Overview

Dataset statistics

Number of variables12
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory101.3 B

Variable types

Text4
Numeric3
Categorical5

Alerts

생성날짜 has constant value ""Constant
설치년도 is highly overall correlated with 위도(Latitude) and 1 other fieldsHigh correlation
위도(Latitude) is highly overall correlated with 설치년도 and 1 other fieldsHigh correlation
경도(Longitude) is highly overall correlated with 관리기관명High correlation
관리기관명 is highly overall correlated with 위도(Latitude) and 3 other fieldsHigh correlation
측정망 is highly overall correlated with 설치년도 and 1 other fieldsHigh correlation
측정항목 is highly overall correlated with 관리기관명High correlation
측정소 전경 is highly imbalanced (52.5%)Imbalance
측정항목 is highly imbalanced (84.9%)Imbalance
측정소명 has unique valuesUnique
측정소 주소 has unique valuesUnique
측정소 지도이미지 has unique valuesUnique
위도(Latitude) has unique valuesUnique
경도(Longitude) has unique valuesUnique
설치년도 has 18 (18.0%) zerosZeros

Reproduction

Analysis started2023-12-10 12:26:36.026791
Analysis finished2023-12-10 12:26:41.085411
Duration5.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정소명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:26:41.452239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.36
Min length2

Characters and Unicode

Total characters336
Distinct characters113
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row반송로
2nd row사파동
3rd row경화동
4th row하동읍
5th row동상동
ValueCountFrequency (%)
반송로 1
 
1.0%
정릉로 1
 
1.0%
종로구 1
 
1.0%
영등포구 1
 
1.0%
구로구 1
 
1.0%
공항대로 1
 
1.0%
강서구 1
 
1.0%
신촌로 1
 
1.0%
마포구 1
 
1.0%
서대문구 1
 
1.0%
Other values (91) 91
90.1%
2023-12-10T21:26:42.106618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 51
 
15.2%
구 27
 
8.0%
로 20
 
6.0%
대 13
 
3.9%
천 10
 
3.0%
강 8
 
2.4%
리 7
 
2.1%
상 6
 
1.8%
읍 5
 
1.5%
산 5
 
1.5%
Other values (103) 184
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 326
97.0%
Open Punctuation 4
 
1.2%
Close Punctuation 4
 
1.2%
Space Separator 1
 
0.3%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 51
 
15.6%
구 27
 
8.3%
로 20
 
6.1%
대 13
 
4.0%
천 10
 
3.1%
강 8
 
2.5%
리 7
 
2.1%
상 6
 
1.8%
읍 5
 
1.5%
산 5
 
1.5%
Other values (99) 174
53.4%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 326
97.0%
Common 10
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 51
 
15.6%
구 27
 
8.3%
로 20
 
6.1%
대 13
 
4.0%
천 10
 
3.1%
강 8
 
2.5%
리 7
 
2.1%
상 6
 
1.8%
읍 5
 
1.5%
산 5
 
1.5%
Other values (99) 174
53.4%
Common
ValueCountFrequency (%)
( 4
40.0%
) 4
40.0%
1
 
10.0%
1 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 326
97.0%
ASCII 10
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 51
 
15.6%
구 27
 
8.3%
로 20
 
6.1%
대 13
 
4.0%
천 10
 
3.1%
강 8
 
2.5%
리 7
 
2.1%
상 6
 
1.8%
읍 5
 
1.5%
산 5
 
1.5%
Other values (99) 174
53.4%
ASCII
ValueCountFrequency (%)
( 4
40.0%
) 4
40.0%
1
 
10.0%
1 1
 
10.0%

측정소 주소
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:26:42.416268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length36
Mean length28.01
Min length17

Characters and Unicode

Total characters2801
Distinct characters242
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

Unique100 ?
Unique (%)100.0%

Sample

1st row경남 창원시 의창구 원이대로 450(시설관리공단 실내수영장 앞)
2nd row경남 창원시 성산구 창이대로 706번길 16-23(사파민원센터)
3rd row경남 창원시 진해구 경화로16번길 31(병암동주민센터)
4th row경남 하동군 하동읍 군청로 23(하동군청)
5th row경남 김해시 호계로 517번길 8(동상동 주민센터)
ValueCountFrequency (%)
서울 37
 
