Overview

Dataset statistics

Number of variables19
Number of observations500
Missing cells499
Missing cells (%)5.3%
Duplicate rows101
Duplicate rows (%)20.2%
Total size in memory77.3 KiB
Average record size in memory158.3 B

Variable types

Categorical16
Numeric2
Text1

Dataset

Description샘플 데이터
Author대한제분㈜ / 0234550285
URLhttps://www.bigdata-transportation.kr/frn/prdt/detail?prdtId=PRDTNUM_000000020451

Alerts

결제시간_년 has constant value ""Constant
결제시간_월 has constant value ""Constant
결제시간_일 has constant value ""Constant
요일 has constant value ""Constant
할인가격 has constant value ""Constant
Dataset has 101 (20.2%) duplicate rowsDuplicates
오더유형상세명 is highly overall correlated with 오더유형명 and 3 other fieldsHigh correlation
할인율 is highly overall correlated with 상권 and 5 other fieldsHigh correlation
오더유형명 is highly overall correlated with 오더유형상세명 and 3 other fieldsHigh correlation
할인명 is highly overall correlated with 상권 and 5 other fieldsHigh correlation
품목중분류 is highly overall correlated with 품목대분류 and 1 other fieldsHigh correlation
품목소분류 is highly overall correlated with 품목대분류 and 1 other fieldsHigh correlation
품목대분류 is highly overall correlated with 품목중분류 and 1 other fieldsHigh correlation
매출구분 is highly overall correlated with 할인율 and 1 other fieldsHigh correlation
주소 is highly overall correlated with 상권High correlation
상권 is highly overall correlated with 주소 and 2 other fieldsHigh correlation
결제분류 is highly overall correlated with 오더유형명 and 3 other fieldsHigh correlation
매출구분 is highly imbalanced (82.6%)Imbalance
오더유형명 is highly imbalanced (57.8%)Imbalance
오더유형상세명 is highly imbalanced (67.2%)Imbalance
판매수량 is highly imbalanced (70.4%)Imbalance
할인율 is highly imbalanced (53.2%)Imbalance
할인명 is highly imbalanced (54.2%)Imbalance
할인가격 has 499 (99.8%) missing valuesMissing
총금액 has 29 (5.8%) zerosZeros

Reproduction

Analysis started2024-01-06 12:00:29.818181
Analysis finished2024-01-06 12:00:38.230408
Duration8.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주소
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
서울특별시 강남구
184 
서울특별시 서초구
145 
서울특별시 송파구
74 
경기도 수원시 영통구
27 
경기도 성남시 분당구
22 
Other values (5)
48 

Length

Max length11
Median length9
Mean length9.264
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 강남구
2nd row서울특별시 서초구
3rd row서울특별시 서초구
4th row서울특별시 서초구
5th row서울특별시 서초구

Common Values

ValueCountFrequency (%)
서울특별시 강남구 184
36.8%
서울특별시 서초구 145
29.0%
서울특별시 송파구 74
14.8%
경기도 수원시 영통구 27
 
5.4%
경기도 성남시 분당구 22
 
4.4%
서울특별시 용산구 15
 
3.0%
서울특별시 마포구 11
 
2.2%
서울특별시 영등포구 10
 
2.0%
경기도 수원시 팔달구 8
 
1.6%
제주특별자치도 제주시 4
 
0.8%

Length

2024-01-06T12:00:38.400263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:38.653377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 439
41.5%
강남구 184
17.4%
서초구 145
 
13.7%
송파구 74
 
7.0%
경기도 57
 
5.4%
수원시 35
 
3.3%
영통구 27
 
2.6%
성남시 22
 
2.1%
분당구 22
 
2.1%
용산구 15
 
1.4%
Other values (5) 37
 
3.5%

상권
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
병원
163 
주택가
154 
복합상권
117 
쇼핑몰
36 
오피스
30 

Length

Max length4
Median length3
Mean length2.908
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
병원 163
32.6%
주택가 154
30.8%
복합상권 117
23.4%
쇼핑몰 36
 
