Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory908.2 KiB
Average record size in memory93.0 B

Variable types

DateTime1
Categorical2
Text2
Numeric5

Dataset

Description화훼유통정보시스템(https://flower.at.or.kr/main/flowerMain.do)에 수집된전국 5대 화훼공판장 소속 도매법인을 통해 거래되는 품목, 품종들의 경락가격 등 시세자료
URLhttps://www.data.go.kr/data/15052544/fileData.do

Alerts

최고단가(원) is highly overall correlated with 최저단가(원) and 1 other fieldsHigh correlation
최저단가(원) is highly overall correlated with 최고단가(원) and 1 other fieldsHigh correlation
평균단가(원) is highly overall correlated with 최고단가(원) and 1 other fieldsHigh correlation
총수량 is highly overall correlated with 총금액(원)High correlation
총금액(원) is highly overall correlated with 총수량High correlation
화훼구분명 is highly overall correlated with 등급명High correlation
등급명 is highly overall correlated with 화훼구분명High correlation

Reproduction

Analysis started2023-12-12 08:07:07.345771
Analysis finished2023-12-12 08:07:13.234944
Duration5.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정산일자
Date

Distinct75
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-01-03 00:00:00
Maximum2022-04-11 00:00:00
2023-12-12T17:07:13.348088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:13.521565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

화훼구분명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
절화
7208 
난
1495 
관엽
1297 

Length

Max length2
Median length2
Mean length1.8505
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row절화
2nd row난
3rd row절화
4th row절화
5th row절화

Common Values

ValueCountFrequency (%)
절화 7208
72.1%
난 1495
 
14.9%
관엽 1297
 
13.0%

Length

2023-12-12T17:07:13.693983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:07:13.809078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
절화 7208
72.1%
난 1495
 
14.9%
관엽 1297
 
13.0%

품목명
Text

Distinct286
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T17:07:14.147692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.1454
Min length1

Characters and Unicode

Total characters31454
Distinct characters275
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)0.7%

Sample

1st row거베라
2nd row팔레높시스
3rd row금어초
4th row리시안사스
5th row장미
ValueCountFrequency (%)
장미 2726
27.3%
호접란 837
 
8.4%
팔레높시스 443
 
4.4%
라넌큘러스 420
 
4.2%
튜립 406
 
4.1%
국화 402
 
4.0%
프리지아 393
 
3.9%
리시안사스 285
 
2.9%
거베라 273
 
2.7%
델피니움 182
 
1.8%
Other values (276) 3633
36.3%
2023-12-12T17:07:14.637704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
미 2777
 
8.8%
장 2774
 
8.8%
스 2164
 
6.9%
라 1053
 
3.3%
시 1020
 
3.2%
리 1010
 
3.2%
란 968
 
3.1%
아 908
 
2.9%
호 867
 
2.8%
접 837
 
2.7%
Other values (265) 17076
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31332
99.6%
Close Punctuation 52
 
0.2%
Open Punctuation 52
 
0.2%
Uppercase Letter 18
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 2777
 
8.9%
장 2774
 
8.9%
스 2164
 
6.9%
라 1053
 
3.4%
시 1020
 
3.3%
리 1010
 
3.2%
란 968
 
3.1%
아 908
 
2.9%
호 867
 
2.8%
접 837
 
2.7%
Other values (260) 16954
54.1%
Uppercase Letter
ValueCountFrequency (%)
O 6
33.3%
B 6
33.3%
X 6
33.3%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31332
99.6%
Common 104
 
0.3%
Latin 18
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
미 2777
 
8.9%
장 2774
 
8.9%
스 2164
 
6.9%
라 1053
 
3.4%
시 1020
 
3.3%
리 1010
 
3.2%
란 968
 
3.1%
아 908
 
2.9%
호 867
 
2.8%
접 837
 
2.7%
Other values (260) 16954
54.1%
Latin
ValueCountFrequency (%)
O 6
33.3%
B 6
33.3%
X 6
33.3%
Common
ValueCountFrequency (%)
) 52
50.0%
( 52
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31332
99.6%
ASCII 122
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
미 2777
 
8.9%
장 2774
 
8.9%
스 2164
 
6.9%
라 1053
 
3.4%
시 1020
 
3.3%
리 1010
 
3.2%
란 968
 
3.1%
아 908
 
2.9%
호 867
 
2.8%
접 837
 
2.7%
Other values (260) 16954
54.1%
ASCII
ValueCountFrequency (%)
) 52
42.6%
( 52
42.6%
O 6
 