6.7%
주민센터 18
 
3.2%
전남 17
 
3.1%
옥상 16
 
2.9%
경남 14
 
2.5%
경기 11
 
2.0%
광주 9
 
1.6%
앞 9
 
1.6%
수원시 7
 
1.3%
여수시 5
 
0.9%
Other values (353) 412
74.2%
2023-12-10T21:26:43.102553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
455
 
16.2%
1 91
 
3.2%
로 83
 
3.0%
동 80
 
2.9%
구 79
 
2.8%
서 68
 
2.4%
시 61
 
2.2%
주 60
 
2.1%
2 58
 
2.1%
울 49
 
1.7%
Other values (232) 1717
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1871
66.8%
Space Separator 455
 
16.2%
Decimal Number 373
 
13.3%
Close Punctuation 44
 
1.6%
Open Punctuation 42
 
1.5%
Dash Punctuation 13
 
0.5%
Uppercase Letter 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 83
 
4.4%
동 80
 
4.3%
구 79
 
4.2%
서 68
 
3.6%
시 61
 
3.3%
주 60
 
3.2%
울 49
 
2.6%
남 49
 
2.6%
길 44
 
2.4%
터 39
 
2.1%
Other values (215) 1259
67.3%
Decimal Number
ValueCountFrequency (%)
1 91
24.4%
2 58
15.5%
3 45
12.1%
6 32
 
8.6%
5 30
 
8.0%
4 30
 
8.0%
7 29
 
7.8%
0 27
 
7.2%
9 20
 
5.4%
8 11
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
455
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1871
66.8%
Common 928
33.1%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 83
 
4.4%
동 80
 
4.3%
구 79
 
4.2%
서 68
 
3.6%
시 61
 
3.3%
주 60
 
3.2%
울 49
 
2.6%
남 49
 
2.6%
길 44
 
2.4%
터 39
 
2.1%
Other values (215) 1259
67.3%
Common
ValueCountFrequency (%)
455
49.0%
1 91
 
9.8%
2 58
 
6.2%
3 45
 
4.8%
) 44
 
4.7%
( 42
 
4.5%
6 32
 
3.4%
5 30
 
3.2%
4 30
 
3.2%
7 29
 
3.1%
Other values (5) 72
 
7.8%
Latin
ValueCountFrequency (%)
C 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1871
66.8%
ASCII 930
33.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
455
48.9%
1 91
 
9.8%
2 58
 
6.2%
3 45
 
4.8%
) 44
 
4.7%
( 42
 
4.5%
6 32
 
3.4%
5 30
 
3.2%
4 30
 
3.2%
7 29
 
3.1%
Other values (7) 74
 
8.0%
Hangul
ValueCountFrequency (%)
로 83
 
4.4%
동 80
 
4.3%
구 79
 
4.2%
서 68
 
3.6%
시 61
 
3.3%
주 60
 
3.2%
울 49
 
2.6%
남 49
 
2.6%
길 44
 
2.4%
터 39
 
2.1%
Other values (215) 1259
67.3%

설치년도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1637.87
Minimum0
Maximum2019
Zeros18
Zeros (%)18.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:26:43.338055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11980
median1995
Q32004
95-th percentile2013
Maximum2019
Range2019
Interquartile range (IQR)24

Descriptive statistics

Standard deviation771.31016
Coefficient of variation (CV)0.4709227
Kurtosis0.87660605
Mean1637.87
Median Absolute Deviation (MAD)11
Skewness-1.6906388
Sum163787
Variance594919.37
MonotonicityNot monotonic
2023-12-10T21:26:43.621360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 18
18.0%
1997 8
 
