Overview

Dataset statistics

Number of variables8
Number of observations22
Missing cells24
Missing cells (%)13.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory70.0 B

Variable types

Text6
Categorical2

Dataset

Description2014데미샘자연휴양림통계
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202262

Alerts

Unnamed: 2 is highly overall correlated with Unnamed: 3High correlation
Unnamed: 3 is highly overall correlated with Unnamed: 2High correlation
2014년 데미샘자연휴양림 통계 has 19 (86.4%) missing valuesMissing
Unnamed: 1 has 2 (9.1%) missing valuesMissing
Unnamed: 5 has 1 (4.5%) missing valuesMissing
Unnamed: 6 has 1 (4.5%) missing valuesMissing
Unnamed: 7 has 1 (4.5%) missing valuesMissing

Reproduction

Analysis started2024-03-14 03:00:00.087282
Analysis finished2024-03-14 03:00:00.944242
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2014년 데미샘자연휴양림 통계
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing19
Missing (%)86.4%
Memory size308.0 B
2024-03-14T12:00:01.012755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters9
Distinct characters9
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

Unique3 ?
Unique (%)100.0%

Sample

1st row구분
2nd row휴양관
3rd row숲속의집
ValueCountFrequency (%)
구분 1
33.3%
휴양관 1
33.3%
숲속의집 1
33.3%
2024-03-14T12:00:01.259552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 1
11.1%
분 1
11.1%
휴 1
11.1%
양 1
11.1%
관 1
11.1%
숲 1
11.1%
속 1
11.1%
의 1
11.1%
집 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1
11.1%
분 1
11.1%
휴 1
11.1%
양 1
11.1%
관 1
11.1%
숲 1
11.1%
속 1
11.1%
의 1
11.1%
집 1
11.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1
11.1%
분 1
11.1%
휴 1
11.1%
양 1
11.1%
관 1
11.1%
숲 1
11.1%
속 1
11.1%
의 1
11.1%
집 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 1
11.1%
분 1
11.1%
휴 1
11.1%
양 1
11.1%
관 1
11.1%
숲 1
11.1%
속 1
11.1%
의 1
11.1%
집 1
11.1%

Unnamed: 1
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing2
Missing (%)9.1%
Memory size308.0 B
2024-03-14T12:00:01.405231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.75
Min length3

Characters and Unicode

Total characters75
Distinct characters38
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st row101호
2nd row102호
3rd row103호
4th row104호
5th row105호
ValueCountFrequency (%)
101호 1
 
5.0%
102호 1
 
5.0%
하늘다람쥐 1
 
5.0%
잠자리 1
 
5.0%
산토끼 1
 
5.0%
부엉이 1
 
5.0%
반딧불이 1
 
5.0%
무당벌레 1
 
5.0%
메뚜기 1
 
5.0%
너구리 1
 
5.0%
Other values (10) 10
50.0%
2024-03-14T12:00:01.668342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
호 10
 
13.3%
0 10
 
13.3%
1 7
 
9.3%
2 7
 
9.3%
늘 2
 
2.7%
리 2
 
2.7%
하 2
 
2.7%
5 2
 
2.7%
4 2
 
2.7%
3 2
 
2.7%
Other values (28) 29
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45
60.0%
Decimal Number 30
40.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 10
22.2%
늘 2
 
4.4%
리 2
 
4.4%
하 2
 
4.4%
이 2
 
4.4%
쥐 1
 
2.2%
람 1
 
2.2%
다 1
 
2.2%
불 1
 
2.2%
자 1
 
2.2%
Other values (22) 22
48.9%
Decimal Number
ValueCountFrequency (%)
0 10
33.3%
1 7
23.3%
2 7
23.3%
5 2
 
6.7%
4 2
 
6.7%
3 2
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45
60.0%
Common 30
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 10
22.2%
늘 2
 
4.4%
리 2
 
4.4%
하 2
 
4.4%
이 2
 
4.4%
쥐 1
 
2.2%
람 1
 
2.2%
다 1
 
2.2%
불 1
 
2.2%
자 1
 
2.2%
Other values (22) 22
48.9%
Common
ValueCountFrequency (%)
0 10
33.3%
1 7
23.3%
2 7
23.3%
5 2
 
6.7%
4 2
 
6.7%
3 2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45
60.0%
ASCII 30
40.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
호 10
22.2%
늘 2
 