7.2%
오피스 30
 
6.0%

Length

2024-01-06T12:00:39.111646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:39.498118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
병원 163
32.6%
주택가 154
30.8%
복합상권 117
23.4%
쇼핑몰 36
 
7.2%
오피스 30
 
6.0%

매출구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
매출
487 
반품
 
13

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
매출 487
97.4%
반품 13
 
2.6%

Length

2024-01-06T12:00:39.907256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:40.257493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
매출 487
97.4%
반품 13
 
2.6%

오더유형명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
매장주문
413 
배달
 
38
스마트오더(예약)
 
27
포장
 
12
스마트오더(픽업)
 
10

Length

Max length9
Median length4
Mean length4.17
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
매장주문 413
82.6%
배달 38
 
7.6%
스마트오더(예약) 27
 
5.4%
포장 12
 
2.4%
스마트오더(픽업) 10
 
2.0%

Length

2024-01-06T12:00:40.672966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:41.092529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
매장주문 413
82.6%
배달 38
 
7.6%
스마트오더(예약 27
 
5.4%
포장 12
 
2.4%
스마트오더(픽업 10
 
2.0%

오더유형상세명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
일반
440 
배달의민족(라이더스)
 
21
쿠팡이츠
 
17
배달의민족(포장)
 
12
일반(스마트오더_픽업)
 
10

Length

Max length12
Median length2
Mean length2.814
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 440
88.0%
배달의민족(라이더스) 21
 
4.2%
쿠팡이츠 17
 
3.4%
배달의민족(포장) 12
 
2.4%
일반(스마트오더_픽업) 10
 
2.0%

Length

2024-01-06T12:00:41.473366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:41.836585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 440
88.0%
배달의민족(라이더스 21
 
4.2%
쿠팡이츠 17
 
3.4%
배달의민족(포장 12
 
2.4%
일반(스마트오더_픽업 10
 
2.0%

결제시간_년
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2022
500 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 500
100.0%

Length

2024-01-06T12:00:42.215649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:42.509532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 500
100.0%

결제시간_월
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2024-01-06T12:00:42.800846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:43.204364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

결제시간_일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2024-01-06T12:00:43.538872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:43.805384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

결제시간_시간
Real number (ℝ)

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.792
Minimum6
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-06T12:00:44.078800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile6
Q18
median9
Q310
95-th percentile10
Maximum11
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3252353
Coefficient of variation (CV)0.15073195
Kurtosis-0.72943581
Mean8.792
Median Absolute Deviation (MAD)1
Skewness-0.70771401
Sum4396
Variance1.7562485
MonotonicityNot monotonic
2024-01-06T12:00:44.386846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
10 206
41.2%
9 115
23.0%
7 71
 
14.2%
8 68
 
13.6%
6 36
 
7.2%
11 4
 
0.8%
ValueCountFrequency (%)
6 36
 
7.2%
7 71
 
14.2%
8 68
 
13.6%
9 115
23.0%
10 206
41.2%
11 4
 
0.8%
ValueCountFrequency (%)
11 4
 
0.8%
10 206
41.2%
9 115
23.0%
8 68
 
13.6%
7 71
 
14.2%
6 36
 
7.2%

요일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
토요일
500 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
토요일 500
100.0%

Length

2024-01-06T12:00:44.722993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:45.038077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토요일 500
100.0%

품목대분류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Food
347 
Beverage
153 

Length

Max length8
Median length4
Mean length5.224
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBeverage
2nd rowBeverage
3rd rowBeverage
4th rowFood
5th rowFood

Common Values

ValueCountFrequency (%)
Food 347
69.4%
Beverage 153
30.6%

Length

2024-01-06T12:00:45.438289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:45.782674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
food 347
69.4%
beverage 153
30.6%

품목중분류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
베이커리
205 
커피
115 
케이크
93 
식사
49 
음료
36 