4.9%
B 6
 
4.9%
X 6
 
4.9%

품종명
Text

Distinct1862
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T17:07:14.948390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length4.8109
Min length1

Characters and Unicode

Total characters48109
Distinct characters559
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique756 ?
Unique (%)7.6%

Sample

1st row폼포니(제이제이)
2nd rowV3
3rd row화이트
4th row리시안(겹꽃)
5th row스윗핑크(sp)
ValueCountFrequency (%)
쏠레이 216
 
2.2%
혼합 114
 
1.1%
미니 112
 
1.1%
빅토리아 110
 
1.1%
화이트 109
 
1.1%
헤라 96
 
1.0%
푸에고 93
 
0.9%
핑크 91
 
0.9%
라넌큘러스 86
 
0.9%
하젤 77
 
0.8%
Other values (1852) 8901
89.0%
2023-12-12T17:07:15.453438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 1926
 
4.0%
이 1577
 
3.3%
( 1455
 
3.0%
) 1455
 
3.0%
라 1188
 
2.5%
아 1138
 
2.4%
리 1122
 
2.3%
5 988
 
2.1%
p 957
 
2.0%
s 954
 
2.0%
Other values (549) 35349
73.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39675
82.5%
Decimal Number 2496
 
5.2%
Lowercase Letter 1920
 
4.0%
Open Punctuation 1455
 
3.0%
Close Punctuation 1455
 
3.0%
Other Punctuation 620
 
1.3%
Uppercase Letter 434
 
0.9%
Dash Punctuation 34
 
0.1%
Letter Number 14
 
< 0.1%
Space Separator 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 1926
 
4.9%
이 1577
 
4.0%
라 1188
 
3.0%
아 1138
 
2.9%
리 1122
 
2.8%
지 951
 
2.4%
트 906
 
2.3%
가 859
 
2.2%
레 855
 
2.2%
대 803
 
2.0%
Other values (504) 28350
71.5%
Uppercase Letter
ValueCountFrequency (%)
T 84
19.4%
B 84
19.4%
K 76
17.5%
V 50
11.5%
L 26
 
6.0%
A 16
 
3.7%
P 16
 
3.7%
H 14
 
3.2%
O 13
 
3.0%
C 11
 
2.5%
Other values (13) 44
10.1%
Decimal Number
ValueCountFrequency (%)
5 988
39.6%
3 714
28.6%
1 153
 
6.1%
4 143
 
5.7%
6 129
 
5.2%
7 117
 
4.7%
8 94
 
3.8%
9 69
 
2.8%
2 53
 
2.1%
0 36
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
p 957
49.8%
s 954
49.7%
x 3
 
0.2%
o 3
 
0.2%
b 3
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1455
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1455
100.0%
Other Punctuation
ValueCountFrequency (%)
. 620
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 14
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39675
82.5%
Common 6066
 
12.6%
Latin 2368
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 1926
 
4.9%
이 1577
 
4.0%
라 1188
 
3.0%
아 1138
 
2.9%
리 1122
 
2.8%
지 951
 
2.4%
트 906
 
2.3%
가 859
 
2.2%
레 855
 
2.2%
대 803
 
2.0%
Other values (504) 28350
71.5%
Latin
ValueCountFrequency (%)
p 957
40.4%
s 954
40.3%
T 84
 
3.5%
B 84
 
3.5%
K 76
 
3.2%
V 50
 
2.1%
L 26
 
1.1%
A 16
 
0.7%
P 16
 
0.7%
H 14
 
0.6%
Other values (19) 91
 
3.8%
Common
ValueCountFrequency (%)
( 1455
24.0%
) 1455
24.0%
5 988
16.3%
3 714
11.8%
. 620
10.2%
1 153
 
2.5%
4 143
 
2.4%
6 129
 
2.1%
7 117
 
1.9%
8 94
 
1.5%
Other values (6) 198
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39675
82.5%
ASCII 8420
 
