Overview

Dataset statistics

Number of variables11
Number of observations310
Missing cells201
Missing cells (%)5.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.3 KiB
Average record size in memory93.4 B

Variable types

Categorical4
Text3
Numeric4

Alerts

집계년도 has constant value ""Constant
낚시터위치우편번호 is highly overall correlated with WGS84위도 and 2 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 낚시터위치우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 낚시터위치우편번호 and 3 other fieldsHigh correlation
등록구분명 is highly overall correlated with 낚시터위치우편번호 and 1 other fieldsHigh correlation
낚시터위치우편번호 has 20 (6.5%) missing valuesMissing
낚시터위치도로명주소 has 149 (48.1%) missing valuesMissing
WGS84위도 has 16 (5.2%) missing valuesMissing
WGS84경도 has 16 (5.2%) missing valuesMissing

Reproduction

Analysis started2023-12-10 21:20:35.074400
Analysis finished2023-12-10 21:20:37.348692
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2022
310 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 310
100.0%

Length

2023-12-11T06:20:37.421040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:20:37.515548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 310
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
안성시
35 
화성시
28 
포천시
24 
용인시
23 
시흥시
23 
Other values (23)
177 

Length

Max length4
Median length3
Mean length3.0645161
Min length3

Unique

Unique3 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
안성시 35
 
11.3%
화성시 28
 
9.0%
포천시 24
 
7.7%
용인시 23
 
7.4%
시흥시 23
 
7.4%
남양주시 17
 
5.5%
안산시 17
 
5.5%
양주시 17
 
5.5%
파주시 15
 
4.8%
김포시 14
 
4.5%
Other values (18) 97
31.3%

Length

2023-12-11T06:20:37.606091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안성시 35
 
11.3%
화성시 28
 
9.0%
포천시 24
 
7.7%
용인시 23
 
7.4%
시흥시 23
 
7.4%
남양주시 17
 
5.5%
안산시 17
 
5.5%
양주시 17
 
5.5%
파주시 15
 
4.8%
김포시 14
 
4.5%
Other values (18) 97
31.3%

등록구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
등록
158 
허가
152 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row등록
2nd row허가
3rd row허가
4th row등록
5th row등록

Common Values

ValueCountFrequency (%)
등록 158
51.0%
허가 152
49.0%

Length

2023-12-11T06:20:37.727241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:20:37.811817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록 158
51.0%
허가 152
49.0%

낚시터명
Text

Distinct306
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T06:20:38.074443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length5
Mean length5.4258065
Min length2

Characters and Unicode

Total characters1682
Distinct characters255
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

Unique302 ?
Unique (%)97.4%

Sample

1st row산수낚시터
2nd row도장골낚시터
3rd row상천낚시터
4th row폭포낚시터
5th row가평낚시터
ValueCountFrequency (%)
낚시터 3
 
0.9%
물어실내바다 2
 
0.6%
그린낚시터 2
 
0.6%
실내바다 2
 
0.6%
남양주 2
 
0.6%
락 2
 
0.6%
놀러와실내낚시카페 2
 
0.6%
한탄강 2
 
0.6%
삼인 1
 
0.3%
통삼 1
 
0.3%
Other values (305) 305
94.1%
2023-12-11T06:20:38.786754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
낚 254
 
15.1%
시 254
 
15.1%
터 239
 
14.2%
바 30
 
1.8%
다 30
 
1.8%
실 29
 
1.7%
내 29
 
1.7%
원 22
 
1.3%
산 17
 
1.0%
리 17
 
1.0%
Other values (245) 761
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1641
97.6%
Space Separator 14
 
0.8%
Decimal Number 11
 
0.7%
Lowercase Letter 4
 
0.2%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%
Other Punctuation 3
 
0.2%
Uppercase Letter 2
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
낚 254
 
