Overview

Dataset statistics

Number of variables4
Number of observations72
Missing cells8
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory33.8 B

Variable types

Text3
DateTime1

Dataset

Description전북특별자치도 산림환경연구소의 나무병원 데이터입니다. 나무병원에 관한 요청사항, 요청인, 사진, 접수일을 포함하고 있습니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15067747/fileData.do

Alerts

요청인 has 1 (1.4%) missing valuesMissing
사진 has 6 (8.3%) missing valuesMissing
접수일 has 1 (1.4%) missing valuesMissing

Reproduction

Analysis started2024-03-14 15:48:46.477643
Analysis finished2024-03-14 15:48:48.095274
Duration1.62 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

요청사항
Text

Distinct68
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size704.0 B
2024-03-15T00:48:49.101880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length17.013889
Min length5

Characters and Unicode

Total characters1225
Distinct characters202
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)90.3%

Sample

1st row당산나무인 느티나무가 말라죽어가요
2nd row나무 충해 신고
3rd row소나무 가지가 노랗게 말라갑니다.
4th row가이즈까 향나무
5th row단지내 소나무 고사중 입니다
ValueCountFrequency (%)
소나무 28
 
9.1%
잎이 7
 
2.3%
및 6
 
1.9%
진단 5
 
1.6%
단지내 5
 
1.6%
스트로브 4
 
1.3%
고사 4
 
1.3%
원인 4
 
1.3%
호두나무 4
 
1.3%
잣나무 4
 
1.3%
Other values (181) 238
77.0%
2024-03-15T00:48:51.114008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
248
 
20.2%
나 57
 
4.7%
무 57
 
4.7%
소 31
 
2.5%
가 31
 
2.5%
고 26
 
2.1%
니 24
 
2.0%
다 24
 
2.0%
요 23
 
1.9%
이 23
 
1.9%
Other values (192) 681
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 941
76.8%
Space Separator 248
 
20.2%
Other Punctuation 28
 
2.3%
Decimal Number 3
 
0.2%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
나 57
 
6.1%
무 57
 
6.1%
소 31
 
3.3%
가 31
 
3.3%
고 26
 
2.8%
니 24
 
2.6%
다 24
 
2.6%
요 23
 
2.4%
이 23
 
2.4%
단 20
 
2.1%
Other values (185) 625
66.4%
Other Punctuation
ValueCountFrequency (%)
. 21
75.0%
? 7
 
25.0%
Space Separator
ValueCountFrequency (%)
248
100.0%
Decimal Number
ValueCountFrequency (%)
1 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 941
76.8%
Common 284
 
23.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
나 57
 
6.1%
무 57
 
6.1%
소 31
 
3.3%
가 31
 
3.3%
고 26
 
2.8%
니 24
 
2.6%
다 24
 
2.6%
요 23
 
2.4%
이 23
 
2.4%
단 20
 
2.1%
Other values (185) 625
66.4%
Common
ValueCountFrequency (%)
248
87.3%
. 21
 
7.4%
? 7
 
2.5%
1 3
 
1.1%
( 2
 
0.7%
) 2
 
0.7%
_ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 940
76.7%
ASCII 284
 
23.2%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
248
87.3%
. 21
 
7.4%
? 7
 
2.5%
1 3
 
1.1%
( 2
 
0.7%
) 2
 
0.7%
_ 1
 
0.4%
Hangul
ValueCountFrequency (%)
나 57
 
6.1%
무 57
 
6.1%
소 31
 
3.3%
가 31
 
3.3%
고 26
 
2.8%
니 24
 
2.6%
다 24
 
2.6%
요 23
 
2.4%
이 23
 
2.4%
단 20
 
2.1%
Other values (184) 624
66.4%
Compat Jamo
ValueCountFrequency (%)
ㅡ 1
100.0%

요청인
Text

MISSING 

Distinct48
Distinct (%)67.6%
Missing1
Missing (%)1.4%
Memory size704.0 B
2024-03-15T00:48:52.165427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9859155
Min length2

Characters and Unicode

Total characters212
Distinct characters50
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

Unique34 ?
Unique (%)47.9%

Sample

1st row김*화
2nd row오*권
3rd row김*우
4th row이*철
5th row유*
ValueCountFrequency (%)
문*일 4
 
5.6%
김*숙 4
 
5.6%
김*수 4
 
5.6%
김*우 3
 
4.2%
하*학 3
 
4.2%
최*영 3
 
4.2%
신*근 2
 
2.8%
김*화 2
 
2.8%
백*정 2
 
2.8%
이*덕 2
 
2.8%
Other values (38) 42
59.2%
2024-03-15T00:48:53.546940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 71
33.5%
김 22
 