17.5%
Number Forms 14
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 1926
 
4.9%
이 1577
 
4.0%
라 1188
 
3.0%
아 1138
 
2.9%
리 1122
 
2.8%
지 951
 
2.4%
트 906
 
2.3%
가 859
 
2.2%
레 855
 
2.2%
대 803
 
2.0%
Other values (504) 28350
71.5%
ASCII
ValueCountFrequency (%)
( 1455
17.3%
) 1455
17.3%
5 988
11.7%
p 957
11.4%
s 954
11.3%
3 714
8.5%
. 620
7.4%
1 153
 
1.8%
4 143
 
1.7%
6 129
 
1.5%
Other values (34) 852
10.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 14
100.0%

등급명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
특1
3819 
특2
2823 
특3
1496 
상1
796 
상2
519 
Other values (4)
547 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row특2
2nd row특1
3rd row특2
4th row특2
5th row특2

Common Values

ValueCountFrequency (%)
특1 3819
38.2%
특2 2823
28.2%
특3 1496
 
15.0%
상1 796
 
8.0%
상2 519
 
5.2%
상3 490
 
4.9%
보3 41
 
0.4%
보2 14
 
0.1%
보1 2
 
< 0.1%

Length

2023-12-12T17:07:15.618659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:07:15.773136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
특1 3819
38.2%
특2 2823
28.2%
특3 1496
 
15.0%
상1 796
 
8.0%
상2 519
 
5.2%
상3 490
 
4.9%
보3 41
 
0.4%
보2 14
 
0.1%
보1 2
 
< 0.1%

최고단가(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct1556
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7468.9642
Minimum100
Maximum54000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:07:15.964526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile1230
Q13495
median6000
Q39400
95-th percentile19400
Maximum54000
Range53900
Interquartile range (IQR)5905

Descriptive statistics

Standard deviation5984.7806
Coefficient of variation (CV)0.80128655
Kurtosis5.7039757
Mean7468.9642
Median Absolute Deviation (MAD)2870
Skewness1.9773775
Sum74689642
Variance35817598
MonotonicityNot monotonic
2023-12-12T17:07:16.119511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7000 102
 
1.0%
3000 96
 
1.0%
4000 91
 
0.9%
5000 91
 
0.9%
10000 85
 
0.9%
2000 70
 
0.7%
1500 61
 
0.6%
8000 60
 
0.6%
3500 60
 
0.6%
9000 58
 
0.6%
Other values (1546) 9226
92.3%
ValueCountFrequency (%)
100 1
 
< 0.1%
200 2
< 0.1%
270 1
 
< 0.1%
290 1
 
< 0.1%
320 1
 
< 0.1%
330 1
 
< 0.1%
360 1
 
< 0.1%
370 3
< 0.1%
380 2
< 0.1%
381 1
 
< 0.1%
ValueCountFrequency (%)
54000 1
 
< 0.1%
51100 1
 
< 0.1%
50500 1
 
< 0.1%
46900 1
 
< 0.1%
45500 1
 
< 0.1%
45000 1
 
< 0.1%
44750 1
 
< 0.1%
42100 1
 
< 0.1%
42002 1
 
< 0.1%
42000 4
< 0.1%

최저단가(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct1386
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6996.4189
Minimum100
Maximum50000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:07:16.254702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile1150
Q13150
median5600
Q38850
95-th percentile18200
Maximum50000
Range49900
Interquartile range (IQR)5700

Descriptive statistics

Standard deviation5674.4684
Coefficient of variation (CV)0.81105327
Kurtosis6.1036322
Mean6996.4189
Median Absolute Deviation (MAD)2670
Skewness2.0326917
Sum69964189
Variance32199592
MonotonicityNot monotonic
2023-12-12T17:07:16.409122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000 114
 
1.1%
4000 112
 
1.1%
5000 110
 
1.1%
2000 95
 
0.9%
7000 91
 
0.9%
10000 88
 
0.9%
3500 87
 
0.9%
6000 84
 
0.8%
1000 82
 
0.8%
1500 73
 
0.7%
Other values (1376) 9064
90.6%
ValueCountFrequency (%)
100 1
 
< 0.1%
200 2
< 0.1%
240 1
 
< 0.1%
290 1
 
< 0.1%
310 1
 
< 0.1%
320 2
< 0.1%
350 1
 
< 0.1%
360 2
< 0.1%
370 3
< 0.1%
380 2
< 0.1%
ValueCountFrequency (%)
50000 1
 
< 0.1%
49700 1
 
< 0.1%
45500 1
 
< 0.1%
45000 1
 
< 0.1%
42000 6
0.1%
40600 1
 
< 0.1%
40250 1
 
< 0.1%
40002 1
 
< 0.1%
40000 5
0.1%
39500 1
 
< 0.1%

평균단가(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct3430
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7227.3331
Minimum100
Maximum50400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:07:16.583198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile1200.95
Q13330
median5838.5
Q39082.5
95-th percentile18750
Maximum50400
Range50300
Interquartile range (IQR)5752.5

