Overview

Dataset statistics

Number of variables4
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory36.9 B

Variable types

Categorical2
Text1
Numeric1

Dataset

Description공원녹화 업무와 관련하여 제주특별자치도 제주시 관내 가로수 조성 현황 데이터를 제공합니다.항목 : 성상, 수종, 수량 등
Author제주특별자치도 제주시
URLhttps://www.data.go.kr/data/3083418/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
수종 has unique valuesUnique

Reproduction

Analysis started2024-04-13 11:24:06.761644
Analysis finished2024-04-13 11:24:09.746341
Duration2.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

성상
Categorical

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size392.0 B
상록수
16 
낙엽수
14 
야자류외
3 

Length

Max length4
Median length3
Mean length3.0909091
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상록수 16
48.5%
낙엽수 14
42.4%
야자류외 3
 
9.1%

Length

2024-04-13T20:24:09.971536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T20:24:10.318063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상록수 16
48.5%
낙엽수 14
42.4%
야자류외 3
 
9.1%

수종
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
2024-04-13T20:24:11.039036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.7272727
Min length2

Characters and Unicode

Total characters123
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row후박나무
2nd row구실잣밤나무
3rd row담팔수
4th row해송
5th row협죽도
ValueCountFrequency (%)
후박나무 1
 
3.0%
은행나무 1
 
3.0%
당종려 1
 
3.0%
와싱톤야자 1
 
3.0%
겹벚나무 1
 
3.0%
느티나무 1
 
3.0%
매화나무 1
 
3.0%
목련 1
 
3.0%
백합나무 1
 
3.0%
느릅나무 1
 
3.0%
Other values (23) 23
69.7%
2024-04-13T20:24:12.240722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
나 22
 
17.9%
무 22
 
17.9%
목 3
 
2.4%
백 3
 
2.4%
종 3
 
2.4%
느 2
 
1.6%
벚 2
 
1.6%
서 2
 
1.6%
은 2
 
1.6%
후 2
 
1.6%
Other values (60) 60
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
나 22
 
17.9%
무 22
 
17.9%
목 3
 
2.4%
백 3
 
2.4%
종 3
 
2.4%
느 2
 
1.6%
벚 2
 
1.6%
서 2
 
1.6%
은 2
 
1.6%
후 2
 
1.6%
Other values (60) 60
48.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
나 22
 
17.9%
무 22
 
17.9%
목 3
 
2.4%
백 3
 
2.4%
종 3
 
2.4%
느 2
 
1.6%
벚 2
 
1.6%
서 2
 
1.6%
은 2
 
1.6%
후 2
 
1.6%
Other values (60) 60
48.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
나 22
 
17.9%
무 22
 
17.9%
목 3
 
2.4%
백 3
 
2.4%
종 3
 
2.4%
느 2
 
1.6%
벚 2
 
1.6%
서 2
 
1.6%
은 2
 
1.6%
후 2
 
1.6%
Other values (60) 60
48.8%

수량
Real number (ℝ)

Distinct32
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1258.5152
Minimum1
Maximum10552
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size425.0 B
2024-04-13T20:24:12.634548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.8
Q168
median259
Q31602
95-th percentile5132.6
Maximum10552
Range10551
Interquartile range (IQR)1534

Descriptive statistics

Standard deviation2217.4926
Coefficient of variation (CV)1.7619912
Kurtosis9.4641915
Mean1258.5152
Median Absolute Deviation (MAD)217
Skewness2.8592747
Sum41531
Variance4917273.3
MonotonicityNot monotonic
2024-04-13T20:24:13.030514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
42 2
 
6.1%
6101 1
 
3.0%
97 1
 
3.0%
43 1
 
3.0%
404 1
 
3.0%
999 1
 
3.0%
127 1
 
3.0%
2488 1
 
3.0%
46 1
 
3.0%
75 1
 
3.0%
Other values (22) 22
66.7%
ValueCountFrequency (%)
1 1
3.0%
10 1
3.0%
28 1
3.0%
42 2
6.1%
43 1
3.0%
45 1
3.0%
46 1
3.0%
68 1
3.0%
75 1
3.0%
77 1
3.0%
ValueCountFrequency (%)
10552 1
3.0%
6101 1
3.0%
4487 1
3.0%
3438 1
3.0%
2990 1
3.0%
2488 1
3.0%
2119 1
3.0%
1608 1
3.0%
1602 1
3.0%
1285 1
3.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size392.0 B
2024-03-31
33 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-31
2nd row2024-03-31
3rd row2024-03-31
4th row2024-03-31
5th row2024-03-31

Common Values

ValueCountFrequency (%)
2024-03-31 33
100.0%

Length

2024-04-13T20:24:13.412142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T20:24:13.712675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-31 33
100.0%

Interactions

2024-04-13T20:24:09.021434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-13T20:24:13.888245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성상수종수량
성상1.0001.0000.000
수종1.0001.0001.000
수량0.0001.0001.000
2024-04-13T20:24:14.118175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수량성상
수량1.0000.000
성상0.0001.000

Missing values

2024-04-13T20:24:09.344151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-13T20:24:09.625479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

성상수종수량데이터기준일자
0상록수후박나무61012024-03-31
1상록수구실잣밤나무21192024-03-31
2상록수담팔수16082024-03-31
3상록수해송29902024-03-31
4상록수협죽도2902024-03-31
5상록수동백나무452024-03-31
6상록수녹나무16022024-03-31
7상록수먼나무44872024-03-31
8상록수조록나무2592024-03-31
9상록수후피향나무1052024-03-31
성상수종수량데이터기준일자
23낙엽수이팝나무12852024-03-31
24낙엽수느릅나무5822024-03-31
25낙엽수백합나무752024-03-31
26낙엽수목련462024-03-31
27낙엽수매화나무422024-03-31
28낙엽수느티나무24882024-03-31
29낙엽수겹벚나무1272024-03-31
30야자류외와싱톤야자9992024-03-31
31야자류외당종려4042024-03-31
32야자류외하귤432024-03-31