Overview

Dataset statistics

Number of variables9
Number of observations314
Missing cells425
Missing cells (%)15.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.4 KiB
Average record size in memory76.4 B

Variable types

Text3
DateTime2
Numeric4

Dataset

Description산림사업 실적 (산림사업시작일자, 산림사업종료일자, 산림사업횟수, 산림사업일수, 산림사업장소내용, 산림사업비고, 항공방재면적, 자재무게)
Author산림청 산림항공본부
URLhttps://www.data.go.kr/data/15069451/fileData.do

Alerts

산림사업비고 has 5 (1.6%) missing valuesMissing
항공방재면적 has 209 (66.6%) missing valuesMissing
자재무게 has 211 (67.2%) missing valuesMissing
산림사업실적번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:29:29.661381
Analysis finished2023-12-12 01:29:32.806310
Duration3.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

산림사업실적번호
Text

UNIQUE 

Distinct314
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T10:29:32.959729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters4396
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique314 ?
Unique (%)100.0%

Sample

1st row20210111-00001
2nd row20210111-00002
3rd row20210113-00001
4th row20210113-00002
5th row20210113-00003
ValueCountFrequency (%)
20210111-00001 1
 
0.3%
20220707-00002 1
 
0.3%
20220712-00002 1
 
0.3%
20220712-00001 1
 
0.3%
20220711-00005 1
 
0.3%
20220711-00004 1
 
0.3%
20220711-00003 1
 
0.3%
20220718-00002 1
 
0.3%
20220711-00001 1
 
0.3%
20220707-00001 1
 
0.3%
Other values (304) 304
96.8%
2023-12-12T10:29:33.325659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1959
44.6%
2 1033
23.5%
1 601
 
13.7%
- 314
 
7.1%
7 106
 
2.4%
3 80
 
1.8%
9 79
 
1.8%
8 70
 
1.6%
6 63
 
1.4%
5 49
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4082
92.9%
Dash Punctuation 314
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1959
48.0%
2 1033
25.3%
1 601
 
14.7%
7 106
 
2.6%
3 80
 
2.0%
9 79
 
1.9%
8 70
 
1.7%
6 63
 
1.5%
5 49
 
1.2%
4 42
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 314
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4396
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1959
44.6%
2 1033
23.5%
1 601
 
13.7%
- 314
 
7.1%
7 106
 
2.4%
3 80
 
1.8%
9 79
 
1.8%
8 70
 
1.6%
6 63
 
1.4%
5 49
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1959
44.6%
2 1033
23.5%
1 601
 
13.7%
- 314
 
7.1%
7 106
 
2.4%
3 80
 
1.8%
9 79
 
1.8%
8 70
 
1.6%
6 63
 
1.4%
5 49
 
1.1%

산림사업시작일자
Date

Distinct182
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2021-01-11 00:00:00
Maximum2022-11-14 00:00:00
2023-12-12T10:29:33.480364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:33.653872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

산림사업종료일자
Date

Distinct191
Distinct (%)60.8%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2021-01-11 00:00:00
Maximum2022-11-18 00:00:00
2023-12-12T10:29:33.815579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:33.964334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

산림사업횟수
Real number (ℝ)

Distinct8
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4840764
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T10:29:34.094359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum13
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4481677
Coefficient of variation (CV)0.97580399
Kurtosis37.350682
Mean1.4840764
Median Absolute Deviation (MAD)0
Skewness5.6694698
Sum466
Variance2.0971897
MonotonicityNot monotonic
2023-12-12T10:29:34.220083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 236
75.2%
2 57
 
18.2%
3 7
 
2.2%
4 7
 
2.2%
13 2
 
0.6%
10 2
 
0.6%
5 2
 
0.6%
11 1
 
0.3%
ValueCountFrequency (%)
1 236
75.2%
2 57
 
18.2%
3 7
 
2.2%
4 7
 
2.2%
5 2
 
0.6%
10 2
 
0.6%
11 1
 
0.3%
13 2
 
0.6%
ValueCountFrequency (%)
13 2
 
0.6%
11 1
 
0.3%
10 2
 
0.6%
5 2
 
0.6%
4 7
 
2.2%
3 7
 
2.2%
2 57
 
18.2%
1 236
75.2%

산림사업일수
Real number (ℝ)

Distinct11
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0573248
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T10:29:34.346378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile6
Maximum11
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8822936
Coefficient of variation (CV)0.9149229
Kurtosis4.3533699
Mean2.0573248
Median Absolute Deviation (MAD)0
Skewness2.1296993
Sum646
Variance3.5430292
MonotonicityNot monotonic
2023-12-12T10:29:34.455092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 197
62.7%
2 48
 
