Overview

Dataset statistics

Number of variables20
Number of observations131
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.0 KiB
Average record size in memory172.0 B

Variable types

Numeric4
Categorical16

Dataset

Description객체id,종명,학명,과명,서울시보호,멸종위기1,멸종위기2,천연기념물,고유종,유해종,포획금지종,자치구,조사지역,조사연도,조사출처,참고문헌,x_value,y_value,특이종범례,조사시점
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21167/S/1/datasetView.do

Alerts

천연기념물 has constant value ""Constant
유해종 has constant value ""Constant
조사출처 has constant value ""Constant
조사지역 is highly overall correlated with 객체id and 6 other fieldsHigh correlation
과명 is highly overall correlated with 종명 and 6 other fieldsHigh correlation
종명 is highly overall correlated with 학명 and 7 other fieldsHigh correlation
멸종위기1 is highly overall correlated with 종명 and 2 other fieldsHigh correlation
포획금지종 is highly overall correlated with 종명 and 2 other fieldsHigh correlation
자치구 is highly overall correlated with 객체id and 6 other fieldsHigh correlation
학명 is highly overall correlated with 종명 and 7 other fieldsHigh correlation
고유종 is highly overall correlated with 종명 and 4 other fieldsHigh correlation
서울시보호 is highly overall correlated with 종명 and 4 other fieldsHigh correlation
조사시점 is highly overall correlated with 객체id and 6 other fieldsHigh correlation
특이종범례 is highly overall correlated with 종명 and 6 other fieldsHigh correlation
멸종위기2 is highly overall correlated with 종명 and 3 other fieldsHigh correlation
객체id is highly overall correlated with x_value and 3 other fieldsHigh correlation
조사연도 is highly overall correlated with 자치구 and 3 other fieldsHigh correlation
x_value is highly overall correlated with 객체id and 4 other fieldsHigh correlation
y_value is highly overall correlated with 자치구 and 3 other fieldsHigh correlation
참고문헌 is highly overall correlated with 조사연도 and 5 other fieldsHigh correlation
멸종위기1 is highly imbalanced (93.5%)Imbalance
멸종위기2 is highly imbalanced (76.6%)Imbalance
특이종범례 is highly imbalanced (56.7%)Imbalance
객체id has unique valuesUnique

Reproduction

Analysis started2024-05-10 23:34:24.914582
Analysis finished2024-05-10 23:34:34.911219
Duration10 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

객체id
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10601.344
Minimum10359
Maximum10681
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-10T23:34:35.106239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10359
5-th percentile10365.5
Q110583.5
median10616
Q310648.5
95-th percentile10674.5
Maximum10681
Range322
Interquartile range (IQR)65

Descriptive statistics

Standard deviation76.467667
Coefficient of variation (CV)0.0072130167
Kurtosis4.6370956
Mean10601.344
Median Absolute Deviation (MAD)33
Skewness-2.1834912
Sum1388776
Variance5847.3042
MonotonicityStrictly increasing
2024-05-10T23:34:35.552456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10359 1
 
0.8%
10634 1
 
0.8%
10648 1
 
0.8%
10647 1
 
0.8%
10646 1
 
0.8%
10645 1
 
0.8%
10644 1
 
0.8%
10643 1
 
0.8%
10642 1
 
0.8%
10641 1
 
0.8%
Other values (121) 121
92.4%
ValueCountFrequency (%)
10359 1
0.8%
10360 1
0.8%
10361 1
0.8%
10362 1
0.8%
10363 1
0.8%
10364 1
0.8%
10365 1
0.8%
10366 1
0.8%
10367 1
0.8%
10368 1
0.8%
ValueCountFrequency (%)
10681 1
0.8%
10680 1
0.8%
10679 1
0.8%
10678 1
0.8%
10677 1
0.8%
10676 1
0.8%
10675 1
0.8%
10674 1
0.8%
10673 1
0.8%
10672 1
0.8%