Length

Max length4
Median length3
Mean length3.002
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row커피
2nd row커피
3rd row음료
4th row베이커리
5th row베이커리

Common Values

ValueCountFrequency (%)
베이커리 205
41.0%
커피 115
23.0%
케이크 93
18.6%
식사 49
 
9.8%
음료 36
 
7.2%
티 2
 
0.4%

Length

2024-01-06T12:00:46.148823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:46.494251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
베이커리 205
41.0%
커피 115
23.0%
케이크 93
18.6%
식사 49
 
9.8%
음료 36
 
7.2%
티 2
 
0.4%

품목소분류
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
브레드
155 
에스프레소
77 
홀케이크
63 
아이스 에스프레소
38 
조각케이크
30 
Other values (13)
137 

Length

Max length10
Median length9
Mean length4.444
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row에스프레소
2nd row에스프레소
3rd rowAdd Extra
4th row브레드
5th row브레드

Common Values

ValueCountFrequency (%)
브레드 155
31.0%
에스프레소 77
15.4%
홀케이크 63
12.6%
아이스 에스프레소 38
 
7.6%
조각케이크 30
 
6.0%
샌드위치 26
 
5.2%
마카롱 17
 
3.4%
식사메뉴 15
 
3.0%
쿠키 15
 
3.0%
양과자 10
 
2.0%
Other values (8) 54
 
10.8%

Length

2024-01-06T12:00:46.920046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
브레드 155
27.0%
에스프레소 115
20.0%
홀케이크 63
11.0%
아이스 48
 
8.4%
조각케이크 30
 
5.2%
샌드위치 26
 
4.5%
마카롱 17
 
3.0%
쿠키 15
 
2.6%
스페셜리티 15
 
2.6%
식사메뉴 15
 
2.6%
Other values (10) 75
13.1%

총금액
Real number (ℝ)

ZEROS 

Distinct79
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8909.8
Minimum0
Maximum49000
Zeros29
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-01-06T12:00:47.345613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12800
median5200
Q37500
95-th percentile40000
Maximum49000
Range49000
Interquartile range (IQR)4700

Descriptive statistics

Standard deviation11439.097
Coefficient of variation (CV)1.2838781
Kurtosis4.052759
Mean8909.8
Median Absolute Deviation (MAD)2400
Skewness2.2890614
Sum4454900
Variance1.3085295 × 108
MonotonicityNot monotonic
2024-01-06T12:00:47.766746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29
 
5.8%
5200 27
 
5.4%
2400 26
 
5.2%
2800 26
 
5.2%
5900 22
 
4.4%
2700 22
 
4.4%
4700 21
 
4.2%
5700 17
 
3.4%
39000 14
 
2.8%
8000 14
 
2.8%
Other values (69) 282
56.4%
ValueCountFrequency (%)
0 29
5.8%
500 4
 
0.8%
1000 1
 
0.2%
1300 6
 
1.2%
1600 2
 
0.4%
1800 1
 
0.2%
2000 5
 
1.0%
2200 9
 
1.8%
2300 4
 
0.8%
2400 26
5.2%
ValueCountFrequency (%)
49000 4
 
0.8%
45000 12
2.4%
43000 5
 
1.0%
41000 2
 
0.4%
40000 3
 
0.6%
39000 14
2.8%
38000 4
 
0.8%
37000 3
 
0.6%
25000 7
1.4%
21000 3
 
0.6%

판매수량
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
456 
2
 
40
3
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 456
91.2%
2 40
 
8.0%
3 4
 
0.8%

Length

2024-01-06T12:00:48.106880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:48.419701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 456
91.2%
2 40
 
8.0%
3 4
 
0.8%

할인율
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
394 
10%
56 
30%
 
32
50%
 
10
20%
 
8

Length

Max length4
Median length4
Mean length3.788
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50%
2nd row<NA>
3rd row<NA>
4th row10%
5th row10%

