Overview

Dataset statistics

Number of variables42
Number of observations597
Missing cells9441
Missing cells (%)37.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory218.8 KiB
Average record size in memory375.2 B

Variable types

Categorical21
Text2
Numeric14
Unsupported5

Dataset

Description충청북도 청주시 가로수 현황을 현행화 하여 효율적인 가로수 관리를 위한 자료 구축하고 향후 가로수 조성 계획과 수종 변경을 위한 자료로 사용하기 위함임
Author충청북도 청주시
URLhttps://www.data.go.kr/data/15101125/fileData.do

Alerts

버드 is highly imbalanced (98.2%)Imbalance
칠엽수 is highly imbalanced (96.5%)Imbalance
배롱 is highly imbalanced (96.5%)Imbalance
자귀 is highly imbalanced (98.2%)Imbalance
주목 is highly imbalanced (98.2%)Imbalance
향나무 is highly imbalanced (97.7%)Imbalance
무궁화 is highly imbalanced (97.3%)Imbalance
노각 is highly imbalanced (98.2%)Imbalance
계수 is highly imbalanced (97.7%)Imbalance
감 is highly imbalanced (97.7%)Imbalance
산수유 is highly imbalanced (98.2%)Imbalance
사과 is highly imbalanced (98.2%)Imbalance
매실 is highly imbalanced (98.2%)Imbalance
모과 is highly imbalanced (97.3%)Imbalance
대왕참 is highly imbalanced (97.3%)Imbalance
대추 is highly imbalanced (98.2%)Imbalance
튤립나무 is highly imbalanced (98.2%)Imbalance
공작단풍 is highly imbalanced (98.2%)Imbalance
소나무 is highly imbalanced (98.2%)Imbalance
산딸나무 is highly imbalanced (98.2%)Imbalance
연장(km) has 10 (1.7%) missing valuesMissing
버짐 has 504 (84.4%) missing valuesMissing
은행 has 438 (73.4%) missing valuesMissing
느티 has 507 (84.9%) missing valuesMissing
벚 has 494 (82.7%) missing valuesMissing
메타 has 573 (96.0%) missing valuesMissing
중국단풍 has 585 (98.0%) missing valuesMissing
단풍 has 591 (99.0%) missing valuesMissing
회화 has 570 (95.5%) missing valuesMissing
귀룽 has 597 (100.0%) missing valuesMissing
느릅 has 576 (96.5%) missing valuesMissing
이팝 has 433 (72.5%) missing valuesMissing
목백합 has 597 (100.0%) missing valuesMissing
살구 has 587 (98.3%) missing valuesMissing
반송 has 587 (98.3%) missing valuesMissing
개목련 has 597 (100.0%) missing valuesMissing
둥근소나무 has 597 (100.0%) missing valuesMissing
수수꽃다리 has 597 (100.0%) missing valuesMissing
귀룽 is an unsupported type, check if it needs cleaning or further analysisUnsupported
목백합 is an unsupported type, check if it needs cleaning or further analysisUnsupported
개목련 is an unsupported type, check if it needs cleaning or further analysisUnsupported
둥근소나무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수수꽃다리 is an unsupported type, check if it needs cleaning or further analysisUnsupported
계 has 15 (2.5%) zerosZeros

Reproduction

Analysis started2023-12-12 12:40:13.934217
Analysis finished2023-12-12 12:40:14.671809
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구 분
Categorical

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
흥덕구
194 
청원구
159 
상당구
145 
서원구
99 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상당구
2nd row서원구
3rd row서원구
4th row흥덕구
5th row상당구

Common Values

ValueCountFrequency (%)
흥덕구 194
32.5%
청원구 159
26.6%
상당구 145
24.3%
서원구 99
16.6%

Length

2023-12-12T21:40:14.733239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:14.854182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
흥덕구 194
32.5%
청원구 159
26.6%
상당구 145
24.3%
서원구 99
16.6%

노 선
Text

Distinct370
Distinct (%)62.1%
Missing1
Missing (%)0.2%
Memory size4.8 KiB
2023-12-12T21:40:15.104692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length5.1812081
Min length3

Characters and Unicode

Total characters3088
Distinct characters184
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique284 ?
Unique (%)47.7%

Sample

1st row제2순환로
2nd row제2순환로
3rd row제2순환로
4th row제2순환로
5th row금관로
ValueCountFrequency (%)
제1순환로 24
 
3.7%
청남로 16
 
2.5%
단재로 15
 
2.3%
제2순환로 12
 
1.9%
상당로 10
 
1.6%
충청대로 9
 
1.4%
산성로 9
 
1.4%
사직대로 9
 
1.4%
오송생명5로 8
 
1.2%
가로수로 8
 
1.2%
Other values (365) 523
81.3%
2023-12-12T21:40:15.494369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 562
 
18.2%
길 182
 
5.9%
번 126
 
4.1%
1 124
 
4.0%
2 86
 
2.8%
산 86
 
2.8%
대 66
 
2.1%
제 53
 
1.7%
청 49
 
1.6%
49
 
1.6%
Other values (174) 1705
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2584
83.7%
Decimal Number 452
 
14.6%
Space Separator 49
 
1.6%
Uppercase Letter 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 562
21.7%
길 182
 