15.5%
시 254
 
15.5%
터 239
 
14.6%
바 30
 
1.8%
다 30
 
1.8%
실 29
 
1.8%
내 29
 
1.8%
원 22
 
1.3%
산 17
 
1.0%
리 17
 
1.0%
Other values (232) 720
43.9%
Lowercase Letter
ValueCountFrequency (%)
n 1
25.0%
g 1
25.0%
i 1
25.0%
k 1
25.0%
Decimal Number
ValueCountFrequency (%)
1 4
36.4%
3 4
36.4%
2 3
27.3%
Space Separator
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
K 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1641
97.6%
Common 35
 
2.1%
Latin 6
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
낚 254
 
15.5%
시 254
 
15.5%
터 239
 
14.6%
바 30
 
1.8%
다 30
 
1.8%
실 29
 
1.8%
내 29
 
1.8%
원 22
 
1.3%
산 17
 
1.0%
리 17
 
1.0%
Other values (232) 720
43.9%
Common
ValueCountFrequency (%)
14
40.0%
1 4
 
11.4%
3 4
 
11.4%
( 3
 
8.6%
) 3
 
8.6%
. 3
 
8.6%
2 3
 
8.6%
~ 1
 
2.9%
Latin
ValueCountFrequency (%)
K 2
33.3%
n 1
16.7%
g 1
16.7%
i 1
16.7%
k 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1641
97.6%
ASCII 41
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
낚 254
 
15.5%
시 254
 
15.5%
터 239
 
14.6%
바 30
 
1.8%
다 30
 
1.8%
실 29
 
1.8%
내 29
 
1.8%
원 22
 
1.3%
산 17
 
1.0%
리 17
 
1.0%
Other values (232) 720
43.9%
ASCII
ValueCountFrequency (%)
14
34.1%
1 4
 
9.8%
3 4
 
9.8%
( 3
 
7.3%
) 3
 
7.3%
. 3
 
7.3%
2 3
 
7.3%
K 2
 
4.9%
n 1
 
2.4%
g 1
 
2.4%
Other values (3) 3
 
7.3%

낚시터면적(ha)
Real number (ℝ)

Distinct220
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5206419
Minimum0.002
Maximum274.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T06:20:39.003658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.002
5-th percentile0.006
Q10.14175
median0.5255
Q32.4875
95-th percentile31.87
Maximum274.7
Range274.698
Interquartile range (IQR)2.34575

Descriptive statistics

Standard deviation19.996424
Coefficient of variation (CV)3.6221193
Kurtosis113.51718
Mean5.5206419
Median Absolute Deviation (MAD)0.51
Skewness9.4395077
Sum1711.399
Variance399.85696
MonotonicityNot monotonic
2023-12-11T06:20:39.152132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3 6
 
1.9%
0.005 6
 
1.9%
0.29 5
 
1.6%
0.2 5
 
1.6%
0.004 4
 
1.3%
2.0 4
 
1.3%
0.006 4
 
1.3%
0.5 4
 
1.3%
0.6 4
 
1.3%
0.7 3
 
1.0%
Other values (210) 265
85.5%
ValueCountFrequency (%)
0.002 2
 
0.6%
0.003 1
 
0.3%
0.004 4
1.3%
0.005 6
1.9%
0.006 4
1.3%
0.007 1
 
0.3%
0.008 2
 
0.6%
0.009 3
1.0%
0.01 3
1.0%
0.011 2
 
0.6%
ValueCountFrequency (%)
274.7 1
0.3%
138.4 1
0.3%
93.82 1
0.3%
52.66 1
0.3%
48.37 1
0.3%
48.1 1
0.3%
45.2 1
0.3%
42.22 1
0.3%
40.8 1
0.3%
40.0 1
0.3%

이용료(원)
Categorical

Distinct38
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
30,000
76 
20,000
47 
10,000
39 
25,000
32 
15,000
23 
Other values (33)
93 