Common Values

ValueCountFrequency (%)
<NA> 394
78.8%
10% 56
 
11.2%
30% 32
 
6.4%
50% 10
 
2.0%
20% 8
 
1.6%

Length

2024-01-06T12:00:48.823819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:49.446764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 394
78.8%
10 56
 
11.2%
30 32
 
6.4%
50 10
 
2.0%
20 8
 
1.6%

할인가격
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing499
Missing (%)99.8%
Memory size4.0 KiB
2024-01-06T12:00:49.782117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters3
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

Unique1 ?
Unique (%)100.0%

Sample

1st row500원
ValueCountFrequency (%)
500원 1
100.0%
2024-01-06T12:00:50.852720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
50.0%
5 1
25.0%
원 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
75.0%
Other Letter 1
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
66.7%
5 1
33.3%
Other Letter
ValueCountFrequency (%)
원 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3
75.0%
Hangul 1
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2
66.7%
5 1
33.3%
Hangul
ValueCountFrequency (%)
원 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
75.0%
Hangul 1
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
66.7%
5 1
33.3%
Hangul
ValueCountFrequency (%)
원 1
100.0%

할인명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
<NA>
393 
입점제휴
58 
제휴할인
 
32
고객사임직원할인
 
16
텀블러할인
 
1

Length

Max length8
Median length4
Mean length4.13
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 393
78.6%
입점제휴 58
 
11.6%
제휴할인 32
 
6.4%
고객사임직원할인 16
 
3.2%
텀블러할인 1
 
0.2%

Length

2024-01-06T12:00:51.363209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:51.832465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 393
78.6%
입점제휴 58
 
11.6%
제휴할인 32
 
6.4%
고객사임직원할인 16
 
3.2%
텀블러할인 1
 
0.2%

결제분류
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
카드
230 
모바일쿠폰
91 
전자상품권
60 
후불
55 
멤버십포인트
 
21
Other values (5)
43 

Length

Max length6
Median length2
Mean length3.14
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row카드
2nd row전자상품권
3rd row전자상품권
4th row전자상품권
5th row전자상품권

Common Values

ValueCountFrequency (%)
카드 230
46.0%
모바일쿠폰 91
 
18.2%
전자상품권 60
 
12.0%
후불 55
 
11.0%
멤버십포인트 21
 
4.2%
선불금 17
 
3.4%
가승인 14
 
2.8%
쿠폰 8
 
1.6%
상품권 2
 
0.4%
현금 2
 
0.4%

Length

2024-01-06T12:00:52.288709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T12:00:52.769881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
카드 230
46.0%
모바일쿠폰 91
 