7.0%
번 126
 
4.9%
산 86
 
3.3%
대 66
 
2.6%
제 53
 
2.1%
청 49
 
1.9%
오 47
 
1.8%
순 44
 
1.7%
환 44
 
1.7%
Other values (160) 1325
51.3%
Decimal Number
ValueCountFrequency (%)
1 124
27.4%
2 86
19.0%
3 47
 
10.4%
4 43
 
9.5%
6 33
 
7.3%
5 28
 
6.2%
0 26
 
5.8%
9 24
 
5.3%
7 23
 
5.1%
8 18
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2584
83.7%
Common 502
 
16.3%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 562
21.7%
길 182
 
7.0%
번 126
 
4.9%
산 86
 
3.3%
대 66
 
2.6%
제 53
 
2.1%
청 49
 
1.9%
오 47
 
1.8%
순 44
 
1.7%
환 44
 
1.7%
Other values (160) 1325
51.3%
Common
ValueCountFrequency (%)
1 124
24.7%
2 86
17.1%
49
 
9.8%
3 47
 
9.4%
4 43
 
8.6%
6 33
 
6.6%
5 28
 
5.6%
0 26
 
5.2%
9 24
 
4.8%
7 23
 
4.6%
Other values (2) 19
 
3.8%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2584
83.7%
ASCII 504
 
16.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 562
21.7%
길 182
 
7.0%
번 126
 
4.9%
산 86
 
3.3%
대 66
 
2.6%
제 53
 
2.1%
청 49
 
1.9%
오 47
 
1.8%
순 44
 
1.7%
환 44
 
1.7%
Other values (160) 1325
51.3%
ASCII
ValueCountFrequency (%)
1 124
24.6%
2 86
17.1%
49
 
9.7%
3 47
 
9.3%
4 43
 
8.5%
6 33
 
6.5%
5 28
 
5.6%
0 26
 
5.2%
9 24
 
4.8%
7 23
 
4.6%
Other values (4) 21
 
4.2%

구 간
Text

Distinct585
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2023-12-12T21:40:15.733706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length12.666667
Min length3

Characters and Unicode

Total characters7562
Distinct characters352
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

Unique573 ?
Unique (%)96.0%

Sample

1st row지북교차로 장암사거리
2nd row장암사거리 가마교차로
3rd row가마교차로 죽림사거리
4th row죽림사거리 시외버스터미널사거리
5th row청주시경계(청천면) 금관교
ValueCountFrequency (%)
사잇길 20
 
2.4%
지북교차로 4
 
0.5%
상당로 4
 
0.5%
산남사거리 4
 
0.5%
방아다리사거리 4
 
0.5%
앞길 4
 
0.5%
방서교 4
 
0.5%
대림아파트사거리 4
 
0.5%
무성삼거리 4
 
0.5%
금석교사거리 4
 
0.5%
Other values (643) 765
93.2%
2023-12-12T21:40:16.099232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 499
 
6.6%
리 460
 
6.1%
거 430
 
5.7%
- 391
 
5.2%
사 323
 
4.3%
224
 
3.0%
교 218
 
2.9%
길 162
 
2.1%
삼 160
 
2.1%
산 126
 
1.7%
Other values (342) 4569
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6386
84.4%
Decimal Number 450
 
6.0%
Dash Punctuation 391
 
5.2%
Space Separator 224
 
3.0%
Uppercase Letter 35
 
0.5%
Open Punctuation 31
 
0.4%
Close Punctuation 31
 
0.4%
Lowercase Letter 8
 
0.1%
Other Punctuation 5
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 499
 
7.8%
리 460
 
7.2%
거 430
 
6.7%
사 323
 
5.1%
교 218
 
3.4%
길 162
 
2.5%
삼 160
 
2.5%
산 126
 
2.0%
대 110
 
1.7%
청 105
 
1.6%
Other values (308) 3793
59.4%
Uppercase Letter
ValueCountFrequency (%)
S 6
17.1%
I 6
17.1%
C 4
11.4%
D 4
11.4%
B 3
8.6%
L 3
8.6%
H 2
 
5.7%
K 2
 
5.7%
O 2
 
5.7%
U 1
 
2.9%
Other values (2) 2
 
5.7%
Decimal Number
ValueCountFrequency (%)
1 120
26.7%
2 111
24.7%
4 50
11.1%
3 38
 
8.4%
9 29
 
6.4%
6 29
 
6.4%
0 24
 
5.3%
7 21
 
4.7%
5 15
 
3.3%
8 13
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
c 4
50.0%
m 2
25.0%
k 2
25.0%
Open Punctuation
ValueCountFrequency (%)
( 27
87.1%
[ 4
 
12.9%
Close Punctuation
ValueCountFrequency (%)
) 27
87.1%
] 4
 
12.9%
Other Punctuation
ValueCountFrequency (%)
/ 3
60.0%
' 2
40.0%
Dash Punctuation
ValueCountFrequency (%)
- 391
100.0%
Space Separator
ValueCountFrequency (%)
224
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6386
84.4%
Common 1133
 
15.0%
Latin 43
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 499
 
7.8%
리 460
 
7.2%
거 430
 
6.7%
사 323
 
5.1%
교 218
 
3.4%
길 162
 
2.5%
삼 160
 
2.5%
산 126
 
2.0%
대 110
 
1.7%
청 105
 
1.6%
Other values (308) 3793
59.4%
Common
ValueCountFrequency (%)
- 391
34.5%
224
19.8%
1 120
 