종명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
족제비
42 
다람쥐
40 
멧토끼
18 
고슴도치
18 
삵
5 
Other values (3)
8 

Length

Max length4
Median length3
Mean length3.0458015
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row다람쥐
2nd row다람쥐
3rd row족제비
4th row족제비
5th row족제비

Common Values

ValueCountFrequency (%)
족제비 42
32.1%
다람쥐 40
30.5%
멧토끼 18
13.7%
고슴도치 18
13.7%
삵 5
 
3.8%
오소리 4
 
3.1%
노루 3
 
2.3%
대륙사슴 1
 
0.8%

Length

2024-05-10T23:34:36.036339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:34:36.412265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
족제비 42
32.1%
다람쥐 40
30.5%
멧토끼 18
13.7%
고슴도치 18
13.7%
삵 5
 
3.8%
오소리 4
 
3.1%
노루 3
 
2.3%
대륙사슴 1
 
0.8%

학명
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Mustela sibirica (Pallas, 1773)
42 
Tamias sibiricus (Laxmannm, 1769)
40 
Erinaceus amurensis (Schrenk, 1859)
18 
Prionailurus bengalensis (Kerr, 1792)
5 
Meles leucurus (Hodgson, 1847)
 
4
Other values (22)
22 

Length

Max length39
Median length37
Mean length33.656489
Min length13

Unique

Unique22 ?
Unique (%)16.8%

Sample

1st rowTamias sibiricus (Laxmannm, 1769)
2nd rowTamias sibiricus (Laxmannm, 1769)
3rd rowMustela sibirica (Pallas, 1773)
4th rowMustela sibirica (Pallas, 1773)
5th rowMustela sibirica (Pallas, 1773)

Common Values

ValueCountFrequency (%)
Mustela sibirica (Pallas, 1773) 42
32.1%
Tamias sibiricus (Laxmannm, 1769) 40
30.5%
Erinaceus amurensis (Schrenk, 1859) 18
13.7%
Prionailurus bengalensis (Kerr, 1792) 5
 
3.8%
Meles leucurus (Hodgson, 1847) 4
 
3.1%
Capreolus pygargus (Pallas, 1771) 1
 
0.8%
Lepus coreanus (Thomas, 1906) 1
 
0.8%
Lepus coreanus (Thomas, 1902) 1
 
0.8%
Lepus coreanus (Thomas, 1904) 1
 
0.8%
Lepus coreanus (Thomas, 1895) 1
 
0.8%
Other values (17) 17
13.0%

Length

2024-05-10T23:34:36.843105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pallas 45
 
8.6%
1773 43
 
8.2%
mustela 42
 
8.0%
sibirica 42
 
8.0%
tamias 40
 
7.7%
sibiricus 40
 
7.7%
laxmannm 40
 
7.7%
1769 40
 
7.7%
1859 18
 
3.4%
thomas 18
 
3.4%
Other values (37) 154
29.5%

과명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
족제비과
46 
다람쥐과
40 
토끼과
18 
고슴도치과
18 
고양이과
5 

Length

Max length5
Median length4
Mean length3.9694656
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row다람쥐과
2nd row다람쥐과
3rd row족제비과
4th row족제비과
5th row족제비과

Common Values

ValueCountFrequency (%)
족제비과 46
35.1%
다람쥐과 40
30.5%
토끼과 18
 
13.7%
고슴도치과 18
 
13.7%
고양이과 5
 
3.8%
사슴과 4
 
3.1%

Length

2024-05-10T23:34:37.283594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:34:37.627086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
족제비과 46
35.1%
다람쥐과 40
30.5%
토끼과 18
 
13.7%
고슴도치과 18
 
13.7%
고양이과 5
 
3.8%
사슴과 4
 
3.1%

서울시보호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1
107 
0
24 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 107
81.7%
0 24
 
18.3%

Length

2024-05-10T23:34:38.019959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:34:38.319855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 107
81.7%
0 24
 
18.3%

멸종위기1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0
130 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 130
99.2%
1 1
 
