Overview

Dataset statistics

Number of variables12
Number of observations1227
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory119.9 KiB
Average record size in memory100.1 B

Variable types

Categorical6
Numeric3
Text3

Dataset

Description전북특별자치도의 식물 정보. 목본식물과 초본식물 포함. 학명, 국명, 나무 종류, 수량 , 보유연도, 수집경로, 원산지, 위치 등 정보 포함
Author전북특별자치도
URLhttps://www.data.go.kr/data/15067749/fileData.do

Alerts

목본식물 has constant value ""Constant
번호 is highly overall correlated with 구분High correlation
수량 is highly overall correlated with 원산지High correlation
구분 is highly overall correlated with 번호High correlation
보유연도 is highly overall correlated with 수집경로High correlation
수집경로 is highly overall correlated with 보유연도 and 1 other fieldsHigh correlation
원산지 is highly overall correlated with 수량 and 1 other fieldsHigh correlation
원산지 is highly imbalanced (88.0%)Imbalance
수량 is highly skewed (γ1 = 24.10976857)Skewed
색인번호 has unique valuesUnique
번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 09:41:12.353391
Analysis finished2024-03-14 09:41:17.084551
Duration4.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

목본식물
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
목본식물
1227 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
목본식물 1227
100.0%

Length

2024-03-14T18:41:17.284055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:41:17.585509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목본식물 1227
100.0%

색인번호
Real number (ℝ)

UNIQUE 

Distinct1227
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3072.1866
Minimum2459
Maximum3686
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-03-14T18:41:17.913692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2459
5-th percentile2520.3
Q12765.5
median3072
Q33378.5
95-th percentile3624.7
Maximum3686
Range1227
Interquartile range (IQR)613

Descriptive statistics

Standard deviation354.61185
Coefficient of variation (CV)0.11542653
Kurtosis-1.1991357
Mean3072.1866
Median Absolute Deviation (MAD)307
Skewness0.0016139191
Sum3769573
Variance125749.56
MonotonicityNot monotonic
2024-03-14T18:41:18.362737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3628 1
 
0.1%
2888 1
 
0.1%
2895 1
 
0.1%
2894 1
 
0.1%
2893 1
 
0.1%
2892 1
 
0.1%
2891 1
 
0.1%
2890 1
 
0.1%
2889 1
 
0.1%
2887 1
 
0.1%
Other values (1217) 1217
99.2%
ValueCountFrequency (%)
2459 1
0.1%
2460 1
0.1%
2461 1
0.1%
2462 1
0.1%
2463 1
0.1%
2464 1
0.1%
2465 1
0.1%
2466 1
0.1%
2467 1
0.1%
2468 1
0.1%
ValueCountFrequency (%)
3686 1
0.1%
3685 1
0.1%
3684 1
0.1%
3683 1
0.1%
3682 1
0.1%
3681 1
0.1%
3680 1
0.1%
3679 1
0.1%
3678 1
0.1%
3677 1
0.1%

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1227
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1844.3073
Minimum1231
Maximum2458
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-03-14T18:41:18.786561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1231
5-th percentile1292.3
Q11537.5
median1844
Q32151.5
95-th percentile2396.7
Maximum2458
Range1227
Interquartile range (IQR)614

Descriptive statistics

Standard deviation354.71762
Coefficient of variation (CV)0.19233109
Kurtosis-1.2003216
Mean1844.3073
Median Absolute Deviation (MAD)307
Skewness0.0013906641
Sum2262965
Variance125824.59
MonotonicityNot monotonic
2024-03-14T18:41:19.242313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1821 1
 