10.4%
오 7
 
3.3%
일 7
 
3.3%
수 6
 
2.8%
이 5
 
2.4%
문 5
 
2.4%
최 4
 
1.9%
숙 4
 
1.9%
정 4
 
1.9%
Other values (40) 77
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 141
66.5%
Other Punctuation 71
33.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 22
 
15.6%
오 7
 
5.0%
일 7
 
5.0%
수 6
 
4.3%
이 5
 
3.5%
문 5
 
3.5%
최 4
 
2.8%
숙 4
 
2.8%
정 4
 
2.8%
백 4
 
2.8%
Other values (39) 73
51.8%
Other Punctuation
ValueCountFrequency (%)
* 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 141
66.5%
Common 71
33.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 22
 
15.6%
오 7
 
5.0%
일 7
 
5.0%
수 6
 
4.3%
이 5
 
3.5%
문 5
 
3.5%
최 4
 
2.8%
숙 4
 
2.8%
정 4
 
2.8%
백 4
 
2.8%
Other values (39) 73
51.8%
Common
ValueCountFrequency (%)
* 71
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 141
66.5%
ASCII 71
33.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 71
100.0%
Hangul
ValueCountFrequency (%)
김 22
 
15.6%
오 7
 
5.0%
일 7
 
5.0%
수 6
 
4.3%
이 5
 
3.5%
문 5
 
3.5%
최 4
 
2.8%
숙 4
 
2.8%
정 4
 
2.8%
백 4
 
2.8%
Other values (39) 73
51.8%

사진
Text

MISSING 

Distinct60
Distinct (%)90.9%
Missing6
Missing (%)8.3%
Memory size704.0 B
2024-03-15T00:48:54.354687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length31
Mean length18.969697
Min length5

Characters and Unicode

Total characters1252
Distinct characters131
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

Unique54 ?
Unique (%)81.8%

Sample

1st row20180202_125020.jpg
2nd row겹벚나무 충해.zip
3rd row305동 앞 소나무사진4.jpg
4th rowKakaoTalk_20180605_120102915.jpg
5th row180620_73번지밑에 잣나무 죽은사진 (4).jpg
ValueCountFrequency (%)
소나무 4
 
4.5%
20200514_171127.jpg 2
 
2.2%
305동 2
 
2.2%
사진.jpg 2
 
2.2%
호두열매.jpg 2
 
2.2%
꾸미기]소나무사진.jpg 2
 
2.2%
잣나무.hwp 2
 
2.2%
스트로브 2
 
2.2%
120191011.jpg 2
 
2.2%
22.jpg 2
 
2.2%
Other values (67) 67
75.3%
2024-03-15T00:48:55.359878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 132
 
10.5%
2 94
 
7.5%
1 86
 
6.9%
. 66
 
5.3%
p 61
 
4.9%
j 56
 
4.5%
g 53
 
4.2%
5 45
 
3.6%
3 42
 
3.4%
_ 40
 
3.2%
Other values (121) 577
46.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 559
44.6%
Lowercase Letter 287
22.9%
Other Letter 174
 
13.9%
Uppercase Letter 87
 
6.9%
Other Punctuation 67
 
5.4%
Connector Punctuation 40
 
3.2%
Space Separator 24
 
1.9%
Open Punctuation 7
 
0.6%
Close Punctuation 7
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
나 18
 
10.3%
무 18
 
10.3%
소 12
 
6.9%
사 10
 
5.7%
진 9
 
5.2%
지 4
 
2.3%
해 3
 
1.7%
충 3
 
1.7%
기 3
 
1.7%
호 3
 
1.7%
Other values (70) 91
52.3%
Lowercase Letter
ValueCountFrequency (%)
p 61
21.3%
j 56
19.5%
g 53
18.5%
a 31
10.8%
k 22
 
7.7%
l 13
 
4.5%
o 12
 
4.2%
e 7
 
2.4%
h 5
 
1.7%
i 5
 
1.7%
Other values (7) 22
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
A 13
14.9%
D 10
11.5%
E 10
11.5%
T 10
11.5%
K 10
11.5%
C 8
9.2%
B 7
8.0%
F 5
 
5.7%
G 3
 
3.4%
J 3
 
3.4%
Other values (6) 8
9.2%
Decimal Number
ValueCountFrequency (%)
0 132
23.6%
2 94
16.8%
1 86
15.4%
5 45
 
8.1%
3 42
 
7.5%
4 38
 
6.8%
9 38
 
6.8%
6 30
 
5.4%
8 29
 
5.2%
7 25
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 66
98.5%
@ 1
 
1.5%
Open Punctuation
ValueCountFrequency (%)
( 4
57.1%
[ 3
42.9%
Close Punctuation
ValueCountFrequency (%)
) 4
57.1%
] 3
42.9%
Connector Punctuation
ValueCountFrequency (%)
_ 40
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 704
56.2%
Latin 374
29.9%
Hangul 174
 