8.0%
1994 5
 
5.0%
2006 4
 
4.0%
2003 4
 
4.0%
2013 4
 
4.0%
2004 4
 
4.0%
1986 3
 
3.0%
1984 3
 
3.0%
1980 3
 
3.0%
Other values (24) 44
44.0%
ValueCountFrequency (%)
0 18
18.0%
1973 2
 
2.0%
1978 2
 
2.0%
1979 2
 
2.0%
1980 3
 
3.0%
1982 3
 
3.0%
1984 3
 
3.0%
1986 3
 
3.0%
1987 1
 
1.0%
1990 1
 
1.0%
ValueCountFrequency (%)
2019 2
2.0%
2017 1
 
1.0%
2015 1
 
1.0%
2013 4
4.0%
2012 1
 
1.0%
2011 2
2.0%
2009 3
3.0%
2008 3
3.0%
2007 1
 
1.0%
2006 4
4.0%

관리기관명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시보건환경연구원
39 
전라남도보건환경연구원
16 
경상남도보건환경연구원
11 
경기도보건환경연구원
11 
광주광역시보건환경연구원
9 
Other values (6)
14 

Length

Max length15
Median length12
Mean length11.66
Min length10

Unique

Unique2 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시보건환경연구원 39
39.0%
전라남도보건환경연구원 16
16.0%
경상남도보건환경연구원 11
 
11.0%
경기도보건환경연구원 11
 
11.0%
광주광역시보건환경연구원 9
 
9.0%
울산광역시보건환경연구원 4
 
4.0%
한국환경공단 대구경북지역본부 3
 
3.0%
제주특별자치도보건환경연구원 3
 
3.0%
한국환경공단 호남지역본부 2
 
2.0%
충청남도보건환경연구원 1
 
1.0%

Length

2023-12-10T21:26:43.872699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시보건환경연구원 39
37.1%
전라남도보건환경연구원 16
15.2%
경상남도보건환경연구원 11
 
10.5%
경기도보건환경연구원 11
 
10.5%
광주광역시보건환경연구원 9
 
8.6%
한국환경공단 5
 
4.8%
울산광역시보건환경연구원 4
 
3.8%
대구경북지역본부 3
 
2.9%
제주특별자치도보건환경연구원 3
 
2.9%
호남지역본부 2
 
1.9%
Other values (2) 2
 
1.9%

측정소 이미지
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:26:44.220380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length95
Median length95
Mean length93.09
Min length1

Characters and Unicode

Total characters9309
Distinct characters45
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st rowhttp://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238145/INSIDE_OTHER_1.png
2nd rowhttp://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238146/INSIDE_OTHER_1.jpg
3rd rowhttp://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238151/INSIDE_OTHER_1.jpg
4th rowhttp://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238161/INSIDE_OTHER_1.png
5th rowhttp://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238181/INSIDE_OTHER_1.jpg
ValueCountFrequency (%)
0 2
 
2.0%
http://www.airkorea.or.kr/airkorea/station_photo/namis/station_images/111241/inside_other_1.bmp 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_photo/namis/station_images/131129/inside_other_1.jpg 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_photo/namis/station_images/111221/inside_other_1.bmp 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_photo/namis/station_images/111213/inside_other_1.bmp 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_photo/namis/station_images/111212/inside_other_1.jpg 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_photo/namis/station_images/111202/inside_other_1.bmp 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_photo/namis/station_images/111201/inside_other_1.bmp 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_photo/namis/station_images/111191/inside_other_1.bmp 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_photo/namis/station_images/111181/inside_other_1.jpg 1
 
1.0%
Other values (89) 89
89.0%
2023-12-10T21:26:44.948835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 781
 
8.4%
t 686
 
7.4%
o 686
 
7.4%
a 686
 
7.4%
r 588
 
6.3%
i 490
 
5.3%
_ 392
 
4.2%
. 392
 
4.2%
1 347
 
3.7%
I 295
 
3.2%
Other values (35) 3966
42.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5381
57.8%
Uppercase Letter 1577
 
16.9%
Other Punctuation 1271
 
13.7%
Decimal Number 688
 
7.4%
Connector Punctuation 392
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 686
12.7%
o 686
12.7%
a 686
12.7%
r 588
10.9%
i 490
9.1%
k 294
 