0.8%

Length

2024-05-10T23:34:38.518049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:34:38.695826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 130
99.2%
1 1
 
0.8%

멸종위기2
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0
126 
1
 
5

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 (%)
0 126
96.2%
1 5
 
3.8%

Length

2024-05-10T23:34:38.884276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:34:39.141740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 126
96.2%
1 5
 
3.8%

천연기념물
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0
131 

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 (%)
0 131
100.0%

Length

2024-05-10T23:34:39.458810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:34:39.632985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 131
100.0%

고유종
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0
113 
1
18 

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 (%)
0 113
86.3%
1 18
 
13.7%

Length

2024-05-10T23:34:39.811950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:34:40.020494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 113
86.3%
1 18
 
13.7%

유해종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0
131 

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 (%)
0 131
100.0%

Length

2024-05-10T23:34:40.356486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:34:40.679936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 131
100.0%

포획금지종
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0
85 
1
46 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 85
64.9%
1 46
35.1%

Length

2024-05-10T23:34:40.993589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:34:41.314679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 85
64.9%
1 46
35.1%

자치구
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
노원구
19 
종로구
18 
마포구
18 
강북구
17 
관악구
12 
Other values (17)
47 

Length

Max length26
Median length3
Mean length3.6717557
Min length2

Unique

Unique7 ?
Unique (%)5.3%

Sample

1st row서대문구
2nd row영등포구, 강서구, 구로구, 양천구, 금천구
3rd row강남구
4th row강남구
5th row영등포구

Common Values

ValueCountFrequency (%)
노원구 19
14.5%
종로구 18
13.7%
마포구 18
13.7%
강북구 17
13.0%
관악구 12
9.2%
서초구 10
7.6%
강남구 8
6.1%
구로구 5
 
3.8%
강서구 5
 
3.8%
서대문구 2
 
1.5%
Other values (12) 17
13.0%

Length

2024-05-10T23:34:41.590697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노원구 20
13.5%
마포구 19
12.8%
종로구 19
12.8%
강북구 17
11.5%
관악구 12
8.1%
서초구 11
7.4%
강남구 9
 
6.1%
구로구 6
 
4.1%
강서구 6
 
4.1%
성동구 5
 
3.4%
Other values (13) 24
16.2%

조사지역
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
북한산
16 
월드컵공원
15 
관악산
12 
수락산
11 
청계산
10 
Other values (31)
67 

Length

Max length15
Median length3
Mean length4.2824427
Min length2

Unique

Unique16 ?
Unique (%)12.2%

Sample

1st row안산
2nd row안양천
3rd row양재천~탄천 합류부
4th row양재천~탄천 합류부
5th row여의샛강

Common Values

ValueCountFrequency (%)
북한산 16
12.2%
월드컵공원 15
11.5%
관악산 12
 
9.2%
수락산 11
 
8.4%
청계산 10
 
7.6%
북악산 8
 
6.1%
불암산 8
 
6.1%
인왕산 8
 
6.1%
와룡산 3
 
2.3%
난지도 월드컵공원 3
 
2.3%
Other values (26) 37
28.2%

Length

2024-05-10T23:34:41.970911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
월드컵공원 18
 
12.2%
북한산 16
 
10.9%
관악산 12
 
8.2%
수락산 11
 
7.5%
청계산 10
 
6.8%
북악산 8
 
5.4%
불암산 8
 
5.4%
인왕산 8
 
5.4%
생태경관보전지역 5
 
3.4%
합류부 3
 
2.0%
Other values (32) 48
32.7%

조사연도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2004.313
Minimum1997
Maximum2011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-10T23:34:42.317321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1997
5-th percentile1997
Q12003
median2004
Q32007
95-th percentile2010
Maximum2011
Range14
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.0951829
Coefficient of variation (CV)0.0020431853
Kurtosis-0.7409008
Mean2004.313
Median Absolute Deviation (MAD)3
Skewness-0.31939069
Sum262565
Variance16.770523
MonotonicityNot monotonic
2024-05-10T23:34:42.596496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2004 35
26.7%
2009 15
11.5%
2010 15
11.5%
2005 12
 