Length

Max length53
Median length6
Mean length6.6032258
Min length1

Unique

Unique21 ?
Unique (%)6.8%

Sample

1st row30,000
2nd row30,000
3rd row30,000
4th row30,000
5th row30,000

Common Values

ValueCountFrequency (%)
30,000 76
24.5%
20,000 47
15.2%
10,000 39
12.6%
25,000 32
10.3%
15,000 23
 
7.4%
40,000 20
 
6.5%
응답거부 11
 
3.5%
70,000 11
 
3.5%
35,000 6
 
1.9%
50,000 5
 
1.6%
Other values (28) 40
12.9%

Length

2023-12-11T06:20:39.313534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
30,000 76
22.4%
20,000 48
14.2%
10,000 39
11.5%
25,000 32
9.4%
15,000 23
 
6.8%
40,000 20
 
5.9%
응답거부 11
 
3.2%
70,000 11
 
3.2%
35,000 6
 
1.8%
240,000 5
 
1.5%
Other values (48) 68
20.1%

낚시터위치우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct239
Distinct (%)82.4%
Missing20
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean14339.024
Minimum10002
Maximum18609
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T06:20:39.467090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10002
5-th percentile10269.95
Q111429.5
median14781
Q317410
95-th percentile18375.05
Maximum18609
Range8607
Interquartile range (IQR)5980.5

Descriptive statistics

Standard deviation2929.9006
Coefficient of variation (CV)0.20433055
Kurtosis-1.6263279
Mean14339.024
Median Absolute Deviation (MAD)2739
Skewness0.026030091
Sum4158317
Variance8584317.7
MonotonicityNot monotonic
2023-12-11T06:20:39.597636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17504 5
 
1.6%
18553 3
 
1.0%
15643 3
 
1.0%
14987 3
 
1.0%
11165 3
 
1.0%
10806 3
 
1.0%
12241 2
 
0.6%
14635 2
 
0.6%
10043 2
 
0.6%
11166 2
 
0.6%
Other values (229) 262
84.5%
(Missing) 20
 
6.5%
ValueCountFrequency (%)
10002 1
0.3%
10007 1
0.3%
10008 1
0.3%
10009 1
0.3%
10024 1
0.3%
10029 1
0.3%
10043 2
0.6%
10047 1
0.3%
10069 1
0.3%
10119 1
0.3%
ValueCountFrequency (%)
18609 1
 
0.3%
18589 1
 
0.3%
18586 1
 
0.3%
18585 1
 
0.3%
18576 1
 
0.3%
18574 1
 
0.3%
18557 2
0.6%
18553 3
1.0%
18536 1
 
0.3%
18526 1
 
0.3%

낚시터위치도로명주소
Text

MISSING 

Distinct160
Distinct (%)99.4%
Missing149
Missing (%)48.1%
Memory size2.6 KiB
2023-12-11T06:20:39.886559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length20.987578
Min length14

Characters and Unicode

Total characters3379
Distinct characters192
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)98.8%

Sample

1st row경기도 가평군 조종면 대보간선로399번길 63-9
2nd row경기도 가평군 조종면 명지산로 51-183
3rd row경기도 가평군 가평읍 가화로 440-95
4th row경기도 가평군 가평읍 분자골로 22
5th row경기도 가평군 설악면 자잠로23번길 67-55
ValueCountFrequency (%)
경기도 161
 
20.8%
포천시 14
 
1.8%
시흥시 12
 
1.6%
남양주시 12
 
1.6%
용인시 11
 
1.4%
파주시 10
 
1.3%
처인구 9
 
1.2%
고양시 9
 
1.2%
화성시 8
 
1.0%
양주시 8
 
1.0%
Other values (382) 519
67.1%
2023-12-11T06:20:40.347582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
612
 