5.5%
w 294
 
5.5%
e 294
 
5.5%
s 294
 
5.5%
p 291
 
5.4%
Other values (6) 778
14.5%
Uppercase Letter
ValueCountFrequency (%)
I 295
18.7%
S 196
12.4%
E 196
12.4%
N 196
12.4%
T 98
 
6.2%
R 98
 
6.2%
A 98
 
6.2%
D 98
 
6.2%
O 98
 
6.2%
M 98
 
6.2%
Other values (5) 106
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 347
50.4%
3 118
 
17.2%
2 87
 
12.6%
4 36
 
5.2%
6 27
 
3.9%
8 25
 
3.6%
5 24
 
3.5%
7 9
 
1.3%
9 8
 
1.2%
0 7
 
1.0%
Other Punctuation
ValueCountFrequency (%)
/ 781
61.4%
. 392
30.8%
: 98
 
7.7%
Connector Punctuation
ValueCountFrequency (%)
_ 392
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6958
74.7%
Common 2351
 
25.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 686
 
9.9%
o 686
 
9.9%
a 686
 
9.9%
r 588
 
8.5%
i 490
 
7.0%
I 295
 
4.2%
k 294
 
4.2%
w 294
 
4.2%
e 294
 
4.2%
s 294
 
4.2%
Other values (21) 2351
33.8%
Common
ValueCountFrequency (%)
/ 781
33.2%
_ 392
16.7%
. 392
16.7%
1 347
14.8%
3 118
 
5.0%
: 98
 
4.2%
2 87
 
3.7%
4 36
 
1.5%
6 27
 
1.1%
8 25
 
1.1%
Other values (4) 48
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 781
 
8.4%
t 686
 
7.4%
o 686
 
7.4%
a 686
 
7.4%
r 588
 
6.3%
i 490
 
5.3%
_ 392
 
4.2%
. 392
 
4.2%
1 347
 
3.7%
I 295
 
3.2%
Other values (35) 3966
42.6%

측정소 전경
Categorical

IMBALANCE 

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
70 
http://www.airkorea.or.kr/airkorea/vrml/324135.swf
 
1
http://www.airkorea.or.kr/airkorea/vrml/336441.swf
 
1
http://www.airkorea.or.kr/airkorea/vrml/336451.swf
 
1
http://www.airkorea.or.kr/airkorea/vrml/339111.swf
 
1
Other values (26)
26 

Length

Max length50
Median length1
Mean length15.7
Min length1

Unique

Unique30 ?
Unique (%)30.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 70
70.0%
http://www.airkorea.or.kr/airkorea/vrml/324135.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/336441.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/336451.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/339111.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/339112.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/339121.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/339312.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/111121.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/111123.swf 1
 
1.0%
Other values (21) 21
 
21.0%

Length

2023-12-10T21:26:45.230230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 70
70.0%
http://www.airkorea.or.kr/airkorea/vrml/111181.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/111301.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/111291.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/111281.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/111274.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/111273.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/111262.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/111261.swf 1
 
1.0%
http://www.airkorea.or.kr/airkorea/vrml/111251.swf 1
 
1.0%
Other values (21) 21
 
21.0%

측정소 지도이미지
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:26:45.642117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length57
Mean length56.44
Min length1

Characters and Unicode

Total characters5644
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowhttp://www.airkorea.or.kr/airkorea/station_map/238145.gif
2nd rowhttp://www.airkorea.or.kr/airkorea/station_map/238146.gif
3rd rowhttp://www.airkorea.or.kr/airkorea/station_map/238151.gif
4th rowhttp://www.airkorea.or.kr/airkorea/station_map/238161.gif
5th rowhttp://www.airkorea.or.kr/airkorea/station_map/238181.gif
ValueCountFrequency (%)
http://www.airkorea.or.kr/airkorea/station_map/238145.gif 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_map/131129.gif 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_map/111231.gif 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_map/111221.gif 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_map/111213.gif 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_map/111212.gif 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_map/111202.gif 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_map/111201.gif 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_map/111191.gif 1
 
1.0%
http://www.airkorea.or.kr/airkorea/station_map/111181.gif 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T21:26:46.279128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 594
 