13.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
나 18
 
10.3%
무 18
 
10.3%
소 12
 
6.9%
사 10
 
5.7%
진 9
 
5.2%
지 4
 
2.3%
해 3
 
1.7%
충 3
 
1.7%
기 3
 
1.7%
호 3
 
1.7%
Other values (70) 91
52.3%
Latin
ValueCountFrequency (%)
p 61
16.3%
j 56
15.0%
g 53
14.2%
a 31
 
8.3%
k 22
 
5.9%
A 13
 
3.5%
l 13
 
3.5%
o 12
 
3.2%
D 10
 
2.7%
E 10
 
2.7%
Other values (23) 93
24.9%
Common
ValueCountFrequency (%)
0 132
18.8%
2 94
13.4%
1 86
12.2%
. 66
9.4%
5 45
 
6.4%
3 42
 
6.0%
_ 40
 
5.7%
4 38
 
5.4%
9 38
 
5.4%
6 30
 
4.3%
Other values (8) 93
13.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1078
86.1%
Hangul 174
 
13.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 132
 
12.2%
2 94
 
8.7%
1 86
 
8.0%
. 66
 
6.1%
p 61
 
5.7%
j 56
 
5.2%
g 53
 
4.9%
5 45
 
4.2%
3 42
 
3.9%
_ 40
 
3.7%
Other values (41) 403
37.4%
Hangul
ValueCountFrequency (%)
나 18
 
10.3%
무 18
 
10.3%
소 12
 
6.9%
사 10
 
5.7%
진 9
 
5.2%
지 4
 
2.3%
해 3
 
1.7%
충 3
 
1.7%
기 3
 
1.7%
호 3
 
1.7%
Other values (70) 91
52.3%

접수일
Date

MISSING 

Distinct48
Distinct (%)67.6%
Missing1
Missing (%)1.4%
Memory size704.0 B
Minimum2018-03-20 00:00:00
Maximum2020-09-07 00:00:00
2024-03-15T00:48:55.604768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:48:56.016775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)

Correlations

2024-03-15T00:48:56.302353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
요청사항요청인사진접수일
요청사항1.0001.0000.9950.987
요청인1.0001.0001.0000.974
사진0.9951.0001.0000.897
접수일0.9870.9740.8971.000

Missing values

2024-03-15T00:48:47.434530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:48:47.725344image/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.
2024-03-15T00:48:48.002652image/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

요청사항요청인사진접수일
0당산나무인 느티나무가 말라죽어가요김*화20180202_125020.jpg2018-03-20
1나무 충해 신고오*권겹벚나무 충해.zip2018-09-18
2소나무 가지가 노랗게 말라갑니다.김*우305동 앞 소나무사진4.jpg2018-09-18
3가이즈까 향나무이*철KakaoTalk_20180605_120102915.jpg2018-09-18
4단지내 소나무 고사중 입니다유*<NA>2018-09-18
5잣나무가 붉은 색이 됐너요백*준<NA>2018-09-18
6잣나무가 붉은 색이 됐너요 첨부사진입니다백*준180620_73번지밑에 잣나무 죽은사진 (4).jpg2018-07-06
7스트로브 잣나무김*숙20180710_101631.jpg2018-09-18
8스트로브 잣나무 잎이 붉게 변해 가고 있어요.김*숙20180710_101236.jpg2018-09-18
9소나무 수피에 부스럼이 생겼습니다.오*림새 폴더.zip2018-09-18
요청사항요청인사진접수일
62산철쭉 씨로 채취하여 하우스에서 키운 묘종이 잔뿌리가김*수KakaoTalk_20200812_120150583.jpg2020-08-19
63호두나무 병충해 진단 및 치료 문의신*현상아유치원 호두나무.zip2020-08-19
64가로수 충해관련 자문을 구합니다.김*호KakaoTalk_20200820_103031936.jpg2020-08-20
65소나무 상태진단 요청지*수20200824_113210.jpg2020-08-24
66소나무 병을 진단부탁합니다유*덕KakaoTalk_20200824_173433169.jpg2020-08-25
67소나무 현장방문 진단요청지*수<NA>2020-08-25
68소나무류 진단요청드립니다.문*일KakaoTalk_20200901_093150577.jpg2020-09-02
69소나무 잎이 마르고 상태가 나빠지고 있습니다최*명IMG_6112.JPG2020-09-02
70소나무 가지가 말라 죽어가고 있어요권*균15990943224382595454450164035438.jpg2020-09-04
71소나무가 죽어갑니다.김*오KakaoTalk_20200906_202306165.jpg2020-09-07