18.2%
전자상품권 60
 
12.0%
후불 55
 
11.0%
멤버십포인트 21
 
4.2%
선불금 17
 
3.4%
가승인 14
 
2.8%
쿠폰 8
 
1.6%
상품권 2
 
0.4%
현금 2
 
0.4%

Interactions

2024-01-06T12:00:36.567353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:00:35.994355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:00:36.824463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T12:00:36.318218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-06T12:00:53.185056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주소상권매출구분오더유형명오더유형상세명결제시간_시간품목대분류품목중분류품목소분류총금액판매수량할인율할인명결제분류
주소1.0000.9640.0000.6110.3470.6790.2400.3830.5790.4090.0000.6450.6120.772
상권0.9641.0000.1030.4500.4250.5420.0960.2790.4790.2050.0760.6070.5820.737
매출구분0.0000.1031.0000.3790.3780.1450.0000.1090.2090.0000.072NaNNaN0.293
오더유형명0.6110.4500.3791.0000.9910.4930.2080.3940.6630.5730.258NaNNaN0.874
오더유형상세명0.3470.4250.3780.9911.0000.2360.1840.2140.5270.2170.262NaNNaN0.848
결제시간_시간0.6790.5420.1450.4930.2361.0000.2070.5560.6630.5980.3230.4760.4060.566
품목대분류0.2400.0960.0000.2080.1840.2071.0001.0001.0000.2280.0360.5280.5480.252
품목중분류0.3830.2790.1090.3940.2140.5561.0001.0001.0000.6160.1860.3730.3230.356
품목소분류0.5790.4790.2090.6630.5270.6631.0001.0001.0000.7940.2510.5030.3930.553
총금액0.4090.2050.0000.5730.2170.5980.2280.6160.7941.0000.7360.0000.0000.305
판매수량0.0000.0760.0720.2580.2620.3230.0360.1860.2510.7361.0000.1060.1160.195
할인율0.6450.607NaNNaNNaN0.4760.5280.3730.5030.0000.1061.0000.8950.682
할인명0.6120.582NaNNaNNaN0.4060.5480.3230.3930.0000.1160.8951.0000.660
결제분류0.7720.7370.2930.8740.8480.5660.2520.3560.5530.3050.1950.6820.6601.000
2024-01-06T12:00:53.698572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주소오더유형상세명할인율오더유형명할인명품목중분류결제분류판매수량품목소분류상권품목대분류매출구분
주소1.0000.1500.4690.2970.4370.2120.3390.0000.2620.7310.1830.000
오더유형상세명0.1501.0001.0000.8651.0000.1460.5100.2040.2980.1700.2240.460
할인율0.4691.0001.0001.0000.9620.2450.5380.0980.3150.5320.3561.000
오더유형명0.2970.8651.0001.0001.0000.2800.5450.2010.4080.1820.2540.460
할인명0.4371.0000.9621.0001.0000.2100.5130.1080.2370.5060.3711.000
품목중분류0.2120.1460.2450.2800.2101.0000.1950.0770.9880.1920.9960.078
결제분류0.3390.5100.5380.5450.5130.1951.0000.1170.2450.3940.1910.223
판매수량0.0000.2040.0980.2010.1080.0770.1171.0000.1160.0570.0590.120
품목소분류0.2620.2980.3150.4080.2370.9880.2450.1161.0000.2640.9840.162
상권0.7310.1700.5320.1820.5060.1920.3940.0570.2641.0000.1170.126
품목대분류0.1830.2240.3560.2540.3710.9960.1910.0590.9840.1171.0000.000
매출구분0.0000.4601.0000.4601.0000.0780.2230.1200.1620.1260.0001.000
2024-01-06T12:00:54.065738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결제시간_시간총금액주소상권매출구분오더유형명오더유형상세명품목대분류품목중분류품목소분류판매수량할인율할인명결제분류
결제시간_시간1.000-0.1210.4410.4050.1040.3610.1610.1490.2290.3250.1410.4040.3400.340
총금액-0.1211.0000.1990.1190.0000.3750.1260.2260.3610.3910.4380.0000.0000.143
주소0.4410.1991.0000.7310.0000.2970.1500.1830.2120.2620.0000.4690.4370.339
상권0.4050.1190.7311.0000.1260.1820.1700.1170.1920.2640.0570.5320.5060.394
매출구분0.1040.0000.0000.1261.0000.4600.4600.0000.0780.1620.1201.0001.0000.223
오더유형명0.3610.3750.2970.1820.4601.0000.8650.2540.2800.4080.2011.0001.0000.545
오더유형상세명0.1610.1260.1500.1700.4600.8651.0000.2240.1460.2980.2041.0001.0000.510
품목대분류0.1490.2260.1830.1170.0000.2540.2241.0000.9960.9840.0590.3560.3710.191
품목중분류0.2290.3610.2120.1920.0780.2800.1460.9961.0000.9880.0770.2450.2100.195
품목소분류0.3250.3910.2620.2640.1620.4080.2980.9840.9881.0000.1160.3150.2370.245
판매수량0.1410.4380.0000.0570.1200.2010.2040.0590.0770.1161.0000.0980.1080.117
할인율0.4040.0000.4690.5321.0001.0001.0000.3560.2450.3150.0981.0000.9620.538
할인명0.3400.0000.4370.5061.0001.0001.0000.3710.2100.2370.1080.9621.0000.513
결제분류0.3400.1430.3390.3940.2230.5450.5100.1910.1950.2450.1170.5380.5131.000

