Overview

Dataset statistics

Number of variables46
Number of observations68
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.3 KiB
Average record size in memory410.9 B

Variable types

Text3
Numeric11
Categorical32

Dataset

Description부산광역시 강서구 가로수에 대한 데이터로 수종(왕벚나무 등 18종, 54,509주) 및 노선별(낙동남로 등 64개) 식재현황
Author부산광역시 강서구
URLhttps://www.data.go.kr/data/15006073/fileData.do

Alerts

버즘나무 has constant value ""Constant
단풍나무 has constant value ""Constant
벽오동 has constant value ""Constant
대왕참나무 has constant value ""Constant
감나무 has constant value ""Constant
모과나무 has constant value ""Constant
모감주 has constant value ""Constant
계수나무 has constant value ""Constant
가죽나무 has constant value ""Constant
황벽나무 has constant value ""Constant
수양버들 has constant value ""Constant
복자귀 has constant value ""Constant
느릅나무 has constant value ""Constant
대추나무 has constant value ""Constant
구실잣밤나무 has constant value ""Constant
녹나무 has constant value ""Constant
참식 has constant value ""Constant
주목 has constant value ""Constant
아왜나무 has constant value ""Constant
구군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
양버즘 is highly imbalanced (83.5%)Imbalance
칠엽수 is highly imbalanced (83.5%)Imbalance
중국단풍 is highly imbalanced (86.1%)Imbalance
튤립나무 is highly imbalanced (88.9%)Imbalance
산딸나무 is highly imbalanced (81.0%)Imbalance
후박나무 is highly imbalanced (83.5%)Imbalance
해송 is highly imbalanced (88.9%)Imbalance
가시나무 is highly imbalanced (86.1%)Imbalance
개잎갈나무 is highly imbalanced (83.5%)Imbalance
가이즈카향나무 is highly imbalanced (88.9%)Imbalance
기타나무 is highly imbalanced (88.9%)Imbalance
위치명 has unique valuesUnique
왕벚나무 has 37 (54.4%) zerosZeros
은행나무 has 58 (85.3%) zerosZeros
느티나무 has 39 (57.4%) zerosZeros
이팝나무 has 51 (75.0%) zerosZeros
회화나무 has 60 (88.2%) zerosZeros
메타세콰이아 has 62 (91.2%) zerosZeros
팽나무 has 63 (92.6%) zerosZeros
먼나무 has 62 (91.2%) zerosZeros

Reproduction

Analysis started2024-03-14 12:16:10.059573
Analysis finished2024-03-14 12:16:10.801678
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

위치명
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size672.0 B
2024-03-14T21:16:11.623922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length9.2058824
Min length3

Characters and Unicode

Total characters626
Distinct characters111
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

Unique68 ?
Unique (%)100.0%

Sample

1st row미음국제2,5,6로(국제물류 1,6공구)
2nd row미음국제 3,4,7로(국제물류 2공구)
3rd row미음국제 8,9로(국제물류 3공구)
4th row구랑동 1280-1 일원(국제물류 4공구)
5th row생곡로
ValueCountFrequency (%)
미음국제 2
 
2.4%
명지동 2
 
2.4%
신항로 1
 
1.2%
강동양묘장 1
 
1.2%
화전산단2로 1
 
1.2%
천성대항길 1
 
1.2%
2공구 1
 
1.2%
3,4,7로(국제물류 1
 
1.2%
가락대로(가락동 1
 
1.2%
녹산화전로(화전이면도로 1
 
1.2%
Other values (73) 73
85.9%
2024-03-14T21:16:13.111098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 67
 
10.7%
산 42
 
6.7%
단 27
 
4.3%
) 23
 
3.7%
( 23
 
3.7%
1 21
 
3.4%
전 18
 
2.9%
화 17
 
2.7%
17
 
2.7%
2 15
 
2.4%
Other values (101) 356
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 461
73.6%
Decimal Number 84
 
13.4%
Close Punctuation 23
 
3.7%
Open Punctuation 23
 
3.7%
Space Separator 17
 
2.7%
Math Symbol 6
 
1.0%
Other Punctuation 6
 
1.0%
Dash Punctuation 4
 
0.6%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 67
 
14.5%
산 42
 
9.1%
단 27
 
5.9%
전 18
 
3.9%
화 17
 
3.7%
제 14
 
3.0%
동 13
 
2.8%
국 13
 
2.8%
공 11
 
2.4%
녹 10
 
2.2%
Other values (83) 229
49.7%
Decimal Number
ValueCountFrequency (%)
1 21
25.0%
2 15
17.9%
3 14
16.7%
4 8
 
9.5%
6 7
 
8.3%
5 6
 
7.1%
8 4
 
4.8%
9 4
 
4.8%
7 3
 
3.6%
0 2
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 461
73.6%
Common 163
 
