Overview

Dataset statistics

Number of variables23
Number of observations6858
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory196.0 B

Variable types

Numeric5
Text6
Categorical12

Dataset

Description객체id,조사지점,종명,학명,과명,우점도,우점종여부,서울시보호,멸종위기1,멸종위기2,천연기념물,고유종,서식형태,영소길드,채이길드,유형화,자치구명,조사지역,조사연도,조사출처,참고문헌,x_value,y_value
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21158/S/1/datasetView.do

Alerts

고유종 has constant value ""Constant
멸종위기1 is highly imbalanced (98.4%)Imbalance
멸종위기2 is highly imbalanced (84.4%)Imbalance
천연기념물 is highly imbalanced (78.7%)Imbalance
객체id has unique valuesUnique

Reproduction

Analysis started2024-05-11 09:36:35.996729
Analysis finished2024-05-11 09:36:38.020702
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

객체id
Real number (ℝ)

UNIQUE 

Distinct6858
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean248857.19
Minimum245253
Maximum252286
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.4 KiB
2024-05-11T09:36:38.221661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum245253
5-th percentile245771.85
Q1247143.25
median248857.5
Q3250571.75
95-th percentile251943.15
Maximum252286
Range7033
Interquartile range (IQR)3428.5

Descriptive statistics

Standard deviation1980.4245
Coefficient of variation (CV)0.0079580762
Kurtosis-1.1985152
Mean248857.19
Median Absolute Deviation (MAD)1714.5
Skewness-0.0010005438
Sum1.7066626 × 109
Variance3922081.2
MonotonicityStrictly increasing
2024-05-11T09:36:38.677355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
245253 1
 
< 0.1%
250010 1
 
< 0.1%
250008 1
 
< 0.1%
250007 1
 
< 0.1%
250006 1
 
< 0.1%
250005 1
 
< 0.1%
250004 1
 
< 0.1%
250003 1
 
< 0.1%
250002 1
 
< 0.1%
250001 1
 
< 0.1%
Other values (6848) 6848
99.9%
ValueCountFrequency (%)
245253 1
< 0.1%
245254 1
< 0.1%
245255 1
< 0.1%
245256 1
< 0.1%
245257 1
< 0.1%
245258 1
< 0.1%
245259 1
< 0.1%
245260 1
< 0.1%
245261 1
< 0.1%
245262 1
< 0.1%
ValueCountFrequency (%)
252286 1
< 0.1%
252285 1
< 0.1%
252284 1
< 0.1%
252283 1
< 0.1%
252282 1
< 0.1%
252281 1
< 0.1%
252280 1
< 0.1%
252279 1
< 0.1%
252278 1
< 0.1%
252277 1
< 0.1%

조사지점
Real number (ℝ)

Distinct256
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.144649
Minimum1
Maximum256
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.4 KiB
2024-05-11T09:36:39.228891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11
Q128
median66
Q3134
95-th percentile233.15
Maximum256
Range255
Interquartile range (IQR)106

Descriptive statistics

Standard deviation67.511841
Coefficient of variation (CV)0.77471012
Kurtosis-0.33847758
Mean87.144649
Median Absolute Deviation (MAD)41
Skewness0.85476325
Sum597638
Variance4557.8487
MonotonicityNot monotonic
2024-05-11T09:36:39.686411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 576
 
8.4%
56 476
 
6.9%
73 298
 
4.3%
71 176
 
2.6%
61 170
 
2.5%
75 159
 
2.3%
13 148
 
2.2%
20 121
 
1.8%
23 115
 
1.7%
22 114
 
1.7%
Other values (246) 4505
65.7%
ValueCountFrequency (%)
1 31
 
0.5%
2 1
 
< 0.1%
3 15
 
0.2%
4 107
1.6%
5 45
0.7%
6 8
 
0.1%
7 56
0.8%
8 1
 
< 0.1%
9 4
 
0.1%
10 16
 
0.2%
ValueCountFrequency (%)
256 5
 
0.1%
255 9
 
0.1%
254 33
0.5%
253 31
0.5%
252 6
 
0.1%
251 5
 
0.1%
250 14
0.2%
249 6
 
0.1%
248 3
 
< 0.1%
247 5
 
0.1%

종명
Text

Distinct223
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
2024-05-11T09:36:40.326147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.6252552
Min length1

Characters and Unicode

Total characters24862
Distinct characters184
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

Unique23 ?
Unique (%)0.3%

Sample

1st row진박새
2nd row진박새
3rd row진박새
4th row노랑할미새
5th row노랑할미새
ValueCountFrequency (%)
직박구리 434
 