15.3%
5 19
 
6.1%
3 16
 
5.1%
4 12
 
3.8%
6 8
 
2.5%
7 6
 
1.9%
9 3
 
1.0%
8 3
 
1.0%
11 1
 
0.3%
ValueCountFrequency (%)
1 197
62.7%
2 48
 
15.3%
3 16
 
5.1%
4 12
 
3.8%
5 19
 
6.1%
6 8
 
2.5%
7 6
 
1.9%
8 3
 
1.0%
9 3
 
1.0%
10 1
 
0.3%
ValueCountFrequency (%)
11 1
 
0.3%
10 1
 
0.3%
9 3
 
1.0%
8 3
 
1.0%
7 6
 
1.9%
6 8
 
2.5%
5 19
 
6.1%
4 12
 
3.8%
3 16
 
5.1%
2 48
15.3%

산림사업장소내용
Text

Distinct215
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T10:29:34.728706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length7.8152866
Min length2

Characters and Unicode

Total characters2454
Distinct characters165
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)47.8%

Sample

1st row경상남도 하동군
2nd row충청남도 천안시, 아산시
3rd row경상남도 의령군
4th row경기도 광주시
5th row충청북도 증평군, 보은군
ValueCountFrequency (%)
경기도 29
 
4.4%
충북 27
 
4.1%
일원 17
 
2.6%
충청남도 16
 
2.4%
충청북도 15
 
2.3%
경남 14
 
2.1%
영동군 14
 
2.1%
충주시 10
 
1.5%
경상남도 10
 
1.5%
충남 9
 
1.4%
Other values (217) 495
75.5%
2023-12-12T10:29:35.181710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
344
 
14.0%
군 145
 
5.9%
시 116
 
4.7%
산 103
 
4.2%
도 93
 
3.8%
천 85
 
3.5%
충 80
 
3.3%
남 74
 
3.0%
, 64
 
2.6%
경 64
 
2.6%
Other values (155) 1286
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1959
79.8%
Space Separator 344
 
14.0%
Other Punctuation 70
 
2.9%
Open Punctuation 27
 
1.1%
Close Punctuation 26
 
1.1%
Decimal Number 22
 
0.9%
Dash Punctuation 3
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 145
 
7.4%
시 116
 
5.9%
산 103
 
5.3%
도 93
 
4.7%
천 85
 
4.3%
충 80
 
4.1%
남 74
 
3.8%
경 64
 
3.3%
주 54
 
2.8%
원 52
 
2.7%
Other values (139) 1093
55.8%
Decimal Number
ValueCountFrequency (%)
0 6
27.3%
1 5
22.7%
3 4
18.2%
2 3
13.6%
6 2
 
9.1%
4 1
 
4.5%
5 1
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
Z 1
33.3%
M 1
33.3%
D 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 64
91.4%
/ 6
 
8.6%
Space Separator
ValueCountFrequency (%)
344
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1959
79.8%
Common 492
 
20.0%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 145
 
7.4%
시 116
 
5.9%
산 103
 
5.3%
도 93
 
4.7%
천 85
 
4.3%
충 80
 
4.1%
남 74
 
3.8%
경 64
 
3.3%
주 54
 
2.8%
원 52
 
2.7%
Other values (139) 1093
55.8%
Common
ValueCountFrequency (%)
344
69.9%
, 64
 
13.0%
( 27
 
5.5%
) 26
 
5.3%
0 6
 
1.2%
/ 6
 
1.2%
1 5
 
1.0%
3 4
 
0.8%
- 3
 
0.6%
2 3
 
0.6%
Other values (3) 4
 
0.8%
Latin
ValueCountFrequency (%)
Z 1
33.3%
M 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1959
79.8%
ASCII 495
 
20.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
344
69.5%
, 64
 
12.9%
( 27
 
5.5%
) 26
 
5.3%
0 6
 
1.2%
/ 6
 
1.2%
1 5
 
1.0%
3 4
 
0.8%
- 3
 
0.6%
2 3
 
0.6%
Other values (6) 7
 
1.4%
Hangul
ValueCountFrequency (%)
군 145
 
7.4%
시 116
 
5.9%
산 103
 
5.3%
도 93
 
4.7%
천 85
 
4.3%
충 80
 
4.1%
남 74
 
3.8%
경 64
 
3.3%
주 54
 
2.8%
원 52
 
2.7%
Other values (139) 1093
55.8%

산림사업비고
Text

MISSING 

Distinct272
Distinct (%)88.0%
Missing5
Missing (%)1.6%
Memory size2.6 KiB
2023-12-12T10:29:35.462800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length129
Median length72
Mean length41.417476
Min length4

