Overview

Dataset statistics

Number of variables15
Number of observations60
Missing cells39
Missing cells (%)4.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory130.2 B

Variable types

Categorical9
Text2
Numeric4

Dataset

Description서울특별시 동대문구 서울약령시한의약박물관의 월별 입장객 수를 권종그룹, 권종, 출력가에 따라 정리한 데이터입니다.
URLhttps://www.data.go.kr/data/15037772/fileData.do

Alerts

방문시기 has constant value ""Constant
방문시작월 has constant value ""Constant
방문종료월 has constant value ""Constant
구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
7월 is highly overall correlated with 8월 and 2 other fieldsHigh correlation
8월 is highly overall correlated with 7월 and 3 other fieldsHigh correlation
10월 is highly overall correlated with 7월 and 3 other fieldsHigh correlation
12월 is highly overall correlated with 8월 and 2 other fieldsHigh correlation
9월 is highly overall correlated with 8월High correlation
11월 is highly overall correlated with 7월 and 2 other fieldsHigh correlation
9월 is highly imbalanced (79.0%)Imbalance
상품 has 39 (65.0%) missing valuesMissing
7월 has 46 (76.7%) zerosZeros
8월 has 43 (71.7%) zerosZeros
10월 has 24 (40.0%) zerosZeros
12월 has 51 (85.0%) zerosZeros

Reproduction

Analysis started2023-12-12 15:18:43.789207
Analysis finished2023-12-12 15:18:46.784205
Duration2.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

방문시기
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2020
60 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 60
100.0%

Length

2023-12-13T00:18:46.855162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:18:47.002016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 60
100.0%

방문시작월
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
7
60 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row7
3rd row7
4th row7
5th row7

Common Values

ValueCountFrequency (%)
7 60
100.0%

Length

2023-12-13T00:18:47.130849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:18:47.265322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 60
100.0%

방문종료월
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
12
60 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12
2nd row12
3rd row12
4th row12
5th row12

Common Values

ValueCountFrequency (%)
12 60
100.0%

Length

2023-12-13T00:18:47.374888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:18:47.486947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12 60
100.0%

상품
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing39
Missing (%)65.0%
Memory size612.0 B
2023-12-13T00:18:47.691678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length15
Mean length9.7142857
Min length4

Characters and Unicode

Total characters204
Distinct characters104
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row달콤한 힐링족욕+박물관 관람
2nd row건강채움소 보제원+박물관 관람
3rd row박물관_즐거운한방DIY
4th row박물관_우리가족힐링한방(예약자전용)
5th row박물관(목,금)_유아단체(10:30~11:50)
ValueCountFrequency (%)
관람 3
 
8.3%
박물관 2
 
5.6%
센터 2
 
5.6%
행사 1
 
2.8%
투어리즘 1
 
2.8%
학교연계 1
 
2.8%
한서초등학교 1
 
2.8%
한방뷰티클럽(온라인 1
 
2.8%
집콕 1
 
2.8%
달콤한 1
 
2.8%
Other values (22) 22
61.1%
2023-12-13T00:18:48.090292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
7.4%
관 11
 
5.4%
한 9
 
4.4%
방 8
 
3.9%
박 7
 
3.4%
물 7
 
3.4%
) 5
 
2.5%
( 5
 
2.5%
원 4
 
2.0%
족 3
 
1.5%
Other values (94) 130
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 156
76.5%
Space Separator 15
 
7.4%
Decimal Number 8
 
3.9%
Close Punctuation 6
 
2.9%
Open Punctuation 6
 
2.9%
Other Punctuation 4
 
2.0%
Connector Punctuation 3
 
1.5%
Math Symbol 3
 
1.5%
Uppercase Letter 3
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 11
 
7.1%
한 9
 
5.8%
방 8
 
5.1%
박 7
 
4.5%
물 7
 
4.5%
원 4
 
2.6%
족 3
 
1.9%
람 3
 
1.9%
체 3
 
1.9%
교 3
 
1.9%
Other values (76) 98
62.8%
Decimal Number
ValueCountFrequency (%)
1 3
37.5%
0 3
37.5%
5 1
 
12.5%
3 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
: 2
50.0%
! 1
25.0%
, 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
Y 1
33.3%
I 1
33.3%
D 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 5
83.3%
] 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 5
83.3%
[ 1
 
16.7%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
~ 1
33.3%
Space Separator
ValueCountFrequency (%)
15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 156
76.5%
Common 45
 