9.2%
1998 12
 
9.2%
1997 12
 
9.2%
2007 9
 
6.9%
2003 8
 
6.1%
2002 5
 
3.8%
2006 3
 
2.3%
Other values (2) 5
 
3.8%
ValueCountFrequency (%)
1997 12
 
9.2%
1998 12
 
9.2%
2001 3
 
2.3%
2002 5
 
3.8%
2003 8
 
6.1%
2004 35
26.7%
2005 12
 
9.2%
2006 3
 
2.3%
2007 9
 
6.9%
2009 15
11.5%
ValueCountFrequency (%)
2011 2
 
1.5%
2010 15
11.5%
2009 15
11.5%
2007 9
 
6.9%
2006 3
 
2.3%
2005 12
 
9.2%
2004 35
26.7%
2003 8
 
6.1%
2002 5
 
3.8%
2001 3
 
2.3%

조사출처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
문헌조사
131 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문헌조사 131
100.0%

Length

2024-05-10T23:34:42.825548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:34:43.131292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문헌조사 131
100.0%

참고문헌
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
산림생태계조사 연구보고서
24 
공원녹지의 효과적인 연결을 위한 기본계획
22 
북한산 국립공원 자원 모니터링
13 
월드컵공원 자연생태계 모니터링 및 관리방안
12 
서울시 도시숲(산림) 생태계 조사 학술 연구
11 
Other values (17)
49 

Length

Max length31
Median length28
Mean length19.320611
Min length10

Unique

Unique8 ?
Unique (%)6.1%

Sample

1st row서울시 도시숲 산림 건강성 및 생물다양성 학술연구
2nd row2007년 한강생태계 조사
3rd row양재천 자연형 하천 조성사례
4th row탄천 생태계 보전지역 생태변화관찰 및 관리대책
5th row2007년 한강생태계 조사

Common Values

ValueCountFrequency (%)
산림생태계조사 연구보고서 24
18.3%
공원녹지의 효과적인 연결을 위한 기본계획 22
16.8%
북한산 국립공원 자원 모니터링 13
9.9%
월드컵공원 자연생태계 모니터링 및 관리방안 12
9.2%
서울시 도시숲(산림) 생태계 조사 학술 연구 11
8.4%
서울시 도시숲 산림 건강성 및 생물다양성 학술연구 10
7.6%
2007년 한강생태계 조사 8
 
6.1%
월드컵공원 자연생태계 모니터링 6
 
4.6%
탄천 생태계 보전지역 생태변화관찰 및 관리대책 5
 
3.8%
한강생태계 조사연구 3
 
2.3%
Other values (12) 17
13.0%

Length

2024-05-10T23:34:43.336981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
및 33
 
5.9%
모니터링 33
 
5.9%
산림생태계조사 24
 
4.3%
연구보고서 24
 
4.3%
서울시 23
 
4.1%
위한 22
 
3.9%
공원녹지의 22
 
3.9%
기본계획 22
 
3.9%
연결을 22
 
3.9%
효과적인 22
 
3.9%
Other values (52) 313
55.9%

x_value
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean198364.68
Minimum182514.7
Maximum212478.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-10T23:34:43.666194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182514.7
5-th percentile184046.63
Q1194749.85
median198426.6
Q3204768.45
95-th percentile207848.3
Maximum212478.3
Range29963.6
Interquartile range (IQR)10018.6

Descriptive statistics

Standard deviation7346.7009
Coefficient of variation (CV)0.037036336
Kurtosis-0.65166443
Mean198364.68
Median Absolute Deviation (MAD)5739.1
Skewness-0.26612164
Sum25985773
Variance53974014
MonotonicityNot monotonic
2024-05-10T23:34:43.894348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
198426.6 16
12.2%
190107.9 15
11.5%
196429.0 12
 