10.6%
2 111
 
9.8%
4 50
 
4.4%
3 38
 
3.4%
9 29
 
2.6%
6 29
 
2.6%
( 27
 
2.4%
) 27
 
2.4%
Other values (9) 87
 
7.7%
Latin
ValueCountFrequency (%)
S 6
14.0%
I 6
14.0%
c 4
9.3%
C 4
9.3%
D 4
9.3%
B 3
7.0%
L 3
7.0%
H 2
 
4.7%
K 2
 
4.7%
m 2
 
4.7%
Other values (5) 7
16.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6385
84.4%
ASCII 1176
 
15.6%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 499
 
7.8%
리 460
 
7.2%
거 430
 
6.7%
사 323
 
5.1%
교 218
 
3.4%
길 162
 
2.5%
삼 160
 
2.5%
산 126
 
2.0%
대 110
 
1.7%
청 105
 
1.6%
Other values (307) 3792
59.4%
ASCII
ValueCountFrequency (%)
- 391
33.2%
224
19.0%
1 120
 
10.2%
2 111
 
9.4%
4 50
 
4.3%
3 38
 
3.2%
9 29
 
2.5%
6 29
 
2.5%
( 27
 
2.3%
) 27
 
2.3%
Other values (24) 130
 
11.1%
Compat Jamo
ValueCountFrequency (%)
ㄷ 1
100.0%

연장(km)
Real number (ℝ)

MISSING 

Distinct270
Distinct (%)46.0%
Missing10
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean1.3955707
Minimum0.02
Maximum10.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:16.246406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.15
Q10.345
median0.87
Q31.78
95-th percentile4.864
Maximum10.49
Range10.47
Interquartile range (IQR)1.435

Descriptive statistics

Standard deviation1.5694203
Coefficient of variation (CV)1.1245724
Kurtosis6.6093674
Mean1.3955707
Median Absolute Deviation (MAD)0.59
Skewness2.3204319
Sum819.2
Variance2.46308
MonotonicityNot monotonic
2023-12-12T21:40:16.391195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3 12
 
2.0%
0.34 11
 
1.8%
0.15 9
 
1.5%
0.21 8
 
1.3%
0.12 7
 
1.2%
0.26 7
 
1.2%
0.16 7
 
1.2%
0.93 7
 
1.2%
0.54 7
 
1.2%
1.16 7
 
1.2%
Other values (260) 505
84.6%
(Missing) 10
 
1.7%
ValueCountFrequency (%)
0.02 1
 
0.2%
0.04 1
 
0.2%
0.06 1
 
0.2%
0.07 1
 
0.2%
0.08 3
0.5%
0.09 2
 
0.3%
0.1 5
0.8%
0.11 4
0.7%
0.12 7
1.2%
0.13 1
 
0.2%
ValueCountFrequency (%)
10.49 1
0.2%
9.69 1
0.2%
8.9 1
0.2%
8.68 1
0.2%
8.29 1
0.2%
7.67 1
0.2%
7.57 1
0.2%
6.77 1
0.2%
6.75 1
0.2%
6.58 1
0.2%

계
Real number (ℝ)

ZEROS 

Distinct298
Distinct (%)49.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.60972
Minimum0
Maximum2039
Zeros15
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:16.508776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11
Q139
median90
Q3206
95-th percentile525.2
Maximum2039
Range2039
Interquartile range (IQR)167

Descriptive statistics

Standard deviation193.99519
Coefficient of variation (CV)1.2154347
Kurtosis18.731876
Mean159.60972
Median Absolute Deviation (MAD)64
Skewness3.2610661
Sum95287
Variance37634.134
MonotonicityNot monotonic
2023-12-12T21:40:16.645647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
2.5%
25 10
 
1.7%
26 8
 
1.3%
28 8
 
1.3%
39 7
 
1.2%
31 7
 
1.2%
33 7
 
1.2%
45 6
 
1.0%
49 6
 
1.0%
10 6
 
1.0%
Other values (288) 517
86.6%
ValueCountFrequency (%)
0 15
2.5%
4 1
 
0.2%
6 3
 
0.5%
7 2
 
0.3%
8 2
 
0.3%
10 6
 
1.0%
11 5
 
0.8%
12 4
 
0.7%
13 1
 
0.2%
14 3
 
0.5%
ValueCountFrequency (%)
2039 1
0.2%
1208 1
0.2%
1164 1
0.2%
1050 1
0.2%
918 1
0.2%
908 1
0.2%
845 1
0.2%
844 1
0.2%
826 1
0.2%
795 1
0.2%

버짐
Real number (ℝ)

MISSING 

Distinct77
Distinct (%)82.8%
Missing504
Missing (%)84.4%
Infinite0
Infinite (%)0.0%
Mean112.06452
Minimum2
Maximum918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:16.779326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6.6
Q131
median69
Q3118
95-th percentile393
Maximum918
Range916
Interquartile range (IQR)87

Descriptive statistics

Standard deviation145.4401
Coefficient of variation (CV)1.2978247
Kurtosis11.260094
Mean112.06452
Median Absolute Deviation (MAD)41
Skewness3.0036606
Sum10422
Variance21152.822
MonotonicityNot monotonic
2023-12-12T21:40:16.893303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 3
 