26.0%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 67
 
14.5%
산 42
 
9.1%
단 27
 
5.9%
전 18
 
3.9%
화 17
 
3.7%
제 14
 
3.0%
동 13
 
2.8%
국 13
 
2.8%
공 11
 
2.4%
녹 10
 
2.2%
Other values (83) 229
49.7%
Common
ValueCountFrequency (%)
) 23
14.1%
( 23
14.1%
1 21
12.9%
17
10.4%
2 15
9.2%
3 14
8.6%
4 8
 
4.9%
6 7
 
4.3%
~ 6
 
3.7%
, 6
 
3.7%
Other values (6) 23
14.1%
Latin
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 461
73.6%
ASCII 165
 
26.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 67
 
14.5%
산 42
 
9.1%
단 27
 
5.9%
전 18
 
3.9%
화 17
 
3.7%
제 14
 
3.0%
동 13
 
2.8%
국 13
 
2.8%
공 11
 
2.4%
녹 10
 
2.2%
Other values (83) 229
49.7%
ASCII
ValueCountFrequency (%)
) 23
13.9%
( 23
13.9%
1 21
12.7%
17
10.3%
2 15
9.1%
3 14
8.5%
4 8
 
4.8%
6 7
 
4.2%
~ 6
 
3.6%
, 6
 
3.6%
Other values (8) 25
15.2%

위도
Real number (ℝ)

Distinct66
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.186788
Minimum34.752398
Maximum37.44423
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-14T21:16:13.542946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.752398
5-th percentile35.043843
Q135.100797
median35.11612
Q335.151451
95-th percentile35.219927
Maximum37.44423
Range2.6918316
Interquartile range (IQR)0.05065392

Descriptive statistics

Standard deviation0.381707
Coefficient of variation (CV)0.01084802
Kurtosis29.860049
Mean35.186788
Median Absolute Deviation (MAD)0.02427862
Skewness5.4531804
Sum2392.7016
Variance0.14570023
MonotonicityNot monotonic
2024-03-14T21:16:13.998750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.13924124 2
 
2.9%
35.138576 2
 
2.9%
35.101713 1
 
1.5%
35.138962 1
 
1.5%
35.083867 1
 
1.5%
35.146187 1
 
1.5%
35.152777 1
 
1.5%
35.13390498 1
 
1.5%
34.75239808 1
 
1.5%
35.14762 1
 
1.5%
Other values (56) 56
82.4%
ValueCountFrequency (%)
34.75239808 1
1.5%
35.0069102 1
1.5%
35.02206373 1
1.5%
35.02246588 1
1.5%
35.083543 1
1.5%
35.083867 1
1.5%
35.084313 1
1.5%
35.0889516 1
1.5%
35.08904398 1
1.5%
35.090684 1
1.5%
ValueCountFrequency (%)
37.44422971 1
1.5%
37.21446546 1
1.5%
35.22778907 1
1.5%
35.22034673 1
1.5%
35.21914741 1
1.5%
35.21491523 1
1.5%
35.214367 1
1.5%
35.21294475 1
1.5%
35.209882 1
1.5%
35.20584928 1
1.5%

경도
Real number (ℝ)

Distinct66
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.75043
Minimum126.35848
Maximum129.07564
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-14T21:16:14.423423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.35848
5-th percentile127.57859
Q1128.84657
median128.87812
Q3128.9045
95-th percentile128.97144
Maximum129.07564
Range2.7171621
Interquartile range (IQR)0.0579305

Descriptive statistics

Standard deviation0.53532788
Coefficient of variation (CV)0.0041578727
Kurtosis13.637947
Mean128.75043
Median Absolute Deviation (MAD)0.030304
Skewness-3.8236049
Sum8755.029
Variance0.28657594
MonotonicityNot monotonic
2024-03-14T21:16:14.881390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8721258 2
 
2.9%
128.846566 2
 
2.9%
128.868141 1
 
1.5%
128.877977 1
 
1.5%
128.827667 1
 
1.5%
128.831808 1
 
1.5%
128.83021 1
 
1.5%
128.8825466 1
 
1.5%
126.3584789 1
 
1.5%
128.865609 1
 
1.5%
Other values (56) 56
82.4%
ValueCountFrequency (%)
126.3584789 1
1.5%
126.449637 1
1.5%
126.7122579 1
1.5%
127.1649821 1
1.5%
128.3467217 1
1.5%
128.820129 1
1.5%
128.8221487 1
1.5%
128.827667 1
1.5%
128.8277201 1
1.5%
128.83021 1
1.5%
ValueCountFrequency (%)
129.075641 1
1.5%
128.985275 1
1.5%
128.975623 1
1.5%
128.972345 1
1.5%
128.9697715 1
1.5%
128.9693749 1
1.5%
128.9614581 1
1.5%
128.959676 1
1.5%
128.954841 1
1.5%
128.9480986 1
1.5%

구간시점
Text

Distinct66
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size672.0 B
2024-03-14T21:16:15.784828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length6.5294118
Min length2

Characters and Unicode

Total characters444
Distinct characters128
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)95.6%