0.1%
2293 1
 
0.1%
2329 1
 
0.1%
2318 1
 
0.1%
2312 1
 
0.1%
2306 1
 
0.1%
2304 1
 
0.1%
2301 1
 
0.1%
2298 1
 
0.1%
2290 1
 
0.1%
Other values (1217) 1217
99.2%
ValueCountFrequency (%)
1231 1
0.1%
1232 1
0.1%
1233 1
0.1%
1234 1
0.1%
1235 1
0.1%
1236 1
0.1%
1237 1
0.1%
1238 1
0.1%
1239 1
0.1%
1240 1
0.1%
ValueCountFrequency (%)
2458 1
0.1%
2457 1
0.1%
2456 1
0.1%
2455 1
0.1%
2454 1
0.1%
2453 1
0.1%
2452 1
0.1%
2451 1
0.1%
2450 1
0.1%
2449 1
0.1%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
2
746 
1
481 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 746
60.8%
1 481
39.2%

Length

2024-03-14T18:41:19.664989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:41:19.975197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 746
60.8%
1 481
39.2%

학명
Text

Distinct974
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
2024-03-14T18:41:21.087193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length40
Mean length24.621027
Min length9

Characters and Unicode

Total characters30210
Distinct characters68
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique938 ?
Unique (%)76.4%

Sample

1st rowDeutzia parviflora Bunge
2nd rowHydrangea macrophylla ""Ayesha""
3rd rowHydrangea macrophylla ""Nigra""
4th rowCorylopsis veitchiana
5th rowChaenomeles speciosa Nakai
ValueCountFrequency (%)
spp 319
 
8.0%
rosa 137
 
3.4%
japonica 96
 
2.4%
var 90
 
2.3%
hibiscus 88
 
2.2%
camellia 73
 
1.8%
syriacus 70
 
1.8%
l 61
 
1.5%
magnolia 60
 
1.5%
et 54
 
1.4%
Other values (1334) 2937
73.7%
2024-03-14T18:41:22.491535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3063
 
10.1%
2995
 
9.9%
i 2187
 
7.2%
s 1917
 
6.3%
e 1597
 
5.3%
r 1498
 
5.0%
o 1489
 
4.9%
n 1414
 
4.7%
u 1352
 
4.5%
" 1278
 
4.2%
Other values (58) 11420
37.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22307
73.8%
Space Separator 2995
 
9.9%
Uppercase Letter 2494
 
8.3%
Other Punctuation 2260
 
7.5%
Open Punctuation 64
 
0.2%
Close Punctuation 64
 
0.2%
Decimal Number 24
 
0.1%
Modifier Symbol 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3063
13.7%
i 2187
 
9.8%
s 1917
 
8.6%
e 1597
 
7.2%
r 1498
 
6.7%
o 1489
 
6.7%
n 1414
 
6.3%
u 1352
 
6.1%
l 1170
 
5.2%
p 1129
 
5.1%
Other values (16) 5491
24.6%
Uppercase Letter
ValueCountFrequency (%)
R 280
11.2%
C 246
 
9.9%
M 211
 
8.5%
P 203
 
8.1%
H 200
 
8.0%
S 190
 
7.6%
L 155
 
6.2%
T 136
 
5.5%
A 127
 
5.1%
B 102
 
4.1%
Other values (16) 644
25.8%
Decimal Number
ValueCountFrequency (%)
6 7
29.2%
2 4
16.7%
1 4
16.7%
9 2
 
8.3%
8 2
 
8.3%
0 1
 
4.2%
4 1
 
4.2%
3 1
 
4.2%
5 1
 
4.2%
7 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
" 1278
56.5%
. 982
43.5%
Space Separator
ValueCountFrequency (%)
2995
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24801
82.1%
Common 5409
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3063
 
12.4%
i 2187
 
8.8%
s 1917
 
7.7%
e 1597
 
6.4%
r 1498
 
6.0%
o 1489
 
6.0%
n 1414
 
5.7%
u 1352
 
5.5%
l 1170
 
4.7%
p 1129
 
4.6%
Other values (42) 7985
32.2%
Common
ValueCountFrequency (%)
2995
55.4%
" 1278
23.6%
. 982
 