0.5%
31 3
 
0.5%
7 3
 
0.5%
53 3
 
0.5%
6 2
 
0.3%
102 2
 
0.3%
69 2
 
0.3%
140 2
 
0.3%
49 2
 
0.3%
74 2
 
0.3%
Other values (67) 69
 
11.6%
(Missing) 504
84.4%
ValueCountFrequency (%)
2 1
 
0.2%
3 1
 
0.2%
5 1
 
0.2%
6 2
0.3%
7 3
0.5%
8 1
 
0.2%
11 1
 
0.2%
12 1
 
0.2%
13 1
 
0.2%
15 1
 
0.2%
ValueCountFrequency (%)
918 1
0.2%
591 1
0.2%
533 1
0.2%
479 1
0.2%
453 1
0.2%
353 1
0.2%
352 1
0.2%
338 1
0.2%
321 1
0.2%
316 1
0.2%

은행
Real number (ℝ)

MISSING 

Distinct117
Distinct (%)73.6%
Missing438
Missing (%)73.4%
Infinite0
Infinite (%)0.0%
Mean115.13836
Minimum2
Maximum549
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:17.008622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6.9
Q138
median78
Q3156
95-th percentile380.7
Maximum549
Range547
Interquartile range (IQR)118

Descriptive statistics

Standard deviation114.64819
Coefficient of variation (CV)0.99574277
Kurtosis2.7764056
Mean115.13836
Median Absolute Deviation (MAD)53
Skewness1.6977355
Sum18307
Variance13144.209
MonotonicityNot monotonic
2023-12-12T21:40:17.172487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 4
 
0.7%
2 4
 
0.7%
39 4
 
0.7%
48 3
 
0.5%
14 3
 
0.5%
13 2
 
0.3%
78 2
 
0.3%
51 2
 
0.3%
53 2
 
0.3%
10 2
 
0.3%
Other values (107) 131
 
21.9%
(Missing) 438
73.4%
ValueCountFrequency (%)
2 4
0.7%
6 4
0.7%
7 1
 
0.2%
10 2
0.3%
12 2
0.3%
13 2
0.3%
14 3
0.5%
15 2
0.3%
16 1
 
0.2%
17 1
 
0.2%
ValueCountFrequency (%)
549 1
0.2%
525 1
0.2%
476 1
0.2%
470 1
0.2%
461 1
0.2%
407 1
0.2%
396 1
0.2%
387 1
0.2%
380 1
0.2%
357 1
0.2%

느티
Real number (ℝ)

MISSING 

Distinct77
Distinct (%)85.6%
Missing507
Missing (%)84.9%
Infinite0
Infinite (%)0.0%
Mean124.21111
Minimum2
Maximum845
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:17.367790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6.45
Q125
median68.5
Q3194.75
95-th percentile348.55
Maximum845
Range843
Interquartile range (IQR)169.75

Descriptive statistics

Standard deviation142.73008
Coefficient of variation (CV)1.1490927
Kurtosis7.0832881
Mean124.21111
Median Absolute Deviation (MAD)51
Skewness2.2193633
Sum11179
Variance20371.876
MonotonicityNot monotonic
2023-12-12T21:40:17.798242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25 4
 
0.7%
21 2
 
0.3%
52 2
 
0.3%
58 2
 
0.3%
2 2
 
0.3%
4 2
 
0.3%
69 2
 
0.3%
26 2
 
0.3%
236 2
 
0.3%
31 2
 
0.3%
Other values (67) 68
 
11.4%
(Missing) 507
84.9%
ValueCountFrequency (%)
2 2
0.3%
4 2
0.3%
6 1
0.2%
7 1
0.2%
8 1
0.2%
10 1
0.2%
11 1
0.2%
13 1
0.2%
14 1
0.2%
17 1
0.2%
ValueCountFrequency (%)
845 1
0.2%
579 1
0.2%
467 1
0.2%
415 1
0.2%
358 1
0.2%
337 1
0.2%
328 1
0.2%
327 1
0.2%
311 1
0.2%
301 1
0.2%

벚
Real number (ℝ)

MISSING 

Distinct88
Distinct (%)85.4%
Missing494
Missing (%)82.7%
Infinite0
Infinite (%)0.0%
Mean177.74757
Minimum7
Maximum1055
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:17.957678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile11.2
Q134.5
median105
Q3268
95-th percentile510.9
Maximum1055
Range1048
Interquartile range (IQR)233.5

Descriptive statistics

Standard deviation200.67449
Coefficient of variation (CV)1.1289858
Kurtosis5.6977801
Mean177.74757
Median Absolute Deviation (MAD)83
Skewness2.1574793
Sum18308
Variance40270.249
MonotonicityNot monotonic
2023-12-12T21:40:18.098658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16 4
 
0.7%
83 3
 
0.5%
10 2
 
0.3%
104 2
 
0.3%
19 2
 
0.3%
166 2
 
0.3%
84 2
 
0.3%
41 2
 
0.3%
23 2
 
0.3%
7 2
 
0.3%
Other values (78) 80
 
13.4%
(Missing) 494
82.7%
ValueCountFrequency (%)
7 2
0.3%
8 1
 
0.2%
10 2
0.3%
11 1
 
0.2%
13 1
 
0.2%
15 1
 
0.2%
16 4
0.7%
17 1
 
0.2%
19 2
0.3%
22 2
0.3%
ValueCountFrequency (%)
1055 1
0.2%
983 1
0.2%
795 1
0.2%
761 1
0.2%
560 1
0.2%
512 1
0.2%
501 1
0.2%
486 1
0.2%
465 1
0.2%
458 1
0.2%