9.2%
206693.8 11
 
8.4%
203920.1 10
 
7.6%
197599.8 8
 
6.1%
207848.3 8
 
6.1%
196252.9 8
 
6.1%
184046.633 3
 
2.3%
189432.0 3
 
2.3%
Other values (25) 37
28.2%
ValueCountFrequency (%)
182514.7 3
 
2.3%
183705.691 2
 
1.5%
184046.633 3
 
2.3%
185078.563 2
 
1.5%
189432.0 3
 
2.3%
189443.6 1
 
0.8%
190107.9 15
11.5%
191803.359 2
 
1.5%
192687.5 1
 
0.8%
194448.9 1
 
0.8%
ValueCountFrequency (%)
212478.3 2
 
1.5%
210817.4 1
 
0.8%
209484.4 1
 
0.8%
208666.8 2
 
1.5%
207848.3 8
6.1%
207194.9 1
 
0.8%
206693.8 11
8.4%
206564.3 2
 
1.5%
206409.8 2
 
1.5%
206389.4 1
 
0.8%

y_value
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean451968.12
Minimum437272.4
Maximum465056.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-10T23:34:44.328409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437272.4
5-th percentile437272.4
Q1444099.1
median452034
Q3461398.5
95-th percentile465056.8
Maximum465056.8
Range27784.4
Interquartile range (IQR)17299.4

Descriptive statistics

Standard deviation8654.8997
Coefficient of variation (CV)0.019149359
Kurtosis-1.0727402
Mean451968.12
Median Absolute Deviation (MAD)8888.9
Skewness-0.15025917
Sum59207823
Variance74907289
MonotonicityNot monotonic
2024-05-10T23:34:44.581944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
461398.5 16
12.2%
451442.6 15
11.5%
440098.8 12
 
9.2%
465056.8 11
 
8.4%
437272.4 10
 
7.6%
454548.1 8
 
6.1%
462895.7 8
 
6.1%
453421.1 8
 
6.1%
443673.823 3
 
2.3%
452034.0 3
 
2.3%
Other values (25) 37
28.2%
ValueCountFrequency (%)
437272.4 10
7.6%
440098.8 12
9.2%
440774.0 1
 
0.8%
441372.6 2
 
1.5%
441972.486 2
 
1.5%
443015.0 1
 
0.8%
443025.1 1
 
0.8%
443673.823 3
 
2.3%
443793.2 1
 
0.8%
444405.0 2
 
1.5%
ValueCountFrequency (%)
465056.8 11
8.4%
462895.7 8
6.1%
462337.416 1
 
0.8%
461398.5 16
12.2%
460922.9 1
 
0.8%
455621.9 3
 
2.3%
454548.1 8
6.1%
454339.7 1
 
0.8%
453917.161 2
 
1.5%
453647.8 1
 
0.8%

특이종범례
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
서울시보호종
107 
고유종
18 
멸종위기종2급
 
5
멸종위기종1급
 
1

Length

Max length7
Median length6
Mean length5.6335878
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
서울시보호종 107
81.7%
고유종 18
 
13.7%
멸종위기종2급 5
 
3.8%
멸종위기종1급 1
 
0.8%

Length

2024-05-10T23:34:44.842769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:34:45.100314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울시보호종 107
81.7%
고유종 18
 
13.7%
멸종위기종2급 5
 
3.8%
멸종위기종1급 1
 
0.8%

조사시점
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
p0102
16 
p0198
15 
p0036
12 
p0148
11 
p0243
10 
Other values (31)
67 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique16 ?
Unique (%)12.2%

Sample

1st rowp0157
2nd rowp0158
3rd rowp0168
4th rowp0168
5th rowp0175

Common Values

ValueCountFrequency (%)
p0102 16
12.2%
p0198 15
11.5%
p0036 12
 
9.2%
p0148 11
 
8.4%
p0243 10
 
7.6%
p0099 8
 
6.1%
p0119 8
 
6.1%
p0205 8
 
6.1%
p0309 3
 
2.3%
p0056 3
 
2.3%
Other values (26) 37
28.2%

Length

2024-05-10T23:34:45.468444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
p0102 16
12.2%
p0198 15
11.5%
p0036 12
 