18.1%
경 169
 
5.0%
기 168
 
5.0%
도 165
 
4.9%
시 164
 
4.9%
1 123
 
3.6%
로 117
 
3.5%
2 114
 
3.4%
길 101
 
3.0%
5 73
 
2.2%
Other values (182) 1573
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2033
60.2%
Decimal Number 674
 
19.9%
Space Separator 612
 
18.1%
Dash Punctuation 60
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 169
 
8.3%
기 168
 
8.3%
도 165
 
8.1%
시 164
 
8.1%
로 117
 
5.8%
길 101
 
5.0%
면 61
 
3.0%
번 55
 
2.7%
양 53
 
2.6%
주 40
 
2.0%
Other values (170) 940
46.2%
Decimal Number
ValueCountFrequency (%)
1 123
18.2%
2 114
16.9%
5 73
10.8%
4 64
9.5%
3 58
8.6%
6 54
8.0%
7 52
7.7%
8 50
7.4%
0 44
 
6.5%
9 42
 
6.2%
Space Separator
ValueCountFrequency (%)
612
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2033
60.2%
Common 1346
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 169
 
8.3%
기 168
 
8.3%
도 165
 
8.1%
시 164
 
8.1%
로 117
 
5.8%
길 101
 
5.0%
면 61
 
3.0%
번 55
 
2.7%
양 53
 
2.6%
주 40
 
2.0%
Other values (170) 940
46.2%
Common
ValueCountFrequency (%)
612
45.5%
1 123
 
9.1%
2 114
 
8.5%
5 73
 
5.4%
4 64
 
4.8%
- 60
 
4.5%
3 58
 
4.3%
6 54
 
4.0%
7 52
 
3.9%
8 50
 
3.7%
Other values (2) 86
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2033
60.2%
ASCII 1346
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
612
45.5%
1 123
 
9.1%
2 114
 
8.5%
5 73
 
5.4%
4 64
 
4.8%
- 60
 
4.5%
3 58
 
4.3%
6 54
 
4.0%
7 52
 
3.9%
8 50
 
3.7%
Other values (2) 86
 
6.4%
Hangul
ValueCountFrequency (%)
경 169
 
8.3%
기 168
 
8.3%
도 165
 
8.1%
시 164
 
8.1%
로 117
 
5.8%
길 101
 
5.0%
면 61
 
3.0%
번 55
 
2.7%
양 53
 
2.6%
주 40
 
2.0%
Other values (170) 940
46.2%

낚시터위치지번주소
Text

Distinct309
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T06:20:40.634776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length20.390323
Min length14

Characters and Unicode

Total characters6321
Distinct characters215
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique308 ?
Unique (%)99.4%

Sample

1st row경기도 가평군 북면 도대리 531
2nd row경기도 가평군 조종면 대보리 243-4번지
3rd row경기도 가평군 청평면 상천리 1747
4th row경기도 가평군 조종면 운악리 211-2번지
5th row경기도 가평군 가평읍 마장리 983-14번지
ValueCountFrequency (%)
경기도 310
 
20.3%
안성시 35
 
2.3%
화성시 28
 
1.8%
시흥시 28
 
1.8%
포천시 24
 
1.6%
용인시 23
 
1.5%
처인구 19
 
1.2%
안산시 17
 
1.1%
남양주시 17
 
1.1%
양주시 17
 
1.1%
Other values (686) 1012
66.1%
2023-12-11T06:20:41.071554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1220
19.3%
도 321
 
5.1%
기 318
 
5.0%
시 315
 
5.0%
경 311
 
4.9%
1 214
 
3.4%
리 212
 
3.4%
- 166
 
2.6%
3 149
 
2.4%
면 148
 
2.3%
Other values (205) 2947
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3808
60.2%
Space Separator 1220
 
19.3%
Decimal Number 1113
 
17.6%
Dash Punctuation 166
 
2.6%
Open Punctuation 6
 
0.1%
Close Punctuation 6
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 321
 