Characters and Unicode

Total characters12798
Distinct characters301
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

Unique259 ?
Unique (%)83.8%

Sample

1st row2021년 제1차 소나무재선충병 정기 항공예찰(하동군 면적 20,000
2nd row2021년 제1차 소나무재선충병 정기 항공예찰(천안시, 아산시 면적 천안시 1,006, 아산시 1,300
3rd row2021년 제1차 소나무재선충병 정기 항공예찰(의령군 면적 3,000
4th row2021년 제1차 소나무재선충병 정기 항공예찰(광주시 면적 13,800
5th row2021년 제1차 소나무재선충병 정기 항공예찰(증평군, 보은군 면적 증평군 300, 보은군 15,000
ValueCountFrequency (%)
303
 
11.6%
소나무재선충병 66
 
2.5%
2022년 64
 
2.4%
지원 63
 
2.4%
자재운반 62
 
2.4%
면적 58
 
2.2%
산림사업 56
 
2.1%
정기 54
 
2.1%
항공방제 50
 
1.9%
제1차 38
 
1.5%
Other values (747) 1802
68.9%
2023-12-12T10:29:35.955092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2450
 
19.1%
2 554
 
4.3%
. 449
 
3.5%
1 430
 
3.4%
0 373
 
2.9%
/ 338
 
2.6%
( 231
 
1.8%
지 229
 
1.8%
무 202
 
1.6%
기 196
 
1.5%
Other values (291) 7346
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6481
50.6%
Space Separator 2450
 
19.1%
Decimal Number 2152
 
16.8%
Other Punctuation 1027
 
8.0%
Open Punctuation 233
 
1.8%
Close Punctuation 172
 
1.3%
Uppercase Letter 113
 
0.9%
Math Symbol 99
 
0.8%
Lowercase Letter 60
 
0.5%
Dash Punctuation 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 229
 
3.5%
무 202
 
3.1%
기 196
 
3.0%
재 184
 
2.8%
시 181
 
2.8%
사 177
 
2.7%
산 170
 
2.6%
항 163
 
2.5%
일 160
 
2.5%
충 158
 
2.4%
Other values (248) 4661
71.9%
Decimal Number
ValueCountFrequency (%)
2 554
25.7%
1 430
20.0%
0 373
17.3%
3 156
 
7.2%
7 130
 
6.0%
6 125
 
5.8%
4 116
 
5.4%
5 97
 
4.5%
8 87
 
4.0%
9 84
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
a 23
38.3%
h 22
36.7%
t 5
 
8.3%
g 2
 
3.3%
d 2
 
3.3%
o 2
 
3.3%
s 1
 
1.7%
y 1
 
1.7%
i 1
 
1.7%
n 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 449
43.7%
/ 338
32.9%
, 160
 
15.6%
: 72
 
7.0%
* 2
 
0.2%
; 2
 
0.2%
& 2
 
0.2%
# 2
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
A 37
32.7%
F 36
31.9%
P 24
21.2%
S 14
 
12.4%
H 1
 
0.9%
T 1
 
0.9%
Math Symbol
ValueCountFrequency (%)
~ 97
98.0%
→ 1
 
1.0%
+ 1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 231
99.1%
[ 2
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 171
99.4%
] 1
 
0.6%
Space Separator
ValueCountFrequency (%)
2450
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6481
50.6%
Common 6144
48.0%
Latin 173
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 229
 
3.5%
무 202
 
3.1%
기 196
 
3.0%
재 184
 
2.8%
시 181
 
2.8%
사 177
 
2.7%
산 170
 
2.6%
항 163
 
2.5%
일 160
 
2.5%
충 158
 
2.4%
Other values (248) 4661
71.9%
Common
ValueCountFrequency (%)
2450
39.9%
2 554
 
9.0%
. 449
 
7.3%
1 430
 
7.0%
0 373
 
6.1%
/ 338
 
5.5%
( 231
 
3.8%
) 171
 
2.8%
, 160
 
2.6%
3 156
 
2.5%
Other values (17) 832
 
13.5%
Latin
ValueCountFrequency (%)
A 37
21.4%
F 36
20.8%
P 24
13.9%
a 23
13.3%
h 22
12.7%
S 14
 
8.1%
t 5
 
2.9%
g 2
 
1.2%
d 2
 
1.2%
o 2
 
1.2%
Other values (6) 6
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6481
50.6%
ASCII 6316
49.4%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2450
38.8%
2 554
 