6.3%
까치 433
 
6.3%
참새 431
 
6.3%
박새 347
 
5.1%
멧비둘기 281
 
4.1%
쇠박새 217
 
3.2%
붉은머리오목눈이 182
 
2.7%
꾀꼬리 160
 
2.3%
꿩 136
 
2.0%
집비둘기 134
 
2.0%
Other values (213) 4103
59.8%
2024-05-11T09:36:41.357718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
새 2359
 
9.5%
리 2048
 
8.2%
박 1149
 
4.6%
기 869
 
3.5%
구 804
 
3.2%
오 788
 
3.2%
까 667
 
2.7%
치 630
 
2.5%
비 624
 
2.5%
딱 572
 
2.3%
Other values (174) 14352
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24862
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
새 2359
 
9.5%
리 2048
 
8.2%
박 1149
 
4.6%
기 869
 
3.5%
구 804
 
3.2%
오 788
 
3.2%
까 667
 
2.7%
치 630
 
2.5%
비 624
 
2.5%
딱 572
 
2.3%
Other values (174) 14352
57.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24862
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
새 2359
 
9.5%
리 2048
 
8.2%
박 1149
 
4.6%
기 869
 
3.5%
구 804
 
3.2%
오 788
 
3.2%
까 667
 
2.7%
치 630
 
2.5%
비 624
 
2.5%
딱 572
 
2.3%
Other values (174) 14352
57.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24862
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
새 2359
 
9.5%
리 2048
 
8.2%
박 1149
 
4.6%
기 869
 
3.5%
구 804
 
3.2%
오 788
 
3.2%
까 667
 
2.7%
치 630
 
2.5%
비 624
 
2.5%
딱 572
 
2.3%
Other values (174) 14352
57.7%

학명
Text

Distinct223
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
2024-05-11T09:36:42.252168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length34.574366
Min length13

Characters and Unicode

Total characters237111
Distinct characters67
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.3%

Sample

1st rowParus ater (Linnaeus, 1758)
2nd rowParus ater (Linnaeus, 1758)
3rd rowParus ater (Linnaeus, 1758)
4th rowMotacilla cinerea (Tunstall, 1771)
5th rowMotacilla cinerea (Tunstall, 1771)
ValueCountFrequency (%)
linnaeus 3639
 
13.2%
1758 3331
 
12.1%
temminck 1066
 
3.9%
pica 866
 
3.1%
parus 709
 
2.6%
major 466
 
1.7%
1830 450
 
1.6%
amaurotis 434
 
1.6%
microscelis 434
 
1.6%
montanus 431
 
1.6%
Other values (409) 15701
57.0%
2024-05-11T09:36:43.589990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33152
 
14.0%
a 17834
 
7.5%
s 15323
 
6.5%
i 14258
 
6.0%
n 14009
 
5.9%
u 12111
 
5.1%
e 11780
 
5.0%
r 9245
 
3.9%
o 8422
 
3.6%
c 7751
 
3.3%
Other values (57) 93226
39.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 143418
60.5%
Space Separator 33152
 
14.0%
Decimal Number 26544
 
11.2%
Uppercase Letter 13781
 
5.8%
Other Punctuation 6930
 
2.9%
Close Punctuation 6643
 
2.8%
Open Punctuation 6643
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 17834
12.4%
s 15323
10.7%
i 14258
9.9%
n 14009
9.8%
u 12111
8.4%
e 11780
8.2%
r 9245
 
6.4%
o 8422
 
5.9%
c 7751
 
5.4%
l 7172
 
5.0%
Other values (16) 25513
17.8%
Uppercase Letter
ValueCountFrequency (%)
L 4191
30.4%
P 2763
20.0%
T 1396
 
10.1%
S 807
 
5.9%
A 777
 
5.6%
C 648
 
4.7%
M 633
 
4.6%
G 552
 
4.0%
E 383
 
2.8%
F 316
 
2.3%
Other values (13) 1315
 
9.5%
Decimal Number
ValueCountFrequency (%)
1 7053
26.6%
8 5774
21.8%
7 5321
20.0%
5 3719
14.0%
6 1420
 
5.3%
3 1097
 
4.1%
0 851
 
3.2%
2 486
 
1.8%
9 444
 
1.7%
4 379
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 6636
95.8%
& 247
 
3.6%
. 47
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 6637
99.9%
] 6
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 6637
99.9%
[ 6
 
0.1%
Space Separator
ValueCountFrequency (%)
33152
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 157199
66.3%
Common 79912
33.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 17834
11.3%
s 15323
 