18.2%
( 64
 
1.2%
) 64
 
1.2%
6 7
 
0.1%
2 4
 
0.1%
1 4
 
0.1%
` 2
 
< 0.1%
9 2
 
< 0.1%
Other values (6) 7
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30210
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 3063
 
10.1%
2995
 
9.9%
i 2187
 
7.2%
s 1917
 
6.3%
e 1597
 
5.3%
r 1498
 
5.0%
o 1489
 
4.9%
n 1414
 
4.7%
u 1352
 
4.5%
" 1278
 
4.2%
Other values (58) 11420
37.8%

국명
Text

Distinct1046
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
2024-03-14T18:41:23.548074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length5.792991
Min length1

Characters and Unicode

Total characters7108
Distinct characters499
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1028 ?
Unique (%)83.8%

Sample

1st row말발도리
2nd row수국(재배종)
3rd row수국(재배종)
4th row히어리(향기)
5th row산당화
ValueCountFrequency (%)
동백나무(재배종 66
 
5.3%
목련(재배종 49
 
4.0%
철쭉류 18
 
1.5%
모란(재배종 12
 
1.0%
수국(재배종 11
 
0.9%
무궁화(품종 11
 
0.9%
단풍나무(재배종 6
 
0.5%
무궁화류 4
 
0.3%
사철나무(재배종 4
 
0.3%
나무수국(재배종 3
 
0.2%
Other values (1036) 1050
85.1%
2024-03-14T18:41:25.077075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
무 558
 
7.9%
나 459
 
6.5%
* 325
 
4.6%
( 284
 
4.0%
) 284
 
4.0%
종 208
 
2.9%
배 173
 
2.4%
재 166
 
2.3%
미 150
 
2.1%
장 143
 
2.0%
Other values (489) 4358
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6185
87.0%
Other Punctuation 327
 
4.6%
Open Punctuation 284
 
4.0%
Close Punctuation 284
 
4.0%
Decimal Number 16
 
0.2%
Space Separator 12
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
무 558
 
9.0%
나 459
 
7.4%
종 208
 
3.4%
배 173
 
2.8%
재 166
 
2.7%
미 150
 
2.4%
장 143
 
2.3%
화 133
 
2.2%
백 121
 
2.0%
리 94
 
1.5%
Other values (477) 3980
64.3%
Decimal Number
ValueCountFrequency (%)
2 4
25.0%
9 3
18.8%
1 3
18.8%
8 3
18.8%
0 1
 
6.2%
7 1
 
6.2%
4 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
* 325
99.4%
" 2
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 284
100.0%
Close Punctuation
ValueCountFrequency (%)
) 284
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6185
87.0%
Common 923
 
13.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
무 558
 
9.0%
나 459
 
7.4%
종 208
 
3.4%
배 173
 
2.8%
재 166
 
2.7%
미 150
 
2.4%
장 143
 
2.3%
화 133
 
2.2%
백 121
 
2.0%
리 94
 
1.5%
Other values (477) 3980
64.3%
Common
ValueCountFrequency (%)
* 325
35.2%
( 284
30.8%
) 284
30.8%
12
 
1.3%
2 4
 
0.4%
9 3
 
0.3%
1 3
 
0.3%
8 3
 
0.3%
" 2
 
0.2%
0 1
 
0.1%
Other values (2) 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6185
87.0%
ASCII 923
 
13.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
무 558
 
9.0%
나 459
 
7.4%
종 208
 
3.4%
배 173
 
2.8%
재 166
 
2.7%
미 150
 
2.4%
장 143
 
2.3%
화 133
 
2.2%
백 121
 
2.0%
리 94
 
1.5%
Other values (477) 3980
64.3%
ASCII
ValueCountFrequency (%)
* 325
35.2%
( 284
30.8%
) 284
30.8%
12
 
1.3%
2 4
 
0.4%
9 3
 
0.3%
1 3
 
0.3%
8 3
 
0.3%
" 2
 
0.2%
0 1
 
0.1%
Other values (2) 2
 
0.2%

나무종류
Text

Distinct89
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
2024-03-14T18:41:25.865077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.9869601
Min length1