9.2%
p0148 11
 
8.4%
p0243 10
 
7.6%
p0099 8
 
6.1%
p0119 8
 
6.1%
p0205 8
 
6.1%
p0309 3
 
2.3%
p0056 3
 
2.3%
Other values (26) 37
28.2%

Interactions

2024-05-10T23:34:32.188908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:29.516810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:30.506382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:31.275966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:32.438113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:29.773196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:30.715533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:31.443189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:32.706256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:30.036896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:30.959392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:31.679588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:33.031356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:30.300008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:31.116401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:34:31.933733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T23:34:45.733163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id종명학명과명서울시보호멸종위기1멸종위기2고유종포획금지종자치구조사지역조사연도참고문헌x_valuey_value특이종범례조사시점
객체id1.0000.2150.1060.1920.0000.0000.1180.0000.0850.8850.9710.4330.7470.7520.8050.0000.971
종명0.2151.0001.0001.0001.0001.0001.0001.0001.0000.0000.0000.2830.2790.0000.4681.0000.000
학명0.1061.0001.0001.0001.0001.0001.0001.0001.0000.0000.0000.4020.0000.0000.0001.0000.000
과명0.1921.0001.0001.0000.9990.6351.0001.0001.0000.0000.0000.3540.4650.1900.3210.9540.000
서울시보호0.0001.0001.0000.9991.0000.0000.5360.9570.4780.0000.0000.2180.0000.0000.0001.0000.000
멸종위기10.0001.0001.0000.6350.0001.0000.0000.0000.0000.0000.0000.0950.0000.0000.0001.0000.000
멸종위기20.1181.0001.0001.0000.5360.0001.0000.0000.0910.0000.0000.3260.6580.1900.0001.0000.000
고유종0.0001.0001.0001.0000.9570.0000.0001.0000.3930.0000.0000.0590.0000.0610.0901.0000.000
포획금지종0.0851.0001.0001.0000.4780.0000.0910.3931.0000.1880.0000.0920.3340.0000.2640.4700.000
자치구0.8850.0000.0000.0000.0000.0000.0000.0000.1881.0001.0000.8510.9720.9810.9750.0001.000
조사지역0.9710.0000.0000.0000.0000.0000.0000.0000.0001.0001.0000.9250.9831.0001.0000.0001.000
조사연도0.4330.2830.4020.3540.2180.0950.3260.0590.0920.8510.9251.0000.9840.7050.5930.3090.925
참고문헌0.7470.2790.0000.4650.0000.0000.6580.0000.3340.9720.9830.9841.0000.8910.8920.3490.983
x_value0.7520.0000.0000.1900.0000.0000.1900.0610.0000.9811.0000.7050.8911.0000.8190.0001.000
y_value0.8050.4680.0000.3210.0000.0000.0000.0900.2640.9751.0000.5930.8920.8191.0000.0001.000
특이종범례0.0001.0001.0000.9541.0001.0001.0001.0000.4700.0000.0000.3090.3490.0000.0001.0000.000
조사시점0.9710.0000.0000.0000.0000.0000.0000.0000.0001.0001.0000.9250.9831.0001.0000.0001.000