8.8%
. 449
 
7.1%
1 430
 
6.8%
0 373
 
5.9%
/ 338
 
5.4%
( 231
 
3.7%
) 171
 
2.7%
, 160
 
2.5%
3 156
 
2.5%
Other values (32) 1004
15.9%
Hangul
ValueCountFrequency (%)
지 229
 
3.5%
무 202
 
3.1%
기 196
 
3.0%
재 184
 
2.8%
시 181
 
2.8%
사 177
 
2.7%
산 170
 
2.6%
항 163
 
2.5%
일 160
 
2.5%
충 158
 
2.4%
Other values (248) 4661
71.9%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

항공방재면적
Real number (ℝ)

MISSING 

Distinct83
Distinct (%)79.0%
Missing209
Missing (%)66.6%
Infinite0
Infinite (%)0.0%
Mean2732.2757
Minimum27.6
Maximum52000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T10:29:36.115111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27.6
5-th percentile42.88
Q1127.4
median383.1
Q31248.4
95-th percentile15000
Maximum52000
Range51972.4
Interquartile range (IQR)1121

Descriptive statistics

Standard deviation8227.8854
Coefficient of variation (CV)3.0113672
Kurtosis20.2894
Mean2732.2757
Median Absolute Deviation (MAD)283.1
Skewness4.4045202
Sum286888.95
Variance67698097
MonotonicityNot monotonic
2023-12-12T10:29:36.277259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 9
 
2.9%
160.0 4
 
1.3%
15000.0 2
 
0.6%
1248.4 2
 
0.6%
141.8 2
 
0.6%
466.3 2
 
0.6%
1890.0 2
 
0.6%
40.6 2
 
0.6%
300.0 2
 
0.6%
1323.7 2
 
0.6%
Other values (73) 76
 
24.2%
(Missing) 209
66.6%
ValueCountFrequency (%)
27.6 1
0.3%
30.0 1
0.3%
34.7 1
0.3%
39.8 1
0.3%
40.6 2
0.6%
52.0 1
0.3%
57.6 1
0.3%
73.1 1
0.3%
76.8 1
0.3%
86.3 1
0.3%
ValueCountFrequency (%)
52000.0 1
0.3%
45000.0 1
0.3%
30412.0 1
0.3%
30000.0 1
0.3%
25000.0 1
0.3%
15000.0 2
0.6%
6700.0 1
0.3%
6340.0 1
0.3%
5825.0 1
0.3%
3400.0 1
0.3%

자재무게
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)52.4%
Missing211
Missing (%)67.2%
Infinite0
Infinite (%)0.0%
Mean17.745631
Minimum0.16
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T10:29:36.439510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.16
5-th percentile1
Q12.75
median9
Q322.5
95-th percentile70
Maximum120
Range119.84
Interquartile range (IQR)19.75

Descriptive statistics

Standard deviation23.939491
Coefficient of variation (CV)1.3490358
Kurtosis6.4126993
Mean17.745631
Median Absolute Deviation (MAD)7
Skewness2.4374482
Sum1827.8
Variance573.09922
MonotonicityNot monotonic
2023-12-12T10:29:36.614183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.0 10
 
3.2%
1.0 6
 
1.9%
14.0 6
 
1.9%
10.0 6
 
1.9%
1.7 4
 
1.3%
4.0 4
 
1.3%
8.0 4
 
1.3%
3.0 3
 
1.0%
30.15 2
 
0.6%
70.0 2
 
0.6%
Other values (44) 56
 
17.8%
(Missing) 211
67.2%
ValueCountFrequency (%)
0.16 1
 
0.3%
1.0 6
1.9%
1.3 1
 
0.3%
1.4 1
 
0.3%
1.69 1
 
0.3%
1.7 4
 
1.3%
1.8 1
 
0.3%
2.0 10
3.2%
2.5 1
 
0.3%
3.0 3
 
1.0%
ValueCountFrequency (%)
120.0 2
0.6%
88.5 1
0.3%
80.0 2
0.6%
70.0 2
0.6%
67.0 1
0.3%
50.0 1
0.3%
47.5 1
0.3%
43.6 1
0.3%
40.5 1
0.3%
40.0 1
0.3%