4.4%
리 2
 
4.4%
하 2
 
4.4%
이 2
 
4.4%
쥐 1
 
2.2%
람 1
 
2.2%
다 1
 
2.2%
불 1
 
2.2%
자 1
 
2.2%
Other values (22) 22
48.9%
ASCII
ValueCountFrequency (%)
0 10
33.3%
1 7
23.3%
2 7
23.3%
5 2
 
6.7%
4 2
 
6.7%
3 2
 
6.7%

Unnamed: 2
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
35,000
6 
49,000
5 
28,000
4 
91,000
4 
단가
1 
Other values (2)
2 

Length

Max length7
Median length6
Mean length5.7272727
Min length2

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st row단가
2nd row비수기
3rd row35,000
4th row35,000
5th row35,000

Common Values

ValueCountFrequency (%)
35,000 6
27.3%
49,000 5
22.7%
28,000 4
18.2%
91,000 4
18.2%
단가 1
 
4.5%
비수기 1
 
4.5%
112,000 1
 
4.5%

Length

2024-03-14T12:00:01.819725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:00:01.938801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
35,000 6
27.3%
49,000 5
22.7%
28,000 4
18.2%
91,000 4
18.2%
단가 1
 
4.5%
비수기 1
 
4.5%
112,000 1
 
4.5%

Unnamed: 3
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
50,000
6 
70,000
5 
40,000
4 
130,000
4 
<NA>
1 
Other values (2)
2 

Length

Max length7
Median length6
Mean length6
Min length3

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st row<NA>
2nd row성수기
3rd row50,000
4th row50,000
5th row50,000

Common Values

ValueCountFrequency (%)
50,000 6
27.3%
70,000 5
22.7%
40,000 4
18.2%
130,000 4
18.2%
<NA> 1
 
4.5%
성수기 1
 
4.5%
160,000 1
 
4.5%

Length

2024-03-14T12:00:02.055601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:00:02.193366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50,000 6
27.3%
70,000 5
22.7%
40,000 4
18.2%
130,000 4
18.2%
na 1
 
4.5%
성수기 1
 
4.5%
160,000 1
 
4.5%

Unnamed: 4
Text

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-03-14T12:00:02.302923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.6818182
Min length1

Characters and Unicode

Total characters37
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)68.2%

Sample

1st row예약
2nd row비수기
3rd row7
4th row6
5th row4
ValueCountFrequency (%)
7 3
 
13.6%
13 2
 
9.1%
4 2
 
9.1%
30 1
 
4.5%
예약 1
 
4.5%
39 1
 
4.5%
48 1
 
4.5%
12 1
 
4.5%
41 1
 
4.5%
46 1
 
4.5%
Other values (8) 8
36.4%
2024-03-14T12:00:02.558354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7
18.9%
4 6
16.2%
7 4
10.8%
3 4
10.8%
8 3
8.1%
6 2
 
5.4%
5 2
 
5.4%
2 2
 
5.4%
비 1
 
2.7%
수 1
 
2.7%
Other values (5) 5
13.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32
86.5%
Other Letter 5
 
13.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7
21.9%
4 6
18.8%
7 4
12.5%
3 4
12.5%
8 3
9.4%
6 2
 
6.2%
5 2
 
6.2%
2 2
 
6.2%
0 1
 
3.1%
9 1
 
3.1%
Other Letter
ValueCountFrequency (%)
비 1
20.0%
수 1
20.0%
기 1
20.0%
예 1
20.0%
약 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32
86.5%
Hangul 5
 
13.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7
21.9%
4 6
18.8%
7 4
12.5%
3 4
12.5%
8 3
9.4%
6 2
 
6.2%
5 2
 
6.2%
2 2
 
6.2%
0 1
 
3.1%
9 1
 
3.1%
Hangul
ValueCountFrequency (%)
비 1
20.0%
수 1
20.0%
기 1
20.0%
예 1
20.0%
약 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
86.5%
Hangul 5
 
13.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7
21.9%
4 6
18.8%
7 4
12.5%
3 4
12.5%
8 3
9.4%
6 2
 
6.2%
5 2
 
6.2%
2 2
 
6.2%
0 1
 
3.1%
9 1
 
3.1%
Hangul
ValueCountFrequency (%)
비 1
20.0%
수 1
20.0%
기 1
20.0%
예 1
20.0%
약 1
20.0%

Unnamed: 5
Text

MISSING 

Distinct19
Distinct (%)90.5%
Missing1
Missing (%)4.5%
Memory size308.0 B
2024-03-14T12:00:02.698011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.4761905
Min length2