Missing values

2024-01-06T12:00:37.216388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-06T12:00:37.930900image/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

주소상권매출구분오더유형명오더유형상세명결제시간_년결제시간_월결제시간_일결제시간_시간요일품목대분류품목중분류품목소분류총금액판매수량할인율할인가격할인명결제분류
0서울특별시 강남구주택가매출매장주문일반2022117토요일Beverage커피에스프레소4700150%<NA>고객사임직원할인카드
1서울특별시 서초구주택가매출매장주문일반2022117토요일Beverage커피에스프레소47001<NA><NA><NA>전자상품권
2서울특별시 서초구주택가매출매장주문일반2022117토요일Beverage음료Add Extra01<NA><NA><NA>전자상품권
3서울특별시 서초구주택가매출매장주문일반2022117토요일Food베이커리브레드4800210%<NA>입점제휴전자상품권
4서울특별시 서초구주택가매출매장주문일반2022117토요일Food베이커리브레드5000210%<NA>입점제휴전자상품권
5서울특별시 서초구주택가매출매장주문일반2022117토요일Food베이커리브레드4800210%<NA>입점제휴전자상품권
6서울특별시 서초구주택가매출매장주문일반2022117토요일Food베이커리브레드2700110%<NA>입점제휴전자상품권
7서울특별시 서초구주택가매출매장주문일반2022117토요일Food베이커리브레드2400110%<NA>입점제휴전자상품권
8서울특별시 서초구주택가매출매장주문일반2022117토요일Beverage커피에스프레소4700130%<NA>제휴할인모바일쿠폰
9서울특별시 서초구주택가매출매장주문일반2022117토요일Beverage커피아이스 에스프레소4700130%<NA>제휴할인모바일쿠폰
주소상권매출구분오더유형명오더유형상세명결제시간_년결제시간_월결제시간_일결제시간_시간요일품목대분류품목중분류품목소분류총금액판매수량할인율할인가격할인명결제분류
490경기도 수원시 영통구쇼핑몰매출매장주문일반20221110토요일Food베이커리브레드51001<NA><NA><NA>모바일쿠폰
491경기도 수원시 영통구쇼핑몰매출매장주문일반20221110토요일Food베이커리브레드51001<NA><NA><NA>가승인
492경기도 수원시 영통구쇼핑몰매출매장주문일반20221110토요일Food베이커리브레드24001<NA><NA><NA>모바일쿠폰
493경기도 수원시 영통구쇼핑몰매출매장주문일반20221110토요일Food베이커리브레드24001<NA><NA><NA>가승인
494경기도 수원시 영통구쇼핑몰매출매장주문일반20221110토요일Food베이커리파운드 및 카스텔라95001<NA><NA><NA>모바일쿠폰
495경기도 수원시 영통구쇼핑몰매출매장주문일반20221110토요일Food베이커리파운드 및 카스텔라95001<NA><NA><NA>가승인
496제주특별자치도 제주시복합상권매출매장주문일반2022118토요일Beverage커피에스프레소20001<NA><NA><NA>후불
497제주특별자치도 제주시복합상권매출매장주문일반2022118토요일Beverage커피아이스 에스프레소01<NA><NA><NA>후불
498제주특별자치도 제주시복합상권매출매장주문일반2022118토요일Beverage커피에스프레소20001<NA><NA><NA>후불
499제주특별자치도 제주시복합상권매출매장주문일반2022118토요일Beverage커피아이스 에스프레소01<NA><NA><NA>후불

Duplicate rows

Most frequently occurring

주소상권매출구분오더유형명오더유형상세명결제시간_년결제시간_월결제시간_일결제시간_시간요일품목대분류품목중분류품목소분류총금액판매수량할인율할인가격할인명결제분류# duplicates
22서울특별시 강남구병원매출매장주문일반2022119토요일Food베이커리브레드26001<NA><NA><NA>카드5
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