22.1%
Latin 3
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 11
 
7.1%
한 9
 
5.8%
방 8
 
5.1%
박 7
 
4.5%
물 7
 
4.5%
원 4
 
2.6%
족 3
 
1.9%
람 3
 
1.9%
체 3
 
1.9%
교 3
 
1.9%
Other values (76) 98
62.8%
Common
ValueCountFrequency (%)
15
33.3%
) 5
 
11.1%
( 5
 
11.1%
_ 3
 
6.7%
1 3
 
6.7%
0 3
 
6.7%
: 2
 
4.4%
+ 2
 
4.4%
] 1
 
2.2%
! 1
 
2.2%
Other values (5) 5
 
11.1%
Latin
ValueCountFrequency (%)
Y 1
33.3%
I 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 156
76.5%
ASCII 48
 
23.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
31.2%
) 5
 
10.4%
( 5
 
10.4%
_ 3
 
6.2%
1 3
 
6.2%
0 3
 
6.2%
: 2
 
4.2%
+ 2
 
4.2%
] 1
 
2.1%
! 1
 
2.1%
Other values (8) 8
16.7%
Hangul
ValueCountFrequency (%)
관 11
 
7.1%
한 9
 
5.8%
방 8
 
5.1%
박 7
 
4.5%
물 7
 
4.5%
원 4
 
2.6%
족 3
 
1.9%
람 3
 
1.9%
체 3
 
1.9%
교 3
 
1.9%
Other values (76) 98
62.8%

권종그룹
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
<NA>
38 
일반
19 
단체
 
3

Length

Max length4
Median length4
Mean length3.2666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 38
63.3%
일반 19
31.7%
단체 3
 
5.0%

Length

2023-12-13T00:18:48.241108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:18:48.366425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 38
63.3%
일반 19
31.7%
단체 3
 
5.0%

권종
Text

Distinct36
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-13T00:18:48.556668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length6.9666667
Min length2

Characters and Unicode

Total characters418
Distinct characters79
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)43.3%

Sample

1st row족욕1팀(최대2명)
2nd row족욕1팀(최대1명)
3rd row족욕1팀 (최대2명)
4th row족욕1팀 (최대2인)
5th row족욕1팀(최대2인) 50%할인
ValueCountFrequency (%)
일반 19
22.9%
20%할인 8
 
9.6%
50%할인 5
 
6.0%
입장_무료 3
 
3.6%
한방체험1인 3
 
3.6%
할인 3
 
3.6%
족욕1팀(최대2명 3
 
3.6%
학교연계)한방뷰티클럽 2
 
2.4%
단체 2
 
2.4%
구민20 2
 
2.4%
Other values (26) 33
39.8%
2023-12-13T00:18:48.948878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 27
 
6.5%
23
 
5.5%
일 19
 
4.5%
반 19
 
4.5%
2 18
 
4.3%
0 18
 
4.3%
% 18
 
4.3%
할 16
 
3.8%
1 12
 
2.9%
) 12
 
2.9%
Other values (69) 236
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 284
67.9%
Decimal Number 55
 
13.2%
Space Separator 23
 
5.5%
Other Punctuation 22
 
5.3%
Close Punctuation 12
 
2.9%
Open Punctuation 12
 
2.9%
Connector Punctuation 10
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 27
 
9.5%
일 19
 
6.7%
반 19
 
6.7%
할 16
 
5.6%
대 11
 
3.9%
장 10
 
3.5%
입 9
 
3.2%
족 8
 
2.8%
욕 8
 
2.8%
팀 8
 
2.8%
Other values (58) 149
52.5%
Decimal Number
ValueCountFrequency (%)
2 18
32.7%
0 18
32.7%
1 12
21.8%
5 7
 
12.7%
Other Punctuation
ValueCountFrequency (%)
% 18
81.8%
, 2
 
9.1%
! 2
 
9.1%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 284
67.9%
Common 134
32.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 27
 
9.5%
일 19
 
6.7%
반 19
 
6.7%
할 16
 
5.6%
대 11
 
3.9%
장 10
 
3.5%
입 9
 
3.2%
족 8
 
2.8%
욕 8
 
2.8%
팀 8
 
2.8%
Other values (58) 149
52.5%
Common
ValueCountFrequency (%)
23
17.2%
2 18
13.4%
0 18
13.4%
% 18
13.4%
1 12
9.0%
) 12
9.0%
( 12
9.0%
_ 10
7.5%
5 7
 