9.7%
i 14258
 
9.1%
n 14009
 
8.9%
u 12111
 
7.7%
e 11780
 
7.5%
r 9245
 
5.9%
o 8422
 
5.4%
c 7751
 
4.9%
l 7172
 
4.6%
Other values (39) 39294
25.0%
Common
ValueCountFrequency (%)
33152
41.5%
1 7053
 
8.8%
) 6637
 
8.3%
( 6637
 
8.3%
, 6636
 
8.3%
8 5774
 
7.2%
7 5321
 
6.7%
5 3719
 
4.7%
6 1420
 
1.8%
3 1097
 
1.4%
Other values (8) 2466
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 237111
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33152
 
14.0%
a 17834
 
7.5%
s 15323
 
6.5%
i 14258
 
6.0%
n 14009
 
5.9%
u 12111
 
5.1%
e 11780
 
5.0%
r 9245
 
3.9%
o 8422
 
3.6%
c 7751
 
3.3%
Other values (57) 93226
39.3%

과명
Text

Distinct51
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
2024-05-11T09:36:44.358201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.8499563
Min length2

Characters and Unicode

Total characters26403
Distinct characters86
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st row박새과
2nd row박새과
3rd row박새과
4th row할미새과
5th row할미새과
ValueCountFrequency (%)
까마귀과 717
 
10.5%
박새과 709
 
10.3%
비둘기과 444
 
6.5%
참새과 439
 
6.4%
직박구리과 434
 
6.3%
오리과 399
 
5.8%
딱다구리과 361
 
5.3%
백로과 307
 
4.5%
지빠귀과 302
 
4.4%
딱새과 280
 
4.1%
Other values (41) 2466
36.0%
2024-05-11T09:36:45.583381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 6858
26.0%
새 2376
 
9.0%
리 1791
 
6.8%
박 1149
 
4.4%
귀 1026
 
3.9%
구 795
 
3.0%
까 775
 
2.9%
마 757
 
2.9%
오 664
 
2.5%
딱 641
 
2.4%
Other values (76) 9571
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26403
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 6858
26.0%
새 2376
 
9.0%
리 1791
 
6.8%
박 1149
 
4.4%
귀 1026
 
3.9%
구 795
 
3.0%
까 775
 
2.9%
마 757
 
2.9%
오 664
 
2.5%
딱 641
 
2.4%
Other values (76) 9571
36.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26403
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 6858
26.0%
새 2376
 
9.0%
리 1791
 
6.8%
박 1149
 
4.4%
귀 1026
 
3.9%
구 795
 
3.0%
까 775
 
2.9%
마 757
 
2.9%
오 664
 
2.5%
딱 641
 
2.4%
Other values (76) 9571
36.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26403
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 6858
26.0%
새 2376
 
9.0%
리 1791
 
6.8%
박 1149
 
4.4%
귀 1026
 
3.9%
구 795
 
3.0%
까 775
 
2.9%
마 757
 
2.9%
오 664
 
2.5%
딱 641
 
2.4%
Other values (76) 9571
36.2%

우점도
Text

Distinct211
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
2024-05-11T09:36:46.526111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length2.6552931
Min length1

Characters and Unicode

Total characters18210
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)0.8%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
30.597723 188
 
7.3%
11.005693 127
 
4.9%
7.969639 105
 
4.1%
8.444023 103
 
4.0%
4 77
 
3.0%
3 68
 
2.6%
2.466793 68
 
2.6%
10 65
 
2.5%
2 64
 
2.5%
6 64
 
2.5%
Other values (200) 1641
63.9%
2024-05-11T09:36:47.933517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4288
23.5%
3 2019
11.1%
. 1479
 
8.1%
0 1465
 
8.0%
1 1388
 
7.6%
6 1306
 
7.2%
2 1200
 
6.6%
7 1115
 
6.1%
9 1110
 
6.1%
5 1104
 
6.1%
Other values (2) 1736
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12443
68.3%
Space Separator 4288
 
23.5%
Other Punctuation 1479
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2019
16.2%
0 1465
11.8%
1 1388
11.2%
6 1306
10.5%
2 1200
9.6%
7 1115
9.0%
9 1110
8.9%
5 1104
8.9%
4 1023
8.2%
8 713
 
5.7%
Space Separator
ValueCountFrequency (%)
4288
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1479
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18210
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4288
23.5%
3 2019
11.1%
. 1479
 
8.1%
0 1465
 
8.0%
1 1388
 
7.6%
6 1306
 
7.2%
2 1200
 
6.6%
7 1115
 
6.1%
9 1110
 
6.1%
5 1104
 
6.1%
Other values (2) 1736
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18210
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4288
23.5%
3 2019
11.1%
. 1479
 