Characters and Unicode

Total characters52
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)81.0%

Sample

1st row성수기
2nd row74
3rd row68
4th row71
5th row67
ValueCountFrequency (%)
74 2
 
9.5%
110 2
 
9.5%
78 1
 
4.8%
106 1
 
4.8%
132 1
 
4.8%
116 1
 
4.8%
104 1
 
4.8%
103 1
 
4.8%
115 1
 
4.8%
94 1
 
4.8%
Other values (9) 9
42.9%
2024-03-14T12:00:02.971467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
30.8%
7 8
15.4%
0 7
13.5%
4 4
 
7.7%
6 4
 
7.7%
8 3
 
5.8%
3 3
 
5.8%
5 2
 
3.8%
성 1
 
1.9%
수 1
 
1.9%
Other values (3) 3
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49
94.2%
Other Letter 3
 
5.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
32.7%
7 8
16.3%
0 7
14.3%
4 4
 
8.2%
6 4
 
8.2%
8 3
 
6.1%
3 3
 
6.1%
5 2
 
4.1%
9 1
 
2.0%
2 1
 
2.0%
Other Letter
ValueCountFrequency (%)
성 1
33.3%
수 1
33.3%
기 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 49
94.2%
Hangul 3
 
5.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
32.7%
7 8
16.3%
0 7
14.3%
4 4
 
8.2%
6 4
 
8.2%
8 3
 
6.1%
3 3
 
6.1%
5 2
 
4.1%
9 1
 
2.0%
2 1
 
2.0%
Hangul
ValueCountFrequency (%)
성 1
33.3%
수 1
33.3%
기 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49
94.2%
Hangul 3
 
5.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
32.7%
7 8
16.3%
0 7
14.3%
4 4
 
8.2%
6 4
 
8.2%
8 3
 
6.1%
3 3
 
6.1%
5 2
 
4.1%
9 1
 
2.0%
2 1
 
2.0%
Hangul
ValueCountFrequency (%)
성 1
33.3%
수 1
33.3%
기 1
33.3%

Unnamed: 6
Text

MISSING 

Distinct20
Distinct (%)95.2%
Missing1
Missing (%)4.5%
Memory size308.0 B
2024-03-14T12:00:03.141082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.8571429
Min length3

Characters and Unicode

Total characters123
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)90.5%

Sample

1st row예약률
2nd row22.19%
3rd row20.17%
4th row20.55%
5th row20.27%
ValueCountFrequency (%)
21.10 2
 
9.5%
24.96 1
 
4.8%
32.88 1
 
4.8%
46.85 1
 
4.8%
44.93 1
 
4.8%
32.05 1
 
4.8%
31.51 1
 
4.8%
43.84 1
 
4.8%
44.11 1
 
4.8%
38.36 1
 
4.8%
Other values (10) 10
47.6%
2024-03-14T12:00:03.370961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 20
16.3%
% 20
16.3%
2 17
13.8%
1 11
8.9%
3 11
8.9%
0 8
 
6.5%
4 8
 
6.5%
8 7
 
5.7%
5 6
 
4.9%
9 5
 
4.1%
Other values (5) 10
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
65.0%
Other Punctuation 40
32.5%
Other Letter 3
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 17
21.2%
1 11
13.8%
3 11
13.8%
0 8
10.0%
4 8
10.0%
8 7
8.8%
5 6
 
7.5%
9 5
 
6.2%
6 5
 
6.2%
7 2
 
2.5%
Other Letter
ValueCountFrequency (%)
예 1
33.3%
약 1
33.3%
률 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 20
50.0%
% 20
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120
97.6%
Hangul 3
 
2.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 20
16.7%
% 20
16.7%
2 17
14.2%
1 11
9.2%
3 11
9.2%
0 8
 
6.7%
4 8
 
6.7%
8 7
 
5.8%
5 6
 
5.0%
9 5
 
4.2%
Other values (2) 7
 
5.8%
Hangul
ValueCountFrequency (%)
예 1
33.3%
약 1
33.3%
률 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
97.6%
Hangul 3
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 20
16.7%
% 20
16.7%
2 17
14.2%
1 11
9.2%
3 11
9.2%
0 8
 
6.7%
4 8
 
6.7%
8 7
 
5.8%
5 6
 
5.0%
9 5
 
4.2%
Other values (2) 7
 
5.8%
Hangul
ValueCountFrequency (%)
예 1
33.3%
약 1
33.3%
률 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct19
Distinct (%)90.5%
Missing1
Missing (%)4.5%
Memory size308.0 B
2024-03-14T12:00:03.516401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.8571429
Min length3