8.4%
기 318
 
8.4%
시 315
 
8.3%
경 311
 
8.2%
리 212
 
5.6%
면 148
 
3.9%
동 121
 
3.2%
양 85
 
2.2%
성 82
 
2.2%
지 69
 
1.8%
Other values (190) 1826
48.0%
Decimal Number
ValueCountFrequency (%)
1 214
19.2%
3 149
13.4%
2 144
12.9%
5 113
10.2%
4 102
9.2%
7 96
8.6%
6 83
 
7.5%
9 80
 
7.2%
0 67
 
6.0%
8 65
 
5.8%
Space Separator
ValueCountFrequency (%)
1220
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 166
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3808
60.2%
Common 2513
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 321
 
8.4%
기 318
 
8.4%
시 315
 
8.3%
경 311
 
8.2%
리 212
 
5.6%
면 148
 
3.9%
동 121
 
3.2%
양 85
 
2.2%
성 82
 
2.2%
지 69
 
1.8%
Other values (190) 1826
48.0%
Common
ValueCountFrequency (%)
1220
48.5%
1 214
 
8.5%
- 166
 
6.6%
3 149
 
5.9%
2 144
 
5.7%
5 113
 
4.5%
4 102
 
4.1%
7 96
 
3.8%
6 83
 
3.3%
9 80
 
3.2%
Other values (5) 146
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3808
60.2%
ASCII 2513
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1220
48.5%
1 214
 
8.5%
- 166
 
6.6%
3 149
 
5.9%
2 144
 
5.7%
5 113
 
4.5%
4 102
 
4.1%
7 96
 
3.8%
6 83
 
3.3%
9 80
 
3.2%
Other values (5) 146
 
5.8%
Hangul
ValueCountFrequency (%)
도 321
 
8.4%
기 318
 
8.4%
시 315
 
8.3%
경 311
 
8.2%
리 212
 
5.6%
면 148
 
3.9%
동 121
 
3.2%
양 85
 
2.2%
성 82
 
2.2%
지 69
 
1.8%
Other values (190) 1826
48.0%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct293
Distinct (%)99.7%
Missing16
Missing (%)5.2%
Infinite0
Infinite (%)0.0%
Mean37.430201
Minimum36.954235
Maximum38.17435
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T06:20:41.242561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.954235
5-th percentile37.037228
Q137.166712
median37.363588
Q337.705126
95-th percentile37.931972
Maximum38.17435
Range1.2201155
Interquartile range (IQR)0.53841488

Descriptive statistics

Standard deviation0.30509178
Coefficient of variation (CV)0.0081509522
Kurtosis-1.1097104
Mean37.430201
Median Absolute Deviation (MAD)0.25511658
Skewness0.38238984
Sum11004.479
Variance0.093080992
MonotonicityNot monotonic
2023-12-11T06:20:41.433681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6451473608 2
 
0.6%
37.8011963352 1
 
0.3%
37.2311637015 1
 
0.3%
37.1341069489 1
 
0.3%
37.1370168643 1
 
0.3%
37.1653309874 1
 
0.3%
37.2192334494 1
 
0.3%
37.2903053177 1
 
0.3%
37.2952656278 1
 
0.3%
37.2256362996 1
 
0.3%
Other values (283) 283
91.3%
(Missing) 16
 
5.2%
ValueCountFrequency (%)
36.9542347785 1
0.3%
36.9702763993 1
0.3%
36.9832788299 1
0.3%
36.9907322207 1
0.3%
36.9932506996 1
0.3%
36.9966734541 1
0.3%
37.0081925419 1
0.3%
37.0092708215 1
0.3%
37.0163323415 1
0.3%
37.0212530226 1
0.3%
ValueCountFrequency (%)
38.1743502738 1
0.3%
38.1366670327 1
0.3%
38.0991193842 1
0.3%
38.0429557784 1
0.3%
38.0289521108 1
0.3%
38.0191836479 1
0.3%
38.0151757876 1
0.3%
38.0127066048 1
0.3%
37.9875704115 1
0.3%
37.9737641471 1
0.3%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct293
Distinct (%)99.7%
Missing16
Missing (%)5.2%
Infinite0
Infinite (%)0.0%
Mean127.07594
Minimum126.54074
Maximum127.72681
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-11T06:20:41.568720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54074
5-th percentile126.58999
Q1126.86002
median127.09602
Q3127.2754
95-th percentile127.54516
Maximum127.72681
Range1.1860727
Interquartile range (IQR)0.41537856