Sample

1st row국제물류 1,6공구 내
2nd row국제물류 2공구 내
3rd row국제물류 3공구 내
4th row국제물류 4공구 내
5th row녹산동 산5-1
ValueCountFrequency (%)
내 14
 
14.3%
국제물류 5
 
5.1%
명지ic 3
 
3.1%
화전동 2
 
2.0%
명지동 2
 
2.0%
견마교 1
 
1.0%
태웅 1
 
1.0%
천성 1
 
1.0%
조만포삼거리 1
 
1.0%
지사2일반산단 1
 
1.0%
Other values (67) 67
68.4%
2024-03-14T21:16:17.093968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
 
6.8%
1 18
 
4.1%
동 18
 
4.1%
산 14
 
3.2%
내 14
 
3.2%
공 14
 
3.2%
지 13
 
2.9%
구 12
 
2.7%
국 11
 
2.5%
- 11
 
2.5%
Other values (118) 289
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 318
71.6%
Decimal Number 63
 
14.2%
Space Separator 30
 
6.8%
Dash Punctuation 11
 
2.5%
Uppercase Letter 11
 
2.5%
Close Punctuation 4
 
0.9%
Open Punctuation 4
 
0.9%
Math Symbol 1
 
0.2%
Other Symbol 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 18
 
5.7%
산 14
 
4.4%
내 14
 
4.4%
공 14
 
4.4%
지 13
 
4.1%
구 12
 
3.8%
국 11
 
3.5%
제 10
 
3.1%
단 10
 
3.1%
명 8
 
2.5%
Other values (98) 194
61.0%
Decimal Number
ValueCountFrequency (%)
1 18
28.6%
5 11
17.5%
2 8
12.7%
3 7
 
11.1%
4 6
 
9.5%
6 5
 
7.9%
0 4
 
6.3%
8 3
 
4.8%
7 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
C 6
54.5%
I 3
27.3%
U 1
 
9.1%
S 1
 
9.1%
Space Separator
ValueCountFrequency (%)
30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 319
71.8%
Common 114
 
25.7%
Latin 11
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 18
 
5.6%
산 14
 
4.4%
내 14
 
4.4%
공 14
 
4.4%
지 13
 
4.1%
구 12
 
3.8%
국 11
 
3.4%
제 10
 
3.1%
단 10
 
3.1%
명 8
 
2.5%
Other values (99) 195
61.1%
Common
ValueCountFrequency (%)
30
26.3%
1 18
15.8%
- 11
 
9.6%
5 11
 
9.6%
2 8
 
7.0%
3 7
 
6.1%
4 6
 
5.3%
6 5
 
4.4%
0 4
 
3.5%
) 4
 
3.5%
Other values (5) 10
 
8.8%
Latin
ValueCountFrequency (%)
C 6
54.5%
I 3
27.3%
U 1
 
9.1%
S 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 318
71.6%
ASCII 125
 
28.2%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30
24.0%
1 18
14.4%
- 11
 
8.8%
5 11
 
8.8%
2 8
 
6.4%
3 7
 
5.6%
4 6
 
4.8%
C 6
 
4.8%
6 5
 
4.0%
0 4
 
3.2%
Other values (9) 19
15.2%
Hangul
ValueCountFrequency (%)
동 18
 
5.7%
산 14
 
4.4%
내 14
 
4.4%
공 14
 
4.4%
지 13
 
4.1%
구 12
 
3.8%
국 11
 
3.5%
제 10
 
3.1%
단 10
 
3.1%
명 8
 
2.5%
Other values (98) 194
61.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

구간종점
Text

Distinct62
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size672.0 B
2024-03-14T21:16:17.982798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length7.1911765
Min length2

Characters and Unicode

Total characters489
Distinct characters131
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)83.8%

Sample

1st row국제물류 1,6공구 내
2nd row국제물류 2공구 내
3rd row국제물류 3공구 내
4th row국제물류 4공구 내
5th row생곡동 1469-2
ValueCountFrequency (%)
내 14
 
14.0%
국제물류 7
 
7.0%
명지ic 3
 
3.0%
화전동 3
 
3.0%
4공구 2
 
2.0%
진해경계 2
 
2.0%
생곡동 2
 
2.0%
명지동 2
 
2.0%
경성테크(지사동 2
 
2.0%
5공구 2
 
2.0%
Other values (60) 61
61.0%
2024-03-14T21:16:19.337031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
 
6.5%
1 18
 
3.7%
지 16
 
3.3%
동 14
 
2.9%
내 14
 
2.9%
국 12
 
2.5%
산 12
 
2.5%
- 12
 
2.5%
공 12
 
2.5%
단 11
 
2.2%
Other values (121) 336
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 345
70.6%
Decimal Number 71
 