Characters and Unicode

Total characters123
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)81.0%

Sample

1st row공실율
2nd row77.81%
3rd row79.73%
4th row79.45%
5th row79.73%
ValueCountFrequency (%)
79.73 2
 
9.5%
78.90 2
 
9.5%
55.89 1
 
4.8%
공실율 1
 
4.8%
70.68 1
 
4.8%
53.15 1
 
4.8%
55.07 1
 
4.8%
67.95 1
 
4.8%
68.49 1
 
4.8%
56.16 1
 
4.8%
Other values (9) 9
42.9%
2024-03-14T12:00:03.765849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 20
16.3%
% 20
16.3%
7 19
15.4%
9 10
8.1%
5 10
8.1%
6 10
8.1%
8 8
 
6.5%
0 6
 
4.9%
1 6
 
4.9%
4 5
 
4.1%
Other values (5) 9
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
65.0%
Other Punctuation 40
32.5%
Other Letter 3
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 19
23.8%
9 10
12.5%
5 10
12.5%
6 10
12.5%
8 8
10.0%
0 6
 
7.5%
1 6
 
7.5%
4 5
 
6.2%
3 4
 
5.0%
2 2
 
2.5%
Other Letter
ValueCountFrequency (%)
공 1
33.3%
실 1
33.3%
율 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 20
50.0%
% 20
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120
97.6%
Hangul 3
 
2.4%

Most frequent character per script

Common
ValueCountFrequency (%)
. 20
16.7%
% 20
16.7%
7 19
15.8%
9 10
8.3%
5 10
8.3%
6 10
8.3%
8 8
 
6.7%
0 6
 
5.0%
1 6
 
5.0%
4 5
 
4.2%
Other values (2) 6
 
5.0%
Hangul
ValueCountFrequency (%)
공 1
33.3%
실 1
33.3%
율 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
97.6%
Hangul 3
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 20
16.7%
% 20
16.7%
7 19
15.8%
9 10
8.3%
5 10
8.3%
6 10
8.3%
8 8
 
6.7%
0 6
 
5.0%
1 6
 
5.0%
4 5
 
4.2%
Other values (2) 6
 
5.0%
Hangul
ValueCountFrequency (%)
공 1
33.3%
실 1
33.3%
율 1
33.3%

Correlations

2024-03-14T12:00:03.847581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2014년 데미샘자연휴양림 통계Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
2014년 데미샘자연휴양림 통계1.0000.0001.0000.0001.0000.0001.0001.000
Unnamed: 10.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0000.9710.9581.0000.958
Unnamed: 30.0001.0001.0001.0000.9660.9581.0000.933
Unnamed: 41.0001.0000.9710.9661.0000.8860.9820.958
Unnamed: 50.0001.0000.9580.9580.8861.0000.9390.923
Unnamed: 61.0001.0001.0001.0000.9820.9391.0001.000
Unnamed: 71.0001.0000.9580.9330.9580.9231.0001.000
2024-03-14T12:00:03.963625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3
Unnamed: 21.0001.000
Unnamed: 31.0001.000
2024-03-14T12:00:04.049393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 3
Unnamed: 21.0001.000
Unnamed: 31.0001.000

Missing values

2024-03-14T12:00:00.384740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T12:00:00.483514image/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.
2024-03-14T12:00:00.884659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

2014년 데미샘자연휴양림 통계Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
0구분<NA>단가<NA>예약<NA>예약률공실율
1<NA><NA>비수기성수기비수기성수기<NA><NA>
2휴양관101호35,00050,00077422.19%77.81%
3<NA>102호35,00050,00066820.17%79.73%
4<NA>103호35,00050,00047120.55%79.45%
5<NA>104호28,00040,00076720.27%79.73%
6<NA>105호28,00040,000158026.03%73.97%
7<NA>201호35,00050,00057521.92%78.08%
8<NA>202호35,00050,00077021.10%78.90%
9<NA>203호35,00050,00047321.10%78.90%
2014년 데미샘자연휴양림 통계Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
12숲속의집고슴도치91,000130,0001410632.88%67.12%
13<NA>너구리91,000130,000139429.32%70.68%
14<NA>메뚜기49,00070,0003011038.36%61.64%
15<NA>무당벌레49,00070,0004611544.11%55.89%
16<NA>반딧불이49,00070,0004111043.84%56.16%
17<NA>부엉이91,000130,0001210331.51%68.49%
18<NA>산토끼91,000130,0001310432.05%67.95%
19<NA>잠자리49,00070,0004811644.93%55.07%
20<NA>하늘다람쥐112,000160,0003913246.85%53.15%
21<NA>하늘소49,00070,0002811138.08%61.92%