Descriptive statistics

Standard deviation0.27920852
Coefficient of variation (CV)0.0021971785
Kurtosis-0.71436643
Mean127.07594
Median Absolute Deviation (MAD)0.21754064
Skewness0.06466313
Sum37360.325
Variance0.077957395
MonotonicityNot monotonic
2023-12-11T06:20:41.703462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.5806472144 2
 
0.6%
126.8676326093 1
 
0.3%
127.1357153565 1
 
0.3%
127.194898713 1
 
0.3%
127.2197810581 1
 
0.3%
127.2524417289 1
 
0.3%
127.1903068904 1
 
0.3%
127.1323537229 1
 
0.3%
127.0948885547 1
 
0.3%
127.3220280313 1
 
0.3%
Other values (283) 283
91.3%
(Missing) 16
 
5.2%
ValueCountFrequency (%)
126.540740279 1
0.3%
126.5530813615 1
0.3%
126.554493744 1
0.3%
126.5549404789 1
0.3%
126.5581979494 1
0.3%
126.5597150842 1
0.3%
126.5629596293 1
0.3%
126.5633133406 1
0.3%
126.5652756499 1
0.3%
126.5668028846 1
0.3%
ValueCountFrequency (%)
127.7268129754 1
0.3%
127.7103586034 1
0.3%
127.6867879432 1
0.3%
127.6736281981 1
0.3%
127.6579414466 1
0.3%
127.6511907591 1
0.3%
127.6065805607 1
0.3%
127.5999999546 1
0.3%
127.5938152892 1
0.3%
127.5793345931 1
0.3%

Interactions

2023-12-11T06:20:36.634001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:35.645220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:35.970437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:36.276649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:36.725466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:35.716837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:36.046893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:36.349534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:36.829901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:35.802074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:36.124097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:36.420456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:36.918769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:35.890690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:36.204591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:36.504062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:20:41.799700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명등록구분명낚시터면적(ha)이용료(원)낚시터위치우편번호WGS84위도WGS84경도
시군명1.0000.6870.0000.9080.9980.9210.885
등록구분명0.6871.0000.1790.6020.6940.5450.568
낚시터면적(ha)0.0000.1791.0000.0000.0000.1890.000
이용료(원)0.9080.6020.0001.0000.8480.6290.688
낚시터위치우편번호0.9980.6940.0000.8481.0000.8910.840
WGS84위도0.9210.5450.1890.6290.8911.0000.582
WGS84경도0.8850.5680.0000.6880.8400.5821.000
2023-12-11T06:20:41.912193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록구분명이용료(원)시군명
등록구분명1.0000.4550.532
이용료(원)0.4551.0000.426
시군명0.5320.4261.000
2023-12-11T06:20:41.997128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
낚시터면적(ha)낚시터위치우편번호WGS84위도WGS84경도시군명등록구분명이용료(원)
낚시터면적(ha)1.0000.218-0.2570.2810.0000.2180.000
낚시터위치우편번호0.2181.000-0.8960.1390.9530.5260.471
WGS84위도-0.257-0.8961.000-0.1230.6430.4140.259
WGS84경도0.2810.139-0.1231.0000.5610.4320.300
시군명0.0000.9530.6430.5611.0000.5320.426
등록구분명0.2180.5260.4140.4320.5321.0000.455
이용료(원)0.0000.4710.2590.3000.4260.4551.000