14.5%
Space Separator 32
 
6.5%
Uppercase Letter 14
 
2.9%
Dash Punctuation 12
 
2.5%
Close Punctuation 6
 
1.2%
Open Punctuation 6
 
1.2%
Other Punctuation 1
 
0.2%
Math Symbol 1
 
0.2%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 16
 
4.6%
동 14
 
4.1%
내 14
 
4.1%
국 12
 
3.5%
산 12
 
3.5%
공 12
 
3.5%
단 11
 
3.2%
제 11
 
3.2%
명 9
 
2.6%
계 9
 
2.6%
Other values (98) 225
65.2%
Decimal Number
ValueCountFrequency (%)
1 18
25.4%
2 10
14.1%
5 8
11.3%
4 7
 
9.9%
6 6
 
8.5%
3 6
 
8.5%
8 5
 
7.0%
9 4
 
5.6%
0 4
 
5.6%
7 3
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
C 5
35.7%
I 5
35.7%
N 1
 
7.1%
S 1
 
7.1%
L 1
 
7.1%
E 1
 
7.1%
Space Separator
ValueCountFrequency (%)
32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 346
70.8%
Common 129
 
26.4%
Latin 14
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 16
 
4.6%
동 14
 
4.0%
내 14
 
4.0%
국 12
 
3.5%
산 12
 
3.5%
공 12
 
3.5%
단 11
 
3.2%
제 11
 
3.2%
명 9
 
2.6%
계 9
 
2.6%
Other values (99) 226
65.3%
Common
ValueCountFrequency (%)
32
24.8%
1 18
14.0%
- 12
 
9.3%
2 10
 
7.8%
5 8
 
6.2%
4 7
 
5.4%
6 6
 
4.7%
3 6
 
4.7%
) 6
 
4.7%
( 6
 
4.7%
Other values (6) 18
14.0%
Latin
ValueCountFrequency (%)
C 5
35.7%
I 5
35.7%
N 1
 
7.1%
S 1
 
7.1%
L 1
 
7.1%
E 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 345
70.6%
ASCII 143
29.2%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
22.4%
1 18
12.6%
- 12
 
8.4%
2 10
 
7.0%
5 8
 
5.6%
4 7
 
4.9%
6 6
 
4.2%
3 6
 
4.2%
) 6
 
4.2%
( 6
 
4.2%
Other values (12) 32
22.4%
Hangul
ValueCountFrequency (%)
지 16
 
4.6%
동 14
 
4.1%
내 14
 
4.1%
국 12
 
3.5%
산 12
 
3.5%
공 12
 
3.5%
단 11
 
3.2%
제 11
 
3.2%
명 9
 
2.6%
계 9
 
2.6%
Other values (98) 225
65.2%
None
ValueCountFrequency (%)
㈜ 1
100.0%

총합계
Real number (ℝ)

Distinct66
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean828.79412
Minimum18
Maximum8608
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-14T21:16:19.647758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile56.5
Q1175.5
median366.5
Q3973.5
95-th percentile2571.6
Maximum8608
Range8590
Interquartile range (IQR)798

Descriptive statistics

Standard deviation1260.0466
Coefficient of variation (CV)1.5203373
Kurtosis21.482736
Mean828.79412
Median Absolute Deviation (MAD)257
Skewness3.984432
Sum56358
Variance1587717.4
MonotonicityNot monotonic
2024-03-14T21:16:19.887763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
112 2
 
2.9%
274 2
 
2.9%
1659 1
 
1.5%
95 1
 
1.5%
1470 1
 
1.5%
18 1
 
1.5%
148 1
 
1.5%
278 1
 
1.5%
315 1
 
1.5%
499 1
 
1.5%
Other values (56) 56
82.4%
ValueCountFrequency (%)
18 1
1.5%
34 1
1.5%
43 1
1.5%
53 1
1.5%
63 1
1.5%
87 1
1.5%
89 1
1.5%
95 1
1.5%
99 1
1.5%
107 1
1.5%
ValueCountFrequency (%)
8608 1
1.5%
3805 1
1.5%
2977 1
1.5%
2664 1
1.5%
2400 1
1.5%
2384 1
1.5%
2341 1
1.5%
2019 1
1.5%
1763 1
1.5%
1737 1
1.5%

왕벚나무
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)45.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean295.02941
Minimum0
Maximum2916
Zeros37
Zeros (%)54.4%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-14T21:16:20.391408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3341.25
95-th percentile1757.3
Maximum2916
Range2916
Interquartile range (IQR)341.25

Descriptive statistics

Standard deviation616.20986
Coefficient of variation (CV)2.0886388
Kurtosis7.8898785
Mean295.02941
Median Absolute Deviation (MAD)0
Skewness2.8598044
Sum20062
Variance379714.6
MonotonicityNot monotonic
2024-03-14T21:16:20.775014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 37
54.4%
158 2
 