Descriptive statistics

Standard deviation5794.2508
Coefficient of variation (CV)0.80171353
Kurtosis5.7637279
Mean7227.3331
Median Absolute Deviation (MAD)2791.5
Skewness1.9873562
Sum72273331
Variance33573342
MonotonicityNot monotonic
2023-12-12T17:07:16.776038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4000 78
 
0.8%
3000 73
 
0.7%
7000 70
 
0.7%
5000 69
 
0.7%
10000 61
 
0.6%
2000 61
 
0.6%
1500 53
 
0.5%
2500 52
 
0.5%
6000 52
 
0.5%
3500 50
 
0.5%
Other values (3420) 9381
93.8%
ValueCountFrequency (%)
100 1
< 0.1%
200 2
< 0.1%
255 1
< 0.1%
290 1
< 0.1%
320 2
< 0.1%
345 1
< 0.1%
359 1
< 0.1%
360 1
< 0.1%
365 1
< 0.1%
370 1
< 0.1%
ValueCountFrequency (%)
50400 1
 
< 0.1%
50250 1
 
< 0.1%
45500 1
 
< 0.1%
45000 1
 
< 0.1%
43750 1
 
< 0.1%
42750 1
 
< 0.1%
42050 1
 
< 0.1%
42001 1
 
< 0.1%
42000 4
< 0.1%
40234 1
 
< 0.1%

총수량
Real number (ℝ)

HIGH CORRELATION 

Distinct550
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.252
Minimum1
Maximum6500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:07:16.978454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q119
median38
Q392
95-th percentile400
Maximum6500
Range6499
Interquartile range (IQR)73

Descriptive statistics

Standard deviation218.0985
Coefficient of variation (CV)2.1329509
Kurtosis128.72991
Mean102.252
Median Absolute Deviation (MAD)24
Skewness8.202844
Sum1022520
Variance47566.955
MonotonicityNot monotonic
2023-12-12T17:07:17.138738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 574
 
5.7%
60 375
 
3.8%
15 354
 
3.5%
20 334
 
3.3%
24 270
 
2.7%
40 250
 
2.5%
12 249
 
2.5%
45 225
 
2.2%
16 219
 
2.2%
10 218
 
2.2%
Other values (540) 6932
69.3%
ValueCountFrequency (%)
1 13
 
0.1%
2 25
 
0.2%
3 48
 
0.5%
4 77
 
0.8%
5 125
1.2%
6 142
1.4%
7 104
1.0%
8 198
2.0%
9 121
1.2%
10 218
2.2%
ValueCountFrequency (%)
6500 1
< 0.1%
4300 1
< 0.1%
3400 1
< 0.1%
3000 1
< 0.1%
2960 2
< 0.1%
2845 1
< 0.1%
2840 1
< 0.1%
2820 1
< 0.1%
2778 1
< 0.1%
2385 1
< 0.1%

총금액(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct6542
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean479510.26
Minimum2980
Maximum25412000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:07:17.344043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2980
5-th percentile38642.5
Q1106230
median222795
Q3491092.5
95-th percentile1723598.7
Maximum25412000
Range25409020
Interquartile range (IQR)384862.5

Descriptive statistics

Standard deviation921928.05
Coefficient of variation (CV)1.9226451
Kurtosis156.70729
Mean479510.26
Median Absolute Deviation (MAD)144795
Skewness9.2309673
Sum4.7951026 × 109
Variance8.4995133 × 1011
MonotonicityNot monotonic
2023-12-12T17:07:17.549491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180000 42
 
