Overview

Dataset statistics

Number of variables7
Number of observations756
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.2 KiB
Average record size in memory61.2 B

Variable types

Categorical3
Text1
Numeric3

Dataset

Description화훼유통정보시스템(https://flower.at.or.kr/main/flowerMain.do)을 통해 수집된 aT 화훼공판장 의 유찰 정보(총 출하량, 총, 유찰량, 유찰률) 입니다.
URLhttps://www.data.go.kr/data/15052545/fileData.do

Alerts

연도 has constant value ""Constant
총 출하량 is highly overall correlated with 총 유찰량High correlation
총 유찰량 is highly overall correlated with 총 출하량 and 1 other fieldsHigh correlation
유찰률(퍼센트) is highly overall correlated with 총 유찰량 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 유찰률(퍼센트)High correlation
구분 is highly imbalanced (52.1%)Imbalance
총 유찰량 has 248 (32.8%) zerosZeros
유찰률(퍼센트) has 248 (32.8%) zerosZeros

Reproduction

Analysis started2023-12-12 05:59:14.022671
Analysis finished2023-12-12 05:59:15.355871
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
절화
678 
난
78 

Length

Max length2
Median length2
Mean length1.8968254
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
절화 678
89.7%
난 78
 
10.3%

Length

2023-12-12T14:59:15.417637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:59:15.530773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
절화 678
89.7%
난 78
 
10.3%

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2021
756 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 756
100.0%

Length

2023-12-12T14:59:15.646009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:59:15.738031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 756
100.0%

분기
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2
214 
3
194 
4
193 
1
155 

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 (%)
2 214
28.3%
3 194
25.7%
4 193
25.5%
1 155
20.5%

Length

2023-12-12T14:59:15.832372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:59:15.939724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 214
28.3%
3 194
25.7%
4 193
25.5%
1 155
20.5%

품목명
Text

Distinct262
Distinct (%)34.7%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-12T14:59:16.204401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.6097884
Min length1

Characters and Unicode

Total characters2729
Distinct characters284
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)5.8%

Sample

1st row깅기아남
2nd row덴드로비움
3rd row도부작
4th row동양란
5th row동양심비
ValueCountFrequency (%)
호접란 8
 
1.1%
반다 6
 
0.8%
심비디움 6
 
0.8%
헬리크리섬 4
 
0.5%
카네이션 4
 
0.5%
칼라 4
 
0.5%
허브 4
 
0.5%
베로니카 4
 
0.5%
버들나무 4
 
0.5%
백합 4
 
0.5%
Other values (252) 708
93.7%
2023-12-12T14:59:16.685559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 188
 
6.9%
리 129
 
4.7%
아 121
 
4.4%
라 85
 
3.1%
시 49
 
1.8%
움 42
 
1.5%
무 41
 
1.5%
란 41
 
1.5%
레 39
 
1.4%
초 39
 
1.4%
Other values (274) 1955
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2723
99.8%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 188
 
6.9%
리 129
 
4.7%
아 121
 
4.4%
라 85
 
3.1%
시 49
 
1.8%
움 42
 
1.5%
무 41
 
1.5%
란 41
 
1.5%
레 39
 
1.4%
초 39
 
1.4%
Other values (272) 1949
71.6%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2723
99.8%
Common 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 188
 
6.9%
리 129
 
4.7%
아 121
 
4.4%
라 85
 
3.1%
시 49
 
1.8%
움 42
 
1.5%
무 41
 
1.5%
란 41
 
1.5%
레 39
 
1.4%
초 39
 
1.4%
Other values (272) 1949
71.6%
Common
ValueCountFrequency (%)
) 3
50.0%
( 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2723
99.8%
ASCII 6
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 188
 
6.9%
리 129
 
4.7%
아 121
 
4.4%
라 85
 
3.1%
시 49
 
1.8%
움 42
 
1.5%
무 41
 
1.5%
란 41
 
1.5%
레 39
 
1.4%
초 39
 
1.4%
Other values (272) 1949
71.6%
ASCII
ValueCountFrequency (%)
) 3
50.0%
( 3
50.0%

총 출하량
Real number (ℝ)

HIGH CORRELATION 

Distinct696
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29823.413
Minimum1
Maximum925664
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T14:59:16.917697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24
Q1437.25
median2081.5
Q314070.25
95-th percentile130281.5
Maximum925664
Range925663
Interquartile range (IQR)13633

Descriptive statistics

Standard deviation97892.48
Coefficient of variation (CV)3.2824037
Kurtosis38.618882
Mean29823.413
Median Absolute Deviation (MAD)1982
Skewness5.8428503
Sum22546500
Variance9.5829375 × 109
MonotonicityNot monotonic
2023-12-12T14:59:17.091977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 5
 
0.7%
15 4
 
0.5%
30 4
 
0.5%
60 4
 
0.5%
40 3
 
0.4%
24 3
 
0.4%
16 3
 
0.4%
11 3
 
0.4%
240 3
 
0.4%
5 3
 
0.4%
Other values (686) 721
95.4%
ValueCountFrequency (%)
1 1
 
0.1%
2 2
0.3%
3 1
 
0.1%
4 1
 
0.1%
5 3
0.4%
7 1
 
0.1%
8 1
 
0.1%
9 2
0.3%
10 1
 
0.1%
11 3
0.4%
ValueCountFrequency (%)
925664 1
0.1%
861180 1
0.1%
811031 1
0.1%
754568 1
0.1%
725218 1
0.1%
700994 1
0.1%
694374 1
0.1%
611877 1
0.1%
542055 1
0.1%
504616 1
0.1%