5.2%
, 2
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 284
67.9%
ASCII 134
32.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 27
 
9.5%
일 19
 
6.7%
반 19
 
6.7%
할 16
 
5.6%
대 11
 
3.9%
장 10
 
3.5%
입 9
 
3.2%
족 8
 
2.8%
욕 8
 
2.8%
팀 8
 
2.8%
Other values (58) 149
52.5%
ASCII
ValueCountFrequency (%)
23
17.2%
2 18
13.4%
0 18
13.4%
% 18
13.4%
1 12
9.0%
) 12
9.0%
( 12
9.0%
_ 10
7.5%
5 7
 
5.2%
, 2
 
1.5%

출력가
Categorical

Distinct17
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0원
11 
3,000원
11 
5,000원
7 
1,000원
5 
4,000원
4 
Other values (12)
22 

Length

Max length7
Median length6
Mean length5.1166667
Min length2

Unique

Unique5 ?
Unique (%)8.3%

Sample

1st row5,000원
2nd row2,500원
3rd row0원
4th row6,000원
5th row3,000원

Common Values

ValueCountFrequency (%)
0원 11
18.3%
3,000원 11
18.3%
5,000원 7
11.7%
1,000원 5
8.3%
4,000원 4
 
6.7%
500원 4
 
6.7%
2,500원 3
 
5.0%
3,200원 2
 
3.3%
10,000원 2
 
3.3%
6,000원 2
 
3.3%
Other values (7) 9
15.0%

Length

2023-12-13T00:18:49.087064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0원 11
18.3%
3,000원 11
18.3%
5,000원 7
11.7%
1,000원 5
8.3%
4,000원 4
 
6.7%
500원 4
 
6.7%
2,500원 3
 
5.0%
2,400원 2
 
3.3%
4,800원 2
 
3.3%
10,000원 2
 
3.3%
Other values (7) 9
15.0%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
인원수
60 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인원수 60
100.0%

Length

2023-12-13T00:18:49.214821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:18:49.313886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인원수 60
100.0%

7월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8
Minimum0
Maximum240
Zeros46
Zeros (%)76.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T00:18:49.427412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile28.4
Maximum240
Range240
Interquartile range (IQR)0

Descriptive statistics

Standard deviation33.20241
Coefficient of variation (CV)4.2567192
Kurtosis42.351498
Mean7.8
Median Absolute Deviation (MAD)0
Skewness6.2441787
Sum468
Variance1102.4
MonotonicityNot monotonic
2023-12-13T00:18:49.569757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 46
76.7%
1 4
 
6.7%
3 1
 
1.7%
36 1
 
1.7%
6 1
 
1.7%
28 1
 
1.7%
27 1
 
1.7%
5 1
 
1.7%
8 1
 
1.7%
24 1
 
1.7%
Other values (2) 2
 
3.3%
ValueCountFrequency (%)
0 46
76.7%
1 4
 
6.7%
3 1
 
1.7%
5 1
 
1.7%
6 1
 
1.7%
8 1
 
1.7%
24 1
 
1.7%
27 1
 
1.7%
28 1
 
1.7%
36 1
 
1.7%
ValueCountFrequency (%)
240 1
1.7%
87 1
1.7%
36 1
1.7%
28 1
1.7%
27 1
1.7%
24 1
1.7%
8 1
1.7%
6 1
1.7%
5 1
1.7%
3 1
1.7%

8월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.85
Minimum0
Maximum350
Zeros43
Zeros (%)71.7%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T00:18:49.711825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32.25
95-th percentile98.85
Maximum350
Range350
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation63.7795
Coefficient of variation (CV)3.213073
Kurtosis17.556961
Mean19.85
Median Absolute Deviation (MAD)0
Skewness4.1459174
Sum1191
Variance4067.8246
MonotonicityNot monotonic
2023-12-13T00:18:49.844980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 43
71.7%
3 2
 
3.3%
2 1
 
1.7%
191 1
 
1.7%
94 1
 
1.7%
350 1
 
1.7%
292 1
 
1.7%
15 1
 
1.7%
44 1
 
1.7%
14 1
 
1.7%
Other values (7) 7
 
11.7%
ValueCountFrequency (%)
0 43
71.7%
1 1
 
1.7%
2 1
 
1.7%
3 2
 
3.3%
4 1
 
1.7%
14 1
 
1.7%
15 1
 
1.7%
16 1
 
1.7%
19 1
 
1.7%
32 1
 
1.7%
ValueCountFrequency (%)
350 1
1.7%
292 1
1.7%
191 1
1.7%
94 1
1.7%
69 1
1.7%
44 1
1.7%
42 1
1.7%
32 1
1.7%
19 1
1.7%
16 1
1.7%