버드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
6
 
1

Length

Max length4
Median length4
Mean length3.9949749
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
6 1
 
0.2%

Length

2023-12-12T21:40:18.232032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:18.334937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
6 1
 
0.2%

칠엽수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
592 
23
 
1
26
 
1
36
 
1
40
 
1

Length

Max length4
Median length4
Mean length3.9832496
Min length2

Unique

Unique5 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 592
99.2%
23 1
 
0.2%
26 1
 
0.2%
36 1
 
0.2%
40 1
 
0.2%
28 1
 
0.2%

Length

2023-12-12T21:40:18.444834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:18.551702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 592
99.2%
23 1
 
0.2%
26 1
 
0.2%
36 1
 
0.2%
40 1
 
0.2%
28 1
 
0.2%

메타
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)100.0%
Missing573
Missing (%)96.0%
Infinite0
Infinite (%)0.0%
Mean201.375
Minimum5
Maximum712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:18.646413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile25.35
Q164
median132.5
Q3339.5
95-th percentile495.2
Maximum712
Range707
Interquartile range (IQR)275.5

Descriptive statistics

Standard deviation182.17474
Coefficient of variation (CV)0.9046542
Kurtosis1.1397486
Mean201.375
Median Absolute Deviation (MAD)81
Skewness1.2647961
Sum4833
Variance33187.636
MonotonicityNot monotonic
2023-12-12T21:40:18.765224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
116 1
 
0.2%
216 1
 
0.2%
33 1
 
0.2%
24 1
 
0.2%
418 1
 
0.2%
379 1
 
0.2%
332 1
 
0.2%
129 1
 
0.2%
115 1
 
0.2%
55 1
 
0.2%
Other values (14) 14
 
2.3%
(Missing) 573
96.0%
ValueCountFrequency (%)
5 1
0.2%
24 1
0.2%
33 1
0.2%
42 1
0.2%
54 1
0.2%
55 1
0.2%
67 1
0.2%
87 1
0.2%
115 1
0.2%
116 1
0.2%
ValueCountFrequency (%)
712 1
0.2%
506 1
0.2%
434 1
0.2%
418 1
0.2%
379 1
0.2%
362 1
0.2%
332 1
0.2%
216 1
0.2%
192 1
0.2%
147 1
0.2%

중국단풍
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)100.0%
Missing585
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean143.91667
Minimum17
Maximum359
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:18.873459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile19.75
Q146.5
median105.5
Q3189
95-th percentile356.8
Maximum359
Range342
Interquartile range (IQR)142.5

Descriptive statistics

Standard deviation130.0912
Coefficient of variation (CV)0.9039342
Kurtosis-0.64744197
Mean143.91667
Median Absolute Deviation (MAD)65.5
Skewness0.97119149
Sum1727
Variance16923.72
MonotonicityNot monotonic
2023-12-12T21:40:18.970728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
107 1
 
0.2%
359 1
 
0.2%
122 1
 
0.2%
53 1
 
0.2%
27 1
 
0.2%
333 1
 
0.2%
17 1
 
0.2%
141 1
 
0.2%
104 1
 
0.2%
355 1
 
0.2%
Other values (2) 2
 
0.3%
(Missing) 585
98.0%
ValueCountFrequency (%)
17 1
0.2%
22 1
0.2%
27 1
0.2%
53 1
0.2%
87 1
0.2%
104 1
0.2%
107 1
0.2%
122 1
0.2%
141 1
0.2%
333 1
0.2%
ValueCountFrequency (%)
359 1
0.2%
355 1
0.2%
333 1
0.2%
141 1
0.2%
122 1
0.2%
107 1
0.2%
104 1
0.2%
87 1
0.2%
53 1
0.2%
27 1
0.2%

단풍
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing591
Missing (%)99.0%
Infinite0
Infinite (%)0.0%
Mean87.833333
Minimum12
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:19.065395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile18
Q137.5
median61
Q3152.75
95-th percentile179.25
Maximum180
Range168
Interquartile range (IQR)115.25

Descriptive statistics

Standard deviation73.545677
Coefficient of variation (CV)0.83733219
Kurtosis-1.9414395
Mean87.833333
Median Absolute Deviation (MAD)37
Skewness0.61820124
Sum527
Variance5408.9667
MonotonicityNot monotonic
2023-12-12T21:40:19.151429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
36 1
 
0.2%
80 1
 
0.2%
177 1
 
0.2%
180 1
 
0.2%
42 1
 
0.2%
12 1
 
0.2%
(Missing) 591
99.0%
ValueCountFrequency (%)
12 1
0.2%
36 1
0.2%
42 1
0.2%
80 1
0.2%
177 1
0.2%
180 1
0.2%
ValueCountFrequency (%)
180 1
0.2%
177 1
0.2%
80 1
0.2%
42 1
0.2%
36 1
0.2%
12 1
0.2%