10.5%
r 594
 
10.5%
/ 495
 
8.8%
. 396
 
7.0%
i 396
 
7.0%
o 396
 
7.0%
t 396
 
7.0%
w 297
 
5.3%
k 297
 
5.3%
1 257
 
4.6%
Other values (19) 1526
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3960
70.2%
Other Punctuation 990
 
17.5%
Decimal Number 595
 
10.5%
Connector Punctuation 99
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 594
15.0%
r 594
15.0%
i 396
10.0%
o 396
10.0%
t 396
10.0%
w 297
7.5%
k 297
7.5%
p 198
 
5.0%
e 198
 
5.0%
h 99
 
2.5%
Other values (5) 495
12.5%
Decimal Number
ValueCountFrequency (%)
1 257
43.2%
3 119
20.0%
2 86
 
14.5%
4 33
 
5.5%
6 28
 
4.7%
8 25
 
4.2%
5 23
 
3.9%
7 10
 
1.7%
9 8
 
1.3%
0 6
 
1.0%
Other Punctuation
ValueCountFrequency (%)
/ 495
50.0%
. 396
40.0%
: 99
 
10.0%
Connector Punctuation
ValueCountFrequency (%)
_ 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3960
70.2%
Common 1684
29.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 594
15.0%
r 594
15.0%
i 396
10.0%
o 396
10.0%
t 396
10.0%
w 297
7.5%
k 297
7.5%
p 198
 
5.0%
e 198
 
5.0%
h 99
 
2.5%
Other values (5) 495
12.5%
Common
ValueCountFrequency (%)
/ 495
29.4%
. 396
23.5%
1 257
15.3%
3 119
 
7.1%
_ 99
 
5.9%
: 99
 
5.9%
2 86
 
5.1%
4 33
 
2.0%
6 28
 
1.7%
8 25
 
1.5%
Other values (4) 47
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5644
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 594
 
10.5%
r 594
 
10.5%
/ 495
 
8.8%
. 396
 
7.0%
i 396
 
7.0%
o 396
 
7.0%
t 396
 
7.0%
w 297
 
5.3%
k 297
 
5.3%
1 257
 
4.6%
Other values (19) 1526
27.0%

측정망
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
도시대기
76 
도로변대기
19 
교외대기
 
4
국가배경농도
 
1

Length

Max length6
Median length4
Mean length4.21
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row도로변대기
2nd row도시대기
3rd row도시대기
4th row도시대기
5th row도시대기

Common Values

ValueCountFrequency (%)
도시대기 76
76.0%
도로변대기 19
 
19.0%
교외대기 4
 
4.0%
국가배경농도 1
 
1.0%

Length

2023-12-10T21:26:46.545014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:26:46.709496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도시대기 76
76.0%
도로변대기 19
 
19.0%
교외대기 4
 
4.0%
국가배경농도 1
 
1.0%

측정항목
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
SO2, CO, O3, NO2, PM10, PM2.5
96 
SO2, CO, O3, NO2, PM10
 
2
SO2, CO, O3, NO2
 
1
SO2, CO, NO2, PM10, PM2.5
 
1

Length

Max length29
Median length29
Mean length28.69
Min length16

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st rowSO2, CO, O3, NO2, PM10, PM2.5
2nd rowSO2, CO, O3, NO2, PM10, PM2.5
3rd rowSO2, CO, O3, NO2, PM10, PM2.5
4th rowSO2, CO, O3, NO2, PM10, PM2.5
5th rowSO2, CO, O3, NO2, PM10, PM2.5

Common Values

ValueCountFrequency (%)
SO2, CO, O3, NO2, PM10, PM2.5 96
96.0%
SO2, CO, O3, NO2, PM10 2
 
2.0%
SO2, CO, O3, NO2 1
 
1.0%
SO2, CO, NO2, PM10, PM2.5 1
 
1.0%

Length

2023-12-10T21:26:46.935757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:26:47.110040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
so2 100
16.8%
co 100
16.8%
no2 100
16.8%
o3 99
16.6%
pm10 99
16.6%
pm2.5 97
16.3%