9월
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
56 
98
 
1
89
 
1
50
 
1
6
 
1

Length

Max length2
Median length1
Mean length1.05
Min length1

Unique

Unique4 ?
Unique (%)6.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 56
93.3%
98 1
 
1.7%
89 1
 
1.7%
50 1
 
1.7%
6 1
 
1.7%

Length

2023-12-13T00:18:50.052426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:18:50.216372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 56
93.3%
98 1
 
1.7%
89 1
 
1.7%
50 1
 
1.7%
6 1
 
1.7%

10월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.9
Minimum0
Maximum841
Zeros24
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T00:18:50.383993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.5
Q328.75
95-th percentile118.5
Maximum841
Range841
Interquartile range (IQR)28.75

Descriptive statistics

Standard deviation123.66106
Coefficient of variation (CV)3.0234978
Kurtosis31.827774
Mean40.9
Median Absolute Deviation (MAD)4.5
Skewness5.363143
Sum2454
Variance15292.058
MonotonicityNot monotonic
2023-12-13T00:18:50.561536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 24
40.0%
7 3
 
5.0%
8 3
 
5.0%
2 3
 
5.0%
44 2
 
3.3%
6 2
 
3.3%
17 2
 
3.3%
4 2
 
3.3%
21 1
 
1.7%
28 1
 
1.7%
Other values (17) 17
28.3%
ValueCountFrequency (%)
0 24
40.0%
1 1
 
1.7%
2 3
 
5.0%
4 2
 
3.3%
5 1
 
1.7%
6 2
 
3.3%
7 3
 
5.0%
8 3
 
5.0%
10 1
 
1.7%
17 2
 
3.3%
ValueCountFrequency (%)
841 1
1.7%
440 1
1.7%
204 1
1.7%
114 1
1.7%
90 1
1.7%
89 1
1.7%
80 1
1.7%
73 1
1.7%
65 1
1.7%
60 1
1.7%

11월
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
0
23 
1
4 
13
3 
10
3 
30
 
2
Other values (21)
25 

Length

Max length5
Median length1
Mean length1.6333333
Min length1

Unique

Unique17 ?
Unique (%)28.3%

Sample

1st row0
2nd row0
3rd row46
4th row33
5th row9

Common Values

ValueCountFrequency (%)
0 23
38.3%
1 4
 
6.7%
13 3
 
5.0%
10 3
 
5.0%
30 2
 
3.3%
18 2
 
3.3%
91 2
 
3.3%
9 2
 
3.3%
33 2
 
3.3%
48 1
 
1.7%
Other values (16) 16
26.7%

Length

2023-12-13T00:18:50.754952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 23
38.3%
1 4
 
6.7%
13 3
 
5.0%
10 3
 
5.0%
91 2
 
3.3%
9 2
 
3.3%
33 2
 
3.3%
18 2
 
3.3%
30 2
 
3.3%
141 1
 
1.7%
Other values (16) 16
26.7%

12월
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6666667
Minimum0
Maximum273
Zeros51
Zeros (%)85.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T00:18:50.913662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile11.3
Maximum273
Range273
Interquartile range (IQR)0

Descriptive statistics

Standard deviation44.304289
Coefficient of variation (CV)5.1120334
Kurtosis29.10921
Mean8.6666667
Median Absolute Deviation (MAD)0
Skewness5.436923
Sum520
Variance1962.8701
MonotonicityNot monotonic
2023-12-13T00:18:51.036866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 51
85.0%
1 4
 
6.7%
17 1
 
1.7%
11 1
 
1.7%
2 1
 
1.7%
213 1
 
1.7%
273 1
 
1.7%
ValueCountFrequency (%)
0 51
85.0%
1 4
 
6.7%
2 1
 
1.7%
11 1
 
1.7%
17 1
 
1.7%
213 1
 
1.7%
273 1
 
1.7%
ValueCountFrequency (%)
273 1
 
1.7%
213 1
 
1.7%
17 1
 
1.7%
11 1
 
1.7%
2 1
 
1.7%
1 4
 
6.7%
0 51
85.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2021-02-09
60 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-02-09
2nd row2021-02-09
3rd row2021-02-09
4th row2021-02-09
5th row2021-02-09