배롱
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
592 
66
 
1
108
 
1
166
 
1
295
 
1

Length

Max length4
Median length4
Mean length3.9882747
Min length2

Unique

Unique5 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 592
99.2%
66 1
 
0.2%
108 1
 
0.2%
166 1
 
0.2%
295 1
 
0.2%
87 1
 
0.2%

Length

2023-12-12T21:40:19.268341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:19.377668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 592
99.2%
66 1
 
0.2%
108 1
 
0.2%
166 1
 
0.2%
295 1
 
0.2%
87 1
 
0.2%

자귀
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
9
 
1

Length

Max length4
Median length4
Mean length3.9949749
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
9 1
 
0.2%

Length

2023-12-12T21:40:19.480241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:19.568390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
9 1
 
0.2%

주목
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
484
 
1

Length

Max length4
Median length4
Mean length3.998325
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
484 1
 
0.2%

Length

2023-12-12T21:40:19.660185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:19.741664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
484 1
 
0.2%

향나무
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
595 
55
 
1
30
 
1

Length

Max length4
Median length4
Mean length3.9932998
Min length2

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 595
99.7%
55 1
 
0.2%
30 1
 
0.2%

Length

2023-12-12T21:40:19.831753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:19.924866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 595
99.7%
55 1
 
0.2%
30 1
 
0.2%

회화
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)88.9%
Missing570
Missing (%)95.5%
Infinite0
Infinite (%)0.0%
Mean65.555556
Minimum2
Maximum177
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:20.010421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile20.2
Q131
median45
Q391
95-th percentile164
Maximum177
Range175
Interquartile range (IQR)60

Descriptive statistics

Standard deviation49.128821
Coefficient of variation (CV)0.74942269
Kurtosis0.13731843
Mean65.555556
Median Absolute Deviation (MAD)17
Skewness1.1134252
Sum1770
Variance2413.641
MonotonicityNot monotonic
2023-12-12T21:40:20.120695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
31 2
 
0.3%
33 2
 
0.3%
93 2
 
0.3%
66 1
 
0.2%
167 1
 
0.2%
45 1
 
0.2%
2 1
 
0.2%
23 1
 
0.2%
79 1
 
0.2%
36 1
 
0.2%
Other values (14) 14
 
2.3%
(Missing) 570
95.5%
ValueCountFrequency (%)
2 1
0.2%
19 1
0.2%
23 1
0.2%
28 1
0.2%
29 1
0.2%
30 1
0.2%
31 2
0.3%
33 2
0.3%
36 1
0.2%
43 1
0.2%
ValueCountFrequency (%)
177 1
0.2%
167 1
0.2%
157 1
0.2%
147 1
0.2%
123 1
0.2%
93 2
0.3%
89 1
0.2%
79 1
0.2%
66 1
0.2%
55 1
0.2%

귀룽
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing597
Missing (%)100.0%
Memory size5.4 KiB

무궁화
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
594 
1605
 
1
74
 
1
556
 
1

Length

Max length4
Median length4
Mean length3.9949749
Min length2

Unique

Unique3 ?
Unique (%)0.5%

Sample

1st row1605
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 594
99.5%
1605 1
 
0.2%
74 1
 
0.2%
556 1
 
0.2%

Length

2023-12-12T21:40:20.247564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:20.356971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 594
99.5%
1605 1
 
0.2%
74 1
 
0.2%
556 1
 
0.2%

노각
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
105
 
1

Length

Max length4
Median length4
Mean length3.998325
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
105 1
 
0.2%

Length

2023-12-12T21:40:20.450179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:20.537188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
105 1
 
0.2%

느릅
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)85.7%
Missing576
Missing (%)96.5%
Infinite0
Infinite (%)0.0%
Mean86.333333
Minimum11
Maximum228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:20.619876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile15
Q128
median50
Q3145
95-th percentile173
Maximum228
Range217
Interquartile range (IQR)117

Descriptive statistics

Standard deviation66.941268
Coefficient of variation (CV)0.77538148
Kurtosis-1.0801725
Mean86.333333
Median Absolute Deviation (MAD)35
Skewness0.53177265
Sum1813
Variance4481.1333
MonotonicityNot monotonic
2023-12-12T21:40:20.728055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
50 2
 
0.3%
20 2
 
0.3%
28 2
 
0.3%
103 1
 
0.2%
145 1
 
0.2%
156 1
 
0.2%
228 1
 
0.2%
173 1
 
0.2%
157 1
 
0.2%
134 1
 
0.2%
Other values (8) 8
 
1.3%
(Missing) 576
96.5%
ValueCountFrequency (%)
11 1
0.2%
15 1
0.2%
20 2
0.3%
26 1
0.2%
28 2
0.3%
37 1
0.2%
43 1
0.2%
50 2
0.3%
84 1
0.2%
103 1
0.2%
ValueCountFrequency (%)
228 1
0.2%
173 1
0.2%
168 1
0.2%
157 1
0.2%
156 1
0.2%
145 1
0.2%
137 1
0.2%
134 1
0.2%
103 1
0.2%
84 1
0.2%

이팝
Real number (ℝ)

MISSING 

Distinct110
Distinct (%)67.1%
Missing433
Missing (%)72.5%
Infinite0
Infinite (%)0.0%
Mean110.03659
Minimum4
Maximum844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:20.866119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile11
Q129.75
median57.5
Q3116.75
95-th percentile406.5
Maximum844
Range840
Interquartile range (IQR)87