8.1%
0 1465
 
8.0%
1 1388
 
7.6%
6 1306
 
7.2%
2 1200
 
6.6%
7 1115
 
6.1%
9 1110
 
6.1%
5 1104
 
6.1%
Other values (2) 1736
9.5%

우점종여부
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
0
6036 
1
822 

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 6036
88.0%
1 822
 
12.0%

Length

2024-05-11T09:36:48.498926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:36:48.855488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6036
88.0%
1 822
 
12.0%

서울시보호
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
0
5848 
1
1010 

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 5848
85.3%
1 1010
 
14.7%

Length

2024-05-11T09:36:49.420566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:36:49.827875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5848
85.3%
1 1010
 
14.7%

멸종위기1
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
0
6848 
1
 
10

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 6848
99.9%
1 10
 
0.1%

Length

2024-05-11T09:36:50.459943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:36:51.060995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6848
99.9%
1 10
 
0.1%

멸종위기2
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
0
6703 
1
 
155

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 6703
97.7%
1 155
 
2.3%

Length

2024-05-11T09:36:51.674726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:36:52.247905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6703
97.7%
1 155
 
2.3%

천연기념물
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
0
6626 
1
 
232

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 6626
96.6%
1 232
 
3.4%

Length

2024-05-11T09:36:52.847709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:36:53.210814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6626
96.6%
1 232
 
3.4%

고유종
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
0
6858 

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 6858
100.0%

Length

2024-05-11T09:36:53.642787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:36:53.991199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6858
100.0%

서식형태
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
텃새
4238 
여름철새
1360 
겨울철새
886 
나그네새
 
366
길잃은새
 
8

Length

Max length4
Median length2
Mean length2.7640712
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row텃새
2nd row텃새
3rd row텃새
4th row여름철새
5th row여름철새

Common Values

ValueCountFrequency (%)
텃새 4238
61.8%
여름철새 1360
 
19.8%
겨울철새 886
 
12.9%
나그네새 366
 
5.3%
길잃은새 8
 
0.1%

Length

2024-05-11T09:36:54.373815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:36:54.789310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
텃새 4238
61.8%
여름철새 1360
 
19.8%
겨울철새 886
 
12.9%
나그네새 366
 
5.3%
길잃은새 8
 
0.1%

영소길드
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
수관층
2469 
나무구멍
1202 
관목층
955 
수변
818 
가장자리
744 

Length

Max length4
Median length3
Mean length3.0667833
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row나무구멍
2nd row나무구멍
3rd row나무구멍
4th row수변
5th row수변

Common Values

ValueCountFrequency (%)
수관층 2469
36.0%
나무구멍 1202
17.5%
관목층 955
 
13.9%
수변 818
 
11.9%
가장자리 744
 
10.8%
기타 670
 
9.8%

Length

2024-05-11T09:36:55.213474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:36:55.607546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수관층 2469
36.0%
나무구멍 1202
17.5%
관목층 955
 
13.9%
수변 818
 
11.9%
가장자리 744
 
10.8%
기타 670
 
9.8%

채이길드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
수관층
2367 
임연부
2024 
관목층
1049 
수면
800 
기타
618 

Length

Max length3
Median length3
Mean length2.7932342
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수관층
2nd row수관층
3rd row수관층
4th row수면
5th row수면

Common Values

ValueCountFrequency (%)
수관층 2367
34.5%
임연부 2024
29.5%
관목층 1049
15.3%
수면 800
 
11.7%
기타 618
 
9.0%

Length

2024-05-11T09:36:56.061505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:36:56.380839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수관층 2367
34.5%
임연부 2024
29.5%
관목층 1049
15.3%
수면 800
 
11.7%
기타 618
 
9.0%

유형화
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
4
2413 
3
1713 
1
1536 
2
1025 
5
 
171

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row1
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 2413
35.2%
3 1713
25.0%
1 1536
22.4%
2 1025
14.9%
5 171
 
2.5%

Length

2024-05-11T09:36:56.701695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:36:57.016718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 2413
35.2%
3 1713
25.0%
1 1536
22.4%
2 1025
14.9%
5 171
 
2.5%

자치구명
Categorical

Distinct25
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
강북구
719 
마포구
597 
강남구
540 
강동구
500 
종로구
427 
Other values (20)
4075 

Length

Max length4
Median length3
Mean length3.0558472
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관악구
2nd row마포구
3rd row중구
4th row용산구
5th row용산구