2.9%
341 1
 
1.5%
336 1
 
1.5%
2916 1
 
1.5%
142 1
 
1.5%
418 1
 
1.5%
342 1
 
1.5%
368 1
 
1.5%
178 1
 
1.5%
Other values (21) 21
30.9%
ValueCountFrequency (%)
0 37
54.4%
34 1
 
1.5%
50 1
 
1.5%
97 1
 
1.5%
99 1
 
1.5%
117 1
 
1.5%
142 1
 
1.5%
144 1
 
1.5%
158 2
 
2.9%
178 1
 
1.5%
ValueCountFrequency (%)
2916 1
1.5%
2410 1
1.5%
2384 1
1.5%
1786 1
1.5%
1704 1
1.5%
1468 1
1.5%
827 1
1.5%
627 1
1.5%
613 1
1.5%
423 1
1.5%

은행나무
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.661765
Minimum0
Maximum1270
Zeros58
Zeros (%)85.3%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-14T21:16:21.129785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile539.9
Maximum1270
Range1270
Interquartile range (IQR)0

Descriptive statistics

Standard deviation223.09222
Coefficient of variation (CV)3.4501412
Kurtosis17.160661
Mean64.661765
Median Absolute Deviation (MAD)0
Skewness4.0755588
Sum4397
Variance49770.138
MonotonicityNot monotonic
2024-03-14T21:16:21.503625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 58
85.3%
605 1
 
1.5%
8 1
 
1.5%
419 1
 
1.5%
643 1
 
1.5%
1270 1
 
1.5%
997 1
 
1.5%
118 1
 
1.5%
100 1
 
1.5%
69 1
 
1.5%
ValueCountFrequency (%)
0 58
85.3%
8 1
 
1.5%
69 1
 
1.5%
100 1
 
1.5%
118 1
 
1.5%
168 1
 
1.5%
419 1
 
1.5%
605 1
 
1.5%
643 1
 
1.5%
997 1
 
1.5%
ValueCountFrequency (%)
1270 1
1.5%
997 1
1.5%
643 1
1.5%
605 1
1.5%
419 1
1.5%
168 1
1.5%
118 1
1.5%
100 1
1.5%
69 1
1.5%
8 1
1.5%

느티나무
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean115.73529
Minimum0
Maximum1527
Zeros39
Zeros (%)57.4%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-14T21:16:21.861725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3156.75
95-th percentile501.85
Maximum1527
Range1527
Interquartile range (IQR)156.75

Descriptive statistics

Standard deviation239.95308
Coefficient of variation (CV)2.0732922
Kurtosis17.940602
Mean115.73529
Median Absolute Deviation (MAD)0
Skewness3.7076258
Sum7870
Variance57577.481
MonotonicityNot monotonic
2024-03-14T21:16:22.260379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 39
57.4%
19 2
 
2.9%
51 1
 
1.5%
199 1
 
1.5%
542 1
 
1.5%
130 1
 
1.5%
250 1
 
1.5%
16 1
 
1.5%
63 1
 
1.5%
66 1
 
1.5%
Other values (19) 19
27.9%
ValueCountFrequency (%)
0 39
57.4%
16 1
 
1.5%
19 2
 
2.9%
23 1
 
1.5%
51 1
 
1.5%
63 1
 
1.5%
66 1
 
1.5%
72 1
 
1.5%
95 1
 
1.5%
100 1
 
1.5%
ValueCountFrequency (%)
1527 1
1.5%
789 1
1.5%
542 1
1.5%
505 1
1.5%
496 1
1.5%
458 1
1.5%
403 1
1.5%
312 1
1.5%
295 1
1.5%
272 1
1.5%

버즘나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:22.678130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:22.987421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

양버즘
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
65 
803
 
1
3019
 
1
128
 
1

Length

Max length4
Median length1
Mean length1.1029412
Min length1

Unique

Unique3 ?
Unique (%)4.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 65
95.6%
803 1
 
1.5%
3019 1
 
1.5%
128 1
 
1.5%

Length

2024-03-14T21:16:23.325756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:23.666693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 65
95.6%
803 1
 
1.5%
3019 1
 
1.5%
128 1
 
1.5%

이팝나무
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.852941
Minimum0
Maximum899
Zeros51
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-14T21:16:23.984441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34.5
95-th percentile614.95
Maximum899
Range899
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation193.59908
Coefficient of variation (CV)2.5190849
Kurtosis8.2329282
Mean76.852941
Median Absolute Deviation (MAD)0
Skewness2.9651817
Sum5226
Variance37480.605
MonotonicityNot monotonic
2024-03-14T21:16:24.340806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 51
75.0%
637 1
 
1.5%
66 1
 
1.5%
43 1
 
1.5%
87 1
 
1.5%
146 1
 
1.5%
211 1
 
1.5%
81 1
 
1.5%
18 1
 
1.5%
765 1
 
1.5%
Other values (8) 8
 
11.8%
ValueCountFrequency (%)
0 51
75.0%
18 1
 
1.5%
43 1
 
1.5%
66 1
 
1.5%
81 1
 
1.5%
87 1
 
1.5%
99 1
 
1.5%
146 1
 
1.5%
160 1
 
1.5%
182 1
 
1.5%
ValueCountFrequency (%)
899 1
1.5%
765 1
1.5%
679 1
1.5%
637 1
1.5%
574 1
1.5%
305 1
1.5%
274 1
1.5%
211 1
1.5%
182 1
1.5%
160 1
1.5%