Common Values

ValueCountFrequency (%)
2021-02-09 60
100.0%

Length

2023-12-13T00:18:51.171671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:18:51.289767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-02-09 60
100.0%

Interactions

2023-12-13T00:18:45.656626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:44.419036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:44.819070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:45.231048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:45.748043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:44.519129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:44.921758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:45.340295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:46.181075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:44.630357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:45.031302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:45.448271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:46.284510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:44.717607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:45.118911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:18:45.547104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:18:51.375170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상품권종그룹권종출력가7월8월9월10월11월12월
상품1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
권종그룹1.0001.0001.0000.5150.0000.0000.0000.0000.0000.000
권종1.0001.0001.0000.9510.0000.0000.5710.0000.0000.000
출력가1.0000.5150.9511.0000.0000.0000.0000.0000.7210.000
7월1.0000.0000.0000.0001.0000.8660.0000.8320.9810.662
8월1.0000.0000.0000.0000.8661.0000.7900.8340.8030.927
9월1.0000.0000.5710.0000.0000.7901.0000.3260.0000.000
10월1.0000.0000.0000.0000.8320.8340.3261.0000.9630.700
11월1.0000.0000.0000.7210.9810.8030.0000.9631.0001.000
12월1.0000.0000.0000.0000.6620.9270.0000.7001.0001.000
2023-12-13T00:18:51.524492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
권종그룹9월출력가11월
권종그룹1.0000.0000.3030.000
9월0.0001.0000.0000.000
출력가0.3030.0001.0000.242
11월0.0000.0000.2421.000
2023-12-13T00:18:51.628963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
7월8월10월12월권종그룹출력가9월11월
7월1.0000.7010.5250.4630.0000.0000.0000.739
8월0.7011.0000.5640.5270.0000.0000.6680.407
10월0.5250.5641.0000.5330.0000.0000.1220.668
12월0.4630.5270.5331.0000.0000.0000.0000.772
권종그룹0.0000.0000.0000.0001.0000.3030.0000.000
출력가0.0000.0000.0000.0000.3031.0000.0000.242
9월0.0000.6680.1220.0000.0000.0001.0000.000
11월0.7390.4070.6680.7720.0000.2420.0001.000

Missing values

2023-12-13T00:18:46.445609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:18:46.690638image/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

방문시기방문시작월방문종료월상품권종그룹권종출력가구분7월8월9월10월11월12월데이터기준일자
02020712달콤한 힐링족욕+박물관 관람일반족욕1팀(최대2명)5,000원인원수0000002021-02-09
12020712<NA><NA>족욕1팀(최대1명)2,500원인원수0000002021-02-09
22020712<NA><NA>족욕1팀 (최대2명)0원인원수3001144602021-02-09
32020712<NA><NA>족욕1팀 (최대2인)6,000원인원수36320513302021-02-09
42020712<NA><NA>족욕1팀(최대2인) 50%할인3,000원인원수1106902021-02-09
52020712<NA><NA>족욕1팀(최대2명) 20%할인4,800원인원수616021902021-02-09
62020712건강채움소 보제원+박물관 관람일반한방체험1인5,000원인원수28420312302021-02-09
72020712<NA><NA>한방체험1인 50%할인2,500원인원수0301002021-02-09
82020712<NA><NA>한방체험1인 20%할인4,000원인원수1190101302021-02-09
92020712박물관_즐거운한방DIY일반일반3,000원인원수0000002021-02-09
방문시기방문시작월방문종료월상품권종그룹권종출력가구분7월8월9월10월11월12월데이터기준일자
502020712두한족열일반일반6,000원인원수0003315202021-02-09
512020712<NA><NA>족욕1팀(최대2인) 50%할인3,000원인원수0002102021-02-09
522020712<NA><NA>족욕1팀(최대2명) 20%할인4,800원인원수000173002021-02-09
532020712한방공작소일반일반3,000원인원수00053302021-02-09
542020712<NA><NA>일반1,000원인원수00043002021-02-09
552020712<NA><NA>일반 20%할인2,400원인원수0000302021-02-09
562020712<NA><NA>일반 50%할인1,500원인원수0000102021-02-09
572020712<NA><NA>50% 할인500원인원수0000102021-02-09
582020712<NA><NA>20%할인800원인원수00082602021-02-09
592020712시장투어일반일반10,000원인원수00001002021-02-09