총 유찰량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct354
Distinct (%)46.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1161.8386
Minimum0
Maximum54658
Zeros248
Zeros (%)32.8%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T14:59:17.239090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median50
Q3418.5
95-th percentile6034.5
Maximum54658
Range54658
Interquartile range (IQR)418.5

Descriptive statistics

Standard deviation4133.6271
Coefficient of variation (CV)3.5578324
Kurtosis62.218427
Mean1161.8386
Median Absolute Deviation (MAD)50
Skewness6.9619621
Sum878350
Variance17086873
MonotonicityNot monotonic
2023-12-12T14:59:17.416466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 248
32.8%
30 16
 
2.1%
40 13
 
1.7%
50 7
 
0.9%
46 6
 
0.8%
32 5
 
0.7%
11 5
 
0.7%
24 5
 
0.7%
100 4
 
0.5%
6 4
 
0.5%
Other values (344) 443
58.6%
ValueCountFrequency (%)
0 248
32.8%
1 1
 
0.1%
4 2
 
0.3%
5 2
 
0.3%
6 4
 
0.5%
7 1
 
0.1%
8 2
 
0.3%
10 4
 
0.5%
11 5
 
0.7%
12 4
 
0.5%
ValueCountFrequency (%)
54658 1
0.1%
36636 1
0.1%
34978 1
0.1%
31411 1
0.1%
31333 1
0.1%
28065 1
0.1%
25085 1
0.1%
22773 1
0.1%
17645 1
0.1%
16568 1
0.1%

유찰률(퍼센트)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct172
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.7369048
Minimum0
Maximum100
Zeros248
Zeros (%)32.8%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T14:59:18.002722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.75
Q35.9
95-th percentile47.65
Maximum100
Range100
Interquartile range (IQR)5.9

Descriptive statistics

Standard deviation16.898524
Coefficient of variation (CV)2.1841453
Kurtosis14.195705
Mean7.7369048
Median Absolute Deviation (MAD)1.75
Skewness3.613251
Sum5849.1
Variance285.56011
MonotonicityNot monotonic
2023-12-12T14:59:18.235349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 248
32.8%
0.4 13
 
1.7%
1.2 12
 
1.6%
0.9 12
 
1.6%
100.0 11
 
1.5%
3.5 11
 
1.5%
2.9 11
 
1.5%
1.9 10
 
1.3%
1.0 10
 
1.3%
1.1 9
 
1.2%
Other values (162) 409
54.1%
ValueCountFrequency (%)
0.0 248
32.8%
0.1 6
 
0.8%
0.2 4
 
0.5%
0.3 6
 
0.8%
0.4 13
 
1.7%
0.5 9
 
1.2%
0.6 7
 
0.9%
0.7 5
 
0.7%
0.8 6
 
0.8%
0.9 12
 
1.6%
ValueCountFrequency (%)
100.0 11
1.5%
83.3 1
 
0.1%
80.0 1
 
0.1%
76.0 1
 
0.1%
70.0 2
 
0.3%
68.6 1
 
0.1%
66.7 1
 
0.1%
65.7 1
 
0.1%
65.1 1
 
0.1%
62.5 1
 
0.1%

Interactions

2023-12-12T14:59:14.921933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:14.386334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:14.670400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:15.016461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:14.484066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:14.753592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:15.097961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:14.572965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:14.834187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:59:18.356025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분분기총 출하량총 유찰량유찰률(퍼센트)
구분1.0000.0710.3070.4710.847
분기0.0711.0000.0550.0000.066
총 출하량0.3070.0551.0000.7570.000
총 유찰량0.4710.0000.7571.0000.266
유찰률(퍼센트)0.8470.0660.0000.2661.000
2023-12-12T14:59:18.485523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분기구분
분기1.0000.047
구분0.0471.000
2023-12-12T14:59:18.610965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총 출하량총 유찰량유찰률(퍼센트)구분분기
총 출하량1.0000.7640.2430.2340.033
총 유찰량0.7641.0000.7120.3530.000
유찰률(퍼센트)0.2430.7121.0000.6800.038
구분0.2340.3530.6801.0000.047
분기0.0330.0000.0380.0471.000

Missing values

2023-12-12T14:59:15.208141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:59:15.315437image/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

구분연도분기품목명총 출하량총 유찰량유찰률(퍼센트)
0난20211깅기아남558361518421.2
1난20211덴드로비움39400.0
2난20211도부작4848100.0
3난20211동양란1873345465833.0
4난20211동양심비29185687332.4
5난20211막실라리아403779561.4
6난20211반다1299862.5
7난20211석곡2144118137.2
8난20211석부작35227261.2
9난20211심비디움50078957113.7
구분연도분기품목명총 출하량총 유찰량유찰률(퍼센트)
746절화20214헬리크리섬17000.0
747절화20214호랑이눈1100.0
748절화20214호엽란26401002.4
749절화20214호접란109372252.2
750절화20214홍가시3141591.6
751절화20214홍죽1625904.8
752절화20214홍화3000.0
753절화20214화살나무282409.6
754절화20214후록스3670460.7
755절화20214히야신스103100.0