회화나무
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.705882
Minimum0
Maximum1135
Zeros60
Zeros (%)88.2%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-14T21:16:24.671230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile245.35
Maximum1135
Range1135
Interquartile range (IQR)0

Descriptive statistics

Standard deviation189.95562
Coefficient of variation (CV)3.981807
Kurtosis22.541102
Mean47.705882
Median Absolute Deviation (MAD)0
Skewness4.6984828
Sum3244
Variance36083.136
MonotonicityNot monotonic
2024-03-14T21:16:25.032366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 60
88.2%
72 1
 
1.5%
1135 1
 
1.5%
919 1
 
1.5%
560 1
 
1.5%
315 1
 
1.5%
61 1
 
1.5%
116 1
 
1.5%
66 1
 
1.5%
ValueCountFrequency (%)
0 60
88.2%
61 1
 
1.5%
66 1
 
1.5%
72 1
 
1.5%
116 1
 
1.5%
315 1
 
1.5%
560 1
 
1.5%
919 1
 
1.5%
1135 1
 
1.5%
ValueCountFrequency (%)
1135 1
 
1.5%
919 1
 
1.5%
560 1
 
1.5%
315 1
 
1.5%
116 1
 
1.5%
72 1
 
1.5%
66 1
 
1.5%
61 1
 
1.5%
0 60
88.2%

메타세콰이아
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.735294
Minimum0
Maximum416
Zeros62
Zeros (%)91.2%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-14T21:16:25.367657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile94
Maximum416
Range416
Interquartile range (IQR)0

Descriptive statistics

Standard deviation67.683773
Coefficient of variation (CV)4.0443731
Kurtosis22.226522
Mean16.735294
Median Absolute Deviation (MAD)0
Skewness4.6302954
Sum1138
Variance4581.0931
MonotonicityNot monotonic
2024-03-14T21:16:25.705278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 62
91.2%
243 1
 
1.5%
42 1
 
1.5%
275 1
 
1.5%
40 1
 
1.5%
122 1
 
1.5%
416 1
 
1.5%
ValueCountFrequency (%)
0 62
91.2%
40 1
 
1.5%
42 1
 
1.5%
122 1
 
1.5%
243 1
 
1.5%
275 1
 
1.5%
416 1
 
1.5%
ValueCountFrequency (%)
416 1
 
1.5%
275 1
 
1.5%
243 1
 
1.5%
122 1
 
1.5%
42 1
 
1.5%
40 1
 
1.5%
0 62
91.2%

칠엽수
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
65 
178
 
1
274
 
1
89
 
1

Length

Max length3
Median length1
Mean length1.0735294
Min length1

Unique

Unique3 ?
Unique (%)4.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 65
95.6%
178 1
 
1.5%
274 1
 
1.5%
89 1
 
1.5%

Length

2024-03-14T21:16:26.122484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:26.479206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 65
95.6%
178 1
 
1.5%
274 1
 
1.5%
89 1
 
1.5%

중국단풍
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
66 
112
 
1
2051
 
1

Length

Max length4
Median length1
Mean length1.0735294
Min length1

Unique

Unique2 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
0 66
97.1%
112 1
 
1.5%
2051 1
 
1.5%

Length

2024-03-14T21:16:26.854585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:27.192895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 66
97.1%
112 1
 
1.5%
2051 1
 
1.5%

팽나무
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.882353
Minimum0
Maximum1061
Zeros63
Zeros (%)92.6%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-14T21:16:27.494686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile182.2
Maximum1061
Range1061
Interquartile range (IQR)0

Descriptive statistics

Standard deviation143.69251
Coefficient of variation (CV)4.8086077
Kurtosis41.167519
Mean29.882353
Median Absolute Deviation (MAD)0
Skewness6.100448
Sum2032
Variance20647.538
MonotonicityNot monotonic
2024-03-14T21:16:27.844468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 63
92.6%
276 1
 
1.5%
288 1
 
1.5%
1061 1
 
1.5%
8 1
 
1.5%
399 1
 
1.5%
ValueCountFrequency (%)
0 63
92.6%
8 1
 
1.5%
276 1
 
1.5%
288 1
 
1.5%
399 1
 
1.5%
1061 1
 
1.5%
ValueCountFrequency (%)
1061 1
 
1.5%
399 1
 
1.5%
288 1
 
1.5%
276 1
 
1.5%
8 1
 
1.5%
0 63
92.6%

튤립나무
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
67 
8
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 67
98.5%
8 1
 
1.5%

Length

2024-03-14T21:16:28.232399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:28.554336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 67
98.5%
8 1
 