Interactions

2023-12-12T10:29:31.850055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:30.089397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:30.511070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:31.364136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:31.971030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:30.200227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:30.610551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:31.494429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:32.095519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:30.297269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:31.066920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:31.635798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:32.207842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:30.403546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:31.186276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:29:31.751791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:29:36.753654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산림사업횟수산림사업일수항공방재면적자재무게
산림사업횟수1.0000.3620.0000.479
산림사업일수0.3621.0000.0000.377
항공방재면적0.0000.0001.000NaN
자재무게0.4790.377NaN1.000
2023-12-12T10:29:36.872695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산림사업횟수산림사업일수항공방재면적자재무게
산림사업횟수1.0000.1350.0640.195
산림사업일수0.1351.0000.2510.298
항공방재면적0.0640.2511.000NaN
자재무게0.1950.298NaN1.000

Missing values

2023-12-12T10:29:32.409027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:29:32.602337image/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.
2023-12-12T10:29:32.732123image/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

산림사업실적번호산림사업시작일자산림사업종료일자산림사업횟수산림사업일수산림사업장소내용산림사업비고항공방재면적자재무게
020210111-000012021-01-112021-01-1111경상남도 하동군2021년 제1차 소나무재선충병 정기 항공예찰(하동군 면적 20,000<NA><NA>
120210111-000022021-01-112021-01-1121충청남도 천안시, 아산시2021년 제1차 소나무재선충병 정기 항공예찰(천안시, 아산시 면적 천안시 1,006, 아산시 1,300<NA><NA>
220210113-000012021-01-132021-01-1311경상남도 의령군2021년 제1차 소나무재선충병 정기 항공예찰(의령군 면적 3,000<NA><NA>
320210113-000022021-01-132021-01-1311경기도 광주시2021년 제1차 소나무재선충병 정기 항공예찰(광주시 면적 13,800<NA><NA>
420210113-000032021-01-132021-01-1321충청북도 증평군, 보은군2021년 제1차 소나무재선충병 정기 항공예찰(증평군, 보은군 면적 증평군 300, 보은군 15,000<NA><NA>
520210114-000012021-01-142021-01-1411충청남도 홍성군2021년 제1차 소나무재선충병 정기 항공예찰(홍성군 면적 3,000<NA><NA>
620210115-000012021-01-152021-01-1511경상남도 산청군2021년 제1차 소나무재선충병 정기 항공예찰(산청군 면적 10,000<NA><NA>
720210115-000022021-01-152021-01-1521충청북도 진천군, 음성군2021년 제1차 소나무재선충병 정기 항공예찰(진천군, 음성군 면적 진천군 15,000, 음성군 1,000<NA><NA>
820210118-000012021-01-182021-01-1912강원 평창산림사업 자재운반 현지조사 [지상(18일공중(19일<NA><NA>
920210119-000012021-01-192021-01-1911경상남도 거창군2021년 제1차 소나무재선충병 정기 항공예찰(거창군 면적 3,500<NA><NA>
산림사업실적번호산림사업시작일자산림사업종료일자산림사업횟수산림사업일수산림사업장소내용산림사업비고항공방재면적자재무게
30420221017-000012022-10-172022-10-1711충북 보은군충북 보은군 국사봉 등산로 정비사업 현지조사<NA>2.0
30520221017-000022022-11-072022-11-0832정선, 인제, 횡성지상예찰<NA><NA>
30620221018-000012022-10-182022-10-1811충북 보은군충북 보은군 국사봉 등산로 정비사업 / FPA631 2톤 / 현지조사 10.17(월)<NA>2.0
30720221018-000022022-10-192022-10-2012진안군등산로 정비 / 10. 18. ~ 10. 20.(18일 전개, 19~20일 임무 실시) / 비행지시 195호 / 특이사항: 요청기관 전라북도, 화물 자연석<NA>50.0
30820221018-000032022-10-192022-10-1911양양, 속초 일원눈잣나무 종자채취 인력 운송 / 10. 19.(19일 관리소에서 이륙, 임무 실시) / 자체비행지시 제48호<NA><NA>
30920221018-000042022-10-172022-10-1812인제 조침령 일원산불감시카메라 폐자제 운반 / 10. 17. ~ 10. 18.(17일 전개, 18일 임무 실시) / 비행지시 제194호 / 특이사항: 호이스트를 이용한 임무지 투입<NA>1.0
31020221028-000012022-10-282022-10-2811충북 충주시 천등산충북 충주시 산림사업 자재운반 현지조사<NA>3.1
31120221031-000012022-10-312022-10-3111충북 충주시 천등산충북 충주시 천등산 무선중계기 유지보수 사업 3.1톤 (현지조사: 10.29.) , (지원:10.31)<NA>3.1
31220221114-000012022-11-142022-11-1835정선, 인제, 횡성 일원무선중계기 교체 설치<NA>5.3
31320221127-000012022-11-102022-11-1031정선, 인제, 횡성항공예찰 / 자체비행지시 제53호<NA><NA>