2024-05-10T23:34:46.139222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조사지역과명종명멸종위기1포획금지종자치구학명고유종서울시보호조사시점특이종범례멸종위기2참고문헌
조사지역1.0000.0000.0000.0000.0000.9340.0000.0000.0001.0000.0000.0000.729
과명0.0001.0000.9920.4550.9840.0000.9120.9840.9650.0000.8520.9840.215
종명0.0000.9921.0000.9760.9760.0000.9200.9760.9760.0000.9840.9760.104
멸종위기10.0000.4550.9761.0000.0000.0000.8980.0000.0000.0000.9920.0000.000
포획금지종0.0000.9840.9760.0001.0000.1320.8980.2570.3170.0000.3150.0580.241
자치구0.9340.0000.0000.0000.1321.0000.0000.0000.0000.9340.0000.0000.588
학명0.0000.9120.9200.8980.8980.0001.0000.8980.8980.0000.9050.8980.000
고유종0.0000.9840.9760.0000.2570.0000.8981.0000.8120.0000.9920.0000.000
서울시보호0.0000.9650.9760.0000.3170.0000.8980.8121.0000.0000.9920.3600.000
조사시점1.0000.0000.0000.0000.0000.9340.0000.0000.0001.0000.0000.0000.729
특이종범례0.0000.8520.9840.9920.3150.0000.9050.9920.9920.0001.0000.9920.175
멸종위기20.0000.9840.9760.0000.0580.0000.8980.0000.3600.0000.9921.0000.485
참고문헌0.7290.2150.1040.0000.2410.5880.0000.0000.0000.7290.1750.4851.000
2024-05-10T23:34:46.552696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id조사연도x_valuey_value종명학명과명서울시보호멸종위기1멸종위기2고유종포획금지종자치구조사지역참고문헌특이종범례조사시점
객체id1.0000.0720.5410.2730.1260.0000.1250.0000.0000.1430.0000.0730.6370.7370.4560.0000.737
조사연도0.0721.000-0.1630.1100.1480.0920.1700.1800.1220.3300.0000.0000.5130.5480.8660.2000.548
x_value0.541-0.1631.0000.2200.0000.0000.0720.0000.0000.1640.0000.0000.8510.8820.5970.0000.882
y_value0.2730.1100.2201.0000.1850.0270.1680.0000.0000.0000.0000.1630.8520.8820.5640.0000.882
종명0.1260.1480.0000.1851.0000.9200.9920.9760.9760.9760.9760.9760.0000.0000.1040.9840.000
학명0.0000.0920.0000.0270.9201.0000.9120.8980.8980.8980.8980.8980.0000.0000.0000.9050.000
과명0.1250.1700.0720.1680.9920.9121.0000.9650.4550.9840.9840.9840.0000.0000.2150.8520.000
서울시보호0.0000.1800.0000.0000.9760.8980.9651.0000.0000.3600.8120.3170.0000.0000.0000.9920.000
멸종위기10.0000.1220.0000.0000.9760.8980.4550.0001.0000.0000.0000.0000.0000.0000.0000.9920.000
멸종위기20.1430.3300.1640.0000.9760.8980.9840.3600.0001.0000.0000.0580.0000.0000.4850.9920.000
고유종0.0000.0000.0000.0000.9760.8980.9840.8120.0000.0001.0000.2570.0000.0000.0000.9920.000
포획금지종0.0730.0000.0000.1630.9760.8980.9840.3170.0000.0580.2571.0000.1320.0000.2410.3150.000
자치구0.6370.5130.8510.8520.0000.0000.0000.0000.0000.0000.0000.1321.0000.9340.5880.0000.934
조사지역0.7370.5480.8820.8820.0000.0000.0000.0000.0000.0000.0000.0000.9341.0000.7290.0001.000
참고문헌0.4560.8660.5970.5640.1040.0000.2150.0000.0000.4850.0000.2410.5880.7291.0000.1750.729
특이종범례0.0000.2000.0000.0000.9840.9050.8520.9920.9920.9920.9920.3150.0000.0000.1751.0000.000
조사시점0.7370.5480.8820.8820.0000.0000.0000.0000.0000.0000.0000.0000.9341.0000.7290.0001.000

Missing values

2024-05-10T23:34:33.700755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T23:34:34.612813image/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

