_kwrd_rn2_nm0.0001.0000.4580.5150.233
cnslt_sclas_nm0.0000.4581.0000.5750.000
cnslt_kwrd_rn1_nm0.0000.5150.5751.0000.351
talk_flag_nm0.0000.2330.0000.3511.000
2023-12-10T19:08:17.936671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
rcept_deupdt_delang_flag_nmcnslt_sclas_nmcnslt_kwrd_rn1_nmcnslt_kwrd_rn2_nmtalk_flag_nm
rcept_de1.0001.0000.0000.2020.2910.2110.169
updt_de1.0001.0000.0000.2020.2910.2110.169
lang_flag_nm0.0000.0001.0000.0000.0000.0000.000
cnslt_sclas_nm0.2020.2020.0001.0000.5750.4580.000
cnslt_kwrd_rn1_nm0.2910.2910.0000.5751.0000.5150.351
cnslt_kwrd_rn2_nm0.2110.2110.0000.4580.5151.0000.233
talk_flag_nm0.1690.1690.0000.0000.3510.2331.000

Missing values

2023-12-10T19:08:05.179466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:08:06.202394image/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.
2023-12-10T19:08:06.750245image/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
020210102한국어쇼핑쇼핑면세점연락처문자숙소면세점중문일반휴양 및 관광홈페이지일반전화인바운드완료20210102
120210106한국어쇼핑쇼핑전통시장대여물품보관운영시간유아사무실일반휴양 및 관광홈페이지일반전화아웃바운드완료20210106
220210123한국어쇼핑쇼핑특산품연락처제주도청소비생활제주<NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210123
320210108한국어쇼핑쇼핑전통시장연락처오일장서귀포중문상인회일반휴양 및 관광홈페이지일반전화아웃바운드완료20210108
420210102한국어쇼핑쇼핑면세점연락처문자숙소면세점중문일반휴양 및 관광홈페이지일반전화아웃바운드완료20210102
520210120한국어쇼핑쇼핑전통시장오일장고성이용<NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210120
620210121한국어쇼핑쇼핑전통시장대정오일장이용<NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210121
720210122한국어쇼핑쇼핑특산품연락처비짓한라제주<NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210122
820210119한국어쇼핑쇼핑전통시장천제연폭포천제연폭포매표소유선일반휴양 및 관광홈페이지일반전화인바운드완료20210119
920210120한국어쇼핑쇼핑전통시장온라인제주문의처<NA><NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210120
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
9020210323한국어쇼핑쇼핑특산품서귀포제주<NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210323
9120210324한국어쇼핑쇼핑전통시장오일장서귀포서귀포향토제주<NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210324
9220210318한국어쇼핑쇼핑면세점면세점중문제주인도장이용일반휴양 및 관광홈페이지일반전화아웃바운드완료20210318
9320210318한국어쇼핑쇼핑면세점면세점제주인도장제주항<NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210318
9420210320한국어쇼핑쇼핑특산품자전거체험1100만장굴숲길일반휴양 및 관광홈페이지일반전화인바운드완료20210320
9520210309한국어쇼핑쇼핑특산품가방마을한라판매<NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210309
9620210312한국어쇼핑쇼핑전통시장오일장제주고사리특산품<NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210312
9720210324한국어쇼핑쇼핑상점·상가기념품<NA><NA><NA><NA>일반휴양 및 관광홈페이지일반전화아웃바운드완료20210324
9820210324한국어쇼핑쇼핑면세점면세점제주<NA><NA><NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210324
9920210329한국어쇼핑쇼핑전통시장오일장서귀포중문<NA><NA>일반휴양 및 관광홈페이지일반전화인바운드완료20210329

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
020210127한국어쇼핑쇼핑전통시장운영시간한림매일한림상인회문의처일반휴양 및 관광홈페이지일반전화아웃바운드완료202101272
120210127한국어쇼핑쇼핑특산품마을제주판매<NA><NA>일반휴양 및 관광홈페이지일반전화인바운드완료202101272