1.5%

단풍나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:28.894274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:29.205104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

벽오동
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:29.537783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:29.850375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

대왕참나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:30.177548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:30.485445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

감나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:30.814338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:31.122216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

산딸나무
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
64 
452
 
1
202
 
1
85
 
1
44
 
1

Length

Max length3
Median length1
Mean length1.0882353
Min length1

Unique

Unique4 ?
Unique (%)5.9%

Sample

1st row452
2nd row0
3rd row202
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 64
94.1%
452 1
 
1.5%
202 1
 
1.5%
85 1
 
1.5%
44 1
 
1.5%

Length

2024-03-14T21:16:31.476483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:31.834531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 64
94.1%
452 1
 
1.5%
202 1
 
1.5%
85 1
 
1.5%
44 1
 
1.5%

모과나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:32.202911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:32.514497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

모감주
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:32.840622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:33.153567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

계수나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:33.481937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:33.789808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

가죽나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:34.117042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:34.401478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

황벽나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:34.579004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:34.744322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

수양버들
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:34.913429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:35.082186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

복자귀
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:35.253017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:35.480878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

느릅나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:35.683005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:35.847089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

대추나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:36.020399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:36.184821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

후박나무
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
65 
822
 
1
72
 
1
507
 
1

Length

Max length3
Median length1
Mean length1.0735294
Min length1

Unique

Unique3 ?
Unique (%)4.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 65
95.6%
822 1
 
1.5%
72 1
 
1.5%
507 1
 
1.5%

Length

2024-03-14T21:16:36.376924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:36.596951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 65
95.6%
822 1
 
1.5%
72 1
 
1.5%
507 1
 
1.5%

먼나무
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.426471
Minimum0
Maximum532
Zeros62
Zeros (%)91.2%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-14T21:16:36.832311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile195.9
Maximum532
Range532
Interquartile range (IQR)0

Descriptive statistics

Standard deviation87.289246
Coefficient of variation (CV)3.5735513
Kurtosis18.893278
Mean24.426471
Median Absolute Deviation (MAD)0
Skewness4.1433549
Sum1661
Variance7619.4124
MonotonicityNot monotonic
2024-03-14T21:16:37.019317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 62
91.2%
246 1
 
1.5%
192 1
 
1.5%
532 1
 
1.5%
317 1
 
1.5%
176 1
 
1.5%
198 1
 
1.5%
ValueCountFrequency (%)
0 62
91.2%
176 1
 
1.5%
192 1
 
1.5%
198 1
 
1.5%
246 1
 
1.5%
317 1
 
1.5%
532 1
 
1.5%
ValueCountFrequency (%)
532 1
 
1.5%
317 1
 
1.5%
246 1
 
1.5%
198 1
 
1.5%
192 1
 
1.5%
176 1
 
1.5%
0 62
91.2%

해송
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
67 
1062
 
1

Length

Max length4
Median length1
Mean length1.0441176
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 67
98.5%
1062 1
 
1.5%

Length

2024-03-14T21:16:37.436462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:37.623210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 67
98.5%
1062 1
 
1.5%

가시나무
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
66 
9
 
1
372
 
1

Length

Max length3
Median length1
Mean length1.0294118
Min length1

Unique

Unique2 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
0 66
97.1%
9 1
 
1.5%
372 1
 
1.5%

Length

2024-03-14T21:16:37.941920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:38.275646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 66
97.1%
9 1
 
1.5%
372 1
 
1.5%

구실잣밤나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:38.618784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:38.923592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

개잎갈나무
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
65 
237
 
1
3
 
1
16
 
1

Length

Max length3
Median length1
Mean length1.0441176
Min length1

Unique

Unique3 ?
Unique (%)4.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 65
95.6%
237 1
 
1.5%
3 1
 
1.5%
16 1
 
1.5%

Length

2024-03-14T21:16:39.290605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:39.642767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 65
95.6%
237 1
 
1.5%
3 1
 
1.5%
16 1
 
1.5%

녹나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:39.998827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:40.305521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

가이즈카향나무
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
67 
110
 
1

Length

Max length3
Median length1
Mean length1.0294118
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 67
98.5%
110 1
 
1.5%

Length

2024-03-14T21:16:40.657648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:40.994860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 67
98.5%
110 1
 
1.5%

참식
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:41.409609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:41.749029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

주목
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:42.051044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:42.389652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

아왜나무
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
68 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 68
100.0%

Length

2024-03-14T21:16:42.921649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:43.311496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
100.0%

기타나무
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size672.0 B
0
67 
81
 
1

Length

Max length2
Median length1
Mean length1.0147059
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 67
98.5%
81 1
 
1.5%

Length

2024-03-14T21:16:43.615078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:44.096050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 67
98.5%
81 1
 
1.5%

구군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
부산광역시 강서구
68 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 강서구
2nd row부산광역시 강서구
3rd row부산광역시 강서구
4th row부산광역시 강서구
5th row부산광역시 강서구