위도(Latitude)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.255795
Minimum33.246244
Maximum37.657415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:26:47.335161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.246244
5-th percentile34.739738
Q135.138529
median37.010363
Q337.535347
95-th percentile37.606857
Maximum37.657415
Range4.411171
Interquartile range (IQR)2.396818

Descriptive statistics

Standard deviation1.3224912
Coefficient of variation (CV)0.036476686
Kurtosis-1.3372959
Mean36.255795
Median Absolute Deviation (MAD)0.645483
Skewness-0.32785956
Sum3625.5795
Variance1.7489831
MonotonicityNot monotonic
2023-12-10T21:26:47.556196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.234141 1
 
1.0%
37.603593 1
 
1.0%
37.520222 1
 
1.0%
37.525007 1
 
1.0%
37.498498 1
 
1.0%
37.562822 1
 
1.0%
37.544656 1
 
1.0%
37.554936 1
 
1.0%
37.555611 1
 
1.0%
37.593749 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
33.246244 1
1.0%
33.292471 1
1.0%
33.48863 1
1.0%
33.500116 1
1.0%
34.71005 1
1.0%
34.741301 1
1.0%
34.7539 1
1.0%
34.754549 1
1.0%
34.766301 1
1.0%
34.766809 1
1.0%
ValueCountFrequency (%)
37.657415 1
1.0%
37.654278 1
1.0%
37.64793 1
1.0%
37.617315 1
1.0%
37.610471 1
1.0%
37.606667 1
1.0%
37.603593 1
1.0%
37.593749 1
1.0%
37.584953 1
1.0%
37.580167 1
1.0%

경도(Longitude)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.35728
Minimum126.16217
Maximum129.35502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:26:47.759838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16217
5-th percentile126.53076
Q1126.93325
median127.0429
Q3127.66649
95-th percentile129.0437
Maximum129.35502
Range3.192857
Interquartile range (IQR)0.733234

Descriptive statistics

Standard deviation0.74620732
Coefficient of variation (CV)0.005859165
Kurtosis0.90147889
Mean127.35728
Median Absolute Deviation (MAD)0.141731
Skewness1.3594237
Sum12735.728
Variance0.55682537
MonotonicityNot monotonic
2023-12-10T21:26:48.001050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.664624 1
 
1.0%
127.026007 1
 
1.0%
126.904967 1
 
1.0%
126.89737 1
 
1.0%
126.889692 1
 
1.0%
126.826072 1
 
1.0%
126.835094 1
 
1.0%
126.937619 1
 
1.0%
126.905458 1
 
1.0%
126.949535 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
126.162165 1
1.0%
126.391767 1
1.0%
126.43457 1
1.0%
126.439193 1
1.0%
126.500055 1
1.0%
126.532371 1
1.0%
126.56506 1
1.0%
126.798833 1
1.0%
126.8072 1
1.0%
126.826072 1
1.0%
ValueCountFrequency (%)
129.355022 1
1.0%
129.336917 1
1.0%
129.305696 1
1.0%
129.172083 1
1.0%
129.113942 1
1.0%
129.04 1
1.0%
128.912222 1
1.0%
128.883333 1
1.0%
128.807221 1
1.0%
128.69825 1
1.0%

생성날짜
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20191217
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20191217
2nd row20191217
3rd row20191217
4th row20191217
5th row20191217

Common Values

ValueCountFrequency (%)
20191217 100
100.0%

Length

2023-12-10T21:26:48.212167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:26:48.346724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20191217 100
100.0%