Common Values

ValueCountFrequency (%)
강북구 719
 
10.5%
마포구 597
 
8.7%
강남구 540
 
7.9%
강동구 500
 
7.3%
종로구 427
 
6.2%
용산구 419
 
6.1%
서초구 391
 
5.7%
노원구 374
 
5.5%
영등포구 369
 
5.4%
중랑구 339
 
4.9%
Other values (15) 2183
31.8%

Length

2024-05-11T09:36:57.416288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강북구 719
 
10.5%
마포구 597
 
8.7%
강남구 540
 
7.9%
강동구 500
 
7.3%
종로구 427
 
6.2%
용산구 419
 
6.1%
서초구 391
 
5.7%
노원구 374
 
5.5%
영등포구 369
 
5.4%
중랑구 339
 
4.9%
Other values (15) 2183
31.8%

조사지역
Text

Distinct274
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
2024-05-11T09:36:58.010302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length6.7818606
Min length2

Characters and Unicode

Total characters46510
Distinct characters282
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

Unique11 ?
Unique (%)0.2%

Sample

1st row관악산
2nd row난지도 월드컵공원
3rd row남산
4th row한강
5th row한강
ValueCountFrequency (%)
생태경관보전지역 831
 
7.9%
북한산 576
 
5.5%
월드컵공원 545
 
5.2%
한강 319
 
3.0%
산림 211
 
2.0%
인근 201
 
1.9%
중랑천 194
 
1.8%
산림지역 183
 
1.7%
탄천 176
 
1.7%
방이동 168
 
1.6%
Other values (350) 7088
67.6%
2024-05-11T09:36:59.037573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3634
 
7.8%
산 2760
 
5.9%
원 2191
 
4.7%
공 1886
 
4.1%
지 1612
 
3.5%
역 1188
 
2.6%
관 1109
 
2.4%
생 1083
 
2.3%
동 1078
 
2.3%
태 1070
 
2.3%
Other values (272) 28899
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41748
89.8%
Space Separator 3634
 
7.8%
Decimal Number 896
 
1.9%
Math Symbol 102
 
0.2%
Uppercase Letter 46
 
0.1%
Open Punctuation 32
 
0.1%
Close Punctuation 32
 
0.1%
Other Punctuation 16
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 2760
 
6.6%
원 2191
 
5.2%
공 1886
 
4.5%
지 1612
 
3.9%
역 1188
 
2.8%
관 1109
 
2.7%
생 1083
 
2.6%
동 1078
 
2.6%
태 1070
 
2.6%
경 1060
 
2.5%
Other values (253) 26711
64.0%
Decimal Number
ValueCountFrequency (%)
1 373
41.6%
2 264
29.5%
3 158
17.6%
4 84
 
9.4%
5 10
 
1.1%
6 7
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
T 10
21.7%
P 10
21.7%
A 10
21.7%
C 8
17.4%
I 8
17.4%
Other Punctuation
ValueCountFrequency (%)
. 8
50.0%
/ 8
50.0%
Lowercase Letter
ValueCountFrequency (%)
s 2
50.0%
k 2
50.0%
Space Separator
ValueCountFrequency (%)
3634
100.0%
Math Symbol
ValueCountFrequency (%)
~ 102
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41748
89.8%
Common 4712
 
10.1%
Latin 50
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 2760
 
6.6%
원 2191
 
5.2%
공 1886
 
4.5%
지 1612
 
3.9%
역 1188
 
2.8%
관 1109
 
2.7%
생 1083
 
2.6%
동 1078
 
2.6%
태 1070
 
2.6%
경 1060
 
2.5%
Other values (253) 26711
64.0%
Common
ValueCountFrequency (%)
3634
77.1%
1 373
 
7.9%
2 264
 
5.6%
3 158
 
3.4%
~ 102
 
2.2%
4 84
 
1.8%
( 32
 
0.7%
) 32
 
0.7%
5 10
 
0.2%
. 8
 
0.2%
Other values (2) 15
 
0.3%
Latin
ValueCountFrequency (%)
T 10
20.0%
P 10
20.0%
A 10
20.0%
C 8
16.0%
I 8
16.0%
s 2
 
4.0%
k 2
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41748
89.8%
ASCII 4762
 
10.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3634
76.3%
1 373
 
7.8%
2 264
 
5.5%
3 158
 
3.3%
~ 102
 
2.1%
4 84
 
1.8%
( 32
 
0.7%
) 32
 
0.7%
T 10
 
0.2%
P 10
 
0.2%
Other values (9) 63
 
1.3%
Hangul
ValueCountFrequency (%)
산 2760
 
6.6%
원 2191
 
5.2%
공 1886
 
4.5%
지 1612
 
3.9%
역 1188
 
2.8%
관 1109
 
2.7%
생 1083
 
2.6%
동 1078
 
2.6%
태 1070
 
2.6%
경 1060
 
2.5%
Other values (253) 26711
64.0%

조사연도
Real number (ℝ)