Descriptive statistics

Standard deviation147.19854
Coefficient of variation (CV)1.3377236
Kurtosis8.84182
Mean110.03659
Median Absolute Deviation (MAD)33.5
Skewness2.8240815
Sum18046
Variance21667.41
MonotonicityNot monotonic
2023-12-12T21:40:21.016866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 5
 
0.8%
52 4
 
0.7%
58 4
 
0.7%
35 4
 
0.7%
14 3
 
0.5%
25 3
 
0.5%
66 3
 
0.5%
83 3
 
0.5%
55 3
 
0.5%
11 3
 
0.5%
Other values (100) 129
 
21.6%
(Missing) 433
72.5%
ValueCountFrequency (%)
4 1
 
0.2%
8 2
0.3%
9 2
0.3%
10 2
0.3%
11 3
0.5%
12 2
0.3%
14 3
0.5%
15 2
0.3%
16 3
0.5%
17 1
 
0.2%
ValueCountFrequency (%)
844 1
0.2%
826 1
0.2%
635 1
0.2%
600 1
0.2%
594 1
0.2%
574 1
0.2%
554 1
0.2%
478 1
0.2%
411 1
0.2%
381 1
0.2%

목백합
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing597
Missing (%)100.0%
Memory size5.4 KiB

계수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
595 
36
 
1
45
 
1

Length

Max length4
Median length4
Mean length3.9932998
Min length2

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 595
99.7%
36 1
 
0.2%
45 1
 
0.2%

Length

2023-12-12T21:40:21.169070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:21.269524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 595
99.7%
36 1
 
0.2%
45 1
 
0.2%

감
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
595 
90
 
1
36
 
1

Length

Max length4
Median length4
Mean length3.9932998
Min length2

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 595
99.7%
90 1
 
0.2%
36 1
 
0.2%

Length

2023-12-12T21:40:21.405333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:21.520965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 595
99.7%
90 1
 
0.2%
36 1
 
0.2%

산수유
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
69
 
1

Length

Max length4
Median length4
Mean length3.9966499
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
69 1
 
0.2%

Length

2023-12-12T21:40:21.644842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:21.745417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
69 1
 
0.2%

사과
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
1208
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
1208 1
 
0.2%

Length

2023-12-12T21:40:21.829309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:21.910592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
1208 1
 
0.2%

매실
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
171
 
1

Length

Max length4
Median length4
Mean length3.998325
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
171 1
 
0.2%

Length

2023-12-12T21:40:22.003983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:22.088713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
171 1
 
0.2%

살구
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)100.0%
Missing587
Missing (%)98.3%
Infinite0
Infinite (%)0.0%
Mean104
Minimum4
Maximum456
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:22.165982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile8.95
Q122.25
median66
Q378.5
95-th percentile350.7
Maximum456
Range452
Interquartile range (IQR)56.25

Descriptive statistics

Standard deviation138.28955
Coefficient of variation (CV)1.3297072
Kurtosis5.0848149
Mean104
Median Absolute Deviation (MAD)38.5
Skewness2.2287359
Sum1040
Variance19124
MonotonicityNot monotonic
2023-12-12T21:40:22.293816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
17 1
 
0.2%
15 1
 
0.2%
4 1
 
0.2%
456 1
 
0.2%
76 1
 
0.2%
38 1
 
0.2%
79 1
 
0.2%
56 1
 
0.2%
222 1
 
0.2%
77 1
 
0.2%
(Missing) 587
98.3%
ValueCountFrequency (%)
4 1
0.2%
15 1
0.2%
17 1
0.2%
38 1
0.2%
56 1
0.2%
76 1
0.2%
77 1
0.2%
79 1
0.2%
222 1
0.2%
456 1
0.2%
ValueCountFrequency (%)
456 1
0.2%
222 1
0.2%
79 1
0.2%
77 1
0.2%
76 1
0.2%
56 1
0.2%
38 1
0.2%
17 1
0.2%
15 1
0.2%
4 1
0.2%

모과
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
594 
5
 
1
13
 
1
80
 
1

Length

Max length4
Median length4
Mean length3.9882747
Min length1

Unique

Unique3 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 594
99.5%
5 1
 
0.2%
13 1
 
0.2%
80 1
 
0.2%

Length

2023-12-12T21:40:22.427204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:22.527888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 594
99.5%
5 1
 
0.2%
13 1
 
0.2%
80 1
 
0.2%

반송
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)100.0%
Missing587
Missing (%)98.3%
Infinite0
Infinite (%)0.0%
Mean119.9
Minimum14
Maximum562
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2023-12-12T21:40:22.613320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile14.45
Q138.5
median54.5
Q395.75
95-th percentile420.7
Maximum562
Range548
Interquartile range (IQR)57.25

Descriptive statistics

Standard deviation169.55986
Coefficient of variation (CV)1.4141773
Kurtosis5.9187578
Mean119.9
Median Absolute Deviation (MAD)28
Skewness2.4041771
Sum1199
Variance28750.544
MonotonicityNot monotonic
2023-12-12T21:40:22.719559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
248 1
 