Interactions

2023-12-10T21:26:39.606347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:26:38.682311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:26:39.180042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:26:39.768309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:26:38.878037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:26:39.338013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:26:39.924390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:26:39.018368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:26:39.463284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:26:48.451479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정소명측정소 주소설치년도관리기관명측정소 이미지측정소 전경측정소 지도이미지측정망측정항목위도(Latitude)경도(Longitude)
측정소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
측정소 주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설치년도1.0001.0001.0000.4131.0000.0001.0000.8840.0000.2960.252
관리기관명1.0001.0000.4131.0001.0000.0001.0000.8260.7560.9690.869
측정소 이미지1.0001.0001.0001.0001.0001.0001.0000.8981.0001.0001.000
측정소 전경1.0001.0000.0000.0001.0001.0001.0000.7220.0000.0000.000
측정소 지도이미지1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
측정망1.0001.0000.8840.8260.8980.7221.0001.0000.0000.4540.640
측정항목1.0001.0000.0000.7561.0000.0001.0000.0001.0000.3470.146
위도(Latitude)1.0001.0000.2960.9691.0000.0001.0000.4540.3471.0000.824
경도(Longitude)1.0001.0000.2520.8691.0000.0001.0000.6400.1460.8241.000
2023-12-10T21:26:48.660859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명측정항목측정소 전경측정망
관리기관명1.0000.5520.0000.645
측정항목0.5521.0000.0000.000
측정소 전경0.0000.0001.0000.392
측정망0.6450.0000.3921.000
2023-12-10T21:26:48.828876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도위도(Latitude)경도(Longitude)관리기관명측정소 전경측정망측정항목
설치년도1.000-0.5410.3430.3770.0000.6840.000
위도(Latitude)-0.5411.000-0.1780.8920.0000.3040.226
경도(Longitude)0.343-0.1781.0000.6090.0000.4260.079
관리기관명0.3770.8920.6091.0000.0000.6450.552
측정소 전경0.0000.0000.0000.0001.0000.3920.000
측정망0.6840.3040.4260.6450.3921.0000.000
측정항목0.0000.2260.0790.5520.0000.0001.000

Missing values

2023-12-10T21:26:40.193930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:26:40.968184image/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