객체id종명학명과명서울시보호멸종위기1멸종위기2천연기념물고유종유해종포획금지종자치구조사지역조사연도조사출처참고문헌x_valuey_value특이종범례조사시점
010359다람쥐Tamias sibiricus (Laxmannm, 1769)다람쥐과1000000서대문구안산2009문헌조사서울시 도시숲 산림 건강성 및 생물다양성 학술연구195050.8452755.2서울시보호종p0157
110360다람쥐Tamias sibiricus (Laxmannm, 1769)다람쥐과1000000영등포구, 강서구, 구로구, 양천구, 금천구안양천2007문헌조사2007년 한강생태계 조사189443.6447227.4서울시보호종p0158
210361족제비Mustela sibirica (Pallas, 1773)족제비과1000001강남구양재천~탄천 합류부2003문헌조사양재천 자연형 하천 조성사례206409.8444405.0서울시보호종p0168
310362족제비Mustela sibirica (Pallas, 1773)족제비과1000001강남구양재천~탄천 합류부2004문헌조사탄천 생태계 보전지역 생태변화관찰 및 관리대책206409.8444405.0서울시보호종p0168
410363족제비Mustela sibirica (Pallas, 1773)족제비과1000001영등포구여의샛강2007문헌조사2007년 한강생태계 조사192687.5446182.8서울시보호종p0175
510364족제비Mustela sibirica (Pallas, 1773)족제비과1000001강남구영동 4~5교 구간2003문헌조사양재천 자연형 하천 조성사례205365.3443025.1서울시보호종p0177
610365멧토끼Lepus coreanus (Thomas, 1906)토끼과0000100구로구와룡산2009문헌조사서울시 도시숲 산림 건강성 및 생물다양성 학술연구184046.633443673.823고유종p0309
710366족제비Mustela sibirica (Pallas, 1773)족제비과1000001구로구와룡산2009문헌조사서울시 도시숲 산림 건강성 및 생물다양성 학술연구184046.633443673.823서울시보호종p0309
810367다람쥐Tamias sibiricus (Laxmannm, 1769)다람쥐과1000000구로구와룡산2009문헌조사서울시 도시숲 산림 건강성 및 생물다양성 학술연구184046.633443673.823서울시보호종p0309
910368고슴도치Erinaceus amurensis (Schrenk, 1859)고슴도치과1000000마포구월드컵공원2003문헌조사월드컵공원 자연생태계 모니터링 및 관리방안190107.9451442.6서울시보호종p0198
객체id종명학명과명서울시보호멸종위기1멸종위기2천연기념물고유종유해종포획금지종자치구조사지역조사연도조사출처참고문헌x_valuey_value특이종범례조사시점
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12210673다람쥐Tamias sibiricus (Laxmannm, 1769)다람쥐과1000000노원구수락산2004문헌조사공원녹지의 효과적인 연결을 위한 기본계획206693.8465056.8서울시보호종p0148
12310674멧토끼Lepus coreanus (Thomas, 1908)토끼과0000100노원구수락산2010문헌조사서울시 도시숲(산림) 생태계 조사 학술 연구206693.8465056.8고유종p0148
12410675오소리Meles leucurus (Hodgson, 1847)족제비과1000001노원구수락산2010문헌조사서울시 도시숲(산림) 생태계 조사 학술 연구206693.8465056.8서울시보호종p0148
12510676족제비Mustela sibirica (Pallas, 1773)족제비과1000001노원구수락산2010문헌조사서울시 도시숲(산림) 생태계 조사 학술 연구206693.8465056.8서울시보호종p0148
12610677삵Prionailurus bengalensis (Kerr, 1792)고양이과0010000노원구수락산2010문헌조사서울시 도시숲(산림) 생태계 조사 학술 연구206693.8465056.8멸종위기종2급p0148
12710678다람쥐Tamias sibiricus (Laxmannm, 1769)다람쥐과1000000노원구수락산2010문헌조사서울시 도시숲(산림) 생태계 조사 학술 연구206693.8465056.8서울시보호종p0148
12810679다람쥐Tamias sibiricus (Laxmannm, 1769)다람쥐과1000000광진구아차산1997문헌조사산림생태계조사 연구보고서208666.8451908.9서울시보호종p0154
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