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2007.8393
Minimum2000
Maximum2014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.4 KiB
2024-05-11T09:36:59.511324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2001
Q12004
median2009
Q32012
95-th percentile2014
Maximum2014
Range14
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.0500536
Coefficient of variation (CV)0.0020171204
Kurtosis-1.141161
Mean2007.8393
Median Absolute Deviation (MAD)4
Skewness-0.06889676
Sum13769762
Variance16.402934
MonotonicityNot monotonic
2024-05-11T09:36:59.883900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2009 1519
22.1%
2013 996
14.5%
2004 677
9.9%
2005 564
 
8.2%
2014 534
 
7.8%
2001 515
 
7.5%
2003 468
 
6.8%
2007 421
 
6.1%
2008 235
 
3.4%
2006 230
 
3.4%
Other values (5) 699
10.2%
ValueCountFrequency (%)
2000 33
 
0.5%
2001 515
 
7.5%
2002 151
 
2.2%
2003 468
 
6.8%
2004 677
9.9%
2005 564
 
8.2%
2006 230
 
3.4%
2007 421
 
6.1%
2008 235
 
3.4%
2009 1519
22.1%
ValueCountFrequency (%)
2014 534
 
7.8%
2013 996
14.5%
2012 206
 
3.0%
2011 149
 
2.2%
2010 160
 
2.3%
2009 1519
22.1%
2008 235
 
3.4%
2007 421
 
6.1%
2006 230
 
3.4%
2005 564
 
8.2%

조사출처
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
문헌조사
4288 
현장조사
2570 

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 4288
62.5%
현장조사 2570
37.5%

Length

2024-05-11T09:37:00.312979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:37:00.783844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문헌조사 4288
62.5%
현장조사 2570
37.5%

참고문헌
Text

Distinct51
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size53.7 KiB
2024-05-11T09:37:01.381728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length34
Mean length13.505395
Min length1

Characters and Unicode

Total characters92620
Distinct characters150
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울시 도시숲(산림) 생태계 조사 학술 연구
2nd row월드컵공원 자연생태계 모니터링 및 관리방안
3rd row남산공원 소나무림에 대한 생태상 모니터링 및 관리방안
4th row2007년 한강생태계 조사
5th row제7차 한강 생태계 조사연구
ValueCountFrequency (%)
및 1203
 
6.0%
모니터링 1140
 
5.7%
서울시 771
 
3.8%
연구 738
 
3.7%
생태경관보전지역 680
 
3.4%
생태계 669
 
3.3%
자연생태계 574
 
2.9%
월드컵공원 545
 
2.7%
북한산 540
 
2.7%
관리계획 517
 
2.6%
Other values (110) 12685
63.2%
2024-05-11T09:37:02.611306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18344
 
19.8%
생 3825
 
4.1%
태 3545
 
3.8%
계 3128
 
3.4%
연 2635
 
2.8%
관 2609
 
2.8%
원 2461
 
2.7%
공 1783
 
1.9%
지 1709
 
1.8%
구 1601
 
1.7%
Other values (140) 50980
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72534
78.3%
Space Separator 18344
 
19.8%
Decimal Number 1167
 
1.3%
Other Punctuation 223
 
0.2%
Close Punctuation 176
 
0.2%
Open Punctuation 176
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
생 3825
 
5.3%
태 3545
 
4.9%
계 3128
 
4.3%
연 2635
 
3.6%
관 2609
 
3.6%
원 2461
 
3.4%
공 1783
 
2.5%
지 1709
 
2.4%
구 1601
 
2.2%
조 1581
 
2.2%
Other values (132) 47657
65.7%
Decimal Number
ValueCountFrequency (%)
0 530
45.4%
7 372
31.9%
2 265
22.7%
Other Punctuation
ValueCountFrequency (%)
: 113
50.7%
? 110
49.3%
Space Separator
ValueCountFrequency (%)
18344
100.0%
Close Punctuation
ValueCountFrequency (%)
) 176
100.0%
Open Punctuation
ValueCountFrequency (%)
( 176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72534
78.3%
Common 20086
 
21.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
생 3825
 
5.3%
태 3545
 
4.9%
계 3128
 
4.3%
연 2635
 
3.6%
관 2609
 
3.6%
원 2461
 
3.4%
공 1783
 
2.5%
지 1709
 
2.4%
구 1601
 
2.2%
조 1581
 
2.2%
Other values (132) 47657
65.7%
Common
ValueCountFrequency (%)
18344
91.3%
0 530
 