측정소명측정소 주소설치년도관리기관명측정소 이미지측정소 전경측정소 지도이미지측정망측정항목위도(Latitude)경도(Longitude)생성날짜
0반송로경남 창원시 의창구 원이대로 450(시설관리공단 실내수영장 앞)2019경상남도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238145/INSIDE_OTHER_1.png0http://www.airkorea.or.kr/airkorea/station_map/238145.gif도로변대기SO2, CO, O3, NO2, PM10, PM2.535.234141128.66462420191217
1사파동경남 창원시 성산구 창이대로 706번길 16-23(사파민원센터)2009경상남도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238146/INSIDE_OTHER_1.jpg0http://www.airkorea.or.kr/airkorea/station_map/238146.gif도시대기SO2, CO, O3, NO2, PM10, PM2.535.221729128.6982520191217
2경화동경남 창원시 진해구 경화로16번길 31(병암동주민센터)1994경상남도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238151/INSIDE_OTHER_1.jpg0http://www.airkorea.or.kr/airkorea/station_map/238151.gif도시대기SO2, CO, O3, NO2, PM10, PM2.535.154972128.68957820191217
3하동읍경남 하동군 하동읍 군청로 23(하동군청)2019경상남도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238161/INSIDE_OTHER_1.png0http://www.airkorea.or.kr/airkorea/station_map/238161.gif도시대기SO2, CO, O3, NO2, PM10, PM2.535.066944127.75138920191217
4동상동경남 김해시 호계로 517번길 8(동상동 주민센터)1995경상남도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238181/INSIDE_OTHER_1.jpg0http://www.airkorea.or.kr/airkorea/station_map/238181.gif도시대기SO2, CO, O3, NO2, PM10, PM2.535.236667128.88333320191217
5삼방동경남 김해시 활천로 303(신어초등학교)2003경상남도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238182/INSIDE_OTHER_1.jpg0http://www.airkorea.or.kr/airkorea/station_map/238182.gif도시대기SO2, CO, O3, NO2, PM10, PM2.535.243889128.91222220191217
6장유동경남 김해시 장유동 능동로 149(장유건강지원센터)2013경상남도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238183/INSIDE_OTHER_1.jpg0http://www.airkorea.or.kr/airkorea/station_map/238183.gif도시대기SO2, CO, O3, NO2, PM10, PM2.535.202364128.80722120191217
7저구리경남 거제시 남부면 저구리산 116번지1999한국환경공단 대구경북지역본부http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238191/INSIDE_OTHER_1.jpg0http://www.airkorea.or.kr/airkorea/station_map/238191.gif교외대기SO2, CO, O3, NO2, PM10, PM2.534.71005128.5874520191217
8아주동경남 거제시 아주로 3길 7(아주동주민센터)2011경상남도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238201/INSIDE_OTHER_1.jpg0http://www.airkorea.or.kr/airkorea/station_map/238201.gif도시대기SO2, CO, O3, NO2, PM10, PM2.534.866128.69218220191217
9사천읍경남 사천시 사천읍 읍내로 52(사천읍사무소)2013경상남도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/238211/INSIDE_OTHER_1.jpg0http://www.airkorea.or.kr/airkorea/station_map/238211.gif도시대기SO2, CO, O3, NO2, PM10, PM2.535.082551128.09123620191217
측정소명측정소 주소설치년도관리기관명측정소 이미지측정소 전경측정소 지도이미지측정망측정항목위도(Latitude)경도(Longitude)생성날짜
90신풍동경기 수원시 팔달구 신풍로 23번길 68선경도서관1986경기도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/131111/INSIDE_OTHER_1.bmp0http://www.airkorea.or.kr/airkorea/station_map/131111.gif도시대기SO2, CO, O3, NO2, PM10, PM2.537.283798127.01047220191217
91인계동경기 수원시 팔달구 효원로 241수원시청1987경기도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/131112/INSIDE_OTHER_1.bmp0http://www.airkorea.or.kr/airkorea/station_map/131112.gif도시대기SO2, CO, O3, NO2, PM10, PM2.537.26334127.0286320191217
92광교동경기 수원시 영통구 법조로 129이의중학교1992경기도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/131113/INSIDE_OTHER_1.bmp0http://www.airkorea.or.kr/airkorea/station_map/131113.gif도시대기SO2, CO, O3, NO2, PM10, PM2.537.291272127.07081820191217
93영통동경기 수원시 영통구 영통로 217번길 12영통2동 행정복지센터2001경기도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/131114/INSIDE_OTHER_1.bmp0http://www.airkorea.or.kr/airkorea/station_map/131114.gif도시대기SO2, CO, O3, NO2, PM10, PM2.537.246927127.05631520191217
94천천동경기 수원시 장안구 서부로 2066성균관대학교 제2공학관2003경기도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/131115/INSIDE_OTHER_1.bmp0http://www.airkorea.or.kr/airkorea/station_map/131115.gif도시대기SO2, CO, O3, NO2, PM10, PM2.537.292756126.97530320191217
95경수대로(동수원)경기 수원시 팔달구 인계동 1047동수원사거리2004경기도보건환경연구원00http://www.airkorea.or.kr/airkorea/station_map/131116.gif도로변대기SO2, CO, O3, NO2, PM10, PM2.537.276484127.03067620191217
96고색동경기 수원시 권선구 서부로 1600수원시도로교통관리사업소2006경기도보건환경연구원00http://www.airkorea.or.kr/airkorea/station_map/131117.gif도시대기SO2, CO, O3, NO2, PM10, PM2.537.252226126.97630420191217
97대왕판교로(백현동)경기 성남시 분당구 판교동 652-1백현1교차로2011경기도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/131120/INSIDE_OTHER_1.GIF0http://www.airkorea.or.kr/airkorea/station_map/131120.gif도로변대기SO2, CO, NO2, PM10, PM2.537.382576127.10274420191217
98단대동경기 성남시 수정구 희망로 506번길 21단대동행정복지센터1993경기도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/131121/INSIDE_OTHER_1.bmp0http://www.airkorea.or.kr/airkorea/station_map/131121.gif도시대기SO2, CO, O3, NO2, PM10, PM2.537.449479127.15551220191217
99정자동경기 성남시 분당구 돌마로 242정자3동행정복지센터1998경기도보건환경연구원http://www.airkorea.or.kr/airkorea/station_photo/NAMIS/station_images/131123/INSIDE_OTHER_1.bmp0http://www.airkorea.or.kr/airkorea/station_map/131123.gif도시대기SO2, CO, O3, NO2, PM10, PM2.537.361416127.1115320191217