Characters and Unicode

Total characters3665
Distinct characters143
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

Unique27 ?
Unique (%)2.2%

Sample

1st row범의귀
2nd row범의귀
3rd row범의귀
4th row조록나무
5th row장미
ValueCountFrequency (%)
장미 233
19.0%
아욱 88
 
7.2%
차나무 79
 
6.4%
목련 63
 
5.1%
미나리아재비 60
 
4.9%
진달래 60
 
4.9%
측백나무 44
 
3.6%
단풍나무 42
 
3.4%
인동 31
 
2.5%
범의귀 30
 
2.4%
Other values (79) 497
40.5%
2024-03-14T18:41:26.988619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
나 516
 
14.1%
무 452
 
12.3%
미 294
 
8.0%
장 233
 
6.4%
아 153
 
4.2%
욱 88
 
2.4%
목 80
 
2.2%
차 79
 
2.2%
리 71
 
1.9%
래 68
 
1.9%
Other values (133) 1631
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3662
99.9%
Space Separator 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
나 516
 
14.1%
무 452
 
12.3%
미 294
 
8.0%
장 233
 
6.4%
아 153
 
4.2%
욱 88
 
2.4%
목 80
 
2.2%
차 79
 
2.2%
리 71
 
1.9%
래 68
 
1.9%
Other values (132) 1628
44.5%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3662
99.9%
Common 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
나 516
 
14.1%
무 452
 
12.3%
미 294
 
8.0%
장 233
 
6.4%
아 153
 
4.2%
욱 88
 
2.4%
목 80
 
2.2%
차 79
 
2.2%
리 71
 
1.9%
래 68
 
1.9%
Other values (132) 1628
44.5%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3662
99.9%
ASCII 3
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
나 516
 
14.1%
무 452
 
12.3%
미 294
 
8.0%
장 233
 
6.4%
아 153
 
4.2%
욱 88
 
2.4%
목 80
 
2.2%
차 79
 
2.2%
리 71
 
1.9%
래 68
 
1.9%
Other values (132) 1628
44.5%
ASCII
ValueCountFrequency (%)
3
100.0%

수량
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct131
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean187.10758
Minimum0
Maximum68071
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-03-14T18:41:27.386670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q320
95-th percentile148.4
Maximum68071
Range68071
Interquartile range (IQR)19

Descriptive statistics

Standard deviation2283.8521
Coefficient of variation (CV)12.206091
Kurtosis666.82358
Mean187.10758
Median Absolute Deviation (MAD)1
Skewness24.109769
Sum229581
Variance5215980.2
MonotonicityNot monotonic
2024-03-14T18:41:27.837982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 556
45.3%
2 132
 
10.8%
3 63
 
5.1%
30 48
 
3.9%
20 32
 
2.6%
5 28
 
2.3%
10 28
 
2.3%
4 28
 
2.3%
100 22
 
1.8%
28 16
 
1.3%
Other values (121) 274
22.3%
ValueCountFrequency (%)
0 1
 
0.1%
1 556
45.3%
2 132
 
10.8%
3 63
 
5.1%
4 28
 
2.3%
5 28
 
2.3%
6 8
 
0.7%
7 10
 
0.8%
8 5
 
0.4%
9 3
 
0.2%
ValueCountFrequency (%)
68071 1
0.1%
29970 1
0.1%
20000 1
0.1%
15170 1
0.1%
6444 1
0.1%
6435 1
0.1%
6205 1
0.1%
5030 1
0.1%
4830 1
0.1%
4555 1
0.1%

보유연도
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
2002
536 
2003
177 
<NA>
154 
2000
138 
1989
63 
Other values (14)
159 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row2003
2nd row2003
3rd row2003
4th row2003
5th row1996