Common Values

ValueCountFrequency (%)
부산광역시 강서구 68
100.0%

Length

2024-03-14T21:16:44.648450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:45.115145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 68
50.0%
강서구 68
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size672.0 B
2024-02-15
68 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-15
2nd row2024-02-15
3rd row2024-02-15
4th row2024-02-15
5th row2024-02-15

Common Values

ValueCountFrequency (%)
2024-02-15 68
100.0%

Length

2024-03-14T21:16:45.600957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:16:45.932991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-15 68
100.0%

Sample

위치명위도경도구간시점구간종점총합계왕벚나무은행나무느티나무버즘나무양버즘이팝나무회화나무메타세콰이아칠엽수중국단풍팽나무튤립나무단풍나무벽오동대왕참나무감나무산딸나무모과나무모감주계수나무가죽나무황벽나무수양버들복자귀느릅나무대추나무후박나무먼나무해송가시나무구실잣밤나무개잎갈나무녹나무가이즈카향나무참식주목아왜나무기타나무구군명데이터기준일자
0미음국제2,5,6로(국제물류 1,6공구)35.14762128.865609국제물류 1,6공구 내국제물류 1,6공구 내165900510063702430027600000452000000000000000000000부산광역시 강서구2024-02-15
1미음국제 3,4,7로(국제물류 2공구)35.144553128.862854국제물류 2공구 내국제물류 2공구 내59337201900160042000000000000000000000000000000부산광역시 강서구2024-02-15
2미음국제 8,9로(국제물류 3공구)35.136353128.863133국제물류 3공구 내국제물류 3공구 내70319600003050000000000202000000000000000000000부산광역시 강서구2024-02-15
3구랑동 1280-1 일원(국제물류 4공구)35.122592128.851467국제물류 4공구 내국제물류 4공구 내795613000018200000000000000000000000000000000부산광역시 강서구2024-02-15
4생곡로35.135406128.893948녹산동 산5-1생곡동 1469-21870018700000000000000000000000000000000000부산광역시 강서구2024-02-15
5낙동남로35.114911128.886876명지IC진해시 경계26642410025400000000000000000000000000000000000부산광역시 강서구2024-02-15
6대저로273번길35.214367128.985275대상초등학교농업기술센터99000009900000000000000000000000000000000부산광역시 강서구2024-02-15
7범방4로(국제물류 5공구)35.153594128.886219국제물류 5공구 내국제물류 5공구 내1830018300000000000000000000000000000000000부산광역시 강서구2024-02-15
8지사동 1426 일원(정주일반산업단지)35.152766128.82772정주일반산업단지정주일반산업단지27600195000000000000000000000000000000000081부산광역시 강서구2024-02-15
9명지국제로(1-1)35.098928128.918167명지국제1-1단계명지국제1-1단계23416270789006790000000000000000000002460000000000부산광역시 강서구2024-02-15
위치명위도경도구간시점구간종점총합계왕벚나무은행나무느티나무버즘나무양버즘이팝나무회화나무메타세콰이아칠엽수중국단풍팽나무튤립나무단풍나무벽오동대왕참나무감나무산딸나무모과나무모감주계수나무가죽나무황벽나무수양버들복자귀느릅나무대추나무후박나무먼나무해송가시나무구실잣밤나무개잎갈나무녹나무가이즈카향나무참식주목아왜나무기타나무구군명데이터기준일자
58화전산단5로14~98번길35.099759128.880274화전산단5로 내화전산단5로 내6770100250002111160000000000000000000000000000000부산광역시 강서구2024-02-15
59화전산단6로35.104733128.883047신마트(화전동 555-11)화전동 594-12740000000027400000000000000000000000000000부산광역시 강서구2024-02-15
60화전산단6로이면도로35.103463128.883227화전산단6로 내화전산단6로 내5870691300014666000000000000000000001760000000000부산광역시 강서구2024-02-15
61화전산단1로63번길35.101525128.874884태광(북)태광(남)89000000008900000000000000000000000000000부산광역시 강서구2024-02-15
62화전산단2로133~134번길35.106146128.886361SCC아산정밀1680168000000000000000000000000000000000000부산광역시 강서구2024-02-15
63화전산단5로117~118번길35.110426128.87571화전동 553-2화전동 578-101980000000000000000000000000001980000000000부산광역시 강서구2024-02-15
64화전산업대로35.101681128.887507화동공원신영기계공원5420054200000000000000000000000000000000000부산광역시 강서구2024-02-15
65화전산단1로35.098646128.877801태웅(화전동601-1)지에스하이드로(화전동594-2)4160000000416000000000000000000000000000000부산광역시 강서구2024-02-15
66명지동 도시바람길숲35.1027128.9222명지동 3348명지동 334887000008700000000000000000000000000000000부산광역시 강서구2024-02-15
67명지동 360935.09548128.89996명지동 3581-1명지동 3579-143000004300000000000000000000000000000000부산광역시 강서구2024-02-15