Missing values

2023-12-11T06:20:37.024352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:20:37.188722image/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.
2023-12-11T06:20:37.293980image/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

집계년도시군명등록구분명낚시터명낚시터면적(ha)이용료(원)낚시터위치우편번호낚시터위치도로명주소낚시터위치지번주소WGS84위도WGS84경도
02022가평군등록산수낚시터0.63430,00012401<NA>경기도 가평군 북면 도대리 53137.967688127.458747
12022가평군허가도장골낚시터0.2930,00012439경기도 가평군 조종면 대보간선로399번길 63-9경기도 가평군 조종면 대보리 243-4번지37.806304127.372824
22022가평군허가상천낚시터2.3930,00012449<NA>경기도 가평군 청평면 상천리 174737.768322127.474692
32022가평군등록폭포낚시터0.20130,00012432경기도 가평군 조종면 명지산로 51-183경기도 가평군 조종면 운악리 211-2번지37.884109127.359977
42022가평군등록가평낚시터0.30430,00012409경기도 가평군 가평읍 가화로 440-95경기도 가평군 가평읍 마장리 983-14번지37.855737127.509788
52022가평군등록산유낚시터0.14730,00012429경기도 가평군 가평읍 분자골로 22경기도 가평군 가평읍 산유리 367-2번지37.757331127.50982
62022가평군등록설악낚시터0.10830,00012466경기도 가평군 설악면 자잠로23번길 67-55경기도 가평군 설악면 선촌리 332-237.681844127.482523
72022가평군등록두밀리낚시터0.22520,00012425<NA>경기도 가평군 가평읍 태봉두밀로 305<NA><NA>
82022고양시등록123실내낚시터0.01응답거부10464경기도 고양시 덕양구 호국로 770경기도 고양시 덕양구 성사동 699-10번지37.655193126.835033
92022고양시등록뚜루실내낚시0.01응답거부10317경기도 고양시 일산동구 견달산로225번길 26-44경기도 고양시 일산동구 식사동 281-3번지37.689179126.818771
집계년도시군명등록구분명낚시터명낚시터면적(ha)이용료(원)낚시터위치우편번호낚시터위치도로명주소낚시터위치지번주소WGS84위도WGS84경도
3002022화성시등록성지골낚시터0.28415,00018553<NA>경기도 화성시 서신면 장외리 214-237.171969126.670236
3012022화성시허가청춘낚시터0.0770,00018557경기도 화성시 우정읍 입파길 17경기도 화성시 우정읍 국화리 산4번지37.102098126.54074
3022022화성시허가버들낚시터14.1525,00018574<NA>경기도 화성시 장안면 석포리 832-137.127645126.829415
3032022화성시허가송라낚시터10.7920,00018288<NA>경기도 화성시 매송면 송라리 7037.282072126.90743
3042022화성시허가기천낚시터42.2215,00018333경기도 화성시 봉담읍 건달산로 309-33경기도 화성시 봉담읍 상기리 65337.196373126.911812
3052022화성시허가대성낚시터10.9925,00018536<NA>경기도 화성시 팔탄면 율암리 267-137.175361126.867941
3062022화성시등록죠스실내낚시카페0.0089,00018398경기도 화성시 효행로 1051경기도 화성시 진안동 914-1 (메인프라자) 305호37.214633127.04197
3072022화성시등록서신레저바다낚시터2.14550,00018553<NA>경기도 화성시 서신면 송교리 42-237.162131126.680232
3082022화성시등록초당낚시터0.27815,00018333경기도 화성시 봉담읍 주석로 891-21경기도 화성시 봉담읍 상기리 60737.200375126.911725
3092022화성시등록화성대어낚시터0.38710,00018283경기도 화성시 비봉면 비봉로528번길 40경기도 화성시 비봉면 삼화리 15-137.260068126.853577