2.6%
7 372
 
1.9%
2 265
 
1.3%
) 176
 
0.9%
( 176
 
0.9%
: 113
 
0.6%
? 110
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72534
78.3%
ASCII 20086
 
21.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18344
91.3%
0 530
 
2.6%
7 372
 
1.9%
2 265
 
1.3%
) 176
 
0.9%
( 176
 
0.9%
: 113
 
0.6%
? 110
 
0.5%
Hangul
ValueCountFrequency (%)
생 3825
 
5.3%
태 3545
 
4.9%
계 3128
 
4.3%
연 2635
 
3.6%
관 2609
 
3.6%
원 2461
 
3.4%
공 1783
 
2.5%
지 1709
 
2.4%
구 1601
 
2.2%
조 1581
 
2.2%
Other values (132) 47657
65.7%

x_value
Real number (ℝ)

Distinct260
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200418.12
Minimum182514.7
Maximum215620.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.4 KiB
2024-05-11T09:37:03.011694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182514.7
5-th percentile189165.04
Q1194604.32
median199375
Q3206758.05
95-th percentile212622.66
Maximum215620.86
Range33106.16
Interquartile range (IQR)12153.729

Descriptive statistics

Standard deviation7665.6268
Coefficient of variation (CV)0.038248173
Kurtosis-0.70880227
Mean200418.12
Median Absolute Deviation (MAD)6516.23
Skewness-0.19740066
Sum1.3744674 × 109
Variance58761835
MonotonicityNot monotonic
2024-05-11T09:37:03.490397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198426.6 576
 
8.4%
190107.9 476
 
6.9%
198658.9 298
 
4.3%
208246.3 176
 
2.6%
206389.4 170
 
2.5%
207170.8 159
 
2.3%
199375.0 148
 
2.2%
212622.656601 121
 
1.8%
210346.19998 115
 
1.7%
183370.939985 114
 
1.7%
Other values (250) 4505
65.7%
ValueCountFrequency (%)
182514.7 11
 
0.2%
182726.2 1
 
< 0.1%
183370.939985 114
1.7%
184149.98 86
1.3%
184311.265 3
 
< 0.1%
184617.88378 5
 
0.1%
184760.03175 8
 
0.1%
184828.54 2
 
< 0.1%
184917.14695 4
 
0.1%
184944.819 6
 
0.1%
ValueCountFrequency (%)
215620.86001 13
 
0.2%
214256.83001 8
 
0.1%
214034.7 11
 
0.2%
213848.20437 24
 
0.3%
213686.3 45
0.7%
213611.0 87
1.3%
213532.82001 13
 
0.2%
213332.39001 5
 
0.1%
213301.0 15
 
0.2%
213085.8 107
1.6%

y_value
Real number (ℝ)

Distinct261
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean450567.7
Minimum437272.4
Maximum465056.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.4 KiB
2024-05-11T09:37:03.931699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437272.4
5-th percentile440246.8
Q1445458
median450647
Q3453647.8
95-th percentile461398.5
Maximum465056.8
Range27784.4
Interquartile range (IQR)8189.8

Descriptive statistics

Standard deviation6483.114
Coefficient of variation (CV)0.014388768
Kurtosis-0.6848683
Mean450567.7
Median Absolute Deviation (MAD)4618.651
Skewness0.23228081
Sum3.0899933 × 109
Variance42030767
MonotonicityNot monotonic
2024-05-11T09:37:04.363784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
461398.5 576
 