Common Values

ValueCountFrequency (%)
2002 536
43.7%
2003 177
 
14.4%
<NA> 154
 
12.6%
2000 138
 
11.2%
1989 63
 
5.1%
2001 33
 
2.7%
2004 28
 
2.3%
1994 24
 
2.0%
1996 18
 
1.5%
1995 16
 
1.3%
Other values (9) 40
 
3.3%

Length

2024-03-14T18:41:28.268860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2002 536
43.9%
2003 177
 
14.5%
na 154
 
12.6%
2000 138
 
11.3%
1989 63
 
5.2%
2001 33
 
2.7%
2004 28
 
2.3%
1994 24
 
2.0%
1996 18
 
1.5%
1995 16
 
1.3%
Other values (8) 35
 
2.9%

수집경로
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
수집
1064 
자생
163 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수집 1064
86.7%
자생 163
 
13.3%

Length

2024-03-14T18:41:28.648631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:41:28.966266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수집 1064
86.7%
자생 163
 
13.3%

원산지
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct22
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
<NA>
1150 
중국
 
25
일본
 
21
북아메리카
 
6
수집
 
5
Other values (17)
 
20

Length

Max length10
Median length4
Mean length3.9299104
Min length2

Unique

Unique15 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1150
93.7%
중국 25
 
2.0%
일본 21
 
1.7%
북아메리카 6
 
0.5%
수집 5
 
0.4%
인도 3
 
0.2%
유럽 2
 
0.2%
미국 동부 1
 
0.1%
아라비아 서부 1
 
0.1%
중국 북부 1
 
0.1%
Other values (12) 12
 
1.0%

Length

2024-03-14T18:41:29.349654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1150
92.7%
중국 30
 
2.4%
일본 22
 
1.8%
북아메리카 7
 
0.6%
수집 5
 
0.4%
인도 3
 
0.2%
유럽 3
 
0.2%
남부 3
 
0.2%
미국 2
 
0.2%
서부 2
 
0.2%
Other values (13) 13
 
1.0%

위치
Categorical

Distinct37
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
완주
575 
천리포수목원
193 
뉴코리아장미
128 
전북산림
95 
미림종묘
 
46
Other values (32)
190 

Length

Max length6
Median length2
Mean length3.4621027
Min length2

Unique

Unique15 ?
Unique (%)1.2%

Sample

1st row전주
2nd row천리포수목원
3rd row천리포수목원
4th row천리포수목원
5th row완주

Common Values

ValueCountFrequency (%)
완주 575
46.9%
천리포수목원 193
 
15.7%
뉴코리아장미 128
 
10.4%
전북산림 95
 
7.7%
미림종묘 46
 
3.7%
프롬엔 42
 
3.4%
순창 31
 
2.5%
천보식물원 16
 
1.3%
완주동상 13
 
1.1%
익산 13
 
1.1%
Other values (27) 75
 
6.1%

Length

2024-03-14T18:41:29.797120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
완주 575
46.9%
천리포수목원 193
 