0.4%
120000 41
 
0.4%
240000 40
 
0.4%
150000 30
 
0.3%
72000 29
 
0.3%
90000 27
 
0.3%
300000 27
 
0.3%
75000 26
 
0.3%
200000 24
 
0.2%
96000 22
 
0.2%
Other values (6532) 9692
96.9%
ValueCountFrequency (%)
2980 1
< 0.1%
3190 1
< 0.1%
3240 1
< 0.1%
3780 1
< 0.1%
4000 2
< 0.1%
4060 1
< 0.1%
4440 1
< 0.1%
5180 1
< 0.1%
5460 1
< 0.1%
5650 1
< 0.1%
ValueCountFrequency (%)
25412000 1
< 0.1%
22909500 1
< 0.1%
20405000 1
< 0.1%
16795410 1
< 0.1%
16783980 1
< 0.1%
13865500 1
< 0.1%
12845020 1
< 0.1%
11057650 1
< 0.1%
10804920 1
< 0.1%
10490600 1
< 0.1%

Interactions

2023-12-12T17:07:12.267231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:09.274701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:09.950397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:10.893507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:11.596833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:12.372271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:09.401818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:10.057550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:11.021497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:11.743370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:12.478342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:09.542384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:10.491920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:11.160224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:11.878575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:12.622910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:09.683246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:10.589239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:11.304669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:11.999815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:12.770919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:09.796595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:10.737202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:11.450292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:07:12.129147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:07:17.659507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정산일자화훼구분명등급명최고단가(원)최저단가(원)평균단가(원)총수량총금액(원)
정산일자1.0000.8960.4120.3760.3910.3940.2070.142
화훼구분명0.8961.0000.8280.2940.2950.3030.1820.082
등급명0.4120.8281.0000.2190.2150.2180.0270.030
최고단가(원)0.3760.2940.2191.0000.9760.9840.0740.216
최저단가(원)0.3910.2950.2150.9761.0000.9980.0880.055
평균단가(원)0.3940.3030.2180.9840.9981.0000.0790.097
총수량0.2070.1820.0270.0740.0880.0791.0000.456
총금액(원)0.1420.0820.0300.2160.0550.0970.4561.000
2023-12-12T17:07:18.153413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등급명화훼구분명
등급명1.0000.539
화훼구분명0.5391.000
2023-12-12T17:07:18.266149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최고단가(원)최저단가(원)평균단가(원)총수량총금액(원)화훼구분명등급명
최고단가(원)1.0000.9820.996-0.3350.3000.1840.101
최저단가(원)0.9821.0000.994-0.4060.2280.1850.099
평균단가(원)0.9960.9941.000-0.3690.2670.1900.100
총수량-0.335-0.406-0.3691.0000.7560.1170.013
총금액(원)0.3000.2280.2670.7561.0000.0360.010
화훼구분명0.1840.1850.1900.1170.0361.0000.539
등급명0.1010.0990.1000.0130.0100.5391.000

Missing values

2023-12-12T17:07:12.933706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:07:13.139966image/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

정산일자화훼구분명품목명품종명등급명최고단가(원)최저단가(원)평균단가(원)총수량총금액(원)
158712022-01-19절화거베라폼포니(제이제이)특21050105010503031500
19922022-01-03난팔레높시스V3특16899555564602251439325
1952022-01-03절화금어초화이트특28300620074078296099200
524452022-03-02절화리시안사스리시안(겹꽃)특214250142501425012171000
712342022-03-21절화장미스윗핑크(sp)특282508250825016132000
343872022-02-14절화거베라미니백색특2110308050904597879350
180632022-01-21절화장미도미니카특2431043104310938790
626382022-03-11절화프리지아쏠레이특3740700720205147700
440072022-02-21난호접란엔젤3대가지특1739973227357135993195
609212022-03-09절화프리지아쏠레이특22380203022085801284200
정산일자화훼구분명품목명품종명등급명최고단가(원)최저단가(원)평균단가(원)총수량총금액(원)
19952022-01-03난팔레높시스V3특17990772278501801413045
254442022-02-04절화스톡크마린(sp)상23930393039302078600
888202022-04-05관엽율마율마3.5특1138013001320600790100
894492022-04-06절화라넌큘러스피탈로스(BT)특3493026804338125542250
831742022-04-01절화델피니움미니특372007100715061436700
120852022-01-14절화장미돌세토특11630016300163008130400
326932022-02-11절화다알리아탐피코특340504000402532128800
93412022-01-10난호접란쥬피터쌍대가지특111111111111111130333330
381112022-02-16절화리시안사스레이나(라벤다)특2234001695020650621250150
613852022-03-11절화라넌큘러스코메디아특346904590464026120340