8.4%
451442.6 476
 
6.9%
445458.0 298
 
4.3%
443827.0 176
 
2.6%
453647.8 170
 
2.5%
440246.8 159
 
2.3%
449747.8 148
 
2.2%
446666.568533 121
 
1.8%
445522.70003 115
 
1.7%
453330.649986 114
 
1.7%
Other values (251) 4505
65.7%
ValueCountFrequency (%)
437272.4 17
 
0.2%
437564.60003 60
0.9%
437647.6015 8
 
0.1%
438328.317198 2
 
< 0.1%
438332.29573 5
 
0.1%
438353.39663 14
 
0.2%
438498.2218 5
 
0.1%
438829.15998 7
 
0.1%
438960.4616 10
 
0.1%
438987.6685 3
 
< 0.1%
ValueCountFrequency (%)
465056.8 50
 
0.7%
464769.2 10
 
0.1%
462895.7 97
 
1.4%
462420.2 16
 
0.2%
462313.966345 9
 
0.1%
462155.239413 10
 
0.1%
462150.6 5
 
0.1%
461636.4 12
 
0.2%
461540.014057 6
 
0.1%
461398.5 576
8.4%

Sample

객체id조사지점종명학명과명우점도우점종여부서울시보호멸종위기1멸종위기2천연기념물고유종서식형태영소길드채이길드유형화자치구명조사지역조사연도조사출처참고문헌x_valuey_value
02452537진박새Parus ater (Linnaeus, 1758)박새과000000텃새나무구멍수관층1관악구관악산2010문헌조사서울시 도시숲(산림) 생태계 조사 학술 연구196429.0440098.8
124525412진박새Parus ater (Linnaeus, 1758)박새과000000텃새나무구멍수관층3마포구난지도 월드컵공원2004문헌조사월드컵공원 자연생태계 모니터링 및 관리방안189432.0452034.0
224525513진박새Parus ater (Linnaeus, 1758)박새과000000텃새나무구멍수관층1중구남산2005문헌조사남산공원 소나무림에 대한 생태상 모니터링 및 관리방안199375.0449747.8
324525673노랑할미새Motacilla cinerea (Tunstall, 1771)할미새과000000여름철새수변수면4용산구한강2007문헌조사2007년 한강생태계 조사198658.9445458.0
424525773노랑할미새Motacilla cinerea (Tunstall, 1771)할미새과000000여름철새수변수면4용산구한강2012문헌조사제7차 한강 생태계 조사연구198658.9445458.0
524525873논병아리Tachybaptus ruficollis (Pallas, 1764)논병아리과000000텃새기타기타4용산구한강2007문헌조사2007년 한강생태계 조사198658.9445458.0
624525973논병아리Tachybaptus ruficollis (Pallas, 1764)논병아리과000000텃새기타기타4용산구한강2010문헌조사겨울철 조류 동시 센서스198658.9445458.0
724526073논병아리Tachybaptus ruficollis (Pallas, 1764)논병아리과000000텃새기타기타4용산구한강2011문헌조사겨울철 조류 동시 센서스198658.9445458.0
824526173논병아리Tachybaptus ruficollis (Pallas, 1764)논병아리과000000텃새기타기타4용산구한강2012문헌조사겨울철 조류 동시 센서스198658.9445458.0
924526273논병아리Tachybaptus ruficollis (Pallas, 1764)논병아리과000000텃새기타기타4용산구한강2012문헌조사제7차 한강 생태계 조사연구198658.9445458.0
객체id조사지점종명학명과명우점도우점종여부서울시보호멸종위기1멸종위기2천연기념물고유종서식형태영소길드채이길드유형화자치구명조사지역조사연도조사출처참고문헌x_valuey_value
6848252277127직박구리Microscelis amaurotis (Temminck, 1830)직박구리과11.005693100000텃새수관층수관층3서대문구백련산22013현장조사193930.803545454792.1695
6849252278127멧비둘기Streptopelia orietalis (Latham, 1790)비둘기과3.842505100000텃새수관층관목층3서대문구백련산22013현장조사193930.803545454792.1695
6850252279127산솔새Phylloscopus coronatus (Temminck & Schlegel, 1847)휘파람새과3.605313100000여름철새관목층수관층3서대문구백련산22013현장조사193930.803545454792.1695
6851252280127박새Parus major (Linnaeus, 1758)박새과8.444023110000텃새나무구멍수관층3서대문구백련산22013현장조사193930.803545454792.1695
6852252281127꿩Phasianus colchicus (Linnaeus, 1758)꿩과0.901328000000텃새관목층관목층3서대문구백련산22013현장조사193930.803545454792.1695
6853252282240직박구리Microscelis amaurotis (Temminck, 1830)직박구리과11.005693100000텃새수관층수관층2서대문구백련산32013현장조사194421.964403454520.994608
6854252283240물까치Cyanopica cyanus (Pallas, 1776)까마귀과0.616698000000텃새수관층임연부2서대문구백련산32013현장조사194421.964403454520.994608
6855252284240울새Luscinia sibilans (Swinhoe, 1863)지빠귀과2.466793000000나그네새기타관목층2서대문구백련산32013현장조사194421.964403454520.994608
6856252285240개똥지빠귀Turdus eunomus (Temminck, 1831)지빠귀과0.047438000000겨울철새관목층수관층2서대문구백련산32013현장조사194421.964403454520.994608
6857252286240까치Pica pica (Linnaeus, 1758)까마귀과7.969639100000텃새수관층임연부2서대문구백련산32013현장조사194421.964403454520.994608