15.7%
뉴코리아장미 128
 
10.4%
전북산림 95
 
7.7%
미림종묘 46
 
3.7%
프롬엔 42
 
3.4%
순창 31
 
2.5%
천보식물원 16
 
1.3%
익산 13
 
1.1%
완주동상 13
 
1.1%
Other values (26) 75
 
6.1%

Interactions

2024-03-14T18:41:15.413944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:41:14.063444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:41:14.658126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:41:15.686247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:41:14.317166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:41:14.874912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:41:15.956934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:41:14.484293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:41:15.141521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:41:30.071717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
색인번호번호구분나무종류수량보유연도수집경로원산지위치
색인번호1.0000.3570.2750.3370.0820.1230.0000.4260.172
번호0.3571.0001.0000.9670.0000.5890.2190.0000.798
구분0.2751.0001.0000.9050.0510.2790.0590.3270.609
나무종류0.3370.9670.9051.0000.6100.8430.5660.7890.929
수량0.0820.0000.0510.6101.0000.5670.0001.0000.000
보유연도0.1230.5890.2790.8430.5671.0000.8830.7600.743
수집경로0.0000.2190.0590.5660.0000.8831.0000.8440.473
원산지0.4260.0000.3270.7891.0000.7600.8441.0000.851
위치0.1720.7980.6090.9290.0000.7430.4730.8511.000
2024-03-14T18:41:30.558925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위치원산지수집경로보유연도구분
위치1.0000.4580.3730.2880.483
원산지0.4581.0000.6720.3610.241
수집경로0.3730.6721.0000.7360.038
보유연도0.2880.3610.7361.0000.218
구분0.4830.2410.0380.2181.000
2024-03-14T18:41:30.831549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
색인번호번호수량구분보유연도수집경로원산지위치
색인번호1.0000.0870.0440.2110.0470.0000.1440.060
번호0.0871.0000.0540.9810.2700.1670.0000.423
수량0.0440.0541.0000.0340.3440.0000.8640.000
구분0.2110.9810.0341.0000.2180.0380.2410.483
보유연도0.0470.2700.3440.2181.0000.7360.3610.288
수집경로0.0000.1670.0000.0380.7361.0000.6720.373
원산지0.1440.0000.8640.2410.3610.6721.0000.458
위치0.0600.4230.0000.4830.2880.3730.4581.000

Missing values

2024-03-14T18:41:16.352832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:41:16.876856image/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

목본식물색인번호번호구분학명국명나무종류수량보유연도수집경로원산지위치
0목본식물362818212Deutzia parviflora Bunge말발도리범의귀112003수집<NA>전주
1목본식물362918342Hydrangea macrophylla ""Ayesha""수국(재배종)범의귀152003수집<NA>천리포수목원
2목본식물363018412Hydrangea macrophylla ""Nigra""수국(재배종)범의귀152003수집<NA>천리포수목원
3목본식물363118542Corylopsis veitchiana히어리(향기)조록나무22003수집<NA>천리포수목원
4목본식물363218602Chaenomeles speciosa Nakai산당화장미21996수집<NA>완주
5목본식물363318662Kerria japonica var. albescens백매화장미12001수집<NA>완주
6목본식물363418782Pyracantha angustifolia Schneid.피라칸다장미902000수집중국완주
7목본식물363518822Rhaphiolepis umbellata (Thunb) Makino다정큼나무장미12002수집<NA>순창
8목본식물363618982Spiraea frutschiana Schneid.참조팝나무장미1<NA>자생<NA>완주
9목본식물363719062Spiraea spp.황금조팝나무*장미302002수집<NA>천보식물원
목본식물색인번호번호구분학명국명나무종류수량보유연도수집경로원산지위치
1217목본식물249414831Sorbus alnifolia (S. et Z.) K. Koch.팥배나무장미682000수집<NA>완주
1218목본식물249515091Acer palmatum ""Asahizuru""욱학단풍단풍나무102003수집<NA>완주
1219목본식물249615141Acer palmatum ""Samidare""단풍나무(재배종)단풍나무12002수집<NA>천리포수목원
1220목본식물249715151Acer palmatum ""Seiru""단풍나무(청용)단풍나무102003수집<NA>완주
1221목본식물249815201Acer palmatum Thunb.단풍나무단풍나무1<NA>자생<NA>완주
1222목본식물249915251Acer spp.수양청홍세열단풍*단풍나무12002수집<NA>완주
1223목본식물250015291Acer pseudosieboldianum (Paxton) Kom.당단풍단풍나무11996수집<NA>완주
1224목본식물250115321Acer saccharinum L.은단풍단풍나무1<NA>자생<NA>완주
1225목본식물250215381Meliosma oldhamii Max.합다리나무나도밤나무1<NA>자생<NA>완주
1226목본식물250315441Stewartia pseudocamellia Maxim.일본노각나무차나무12002수집<NA>완주