0.2%
14 1
 
0.2%
105 1
 
0.2%
47 1
 
0.2%
38 1
 
0.2%
68 1
 
0.2%
15 1
 
0.2%
40 1
 
0.2%
62 1
 
0.2%
562 1
 
0.2%
(Missing) 587
98.3%
ValueCountFrequency (%)
14 1
0.2%
15 1
0.2%
38 1
0.2%
40 1
0.2%
47 1
0.2%
62 1
0.2%
68 1
0.2%
105 1
0.2%
248 1
0.2%
562 1
0.2%
ValueCountFrequency (%)
562 1
0.2%
248 1
0.2%
105 1
0.2%
68 1
0.2%
62 1
0.2%
47 1
0.2%
40 1
0.2%
38 1
0.2%
15 1
0.2%
14 1
0.2%

대왕참
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
594 
199
 
1
160
 
1
66
 
1

Length

Max length4
Median length4
Mean length3.9932998
Min length2

Unique

Unique3 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 594
99.5%
199 1
 
0.2%
160 1
 
0.2%
66 1
 
0.2%

Length

2023-12-12T21:40:22.910374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:23.054953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 594
99.5%
199 1
 
0.2%
160 1
 
0.2%
66 1
 
0.2%

대추
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
10
 
1

Length

Max length4
Median length4
Mean length3.9966499
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
10 1
 
0.2%

Length

2023-12-12T21:40:23.172633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:23.295529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
10 1
 
0.2%

개목련
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing597
Missing (%)100.0%
Memory size5.4 KiB

둥근소나무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing597
Missing (%)100.0%
Memory size5.4 KiB

수수꽃다리
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing597
Missing (%)100.0%
Memory size5.4 KiB

튤립나무
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
10
 
1

Length

Max length4
Median length4
Mean length3.9966499
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
10 1
 
0.2%

Length

2023-12-12T21:40:23.426438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:23.553179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
10 1
 
0.2%

공작단풍
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
60
 
1

Length

Max length4
Median length4
Mean length3.9966499
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
60 1
 
0.2%

Length

2023-12-12T21:40:23.999094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:24.109873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
60 1
 
0.2%

소나무
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
15
 
1

Length

Max length4
Median length4
Mean length3.9966499
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
15 1
 
0.2%

Length

2023-12-12T21:40:24.237363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:24.366965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
15 1
 
0.2%

산딸나무
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
596 
44
 
1

Length

Max length4
Median length4
Mean length3.9966499
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 596
99.8%
44 1
 
0.2%

Length

2023-12-12T21:40:24.484891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:24.609804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 596
99.8%
44 1
 
0.2%

Sample

구 분노 선구 간연장(km)계버짐은행느티벚버드칠엽수메타중국단풍단풍배롱자귀주목향나무회화귀룽무궁화노각느릅이팝목백합계수감산수유사과매실살구모과반송대왕참대추개목련둥근소나무수수꽃다리튤립나무공작단풍소나무산딸나무
0상당구제2순환로지북교차로 장암사거리1.72039<NA><NA><NA><NA><NA><NA>434<NA><NA><NA><NA><NA><NA><NA><NA>1605<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1서원구제2순환로장암사거리 가마교차로1.41362<NA><NA><NA><NA><NA><NA>362<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2서원구제2순환로가마교차로 죽림사거리3.38712<NA><NA><NA><NA><NA><NA>712<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3흥덕구제2순환로죽림사거리 시외버스터미널사거리1.66418<NA>190<NA><NA><NA><NA>192<NA>36<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4상당구금관로청주시경계(청천면) 금관교2.0137<NA><NA><NA>83<NA><NA>54<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5상당구낭성시내길무성삼거리 호정삼거리(마을안길)0.8887<NA><NA><NA><NA><NA><NA>87<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6상당구산성로현암삼거리 무성삼거리1.48126<NA><NA><NA><NA><NA><NA>126<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7상당구산성로호정삼거리 관정삼거리2.58136<NA><NA><NA><NA><NA><NA>136<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8상당구호정대신로호정삼거리 대신삼거리9.69146<NA><NA><NA><NA><NA><NA>146<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9상당구수영로청주동중학교사거리 용정축구공원교차로1.12191<NA><NA><NA><NA><NA><NA>147<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>44
구 분노 선구 간연장(km)계버짐은행느티벚버드칠엽수메타중국단풍단풍배롱자귀주목향나무회화귀룽무궁화노각느릅이팝목백합계수감산수유사과매실살구모과반송대왕참대추개목련둥근소나무수수꽃다리튤립나무공작단풍소나무산딸나무
587흥덕구풍산로복대초교입구삼거리-시외버스터미널사거리1.83279<NA>279<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
588흥덕구풍산로34번길풍산로-풍년로142번길0.1211<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>11<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
589흥덕구풍산로47번길풍년로194번길-풍산로0.3332<NA><NA>32<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
590흥덕구풍산로48번길풍산로-풍년로142번길0.1220<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
591흥덕구호죽성재로장남교-청주시경계(병천면)6.17221<NA><NA><NA>221<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
592흥덕구호죽화산로강촌교-호죽삼거리1.53197<NA><NA><NA>197<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
593흥덕구흥덕로무심서로-고인쇄박물관사거리1.0223<NA>223<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
594청원구충청대로청주 그랜드 플라자 앞0.0212<NA><NA><NA><NA><NA><NA><NA><NA>12<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
595청원구<NA>3산업단지 일원3.8635<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>635<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
596서원구가장로장암사거리(아름다운 웨딩홀) ~ 고은삼거리1.16140<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>140<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>